- Email: [email protected]
Financial shocks, comovement and credit frictions
Economics Letters 143 (2016) 20–23
Contents lists available at ScienceDirect
Economics Letters journal homepage: www.elsevier.com/locate/ecolet
Financial shocks, comovement and credit frictions✩ Daria Finocchiaro a,∗ , Caterina Mendicino b a
Sveriges Riksbank, Monetary Policy Department - Research, SE-103 37 Stockholm, Sweden
b
European Central Bank, Directorate General Research, Monetary Policy Research, Sonnemannstrasse 20, 60314 Frankfurt am Main, Germany
highlights • Financial shocks can generate comovement between macro variables and asset prices. • The quantitative implications of different borrowing constraints are evaluated. • The interaction between financial frictions and labor demand is key to the result.
article
info
Article history: Received 16 December 2015 Received in revised form 16 March 2016 Accepted 18 March 2016 Available online 23 March 2016
abstract In models with frictional financial markets, the specification of the borrowing constraint is crucial to generating comovement between macro variables and asset prices after credit shocks. The interaction between financial frictions and labor demand is key to the results. © 2016 Elsevier B.V. All rights reserved.
JEL classification: E32 E44 Keywords: Financial shocks Borrowing constraints Asset prices Comovement
1. Introduction Can financial shocks generate comovement between financial variables and economic activity? Comovement between asset prices and macro variables in response to financial disturbances is the basis of the liquidity shock hypothesis, i.e. a theory which suggests that financial factors are an important source of business cycles through their impact on asset prices. However, Shi (2015) documents puzzling positive effects of negative financial shocks on equity prices in a wide range of models with financial frictions. We argue that in the presence of equity and debt financing, the
✩ This paper was previously circulated as ‘‘Debt, equity and the equity price puzzle’’. We are grateful to Karl Walentin and seminar participants at Sveriges Riksbank for useful comments and suggestions. The opinions expressed in this article are the sole responsibility of the authors and do not necessarily reflect the position of the European Central Bank or of Sveriges Riksbank. ∗ Corresponding author. E-mail addresses: [email protected] (D. Finocchiaro), [email protected] (C. Mendicino).
http://dx.doi.org/10.1016/j.econlet.2016.03.017 0165-1765/© 2016 Elsevier B.V. All rights reserved.
specification of the borrowing constraint is crucial to generating comovement between equity prices and key macro variables in response to financial shocks. In a model that encompasses two popular borrowing constraints, i.e. a la Kiyotaki and Moore (1997) and a la Jermann and Quadrini (2012) (henceforth KM and JQ, respectively), asset prices and consumption fall substantially and persistently in response to a negative financial shock only in JQ. The interaction between the financial friction and the labor market is key to the result. Put simply, in JQ financial shocks are transmitted to the real sector through their effect on both investments and labor demand. When firm’s financing conditions tighten and it is costly to readjust the composition of external funds, the effective cost of labor increases thereby reducing labor demand. This effect on labor demand, absent in KM, strengthens macro-financial linkages. Consumption, employment and investment fall persistently in response to a negative financial shock. Importantly, tighter credit conditions also trigger a stock market crash. In contrast in KM, firms react to the shock by sharply cutting equity payouts, thereby insulating the rest of the economy, including the stock market, from disturbances to their financing conditions.
D. Finocchiaro, C. Mendicino / Economics Letters 143 (2016) 20–23
21
This paper contributes to the growing literature on macrofinancial linkages (see Kiyotaki and Moore, 1997, Bernanke et al., 1999 and Jermann and Quadrini, 2012, among others) by showing that in order to generate an empirical plausible response in the economy to financial factors, the interplay between financial friction and labor market dynamics should not be neglected. Walentin (2014) highlights the importance of limited commitment for the comovement of macro variables and asset prices in response to news shocks, while Christiano et al. (2010), focus on nominal frictions. Our paper’s emphasis is on disturbances which originate in financial markets, i.e. an unanticipated tightening of the collateral constraint. Our results high-light the important role of labor markets in the transmission mechanism of financial shocks.1
Table 1 Parameters’ values.
