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Government debt maturity and debt dynamics in euro area countries
Accepted Manuscript
Government Debt Maturity and Debt Dynamics in Euro Area Countries Juan Equiza-Goni ˜ PII: DOI: Reference:
S0164-0704(16)00015-X 10.1016/j.jmacro.2016.01.005 JMACRO 2855
To appear in:
Journal of Macroeconomics
Received date: Revised date: Accepted date:
21 August 2015 26 January 2016 30 January 2016
Please cite this article as: Juan Equiza-Goni, ˜ Government Debt Maturity and Debt Dynamics in Euro Area Countries, Journal of Macroeconomics (2016), doi: 10.1016/j.jmacro.2016.01.005
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Highlights • A new database of EA sovereign debt stocks, at different maturities, in 1991-2013
• Debt dynamics decomposed into factors based on the theoretical budget constraint
• Real returns on debt is the biggest factor pushing-up debt-to-GDP ratios in the EA
• Long-term bond-holders experienced large capital gains, especially in run-up to Euro
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• Higher inflation in EA countries would lower their fiscal burden more than in the US
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Government Debt Maturity and Debt Dynamics in Euro Area Countries
February 13, 2016 Abstract
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Juan Equiza-Goñi∗
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This paper studies the impact of debt maturity on the dynamics of sovereign debt of Euro Area (EA) countries. Due to lack of data, this key issue had not been studied before. Thus, my first contribution is to build a new comprehensive database of sovereign debt stocks and yields, at all different maturities, for six EA countries in 1991-2013: Belgium, Finland, France, Germany, Italy and Spain. In general, since 1991, interests rates in the EA have fallen while Treasuries in the region extended debt maturity; thus, an increasing number of long-term bondholders experienced large capital gains. I show with counterfactual simulations the effect of a different maturity structure on the evolution of debt. My analysis suggests that extending debt maturity in 2013-2015 would result in lower debt ratios by 2022. I also estimate the impact on EA debt-to-GDP ratios induced by changes in current and future inflation. My estimates indicate that higher (lower) inflation in EA countries would lower (raise) their fiscal burden much more than in the US. JEL codes: E31, E43, G12, H63 Keywords: debt dynamics; interest rate risk; debt maturity; inflation
Universidad de Navarra, Pamplona, 31080, Spain. Email: jequizag at unav.es. I am grateful to my PhD adviser Robert Kollmann at Université libre de Bruxelles (ULB) and to this institution for granting mini-Arc funding to my research project. I would also like to thank my discussants and participants at the Belgian Macroeconomics Workshop 2014, SAEe 2014, RES PhD conference 2015 and ENTER Jamboree 2015, as well as Philippe Weil, Raf Wouters and Rigas Oikonomou for comments and suggestions. ∗
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Introduction
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The financial crisis increased substantially the debt-to-GDP ratios of the Euro Area (EA) sovereigns, raising doubts about the sustainability of some countries’ debt and the survival of the currency union as a whole. Consequently, there is a renewed interest in understanding the drivers of debt-to-GDP changes. Theory suggests that the maturity structure of debt can play an important role in the evolution of these ratios through different channels. First, bond prices can absorb adverse fiscal shocks and facilitate tax smoothing (e.g. Lucas and Stokey (1983) or Buera and Nicolini (2004)). Second, debt with longer maturity can be eroded for a longer time by higher than expected inflation (e.g. Lustig et al. (2008) or Faraglia et al. (2013)).
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This paper studies empirically the role of debt maturity in the evolution of debt-to-GDP ratios in the Euro Area. In particular, my analysis generates a set of stylized facts on sovereign debt and yield dynamics for six EA countries: Belgium, Finland, France, Germany, Italy and Spain. My first contribution is to build a new database on outstanding debt securities and yields for these countries in 1991-2013. Then, following an accounting scheme based on the period-by-period government budget constraint, this paper studies past contributions to debt-to-GDP changes of nominal returns on debt with different maturities, inflation and other factors. I find that the high return on long-term debt has been the factor that contributed the most to changing (increasing) the debt ratios in the EA.
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Moreover, I use simulations to show the effect of counterfactual distributions of debt across maturities on debt-to-GDP dynamics. For example, I document that the long maturity of Spanish and Italian sovereign debt during the Euro crisis protected their public budgets from interest rate increases and lowered their debt ratios. I also simulate the trajectory of debt ratios for plausible projections of future yields and fiscal variables. This exercise suggests that EA countries would lower their future debt-to-GDP ratios by increasing debt maturity in 2013-2015. Finally, my paper provides estimates of the impact of higher inflation on the debt burden of EA countries. This effect would be moderate, but larger than in the US. Due to lack of data, no previous work has studied empirically the relation between debt maturity and debt-to-GDP dynamics in EA countries. Thus, my new database is an essential contribution of the paper. I constructed this database mostly on a security by security basis and it combines data from different sources: mainly, national Treasuries and Central Banks. As a result, it provides a unique and complete description of the maturity structure of these sovereigns’ debt. Recent studies of the impact of debt maturity on debt dynamics for the US Federal government used data on the US with a similar level of detail 3
ACCEPTED MANUSCRIPT –see Hall and Sargent (2011) or Berndt et al. (2012), for example. My database makes this information readily available for EA countries.
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As mentioned, my paper exploits this original database on Euro Area debt and yields to describe past contributions of different factors (nominal returns, inflation, real GDP growth and primary deficits) to changes in the debt-to-GDP ratios of the EA. These contributions are calculated following the accounting identity defined in the government budget constraint, as in Hall and Sargent (2011). The concept of debt return defined in the budget constraint is the one-period holding return on bonds with different maturities. Thus, it includes capital gains experienced by bondholders due to responses of the yield curve to macroeconomic shocks. The size of these capital gains varies with the maturity of the bond and the theory of optimal debt management has stressed the role of capital gains in inducing fiscal stability –see Angeletos (2002) or Buera and Nicolini (2004), for example. Thus, documenting debt returns in this framework and their effect on debt dynamics is a key contribution of my paper.
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I find that, in both regions, the return on debt is the largest factor contributing to debtto-GDP changes, and it increased this ratio relatively more in the Euro Area than in the US. The difference is due to higher holding returns on medium- and long-term debt in the EA compared to the US. This is explained by bondholders of these maturities receiving a higher rate of return (relative to short-term bondholders) as well as EA countries having larger stocks of medium- and long-term debt. In particular, the capital gains enjoyed by holders of EA long-term bonds were remarkably large before the introduction of the Euro, from 1995 to 1998, when yields in these countries fell sharply. Moreover, primary deficits have been a much more important driver of debt ratios in the US than in the EA. Finally, both regions achieved similar erosions of their debt-to-GDP ratios with GDP growth. Real output growth contributed relatively more than inflation in the US, whereas the opposite has been observed in the EA.
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I also use the government budget constraint to quantify the effect of alternative distributions of debt across maturities in public debt-to-GDP dynamics. For this purpose, I simulate the evolution of these ratios combining historical values for primary deficits, GDP growth and yields with a maturity structure of debt different from the one historically observed. First, I focus on changing the timing of the largest extensions in public debt maturity in my timespan. These were performed by Italy and Spain in the 90’s. I find that, if Spain had had over the period 1995-1998 the (longer) maturity structure observed at the end of 1998, the Spanish debt-to-GDP ratio would have become notably larger. Intuitively, since the Spanish yield curve fell abruptly in these years, a longer debt maturity would have implied higher capital gains for bondholders. Similarly, holders of Italian debt would have experienced less capital gains if the increase in debt maturity experienced in 1994 would have been postponed to 1998, thus lowering the Italian debt-to-GDP ratio. 4
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I perform a similar exercise to study the hypothetical change in the debt-to-GDP ratios that would result from these countries reducing drastically their debt maturity after 2009. Recent studies –Giordano et al. (2013), Ludwig (2014) or Bordon et al. (2014)– have documented that yields of peripheral countries in this period were very sensitive to changes in their debt-to-GDP ratios. Thus, these simulations do not take historical yields as given, but instead the counterfactual interest rates at each maturity are modelled as (increasing) functions of the stock of debt with that maturity (divided by GDP). Simulations for both countries show that their debt-to-GDP ratios would have increased more if their debt maturity had been considerably shorter after 2009. Intuitively, a shorter maturity structure would have implied the need to roll over more debt and a higher exposure to the risk premia observed in these years. Therefore, long-term debt in these countries acted as a stabilizer of their debt-to-GDP ratio in this recent crisis.
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Finally, this paper also studies the implications of the currently observed maturity structure of debt for debt-to-GDP dynamics. First, using projections for GDP, primary surpluses and nominal yields from the OECD, I simulate the evolution of the debt-to-GDP ratio until 2022. Given that yields are expected to rise in the coming years (especially in France, Italy and Spain), I find that extending debt maturity in these countries in 2013-2015 will imply more capital losses for bondholders and, as a result, lower public debt ratios. Second, I estimate the expected change in the debt-to-GDP ratios induced by a change in inflation over the next years. The size of this change in the ratio critically depends on the current maturity structure of debt. My estimates indicate that, in the Euro Area, higher (lower) inflation can lower (increase) the fiscal burden of these countries much more than in the US.
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In the next section, I summarize the related literature. In Section 3, I briefly describe the theoretical framework used to study the impact of debt maturity on the evolution of debt-to-GDP ratios. Section 4 presents the database and provides an overview of the data. Section 5 decomposes the contributions of different factors to debt-to-GDP changes in the US and the EA in 1991-2013. Section 6 shows the role that debt maturity played in the debt-to-GDP dynamics of EA countries using counterfactual simulations, and Section 7 provides estimates of the impact of higher inflation in these ratios.
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Review of related literature
The financial crisis was followed by sharp debt surges in advanced economies that motivated several empirical studies of debt dynamics. Abbas et al. (2011) use a new database covering nearly all IMF members and an exceptionally long timespan to document that debt and growth are negatively correlated. Abbas et al. (2013) look at 30 advanced 5
ACCEPTED MANUSCRIPT economies in 1980-2011 and find that debt-to-GDP reductions have been mainly associated with primary surpluses and strong growth. This confirms the finding of Giannitsarou and Scott (2008) that, since 1960, more than 80% of the efforts enhancing fiscal sustainability were done through primary surpluses in industrialized countries. Recently, Reinhart and Sbrancia (2011) study a sample of 12 countries (including Belgium, France, Italy and the US) and find that inflation and financial repression implied annual savings on average interest expenses ranging between 1 and 5% of GDP in 1945-19801 .
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However, most empirical papers on debt-to-GDP dynamics do not study the relation between debt maturity and the evolution of these ratios. One important reason is the lack of data describing the maturity structure of government debt in each country. Recently, Abbas et al. (2014) provide an overview of the composition of sovereign debt in 13 advanced economies from 1900 to 2011 and document that short-term debt was used intensively in debt build-ups. Aizenman and Marion (2011) document a large erosion of the US Federal debt-to-GDP ratio in the aftermath of WWII caused by inflation and facilitated by the higher (average) maturity of US debt in those years. Hall and Sargent (2011) confirm this finding and clarify that, nonetheless, in 1945-2009 bondholders received on average positive returns. They also point at real output growth as the main factor that held down the US debt-to-GDP ratio since WWII.
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A distinctive feature of Hall and Sargent (2011) is that their analysis is based on a full description of the distribution by maturity of the US debt obligations since 19452 . Using estimates of yields for all maturities, they calculate the market value of the US Federal debt and the one-period holding-returns on bonds with different maturities. They find that holders of long-term US bonds suffered large capital losses during the 70’s, when interest rates rose driven by increasingly higher inflation expectations. However, longterm bondholders enjoyed high capital gains in the 80’s, after Volker brought inflation under control and interest rates fell significantly.
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Hilscher et al. (2014) also use a complete description of the claimholder and maturity structures of the US government debt in 2012. They assess the effect of changes in the probability distribution of future inflation on the US fiscal burden. Their estimate for the impact of a 1% permanent increase in inflation is a 1.75% reduction in the debt-toGDP ratio, much lower than previous estimates. This difference is caused by Hilscher et al. (2014) using more detailed data on the amount (and maturity) of debt that could actually be inflated away. Importantly, my original database provides equivalent data for EA countries in 1991-2013. Moreover, this paper describes the impact of debt maturity on debt-to-GDP dynamics for six EA countries following the approach of these studies 1
Reinhart and Sbrancia (2011) define financial repression as interest rate ceilings, large scale official intervention and other policies dampening nominal interest rates. 2 The Center for Research in Security Prices (CRSP) US Treasury Database provides the stocks and characteristics of each of the outstanding Federal government bonds.
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ACCEPTED MANUSCRIPT for the US3 .
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My work is related to the theoretical literature on optimal management of debt maturity. The seminal work of Lucas and Stokey (1983) showed that, under complete markets, government debt management could increase welfare by minimising the costs of distortionary taxation. Later, Angeletos (2002) and Buera and Nicolini (2004) –among others– extended this analysis to incomplete markets. Their results hinge on the ability of debt management to reduce financing needs when facing adverse fiscal shocks (known as fiscal insurance). More recently, Lustig et al. (2008) and Faraglia et al. (2013) present models with sticky prices and incomplete markets in which longer maturity contributes optimally to the liquidation of a significant amount of debt through higher inflation.
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In contrast, there are very few papers studying empirically debt maturity management. Early work by Missale and Blanchard (1994) documents an inverse relation of debt ratios and debt maturity for Italy, Belgium and Ireland in 1960-1990. Importantly, in their model shorter debt maturity signals the commitment of the country not to use inflation to erode the real value of debt. Therefore, the attempt to gain fiscal credibility can explain the management of debt maturity in these countries. More recently, Faraglia et al. (2008) study 11 OECD countries in 1970-2000 and find almost no connection between the degree of fiscal insurance and cross-country variations in debt issuance patterns. Berndt et al. (2012) find that, since WWII, 9 % of unanticipated public spending needs in the US were offset by a reduction in the market value of debt. They also document that long-term debt is more effective in absorbing fiscal shocks than short-term debt.
Basic framework
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As in Hall and Sargent (2011), my work exploits the law of motion of debt described in the period-by-period budget constraint of the government for any time t. If a government issues debt that matures in j = 1, 2, ..., J periods (years), the period t budget constraint takes the form: J X j=1
˜ jt−1 pj−1 Q t
=
J X j=1
˜ jt−1 pjt−1 Q
+
J X j=1
3
j ˜ jt−1 pjt−1 Q rt−1,t
= St +
J X
˜ jt−1 pjt Q
(1)
j=1
Lojsch et al. (2011) provides an overview of the composition of sovereign debt in the EA but without describing in detail its maturity structure. Das (2011) compares debt-to-GDP dynamics of the US and the United Kingdom in 1984-2011 using the approach of Hall and Sargent (2011).
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ACCEPTED MANUSCRIPT j where St is the primary surplus of year t, Q˜t is the nominal value of outstanding net debt obligations at the end of year t maturing after j periods 4 , and pjt is the price in time t euros of an asset that delivers one euro in year t + j (typically, called IOUs). Also, −j pjt = 1 + yt (j) , where yt (j) is the market yield at time t for zero-coupon bonds of maturity j. Debt securities that pay coupons are included in Equation 1 as bundles of promised payments that comprise the repayment of the principal and all implied coupons.
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j Holders earn in period t a rate of return rt−1,t = (pj−1 − pjt−1 )/pjt−1 on each bond. If t the bond does not mature at the end of this period (i.e. the remaining life of the bond exceeds one period or j > 1), the return received by holding the bond includes capital gains (losses) resulting from unexpected decreases (increases) in the yield curve in period t (i.e. in the level of interest rates in the economy). Typically, the longer the remaining life of debt, the larger are these capital gains (losses) experienced by bondholders and the higher (lower) becomes the market value of sovereign debt. Crucially, Equation 2 (the expected present-value budget constraint) states that a higher value of debt requires higher current or future surpluses. Thus, the capital gains experienced by medium- and long-term bondholders are costly for the government. Similarly, Equation 2 requires lower current or future surpluses when bondholders suffer capital losses as a result of an unexpected increase in interest rates. Therefore, the government benefits from bondholders capital losses because this implies a smaller return on debt and a lower fiscal burden5 .
The expected present-value budget constraint of the government is derived as 4
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N et debt obligations are equal to gross outstanding debt minus all kind of asset holdings. Since the central bank is considered by many models part of the government sector, central bank holdings of sovereign debt could be netted out. There are detailed data on Federal Reserve holdings of Treasury bonds but, unfortunately, there are no data available for the ECB. Moreover, my database does not include a maturity description for other assets held by governments in the EA. Thus, I can only exploit the maturity profile of gross government debt obligations in my empirical analysis. Of course, changes in the market value of gross debt could also be influenced by changes in the market value of assets (but, admittedly, they are captured as a residual). 5 In other words, the capital gains (losses) experienced by holders of bonds with remaining life longer than one period represent an opportunity cost (benefit) for the government. Think of a bond issued in period t-1 that matures at t+1. If at time t there is an unexpected decrease (increase) in the level of interest rates, the government promised at issuance (t-1 ) to pay in t+1 an interest higher (lower) than the yield demanded at time t by the markets for a one-period bond. Thus, the price of the bond increases –and the bondholder experiences a capital gain– to align the yield to maturity of previously-issued bonds with newly-issued bonds of the same residual maturity.
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J X
˜ jt−1 pj−1 Q t
= St + Et [mt (1)St+1 ] + Et [mt (1)
j=1
J X
j pjt+1 Q˜t ]
j=1
= St + = St +
K X
k=1 ∞ X
Et [mk (j)St+k ] + Et [mt (K)
J X
˜j ] pjt+K Q t+K
j=1
Et [mt (j)St+j ]
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(2)
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where mt (j) are general pricing kernels used to discount future surpluses. The first line in Equation 2 is basically Equation 1 with the new debt rewritten as the discounted value of next periods’ surplus and newly issued debt, i.e. using Equation 2 for period t+1 and pjt = Et [mt (1)pj−1 t+1 ].
The second line substitutes forward (and up to period t+K ) the period budget constraint and the fact that Et [mt (k)mt+1 (1)] = Et [mt (k + 1)].
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Finally, the third line is the limit when K goes to infinity and applies the well known no-Ponzi-game condition: J X ˜j lim Et mt (K) pjt+K Q t+K = 0 j=1
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K→∞
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Summing up, Equation 1 states that changes in net debt are due to primary deficits or returns on debt. Doing simple arithmetic allows to compare the contribution of different factors pushing up the debt-to-GDP ratio: nominal returns on debt, inflation, real GDP growth or primary deficits. Since my database contains outstanding quantities of gross debt, a residual term is included. Therefore, dividing Equation 1 by nominal output Yt and defining Qjt as the nominal value of outstanding gross debt obligations at the end of year t maturing in j periods, I obtain changes in the gross debt-to-GDP ratio to be J X pjt Qjt j=1
Yt
−
J X pjt−1 Qjt−1 j=1
Yt−1
=
J X j=1
j (rt−1,t
pjt−1 Qjt−1 St SF At − πt−1,t − gt−1,t ) − + Yt−1 Yt Yt
(3)
where πt−1,t and gt−1,t are the inflation6 and real output growth rates. I label the residual 6
Following Hall and Sargent (2011), TIPs for the US where included as separate bonds whose return contribution is not affected by inflation. For simplicity, this is not written explicitly in Equation 3.
