Financial openness, the financial accelerator and sectoral dynamics

REVECO-01190; No of Pages 14 International Review of Economics and Finance xxx (2015) xxx–xxx

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International Review of Economics and Finance journal homepage: www.elsevier.com/locate/iref

Financial openness, the financial accelerator and sectoral dynamics☆ Joonyoung Hur a,⁎, Emmanuel K.K. Lartey b,1 a b

Economic Research Institute, The Bank of Korea, Seoul, South Korea Department of Economics, California State University, Fullerton, CA, United States

a r t i c l e

i n f o

Article history: Received 25 July 2015 Received in revised form 18 November 2015 Accepted 18 November 2015 Available online xxxx JEL classification: E52 F40 F41 Keywords: Financial openness Monetary policy Nontradable inflation Dutch disease

a b s t r a c t This paper studies the role of financial openness and the financial accelerator in the sectoral dynamics generated in a small open economy following capital inflow. The results show that where the financial accelerator exists, capital inflow in response to a foreign interest rate shock ultimately results in intersectoral resource transfer that is favorable to the nontradable sector under different monetary policies; the magnitude of the expansion in the nontradable sector being greater under a higher degree of financial openness. The study also finds that, in comparison to CPI inflation targeting, nontradable inflation targeting is better at mitigating resource transfers toward production of nontradables, and at reducing and stabilizing both nontradable inflation and CPI inflation. Furthermore, the findings suggest that the financial accelerator mechanism matters for the effectiveness of monetary policy in addressing dynamics pertinent to the Dutch disease phenomenon, such that CPI inflation targeting is only effective in such a scenario where the financial accelerator is non-existent, and that nontradable inflation targeting operates more effectively in the absence of the financial accelerator as well. © 2015 Elsevier Inc. All rights reserved.

1. Introduction The recent global financial crisis has reignited the debate about the pros and cons of financial liberalization, with a particular focus on the implications for macroeconomic instability. The finance–growth relationship has been studied extensively, producing a substantial body of evidence which indicates that financial development has a positive and significant effect on economic growth. More developed financial markets, as has been documented, do provide economic agents with a mechanism that allows for hedging, trading and pooling of risk, thereby raising the level of investments and economic growth. An alternative line of thought contends that financial liberalization generates excessive risk taking, increases the propagation of adverse shocks and contributes to boom–bust cycles that hinder economic growth. The maintenance of macroeconomic stability and external competitiveness through relative price movements during periods of massive inflow of capital to emerging market economies is an issue that has featured prominently in the extant literature. One aspect of the literature has centered on how such inflows increase output of tradable goods, lowers the relative price of

☆ The authors are very grateful to Michael Curran for providing invaluable comments. The views expressed herein are those of the authors and do not necessarily reflect the official views of the Bank of Korea. The conventional disclaimer applies. ⁎ Corresponding author at: Economic Research Institute, The Bank of Korea, 39, Namdaemun-ro, Jung-gu, Seoul, South Korea. Tel.: +82 2 759 5647; fax: +82 2 759 5420. E-mail addresses: [email protected] (J. Hur), [email protected] (E.K.K. Lartey). 1 Department of Economics, California State University, Fullerton, 800 N. State College Blvd, Fullerton, CA 92834, United States. Tel.: +1 657 278 7298; fax: +1 657 278 3097.

http://dx.doi.org/10.1016/j.iref.2015.11.006 1059-0560/© 2015 Elsevier Inc. All rights reserved.

Please cite this article as: Hur, J., & Lartey, E.K.K., Financial openness, the financial accelerator and sectoral dynamics, International Review of Economics and Finance (2015), http://dx.doi.org/10.1016/j.iref.2015.11.006