2. Model
2 φ (dt ) = dt + κ2 dt − d¯ , where d¯ is the steady-state payout target and κ can be interpreted as the degree of rigidity in a firm’s financial structure. Debt is limited by a borrowing constraint (BC )
Consider a discrete time infinite horizon economy populated by firms and households. Firms combine labor and capital to produce the final good. They can finance their activity with both debt and equity, but debt is preferred because it creates a tax shield. There are two sources of financial frictions. (i) firms’ ability to borrow is limited by a borrowing constraint (ii) firms’ financial structure is rigid, i.e. equity payout is subject to quadratic costs. Households are shareholders, consume the final good, supply labor and hold noncontingent bonds issued by the firms. In what follows, we describe in more detail the economic environment.2
Preferences. Households hold both equity shares (s) and noncontingent bonds (b) issued by the firms. They choose consumption (c ) and labor (l) in order to maximize their lifetime utility subject to a budget constraint ∞
β t [ln (ct ) + η ln (1 − lt )]
t =0
st : wt lt + bt −1 (1 + rt −1 ) + st −1 (dt + qt )
− bt − st qt − ct − Tt = 0 where Tt represents a lump-sum tax.3 Technology. The final output is produced by combining labor and capital according to a Cobb–Douglas production function, Yt = kαt −1 lt1−α . Each firm i maximizes its market value for the shareholders subject to the budget constraint and a borrowing constraint max E0
∞
Value
α β υ δ τ κ Ψ
Production technology Discount factor Utility parameter Depreciation rate Tax advantage Equity payout costs Investment adjustment costs
0.360 0.985 1.630 0.025 0.350 0.146 1.728
γ¯ ξ¯ Ω
Financial shock, mean Financial shock, mean Working capital
Source or target
Standard RBC JQ lss ≈ 0.3 Standard RBC JQ JQ Gertler and Karadi (2011) b 0.380 = 3.36 Y 0.163 JQ 0 (KM) or 1 (KM with working capital)
as specified below. Financial frictions. We consider three different specifications for the borrowing constraint (Eq. (3)) JQ : ξt (Et qt +1 kt − bt ) − Yt (kt −1 , lt ) ≥ 0, wt lt qt +1 kt KM : bt + Ω ≤ γt Et , Ω ∈ {0, 1}. 1 + rt (1 + rt ) The first expression specifies an enforcement constraint, where
ξt represents the probability that the lender will recover the full
2.1. Setup
E0
Parameter
3. Financial shocks and equity prices
Λt ,t +1 di,t
t =0
3.1. Calibration
st : Yi,t − wi,t li,t + bi,t − (1 + rt −1 (1 − τ )) bi,t −1
− Ii,t − φ di,t = 0 (1 − δ) ki,t −1 + ϱ Ii,t (i), Kt −1 − ki,t = 0
(1)
bit ≤ BC
(3)
(2)
where Λt ,t +1 = β c ct is the stochastic discount factor. t +1
Investment (Ii ) is subject to adjustment costs in aggregate
capital (K ), ϱ Ii,t , Kt −1
value of capital, kt , in the event of liquidation. Exogenous changes in ξt , i.e. financial shocks, directly affect the effective cost of labor and its demand. Moreover, since both kt and kt −1 , enter the constraint, present investment decisions have an impact on the future tightness of the constraint. This formulation follows Jermann and Quadrini (2012).4 An implicit assumption behind this constraint, is that firms also borrow to cover liquidity mismatches intraperiod.5 Both working capital and intraperiod loans are connected to the production scale, thereby creating a link between labor and financial markets. The second formulation in which Ω = 0 represents a standard collateral constraint a la Kiyotaki and Moore (1997) (KM). Firms’ borrowing capacity is limited to a fraction γt of the liquidation value of capital. When Ω = 1, producers are assumed to pay the wage bill before the realization of revenues (working capital).6 Exogenous movements in γt capture financial shocks in both specifications of the KM constraint.
=
1−
Ψ
2
Ii,t
δ Kt −1
2
−1
δ Kt −1 Iit
Iit and
equity payouts (dt ) are subject to a quadratic adjustment cost,
1 Wasmer and Weil (2004) reach a similar conclusion in a search theoretic model. Zanetti (2015) investigates the effect of financial and labor market frictions. 2 Appendix reports all the first order conditions. 3 Lump sum taxes are used to finance firms’ interest rate deductions.