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term SF At /Yt , that is equivalent to negative changes in the market value of assets held by the government, divided by GDP. The latter is similar to the stock-flow adjustment term used in similar decompositions –see Campos et al. (2006) or Eurostat (2013)– which reflects mainly the acquisition of assets by the government. As discussed in the next section, these residuals are relevant in recent years, when governments and central banks acquired large quantities of bank assets and government bonds. However, they played a minor role in most of the timespan covered in this analysis for EA countries7 .
Data
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Calculating the contributions to debt-to-GDP changes as in Section 3 requires a complete description of the outstanding stocks of sovereign debt securities, as well as their prices and characteristics, namely maturity dates and promised coupons. Hall and Sargent (2011) study the evolution of US Federal government debt-to-GDP ratios using the Center for Research in Security Prices (CRSP) US Treasury database. I also analyse debt-to-GDP dynamics in the US so that they can be compared with the main focus of my paper: debtto-GDP dynamics in the Euro Area. Thus, I also exploit the CRSP US Treasury database to study the period 1991-2013. Moreover, I include data from the Treasury Bulletin on non-marketable debt and inflation protected securities, called TIPs. In addition, I use estimates of the zero-coupon yield curve provided by Gürkaynak et al. (2007) –and Gürkaynak et al. (2010) for TIPs– to price all promised payments: principals and stripped coupons8 . Data for GDP, inflation and primary deficits come from the NIPA tables.
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Fiscal data for the central government of countries in the Euro Area are provided by Eurostat 9 . Unfortunately, data on debt of EA countries on a security-by-security basis are not readily available in any database. Thus, I built my own dataset with information about each outstanding security published in the reports of the Treasuries, debt management agencies and Central Banks. An appendix lists all my sources as well as the criteria used
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In the US, unconventional monetary policies absorbed part of the Treasury’s outstanding long-term debt, reducing the maturity of debt held by private investors –see Greenwood et al. (2014). Thus, the role played by capital gains in US debt dynamics would be slightly smaller if my analysis had excluded the debt held by the Fed. This is because fewer bonds will be considered a source of capital gains, and their average maturity will be shorter (and this typically reduces the size of bond price changes in response to macroeconomic shocks). In the Euro Area, similar policies were implemented during the debt crisis. Thus, the size of the contributions of debt returns to debt-to-GDP changes would also be slightly smaller if I had only considered government bonds in private hands. Due to lack of data, I cannot bring my analysis to this level of detail; however, the conclusions will be very similar because this issue became relevant only in very recent years. 8 Hall and Sargent (2011) show that using these yield estimates instead of the actual prices reported by CRSP result in very similar market values of debt. 9 Data for deficits and net interest payments can be found at Government revenue, expenditure and main aggregates; see Annual National Accounts for data on GDP and its deflator.
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1.1
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50
(market−valued) debt−to−GDP (%)
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Debt−to−GDP (%) in EA countries (market−valued)
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US market debt/GDP EA market debt/GDP US market−to−face debt EA market−to−face debt
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(market−valued) debt−to−GDP ratio (%)
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Market−valued debt−to−GDP and market−to−face debt values
market−to−face value debt ratio
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Then, I calculate the market value of debt as the sum of all promised payments discounted using zero-coupon yield estimates available in the BIS databank11 . These estimates do not cover the complete timespan for Italy, Belgium and France; thus yield estimates offered by Bloomberg are used instead. In the Online Appendix I document that my database contains the main changes in the debt maturity structure of the six countries in my sample. I also show that my calculations of the market values of debt replicate the values officially reported in the financial accounts12 . Moreover, although the data on primary deficits and my computed debt returns replicate to a large extent the historical changes in the market value of debt, I also document any residual term. The latter are highly correlated with the series for asset acquisitions provided in Eurostat and they become a relevant contributor to debt changes in the years following the financial crisis13 .
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60
40
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Figure 1: Debt-to-GDP ratios for US and EA (market value) 10
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Figure 1 of the Online Appendix plots annual promised payments (including both principals and stripped coupons) on marketable debt with different maturities for each country. Italy and France have issued indexed and inflation-protected securities, thus reference indexes and actual inflation values have been used to determine realized coupon payments. Germany also issues a few inflation-protected bonds. In the case of Finland, I could only find data from 2002 to 2013. 11 These estimates follow the methodology of Nelson and Siegel or Svensson’s extension. More details can be found at BIS (2005). Figure 2 in the Online Appendix shows 1-, 4-, 7- and 10-years yields for each European country separately. 12 See Figure 3 of the Online Appendix. ESA95 and ESA2010 rules determine that securities should be included as assets or liabilities in the balance sheet of any economic sector at their market value. ESA rules consider the central government a subsector of the general government (S13). 13 My dataset contains stocks of gross debt. Changes in asset holdings and their returns are both determinants of gross debt changes. Unfortunately, given the lack of detailed data on asset holdings and their maturity structure, my analysis captures these factors in the residual term. Figure 4 of the Online Appendix plots the contribution of each factor in the government budget constraint to debt changes. It also compares the residuals and the series for asset acquisitions provided in Eurostat (see Transition from the deficit/surplus to the change in debt or Quarterly financial accounts).
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Figure 1 shows, on the left-hand side, the ratios of the market value of debt and GDP for US and the Euro Area14 . Both economies increased their debt-to-GDP ratios substantially between 1991 and 2013: by 26 percentage points (pp) and 40pp, respectively. The evolution of these ratios is similar: a sharp increase in the recent crises preceded by stabilization in the 2000’s. In 1991-1999, however, the EA debt ratio increased by 2.35pp annually whereas the US lowered it by 1.2pp. In addition, Figure 1 shows the ratio of the market value to the face value of debt that fluctuates in both economies around 105%. Policy discussions typically focus on the face value of debt (equal to the nominal value of all principal payment obligations), whereas the economically relevant value should be measured at market prices. Differences between both measures reflect mainly capital gains (losses) resulting from unexpected changes in the yield curve. My analysis shows that, although these differences are generally small, accounting for them helps in understanding the evolution of the debt-to-GDP ratios.
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The right-hand side of Figure 1 shows the ratios of the market value of debt and GDP for each of the six EA countries in my sample. France and Germany had low initial ratios (below 30% of GDP) that increased almost without interruption during the sample period. Belgium and Italy, on the contrary, had high initial ratios (around 100% of GDP) but consolidated between 1998 and 2007 (achieving, approximately, reductions of 30pp in the former and 18pp in the latter). Finland in the early 90’s, and Spain in recent years, raised their debt ratios by 60pp. In these years, both countries rescued part of their banking sector in the midst of a strong recession. 14
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In general, EA values are calculated adding the six countries’ values weighted by their shares on total annual GDP. These shares are close to 36% in the case of Germany, 26% for France, 21% Italy, 12% Spain, 4% Belgium and 2% Finland. The EA debt concept is all debt issued by the central government and held by other economic sectors, including other general government subsectors. However, the amount of central government debt held by the Social Security sector and State or Local governments is much smaller than in the case of the US. Thus, the US debt concept is Federal government debt held by the Federal Reserve and private investors.
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8
8
Average debt maturity (years) in EA countries
7
6
6
5
5
4
4
3
3
2
2
US EA 1 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13
BE FI FR DE IT ES 1 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13
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Figure 2: Average term to maturity of debt
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To summarize the evolution of debt maturity, the left-hand side of Figure 2 shows the average remaining life of debt (or residual maturity) in the US and EA. Average debt maturity in the US has fluctuated between 6 years (in 2000) and 4 years (in 2008), when debt increased rapidly with bailouts of financial institutions. Typically, close to one fourth of US debt had a remaining term-to-maturity longer than 10 years and 35% was shortterm debt. In contrast, the Euro Area had 20% of short-term debt and increased its share of very long-term debt from 5% to 18%. Thus, the EA average maturity increased from 4.5 to 6.7 years in 2007. Afterwards, with the financial and Euro debt crises, debt maturity of EA countries fluctuated around 6.6 years15 . The right-hand side of Figure 2 shows the average debt maturity in each of the EA countries studied. The largest extensions took place in the 90’s, specially in Italy and Spain. Lately, Belgium and Finland show also large increases, whereas Spain and Italy shortened debt maturity in the Euro debt crisis.
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Figure 3 shows the evolution of 1-year (top row) and 10-year (bottom row) yields for EA countries and the US, the latter with a dashed line. We can easily distinguish three different subperiods marked by the introduction of the Euro in 1999 and the financial crisis in 2007. The early 90’s are characterized by financial turbulences and a recession that depressed bond yields (both short-term and long-term) in 1993. During 1995, the agreement for the establishment of a currency union in 1999 reduced yields by at least 3pp in all countries and initiated a convergence process observed at all maturities, although slightly faster for long-term yields. For countries like Italy and Spain, this episode brought down yields by 2 and 1.5 annual pp respectively, a fall larger than the annual decline of 1.25pp observed in the US after Volcker’s intervention contributed to bringing inflation under control. 15
De Broeck and Guscina (2011) document that a shortening in maturity became debt issuance practice in 16 EA countries and Denmark after the financial crises.
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Between 1999 and 2007, yields in the Euro Area were similar enough to be described as a single yield curve common to all EA countries. There were not large changes in the level of interest rates, but the reduction by 2.5pp observed before 2005 provided capital gains to long-term bondholders that were not offset by a subsequent increase in yields of 1.5pp. The financial crisis brought back fragmentation in the sovereign bond market of EA countries. First, interest rates fell in all countries until 2009, especially short-term yields. Afterwards, risk premia appeared for all maturities. In particular, Italy and Spain were asked (on average) an interest rate 1.5pp higher than Germany for 1-year bonds and 2.5pp higher for 10-year bonds. Other countries were also asked for sizeable risk premia, like Belgium’s average differential with Germany in 10-year bond yields of 0.9pp. 14
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Comparing debt-to-GDP dynamics in US and EA
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This section reports the contributions of different factors to the evolution of each country’s debt-to-GDP ratio. As shown in Equation 3, changes in the debt-to-GDP ratio are caused by inflation, real output growth, primary deficits and returns on debt. To describe the relative importance of these drivers, I report their cumulative contributions to the debtto-GDP separately. In other words, I provide the evolution of the debt-to-GDP ratio that results from adding the contributions of one specific factor and putting those of other drivers equal to zero. Obviously, these determinants of debt-to-GDP changes depend on each other. For example, lower contributions of primary deficits might reflect policies aiming at reducing the contributions of returns. Similarly, higher contributions of inflation might come from the accumulation –through primary deficits, for instance– of a larger stock of debt that can be inflated away. Nonetheless, the simple decomposition of debtto-GDP changes emerging from Equation 3 provides an informative description of the relative role played by these factors.
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Figure 4: Cumulative contributions to changes in debt-to-GDP ratio of US & EA
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First, I compare the drivers of debt-to-GDP ratios in the US and the Euro Area. The top row in Figure 4 summarizes these results showing the cumulative contribution of each factor, relative to each country’s debt ratio in 1991. The bottom row in Figure 4 displays the cumulative contribution of returns on debt with different maturities. More information can be found on Tables reported in the Online Appendix. The first similarity clearly observable in Figure 4 is that the biggest contributor pushing up debt-to-GDP ratios in both economies was the nominal return on debt. However, this factor played a much bigger role in the Euro Area than in the US. This is not surprising, given that the Euro Area had higher debt ratios than the US in most years (as showed in Figure 1). Nonetheless, the US Federal government also gave a lower nominal rate of return (5.1%) than the Euro Area (5.6%) on its debt (on average, across all maturities and along the complete timespan). This will be discussed further by studying the returns on debt of different maturities.
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Moreover, primary fiscal deficits did not play an important role in the Euro Area, but they were key in the US. On average, primary deficits increased annually the US debt-to-GDP ratio by 1.6pp (percentage points), whereas in the Euro Area only by 0.24pp. Although inflation was 2% in both regions, its contribution to eroding the debt-to-GDP ratio was larger in the Euro Area than in the US. Again, this is mainly due to the EA having higher debt ratios that can be inflated away than the US. Annual real output growth averaged 2.6% in the US whereas only 1.3% in the Euro Area. Thus, its contribution to eroding the debt-to-GDP ratio was bigger in the US. Nonetheless, it is worth noticing that annual contributions close to zero in the EA during the last 5 years can explain this difference.
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The bottom row in Figure 4 shows that the difference in contributions of nominal returns between the Euro Area and the US came from debt with maturity longer than one year. Although the EA gave a higher nominal rate of return on short-term debt (3.8%) than the US (3.4%), the EA issued less debt with this maturity. Thus, the contribution of the return on short-term debt to the EA debt-to-GDP ratio was similar to that of the US. However, the EA had much higher stocks of medium- and long-term debt than the US and gave a higher average rate of return on them. Therefore, returns on debt with these maturities made a big difference between the debt-to-GDP ratios of both economies.
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total average on short-term debt on long-term debt 91-99 99-07 07-13 91-13 91-99 99-07 07-13 91-13 91-99 99-07 07-13 91-13 4.2 3.0 1.6 3.1 3.3 1.4 -0.5 1.6 7.6 7.2 5.8 7.0 5.8 2.3 3.1 3.7 3.9 1.3 0.3 1.9 11.4 4.8 6.5 7.7 5.9 2.1 2.5 3.6 3.6 0.7 -0.5 1.4 10.1 4.6 6.2 7.0 6.4 2.2 3.2 4.0 4.4 1.1 -0.1 2.0 10.3 4.5 7.0 7.3 5.2 3.4 2.9 3.9 3.2 2.4 -0.2 2.0 8.2 5.9 7.6 7.2 6.6 1.6 3.0 3.8 4.4 0.9 0.9 2.2 18.9 4.6 5.1 9.9 4.9 0.2 3.7 2.9 4.1 -0.8 2.0 1.7 11.6 2.8 5.2 6.7 is the sum of each country’s values (except Finland) weighted by its share in total GDP
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Table 1: Average real return (%)
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Table 1 shows the average (one-year) real rate of return received by holders of shortterm debt, of debt with maturity longer than seven years and, finally, of debt with all maturities. Comparing real rates of return is more informative as there are remarkable differences on inflation between EA countries and across different periods. Thus, the set of columns on the left shows the average real rate of return of debt of the market portfolio P30 j j j j=1 rt−1,t st−1 − πt−1,t where st−1 is the share of the market value of debt at the end of P j j j / 30 t − 1 maturing in j years, i.e. sjt−1 = pjt−1 qt−1 j=1 pt−1 qt−1 . The set of columns in the center of Table 1 shows the average real rate of return of a portfolio containing only the 1 short-term debt outstanding between 1991 and 2013, that is, rt−1,t − πt−1,t . Finally, the set of columns on the right in Table 1 shows the average real rate of return of a portfolio containing only the outstanding bonds maturing after 7 years. Therefore, this rate is P P30 j j j calculated as 30 j=8 rt−1,t (st−1 / j=8 st−1 ) − πt−1,t . 17
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These average rates of return are ex-post annual rates of return received by the holder of a portfolio of debt during a subperiod or the complete timespan. They are different from the debt interest payments typically reported in the financial accounts in that they include the gains (losses) experienced by holders due to bond price changes. Theory suggests that the absorption of shocks by prices of long-term bonds can play a crucial role in ensuring debt sustainability. For instance, in Angeletos (2002), interest rates increase in response to a government spending shock and the market value of long-term debt drops. As a result, long-term debt is optimal because it reduces the exposure of the government budget to these higher interest rates when rolling-over the debt. In Faraglia et al. (2013), inflation contributes notably to achieving fiscal solvency in a model with sticky prices and an independent central bank. Thus, it is of great interest to document capital gains (losses) for holders of sovereign bonds of EA countries, as well as the reduction of debt returns linked to inflation.
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First, it becomes clear from Table 1 that the average real rate of return on the market portfolio of debt was at least 0.5pp higher in the Euro Area than in the US. Second, this difference in the rate of return was larger on very long-term debt than on short-term debt. In other words, holders of EA long-term bonds did much better than those in the US, in comparison to holders of short-term debt16 . Third, bondholders of all EA countries did very well before the introduction of the Euro, especially long-term bondholders of Italy and Spain. And fourth, in the recent crises, long-term bondholders of EA countries received much higher real returns than short-term bondholders as they enjoyed the highest capital gains since the establishment of the currency union. However, long-term bondholders of Italy and Spain received lower capital gains because the presence of risk premia brought down the price of their bonds.
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An overview of the contributions of different factors to debt-to-GDP changes in each of the countries in my sample can be found in Figure 5. One common feature is that, as observed in Figure 4, nominal returns on debt played a crucial role in raising these ratios17 . In Italy and Spain, there was a clear reduction of these positive contributions after the introduction of the Euro. However, this was not offset by smaller negative contributions of inflation. Another feature common to all countries is that, during the crises, output growth and inflation eroded the debt-to-GDP ratios by less than in previous years. However, higher contributions of primary deficits were, by far, the factor responsible of the dramatic increase in these ratios. 16
In other words, the excess real return rate of long-term debt relative to short-term debt was, on average, larger in the US (5.4pp) than in the Euro Area (5.8pp). Nonetheless, US bondholders received higher real returns between 1999 and 2007 than holders of EA debt securities. 17 In 2002-2013, Finland typically held large stocks of assets whose returns I subtracted from those on its debt. I assumed the rate of return on Finnish assets to be equal to that of its liabilities, thus I multiplied the contributions of debt returns by one minus the ratio of the market values of assets and liabilities. This is the reason behind the lower contributions of debt returns to its debt-to-GDP ratio.
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Figure 5: Cumulative contributions to changes in debt-to-GDP ratio of EA countries
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There are also some remarkable differences between a priori similar economies. For example, the contributions of all factors in France and Germany –the two largest economies in the EA– were very similar, with the exception of primary deficits. In the case of France, deficits contributed every year without interruption, whereas in Germany their contributions were contained since the mid 90’s. Moreover, the two EA countries most highly indebted, Belgium and Italy, ran primary surpluses. The former achieved a sizeable consolidation and successfully lowered the contributions of debt returns, whereas the latter obtained much more modest results. Interestingly, these two economies were the ones that achieved a lower relative erosion of their debt-to-GDP ratio through real output growth. Finally, it is worth stressing the role of my residual term in pushing up the debt ratio of Spain during the recent crises. Even though this result should be interpreted cautiously, it points at the important role played by bank rescue measures (asset acquisitions) in increasing the fiscal burden of this country.
6
Counterfactual simulations
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This section illustrates the role played by debt maturity in debt-to-GDP dynamics using counterfactual simulations. In particular, these simulations show how the debt-to-GDP ratios of EA countries would have evolved if the maturity structure of sovereign debt would have been managed differently18 . I focus on those countries that experienced larger changes in the debt maturity structure and the level of interest rates. Finally, this section studies the impact of an extension of debt maturity in 2013-2015 on the evolution of future debt-to-GDP ratios for the six countries in my sample.
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As discussed in Section 4, Italy and Spain increased the maturity of their sovereign debt more than any other country in my sample. Their largest debt maturity lengthening took place in the 90’s, when bond yields of Euro Area countries fell and converged to a low and stable yield curve common to all EA countries. Moreover, this drop in interest rates was specially pronounced in Italy and Spain: between 1995 and 1998, their long-term bond yields fell every year by 2 and 1.5pp, respectively. These reductions in yields were as strong as the one observed in the US after Federal Reserve Chairman Paul Volcker brought inflation under control19 . Hall and Sargent (1997) show that the US Treasury, by raising the maturity of debt during this episode, gave relatively higher returns on its debt. Similarly, the timing of the debt maturity extensions of Italy and Spain in the 90’s must have had an important effect in these countries’ debt-to-GDP ratios. 18
Find similar simulations for the US in Hall and Sargent (1997), Berman (2013) and Greenwood et al. (2014). 19 Between June 1983 and June 1986, the 10-year Federal government bond fell by 1.9pp annually.
