Macro-prudential policies, the global financial cycle and the real exchange rate

Journal of International Money and Finance 96 (2019) 147–167

Contents lists available at ScienceDirect

Journal of International Money and Finance journal homepage: www.elsevier.com/locate/jimf

Macro-prudential policies, the global financial cycle and the real exchange rate Alice Y. Ouyang a,⇑, Shen Guo b a b

China Academy of Public Finance and Public Policy, Central University of Finance and Economics, #39, S. College Rd., Haidian Dist., Beijing 100081, China China Academy of Public Finance and Public Policy, Central University of Finance and Economics, China

a r t i c l e

i n f o

Article history: Available online 17 May 2019 JEL Classification: E44 F41 F42 Keywords: Macro-prudential policies Global financial cycle Real exchange rate U.S. interest rate Global liquidity Reserve requirement Loan-to-value ratio

a b s t r a c t This paper examines whether a global financial cycle originating from center economies affects the real exchange rates in peripheral economies and to what extent macroprudential policies can isolate peripheral economies from this external shock. We build a dynamic stochastic general equilibrium (DSGE) model to describe how macro-prudential policies mitigate the fluctuations of the real exchange rate in a small open economy in response to external shocks, in which households are subject to liquidity constraints. Using a sample of 37 emerging and small advanced economies, we show that a countercyclical macro-prudential policy implementation is effective in mitigating the fluctuations in the real exchange rates caused by a U.S. interest rate shock. Ó 2019 Elsevier Ltd. All rights reserved.

1. Introduction With the continuous integration of global financial systems, many researchers have argued that there is a global financial cycle comprised of capital flows, asset prices and credit growth, mainly originating from the monetary policy changes of the center economies (Rey, 2015, 2016; Lane and Milesi-Ferretti, 2007; Gourinchas and Jeanne, 2013; Miranda-Agrippino and Rey, 2015; Bruno and Shin, 2015a; Anaya et al., 2017; Adrian et al., 2009; Cetorelli and Goldberg, 2012). They find that a relatively lax monetary environment of center economies tends to increase global liquidity and change the global financial intermediates’ appetite for risk, driving a large-scale cross-border capital flow from low-yielding center economies to highyielding peripheral economies — further causing currency appreciations, credit booms and high asset prices in the capital recipient economies. The combination of high bank leverage and rapid currency appreciation tends to expose the emerging countries toward the risk of capital reversal. Therefore, the growing financial integration has exposed the macroeconomic conditions of peripheral economies to the center economies and made them sensitive to the so-called global financial cycle through cross-border capital flows (Aizenman et al., 2017; Passari and Rey, 2015; Nier et al., 2014; Obstfeld, 2015). The traditional ‘‘trilemma” view of the open economy indicates that flexible exchange rates can insulate periphery economies from the global financial cycle, but Rey (2015) argues that monetary conditions are transmitted from the main financial ⇑ Corresponding author. E-mail address: [email protected] (A.Y. Ouyang). https://doi.org/10.1016/j.jimonfin.2019.05.009 0261-5606/Ó 2019 Elsevier Ltd. All rights reserved.