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tradables, and culminates in the reallocation of production factors to the nontradable goods sector. It has been argued that such dynamics are associated with a decline in the export sector, with adverse consequences for economic growth. This is the widely known Dutch disease effects. Numerous empirical studies have been conducted on the relationship between various types of capital inflow and the Dutch disease symptoms. There is, however, a rather limited number of studies that have examined the dynamics generated by capital inflow in small open economies within the context of Dutch disease effects in a dynamic general equilibrium setting. This paper seeks to investigate the role of financial openness and the financial accelerator in such dynamics following capital inflow triggered by external factors. Among the existing scanty research, Lartey (2008b) analyzes the effects of capital inflows on resource reallocation and real exchange rate movements in a small open economy, the results showing that an expansion of the tradable goods sector generated by capital inflows increases the relative price of nontradables and culminates in an appreciation of the real exchange rate, which implies a loss of international competitiveness that is detrimental to the tradable sector. Lartey (2008a) develops a two-sector model of a small open economy to analyze the effects of an increase in capital inflow on resource reallocation and real exchange rate movement under alternative monetary policy rules, and finds that the optimal policy rule in such an economy is characterized by nominal exchange rate flexibility, and somewhat aggressive reaction to nontradable inflation. Another strand of the literature has focused on the interaction of financial market imperfections and capital inflows in emerging market economies. Devereux, Lane, and Xu (2006), for instance, explore how collateral constraints in investment financing for emerging markets and the sensitivity of price levels to fluctuations in exchange rates affect the choice of monetary policy rules in such economies. They observe that the degree of exchange rate pass-through matters for the optimal choice of monetary rule, with nontradable good price stability being preferred under high pass-through, and CPI stability, the optimal choice under delayed pass-through. Cerra, Tekin, and Turnovsky (2009) examine real exchange rate adjustments and sectoral resource movements for alternative forms of foreign transfer into a financially constrained dependent economy. A key element of the model is that the economy has restricted access to international capital markets which allows an examination of the interaction of the economy with international capital markets. They find, inter alia, that transfers directed toward productive uses do generate permanent real exchange rate adjustments in response to sectoral reallocation of productive factors. Lartey (2012) examines the dynamics of nontradable inflation and the properties of monetary policy under different degrees of financial openness following an increase in foreign investment, triggered by a shock to the price of foreign investment. The findings show that higher openness generates a more sensitive response in nontradable inflation, and the optimal monetary policy is characterized by a strong reaction to nontradable inflation, which decreases with openness. This paper develops a small open economy model to examine the impact of a foreign interest rate shock on sectoral dynamics and nontradable inflation under alternative monetary regimes. It is closest in spirit to Cerra et al. (2009) and Lartey (2012), in that it examines dynamics associated with the Dutch disease phenomenon. However, it differs in the following aspects. Foremost, different from Cerra et al. (2009), we consider the dynamics following capital inflow to a financially constrained economy using a dynamic stochastic general equilibrium (DSGE) framework that incorporates sticky prices in the nontradable sector, and an analysis of the role of monetary policy rules. In comparison to Lartey (2012), this paper assesses how the degree of openness matters for the Dutch disease mechanism following negative shock to the foreign interest rate in a model that introduces the financial accelerator mechanism. Following Cerra et al. (2009) and Eicher and Hull (2004), we utilize the elasticity of the external finance premium with respect to a change in the leverage position of entrepreneurs as a proxy for the degree of financial openness. This represents an important feature of the model, such that a higher elasticity represents a higher degree of openness and a lower finance premium. Another contribution the paper makes is that, with the introduction of the financial accelerator mechanism, we are able to capture and compare the dynamics of the model following capital inflow with respect to the Dutch disease phenomenon, with and without the financial accelerator for a given monetary policy stance, which is an analysis that has not been directly considered in the literature. Moreover, we assess the relative effectiveness of CPI inflation targeting vis-a-vis nontradable inflation targeting policy in mitigating price movements and resource transfers that are detrimental to the tradable goods sector, and which have consequences for economic growth.2 The rest of the paper is structured as follows. The next section presents the theoretical framework, and Section 3 discusses the solution and dynamics of the model. Section 4 presents an assessment of the performance of the model in replicating quantitative and qualitative features of a group of emerging economies, and the concluding remarks are given in Section 5. 2. The model 2.1. Households A representative household maximizes its utility function given by

E0

∞ X t¼0

t

β εg;t

" # 1þφ C 1−σ ‘ t − t ; 1−σ 1 þ φ

2 We approach this issue from the standpoint of a policy maker whose goal is to enhance external competitiveness and boost the production of tradable (export) goods in order to promote economic growth.

Please cite this article as: Hur, J., & Lartey, E.K.K., Financial openness, the financial accelerator and sectoral dynamics, International Review of Economics and Finance (2015), http://dx.doi.org/10.1016/j.iref.2015.11.006

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3

where β is the discount factor, Ct is a composite consumption index, ‘t is the labor input, σ N 0 and φ N 0 denote the inverse of intertemporal elasticity of substitution and Frisch labor supply elasticity respectively. The variable εg,t is a general preference shock.3 The consumption index Ct is an aggregate of nontradable good (CN,t) and tradable good (CT,t) given by η   η−1  η−1 n−1 1 1 η η C t ¼ γη C T;t þ ð1−γ Þη C N;t ;

where γ ∈ [0, 1] is the share of tradables and η N 0 is the elasticity of substitution between tradable and nontradable goods. Con1

θ θ1

θ1

sumption of nontradable goods is differentiated, with a sub-index C N ¼ ð∫ 0 C N ðjÞ θ djÞ , θ N 1. The tradable consumption good is a composite of home (CH,t) and foreign (CF,t) tradable goods, " 1

ρh 1 ρ

1

ρh 1 ρ

C T;t ¼ ðγ h Þρh C H;th þ ð1  γh Þρh C F;th

#

ρh ρh 1

;

where γh ∈ [0, 1] is1 the share of domestic tradable goods and ρh N 0. The corresponding price index is P T;t ¼ ½γh ðP H;t Þ1ρh þ ð1  γh ÞðP F;t Þ1ρh 1ρh , where PF ,t is the price of the foreign tradable consumption good and PH,t is the1 price of the domestic tradable 1

1

good. The consumer price index is P t ¼ ½γðP T;t Þ1η þ ð1  γÞðP N;t Þ1η 1η , where P N ¼ ð∫ 0 P N ðjÞ1θ djÞ1θ is the price subindex for the nontradable good and PT is the price of tradable consumption good. The household's choices are subject to a budget constraint represented by the equation, P t C t þ Dt þ ~et Bt þ

ϑ 2  ð~e B Þ ¼ Dt1 r t1 þ ~et Bt1 r t1 ϕt ðat Þ þ W t ‘t þ ΠH;t þ Π F;t þ T t ; 2 t t

ð1Þ

where Dt and Bt denote the household's holding of one-period domestic and foreign bonds, respectively, with corresponding (gross) interest rates rt and r⁎t ; ~et is the nominal exchange rate, and Wt is the nominal wage. ϑ2 ð~et Bt Þ2 is the cost of adjustment for foreign bonds. ΠH,t and ΠF,t denote profits from holding shares in domestic and imported goods firms respectively, and Tt denotes lump-sum transfers. Following Benigno (2009), Kollmann (2002) and Schmitt-Grohé and Uribe (2003), the function ϕt(⋅) is interest rate premium with respect to debt given as h  i ϕt ¼ exp χ at þ εrp;t ; where at ≡