We calibrate the model to a quarterly frequency, closely following Jermann and Quadrini (2012).7 Our benchmark calibration is reported in Table 1.
4 In Jermann and Quadrini (2012), it is assumed that the liquidation value of capital is kt , rather than qt +1 kt . Our main results are unchanged in a version of the model where qt +1 does not enter the constraint. 5 Specifically, it is assumed that firms need to pay workers, suppliers of investments, shareholders and bondholders before revenues are realized. 6 The literature on the cost channel of monetary transmission provides indirect evidence on the importance of the working capital assumption (see Barth and Ramey, 2000). 7 We chose to calibrate the mean of the financial shock in KM, γ¯ , to target the same debt to quarterly GDP ratio as in JQ. Calibrating γ¯ with flow of funds data on asset and liabilities for the non-financial corporate sector, would result in γ¯ = 0.40, a number roughly close to our benchmark calibration, γ¯ = 0.38.
22
D. Finocchiaro, C. Mendicino / Economics Letters 143 (2016) 20–23
Fig. 1. Responses to a negative financial shock under three alternative specifications for the borrowing constraint.
3.2. Equilibrium responses to financial shocks Fig. 1 displays the impulse responses of key variables to a financial shock under the three alternative formulations for the borrowing constraint.8 In what follows, we discuss the equilibrium dynamics in the three models separately.9 Dynamics in JQ. A negative shock to ξt induces firms to restructure their financing position, by cutting debt and reducing equity payouts. In the presence of rigidities in firms’ financial structure (κ) and investments (Ψ ), firms are forced to reduce both employment and investments. This is better understood by inspecting of the labor demand schedule, wt = 1 − φd (dt ) µt Ylt where φd (dt ) = 1 + κ d − d¯ and µt is the Kuhn–Tucker multiplier on the enforcement constraint, i.e. a measure of financial tightness. The term 1 − φd (dt ) µt creates a labor wedge. The financial shock has a prolonged negative effect on both employment and consumption and thus, on the stochastic discount factor Λt ,t +1 , thereby negatively impacting on asset prices. Both the stock market price, qstock , and the price of capital, qk fall.10 To shed light on the response of qk , it is useful to recall the two equations behind its dynamic
qk,t = µt ξt Et qk,t +1 + Et Λt ,t +1 Ykt + (1 − δ) qk,t +1 − µt +1 Ykt × φd (dt +1 )
an always binding collateral constraint. 10 We refer to the stock market price as the value of the firms normalized by its networth, qstock = q kV−b .
(5)
the demand for capital and the Tobin’s q relation, respectively. Eq. (4) expresses the price of capital as the discounted sum of the expected marginal return of investment. Notably, a future financing tightening (µt +1 ) depresses qk,t since capital investments in t influence the tightness of the constraint tomorrow through its impact on next period production. Eq. (5), documents how firms’ ability to substitute debt for equity, i.e. a decrease in φd (dt ), has a positive effect on qk . Nevertheless, this last channel does not prevail in JQ. Dynamics in KM. The crucial difference between JQ and KM is the absence of a labor wedge linked to the firm’s financing condition. The labor demand schedule now reads Ylt = wt . This implies that rigidities in firm’s financial structure, (κ), do not impact employment or consumption but do impact investment and financial variables. Furthermore, the model shows a disconnect between the real and financial sectors. A financial tightening induces a sizeable reduction in the equity payout, a short-lived and modest dampening in the stock market, and a counterfactual increase in the price of capital and consumption. The demand for capital is as follows
(4)
8 The shock is assumed to be 1% with a persistence of 0.95. 9 The models are log-linearized around the steady state under the assumption of
k
1 , qk,t = It − 1 φd (dt ) 1 − Ψ δk t −1
qk,t
Ykt µt γt Et qk,t +1 + Et Λt ,t +1 + (1 − δ) qk,t +1 . = φd (dt +1 ) (1 + rt )
Intuitively, in KM the financial contraction is followed by a sharp reduction in dividend payouts. Despite the adjustment cost κ , switching source of finance does not impact on the labor market. The decrease in d, has a positive impact on qk through the Tobin’s q equation (Eq. (5)). Moreover, the consumption response