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ACCEPTED MANUSCRIPT Figure 6 shows counterfactual simulations that quantify the effect of the debt maturity extensions done by Italy and Spain in the 90’s. The solid (blue) lines show the evolution of the (historically observed) average maturity of debt and debt-to-GDP ratios. I also show the contributions of nominal returns to debt-to-GDP changes, since this is the main channel through which debt maturity affects debt-to-GDP dynamics. The dashed (red) lines show the effect of changing the timing of the increases in debt maturity. Thus, these simulations combine historical values (for quarterly primary deficits, GDP growth and yields) with a counterfactual debt maturity structure20 .
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The first row shows that delaying until 1998 the increase in Italian debt maturity observed in 1994 would have reduced the debt-to-GDP ratio of this country by 3pp. Intuitively, since the Italian yield curve fell abruptly in 1995-1998, a shorter debt maturity would have implied lower capital gains (and, therefore, holding-returns) to bondholders. Similarly, the second row shows that holders of Spanish government bonds would have enjoyed higher capital gains if the increase in debt maturity observed in 1998 would have been brought forward to 1994. That is, if Spain had had in 1995-1998 the maturity structure observed at the end of 1998, the Spanish debt-to-GDP ratio would have become 5pp higher. The other countries would also have benefited from shorter debt maturity in this episode, but in a lower degree than Italy and Spain since their yield curves fell by less.
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In addition, Italy and Spain were the countries from my sample whose interest rates increased the most during the Euro debt crisis. The difficulties that these countries experienced in bond markets led them to shorten the maturity of their sovereign debt. Recent studies –e.g. Giordano et al. (2013), Ludwig (2014) or Bordon et al. (2014)– have documented that news about fiscal problems in Greece led to a reassessment of the creditworthiness of other countries in the periphery of the Euro Area (referred as wake-up-call contagion in the literature). In particular, Giordano et al. (2013) estimate that a one percent increase in the debt-to-GDP ratio of peripheral countries implied a 50 basis points (bp) increase in their yield differential with respect to Germany. Thus, counterfactual simulations for this episode cannot take historical yields as given, but instead they have been increased with the difference between simulated and historical debt ratios, as in j ˆ jt Q Qt j j − (4) yt − yˆt = φ Yt Yt where the values with a hat are historical while those without, counterfactual.
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In other words, the simulations consist of changing the maturity structure of debt –in particular, the share of total promised payments at different maturities– and iterate Equation 3, the law of motion of public debt, to obtain counterfactual values of debt and returns.
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Nonetheless, this result depends on the value assumed for the coefficient φ. If it were assumed to be 15bp, then the effect of a similar shortening in debt maturity on the debt-to-GDP ratio is almost null. In this case, the term premium demanded on bonds of longer maturity offsets the benefit of reducing roll over risk. But, if it were assumed to be 0.85, the same reduction in maturity would imply increases in the debt-to-GDP ratios of 4pp. Given that the changes in maturity discussed in this section were rather small and that decreasing the debt ratios using alternative tools is economically and politically very costly, these debt ratio changes obtained through debt maturity management are not trivial21 .
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Finally, I discuss counterfactual simulations for future debt-to-GDP ratios in EA countries. The OECD provides annually long-term estimates of macroeconomic variables, including long-term interest rates, primary deficits and GDP22 . I used these forecasts from 2014 to 2022 to simulate the effect of an extension in debt maturity by one year in 2013-2015. However, performing my previous simulations require yields to price bonds with all possible maturities; i.e. the zero-coupon yield curve. Thus, I first took a yield curve observed before 2013 whose term premium was close to the average term premium observed in 1991-201323 . Then, this curve is shifted upwards or downwards according to the difference between its 10-year yield and the long-term forecast provided by the OECD.
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The top-left subplot in Figure 8 shows the forecasts for long-term government bond yields for the six countries in my sample. Interest rates are expected to increase by 2022 in all countries, although following different paths. The top-center and top-right subplots in Figure 8 show the expected evolution of the debt-to-GDP ratios until 2022. The OECD forecasts assume that the debt ratios of all countries are expected to fall24 . Importantly, for each country I also show the expected evolution of the debt-to-GDP ratio in the case that these countries increase the maturity of their public debt by one year in 20132015 (in dashed and dotted lines). In the case of France, Italy and Spain, this maturity 21
The simulations are probably underestimating this effect because the Italian and Spanish governments issued debt more frequently than quarterly, the frequency used in the simulation. Thus, the actual exposure to interest rates incorporating sizeable risk premia was higher. 22 The primary deficits correspond to the general government sector instead of the central government debt and deficit concepts included in my analysis. 23 The term premium is measured as the difference between the 10-year and 1-year interest rates. 24 The OECD assumes that all countries in the Euro Area will have a 60% debt-to-GDP ratio by 2030.
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The bottom row of Figure 8 shows similar simulations under the assumption that interest rates in the Euro Area countries will converge to a single yield curve common to all countries by 2016. I also assume that future long-term yields in EA countries will be equal to those forecasted for France by the OECD and that primary deficits and GDP will be those that this institution predicts for each country. Therefore, the expected impact of extending debt maturity on future French debt-to-GDP ratios is the same as the one shown in the top-row figures. For other countries, the effect of the maturity lengthening is almost null, although Germany would, under this scenario, obtain a slight reduction of its sovereign debt-to-GDP ratio. In the first months of 2014, interest rates in these six EA countries have fallen and yield differentials shrank. In a scenario showing convergence to a very low yield curve, these countries would probably reach relatively higher debt-to-GDP ratios by 2022 as a result of extending debt maturity in 2013-2015.
Estimating the impact of higher inflation
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Section 5 studied past contributions of inflation and other factors to debt-to-GDP dynamics. One of the conclusions drawn was that, in the past, inflation contributed more to bringing down the debt ratio in the Euro Area than in the US. This section estimates the impact of future inflation on the EA debt-to-GDP ratios, based on recent work on the US: Hilscher et al. (2014).
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First, I focus on estimating the effect of a shock that raises inflation by 1pp permanently. Hilscher et al. (2014) interpret this exercise as quantifying the fiscal effect of the Central Bank announcing a permanent increase in its inflation target (as discussed, for instance, in Blanchard et al. (2010) or Krause and Moyen (2013)). A 1% positive shock to inflation that agents know to be permanent would shift the probability distributions that they assign to inflation at all horizons by 1pp. Thus, assuming that this change does not affect the real discounting rate for future payments25 , the nominal rate at which future debt 25
In a model with nominal rigidities, higher distortionary inflation would imply lower output growth and real interest rates. Thus, these estimates would be interpreted as upper bounds to the decrease in the debt burden caused by permanently higher inflation. Moreover, my estimates leave aside whether the real discounting rates could be affected by the reputational implications of this policy change.
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In other words, the impact of 1% higher inflation is approximately equal to 1% times the share (on GDP) of debt that can be actually inflated away times its Macaulay duration26 . Hilscher et al. (2014) show that calculating the effect of the permanent inflationary shock with this approximative formula without using the correct elements in the product would lead to considerably different estimates. For instance, including the average (residual) term-to-maturity to measure the time during which debt can be inflated away instead of duration would lead to overestimating this erosion27 . Moreover, these authors stress that the debt values which can actually be inflated away must exclude inflation-indexed bonds and sovereign debt held by the central bank28 .
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Table 2 shows my estimates of debt-to-GDP reductions resulting from 1% permanently higher inflation (see the column labelled Impact in My estimates). These estimates are also compared with the approximative calculations used in the literature, e.g. Missale and Blanchard (1994) or Aizenman and Marion (2011) (see the column labelled Impact in Basic approximation). I also show measures of the average number of years that debt is exposed to higher inflation –either duration or average (residual) term to maturity– and 26
Macaulay duration is the average term-to-maturity of all future outlays, weighted by their market present value. It also constitutes a measure of the sensitivity of the price of a fixed-income investment to a change in interest rates. PJ ˆj Q 27 t ˆ jt is the nominal (face value) of Average residual maturity is equal to j=1 j · PJ Qˆ j where Q j=1
t
principals to be repaid in j periods (excluding coupons). Duration uses instead the market value of all future outlays (including coupons) and is typically lower than the average residual maturity. 28 Hilscher et al. (2014) also use option prices to construct risk-adjusted probability distributions for inflation at different horizons. Thus, they can also analyse the probability that the market assigns to inflation lowering the fiscal burden significantly. My paper estimates the impact of inflation changes in the debt burden of EA countries under different scenarios without specifying the probability that markets give to these changes. Instead, I am assuming that these are plausible realizations among all possible scenarios that economic agents contemplate when they form (rational) expectations about inflation.
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Table 2: Reduction in debt burden due to permanent higher inflation (data from 2013) Basic approximation Av. Mat Ratio Impact 5.59 74.4 4.2 6.62 83.1 5.5 7.44 105.9 7.9 6.37 54.1 3.4 7.01 84.4 5.9 6.50 51.1 3.3 6.43 124.5 8.0 6.20 99.5 6.2
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My estimates Duration Adj. Ratio Impact 3.31 55.9 1.7 5.76 77.5 4.2 6.10 103.8 6.0 6.00 54.1 3.1 6.09 81.8 4.7 6.00 50.9 2.9 5.35 102.9 5.2 4.91 95.8 4.5
Ratios and Impact are measured as % shares of GDP. Duration and average maturity in years. Adj. Ratio removes inflation-indexed bonds and CB holdings.
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the debt ratios corresponding to both estimates offered. As stressed by Hilscher et al. (2014), the estimated effect for the US is much smaller when it is calculated following Equation 5. The values of Macaulay duration (see the column labelled Duration) and debt ratios without TIPs and Federal Reserve holdings (see the column labelled Adj. Ratio) illustrate the origin of this reduction: the Fed is currently holding a large share of US Federal long-term bonds. Notice that, when this debt-to-GDP erosion is calculated using Equation 5 instead of the product of 1% with average maturity and with all debt obligations, the resulting estimate for the EA changes less than for the US29 . Nevertheless, the main message of Table 2 is that the EA would obtain a reduction in its debt burden 2.5 times higher than the one estimated for the US.
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Belgium stands out as the country that would benefit the most from higher inflation, as it has a large debt ratio with the highest duration. On the contrary, the calculations equal to the product of debt ratios with average term to maturity would point at Italy as the most benefited country, with an expected liquidation of 8%. However, an amount of debt representing over 20% of Italian GDP is held by the Central Bank or consists of inflation-indexed securities and floating rate coupon payments (whose final amounts depend on the evolution of short-term interest rates). Thus, my estimate resulting from applying Equation 5 to securities that can actually be inflated away is only 5.2%. These estimates contribute to the discussion about a higher inflation target for Central Banks. The advantages of this policy change has been discussed by Blanchard et al. (2010) and Krause and Moyen (2013): providing more room for standard monetary policy 29
Total shares of debt held by the Central Bank for each EA country are taken from Bruegel database of sovereign debt holdings, Merler and Pisani-Ferry (2012). Table 2 in the Online Appendix summarizes debt-holder shares in 2013 or the latest date available. Since my dataset is based on information security by security, I can easily exclude TIPs for the US, indexed OAT and BTAN securities for France, and the Italian CCT, BTPi and BTP Italia. CCT securities give flexible rate coupons that will immediately rise with higher inflation. The rest are all inflation-indexed bonds.
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to react to large shocks (increasing the distance to the zero lower bound) and facilitating private and public deleveraging. Although inflation is a random process that cannot be fully controlled by the Central Bank, my framework assumes that this policy would raise inflation expectations at all horizons and reduce the expected real value of future debt payments. This erosion of the real debt burden would be immediately reflected (through higher inflation expectations and interest rates) in a lower current market value of debt. My results suggest that the fiscal burden of highly indebted EA countries like Belgium, France, Italy and Spain can be lowered significantly by permanently higher inflation in the Euro zone. A related question is who will suffer the real losses linked to higher inflation30 . Italian and Spanish residents would face significant losses in the case of higher own-country inflation because they hold close to 65% of their country’s debt. Table 3: Estimated reduction in debt-to-GDP ratio (data from 2013) Temp 1Y 1% π>0 π<0 0.7 -0.7 1.4 -1.4 1.8 -1.9 1.0 -1.1 1.4 -1.5 0.9 -0.9 1.8 -1.9 1.7 -1.7
Temp 5Y 1% π>0 π<0 1.1 -1.2 2.3 -2.4 3.1 -3.3 1.9 -2.0 2.5 -2.6 1.6 -1.6 3.0 -3.2 2.8 -2.9
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Gradual 1% π>0 π<0 1.0 -1.1 2.8 -3.2 4.2 -4.8 2.1 -2.3 3.3 -3.8 2.0 -2.3 3.4 -3.9 2.8 -3.2
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Permanent 1% π>0 π<0 1.7 -1.8 4.2 -4.7 6.0 -6.7 3.1 -3.4 4.7 -5.3 2.9 -3.2 5.2 -5.8 4.5 -5.0
Temp 5Y 2% π>0 π<0 2.2 -2.3 4.6 -5.0 6.1 -6.7 3.7 -4.1 4.9 -5.4 3.0 -3.3 5.9 -6.5 5.5 -5.9
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Finally, Table 3 shows the estimated reduction in the debt-to-GDP ratios under different scenarios of future inflation. The first column shows these estimates for 1% permanently higher and lower inflation (the former was shown already in column 3 of Table 2) . The absolute values of these estimates are similar but those corresponding to negative changes in inflation are higher. This is especially relevant if current low values of inflation in the Euro Area become permanent: the implied increase in the fiscal burden of these countries would be sizeable. Similarly, in the scenarios explored in the following columns, the size of the effect of a negative shock to inflation is always larger than in the case of positive shocks. Thus, current inflation rates in the Euro Area close to zero and very low inflation forecasts should give an alert to governments of EA governments. Similarly, monetary policy should account for the asymmetric fiscal consequences of inflation changes of different signs. The next column Gradual 1% shows the effect of a gradual and permanent increase in inflation. In the first year after the inflationary shock this variable is unaffected, but in the following decade inflation increases 0.1pp every year until a rate 1pp higher is reached and maintained forever. Thus, the large amounts of debt with short- and mediumterm maturity are not exposed to higher inflation and the erosion of the fiscal burden is 30
Debt losses imposed to non-resident bondholders are shown in Table 2 of the Online Appendix.
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The column Temp 1Y 1% shows the impact of an immediate and temporary change of 1pp in the inflation rate that disappears by becoming 0.1pp smaller in each of the next 10 years. My assumption is that nominal yields with different maturities will experience the same change as expected inflation at the corresponding horizon. In the column Temp 5Y 1% the shock starts to die out after keeping during 5 years the inflation rate 1pp higher (or lower) than the currently expected rate. Obviously, the impact estimates in Temp 5Y 1% are higher (in absolute terms) than in the column Temp 1Y 1% because the temporary change in inflation lasts longer. Importantly, the temporary shock in Temp 5Y 1% already produces more than half of the effect of a permanent shock. Thus, transitory shocks to inflation can have a significant impact in the debt burden of EA countries even if they do not last the whole remaining life of outstanding debt.
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Conclusion
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Finally, the column Temp 5Y 2% shows the effect of a shock of the type in Temp 5Y 1% whose size is doubled. In the case of a positive shock, a bigger increase in inflation implies a less-than-proportional extra erosion of the fiscal burden. However, a larger reduction in the inflation rate brings a more-than-proportional increase in the real value of debt (divided by GDP). Thus, the ECB should be aware that periods in which large shifts (positive or negative) in inflation forecasts are plausible constitute a bigger threat for the governments fiscal budget.
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The financial crisis and subsequent Euro debt crisis have increased debt-to-GDP ratios in the Euro Area drastically. As a result, EU leaders and national politicians agreed on the need to monitor the developments in debt ratios so that the necessary measures to guarantee their stability can be taken in a timely fashion. However, the role that debt maturity played (and can play in the future) in EA debt-to-GDP dynamics had received little attention, mainly due to lack of data. My paper has studied these important issues empirically using a unique and original database on bond stocks and yields for six Euro Area countries from 1991 to 2013. Based on the government budget constraint, I calculated past contributions to debt-toGDP dynamics of inflation, returns on debt with different maturities and other factors. I concluded that real returns on long-term debt was the factor that contributed the most to pushing up the debt-to-GDP ratios of EA countries. Moreover, I performed counterfactual simulations to show the evolution of these ratios under a debt maturity structure different from the one historically observed. These exercises illustrated the importance that debt 30
ACCEPTED MANUSCRIPT maturity management had in the years before the introduction of the Euro and during the recent debt crisis. Finally, I estimated that an unexpected increase in inflation can lower significantly the fiscal burden of these countries. Similarly, if the currently observed low inflation persists over the next 5-10 years, fiscal consolidation in these countries will become much more painful as they will give very high real returns to bondholders.
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One possible extension of my work will be to compare debt-to-GDP dynamics for the biggest EA economies and the United Kingdom. More interestingly, my estimates of returns on EA debt with different maturities could be used to test the implications of models of debt management or Faraglia et al. (2013). In their model, if the maturity of government debt is long, then inflation plays a key role in achieving fiscal solvency when an independent authority sets the monetary policy rate optimally. Recently, Berndt et al. (2012) studies the US case and finds that the financing needs raised by government spending shocks were moderated by long-term debt giving lower real holding-returns.
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References Abbas, S. A., Akitoby, M. B., Andritzky, M. J. R., Berger, M. H., Komatsuzaki, M. T., and Tyson, J. (2013). Dealing with high debt in an era of low growth. Number 13-17. International Monetary Fund.
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Abbas, S. A., Belhocine, N., El-Ganainy, A., and Horton, M. (2011). Historical patterns and dynamics of public debt: Evidence from a new database. IMF Economic Review, 59(4):717–742. Abbas, S. A., Blattner, L., De Broeck, M., El-Ganainy, A., and Hu, M. (2014). Sovereign debt composition in advanced economies: A historical perspective. Technical report, International Monetary Fund.
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Aizenman, J. and Marion, N. (2011). Using inflation to erode the us public debt. Journal of Macroeconomics, 33(4):524–541. Angeletos, G.-M. (2002). Fiscal policy with noncontingent debt and the optimal maturity structure. The Quarterly Journal of Economics, 117(3):1105–1131. Berman, J. (2013). The maturity structure of treasury debt: How costly is mismanagement? Yale Journal of Economics.
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Berndt, A., Lustig, H., and Yeltekin, Ş. (2012). How does the us government finance fiscal shocks? American Economic Journal: Macroeconomics, 4(1):69–104.
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BIS (2005). Zero-coupon yield curves: Technical documentation. BIS papers, 25.
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Blanchard, O., Dell’Ariccia, G., and Mauro, P. (2010). Rethinking macroeconomic policy. Journal of Money, Credit and Banking, 42(s1):199–215. Bordon, I. G., Schmid, K. D., and Schmidt, M. (2014). Hypnosis before wake-up call?
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Buera, F. and Nicolini, J. P. (2004). Optimal maturity of government debt without state contingent bonds. Journal of Monetary Economics, 51(3):531–554.