~et1 bt1 pt1 y

is the real foreign debt outstanding expressed in domestic currency as a fraction of domestic steady-state output, and χ is the debt elasticity with respect to the interest rate premium. εrp,t is a risk premium shock that follows  ρ   rp εrp;t ¼  ε rp εrp;t1 =εrp exp σ rp rp;t ; rp;t  Nð0; 1Þ; ε rp is steady-state risk premium. where  The representative household's optimality conditions imply.  η  η C N;t ¼ ð1  γ Þ P N;t =P t C t ; C T;t ¼ γ P T;t =P t Ct

ð2Þ

σ

ð3Þ

λt ¼ P t ‘t =W t

φ

ð4Þ

   λt ~et ¼ E r t βϕtþ1 λtþ1 ~etþ1 =πtþ1

ð5Þ

  λt ¼ E rt βλtþ1 =π tþ1

ð6Þ

λt ¼ C t

3 The specification of a CRRA utility function is inconsequential to the main results of the paper, as Acosta, Lartey, and Mandelman (2009) show that the Dutch disease phenomenon is also realized under Greenwood–Hercowitz–Huffman (GHH) preferences following inflow of remittances, even when they act as private capital inflows.

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where λt is the Lagrange multiplier on the budget constraint and πt = Pt/Pt-1. 2.2. Production sector 2.2.1. Capital goods producers Capital goods are produced in a perfectly competitive environment using a linear technology. Capital producers utilize a fraction of final goods purchased from retailers, It, as inputs and produce efficient investment goods, εi, tIt, which is governed by an investment-specific shock εi , t. They produce new capital goods, Kt + 1, by combining the efficient investment goods and the existing capital stock. Consequently, the law of motion of capital stock is given by K tþ1 ¼ ð1  δÞK t þ εi;t It ;

ð7Þ

where δ is the depreciation rate of capital. We further assume that capital producers pay an adjustment cost in transforming investment goods into new units of productive 2 capital given by κ2 ðKItt  δÞ K t . Hence, the optimization problem for producers of capital goods becomes   2  κ It K  δ Kt ; max Et P t εi;t I t  It  It 2 Kt

ð8Þ

where PKt is the real price of capital. The optimality condition for this decision is given by    I K ¼ 0; Et P t εi;t  1  κ t  δ Kt

ð9Þ

which states that the price of capital equals the marginal adjustment costs. 2.2.2. Tradable sector Tradable good producers purchase the capital stock, Kt+1, from capital goods producers at a given price, PKt , by using both their net worth, Nt+1, and external borrowing denominated in foreign currency as in Céspedes, Chang, and Velasco (2004). Following the costly state verification framework of Bernanke, Gertler, and Gilchrist (1999) and Gertler, Gilchrist, and Natalucci (2007), the cost of external finance is higher than the foreign nominal risk-free rate between t and t + 1, r⁎t . As shown in Bernanke et al. (1999), an external finance premium, S(⋅), depends on the tradable good producers leverage ratio defined as Nt + 1/PKt Kt + 1. In equilibrium, tradable good producers borrow up to the point where the expected marginal external financing cost, Et ft +1, equals an external finance premium over the real risk-free interest rate.4 Accordingly, the optimality condition is given by "

Et f tþ1

! # ~etþ1 rt Ntþ1 ¼ Et S K εrp;t ; ~et πtþ1 P t K tþ1

ð10Þ

with S'(⋅) b 0 and S(1) = 1. The log-linearization of Eq. (10) yields the following expression for the external funds rate:  

  ^ n ^ tþ1 þ ^εrp;t þ Et ^etþ1  ^et þ ψEt p ^kt þ k ^ tþ1 ; Et ^f tþ1 ¼ ^r t  Et π tþ1

ð11Þ

where a hat (ˆ) denotes log deviations from the deterministic steady state and ψ denotes the elasticity of the external finance premium with respect to a change in the leverage position of entrepreneurs. As in Gertler et al. (2007), Eq. (11) implies that the external finance premium over the foreign risk-free rate falls as the amount of tradable good producers collateralized net worth increases. Aggregate net worth of tradable good producers accumulates according to Ntþ1 ¼ νV t þ ð1  ν ÞGt ;

ð12Þ

where ν is the survival rate of tradable good producers so that their expected lifetime is 1/(1 -ν). Vt denotes the net worth of surviving tradable good producers carried over from the previous period and Gt is the transfer that newly established tradable good producers receive from those who die in the previous period. The law of motion of Vt is given by h  i K K V t ¼ f t P t1 K t  Et1 f t P t1 K t  N t ;

ð13Þ

where ft is the ex-post real return on capital held in t, and Et1 f t ¼ Et1 ½SðÞεrp;t1 ~et r t1 =ðπ t ~et1 Þ. 4

See Gertler et al. (2007) for more detailed derivations.

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Combining Eqs. (10), (12), and (13), and deriving the log-linear representation, yields the law of motion for tradable good producers' net worth as    kz kð1  δÞ k k  ^ t þ ^εrp;t1 þ ^et  ^et1 ^zt þ ^t1  p  1 ^rt1  π nf nf n     k k k ^ þψ k1 n ^kt2  ψ ^ t1 : 1 p 1 k  þψ t n n n n

1 ^ ¼ n νf t

where zt is the real marginal productivity of capital, and variables without a time subscript denote steady-state values. Each tradable good producer produces a tradable good, YT,t, according to the technology given by,  1α α Y T;t ¼ K t εa;t ‘T;t ;

ð14Þ

where α is the share of capital in the production function, the variable εa,t is a technology shock, and ‘T;t denotes the labor input in the tradable good sector. Tradable goods are sold in a perfectly competitive market at the price PH,t. Tradable good producers maximize their profits by choosing Kt and ‘T;t subject to the production function ((14)). The optimality conditions for these choices are: αμ t