D. Finocchiaro, C. Mendicino / Economics Letters 143 (2016) 20–23
induces only a modest response in the stochastic discount factor. Importantly, a negative response of qk to financial shocks is key to generating feedback effects from asset prices to the rest of the economy through their impact on the collateral constraint. Dynamics in KM with working capital assumption. To further test our assumption about the importance of the interaction between financial frictions and the labor market we augment the standard KM constraint with working capital. The labor demandoptimality Ω φ (dt ) . Working condition now reads: wt = Ylt 1 + µt (1+ r ) d
4. Concluding remarks We evaluate the asset price implications of financial disturbances. We document that a model with a borrowing constraint a la Jermann and Quadrini (2012), can successfully generate comovement across consumption, investment, hours worked and asset prices in response to financial shocks. The key is the interaction between credit conditions and labor demand. We also show that augmenting a standard KM constraint with a working capital assumption enhances the response of macro and financial variables after a financial shock, although the effects are not persistent. In US data, unemployment and debt issuance are negatively correlated. An enforcement constraint a la JQ and the resulting link between labor and financial market, provide a possible explanation for this pattern, suggesting that in a downturn, firms cut on both employment and debt. Appendix
Yt = kαt −1 l1t −α α Ylt = (1 − α) l−α t kt −1 1 Ykt −1 = α l1t −α kα− t −1
with KM constraint
1 ct
Ul = −v
−
Ult U ct
bt + Ω
wt lt 1 + rt
Ylt = wt
qt +1 kt
1 + rt Ω 1 + µt φd (dt ) , (1 + rt )
1
1
1
− E t Λ t ,t + 1 (1 + rt (1 − τ )) , φd (dt ) πt +1 φd (dt +1 ) µt γt Et qk,t +1 Ykt = + E t Λ t ,t + 1 + (1 − δ) qk,t +1 φd (dt +1 ) (1 + rt )
µt = qk,t
≤ γ ζt Et
with JQ constraint
ξt Et qk,t +1 kt − bt − Yt ≥ 0 wt Ylt = 1 − φd (dt ) µt ξt φd (dt ) µt + Λt ,t +1 (1 + rt (1 − τ ))
φd (dt ) 1 =1 φd (dt +1 ) πt +1
qk,t = µt ξt Et qk,t +1 + Et Λt ,t +1 Ykt × + (1 − δ) qk,t +1 − µt +1 Ykt . φd (dt +1 ) References
Households’ first order conditions Uc =
b t −1
− It − φ (dt ) = 0, πt (1 − δ) kt −1 + ϱ (It , Kt −1 ) − kt = 0
Yt − wt lt + bt − (1 + rt −1 (1 − τ ))
t
capital does indeed generate a labor wedge linked to credit market condition that contributes to the decline in the price of capital. With this variation, the model generates a more sizeable response to financial shocks. However, with the exception of debt, all model variables display limited persistence.
23
1 1−l
= wt ,
(1 + rt ) , π t +1 β EUct +1 (dt +1 + qt +1 ) = Uct qt .
Uct = β Et Uct +1
Firms’ first order conditions qk,t ϱ′ =
1
φd (dt ) It ′ ϱ (It , Kt −1 ) = 1 − Ψ −1 δ kt −1 2 Ψ It δ kt −1 ϱ (It , Kt −1 ) = 1 − −1 It 2 δ k t −1 It
Barth, Marvin J. III, Ramey, Valerie A., 2000. The cost channel of monetary transmission, NBER Working Papers 7675, National Bureau of Economic Research, Inc. Bernanke, Ben S., Gertler, Mark, Gilchrist, Simon, 1999. The financial accelerator in a quantitative business cycle framework. In: Taylor, J.B., Woodford, M. (Eds.), Handbook of Macroeconomics, first ed. In: Handbook of Macroeconomics, vol. 1. Elsevier, pp. 1341–1393. (Chapter 21). Christiano, Lawrence, Ilut, Cosmin, Motto, Roberto, Rostagno, Massimo, 2010. Monetary policy and stock market booms, Proceedings—Economic Policy Symposium—Jackson Hole, Federal Reserve Bank of Kansas City, pp. 85–145. Gertler, Mark, Karadi, Peter, 2011. A model of unconventional monetary policy. J. Monetary Econ. 58 (1), 17–34. Elsevier. Jermann, Urban, Quadrini, Vincenzo, 2012. Macroeconomic effects of financial shocks. Amer. Econ. Rev. 102 (1), 238–271. American Economic Association. Kiyotaki, Nobuhiro, Moore, John, 1997. Credit cycles. J. Polit. Econ. 105 (2), 211–248. University of Chicago Press. Shi, Shouyong, 2015. Liquidity, assets and business cycles. J. Monetary Econ. 70 (C), 116–132. Elsevier. Walentin, Karl, 2014. Expectation driven business cycles with limited enforcement. Econom. Lett. 124 (2), 300–303. Elsevier. Wasmer, Etienne, Weil, Philippe, 2004. The macroeconomics of labor and credit market imperfections. Amer. Econ. Rev. 94 (4), 944–963. American Economic Association. Zanetti, Francesco, 2015. Financial shocks and labor market fluctuations, Economics Series Working Papers Number 746, University of Oxford, Department of Economics.