148

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

center to the rest of the world through gross credit flows and leverage even under the floating exchange rate regime. While this ‘‘dilemma” argument is still widely debated,1 some have also pointed out the rapid appreciation of the currency may also expose the emerging countries toward the risk of subsequent financial crisis (Gourinchas and Obstfeld, 2012; Lund-Jensen, 2012). The observed episodes of financial crisis followed by the rapid exchange rate appreciation arouse the interests in studying the role of the exchange rate as a transmission channel of foreign shocks. Through the traditional trade channel, an exchange rate appreciation may hurt the competitiveness of exports and therefore weaken the domestic economy. Through the financial channel2, which is introduced by Bruno and Shin (2015a, 2015b), an appreciation of local currency can strengthen the balance sheets of domestic borrowers whose liabilities fall relative to assets due to currency mismatches, and further ease domestic financial conditions and expand the credit supply to corporates. But the rapid appreciation of exchange rate may also trigger a subsequent financial crisis because a sudden reversal of the exchange rate induces a turnabout of capital flows. Several recent studies have empirically test the existence of the financial channel. For instance, Hofmann et al. (2016) find the evidence that the currency appreciation against the US dollar lowers emerging market economy (EME) sovereign yields. Kearns and Patel (2016) find that the financial channel can be a significant offset to the trade channel for emerging market economies. This financial channel of currency appreciation entails a link between exchange rates and financial stability, especially for emerging countries with currency mismatches in their balance sheets, which poses a challenge to the policy makers in these countries. It is tempting to let the monetary policy target the exchange rate. However, as Akinci and Queralto (2018) suggest, the desirability of exchange rate targeting monetary policy declines with the degree of balance sheet mismatch due to the conflicts between real exchange rate stability and output stability. This is why some have proposed that we may need other policy instruments — such as macro-prudential policies — to achieve financial stability and let money policy focus on the more traditional macro policy objectives (Aizenman, 2013; Aizenman et al., 2017; Farhi and Werning, 2014; Aoki et al., 2016; Mimir and Sunel, forthcoming). In this paper, we examine the extent to which macro-prudential policies can mitigate the effects of these external shocks on the real exchange rate fluctuations in small open economies. We mainly focus on the macro-prudential instruments associated with financial institutions rather than capital controls. Since the exchange rate is the key variable that links the borrowing capacities of periphery economies to the external financial shocks, a macro-prudential policy successfully abating the exchange rate fluctuations can help strengthen the financial stability in these countries. We study this question from two perspectives. Theoretically, we construct a DSGE model to describe how macroprudential policies affect the fluctuations of the real exchange rate in a small open economy model in which households are subject to liquidity constraints. We consider two types of shocks hitting the economy: one is the world interest rate shock, and the other is the shock to the borrowing constraint. As Mendoza (2002) argues, an exogenous tightening of the borrowing constraint is similar to an exogenous change in the risk premium. Thus, both of these two shocks lead to a rise in the effective interest rates. Faced with a rise in the effective interest rates, households adjust their consumption of tradable goods and non-tradable goods accordingly, causing a decline in the relative price of non-tradable goods and a depreciation of the real exchange rate. The financial channel of the exchange rate works in our model since the depreciation of the exchange rate tightens the households’ borrowing constraints. We consider two macro-prudential policy instruments: a counter-cyclical reserve requirement for foreign funding and a counter-cyclical liquidity requirement for borrowing. The simulation results demonstrate that these two macro-prudential instruments reacting to effective interest rates can dampen the fluctuations in the real exchange rate. The theoretical research examining the impact of macro-prudential policies on macroeconomics fluctuations in DSGE models burgeoned after the 2007 financial crisis. Most of the literature has explored the impact of macro-prudential policies in closed-economy DSGE models (Angeloni and Faia, 2013; Lambertini et al., 2013; Angelini et al., 2014, among others) with a few exceptions. Mendicino and Punzi (2014) explore the effects of dynamic LTV ratio requirements in a two-country model with external shocks. They find that a policy that featured a counter-cyclical LTV ratio that responded to house price dynamics can dampen macroeconomic and financial fluctuations. Aoki et al. (2016) and Mimir and Sunel (forthcoming) show that there is significant welfare gain from combining macro-prudential policies with monetary policies in small open economies in which the external shocks are transmitted through the financial channel. Mendoza (2002, 2010, 2016) and Bianchi et al. (2016) argue that a complex time- and state-contingent optimal macro-prudential policy (i.e., a Pigouvian tax) can improve households’ welfare and prevent the country from a currency crisis. In the theoretical analysis of this paper, we also analyze the impact of macro-prudential policy in an open-economy model. However, we focus on the effectiveness of macroprudential policies on the real exchange rates rather than other economic objectives, such as credit growth, housing prices, and the probability of a crisis. Empirically, we apply a system-GMM estimation, examining whether the monetary policy changes in the U.S. have a significant impact on the emerging economies’ real exchange rates and to what extent the macro-prudential policies can isolate this external shock. Our sample include 37 emerging and small advanced economies over the sample period from 2000Q1 to 2014Q4. We examine the asymmetric effects of monetary tightening and easing shocks from the U.S. and their influences on the effectiveness of macro-prudential policies. We also investigate whether exchange rate regimes make a difference, 1 Some researchers, e.g. Aizenman et al. (2016), Han and Wei (2018), Steiner (2017) and Frankel (2019), argue that the exchange rate flexibility still can lower the sensitivity of developing countries to policy shocks from center economies. 2 The financial channel relates to the broader risk-taking channel of monetary policy, as discussed in Borio and Zhu (2012), Adrian and Shin (2010), Adrian, et al. (2009).