Y T;t Z ¼ t ; Kt P H;t

ð15Þ

Y T;t W ¼ t; ‘T;t P H;t

ð1  α Þμ t

ð16Þ

where μt denotes the Lagrangian multiplier associated with the production function. 2.2.3. Nontradable sector There is a continuum of monopolistically competitive firms of measure unity, each producing nontradable good with technology Y N;t ðjÞ ¼ εa;t ‘N;t ðjÞ. The optimal choice for labor demand is described by, mct

Y N;t ð jÞ W t ¼ ; ‘N;t ð jÞ P N;t

ð17Þ

where mc ¼ MC P N is the real marginal cost and ‘N;t is the labor input in the nontradable good sector. Following Calvo (1983) and Yun (1996), a fraction of nontradable good producers, θN, cannot update their prices each period. ⁎ ( j), to maximize the expected discounted Thus, firms that are able to reset their price in period t, choose the optimal price, PN,t present value of real profits, " max E0 fPN;t ð jÞg

# λtþs Ωtþs ð jÞ ; ∑ ðβθN Þ P N;tþs s¼0 ∞

s

subject to the demand function "

#ρ  P N;t ð jÞ Y N;tþs ; Y N;tþs ð jÞ ¼ P N;tþs where ρ is the nontradable goods elasticity of substitution and Ωt(j) is the nontradable good producer j’s nominal profit function given as h i s  Ωtþs ð jÞ ¼ πN P N;t ð jÞ  P N;tþs mctþs Y N;tþs ð jÞ: The optimality condition is given by



P N;t ð jÞ ¼

Et ∑∞s¼0 ðβθN Þs λtþs Y N;tþs ð jÞ mctþs ᵨ ; ᵨ  1 Et ∑∞s¼0 ðβθN Þs λtþs Y N;tþs ð jÞπsN =P N;tþs

ð18Þ

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so that the aggregate price is:  1ᵨ 1ᵨ 1ᵨ P N;t ¼ θN πN P N;t1 þ ð1  θN ÞP N;t ;

ð19Þ

where πN is steady-state nontradable good inflation. Combining Eqs. ((18)) and ((19)), and log-linearizing, yields the new Keynesian Philips curve for nontradable goods: ^ N;t ¼ βEt π ^ N;tþ1 þ π

ð1  βθN Þð1  θN Þ d mc t : θN

ð20Þ

2.2.4. Import retailers As in Monacelli (2005), import retailers are assumed to be monopolistic competitors and this is a feature that introduces deviations from the law of one price for imported goods. Solving the retailers' optimization problem gives the following new Keynesian Philips curve for imported goods: ^ F;t ¼ βEt π ^ F;tþ1 þ π

ð1  βθ F Þð1  θ F Þ ^ Ψ F;t þ εcp;t ; θF

ð21Þ

where πF,t is domestic currency import price inflation, θF is the fraction of importing firms that cannot optimally adjust price, and εcp,t is an exogenous cost-push shock. ΨF,t denotes deviations from the law of one price defined as ^ ¼q ^t  ð1  γ Þ^st Ψ F;t where Q t and St are the real exchange rate and terms of trade respectively. 2.3. International risk sharing We assume incomplete asset substitution between domestic and foreign bonds, as in Justiniano and Preston (2010), which yields the uncovered interest rate parity condition given by    

Et λtþ1 P tþ1 r t  rt ~etþ1 =~et ϕtþ1 ¼ 0:

ð22Þ

2.4. Monetary policy The monetary authority sets policy according to the Taylor-type interest rate rule as    1ρr r t rt1 ρr πt λπ Y t λy ~et λde ¼ ;  r r  ~et1 y π

ð23Þ

where λπ, λy, and λde measure the policy responses to inflation, output, and nominal exchange rate growth, respectively. 2.5. General equilibrium The goods market clearing conditions in the domestic economy are: Y T;t ¼ Y N;t ¼ Yt ¼



C H;t þ C H;t þ It ; C N;t ; Y N;t þ Y T;t :

ð24Þ

In addition, the labor market clearing condition is ‘t ¼ ‘N;t þ ‘T;t :

ð25Þ

To close the model, the foreign demand for the domestically produced goods is assumed as 

C H;t ¼

  ω P H;t  Yt ; P t

ð26Þ

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Table 1 Parameter values used for the model dynamics. Parameter β γ γh δ k/n α χ σ φ θN θF η ρr λπ λy λde κ ν yT/y ‘T /‘ ψ: high ψ: low

Description

Value

Source

Discount factor Share of tradables Share of domestic produced tradable goods in consumption Steady state capital depreciation rate Steady-state ratio of capital to net worth Share of capital in the production function Debt elasticity w.r.t. the interest rate premium Inverse intertemporal elasticity of substitution Inverse Frisch Calvo nontradable prices Calvo imported prices Elasticity between home and foreign goods Interest rate rule: AR(1) Interest rate rule: inflation Interest rate rule: output Interest rate rule: exchange rate Capital adjustment cost parameter Survival rate of entrepreneurs Steady state share of output in tradable sector Steady state share of labor in tradable sector Elasticity of the external finance premium w.r.t. firm leverage Elasticity of the external finance premium w.r.t. firm leverage

0.99 0.45 0.4 0.025 2 0.3 0.01 1.2 1.5 0.75 0.5 1.5 0.5 1.5 0.25 0.25 1 0.973 0.5 0.5 0.1 0.05