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Campos, C. F., Jaimovich, D., and Panizza, U. (2006). The unexplained part of public debt. Emerging Markets Review, 7(3):228–243. Das, P. (2011). Decomposition of debt-gdp ratio for united kingdom: 1984-2009. Technical report. De Broeck, M. and Guscina, A. (2011). Government Debt Issuance in the Euro Area: The Impact of the Financial Crisis. International Monetary Fund. Eurostat (April 2013). Stock-flow adjustment (sfa) for the member states, the euro area and the eu27 for the period 2009-2012, as reported in the april 2013 edp notification. Technical report, Eurostat. 32
ACCEPTED MANUSCRIPT Faraglia, E., Marcet, A., Oikonomou, R., and Scott, A. (2013). The impact of debt levels and debt maturity on inflation. The Economic Journal, 123(566):F164–F192. Faraglia, E., Marcet, A., and Scott, A. (2008). Fiscal insurance and debt management in oecd economies. The Economic Journal, 118(527):363–386. Giannitsarou, C. and Scott, A. (2008). Inflation implications of rising government debt. In NBER International Seminar on Macroeconomics 2006, pages 393–442. University of Chicago Press.
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Giordano, R., Pericoli, M., and Tommasino, P. (2013). Pure or wake-up-call contagion? another look at the emu sovereign debt crisis. International Finance, 16(2):131–160. Greenwood, R., Hanson, S. G., S., R. J., and Summers, L. H. (2014). Government debt management at the zero lower bound.
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Gürkaynak, R. S., Sack, B., and Wright, J. H. (2007). The us treasury yield curve: 1961 to the present. Journal of Monetary Economics, 54(8):2291–2304. Gürkaynak, R. S., Sack, B., and Wright, J. H. (2010). The tips yield curve and inflation compensation. American Economic Journal: Macroeconomics, pages 70–92.
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Hall, G. J. and Sargent, T. J. (1997). Accounting for the federal government’s cost of funds. Economic Perspectives-Federal Reserve Bank of Chicago, 21:18–28.
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Hall, G. J. and Sargent, T. J. (2011). Interest rate risk and other determinants of post-wwii us government debt/gdp dynamics. American Economic Journal: Macroeconomics, 3(3):192–214.
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Hilscher, J., Raviv, A., and Reis, R. (2014). Inflating away the public debt? an empirical assessment.
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Krause, M. U. and Moyen, S. (2013). Public debt and changing inflation targets. Number 06/2013. Discussion Paper, Deutsche Bundesbank.
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Lojsch, D. H., Rodriguez-Vives, M., and Slavík, M. (2011). The size and composition of government debt in the euro area. Technical report, European Central Bank. Lucas, R. E. and Stokey, N. L. (1983). Optimal fiscal and monetary policy in an economy without capital. Journal of monetary Economics, 12(1):55–93. Ludwig, A. (2014). A unified approach to investigate pure and wake-up-call contagion: Evidence from the eurozone’s first financial crisis. Journal of International Money and Finance, 48:125–146. Lustig, H., Sleet, C., and Yeltekin, Ş. (2008). Fiscal hedging with nominal assets. Journal of Monetary Economics, 55(4):710–727. 33
ACCEPTED MANUSCRIPT Merler, S. and Pisani-Ferry, J. (2012). Who’s afraid of sovereign bonds? Technical report, Bruegel Policy Contribution. Missale, A. and Blanchard, O.-J. (1994). The debt burden and debt maturity. The American Economic Review.
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Reinhart, C. M. and Sbrancia, M. B. (2011). The liquidation of government debt. Technical report, National Bureau of Economic Research.
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Data sources United States
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The analysis for the United States relies heavily on Hall and Sargent (2011). I obtain quantities and characteristics of outstanding marketable nominal bonds (i.e. Treasury Bills, Notes and Bonds) from the Center for Research in Security Prices (CRSP) Annual US Treasury Database (2013). Similar data for TIPs (inflation-protected securities) are retrieved from December issues of the US Treasury’s Monthly Statement of Public Debt for 1997-2013. Moreover, series of nominal non-marketable debt are December observations taken from the Treasury Bulletin31 . Finally I price all payments using the nominal and real zero-coupon yield curves computed by Gürkaynak et al. (2007) and Gürkaynak et al. (2010).
Belgium
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Belgostat, the online database of the National Bank of Belgium (NBB), shows the outstanding amounts of Treasury debt by currency and type of instrument: Linear Bonds (also called OLOs), State Notes and classic loans (that pay coupons and have maturity longer than one year), and Treasury Certificates and Bills (that are zero-coupon shortterm debt instruments). However, the annual reports from the Belgian Debt Agency also include significant amounts of Treasury Bonds issued by the Silver Fund as well as small amounts from a recent program designed to attract German investors called Schuldscheine and EMTNs. This paper’s database collects the details for each outstanding OLO, clasic loan and Silver Fund bond available in these reports and uses information about issuances to build a similar description for State Notes32 .
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The Belgian Debt Agency does not publish reports before 1999, however the report corresponding to that year gives a detailed description of the maturity structure of public debt since 198633 . The outstanding amount of debt with each residual maturity is, nonetheless, the sum of debt issued in different dates and therefore it is unclear which coupon rate would correspond to the outstanding principals. The criterion followed is that debt at time t maturing in j periods is the sum of debt issued at time t-1 with maturity j+1 plus (plausibly) new debt maturing after j periods (i.e. issued at time t). In this way, I assign the year of issuance for different tranches of debt with the same residual maturity and 31
Table OFS-1: Distribution of Federal Securities by Class of Investors and Types of Issue. The small amounts of Schuldscheine and EMTNs are not included because their information is incomplete. For simplicity, the total amounts of debt with maturity lower than one year have been included as one security that matures after one year. 33 Table 13 in the report. 32
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In order to price these outstanding payments at different maturities, I use the yield curves estimated by the NBB which are available at the BIS databank since 1997. For 1991-1996, I interpolated and smoothed the average yield-to-maturity rates of OLOs that the NBB makes available at different maturities in Belgostat. Finally, the small difference between the face value of all above-mentioned debt and the gross (nominal) debt officially reported by the Treasury is added directly to the market value of debt resulting from the model.
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Figure 3 in the Online Appendix compares the resulting market value of debt with the Total Liabilities reported by the OECD’s Belgian balance sheet for the central government34 . It also compares the average debt maturity of the data with the average residual maturity from the OECD’s central government database. Although the resulting market values for this country are more different to the official numbers than for other countries, yearly changes in debt maturity are definitely correctly captured.
Finland
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The database of the Finnish State Treasury shows the stocks of debt by currency and type of industry since 2002. Most of this debt is denominated in euros and issued in serial long-term bonds and Treasury Bills, representing around 90% of all debt in securities. Upon request, the Treasury facilitated the stocks and main characteristics (i.e. maturity date and coupon rate) for each end-of-year outstanding serial bond, as well as the average Finnish debt maturity since 199135 .
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In order to price the implied promised payments at different maturities, I use the yield curves published by Bloomberg since 1998. The nominal value of the 10% of debt in securities with unspecified maturity is added to the market value of all promised payments. Figure 3 in the Online Appendix compares the resulting market value of securities with the Liabilities in securities reported by the OECD’s Finnish balance sheet for the central government. It also compares the reported average debt maturity with that coming from the data collected. Both series are well matched and therefore can be reliably used to study the impact of debt maturity changes on debt dynamics since 2002. Finally, changes in debt in instruments other than securities should be taken into consideration in the exercise of decomposing debt-to-GDP changes. The values of liabilities in 34
As I cannot separate debt in securities from other instruments for the complete timespan, I compare with the value of all liabilities in the balance sheet. 35 As a result, the information necessary and available for our model starts in 2002. Differently than for France and Germany, few information available about previous years is not enough to get a good assessment of the debt maturity structure in that period.
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loans and currency have been retrieved from the OECD’s Finnish balance sheet for the central government. It is clear from this balance sheet that the Finnish central government holds assets whose value represents around 50% of the value of all liabilities. Although the returns on these assets imply a significant source or revenue, the model does not include assets holdings. Instead, it is assumed that asset holdings have a maturity structure similar to that of securities. As a result debt returns net of asset returns would be a share of the returns for all securities derived in the model. Values for these shares –capturing the changing ratio of assets to liabilities– are taken also from the OECD’s Finnish balance sheet.
France
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The website of the Agence France Tresor, the French Treasury, makes available since January 1998 the Monthly Bulletins published by this institution. These bulletins contain all the characteristics and quantities of the securities outstanding at the end of the previous month. These securities are zero-coupon one-year bonds (or BTFs), five-year bonds (or BTANs), and long-term bonds (also called OATs). The Treasury also issues floating-rate bonds (TEC 10 OATs pegged to the constant 10-year maturity rate) and inflation-indexed bonds (OATi, for French inflation; and OATiEUR, for Euro Area inflation). Historical series for these indexes are also available in the Treasury’s website. Differently than for the US, there are not estimates available of the yield curve for these special bonds. My approach consists on assuming perfect knowledge of future realizations of these indexes and apply then in the calculation of future promised payouts. As a result, I can price them as any other standard security.
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Moreover, the OECD’s central government database provides the stocks of debt for 19911996 for each type or class of bond. It is therefore possible to make some assumptions to describe their maturity structure in these years. I choose to assume recursively and backwards that the difference in each year between the total stock outstanding for each class of bonds (i.e. BTFs, OATs, etc) and the sum of outstanding bonds in that class whose details (maturity, coupon rate, etc) are included in my database has its origin on bonds issued one year before. Whenever a coupon rate needs to be fixed, the estimated yield-to-maturity corresponding to that issuance period will be assigned. Following this methodology, the share of unknown (and assumed) information about the maturity structure increases when moving further back in time, but the stocks of debt assigned to each class of bond are exactly those reported by the OECD. In order to price these outstanding payments at different maturities, I use the yield curves estimated by the Banque de France (BdF) since the beginning of 1992 until June 2004 available at the BIS databank. For 2004-2013, I interpolated and smoothed the yield 37
ACCEPTED MANUSCRIPT curve estimates offered by Bloomberg. Figure 3 in the Online Appendix shows that the resulting market value of debt and average debt maturity follow closely the Liabilities in securities and average residual maturity reported by the OECD in its Belgian balance sheet for the central government and central government database36 .
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Finally, changes coming from variations in debt in instruments other than securities should be taken into consideration in the exercise of decomposing debt-to-GDP changes. Values for debt in loans, currency and deposits are taken from the Quarterly series of government debt in Eurostat for 2000-2013 complemented with data for 1991-1999 from the OECD’s central government database.
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The website of Bundesbank makes publicly available the estimates of zero-coupon yields for German government bonds performed by this institution since 1973. Therefore, pricing German debt following the methodology of this paper is straightforward. However the quantities and characteristics of each outstanding bond have not been reported to the public. Upon request, the Bundesbank provides the data that allow to construct a complete description of end-of-year outstanding amounts of Bubills, Schatze, Bobls and Bunds auctioned since the end of 2000 and their characteristics37 .
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The German Central Bank also makes available on its website the total nominal stocks of debt (i.e. principal payments promised) for Federal savings notes (with maturities of 1 and 2 years) and Federal Treasury financing papers (maturities of 6 and 7 years). Lacking more detailed information, their nominal value is added directly to the market value of the other securities in the model. Finally, the Federal Debt Agency provides upon request some data on bonds issued by especial funds like Bundesbahn or Treuhandanstalt. Similarly, their nominal value is added directly whenever the stocks, promised coupons, and maturity are not known. Notice also that with each auction the Federal Government retains a certain nominal amount for secondary market operations. In this paper, only the amounts net of own funds have been taken into consideration. Although the detailed information available for Bunds actually goes back to 1997, for 1991-1999 only data on the total nominal stocks for each class of bond were provided by the Federal Debt Agency. Therefore, it is necessary to make some assumptions to describe 36
This database does not cover the years after 2010, therefore the average residual maturity values for 2011-2013 have been completed with data from the Monthly Bulletin of the Treasury, the original source. 37 Bubills –also called Treasury discount paper – have a maturity lower than one year, and Schatze –or Federal Treasury notes– have 2-years maturity. A few Bobls –or Five-year Federal Notes– and Bunds –long-term bonds– are linked to inflation but, since they represent a very small fraction of all issued bonds, I add them with fixed coupons equal to the corresponding spread over an assumed 2% inflation rate.
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the maturity structure of German sovereign bonds since 1991. I choose to assume recursively and backwards that the difference between the total stock for each class of bonds (i.e. Bubills, Schatze, etc) and the sum of outstanding bonds in that class whose details (maturity, coupon rate, etc) are included in my database has its origin on bonds issued one year before. Whenever a coupon rate needs to be fixed, the estimated yield-to-maturity corresponding to that issuance period will be assigned. Following this methodology, the share of information on the maturity structure unknown (and assumed) increases when moving further back in time, but the stocks of debt assigned to each class of bond are exactly those reported by the Federal Debt Agency38 .
Italy
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All promised payments at different maturities have been priced using the zero-coupon yields estimated by the Bundesbank and available both on its website and the BIS databank. Figure 3 in the Online Appendix compares the market value of debt resulting from the model with the Liabilities in securities reported by the OECD’s German balance sheet for the central government39 . It also compares the average maturity of securities of the data with the average residual maturity (before swaps) reported by the Federal Debt Agency in reports. Both series are reasonably matched except for the maturity average at the beginning of the 90’s, the years for which more assumptions were necessary. Finally, in the exercise decomposing debt-to-GDP changes, debt in instruments other than securities should also be taken into consideration. This series is calculated as the difference between Total Liabilities and Liabilities in securities from the OECD’s German balance sheet.
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Since June 2000, the Italian Treasury (Tesoro d’Italia) publishes monthly reports with the stocks and main characteristics of each outstanding bond. Moreover, this institution provides annual reports with a government debt breakdown by instrument since 1982 and time series starting around 1980 with data (stocks and characteristics) on the issuance of BOT, BTP and CCT securities, the most frequently used. Combining these sources and assuming that all securities issued were paid not earlier than maturity, I construct a detailed description of the stocks, promised coupons and maturity of end-of-year outstanding bonds since 199140 . 38
Also, the debt of special funds was taken over by the Federal government in 1999, but I include it as central government debt since 1991 because the ESA95 concept of central government is larger than the central state. 39 The values reported start in 1995; for 1991-1994 I assigned 90% of quantities in the general government balance sheet because that is the share of outstanding general government securities issued by the central government subsector in the rest of the 90’s. 40 In 1991-1995, the annual amounts of outstanding CCTs are larger than the sums of CCTs not redeemed and issued after 1990. I used backwards (and recursively) the assumption that annual differences come from securities issued before 1990.
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The securities included are: zero-coupon bonds (called BOTs for short-term debt and CTZs for long-term securities) as well as securities yielding fixed coupons (BTPs) and floating coupons (CCTs, whose coupon rate applies a spread to the yield of the 6-month BOT issuance celebrated immediately before the beginning of the accrual period) or coupons indexed to the Euribor (called CCTeu) issued by the Italian central government in Italian markets. There are also inflation-indexed bonds: BTPi and BTPitalia. Their market value is calculated by discounting principal and coupon payment promises with estimated yields41 . They represent around 95% of all Italian government debt issued in securities; the rest is mainly issued in foreign currency whose nominal value is added to the market value of those denominated in euros.
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Yield curves estimates for Italy following the Nelson-Siegel methodology can be found in the BIS databank starting in 1995. Note that, in the estimation before 1998q1, Libor and swap data were used instead of data on government bonds. As a result, I used yield curve estimates available in Bloomberg for 1994q4-1997q4. For 1991q4-1994q3, I interpolated and smoothed data on yields to maturity of BOTs and BTPs. The market value of securities calculated with these yield estimates is compared in Figure 3 of the Online Appendix with value of Liabilities in securities reported by the OECD’s Italian balance sheet for the central government since 199542 . Also, residual maturity averages from the OECD’s central government database (until 2010) and Tesoro d’Italia (for recent values) are shown. However, in the exercise decomposing debt-to-GDP changes, debt in instruments other than securities should be taken into consideration. I calculated its value as the difference between the nominal values provided by Banca d’Italia 43 . with the total nominal value of securities reported by Tesoro d’Italia. This debt represents around one fourth of total debt but, since its maturity structure is not specified in the data collected for the paper, its nominal value is simply added to the market value of securities.
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Data for Spanish outstanding central government bonds is easily accessible at the Bank of Spain (BdE) website, where Public Debt Market time series at daily frequency are available starting in 1988. The files used in this paper are labelled sald (outstanding amounts for each security) and carv (charateristics of each security: coupon rate, maturity date, coupon frequency, etc). Central State debt in securities is issued in Letras (maturing after 3-18 months), medium-term securities called Bonos (with 2-5 years maturity), and 41
Future coupon payments for flexible rate and indexed bonds is calculated assuming perfect knowledge about future realizations of their rates or indexes of reference. 42 The financial accounts of Italy are also accessible in the database of Banca d’Italia since 1997. 43 Detailed data since 1997 can be found the database The Public Finances, Borrowing Requirement and Debt (TCCE0375 - Gross Central Government Debt Position: by instrument, maturity, currency and residence). For previous values, see the Historical tables Debito delle Amministrazioni pubbliche.
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ACCEPTED MANUSCRIPT long-terms bonds named Obligaciones (with maturity up to 30 years). To the extent of my knowledge, Spain issued exclusively fixed-rate debt until June 2014 when it started issuing inflation-indexed bonds. Each of these securities is unbundled into coupon and principal payment promises and priced using the zero-coupon yields estimated by the BdE and available at the BIS databank.
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In addition, the Bank of Spain provides data on securities issued by other units also classified as central government: FFPP, FROB, etc. They are stripped and priced also, but their total face value is lower than the quantities reported in Table 12.09 (line 4) of the BdE Statistical Bulletin, therefore the difference is added without specifying its maturity structure44 . The Statistics Bulletin of Tesoro Público, the Spanish Treasury, also reports debt in foreign currency whose face value is also added directly to the market value of securities denominated in euros because its maturity structure is unknown.
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Figure 3 in the Online Appendix compares the model’s value of all securities with the market value of Liabilities in securities reported by the OECD’s Spanish balance sheet for the central government45 . Also, officially reported residual maturity averages from the OECD’s central government database (until 2010) and the Statistics Bulletin from the Spanish Treasury (for recent values) are shown. Both series are reasonably well matched.
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Finally, the exercise of decomposing debt-to-GDP changes requires values for primary surpluses in 1991-1994 which have been calculated with information from the National Statistical Institute (INE): National Accounts Base 86 (Capacidad o necesidad de financiación + Intereses efectivos). Quarterly data on asset acquisitions is taken from Table 12.05 (line 1) of BdE Statistical Bulletin and the value of debt in instruments other than securities is calculated as Total liabilities minus Liabilities in securities from the OCDE’s balance sheet for Spain.
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The series in Table 12.09 of the BdE Statistical Bulletin starts in 1994, so values for 1991-1993 have been obtained as the difference of Total securities in Table 21.12 (line 1) and the face value of Bonos, Obligaciones and Valores en monedas distintos del euro (line 12). 45 The financial accounts of Spain are also accessible in the website of BdE.