Contents lists available at ScienceDirect
Economics Letters journal homepage: www.elsevier.com/locate/ecolet
Financial shocks, comovement and credit frictions✩ Daria Finocchiaro a,∗ , Caterina Mendicino b a
Sveriges Riksbank, Monetary Policy Department - Research, SE-103 37 Stockholm, Sweden
b
European Central Bank, Directorate General Research, Monetary Policy Research, Sonnemannstrasse 20, 60314 Frankfurt am Main, Germany
highlights • Financial shocks can generate comovement between macro variables and asset prices. • The quantitative implications of different borrowing constraints are evaluated. • The interaction between financial frictions and labor demand is key to the result.
article
info
Article history: Received 16 December 2015 Received in revised form 16 March 2016 Accepted 18 March 2016 Available online 23 March 2016
abstract In models with frictional financial markets, the specification of the borrowing constraint is crucial to generating comovement between macro variables and asset prices after credit shocks. The interaction between financial frictions and labor demand is key to the results. © 2016 Elsevier B.V. All rights reserved.
JEL classification: E32 E44 Keywords: Financial shocks Borrowing constraints Asset prices Comovement
1. Introduction Can financial shocks generate comovement between financial variables and economic activity? Comovement between asset prices and macro variables in response to financial disturbances is the basis of the liquidity shock hypothesis, i.e. a theory which suggests that financial factors are an important source of business cycles through their impact on asset prices. However, Shi (2015) documents puzzling positive effects of negative financial shocks on equity prices in a wide range of models with financial frictions. We argue that in the presence of equity and debt financing, the
✩ This paper was previously circulated as ‘‘Debt, equity and the equity price puzzle’’. We are grateful to Karl Walentin and seminar participants at Sveriges Riksbank for useful comments and suggestions. The opinions expressed in this article are the sole responsibility of the authors and do not necessarily reflect the position of the European Central Bank or of Sveriges Riksbank. ∗ Corresponding author. E-mail addresses: [email protected] (D. Finocchiaro), [email protected] (C. Mendicino).
http://dx.doi.org/10.1016/j.econlet.2016.03.017 0165-1765/© 2016 Elsevier B.V. All rights reserved.
specification of the borrowing constraint is crucial to generating comovement between equity prices and key macro variables in response to financial shocks. In a model that encompasses two popular borrowing constraints, i.e. a la Kiyotaki and Moore (1997) and a la Jermann and Quadrini (2012) (henceforth KM and JQ, respectively), asset prices and consumption fall substantially and persistently in response to a negative financial shock only in JQ. The interaction between the financial friction and the labor market is key to the result. Put simply, in JQ financial shocks are transmitted to the real sector through their effect on both investments and labor demand. When firm’s financing conditions tighten and it is costly to readjust the composition of external funds, the effective cost of labor increases thereby reducing labor demand. This effect on labor demand, absent in KM, strengthens macro-financial linkages. Consumption, employment and investment fall persistently in response to a negative financial shock. Importantly, tighter credit conditions also trigger a stock market crash. In contrast in KM, firms react to the shock by sharply cutting equity payouts, thereby insulating the rest of the economy, including the stock market, from disturbances to their financing conditions.