Lartey (2012) Lartey (2012) Lartey (2012) Schmitt-Grohé and Uribe (2003) Bernanke et al. (1999) Smets and Wouters (2007), prior mean Justiniano and Preston (2010) Justiniano and Preston (2010), prior mean Justiniano and Preston (2010), prior mean Lartey (2012) Justiniano and Preston (2010), prior mean Justiniano and Preston (2010), prior mean Justiniano and Preston (2010), prior mean Justiniano and Preston (2010), prior mean Justiniano and Preston (2010), prior mean Justiniano and Preston (2010), prior mean Hur (2015), prior mean Bernanke et al. (1999) Lartey (2012) Lartey (2012) Bernanke et al. (1999)

where ωN 0 and Y⁎t denotes foreign output.5 3. Model dynamics We obtain a numerical solution for the model by taking log-linear approximations of the equilibrium conditions and applying traditional solution methods following the Sims (2002) gensys algorithm. The solution is of the form xt ¼ GðΘÞxt1 þ M ðΘÞt ; t  Nð0; 1Þ where Θ denotes the vector of structural parameters and xt denotes the vector of variables at time t. We analyze the dynamics of the model economy following an exogenous decline in the foreign interest rate, comparing the impulse responses under two monetary policy regimes; CPI inflation targeting and nontradable inflation targeting. We also compare and contrast the behavior of the economy associated with different levels of financial openness under both policy rules. Furthermore, we examine the role of the financial accelerator for the Dutch disease phenomenon in response to capital inflows, by comparing the dynamics of the model with the financial accelerator to those in a specification without this feature. 3.1. Calibration We calibrate the model at quarterly frequency with choices of parameter values that are roughly consistent with features of a representative emerging market economy. The choice of parameter values for the exercise is summarized in Table 1. The household discount factor β = 0.99, the share of tradables in the consumption basket, γ = 0.45, and the share of domestically produced goods in the tradables consumption index, γh = 0.4. We set the quarterly depreciation rate for capital, δ = 0.025, and gross steadystate inflation rate πss = 1.0085. The steady-state ratio of capital to net worth k/n =2, as in Bernanke et al. (1999), while the gross steady-state risk premium sss = 1.0075, as in Christensen and Dib (2008). We further set α= 0.3, χ = 0.01, σ= 1.2, φ= 1.5, θN = 0.75, θF = 0.5, and η =1.5. The capital adjustment cost parameter κ= 1, and the survival rate of tradable good producers ν = 0.973 are drawn from Bernanke et al. (1999). Following Lartey (2012), we assign yT/y= 0.5 and ‘T =‘ ¼ 0:5. In addition, the risk premium shock autoregressive parameter, ρrp is set to 0.5. For the monetary policy parameters, we assign the following values; λπ = 1.5, λy = 0.25, and λde = 0.25. 3.2. CPI inflation targeting under financial openness Fig. 1 displays the impulse responses under different degrees of financial openness, associated with a CPI inflation targeting regime. In the case of an economy with a higher level of financial openness (ψ = 0.1; solid lines with circles), a decline in the external finance premium following a negative foreign interest rate shock, causes an expansion in capital accumulation as shown by the increase in investment, and consequently an initial boom in output of the tradable (export) sector, which is short-lived. The

5

This demand function is standard in small open-economy models, as in Justiniano and Preston (2010), Kollmann (2002), and McCallum and Nelson (2000).

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output

investment

consumption

5 0 0

8

16

24

0.2

0.2

0

0

−0.2 0

real ER (+: depr., −: appr.) 0

0.4

0.4

10

0.5 0.5

0.6

0.6

1

1

0.8

15

1.5

1.5

nominal interest rate

inflation

8

16

24

0

tradable output

8

16

24

tradable labor

−0.2 0

8

16

24

tradable consumption

8

16

24

nontradable output 1

4

3

0

4

−0.5

3 2

−1 −1.5

1

1

−2

0

0

0

−2.5 0

8

16

24

nontradable labor 1

0

8

16

24

0

nontradable consumption

8

16

24

1

24

real price of capital

8

16

24

8

16

24

external finance premium 0

−1 5

0 0

0

−0.5

−1.5 0

−0.2 16

24

10

0.2

0 8

16

15

0.4

0

8

0.6

2

0

0 0

nontradable inflation

0.8

3

0.5

0.5

2

2

0

8

16

24

0

8

16

24

0

8

16

24

Fig. 1. Impulse responses under different degrees of financial openness associated with the CPI inflation targeting regime: ψ=0.1 (solid lines with circles), ψ=0.05 (solid lines with squares). The x-axis measures quarters.

consumption of both tradable and nontradable goods increase as well. However, there is a movement of resources toward the nontradable sector, as the expansion of output in that sector is sustained, whereas the output of the tradable sector declines. Consumption is therefore biased toward imports and nontradables in response to the boom the economy experiences. The policy stance manages to discourage the consumption of nontradable goods beyond the initial increase, but this increase is quite persistent over the short to medium run. The policy rule, though, is able to lower nontradable goods price inflation and CPI inflation, indicating that the appreciation of the real exchange rate is being driven by nominal exchange rate appreciation due to the capital inflow. The dynamics for the less financially open case (ψ = 0.05; solid lines with squares) is generally identical qualitatively, but less pronounced. Moreover, initially, there is a decline in the consumption of both tradables and nontradables, as well as a drop in the production of nontradable goods. There is therefore, a transfer of resources across sectors in favor of nontradable goods production, and both CPI inflation and nontradable goods price inflation are reduced and stabilized after the initial increase. The dynamics under the more financially open setting is more dramatic due to higher elasticity of the external finance premium with respect to a change in the leverage position of entrepreneurs, which allows greater substitution of foreign funds toward investment finance, thereby generating a larger boom in the economy. Thus the resource reallocation toward the nontradable sector is more amplified in this case, as is the expansion of nontradable output.6 3.3. Nontradable inflation targeting under financial openness Fig. 2 shows the dynamics under nontradable inflation targeting and varying degrees of financial openness. For a more financially open state of the economy (ψ =0.1; solid lines with circles), the negative shock to the foreign interest rate leads to increased investment and capital accumulation and unsustained expansion in the production of tradables. There is an initial decline in consumption of both tradables and nontradables, but both increase subsequently. Tradable sector labor rises on impact of the shock so as to support the temporary expansion in the tradable sector but declines later, whereas nontradable sector labor declines initially but expands 6 Neumeyer and Perri (2005) and Lartey (2008a) use a slightly higher value for the depreciation of capital, so we perform sensitivity analysis with δ=0.044, and find that the amplitude of the impulse responses are moderately minimized without altering the qualitative implications reported in the findings. The results are available upon request.