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Government Debt Maturity and Debt Dynamics in Euro Area Countries Juan Equiza-Goni ˜ PII: DOI: Reference:
S0164-0704(16)00015-X 10.1016/j.jmacro.2016.01.005 JMACRO 2855
To appear in:
Journal of Macroeconomics
Received date: Revised date: Accepted date:
21 August 2015 26 January 2016 30 January 2016
Please cite this article as: Juan Equiza-Goni, ˜ Government Debt Maturity and Debt Dynamics in Euro Area Countries, Journal of Macroeconomics (2016), doi: 10.1016/j.jmacro.2016.01.005
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Highlights • A new database of EA sovereign debt stocks, at different maturities, in 1991-2013
• Debt dynamics decomposed into factors based on the theoretical budget constraint
• Real returns on debt is the biggest factor pushing-up debt-to-GDP ratios in the EA
• Long-term bond-holders experienced large capital gains, especially in run-up to Euro
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• Higher inflation in EA countries would lower their fiscal burden more than in the US
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Government Debt Maturity and Debt Dynamics in Euro Area Countries
February 13, 2016 Abstract
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Juan Equiza-Goñi∗
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This paper studies the impact of debt maturity on the dynamics of sovereign debt of Euro Area (EA) countries. Due to lack of data, this key issue had not been studied before. Thus, my first contribution is to build a new comprehensive database of sovereign debt stocks and yields, at all different maturities, for six EA countries in 1991-2013: Belgium, Finland, France, Germany, Italy and Spain. In general, since 1991, interests rates in the EA have fallen while Treasuries in the region extended debt maturity; thus, an increasing number of long-term bondholders experienced large capital gains. I show with counterfactual simulations the effect of a different maturity structure on the evolution of debt. My analysis suggests that extending debt maturity in 2013-2015 would result in lower debt ratios by 2022. I also estimate the impact on EA debt-to-GDP ratios induced by changes in current and future inflation. My estimates indicate that higher (lower) inflation in EA countries would lower (raise) their fiscal burden much more than in the US. JEL codes: E31, E43, G12, H63 Keywords: debt dynamics; interest rate risk; debt maturity; inflation
Universidad de Navarra, Pamplona, 31080, Spain. Email: jequizag at unav.es. I am grateful to my PhD adviser Robert Kollmann at Université libre de Bruxelles (ULB) and to this institution for granting mini-Arc funding to my research project. I would also like to thank my discussants and participants at the Belgian Macroeconomics Workshop 2014, SAEe 2014, RES PhD conference 2015 and ENTER Jamboree 2015, as well as Philippe Weil, Raf Wouters and Rigas Oikonomou for comments and suggestions. ∗
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Introduction
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The financial crisis increased substantially the debt-to-GDP ratios of the Euro Area (EA) sovereigns, raising doubts about the sustainability of some countries’ debt and the survival of the currency union as a whole. Consequently, there is a renewed interest in understanding the drivers of debt-to-GDP changes. Theory suggests that the maturity structure of debt can play an important role in the evolution of these ratios through different channels. First, bond prices can absorb adverse fiscal shocks and facilitate tax smoothing (e.g. Lucas and Stokey (1983) or Buera and Nicolini (2004)). Second, debt with longer maturity can be eroded for a longer time by higher than expected inflation (e.g. Lustig et al. (2008) or Faraglia et al. (2013)).
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This paper studies empirically the role of debt maturity in the evolution of debt-to-GDP ratios in the Euro Area. In particular, my analysis generates a set of stylized facts on sovereign debt and yield dynamics for six EA countries: Belgium, Finland, France, Germany, Italy and Spain. My first contribution is to build a new database on outstanding debt securities and yields for these countries in 1991-2013. Then, following an accounting scheme based on the period-by-period government budget constraint, this paper studies past contributions to debt-to-GDP changes of nominal returns on debt with different maturities, inflation and other factors. I find that the high return on long-term debt has been the factor that contributed the most to changing (increasing) the debt ratios in the EA.
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Moreover, I use simulations to show the effect of counterfactual distributions of debt across maturities on debt-to-GDP dynamics. For example, I document that the long maturity of Spanish and Italian sovereign debt during the Euro crisis protected their public budgets from interest rate increases and lowered their debt ratios. I also simulate the trajectory of debt ratios for plausible projections of future yields and fiscal variables. This exercise suggests that EA countries would lower their future debt-to-GDP ratios by increasing debt maturity in 2013-2015. Finally, my paper provides estimates of the impact of higher inflation on the debt burden of EA countries. This effect would be moderate, but larger than in the US. Due to lack of data, no previous work has studied empirically the relation between debt maturity and debt-to-GDP dynamics in EA countries. Thus, my new database is an essential contribution of the paper. I constructed this database mostly on a security by security basis and it combines data from different sources: mainly, national Treasuries and Central Banks. As a result, it provides a unique and complete description of the maturity structure of these sovereigns’ debt. Recent studies of the impact of debt maturity on debt dynamics for the US Federal government used data on the US with a similar level of detail 3
ACCEPTED MANUSCRIPT –see Hall and Sargent (2011) or Berndt et al. (2012), for example. My database makes this information readily available for EA countries.
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As mentioned, my paper exploits this original database on Euro Area debt and yields to describe past contributions of different factors (nominal returns, inflation, real GDP growth and primary deficits) to changes in the debt-to-GDP ratios of the EA. These contributions are calculated following the accounting identity defined in the government budget constraint, as in Hall and Sargent (2011). The concept of debt return defined in the budget constraint is the one-period holding return on bonds with different maturities. Thus, it includes capital gains experienced by bondholders due to responses of the yield curve to macroeconomic shocks. The size of these capital gains varies with the maturity of the bond and the theory of optimal debt management has stressed the role of capital gains in inducing fiscal stability –see Angeletos (2002) or Buera and Nicolini (2004), for example. Thus, documenting debt returns in this framework and their effect on debt dynamics is a key contribution of my paper.
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I find that, in both regions, the return on debt is the largest factor contributing to debtto-GDP changes, and it increased this ratio relatively more in the Euro Area than in the US. The difference is due to higher holding returns on medium- and long-term debt in the EA compared to the US. This is explained by bondholders of these maturities receiving a higher rate of return (relative to short-term bondholders) as well as EA countries having larger stocks of medium- and long-term debt. In particular, the capital gains enjoyed by holders of EA long-term bonds were remarkably large before the introduction of the Euro, from 1995 to 1998, when yields in these countries fell sharply. Moreover, primary deficits have been a much more important driver of debt ratios in the US than in the EA. Finally, both regions achieved similar erosions of their debt-to-GDP ratios with GDP growth. Real output growth contributed relatively more than inflation in the US, whereas the opposite has been observed in the EA.
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I also use the government budget constraint to quantify the effect of alternative distributions of debt across maturities in public debt-to-GDP dynamics. For this purpose, I simulate the evolution of these ratios combining historical values for primary deficits, GDP growth and yields with a maturity structure of debt different from the one historically observed. First, I focus on changing the timing of the largest extensions in public debt maturity in my timespan. These were performed by Italy and Spain in the 90’s. I find that, if Spain had had over the period 1995-1998 the (longer) maturity structure observed at the end of 1998, the Spanish debt-to-GDP ratio would have become notably larger. Intuitively, since the Spanish yield curve fell abruptly in these years, a longer debt maturity would have implied higher capital gains for bondholders. Similarly, holders of Italian debt would have experienced less capital gains if the increase in debt maturity experienced in 1994 would have been postponed to 1998, thus lowering the Italian debt-to-GDP ratio. 4
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I perform a similar exercise to study the hypothetical change in the debt-to-GDP ratios that would result from these countries reducing drastically their debt maturity after 2009. Recent studies –Giordano et al. (2013), Ludwig (2014) or Bordon et al. (2014)– have documented that yields of peripheral countries in this period were very sensitive to changes in their debt-to-GDP ratios. Thus, these simulations do not take historical yields as given, but instead the counterfactual interest rates at each maturity are modelled as (increasing) functions of the stock of debt with that maturity (divided by GDP). Simulations for both countries show that their debt-to-GDP ratios would have increased more if their debt maturity had been considerably shorter after 2009. Intuitively, a shorter maturity structure would have implied the need to roll over more debt and a higher exposure to the risk premia observed in these years. Therefore, long-term debt in these countries acted as a stabilizer of their debt-to-GDP ratio in this recent crisis.
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Finally, this paper also studies the implications of the currently observed maturity structure of debt for debt-to-GDP dynamics. First, using projections for GDP, primary surpluses and nominal yields from the OECD, I simulate the evolution of the debt-to-GDP ratio until 2022. Given that yields are expected to rise in the coming years (especially in France, Italy and Spain), I find that extending debt maturity in these countries in 2013-2015 will imply more capital losses for bondholders and, as a result, lower public debt ratios. Second, I estimate the expected change in the debt-to-GDP ratios induced by a change in inflation over the next years. The size of this change in the ratio critically depends on the current maturity structure of debt. My estimates indicate that, in the Euro Area, higher (lower) inflation can lower (increase) the fiscal burden of these countries much more than in the US.
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In the next section, I summarize the related literature. In Section 3, I briefly describe the theoretical framework used to study the impact of debt maturity on the evolution of debt-to-GDP ratios. Section 4 presents the database and provides an overview of the data. Section 5 decomposes the contributions of different factors to debt-to-GDP changes in the US and the EA in 1991-2013. Section 6 shows the role that debt maturity played in the debt-to-GDP dynamics of EA countries using counterfactual simulations, and Section 7 provides estimates of the impact of higher inflation in these ratios.
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Review of related literature
The financial crisis was followed by sharp debt surges in advanced economies that motivated several empirical studies of debt dynamics. Abbas et al. (2011) use a new database covering nearly all IMF members and an exceptionally long timespan to document that debt and growth are negatively correlated. Abbas et al. (2013) look at 30 advanced 5
ACCEPTED MANUSCRIPT economies in 1980-2011 and find that debt-to-GDP reductions have been mainly associated with primary surpluses and strong growth. This confirms the finding of Giannitsarou and Scott (2008) that, since 1960, more than 80% of the efforts enhancing fiscal sustainability were done through primary surpluses in industrialized countries. Recently, Reinhart and Sbrancia (2011) study a sample of 12 countries (including Belgium, France, Italy and the US) and find that inflation and financial repression implied annual savings on average interest expenses ranging between 1 and 5% of GDP in 1945-19801 .
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However, most empirical papers on debt-to-GDP dynamics do not study the relation between debt maturity and the evolution of these ratios. One important reason is the lack of data describing the maturity structure of government debt in each country. Recently, Abbas et al. (2014) provide an overview of the composition of sovereign debt in 13 advanced economies from 1900 to 2011 and document that short-term debt was used intensively in debt build-ups. Aizenman and Marion (2011) document a large erosion of the US Federal debt-to-GDP ratio in the aftermath of WWII caused by inflation and facilitated by the higher (average) maturity of US debt in those years. Hall and Sargent (2011) confirm this finding and clarify that, nonetheless, in 1945-2009 bondholders received on average positive returns. They also point at real output growth as the main factor that held down the US debt-to-GDP ratio since WWII.
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A distinctive feature of Hall and Sargent (2011) is that their analysis is based on a full description of the distribution by maturity of the US debt obligations since 19452 . Using estimates of yields for all maturities, they calculate the market value of the US Federal debt and the one-period holding-returns on bonds with different maturities. They find that holders of long-term US bonds suffered large capital losses during the 70’s, when interest rates rose driven by increasingly higher inflation expectations. However, longterm bondholders enjoyed high capital gains in the 80’s, after Volker brought inflation under control and interest rates fell significantly.
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Hilscher et al. (2014) also use a complete description of the claimholder and maturity structures of the US government debt in 2012. They assess the effect of changes in the probability distribution of future inflation on the US fiscal burden. Their estimate for the impact of a 1% permanent increase in inflation is a 1.75% reduction in the debt-toGDP ratio, much lower than previous estimates. This difference is caused by Hilscher et al. (2014) using more detailed data on the amount (and maturity) of debt that could actually be inflated away. Importantly, my original database provides equivalent data for EA countries in 1991-2013. Moreover, this paper describes the impact of debt maturity on debt-to-GDP dynamics for six EA countries following the approach of these studies 1
Reinhart and Sbrancia (2011) define financial repression as interest rate ceilings, large scale official intervention and other policies dampening nominal interest rates. 2 The Center for Research in Security Prices (CRSP) US Treasury Database provides the stocks and characteristics of each of the outstanding Federal government bonds.
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ACCEPTED MANUSCRIPT for the US3 .
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My work is related to the theoretical literature on optimal management of debt maturity. The seminal work of Lucas and Stokey (1983) showed that, under complete markets, government debt management could increase welfare by minimising the costs of distortionary taxation. Later, Angeletos (2002) and Buera and Nicolini (2004) –among others– extended this analysis to incomplete markets. Their results hinge on the ability of debt management to reduce financing needs when facing adverse fiscal shocks (known as fiscal insurance). More recently, Lustig et al. (2008) and Faraglia et al. (2013) present models with sticky prices and incomplete markets in which longer maturity contributes optimally to the liquidation of a significant amount of debt through higher inflation.
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In contrast, there are very few papers studying empirically debt maturity management. Early work by Missale and Blanchard (1994) documents an inverse relation of debt ratios and debt maturity for Italy, Belgium and Ireland in 1960-1990. Importantly, in their model shorter debt maturity signals the commitment of the country not to use inflation to erode the real value of debt. Therefore, the attempt to gain fiscal credibility can explain the management of debt maturity in these countries. More recently, Faraglia et al. (2008) study 11 OECD countries in 1970-2000 and find almost no connection between the degree of fiscal insurance and cross-country variations in debt issuance patterns. Berndt et al. (2012) find that, since WWII, 9 % of unanticipated public spending needs in the US were offset by a reduction in the market value of debt. They also document that long-term debt is more effective in absorbing fiscal shocks than short-term debt.
Basic framework
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As in Hall and Sargent (2011), my work exploits the law of motion of debt described in the period-by-period budget constraint of the government for any time t. If a government issues debt that matures in j = 1, 2, ..., J periods (years), the period t budget constraint takes the form: J X j=1
˜ jt−1 pj−1 Q t
=
J X j=1
˜ jt−1 pjt−1 Q
+
J X j=1
3
j ˜ jt−1 pjt−1 Q rt−1,t
= St +
J X
˜ jt−1 pjt Q
(1)
j=1
Lojsch et al. (2011) provides an overview of the composition of sovereign debt in the EA but without describing in detail its maturity structure. Das (2011) compares debt-to-GDP dynamics of the US and the United Kingdom in 1984-2011 using the approach of Hall and Sargent (2011).
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ACCEPTED MANUSCRIPT j where St is the primary surplus of year t, Q˜t is the nominal value of outstanding net debt obligations at the end of year t maturing after j periods 4 , and pjt is the price in time t euros of an asset that delivers one euro in year t + j (typically, called IOUs). Also, −j pjt = 1 + yt (j) , where yt (j) is the market yield at time t for zero-coupon bonds of maturity j. Debt securities that pay coupons are included in Equation 1 as bundles of promised payments that comprise the repayment of the principal and all implied coupons.
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j Holders earn in period t a rate of return rt−1,t = (pj−1 − pjt−1 )/pjt−1 on each bond. If t the bond does not mature at the end of this period (i.e. the remaining life of the bond exceeds one period or j > 1), the return received by holding the bond includes capital gains (losses) resulting from unexpected decreases (increases) in the yield curve in period t (i.e. in the level of interest rates in the economy). Typically, the longer the remaining life of debt, the larger are these capital gains (losses) experienced by bondholders and the higher (lower) becomes the market value of sovereign debt. Crucially, Equation 2 (the expected present-value budget constraint) states that a higher value of debt requires higher current or future surpluses. Thus, the capital gains experienced by medium- and long-term bondholders are costly for the government. Similarly, Equation 2 requires lower current or future surpluses when bondholders suffer capital losses as a result of an unexpected increase in interest rates. Therefore, the government benefits from bondholders capital losses because this implies a smaller return on debt and a lower fiscal burden5 .
The expected present-value budget constraint of the government is derived as 4
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N et debt obligations are equal to gross outstanding debt minus all kind of asset holdings. Since the central bank is considered by many models part of the government sector, central bank holdings of sovereign debt could be netted out. There are detailed data on Federal Reserve holdings of Treasury bonds but, unfortunately, there are no data available for the ECB. Moreover, my database does not include a maturity description for other assets held by governments in the EA. Thus, I can only exploit the maturity profile of gross government debt obligations in my empirical analysis. Of course, changes in the market value of gross debt could also be influenced by changes in the market value of assets (but, admittedly, they are captured as a residual). 5 In other words, the capital gains (losses) experienced by holders of bonds with remaining life longer than one period represent an opportunity cost (benefit) for the government. Think of a bond issued in period t-1 that matures at t+1. If at time t there is an unexpected decrease (increase) in the level of interest rates, the government promised at issuance (t-1 ) to pay in t+1 an interest higher (lower) than the yield demanded at time t by the markets for a one-period bond. Thus, the price of the bond increases –and the bondholder experiences a capital gain– to align the yield to maturity of previously-issued bonds with newly-issued bonds of the same residual maturity.
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J X
˜ jt−1 pj−1 Q t
= St + Et [mt (1)St+1 ] + Et [mt (1)
j=1
J X
j pjt+1 Q˜t ]
j=1
= St + = St +
K X
k=1 ∞ X
Et [mk (j)St+k ] + Et [mt (K)
J X
˜j ] pjt+K Q t+K
j=1
Et [mt (j)St+j ]
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(2)
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where mt (j) are general pricing kernels used to discount future surpluses. The first line in Equation 2 is basically Equation 1 with the new debt rewritten as the discounted value of next periods’ surplus and newly issued debt, i.e. using Equation 2 for period t+1 and pjt = Et [mt (1)pj−1 t+1 ].
The second line substitutes forward (and up to period t+K ) the period budget constraint and the fact that Et [mt (k)mt+1 (1)] = Et [mt (k + 1)].
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Finally, the third line is the limit when K goes to infinity and applies the well known no-Ponzi-game condition: J X ˜j lim Et mt (K) pjt+K Q t+K = 0 j=1
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Summing up, Equation 1 states that changes in net debt are due to primary deficits or returns on debt. Doing simple arithmetic allows to compare the contribution of different factors pushing up the debt-to-GDP ratio: nominal returns on debt, inflation, real GDP growth or primary deficits. Since my database contains outstanding quantities of gross debt, a residual term is included. Therefore, dividing Equation 1 by nominal output Yt and defining Qjt as the nominal value of outstanding gross debt obligations at the end of year t maturing in j periods, I obtain changes in the gross debt-to-GDP ratio to be J X pjt Qjt j=1
Yt
−
J X pjt−1 Qjt−1 j=1
Yt−1
=
J X j=1
j (rt−1,t
pjt−1 Qjt−1 St SF At − πt−1,t − gt−1,t ) − + Yt−1 Yt Yt
(3)
where πt−1,t and gt−1,t are the inflation6 and real output growth rates. I label the residual 6
Following Hall and Sargent (2011), TIPs for the US where included as separate bonds whose return contribution is not affected by inflation. For simplicity, this is not written explicitly in Equation 3.
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term SF At /Yt , that is equivalent to negative changes in the market value of assets held by the government, divided by GDP. The latter is similar to the stock-flow adjustment term used in similar decompositions –see Campos et al. (2006) or Eurostat (2013)– which reflects mainly the acquisition of assets by the government. As discussed in the next section, these residuals are relevant in recent years, when governments and central banks acquired large quantities of bank assets and government bonds. However, they played a minor role in most of the timespan covered in this analysis for EA countries7 .