D. Finocchiaro, C. Mendicino / Economics Letters 143 (2016) 20–23
21
This paper contributes to the growing literature on macrofinancial linkages (see Kiyotaki and Moore, 1997, Bernanke et al., 1999 and Jermann and Quadrini, 2012, among others) by showing that in order to generate an empirical plausible response in the economy to financial factors, the interplay between financial friction and labor market dynamics should not be neglected. Walentin (2014) highlights the importance of limited commitment for the comovement of macro variables and asset prices in response to news shocks, while Christiano et al. (2010), focus on nominal frictions. Our paper’s emphasis is on disturbances which originate in financial markets, i.e. an unanticipated tightening of the collateral constraint. Our results high-light the important role of labor markets in the transmission mechanism of financial shocks.1
Table 1 Parameters’ values.
2. Model
2 φ (dt ) = dt + κ2 dt − d¯ , where d¯ is the steady-state payout target and κ can be interpreted as the degree of rigidity in a firm’s financial structure. Debt is limited by a borrowing constraint (BC )
Consider a discrete time infinite horizon economy populated by firms and households. Firms combine labor and capital to produce the final good. They can finance their activity with both debt and equity, but debt is preferred because it creates a tax shield. There are two sources of financial frictions. (i) firms’ ability to borrow is limited by a borrowing constraint (ii) firms’ financial structure is rigid, i.e. equity payout is subject to quadratic costs. Households are shareholders, consume the final good, supply labor and hold noncontingent bonds issued by the firms. In what follows, we describe in more detail the economic environment.2
Preferences. Households hold both equity shares (s) and noncontingent bonds (b) issued by the firms. They choose consumption (c ) and labor (l) in order to maximize their lifetime utility subject to a budget constraint ∞
β t [ln (ct ) + η ln (1 − lt )]
t =0
st : wt lt + bt −1 (1 + rt −1 ) + st −1 (dt + qt )
− bt − st qt − ct − Tt = 0 where Tt represents a lump-sum tax.3 Technology. The final output is produced by combining labor and capital according to a Cobb–Douglas production function, Yt = kαt −1 lt1−α . Each firm i maximizes its market value for the shareholders subject to the budget constraint and a borrowing constraint max E0
∞
Value
α β υ δ τ κ Ψ
Production technology Discount factor Utility parameter Depreciation rate Tax advantage Equity payout costs Investment adjustment costs
0.360 0.985 1.630 0.025 0.350 0.146 1.728
γ¯ ξ¯ Ω
Financial shock, mean Financial shock, mean Working capital
Source or target
Standard RBC JQ lss ≈ 0.3 Standard RBC JQ JQ Gertler and Karadi (2011) b 0.380 = 3.36 Y 0.163 JQ 0 (KM) or 1 (KM with working capital)
as specified below. Financial frictions. We consider three different specifications for the borrowing constraint (Eq. (3)) JQ : ξt (Et qt +1 kt − bt ) − Yt (kt −1 , lt ) ≥ 0, wt lt qt +1 kt KM : bt + Ω ≤ γt Et , Ω ∈ {0, 1}. 1 + rt (1 + rt ) The first expression specifies an enforcement constraint, where
ξt represents the probability that the lender will recover the full
2.1. Setup
E0
Parameter
3. Financial shocks and equity prices
Λt ,t +1 di,t
t =0
3.1. Calibration
st : Yi,t − wi,t li,t + bi,t − (1 + rt −1 (1 − τ )) bi,t −1
− Ii,t − φ di,t = 0 (1 − δ) ki,t −1 + ϱ Ii,t (i), Kt −1 − ki,t = 0
(1)
bit ≤ BC
(3)
(2)
where Λt ,t +1 = β c ct is the stochastic discount factor. t +1
Investment (Ii ) is subject to adjustment costs in aggregate
capital (K ), ϱ Ii,t , Kt −1
value of capital, kt , in the event of liquidation. Exogenous changes in ξt , i.e. financial shocks, directly affect the effective cost of labor and its demand. Moreover, since both kt and kt −1 , enter the constraint, present investment decisions have an impact on the future tightness of the constraint. This formulation follows Jermann and Quadrini (2012).4 An implicit assumption behind this constraint, is that firms also borrow to cover liquidity mismatches intraperiod.5 Both working capital and intraperiod loans are connected to the production scale, thereby creating a link between labor and financial markets. The second formulation in which Ω = 0 represents a standard collateral constraint a la Kiyotaki and Moore (1997) (KM). Firms’ borrowing capacity is limited to a fraction γt of the liquidation value of capital. When Ω = 1, producers are assumed to pay the wage bill before the realization of revenues (working capital).6 Exogenous movements in γt capture financial shocks in both specifications of the KM constraint.