Please cite this article as: Hur, J., & Lartey, E.K.K., Financial openness, the financial accelerator and sectoral dynamics, International Review of Economics and Finance (2015), http://dx.doi.org/10.1016/j.iref.2015.11.006

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output

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Fig. 2. Impulse responses under different degrees of financial openness associated with the nontradable inflation targeting regime: ψ=0.1 (solid lines with circles), ψ=0.05 (solid lines with squares). The x-axis measures quarters.

thereafter in response to the expansion in the output of nontradables. Nontradable consumption rises faster than output in the sector, which puts pressure on nontradable inflation but the policy rule is effective in stabilizing the price of nontradables, and consequently CPI inflation. There is a resource transfer from the tradable sector to nontradable sector, and a sustained increase in consumption of tradables driven by demand for imports. Under the scenario that the economy is less financially open (ψ = 0.05; solid lines with squares), the dynamics is qualitatively identical, with the impulse responses being less pronounced. Comparing the dynamics for the nontradable inflation targeting rule (solid lines with squares) to that for the CPI targeting rule (solid lines with circles) under the same level of financial openness (ψ= 0.1) as shown in Fig. 3, a notable observation is the moderate responses for all the key variables following the shock to the foreign interest rate under nontradable inflation targeting, indicating that nontradable inflation targeting does better at minimizing macroeconomic fluctuations in a financially open economy under such circumstances. Specific to the symptoms of the Dutch disease, there is resource movement toward the nontradable sector that leads to a sustained increase in the production of nontradable goods to the detriment of the tradable sector in both cases, but to a lesser extent under nontradable inflation targeting. Notably also, nontradable inflation targeting performs better at stabilizing both nontradable inflation and CPI inflation close to the steady state level by moderating the increase in demand for both tradables and nontradables. 3.4. Monetary policy and the role of the financial accelerator Fig. 4 depicts the dynamics for the model without the financial accelerator mechanism (solid lines with squares) in comparison to the case with the financial accelerator (solid lines with circles) under the same level of financial openness (ψ= 0.1) for CPI inflation targeting policy. The impulse responses following a shock to the foreign interest rate show that without the balance sheet effect, there is an expansion in total output accompanied by a decline in total consumption as both tradable and nontradable consumption fall. Tradable output expands whereas nontradable output contracts, reversing the Dutch disease phenomenon associated with capital inflows. CPI inflation targeting, therefore, operates to stabilize both CPI inflation and nontradable goods price inflation in the absence of the financial accelerator feature. Fig. 5 shows the impulse responses for nontradable inflation targeting policy without the financial accelerator mechanism (solid lines with squares) and with the financial accelerator (solid lines with circles). The main finding is that the policy rule Please cite this article as: Hur, J., & Lartey, E.K.K., Financial openness, the financial accelerator and sectoral dynamics, International Review of Economics and Finance (2015), http://dx.doi.org/10.1016/j.iref.2015.11.006

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Fig. 3. Impulse responses associated with the CPI inflation targeting regime (ψ=0.1; solid lines with circles) and nontradable inflation targeting regime (ψ=0.1; solid lines with squares). The x-axis measures quarters.

stabilizes nontradable inflation and CPI inflation whether the financial accelerator is present or not. Moreover, when the financial accelerator is not at work, the policy is more effective in controlling the expansion of the nontradable sector and consequently, prevents the transfer of labor from the tradable sector to nontradable sector. Two important observations stand out here. Firstly, the impulse responses in the presence of the financial accelerator under both policy rules are amplified in consonance with the literature, with the dynamics showing the existence of the Dutch disease effects in spite of the policy rules. However, for any given degree of financial openness, nontradable inflation targeting is associated with stabilization of nontradable inflation and less resource transfer toward the nontradable sector, and hence, outperforms CPI inflation targeting in mitigating Dutch disease effects. Secondly, in the absence of the financial accelerator, CPI inflation targeting is nearly as effective as nontradable inflation targeting in minimizing fluctuations in general and averting resource transfer to the nontradable sector, even though nontradable inflation targeting does better at reducing and stabilizing both nontradable inflation and CPI inflation. Thus, the balance sheet effect is relevant to monetary policy effectiveness in dealing with dynamics associated with the Dutch disease mechanism following a boom initiated by capital inflow. 4. Model fit to the data This section presents a quantitative assessment of the model along two dimensions. First, we compare unconditional moments obtained from data for a group of emerging market economies, to moments based on artificial time series samples generated from simulations of the model. Secondly, we estimate a structural VAR model to assess how well the impulse response functions from the model mimic those based on the data for the countries under consideration, particularly in terms of the variation in the amplitude of the impulse responses across different degrees of financial openness. 4.1. Moments We examine the performance of the model by drawing comparisons with quantitative features of the business cycle in four emerging market economies that operate inflation targeting regimes and exhibit varying degrees of financial openness. We use the properties of the model with the financial accelerator under CPI inflation targeting rule, and address in particular, the model's Please cite this article as: Hur, J., & Lartey, E.K.K., Financial openness, the financial accelerator and sectoral dynamics, International Review of Economics and Finance (2015), http://dx.doi.org/10.1016/j.iref.2015.11.006