Data
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Calculating the contributions to debt-to-GDP changes as in Section 3 requires a complete description of the outstanding stocks of sovereign debt securities, as well as their prices and characteristics, namely maturity dates and promised coupons. Hall and Sargent (2011) study the evolution of US Federal government debt-to-GDP ratios using the Center for Research in Security Prices (CRSP) US Treasury database. I also analyse debt-to-GDP dynamics in the US so that they can be compared with the main focus of my paper: debtto-GDP dynamics in the Euro Area. Thus, I also exploit the CRSP US Treasury database to study the period 1991-2013. Moreover, I include data from the Treasury Bulletin on non-marketable debt and inflation protected securities, called TIPs. In addition, I use estimates of the zero-coupon yield curve provided by Gürkaynak et al. (2007) –and Gürkaynak et al. (2010) for TIPs– to price all promised payments: principals and stripped coupons8 . Data for GDP, inflation and primary deficits come from the NIPA tables.
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Fiscal data for the central government of countries in the Euro Area are provided by Eurostat 9 . Unfortunately, data on debt of EA countries on a security-by-security basis are not readily available in any database. Thus, I built my own dataset with information about each outstanding security published in the reports of the Treasuries, debt management agencies and Central Banks. An appendix lists all my sources as well as the criteria used
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In the US, unconventional monetary policies absorbed part of the Treasury’s outstanding long-term debt, reducing the maturity of debt held by private investors –see Greenwood et al. (2014). Thus, the role played by capital gains in US debt dynamics would be slightly smaller if my analysis had excluded the debt held by the Fed. This is because fewer bonds will be considered a source of capital gains, and their average maturity will be shorter (and this typically reduces the size of bond price changes in response to macroeconomic shocks). In the Euro Area, similar policies were implemented during the debt crisis. Thus, the size of the contributions of debt returns to debt-to-GDP changes would also be slightly smaller if I had only considered government bonds in private hands. Due to lack of data, I cannot bring my analysis to this level of detail; however, the conclusions will be very similar because this issue became relevant only in very recent years. 8 Hall and Sargent (2011) show that using these yield estimates instead of the actual prices reported by CRSP result in very similar market values of debt. 9 Data for deficits and net interest payments can be found at Government revenue, expenditure and main aggregates; see Annual National Accounts for data on GDP and its deflator.
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50
(market−valued) debt−to−GDP (%)
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Debt−to−GDP (%) in EA countries (market−valued)
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US market debt/GDP EA market debt/GDP US market−to−face debt EA market−to−face debt
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Market−valued debt−to−GDP and market−to−face debt values
market−to−face value debt ratio
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Then, I calculate the market value of debt as the sum of all promised payments discounted using zero-coupon yield estimates available in the BIS databank11 . These estimates do not cover the complete timespan for Italy, Belgium and France; thus yield estimates offered by Bloomberg are used instead. In the Online Appendix I document that my database contains the main changes in the debt maturity structure of the six countries in my sample. I also show that my calculations of the market values of debt replicate the values officially reported in the financial accounts12 . Moreover, although the data on primary deficits and my computed debt returns replicate to a large extent the historical changes in the market value of debt, I also document any residual term. The latter are highly correlated with the series for asset acquisitions provided in Eurostat and they become a relevant contributor to debt changes in the years following the financial crisis13 .
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60
40
0.9
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20
0.85
BE FI FR DE IT ES 0 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13
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Figure 1: Debt-to-GDP ratios for US and EA (market value) 10
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Figure 1 of the Online Appendix plots annual promised payments (including both principals and stripped coupons) on marketable debt with different maturities for each country. Italy and France have issued indexed and inflation-protected securities, thus reference indexes and actual inflation values have been used to determine realized coupon payments. Germany also issues a few inflation-protected bonds. In the case of Finland, I could only find data from 2002 to 2013. 11 These estimates follow the methodology of Nelson and Siegel or Svensson’s extension. More details can be found at BIS (2005). Figure 2 in the Online Appendix shows 1-, 4-, 7- and 10-years yields for each European country separately. 12 See Figure 3 of the Online Appendix. ESA95 and ESA2010 rules determine that securities should be included as assets or liabilities in the balance sheet of any economic sector at their market value. ESA rules consider the central government a subsector of the general government (S13). 13 My dataset contains stocks of gross debt. Changes in asset holdings and their returns are both determinants of gross debt changes. Unfortunately, given the lack of detailed data on asset holdings and their maturity structure, my analysis captures these factors in the residual term. Figure 4 of the Online Appendix plots the contribution of each factor in the government budget constraint to debt changes. It also compares the residuals and the series for asset acquisitions provided in Eurostat (see Transition from the deficit/surplus to the change in debt or Quarterly financial accounts).
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Figure 1 shows, on the left-hand side, the ratios of the market value of debt and GDP for US and the Euro Area14 . Both economies increased their debt-to-GDP ratios substantially between 1991 and 2013: by 26 percentage points (pp) and 40pp, respectively. The evolution of these ratios is similar: a sharp increase in the recent crises preceded by stabilization in the 2000’s. In 1991-1999, however, the EA debt ratio increased by 2.35pp annually whereas the US lowered it by 1.2pp. In addition, Figure 1 shows the ratio of the market value to the face value of debt that fluctuates in both economies around 105%. Policy discussions typically focus on the face value of debt (equal to the nominal value of all principal payment obligations), whereas the economically relevant value should be measured at market prices. Differences between both measures reflect mainly capital gains (losses) resulting from unexpected changes in the yield curve. My analysis shows that, although these differences are generally small, accounting for them helps in understanding the evolution of the debt-to-GDP ratios.
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The right-hand side of Figure 1 shows the ratios of the market value of debt and GDP for each of the six EA countries in my sample. France and Germany had low initial ratios (below 30% of GDP) that increased almost without interruption during the sample period. Belgium and Italy, on the contrary, had high initial ratios (around 100% of GDP) but consolidated between 1998 and 2007 (achieving, approximately, reductions of 30pp in the former and 18pp in the latter). Finland in the early 90’s, and Spain in recent years, raised their debt ratios by 60pp. In these years, both countries rescued part of their banking sector in the midst of a strong recession. 14
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Figure 2: Average term to maturity of debt
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To summarize the evolution of debt maturity, the left-hand side of Figure 2 shows the average remaining life of debt (or residual maturity) in the US and EA. Average debt maturity in the US has fluctuated between 6 years (in 2000) and 4 years (in 2008), when debt increased rapidly with bailouts of financial institutions. Typically, close to one fourth of US debt had a remaining term-to-maturity longer than 10 years and 35% was shortterm debt. In contrast, the Euro Area had 20% of short-term debt and increased its share of very long-term debt from 5% to 18%. Thus, the EA average maturity increased from 4.5 to 6.7 years in 2007. Afterwards, with the financial and Euro debt crises, debt maturity of EA countries fluctuated around 6.6 years15 . The right-hand side of Figure 2 shows the average debt maturity in each of the EA countries studied. The largest extensions took place in the 90’s, specially in Italy and Spain. Lately, Belgium and Finland show also large increases, whereas Spain and Italy shortened debt maturity in the Euro debt crisis.
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Figure 3 shows the evolution of 1-year (top row) and 10-year (bottom row) yields for EA countries and the US, the latter with a dashed line. We can easily distinguish three different subperiods marked by the introduction of the Euro in 1999 and the financial crisis in 2007. The early 90’s are characterized by financial turbulences and a recession that depressed bond yields (both short-term and long-term) in 1993. During 1995, the agreement for the establishment of a currency union in 1999 reduced yields by at least 3pp in all countries and initiated a convergence process observed at all maturities, although slightly faster for long-term yields. For countries like Italy and Spain, this episode brought down yields by 2 and 1.5 annual pp respectively, a fall larger than the annual decline of 1.25pp observed in the US after Volcker’s intervention contributed to bringing inflation under control. 15
De Broeck and Guscina (2011) document that a shortening in maturity became debt issuance practice in 16 EA countries and Denmark after the financial crises.
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Figure 3: Evolution of short (top) and long-term (bottom) interest rates
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Between 1999 and 2007, yields in the Euro Area were similar enough to be described as a single yield curve common to all EA countries. There were not large changes in the level of interest rates, but the reduction by 2.5pp observed before 2005 provided capital gains to long-term bondholders that were not offset by a subsequent increase in yields of 1.5pp. The financial crisis brought back fragmentation in the sovereign bond market of EA countries. First, interest rates fell in all countries until 2009, especially short-term yields. Afterwards, risk premia appeared for all maturities. In particular, Italy and Spain were asked (on average) an interest rate 1.5pp higher than Germany for 1-year bonds and 2.5pp higher for 10-year bonds. Other countries were also asked for sizeable risk premia, like Belgium’s average differential with Germany in 10-year bond yields of 0.9pp. 14
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Comparing debt-to-GDP dynamics in US and EA
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This section reports the contributions of different factors to the evolution of each country’s debt-to-GDP ratio. As shown in Equation 3, changes in the debt-to-GDP ratio are caused by inflation, real output growth, primary deficits and returns on debt. To describe the relative importance of these drivers, I report their cumulative contributions to the debtto-GDP separately. In other words, I provide the evolution of the debt-to-GDP ratio that results from adding the contributions of one specific factor and putting those of other drivers equal to zero. Obviously, these determinants of debt-to-GDP changes depend on each other. For example, lower contributions of primary deficits might reflect policies aiming at reducing the contributions of returns. Similarly, higher contributions of inflation might come from the accumulation –through primary deficits, for instance– of a larger stock of debt that can be inflated away. Nonetheless, the simple decomposition of debtto-GDP changes emerging from Equation 3 provides an informative description of the relative role played by these factors.
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Figure 4: Cumulative contributions to changes in debt-to-GDP ratio of US & EA
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First, I compare the drivers of debt-to-GDP ratios in the US and the Euro Area. The top row in Figure 4 summarizes these results showing the cumulative contribution of each factor, relative to each country’s debt ratio in 1991. The bottom row in Figure 4 displays the cumulative contribution of returns on debt with different maturities. More information can be found on Tables reported in the Online Appendix. The first similarity clearly observable in Figure 4 is that the biggest contributor pushing up debt-to-GDP ratios in both economies was the nominal return on debt. However, this factor played a much bigger role in the Euro Area than in the US. This is not surprising, given that the Euro Area had higher debt ratios than the US in most years (as showed in Figure 1). Nonetheless, the US Federal government also gave a lower nominal rate of return (5.1%) than the Euro Area (5.6%) on its debt (on average, across all maturities and along the complete timespan). This will be discussed further by studying the returns on debt of different maturities.
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Moreover, primary fiscal deficits did not play an important role in the Euro Area, but they were key in the US. On average, primary deficits increased annually the US debt-to-GDP ratio by 1.6pp (percentage points), whereas in the Euro Area only by 0.24pp. Although inflation was 2% in both regions, its contribution to eroding the debt-to-GDP ratio was larger in the Euro Area than in the US. Again, this is mainly due to the EA having higher debt ratios that can be inflated away than the US. Annual real output growth averaged 2.6% in the US whereas only 1.3% in the Euro Area. Thus, its contribution to eroding the debt-to-GDP ratio was bigger in the US. Nonetheless, it is worth noticing that annual contributions close to zero in the EA during the last 5 years can explain this difference.
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The bottom row in Figure 4 shows that the difference in contributions of nominal returns between the Euro Area and the US came from debt with maturity longer than one year. Although the EA gave a higher nominal rate of return on short-term debt (3.8%) than the US (3.4%), the EA issued less debt with this maturity. Thus, the contribution of the return on short-term debt to the EA debt-to-GDP ratio was similar to that of the US. However, the EA had much higher stocks of medium- and long-term debt than the US and gave a higher average rate of return on them. Therefore, returns on debt with these maturities made a big difference between the debt-to-GDP ratios of both economies.
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total average on short-term debt on long-term debt 91-99 99-07 07-13 91-13 91-99 99-07 07-13 91-13 91-99 99-07 07-13 91-13 4.2 3.0 1.6 3.1 3.3 1.4 -0.5 1.6 7.6 7.2 5.8 7.0 5.8 2.3 3.1 3.7 3.9 1.3 0.3 1.9 11.4 4.8 6.5 7.7 5.9 2.1 2.5 3.6 3.6 0.7 -0.5 1.4 10.1 4.6 6.2 7.0 6.4 2.2 3.2 4.0 4.4 1.1 -0.1 2.0 10.3 4.5 7.0 7.3 5.2 3.4 2.9 3.9 3.2 2.4 -0.2 2.0 8.2 5.9 7.6 7.2 6.6 1.6 3.0 3.8 4.4 0.9 0.9 2.2 18.9 4.6 5.1 9.9 4.9 0.2 3.7 2.9 4.1 -0.8 2.0 1.7 11.6 2.8 5.2 6.7 is the sum of each country’s values (except Finland) weighted by its share in total GDP
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Table 1: Average real return (%)
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Table 1 shows the average (one-year) real rate of return received by holders of shortterm debt, of debt with maturity longer than seven years and, finally, of debt with all maturities. Comparing real rates of return is more informative as there are remarkable differences on inflation between EA countries and across different periods. Thus, the set of columns on the left shows the average real rate of return of debt of the market portfolio P30 j j j j=1 rt−1,t st−1 − πt−1,t where st−1 is the share of the market value of debt at the end of P j j j / 30 t − 1 maturing in j years, i.e. sjt−1 = pjt−1 qt−1 j=1 pt−1 qt−1 . The set of columns in the center of Table 1 shows the average real rate of return of a portfolio containing only the 1 short-term debt outstanding between 1991 and 2013, that is, rt−1,t − πt−1,t . Finally, the set of columns on the right in Table 1 shows the average real rate of return of a portfolio containing only the outstanding bonds maturing after 7 years. Therefore, this rate is P P30 j j j calculated as 30 j=8 rt−1,t (st−1 / j=8 st−1 ) − πt−1,t . 17
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These average rates of return are ex-post annual rates of return received by the holder of a portfolio of debt during a subperiod or the complete timespan. They are different from the debt interest payments typically reported in the financial accounts in that they include the gains (losses) experienced by holders due to bond price changes. Theory suggests that the absorption of shocks by prices of long-term bonds can play a crucial role in ensuring debt sustainability. For instance, in Angeletos (2002), interest rates increase in response to a government spending shock and the market value of long-term debt drops. As a result, long-term debt is optimal because it reduces the exposure of the government budget to these higher interest rates when rolling-over the debt. In Faraglia et al. (2013), inflation contributes notably to achieving fiscal solvency in a model with sticky prices and an independent central bank. Thus, it is of great interest to document capital gains (losses) for holders of sovereign bonds of EA countries, as well as the reduction of debt returns linked to inflation.
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First, it becomes clear from Table 1 that the average real rate of return on the market portfolio of debt was at least 0.5pp higher in the Euro Area than in the US. Second, this difference in the rate of return was larger on very long-term debt than on short-term debt. In other words, holders of EA long-term bonds did much better than those in the US, in comparison to holders of short-term debt16 . Third, bondholders of all EA countries did very well before the introduction of the Euro, especially long-term bondholders of Italy and Spain. And fourth, in the recent crises, long-term bondholders of EA countries received much higher real returns than short-term bondholders as they enjoyed the highest capital gains since the establishment of the currency union. However, long-term bondholders of Italy and Spain received lower capital gains because the presence of risk premia brought down the price of their bonds.
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An overview of the contributions of different factors to debt-to-GDP changes in each of the countries in my sample can be found in Figure 5. One common feature is that, as observed in Figure 4, nominal returns on debt played a crucial role in raising these ratios17 . In Italy and Spain, there was a clear reduction of these positive contributions after the introduction of the Euro. However, this was not offset by smaller negative contributions of inflation. Another feature common to all countries is that, during the crises, output growth and inflation eroded the debt-to-GDP ratios by less than in previous years. However, higher contributions of primary deficits were, by far, the factor responsible of the dramatic increase in these ratios. 16
In other words, the excess real return rate of long-term debt relative to short-term debt was, on average, larger in the US (5.4pp) than in the Euro Area (5.8pp). Nonetheless, US bondholders received higher real returns between 1999 and 2007 than holders of EA debt securities. 17 In 2002-2013, Finland typically held large stocks of assets whose returns I subtracted from those on its debt. I assumed the rate of return on Finnish assets to be equal to that of its liabilities, thus I multiplied the contributions of debt returns by one minus the ratio of the market values of assets and liabilities. This is the reason behind the lower contributions of debt returns to its debt-to-GDP ratio.
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Figure 5: Cumulative contributions to changes in debt-to-GDP ratio of EA countries
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There are also some remarkable differences between a priori similar economies. For example, the contributions of all factors in France and Germany –the two largest economies in the EA– were very similar, with the exception of primary deficits. In the case of France, deficits contributed every year without interruption, whereas in Germany their contributions were contained since the mid 90’s. Moreover, the two EA countries most highly indebted, Belgium and Italy, ran primary surpluses. The former achieved a sizeable consolidation and successfully lowered the contributions of debt returns, whereas the latter obtained much more modest results. Interestingly, these two economies were the ones that achieved a lower relative erosion of their debt-to-GDP ratio through real output growth. Finally, it is worth stressing the role of my residual term in pushing up the debt ratio of Spain during the recent crises. Even though this result should be interpreted cautiously, it points at the important role played by bank rescue measures (asset acquisitions) in increasing the fiscal burden of this country.
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Counterfactual simulations
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This section illustrates the role played by debt maturity in debt-to-GDP dynamics using counterfactual simulations. In particular, these simulations show how the debt-to-GDP ratios of EA countries would have evolved if the maturity structure of sovereign debt would have been managed differently18 . I focus on those countries that experienced larger changes in the debt maturity structure and the level of interest rates. Finally, this section studies the impact of an extension of debt maturity in 2013-2015 on the evolution of future debt-to-GDP ratios for the six countries in my sample.
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As discussed in Section 4, Italy and Spain increased the maturity of their sovereign debt more than any other country in my sample. Their largest debt maturity lengthening took place in the 90’s, when bond yields of Euro Area countries fell and converged to a low and stable yield curve common to all EA countries. Moreover, this drop in interest rates was specially pronounced in Italy and Spain: between 1995 and 1998, their long-term bond yields fell every year by 2 and 1.5pp, respectively. These reductions in yields were as strong as the one observed in the US after Federal Reserve Chairman Paul Volcker brought inflation under control19 . Hall and Sargent (1997) show that the US Treasury, by raising the maturity of debt during this episode, gave relatively higher returns on its debt. Similarly, the timing of the debt maturity extensions of Italy and Spain in the 90’s must have had an important effect in these countries’ debt-to-GDP ratios. 18
Find similar simulations for the US in Hall and Sargent (1997), Berman (2013) and Greenwood et al. (2014). 19 Between June 1983 and June 1986, the 10-year Federal government bond fell by 1.9pp annually.
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ACCEPTED MANUSCRIPT Figure 6 shows counterfactual simulations that quantify the effect of the debt maturity extensions done by Italy and Spain in the 90’s. The solid (blue) lines show the evolution of the (historically observed) average maturity of debt and debt-to-GDP ratios. I also show the contributions of nominal returns to debt-to-GDP changes, since this is the main channel through which debt maturity affects debt-to-GDP dynamics. The dashed (red) lines show the effect of changing the timing of the increases in debt maturity. Thus, these simulations combine historical values (for quarterly primary deficits, GDP growth and yields) with a counterfactual debt maturity structure20 .