=
1−
Ψ
2
Ii,t
δ Kt −1
2
−1
δ Kt −1 Iit
Iit and
equity payouts (dt ) are subject to a quadratic adjustment cost,
1 Wasmer and Weil (2004) reach a similar conclusion in a search theoretic model. Zanetti (2015) investigates the effect of financial and labor market frictions. 2 Appendix reports all the first order conditions. 3 Lump sum taxes are used to finance firms’ interest rate deductions.
We calibrate the model to a quarterly frequency, closely following Jermann and Quadrini (2012).7 Our benchmark calibration is reported in Table 1.
4 In Jermann and Quadrini (2012), it is assumed that the liquidation value of capital is kt , rather than qt +1 kt . Our main results are unchanged in a version of the model where qt +1 does not enter the constraint. 5 Specifically, it is assumed that firms need to pay workers, suppliers of investments, shareholders and bondholders before revenues are realized. 6 The literature on the cost channel of monetary transmission provides indirect evidence on the importance of the working capital assumption (see Barth and Ramey, 2000). 7 We chose to calibrate the mean of the financial shock in KM, γ¯ , to target the same debt to quarterly GDP ratio as in JQ. Calibrating γ¯ with flow of funds data on asset and liabilities for the non-financial corporate sector, would result in γ¯ = 0.40, a number roughly close to our benchmark calibration, γ¯ = 0.38.
22
D. Finocchiaro, C. Mendicino / Economics Letters 143 (2016) 20–23
Fig. 1. Responses to a negative financial shock under three alternative specifications for the borrowing constraint.
3.2. Equilibrium responses to financial shocks Fig. 1 displays the impulse responses of key variables to a financial shock under the three alternative formulations for the borrowing constraint.8 In what follows, we discuss the equilibrium dynamics in the three models separately.9 Dynamics in JQ. A negative shock to ξt induces firms to restructure their financing position, by cutting debt and reducing equity payouts. In the presence of rigidities in firms’ financial structure (κ) and investments (Ψ ), firms are forced to reduce both employment and investments. This is better understood by inspecting of the labor demand schedule, wt = 1 − φd (dt ) µt Ylt where φd (dt ) = 1 + κ d − d¯ and µt is the Kuhn–Tucker multiplier on the enforcement constraint, i.e. a measure of financial tightness. The term 1 − φd (dt ) µt creates a labor wedge. The financial shock has a prolonged negative effect on both employment and consumption and thus, on the stochastic discount factor Λt ,t +1 , thereby negatively impacting on asset prices. Both the stock market price, qstock , and the price of capital, qk fall.10 To shed light on the response of qk , it is useful to recall the two equations behind its dynamic
qk,t = µt ξt Et qk,t +1 + Et Λt ,t +1 Ykt + (1 − δ) qk,t +1 − µt +1 Ykt × φd (dt +1 )
an always binding collateral constraint. 10 We refer to the stock market price as the value of the firms normalized by its networth, qstock = q kV−b .