J. Hur, E.K.K. Lartey / International Review of Economics and Finance xxx (2015) xxx–xxx

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Fig. 4. Impulse responses under the CPI inflation targeting regime: with financial accelerator mechanism (ψ=0.1; solid lines with circles), without financial accelerator mechanism (ψ=0; solid lines with squares). The x-axis measures quarters.

prediction with respect to the volatility of the main macroeconomic variables: output (GDP), consumption, investment, CPI and the real exchange rate. We also explore the contemporaneous correlation of each of the variables with output. Table 2 shows business cycle statistics for The Czech Republic, South Korea, Mexico and Brazil, and moments from the model.7 We present the standard deviations for GDP, consumption, investment, real exchange rate and CPI, as well as the relative standard deviations of consumption to GDP, and investment to GDP. The model performs best in matching the observed volatility in GDP and CPI for all the countries, replicating the standard deviation for output in South Korea and Brazil. The standard deviation for CPI in Mexico and The Czech Republic are quite close to that of the model as well. The model underpredicts the volatility in investment in comparison to that observed in all of the emerging market economies, but the predicted standard deviation is close to the mean of the standard deviations for the four countries. The model does not do as well is predicting the volatility in the real exchange rate and consumption. However, it delivers an observed feature with respect to the ranking in descending order, of the volatility of the real exchange, investment and consumption in all four countries. It also mimics the greater volatility of output in comparison to inflation for all the countries, and shows a greater volatility of consumption compared to output, which is the case for South Korea and Mexico.8 With respect to the relative standard deviations, the model overpredicts the ratio of the standard deviations of consumption to GDP than the observed ratios for all of the countries. It also overpredicts the relative volatility of investment to GDP than is observed in The Czech Republic, South Korea and Mexico, but underpredicts this ratio for Brazil. Still and all, it does well in matching the mean value of the ratios of the standard deviations of investment to GDP. The estimates also show the contemporaneous correlation coefficient for GDP and each of the other variables. The model does well in matching the consumption–GDP correlation, producing a coefficient that lies within the range of observed values for all four countries, being closest to the estimate for Brazil. The predicted consumption–GDP correlation is also close to the mean of the estimates for 7 These countries were chosen from a list of countries identified as operating inflation targeting regime in Brito and Bystedt (2010). The data is drawn from the Federal Reserve Economic Data (FRED) website. 8 Interestingly, volatility of consumption matches output volatility in Brazil, whereas consumption volatility is lower compared to output volatility in The Czech Republic, the latter providing some evidence for consumption smoothing with financial openness.

Please cite this article as: Hur, J., & Lartey, E.K.K., Financial openness, the financial accelerator and sectoral dynamics, International Review of Economics and Finance (2015), http://dx.doi.org/10.1016/j.iref.2015.11.006

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Fig. 5. Impulse responses under the nontradable inflation targeting regime: with financial accelerator mechanism (ψ=0.1; solid lines with circles), without financial accelerator mechanism (ψ=0; solid lines with squares). The x-axis measures quarters.

the four countries. The same cannot be said for the investment–GDP correlation, as the model produces an estimate lower than those obtained for all the countries, but the coefficient bears the correct sign. The real exchange rate–GDP correlation produced by the model has the correct sign, but is greater than the estimates for each of the countries, and the same is true for the correlation

Table 2 Standard deviations, relative standard deviations and contemporaneous correlation with GDP. Yt denotes GDP; Ct denotes consumption; It denotes investment; RERt denotes real exchange rate; πt denotes CPI inflation. Each series is detrended by the Hodrick–Prescott filter. The parameters employed for the simulation are identical to those used for the model dynamics, except for the autoregressive parameters of the shocks, ρ =0.95. Five shocks are used for the simulation: preference, technology, investment, import cost-push, and foreign interest rate shocks. Shock standard deviations are as follows: σg =2, σa =0.5, σi =1, σcp =0.3, σrp =0.1. ‘Openness index’ is the Chinn-Ito Index of financial openness. ‘IT start’ represent when the country is judged to have begun inflation targeting. ‘Mean’ is the average of the moments for all 4 countries. Country

Czech Republic

South Korea

Mexico

Brazil

Mean

Model

IT start Data span Openness index St.Dev.(Yt) St.Dev.(Ct) St.Dev.(It) St.Dev.( RERt) St.Dev.(πt) St.Dev.(Ct)/St.Dev.(Yt) St.Dev.(It)/St.Dev.(Yt) corr(Ct,Yt) corr(It,Yt) corr( RERt,Yt) corr(πt,Yt)

1998 98:Q1-14:Q4 2.42 1.78 0.91 3.83 6.83 0.99 0.51 2.15 0.52 0.82 0.10 0.3

1998 98:Q1-14:Q4 1.19 1.45 2.01 2.55 7.31 0.78 1.38 1.76 0.79 0.70 0.50 0.19

1999 99:Q1-14:Q3 1.11 1.87 2.30 3.60 5.01 0.94 1.23 1.93 0.96 0.89 0.50 0.02

1999 99:Q1-14:Q3 0.12 1.44 1.43 5.25 9.69 0.89 0.99 3.64 0.70 0.92 0.54 0.03

1.64 1.66 3.81 7.21 0.90 1.03 2.37 0.74 0.83 0.41 0.14

1.45 2.98 3.94 4.13 0.96 2.06 2.72 0.68 0.55 0.82 0.53

Please cite this article as: Hur, J., & Lartey, E.K.K., Financial openness, the financial accelerator and sectoral dynamics, International Review of Economics and Finance (2015), http://dx.doi.org/10.1016/j.iref.2015.11.006

J. Hur, E.K.K. Lartey / International Review of Economics and Finance xxx (2015) xxx–xxx output

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Fig. 6. Impulse responses to U.S. federal funds rate shock: Czech Republic (thick solid lines); South Korea (thin solid lines); Mexico (solid lines with circles); Brazil (solid lines with squares). The x-axis measures quarters.