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The first row shows that delaying until 1998 the increase in Italian debt maturity observed in 1994 would have reduced the debt-to-GDP ratio of this country by 3pp. Intuitively, since the Italian yield curve fell abruptly in 1995-1998, a shorter debt maturity would have implied lower capital gains (and, therefore, holding-returns) to bondholders. Similarly, the second row shows that holders of Spanish government bonds would have enjoyed higher capital gains if the increase in debt maturity observed in 1998 would have been brought forward to 1994. That is, if Spain had had in 1995-1998 the maturity structure observed at the end of 1998, the Spanish debt-to-GDP ratio would have become 5pp higher. The other countries would also have benefited from shorter debt maturity in this episode, but in a lower degree than Italy and Spain since their yield curves fell by less.
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In addition, Italy and Spain were the countries from my sample whose interest rates increased the most during the Euro debt crisis. The difficulties that these countries experienced in bond markets led them to shorten the maturity of their sovereign debt. Recent studies –e.g. Giordano et al. (2013), Ludwig (2014) or Bordon et al. (2014)– have documented that news about fiscal problems in Greece led to a reassessment of the creditworthiness of other countries in the periphery of the Euro Area (referred as wake-up-call contagion in the literature). In particular, Giordano et al. (2013) estimate that a one percent increase in the debt-to-GDP ratio of peripheral countries implied a 50 basis points (bp) increase in their yield differential with respect to Germany. Thus, counterfactual simulations for this episode cannot take historical yields as given, but instead they have been increased with the difference between simulated and historical debt ratios, as in j ˆ jt Q Qt j j − (4) yt − yˆt = φ Yt Yt where the values with a hat are historical while those without, counterfactual.
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In other words, the simulations consist of changing the maturity structure of debt –in particular, the share of total promised payments at different maturities– and iterate Equation 3, the law of motion of public debt, to obtain counterfactual values of debt and returns.
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Nonetheless, this result depends on the value assumed for the coefficient φ. If it were assumed to be 15bp, then the effect of a similar shortening in debt maturity on the debt-to-GDP ratio is almost null. In this case, the term premium demanded on bonds of longer maturity offsets the benefit of reducing roll over risk. But, if it were assumed to be 0.85, the same reduction in maturity would imply increases in the debt-to-GDP ratios of 4pp. Given that the changes in maturity discussed in this section were rather small and that decreasing the debt ratios using alternative tools is economically and politically very costly, these debt ratio changes obtained through debt maturity management are not trivial21 .
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Finally, I discuss counterfactual simulations for future debt-to-GDP ratios in EA countries. The OECD provides annually long-term estimates of macroeconomic variables, including long-term interest rates, primary deficits and GDP22 . I used these forecasts from 2014 to 2022 to simulate the effect of an extension in debt maturity by one year in 2013-2015. However, performing my previous simulations require yields to price bonds with all possible maturities; i.e. the zero-coupon yield curve. Thus, I first took a yield curve observed before 2013 whose term premium was close to the average term premium observed in 1991-201323 . Then, this curve is shifted upwards or downwards according to the difference between its 10-year yield and the long-term forecast provided by the OECD.
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The top-left subplot in Figure 8 shows the forecasts for long-term government bond yields for the six countries in my sample. Interest rates are expected to increase by 2022 in all countries, although following different paths. The top-center and top-right subplots in Figure 8 show the expected evolution of the debt-to-GDP ratios until 2022. The OECD forecasts assume that the debt ratios of all countries are expected to fall24 . Importantly, for each country I also show the expected evolution of the debt-to-GDP ratio in the case that these countries increase the maturity of their public debt by one year in 20132015 (in dashed and dotted lines). In the case of France, Italy and Spain, this maturity 21
The simulations are probably underestimating this effect because the Italian and Spanish governments issued debt more frequently than quarterly, the frequency used in the simulation. Thus, the actual exposure to interest rates incorporating sizeable risk premia was higher. 22 The primary deficits correspond to the general government sector instead of the central government debt and deficit concepts included in my analysis. 23 The term premium is measured as the difference between the 10-year and 1-year interest rates. 24 The OECD assumes that all countries in the Euro Area will have a 60% debt-to-GDP ratio by 2030.
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ACCEPTED MANUSCRIPT lengthening would imply reducing their debt ratios by 2, 0.5 and 1.5pp, respectively. In Belgium, Finland and Germany, the effect would be lower than half a percentage point, and in the case of the latter, even slightly negative (i.e. a small increase in the debt ratio). In the first half of 2014, these countries have taken steps towards increasing their public debt maturity and, in the light of these simulations, continuing this policy is expected to lower future debt-to-GDP ratios.
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The bottom row of Figure 8 shows similar simulations under the assumption that interest rates in the Euro Area countries will converge to a single yield curve common to all countries by 2016. I also assume that future long-term yields in EA countries will be equal to those forecasted for France by the OECD and that primary deficits and GDP will be those that this institution predicts for each country. Therefore, the expected impact of extending debt maturity on future French debt-to-GDP ratios is the same as the one shown in the top-row figures. For other countries, the effect of the maturity lengthening is almost null, although Germany would, under this scenario, obtain a slight reduction of its sovereign debt-to-GDP ratio. In the first months of 2014, interest rates in these six EA countries have fallen and yield differentials shrank. In a scenario showing convergence to a very low yield curve, these countries would probably reach relatively higher debt-to-GDP ratios by 2022 as a result of extending debt maturity in 2013-2015.
Estimating the impact of higher inflation
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Section 5 studied past contributions of inflation and other factors to debt-to-GDP dynamics. One of the conclusions drawn was that, in the past, inflation contributed more to bringing down the debt ratio in the Euro Area than in the US. This section estimates the impact of future inflation on the EA debt-to-GDP ratios, based on recent work on the US: Hilscher et al. (2014).
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First, I focus on estimating the effect of a shock that raises inflation by 1pp permanently. Hilscher et al. (2014) interpret this exercise as quantifying the fiscal effect of the Central Bank announcing a permanent increase in its inflation target (as discussed, for instance, in Blanchard et al. (2010) or Krause and Moyen (2013)). A 1% positive shock to inflation that agents know to be permanent would shift the probability distributions that they assign to inflation at all horizons by 1pp. Thus, assuming that this change does not affect the real discounting rate for future payments25 , the nominal rate at which future debt 25
In a model with nominal rigidities, higher distortionary inflation would imply lower output growth and real interest rates. Thus, these estimates would be interpreted as upper bounds to the decrease in the debt burden caused by permanently higher inflation. Moreover, my estimates leave aside whether the real discounting rates could be affected by the reputational implications of this policy change.
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∆
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j=1
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Qjt X Qj − exp(−j · ytj ) t Yt Yt j=1 j=1 J j X j Qt ≈ −∆πt j · exp(−j · yt ) Yt j=1 J J X pjt Qjt X pjt Qjt = −∆πt · · j · PJ j j Y t j=1 pt Qt j=1 j=1 =
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In other words, the impact of 1% higher inflation is approximately equal to 1% times the share (on GDP) of debt that can be actually inflated away times its Macaulay duration26 . Hilscher et al. (2014) show that calculating the effect of the permanent inflationary shock with this approximative formula without using the correct elements in the product would lead to considerably different estimates. For instance, including the average (residual) term-to-maturity to measure the time during which debt can be inflated away instead of duration would lead to overestimating this erosion27 . Moreover, these authors stress that the debt values which can actually be inflated away must exclude inflation-indexed bonds and sovereign debt held by the central bank28 .
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Table 2 shows my estimates of debt-to-GDP reductions resulting from 1% permanently higher inflation (see the column labelled Impact in My estimates). These estimates are also compared with the approximative calculations used in the literature, e.g. Missale and Blanchard (1994) or Aizenman and Marion (2011) (see the column labelled Impact in Basic approximation). I also show measures of the average number of years that debt is exposed to higher inflation –either duration or average (residual) term to maturity– and 26
Macaulay duration is the average term-to-maturity of all future outlays, weighted by their market present value. It also constitutes a measure of the sensitivity of the price of a fixed-income investment to a change in interest rates. PJ ˆj Q 27 t ˆ jt is the nominal (face value) of Average residual maturity is equal to j=1 j · PJ Qˆ j where Q j=1
t
principals to be repaid in j periods (excluding coupons). Duration uses instead the market value of all future outlays (including coupons) and is typically lower than the average residual maturity. 28 Hilscher et al. (2014) also use option prices to construct risk-adjusted probability distributions for inflation at different horizons. Thus, they can also analyse the probability that the market assigns to inflation lowering the fiscal burden significantly. My paper estimates the impact of inflation changes in the debt burden of EA countries under different scenarios without specifying the probability that markets give to these changes. Instead, I am assuming that these are plausible realizations among all possible scenarios that economic agents contemplate when they form (rational) expectations about inflation.
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Table 2: Reduction in debt burden due to permanent higher inflation (data from 2013) Basic approximation Av. Mat Ratio Impact 5.59 74.4 4.2 6.62 83.1 5.5 7.44 105.9 7.9 6.37 54.1 3.4 7.01 84.4 5.9 6.50 51.1 3.3 6.43 124.5 8.0 6.20 99.5 6.2
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My estimates Duration Adj. Ratio Impact 3.31 55.9 1.7 5.76 77.5 4.2 6.10 103.8 6.0 6.00 54.1 3.1 6.09 81.8 4.7 6.00 50.9 2.9 5.35 102.9 5.2 4.91 95.8 4.5
Ratios and Impact are measured as % shares of GDP. Duration and average maturity in years. Adj. Ratio removes inflation-indexed bonds and CB holdings.
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the debt ratios corresponding to both estimates offered. As stressed by Hilscher et al. (2014), the estimated effect for the US is much smaller when it is calculated following Equation 5. The values of Macaulay duration (see the column labelled Duration) and debt ratios without TIPs and Federal Reserve holdings (see the column labelled Adj. Ratio) illustrate the origin of this reduction: the Fed is currently holding a large share of US Federal long-term bonds. Notice that, when this debt-to-GDP erosion is calculated using Equation 5 instead of the product of 1% with average maturity and with all debt obligations, the resulting estimate for the EA changes less than for the US29 . Nevertheless, the main message of Table 2 is that the EA would obtain a reduction in its debt burden 2.5 times higher than the one estimated for the US.
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Belgium stands out as the country that would benefit the most from higher inflation, as it has a large debt ratio with the highest duration. On the contrary, the calculations equal to the product of debt ratios with average term to maturity would point at Italy as the most benefited country, with an expected liquidation of 8%. However, an amount of debt representing over 20% of Italian GDP is held by the Central Bank or consists of inflation-indexed securities and floating rate coupon payments (whose final amounts depend on the evolution of short-term interest rates). Thus, my estimate resulting from applying Equation 5 to securities that can actually be inflated away is only 5.2%. These estimates contribute to the discussion about a higher inflation target for Central Banks. The advantages of this policy change has been discussed by Blanchard et al. (2010) and Krause and Moyen (2013): providing more room for standard monetary policy 29
Total shares of debt held by the Central Bank for each EA country are taken from Bruegel database of sovereign debt holdings, Merler and Pisani-Ferry (2012). Table 2 in the Online Appendix summarizes debt-holder shares in 2013 or the latest date available. Since my dataset is based on information security by security, I can easily exclude TIPs for the US, indexed OAT and BTAN securities for France, and the Italian CCT, BTPi and BTP Italia. CCT securities give flexible rate coupons that will immediately rise with higher inflation. The rest are all inflation-indexed bonds.
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to react to large shocks (increasing the distance to the zero lower bound) and facilitating private and public deleveraging. Although inflation is a random process that cannot be fully controlled by the Central Bank, my framework assumes that this policy would raise inflation expectations at all horizons and reduce the expected real value of future debt payments. This erosion of the real debt burden would be immediately reflected (through higher inflation expectations and interest rates) in a lower current market value of debt. My results suggest that the fiscal burden of highly indebted EA countries like Belgium, France, Italy and Spain can be lowered significantly by permanently higher inflation in the Euro zone. A related question is who will suffer the real losses linked to higher inflation30 . Italian and Spanish residents would face significant losses in the case of higher own-country inflation because they hold close to 65% of their country’s debt. Table 3: Estimated reduction in debt-to-GDP ratio (data from 2013) Temp 1Y 1% π>0 π<0 0.7 -0.7 1.4 -1.4 1.8 -1.9 1.0 -1.1 1.4 -1.5 0.9 -0.9 1.8 -1.9 1.7 -1.7
Temp 5Y 1% π>0 π<0 1.1 -1.2 2.3 -2.4 3.1 -3.3 1.9 -2.0 2.5 -2.6 1.6 -1.6 3.0 -3.2 2.8 -2.9
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Gradual 1% π>0 π<0 1.0 -1.1 2.8 -3.2 4.2 -4.8 2.1 -2.3 3.3 -3.8 2.0 -2.3 3.4 -3.9 2.8 -3.2
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Permanent 1% π>0 π<0 1.7 -1.8 4.2 -4.7 6.0 -6.7 3.1 -3.4 4.7 -5.3 2.9 -3.2 5.2 -5.8 4.5 -5.0
Temp 5Y 2% π>0 π<0 2.2 -2.3 4.6 -5.0 6.1 -6.7 3.7 -4.1 4.9 -5.4 3.0 -3.3 5.9 -6.5 5.5 -5.9
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Finally, Table 3 shows the estimated reduction in the debt-to-GDP ratios under different scenarios of future inflation. The first column shows these estimates for 1% permanently higher and lower inflation (the former was shown already in column 3 of Table 2) . The absolute values of these estimates are similar but those corresponding to negative changes in inflation are higher. This is especially relevant if current low values of inflation in the Euro Area become permanent: the implied increase in the fiscal burden of these countries would be sizeable. Similarly, in the scenarios explored in the following columns, the size of the effect of a negative shock to inflation is always larger than in the case of positive shocks. Thus, current inflation rates in the Euro Area close to zero and very low inflation forecasts should give an alert to governments of EA governments. Similarly, monetary policy should account for the asymmetric fiscal consequences of inflation changes of different signs. The next column Gradual 1% shows the effect of a gradual and permanent increase in inflation. In the first year after the inflationary shock this variable is unaffected, but in the following decade inflation increases 0.1pp every year until a rate 1pp higher is reached and maintained forever. Thus, the large amounts of debt with short- and mediumterm maturity are not exposed to higher inflation and the erosion of the fiscal burden is 30
Debt losses imposed to non-resident bondholders are shown in Table 2 of the Online Appendix.
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The column Temp 1Y 1% shows the impact of an immediate and temporary change of 1pp in the inflation rate that disappears by becoming 0.1pp smaller in each of the next 10 years. My assumption is that nominal yields with different maturities will experience the same change as expected inflation at the corresponding horizon. In the column Temp 5Y 1% the shock starts to die out after keeping during 5 years the inflation rate 1pp higher (or lower) than the currently expected rate. Obviously, the impact estimates in Temp 5Y 1% are higher (in absolute terms) than in the column Temp 1Y 1% because the temporary change in inflation lasts longer. Importantly, the temporary shock in Temp 5Y 1% already produces more than half of the effect of a permanent shock. Thus, transitory shocks to inflation can have a significant impact in the debt burden of EA countries even if they do not last the whole remaining life of outstanding debt.
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Conclusion
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Finally, the column Temp 5Y 2% shows the effect of a shock of the type in Temp 5Y 1% whose size is doubled. In the case of a positive shock, a bigger increase in inflation implies a less-than-proportional extra erosion of the fiscal burden. However, a larger reduction in the inflation rate brings a more-than-proportional increase in the real value of debt (divided by GDP). Thus, the ECB should be aware that periods in which large shifts (positive or negative) in inflation forecasts are plausible constitute a bigger threat for the governments fiscal budget.
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The financial crisis and subsequent Euro debt crisis have increased debt-to-GDP ratios in the Euro Area drastically. As a result, EU leaders and national politicians agreed on the need to monitor the developments in debt ratios so that the necessary measures to guarantee their stability can be taken in a timely fashion. However, the role that debt maturity played (and can play in the future) in EA debt-to-GDP dynamics had received little attention, mainly due to lack of data. My paper has studied these important issues empirically using a unique and original database on bond stocks and yields for six Euro Area countries from 1991 to 2013. Based on the government budget constraint, I calculated past contributions to debt-toGDP dynamics of inflation, returns on debt with different maturities and other factors. I concluded that real returns on long-term debt was the factor that contributed the most to pushing up the debt-to-GDP ratios of EA countries. Moreover, I performed counterfactual simulations to show the evolution of these ratios under a debt maturity structure different from the one historically observed. These exercises illustrated the importance that debt 30
ACCEPTED MANUSCRIPT maturity management had in the years before the introduction of the Euro and during the recent debt crisis. Finally, I estimated that an unexpected increase in inflation can lower significantly the fiscal burden of these countries. Similarly, if the currently observed low inflation persists over the next 5-10 years, fiscal consolidation in these countries will become much more painful as they will give very high real returns to bondholders.
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One possible extension of my work will be to compare debt-to-GDP dynamics for the biggest EA economies and the United Kingdom. More interestingly, my estimates of returns on EA debt with different maturities could be used to test the implications of models of debt management or Faraglia et al. (2013). In their model, if the maturity of government debt is long, then inflation plays a key role in achieving fiscal solvency when an independent authority sets the monetary policy rate optimally. Recently, Berndt et al. (2012) studies the US case and finds that the financing needs raised by government spending shocks were moderated by long-term debt giving lower real holding-returns.
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References Abbas, S. A., Akitoby, M. B., Andritzky, M. J. R., Berger, M. H., Komatsuzaki, M. T., and Tyson, J. (2013). Dealing with high debt in an era of low growth. Number 13-17. International Monetary Fund.
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Abbas, S. A., Belhocine, N., El-Ganainy, A., and Horton, M. (2011). Historical patterns and dynamics of public debt: Evidence from a new database. IMF Economic Review, 59(4):717–742. Abbas, S. A., Blattner, L., De Broeck, M., El-Ganainy, A., and Hu, M. (2014). Sovereign debt composition in advanced economies: A historical perspective. Technical report, International Monetary Fund.
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Aizenman, J. and Marion, N. (2011). Using inflation to erode the us public debt. Journal of Macroeconomics, 33(4):524–541. Angeletos, G.-M. (2002). Fiscal policy with noncontingent debt and the optimal maturity structure. The Quarterly Journal of Economics, 117(3):1105–1131. Berman, J. (2013). The maturity structure of treasury debt: How costly is mismanagement? Yale Journal of Economics.
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Berndt, A., Lustig, H., and Yeltekin, Ş. (2012). How does the us government finance fiscal shocks? American Economic Journal: Macroeconomics, 4(1):69–104.
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BIS (2005). Zero-coupon yield curves: Technical documentation. BIS papers, 25.
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Blanchard, O., Dell’Ariccia, G., and Mauro, P. (2010). Rethinking macroeconomic policy. Journal of Money, Credit and Banking, 42(s1):199–215. Bordon, I. G., Schmid, K. D., and Schmidt, M. (2014). Hypnosis before wake-up call?
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Buera, F. and Nicolini, J. P. (2004). Optimal maturity of government debt without state contingent bonds. Journal of Monetary Economics, 51(3):531–554.