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

149

comparing the effectiveness of macro-prudential policies serving as shock absorbers in fixed and managed floating regimes. Finally, we apply the Jordà (2005) local projections method to a dynamic fixed effects panel model, examining the persistence of the impact of macro-prudential policies on U.S. interest rate shock. In regard to the literature on the empirical studies of macro-prudential policies, most researchers have focused on the impact of macro-prudential policies on the macroeconomic variables, such as credit growth, housing prices and banking risk (Fendog˘lu, 2017; Cerutti et al., 2017a; Ostry et al. 2012; Altunbas et al., 2018; Akinci and Olmstead-Rumsey, 2018, etc.). They did not pay much attention on the fact that macro-prudential policies also may influence real exchange rates through a credit channel by smoothing households’ borrowing constraints. There are several empirical studies related to our work. Zeev (2017) and Edwards and Rigobon (2009) consider capital controls as one of the macro-prudential instruments, and find that capital controls, especially capital inflow controls, can absorb global shocks and moderate the sensitivity of exchange rate to these shocks. Blanchard et al. (2015) and Frankel (2019) find that foreign exchange intervention is effective in stemming exchange rate pressures from global capital flow shocks. Aizenman et al. (2016) report that the peripheral economies’ real effective exchange rate (REER) and exchange market pressure (EMP) are sensitive to the center economies, and exchange rate flexibility and capital control can moderate this connection. These studies again do not examine the effects of bankrelated macro-prudential policies in mitigating the real exchange rate fluctuations caused by a global financial cycle.3 This is the gap we seek to fill with our research. Our paper is organized as follows: In Section 2, we use a theoretical model to describe how macro-prudential policies mitigate the impacts of global financial shocks on the real exchange rate fluctuations in a small open economy; in Section 3, we discuss the data and empirical methodology linking real exchange rates with a global financial cycle as well as macroprudential policies; and in Section 4, we summarize our main findings. The final section concludes. 2. The theoretical model We examine the impact of macro-prudential policies on volatilities of real exchange rates in a modified model from Mendoza (2002). Following Mendoza (2002), households can only borrow up to a percentage of their current incomes measured in units of tradable goods. We extend Mendoza (2002)’s model by introducing financial intermediaries. In our model, the banks obtain deposits solely from foreign countries at the prevailing worldwide interest rate and grant loans to domestic households. The reserve requirement stipulates that banks hold a fraction of the deposits at the monetary authority with no compensation, which generates a wedge between the world-wide interest rate and the domestic lending rate. The model economy is hit by two types of global financial shocks: the world interest rate shock and the borrowing constraint shock. We consider two macro-prudential policy instruments: a counter-cyclical reserve requirement for the foreign funding and a counter-cyclical liquidity requirement for the borrowing. 2.1. Structure of the model We consider a small open economy with two sectors: a tradable goods sector and a non-tradable goods sector. The output of tradable goods is an exogenous endowment Y T . Non-tradable goods are produced using a Cobb-Douglas production function Y Nt ¼ K 1a Lat , where K represents a time-invariant capital stock with a depreciation rate of zero, and L represents labor input. Firms choose labor demand to maximize their profits. At equilibrium, the value of the marginal product of labor equals the real wage:

PNt aK 1a Lta1 ¼ W t

ð1Þ

where PNt denotes the price of non-tradable goods and W t denotes the real wage rate; both of them are measured in units of tradable goods. We assume that purchasing power parity in tradable goods holds, and, therefore, a decline of the relative price of non-tradable goods indicates a depreciation of the real exchange rate. 2.1.1. Households Households consume tradable goods C Tt and non-tradable goods C Nt and supply labor to firms. They maximize an expected lifetime utility that incorporates an endogenous rate of time preference:

E0

1 X t¼0

exp 

t1 X

s¼0

vs

i1r ! h  T N C C t ; C t  HðLt Þ 1

ð2Þ

1r

  h i 1 g g g where C C Tt ; C Nt ¼ xðC Tt Þ þ ð1  xÞðC Nt Þ , HðLt Þ ¼ Ldt =d, and

  n h io ln 1 þ C C Tt ; C Nt  HðLt Þ . The parameter

vt ¼ b

r

denotes the coefficient of relative risk aversion, g determines the elasticity of the substitution between the consumption of tradable goods and non-tradable goods, xindicates the weight of tradable goods in the composite goods and d governs 3 However, Aizenman et al. (2017) do find that macro-prudential policies can help peripheral economies gain some monetary autonomy from the center economies.