coefficient for inflation and GDP generated by the model. Nevertheless, the model does well quantitatively on average, in producing moments with features that are generally consistent with empirically observed counterparts in the four countries.9 4.2. SVAR analysis We conduct a structural vector autoregression (SVAR) analysis for the four countries; Czech Republic, South Korea, Mexico and Brazil, drawing from the same data set, and incorporating the federal funds rate as a proxy for a generic foreign interest rate.10 The goal is to assess how well the model replicates some of the dynamics observed in these countries. We focus on the extent to which the amplitude of the impulse response functions will increase with the degree of financial openness, as observed in the dynamics of the model. A structural VAR model is specified and estimated using the standard identification scheme for structural shocks that impose contemporaneous restrictions on their effects in the form of a recursive Cholesky decomposition. The ordering of the variables, and hence the shocks in the recursive structure is as follows: log of federal funds rate, log of investment, log of GDP and log of CPI. Fig. 6 presents orthogonalized impulse responses of the variables following an exogenous shock to the federal funds rate. A shock to the federal funds rate causes an increase in GDP and investment in all four countries, the amplitude of the responses for GDP being highest for the Czech Republic, followed by Mexico, South Brazil and South Korea, in that order. The amplitude of the responses for investment also follows the same ranking order; the highest is observed in the case of the Czech Republic, with Mexico, Brazil and South Korea following in that order. In spite of the observation that the magnitude of these impulse responses does not decrease with decreasing financial openness for the entire group of countries, the results do reflect the prediction of the model when considering only the Czech Republic, Mexico and Brazil, as the amplitude decreases across these three economies from high to low degree of financial openness. Furthermore, when we split the countries into subgroups by level of income per capita, the results are consistent with dynamics of the model, with impulse responses being of greater magnitude in the Czech Republic compared to South Korea, and more amplified in Mexico compared to Brazil. There is limited movement in the CPI in all four countries following the shock. Moreover, there is an initial increase in the CPI for the Czech Republic, Korea and Mexico, whereas a decrease is observed in the case of Brazil, where the CPI exhibits the highest amplitude beyond the impact period. Although these observations do not match those from the theoretical model it terms of having lower amplitude for lower degree of financial openness; in general, they still capture the initial increase and subsequent decrease in CPI inflation over the first few quarters as observed in Fig. 1. An interesting observation also, is that the impulse responses provide evidence for an inflation targeting monetary regime in these countries. 5. Conclusion This paper develops a small open economy model which incorporates the financial accelerator mechanism to examine the extent to which financial openness influences sectoral dynamics that have implications for Dutch disease effects associated with capital inflows. We consider the behavior of the model economy under varying degrees of financial openness following a negative shock to the foreign interest rate. Specifically, we analyze the dynamics under CPI inflation targeting and nontradable inflation targeting regimes for different levels of financial openness, and the differences in dynamics under these monetary regimes for the same degree of financial openness. The results indicate that under higher degree of openness and CPI inflation targeting, the increase in capital inflow following the decline in the foreign interest rate causes an initial increase in the production of tradables, and an increase in consumption of both 9 It is notable that incorporating additional countries (Israel, Poland and South Africa) that are also identified as operating inflation targeting regimes in Brito and Bystedt (2010) does not enhance the performance of the model in matching the moments in the data. Given that there is data limitation in general, we are unable to increase the sample of countries in an attempt to improve the fit of the model. 10 The data spans the same periods as indicated in Table 2. They are listed in decreasing order of openness, as reflected in the Chin-Ito index. Each country's data as well as the U.S. time series are drawn from the Federal Reserve Economic Data (FRED) website.

Please cite this article as: Hur, J., & Lartey, E.K.K., Financial openness, the financial accelerator and sectoral dynamics, International Review of Economics and Finance (2015), http://dx.doi.org/10.1016/j.iref.2015.11.006

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tradables and nontradables. In subsequent periods, however, resources are diverted to the nontradable sector which causes a decline in the tradable sector. The dynamics is different for a less financially open economy, as we observe that there is an initial drop in consumption of both tradables and nontradables and in the production of nontradables but in subsequent periods, there is sectoral resource transfer that favors the nontradable sector. A notable result is that the allocation of labor toward the nontradable sector, and consequently, the expansion in the nontradable sector is more amplified under a higher level of financial openness. The results further show that specific to the symptoms of the Dutch disease, nontradable inflation targeting does better, in comparison to CPI inflation targeting, at mitigating resource transfer toward the nontradable sector. Moreover, nontradable inflation targeting performs better at stabilizing both nontradable inflation and CPI inflation. Furthermore, we find that in the presence of the financial accelerator, the dynamics of the model is more amplified, and that Dutch disease effects exist under CPI inflation targeting, and to a lesser extent under nontradable inflation targeting. Finally, the results show that CPI inflation targeting is effective at averting Dutch disease effects in the absence of the financial accelerator mechanism, as it minimizes resource transfer to the nontradable sector; nontradable inflation targeting, however, is a better alternative particularly at reducing and stabilizing both CPI inflation and nontradable inflation. References Acosta, P. A., Lartey, E. K. K., & Mandelman, F. S. (2009). Remittances and the Dutch disease. Journal of International Economics, 79, 102–116. Benigno, P. (2009). Price stability with imperfect financial integration. Journal of Money, Credit and Banking, 41, 121–149. Bernanke, B., Gertler, M., & Gilchrist, S. (1999). 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Please cite this article as: Hur, J., & Lartey, E.K.K., Financial openness, the financial accelerator and sectoral dynamics, International Review of Economics and Finance (2015), http://dx.doi.org/10.1016/j.iref.2015.11.006