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Campos, C. F., Jaimovich, D., and Panizza, U. (2006). The unexplained part of public debt. Emerging Markets Review, 7(3):228–243. Das, P. (2011). Decomposition of debt-gdp ratio for united kingdom: 1984-2009. Technical report. De Broeck, M. and Guscina, A. (2011). Government Debt Issuance in the Euro Area: The Impact of the Financial Crisis. International Monetary Fund. Eurostat (April 2013). Stock-flow adjustment (sfa) for the member states, the euro area and the eu27 for the period 2009-2012, as reported in the april 2013 edp notification. Technical report, Eurostat. 32
ACCEPTED MANUSCRIPT Faraglia, E., Marcet, A., Oikonomou, R., and Scott, A. (2013). The impact of debt levels and debt maturity on inflation. The Economic Journal, 123(566):F164–F192. Faraglia, E., Marcet, A., and Scott, A. (2008). Fiscal insurance and debt management in oecd economies. The Economic Journal, 118(527):363–386. Giannitsarou, C. and Scott, A. (2008). Inflation implications of rising government debt. In NBER International Seminar on Macroeconomics 2006, pages 393–442. University of Chicago Press.
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Giordano, R., Pericoli, M., and Tommasino, P. (2013). Pure or wake-up-call contagion? another look at the emu sovereign debt crisis. International Finance, 16(2):131–160. Greenwood, R., Hanson, S. G., S., R. J., and Summers, L. H. (2014). Government debt management at the zero lower bound.
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Gürkaynak, R. S., Sack, B., and Wright, J. H. (2007). The us treasury yield curve: 1961 to the present. Journal of Monetary Economics, 54(8):2291–2304. Gürkaynak, R. S., Sack, B., and Wright, J. H. (2010). The tips yield curve and inflation compensation. American Economic Journal: Macroeconomics, pages 70–92.
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Hall, G. J. and Sargent, T. J. (1997). Accounting for the federal government’s cost of funds. Economic Perspectives-Federal Reserve Bank of Chicago, 21:18–28.
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Hall, G. J. and Sargent, T. J. (2011). Interest rate risk and other determinants of post-wwii us government debt/gdp dynamics. American Economic Journal: Macroeconomics, 3(3):192–214.
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Hilscher, J., Raviv, A., and Reis, R. (2014). Inflating away the public debt? an empirical assessment.
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Krause, M. U. and Moyen, S. (2013). Public debt and changing inflation targets. Number 06/2013. Discussion Paper, Deutsche Bundesbank.
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Lojsch, D. H., Rodriguez-Vives, M., and Slavík, M. (2011). The size and composition of government debt in the euro area. Technical report, European Central Bank. Lucas, R. E. and Stokey, N. L. (1983). Optimal fiscal and monetary policy in an economy without capital. Journal of monetary Economics, 12(1):55–93. Ludwig, A. (2014). A unified approach to investigate pure and wake-up-call contagion: Evidence from the eurozone’s first financial crisis. Journal of International Money and Finance, 48:125–146. Lustig, H., Sleet, C., and Yeltekin, Ş. (2008). Fiscal hedging with nominal assets. Journal of Monetary Economics, 55(4):710–727. 33
ACCEPTED MANUSCRIPT Merler, S. and Pisani-Ferry, J. (2012). Who’s afraid of sovereign bonds? Technical report, Bruegel Policy Contribution. Missale, A. and Blanchard, O.-J. (1994). The debt burden and debt maturity. The American Economic Review.
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Reinhart, C. M. and Sbrancia, M. B. (2011). The liquidation of government debt. Technical report, National Bureau of Economic Research.
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A A.1
Data sources United States
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The analysis for the United States relies heavily on Hall and Sargent (2011). I obtain quantities and characteristics of outstanding marketable nominal bonds (i.e. Treasury Bills, Notes and Bonds) from the Center for Research in Security Prices (CRSP) Annual US Treasury Database (2013). Similar data for TIPs (inflation-protected securities) are retrieved from December issues of the US Treasury’s Monthly Statement of Public Debt for 1997-2013. Moreover, series of nominal non-marketable debt are December observations taken from the Treasury Bulletin31 . Finally I price all payments using the nominal and real zero-coupon yield curves computed by Gürkaynak et al. (2007) and Gürkaynak et al. (2010).
Belgium
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Belgostat, the online database of the National Bank of Belgium (NBB), shows the outstanding amounts of Treasury debt by currency and type of instrument: Linear Bonds (also called OLOs), State Notes and classic loans (that pay coupons and have maturity longer than one year), and Treasury Certificates and Bills (that are zero-coupon shortterm debt instruments). However, the annual reports from the Belgian Debt Agency also include significant amounts of Treasury Bonds issued by the Silver Fund as well as small amounts from a recent program designed to attract German investors called Schuldscheine and EMTNs. This paper’s database collects the details for each outstanding OLO, clasic loan and Silver Fund bond available in these reports and uses information about issuances to build a similar description for State Notes32 .
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The Belgian Debt Agency does not publish reports before 1999, however the report corresponding to that year gives a detailed description of the maturity structure of public debt since 198633 . The outstanding amount of debt with each residual maturity is, nonetheless, the sum of debt issued in different dates and therefore it is unclear which coupon rate would correspond to the outstanding principals. The criterion followed is that debt at time t maturing in j periods is the sum of debt issued at time t-1 with maturity j+1 plus (plausibly) new debt maturing after j periods (i.e. issued at time t). In this way, I assign the year of issuance for different tranches of debt with the same residual maturity and 31
Table OFS-1: Distribution of Federal Securities by Class of Investors and Types of Issue. The small amounts of Schuldscheine and EMTNs are not included because their information is incomplete. For simplicity, the total amounts of debt with maturity lower than one year have been included as one security that matures after one year. 33 Table 13 in the report. 32
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In order to price these outstanding payments at different maturities, I use the yield curves estimated by the NBB which are available at the BIS databank since 1997. For 1991-1996, I interpolated and smoothed the average yield-to-maturity rates of OLOs that the NBB makes available at different maturities in Belgostat. Finally, the small difference between the face value of all above-mentioned debt and the gross (nominal) debt officially reported by the Treasury is added directly to the market value of debt resulting from the model.
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Figure 3 in the Online Appendix compares the resulting market value of debt with the Total Liabilities reported by the OECD’s Belgian balance sheet for the central government34 . It also compares the average debt maturity of the data with the average residual maturity from the OECD’s central government database. Although the resulting market values for this country are more different to the official numbers than for other countries, yearly changes in debt maturity are definitely correctly captured.
Finland
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The database of the Finnish State Treasury shows the stocks of debt by currency and type of industry since 2002. Most of this debt is denominated in euros and issued in serial long-term bonds and Treasury Bills, representing around 90% of all debt in securities. Upon request, the Treasury facilitated the stocks and main characteristics (i.e. maturity date and coupon rate) for each end-of-year outstanding serial bond, as well as the average Finnish debt maturity since 199135 .
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In order to price the implied promised payments at different maturities, I use the yield curves published by Bloomberg since 1998. The nominal value of the 10% of debt in securities with unspecified maturity is added to the market value of all promised payments. Figure 3 in the Online Appendix compares the resulting market value of securities with the Liabilities in securities reported by the OECD’s Finnish balance sheet for the central government. It also compares the reported average debt maturity with that coming from the data collected. Both series are well matched and therefore can be reliably used to study the impact of debt maturity changes on debt dynamics since 2002. Finally, changes in debt in instruments other than securities should be taken into consideration in the exercise of decomposing debt-to-GDP changes. The values of liabilities in 34
As I cannot separate debt in securities from other instruments for the complete timespan, I compare with the value of all liabilities in the balance sheet. 35 As a result, the information necessary and available for our model starts in 2002. Differently than for France and Germany, few information available about previous years is not enough to get a good assessment of the debt maturity structure in that period.
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loans and currency have been retrieved from the OECD’s Finnish balance sheet for the central government. It is clear from this balance sheet that the Finnish central government holds assets whose value represents around 50% of the value of all liabilities. Although the returns on these assets imply a significant source or revenue, the model does not include assets holdings. Instead, it is assumed that asset holdings have a maturity structure similar to that of securities. As a result debt returns net of asset returns would be a share of the returns for all securities derived in the model. Values for these shares –capturing the changing ratio of assets to liabilities– are taken also from the OECD’s Finnish balance sheet.
France
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The website of the Agence France Tresor, the French Treasury, makes available since January 1998 the Monthly Bulletins published by this institution. These bulletins contain all the characteristics and quantities of the securities outstanding at the end of the previous month. These securities are zero-coupon one-year bonds (or BTFs), five-year bonds (or BTANs), and long-term bonds (also called OATs). The Treasury also issues floating-rate bonds (TEC 10 OATs pegged to the constant 10-year maturity rate) and inflation-indexed bonds (OATi, for French inflation; and OATiEUR, for Euro Area inflation). Historical series for these indexes are also available in the Treasury’s website. Differently than for the US, there are not estimates available of the yield curve for these special bonds. My approach consists on assuming perfect knowledge of future realizations of these indexes and apply then in the calculation of future promised payouts. As a result, I can price them as any other standard security.
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Moreover, the OECD’s central government database provides the stocks of debt for 19911996 for each type or class of bond. It is therefore possible to make some assumptions to describe their maturity structure in these years. I choose to assume recursively and backwards that the difference in each year between the total stock outstanding for each class of bonds (i.e. BTFs, OATs, etc) and the sum of outstanding bonds in that class whose details (maturity, coupon rate, etc) are included in my database has its origin on bonds issued one year before. Whenever a coupon rate needs to be fixed, the estimated yield-to-maturity corresponding to that issuance period will be assigned. Following this methodology, the share of unknown (and assumed) information about the maturity structure increases when moving further back in time, but the stocks of debt assigned to each class of bond are exactly those reported by the OECD. In order to price these outstanding payments at different maturities, I use the yield curves estimated by the Banque de France (BdF) since the beginning of 1992 until June 2004 available at the BIS databank. For 2004-2013, I interpolated and smoothed the yield 37
ACCEPTED MANUSCRIPT curve estimates offered by Bloomberg. Figure 3 in the Online Appendix shows that the resulting market value of debt and average debt maturity follow closely the Liabilities in securities and average residual maturity reported by the OECD in its Belgian balance sheet for the central government and central government database36 .
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Finally, changes coming from variations in debt in instruments other than securities should be taken into consideration in the exercise of decomposing debt-to-GDP changes. Values for debt in loans, currency and deposits are taken from the Quarterly series of government debt in Eurostat for 2000-2013 complemented with data for 1991-1999 from the OECD’s central government database.
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The website of Bundesbank makes publicly available the estimates of zero-coupon yields for German government bonds performed by this institution since 1973. Therefore, pricing German debt following the methodology of this paper is straightforward. However the quantities and characteristics of each outstanding bond have not been reported to the public. Upon request, the Bundesbank provides the data that allow to construct a complete description of end-of-year outstanding amounts of Bubills, Schatze, Bobls and Bunds auctioned since the end of 2000 and their characteristics37 .
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The German Central Bank also makes available on its website the total nominal stocks of debt (i.e. principal payments promised) for Federal savings notes (with maturities of 1 and 2 years) and Federal Treasury financing papers (maturities of 6 and 7 years). Lacking more detailed information, their nominal value is added directly to the market value of the other securities in the model. Finally, the Federal Debt Agency provides upon request some data on bonds issued by especial funds like Bundesbahn or Treuhandanstalt. Similarly, their nominal value is added directly whenever the stocks, promised coupons, and maturity are not known. Notice also that with each auction the Federal Government retains a certain nominal amount for secondary market operations. In this paper, only the amounts net of own funds have been taken into consideration. Although the detailed information available for Bunds actually goes back to 1997, for 1991-1999 only data on the total nominal stocks for each class of bond were provided by the Federal Debt Agency. Therefore, it is necessary to make some assumptions to describe 36
This database does not cover the years after 2010, therefore the average residual maturity values for 2011-2013 have been completed with data from the Monthly Bulletin of the Treasury, the original source. 37 Bubills –also called Treasury discount paper – have a maturity lower than one year, and Schatze –or Federal Treasury notes– have 2-years maturity. A few Bobls –or Five-year Federal Notes– and Bunds –long-term bonds– are linked to inflation but, since they represent a very small fraction of all issued bonds, I add them with fixed coupons equal to the corresponding spread over an assumed 2% inflation rate.
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the maturity structure of German sovereign bonds since 1991. I choose to assume recursively and backwards that the difference between the total stock for each class of bonds (i.e. Bubills, Schatze, etc) and the sum of outstanding bonds in that class whose details (maturity, coupon rate, etc) are included in my database has its origin on bonds issued one year before. Whenever a coupon rate needs to be fixed, the estimated yield-to-maturity corresponding to that issuance period will be assigned. Following this methodology, the share of information on the maturity structure unknown (and assumed) increases when moving further back in time, but the stocks of debt assigned to each class of bond are exactly those reported by the Federal Debt Agency38 .
Italy
PT
A.6
ED
M
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All promised payments at different maturities have been priced using the zero-coupon yields estimated by the Bundesbank and available both on its website and the BIS databank. Figure 3 in the Online Appendix compares the market value of debt resulting from the model with the Liabilities in securities reported by the OECD’s German balance sheet for the central government39 . It also compares the average maturity of securities of the data with the average residual maturity (before swaps) reported by the Federal Debt Agency in reports. Both series are reasonably matched except for the maturity average at the beginning of the 90’s, the years for which more assumptions were necessary. Finally, in the exercise decomposing debt-to-GDP changes, debt in instruments other than securities should also be taken into consideration. This series is calculated as the difference between Total Liabilities and Liabilities in securities from the OECD’s German balance sheet.
AC
CE
Since June 2000, the Italian Treasury (Tesoro d’Italia) publishes monthly reports with the stocks and main characteristics of each outstanding bond. Moreover, this institution provides annual reports with a government debt breakdown by instrument since 1982 and time series starting around 1980 with data (stocks and characteristics) on the issuance of BOT, BTP and CCT securities, the most frequently used. Combining these sources and assuming that all securities issued were paid not earlier than maturity, I construct a detailed description of the stocks, promised coupons and maturity of end-of-year outstanding bonds since 199140 . 38
Also, the debt of special funds was taken over by the Federal government in 1999, but I include it as central government debt since 1991 because the ESA95 concept of central government is larger than the central state. 39 The values reported start in 1995; for 1991-1994 I assigned 90% of quantities in the general government balance sheet because that is the share of outstanding general government securities issued by the central government subsector in the rest of the 90’s. 40 In 1991-1995, the annual amounts of outstanding CCTs are larger than the sums of CCTs not redeemed and issued after 1990. I used backwards (and recursively) the assumption that annual differences come from securities issued before 1990.
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The securities included are: zero-coupon bonds (called BOTs for short-term debt and CTZs for long-term securities) as well as securities yielding fixed coupons (BTPs) and floating coupons (CCTs, whose coupon rate applies a spread to the yield of the 6-month BOT issuance celebrated immediately before the beginning of the accrual period) or coupons indexed to the Euribor (called CCTeu) issued by the Italian central government in Italian markets. There are also inflation-indexed bonds: BTPi and BTPitalia. Their market value is calculated by discounting principal and coupon payment promises with estimated yields41 . They represent around 95% of all Italian government debt issued in securities; the rest is mainly issued in foreign currency whose nominal value is added to the market value of those denominated in euros.
Spain
CE
A.7
PT
ED
M
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Yield curves estimates for Italy following the Nelson-Siegel methodology can be found in the BIS databank starting in 1995. Note that, in the estimation before 1998q1, Libor and swap data were used instead of data on government bonds. As a result, I used yield curve estimates available in Bloomberg for 1994q4-1997q4. For 1991q4-1994q3, I interpolated and smoothed data on yields to maturity of BOTs and BTPs. The market value of securities calculated with these yield estimates is compared in Figure 3 of the Online Appendix with value of Liabilities in securities reported by the OECD’s Italian balance sheet for the central government since 199542 . Also, residual maturity averages from the OECD’s central government database (until 2010) and Tesoro d’Italia (for recent values) are shown. However, in the exercise decomposing debt-to-GDP changes, debt in instruments other than securities should be taken into consideration. I calculated its value as the difference between the nominal values provided by Banca d’Italia 43 . with the total nominal value of securities reported by Tesoro d’Italia. This debt represents around one fourth of total debt but, since its maturity structure is not specified in the data collected for the paper, its nominal value is simply added to the market value of securities.
AC
Data for Spanish outstanding central government bonds is easily accessible at the Bank of Spain (BdE) website, where Public Debt Market time series at daily frequency are available starting in 1988. The files used in this paper are labelled sald (outstanding amounts for each security) and carv (charateristics of each security: coupon rate, maturity date, coupon frequency, etc). Central State debt in securities is issued in Letras (maturing after 3-18 months), medium-term securities called Bonos (with 2-5 years maturity), and 41
Future coupon payments for flexible rate and indexed bonds is calculated assuming perfect knowledge about future realizations of their rates or indexes of reference. 42 The financial accounts of Italy are also accessible in the database of Banca d’Italia since 1997. 43 Detailed data since 1997 can be found the database The Public Finances, Borrowing Requirement and Debt (TCCE0375 - Gross Central Government Debt Position: by instrument, maturity, currency and residence). For previous values, see the Historical tables Debito delle Amministrazioni pubbliche.
40
ACCEPTED MANUSCRIPT long-terms bonds named Obligaciones (with maturity up to 30 years). To the extent of my knowledge, Spain issued exclusively fixed-rate debt until June 2014 when it started issuing inflation-indexed bonds. Each of these securities is unbundled into coupon and principal payment promises and priced using the zero-coupon yields estimated by the BdE and available at the BIS databank.
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In addition, the Bank of Spain provides data on securities issued by other units also classified as central government: FFPP, FROB, etc. They are stripped and priced also, but their total face value is lower than the quantities reported in Table 12.09 (line 4) of the BdE Statistical Bulletin, therefore the difference is added without specifying its maturity structure44 . The Statistics Bulletin of Tesoro Público, the Spanish Treasury, also reports debt in foreign currency whose face value is also added directly to the market value of securities denominated in euros because its maturity structure is unknown.
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Figure 3 in the Online Appendix compares the model’s value of all securities with the market value of Liabilities in securities reported by the OECD’s Spanish balance sheet for the central government45 . Also, officially reported residual maturity averages from the OECD’s central government database (until 2010) and the Statistics Bulletin from the Spanish Treasury (for recent values) are shown. Both series are reasonably well matched.
AC
CE
PT
ED
M
Finally, the exercise of decomposing debt-to-GDP changes requires values for primary surpluses in 1991-1994 which have been calculated with information from the National Statistical Institute (INE): National Accounts Base 86 (Capacidad o necesidad de financiación + Intereses efectivos). Quarterly data on asset acquisitions is taken from Table 12.05 (line 1) of BdE Statistical Bulletin and the value of debt in instruments other than securities is calculated as Total liabilities minus Liabilities in securities from the OCDE’s balance sheet for Spain.
44
The series in Table 12.09 of the BdE Statistical Bulletin starts in 1994, so values for 1991-1993 have been obtained as the difference of Total securities in Table 21.12 (line 1) and the face value of Bonos, Obligaciones and Valores en monedas distintos del euro (line 12). 45 The financial accounts of Spain are also accessible in the website of BdE.
41