150

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

the elasticity of the labor supply. The introduction of the endogenous rate of time preference, v t , has been the standard approach used by prior researchers to close a small open economy. The parameter b determines the sensitivity of the rate of time preferences with respect to changes in consumption and labor supply. Households maximize their lifetime utility subject to the following budget constraints:

C Tt þ PNt C Nt þ RLt Bt1 ¼ Y T þ Pt þ W t Lt þ Bt where Pt 

PNt Y Nt

ð3Þ

 W t Lt represents the profits earned by firms producing non-tradable goods, Bt denotes the households’

loans from banks and RLt represents the interest rate charged by the banks. Note that the loans are denominated in terms of tradable goods. In addition, households have to satisfy a liquidity requirement by which a fraction /t ð0 < /t  1Þ of current expenditures and debt service obligations has to be paid out of current income:

h i Y T þ Pt þ W t Lt  /t C Tt þ PNt C Nt þ RLt Bt1

ð4Þ

Given the budget constraints illustrated in Eq. (3), this liquidity requirement is equivalent to a borrowing constraint that limits debt as a share of current income, Y t :

Bt 

 1  /t 1  /t  T Yt ¼ Y þ PNt Y Nt /t /t

ð5Þ

Note that the borrowing constraint tightens when /t increases. Eq. (5) demonstrates a linkage between the relative price of non-tradable goods and the borrowing capacity. When the relative price of non-tradable goods declines, the output measured in terms of tradable goods drops, which leads to a decline in the borrowing capacity. Households maximize expected lifetime utilities as shown in Eq. (2) subject to budget constraints as shown in Eq. (3) and borrowing constraints as shown in Eq. (5). Thus, the optimal conditions for the households’ problem are:

h 



x C C Tt ; C Nt  HðLt Þ

i r  1þg g1 C C Tt ; C Nt ðC Tt Þ ¼ kt

ð6Þ

h  ir   1þg g1 ð1  xÞ C C Tt ; C Nt  HðLt Þ C C Tt ; C Nt ðC Nt Þ ¼ kt PNt

ð7Þ

h  i r  1  /t C C Tt ; C Nt  HðLt Þ ðLt Þd1 ¼ kt W t þ lt W t /t

ð8Þ

exp ðv t ÞRLt ktþ1 ¼ kt  lt

ð9Þ

where kt denotes the marginal utility of tradable goods, and lt denotes the shadow value of the borrowing constraint. Eq. (7) describes the tradeoff between the consumption of tradable goods and non-tradable goods, and Eq. (8) governs the optimal choice of labor supply. The second term on the right side of Eq. (8) represents the utility gain from additional borrowing capacity by working more. Eq. (9) depicts the optimal conditions for borrowing. Mendoza (2002) argues that the second term on the right side of Eq. (9) reflects the implicit risk premium in the use of foreign debt. We can rewrite Eq. (9) as

 exp ðv t Þ RLt þ

lt

exp ðv t Þktþ1



ktþ1 ¼ kt

ð10Þ

h i where Ret ¼ RLt þ exp ðlvt t Þktþ1 is defined as the effective interest rate that incorporates the implicit risk premium. The effective interest rate increases when the borrowing constraint tightens and therefore

lt rises.

We assume that households are impatient enough so that the steady-state value of exp ðtÞRL is less than one, indicating that the borrowing constraint is binding at the steady state and that the steady-state value of lt is positive. 2.1.2. Financial intermediaries Banks obtain deposits, Dt , from foreign countries at the worldwide interest rate, Rt , and grant loans to domestic households at a lending rate of RLt . The reserve requirement stipulates that banks would hold a fraction, st , of the deposits at the monetary authority with no compensation. We further assume that banks held no excess reserves. Assuming there is free entry in the banking industry, the profits of the banks would be driven to zero, indicating that

RLt ð1  st Þ ¼ Rt

ð11Þ

The introduction of the reserve requirement generates a wedge between the worldwide interest rate and the domestic lending rate. We assume that Rt follows an AR(1) process: Rt ¼ ð1  qR ÞR þ qR Rt1 þ et , where R is the steady-state value of Rt , qR indicates the persistence in the interest rate and et represents shocks to worldwide interest rate.