(5)
the demand for capital and the Tobin’s q relation, respectively. Eq. (4) expresses the price of capital as the discounted sum of the expected marginal return of investment. Notably, a future financing tightening (µt +1 ) depresses qk,t since capital investments in t influence the tightness of the constraint tomorrow through its impact on next period production. Eq. (5), documents how firms’ ability to substitute debt for equity, i.e. a decrease in φd (dt ), has a positive effect on qk . Nevertheless, this last channel does not prevail in JQ. Dynamics in KM. The crucial difference between JQ and KM is the absence of a labor wedge linked to the firm’s financing condition. The labor demand schedule now reads Ylt = wt . This implies that rigidities in firm’s financial structure, (κ), do not impact employment or consumption but do impact investment and financial variables. Furthermore, the model shows a disconnect between the real and financial sectors. A financial tightening induces a sizeable reduction in the equity payout, a short-lived and modest dampening in the stock market, and a counterfactual increase in the price of capital and consumption. The demand for capital is as follows
(4)
8 The shock is assumed to be 1% with a persistence of 0.95. 9 The models are log-linearized around the steady state under the assumption of
k
1 , qk,t = It − 1 φd (dt ) 1 − Ψ δk t −1
qk,t
Ykt µt γt Et qk,t +1 + Et Λt ,t +1 + (1 − δ) qk,t +1 . = φd (dt +1 ) (1 + rt )
Intuitively, in KM the financial contraction is followed by a sharp reduction in dividend payouts. Despite the adjustment cost κ , switching source of finance does not impact on the labor market. The decrease in d, has a positive impact on qk through the Tobin’s q equation (Eq. (5)). Moreover, the consumption response
D. Finocchiaro, C. Mendicino / Economics Letters 143 (2016) 20–23
induces only a modest response in the stochastic discount factor. Importantly, a negative response of qk to financial shocks is key to generating feedback effects from asset prices to the rest of the economy through their impact on the collateral constraint. Dynamics in KM with working capital assumption. To further test our assumption about the importance of the interaction between financial frictions and the labor market we augment the standard KM constraint with working capital. The labor demandoptimality Ω φ (dt ) . Working condition now reads: wt = Ylt 1 + µt (1+ r ) d
4. Concluding remarks We evaluate the asset price implications of financial disturbances. We document that a model with a borrowing constraint a la Jermann and Quadrini (2012), can successfully generate comovement across consumption, investment, hours worked and asset prices in response to financial shocks. The key is the interaction between credit conditions and labor demand. We also show that augmenting a standard KM constraint with a working capital assumption enhances the response of macro and financial variables after a financial shock, although the effects are not persistent. In US data, unemployment and debt issuance are negatively correlated. An enforcement constraint a la JQ and the resulting link between labor and financial market, provide a possible explanation for this pattern, suggesting that in a downturn, firms cut on both employment and debt. Appendix
Yt = kαt −1 l1t −α α Ylt = (1 − α) l−α t kt −1 1 Ykt −1 = α l1t −α kα− t −1
with KM constraint
1 ct
Ul = −v
−
Ult U ct
bt + Ω
wt lt 1 + rt
Ylt = wt
qt +1 kt
1 + rt Ω 1 + µt φd (dt ) , (1 + rt )
1
1
1
− E t Λ t ,t + 1 (1 + rt (1 − τ )) , φd (dt ) πt +1 φd (dt +1 ) µt γt Et qk,t +1 Ykt = + E t Λ t ,t + 1 + (1 − δ) qk,t +1 φd (dt +1 ) (1 + rt )
µt = qk,t
≤ γ ζt Et
with JQ constraint
ξt Et qk,t +1 kt − bt − Yt ≥ 0 wt Ylt = 1 − φd (dt ) µt ξt φd (dt ) µt + Λt ,t +1 (1 + rt (1 − τ ))
φd (dt ) 1 =1 φd (dt +1 ) πt +1
qk,t = µt ξt Et qk,t +1 + Et Λt ,t +1 Ykt × + (1 − δ) qk,t +1 − µt +1 Ykt . φd (dt +1 ) References
Households’ first order conditions Uc =
b t −1
− It − φ (dt ) = 0, πt (1 − δ) kt −1 + ϱ (It , Kt −1 ) − kt = 0
Yt − wt lt + bt − (1 + rt −1 (1 − τ ))
t
capital does indeed generate a labor wedge linked to credit market condition that contributes to the decline in the price of capital. With this variation, the model generates a more sizeable response to financial shocks. However, with the exception of debt, all model variables display limited persistence.
23
1 1−l
= wt ,
(1 + rt ) , π t +1 β EUct +1 (dt +1 + qt +1 ) = Uct qt .
Uct = β Et Uct +1
Firms’ first order conditions qk,t ϱ′ =
1
φd (dt ) It ′ ϱ (It , Kt −1 ) = 1 − Ψ −1 δ kt −1 2 Ψ It δ kt −1 ϱ (It , Kt −1 ) = 1 − −1 It 2 δ k t −1 It
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