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

151

2.1.3. Macro-prudential policies We consider two macro-prudential policy instruments: a counter-cyclical reserve requirement for the foreign funding and a counter-cyclical liquidity requirement for the borrowing. First, we assume that the monetary authority adjusts the required reserve rate following this rule:





st ¼ qs st1 þð1  qs Þ s  d Ret  Re



ð12Þ

where qs denotes the inertia in required reserve ratio adjustments, srepresents the steady-state value of st , and d > 0 denotes the reaction of the required reserve ratio to the global liquidity, measured by the deviation of the effective interest rate from its steady state level Re . When the global liquidity shrinks, a worldwide interest rate hike or an exogenous tightening of the borrowing constraint triggers an increase in the effective interest rate, and therefore a decline in the required reserve ratio. Second, we assume that the liquidity requirement follows this rule:

   /t ¼ q/ /t1 þð1  q/ Þ /  c Ret  Re þ nt

ð13Þ

where q/ denotes the inertia in liquidity requirement adjustments, /represents the steady-state value of /t , and c > 0 measures the reaction of the liquidity requirement to the global liquidity. According to the macro-prudential rule specified in Eq. (13), when the global liquidity shrinks, an increase in the effective interest rate triggers a relaxation of the liquidity requirements. nt represents shocks to exogenous borrowing constraints. A positive realization of this shock could replicate the conditions of the taper tantrum in 2013. Despite the fact that there was no lift-off from zero lower bound in the U.S., emerging economy countries faced large swings in capital outflows and their exchange rates. 2.1.4. Equilibrium Equilibrium in the goods market requires that the production of non-tradable goods is equal to households’ consumption of non-tradable goods, Y Nt ¼ C Nt , and the output of tradable goods must equal the domestic consumption of tradable goods and net exports, Y T ¼ C Tt þ NX t . 2.1.5. Solution of the model Mendoza (2002) assumes that the liquidity constraint in Eq. (4) is only occasionally binding and solves his model nonlinearly. We instead assume that the liquidity constraint is always binding under all circumstances. This assumption allows us to solve the model linearly. 2.2. The calibration and simulations 2.2.1. Calibration of parameters We borrow values of most parameters from Mendoza (2002), in which the model is calibrated to match data from Mexico. Some parameters do not have counterparts in Mendoza (2002) and we calibrate them as follows. We set the steady-state required reserve ratio to 0.14, consistent with the average reserve requirement across developing countries since 1975, as reported by Federico et al. (2014). To determine the value of qR , we run an AR(1) regression of a measurement of the worldwide interest rate – we discuss the construction of this indicator later in Section 3.2.1 – and find that the inertia in this rate is 0.93. Following Lambertini et al. (2013), we set the value of qs and q/ to 0.75, indicating a high inertia in macro-prudential policy adjustments. In the simulations, we choose various values for d andc, measuring the macro-prudential policy reaction to the global liquidity, to examine the impact on the volatilities of real exchange rates. Table 1 reports the value of all parameters. 2.2.2. Responses to worldwide interest rate shocks Fig. 1 demonstrates the impulse responses of selected macroeconomic variables to a positive worldwide interest rate shock under different assumptions regarding the reaction of the reserve requirement to the amount of global liquidity, assuming no change in the liquidity requirementðc ¼ 0Þ. All the responses are shown as a percentage of deviation from the steady states. We first analyze the circumstance without macro-prudential policy (d ¼ 0 and c ¼ 0Þ as shown by the solid lines in Fig. 1. When the world real interest rate increases, banks need to raise their lending rates to cover the rising funding costs. Faced with borrowing constraints, households have to cut their domestic consumption of tradable goods and increase net exports to cover the rising interest payments. This adjustment generates a collapse in the relative price of non-tradable goods and, therefore, a depreciation in the real exchange rate. As shown in Fig. 1(f), the consumption of non-tradable goods also drops slightly: on one hand, according to Eq. (1), a decline of the relative price of non-tradable goods lowers the real wage in terms of tradable goods, which lowers the incentive of workers to supply labor to non-tradable goods production; on the other hand, according to the second term in Eq. (8), households have incentives to work more because the extra income enhances their borrowing capacities, which moderates the negative effect of declining wages on labor supply. When the first factor dominates the second one, the labor supply declines and so does the output of non-tradable goods. The liquidity requirement in Eq. (5) magnifies the responses to the shock. As the relative price and output of non-tradable goods declines, the shrinking income in terms of tradable goods tightens the borrowing constraints and forces households to

152

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167 Table 1 Parameter values used in our theoretical model. Parameter

Description

Value

a

Labor share Tradable endowment Sensitivity of time preferences regarding consumption and labor supply Elasticity of substitution between tradables and non-tradables Elasticity of labor supply Weight of tradable goods in the composite goods Coefficient of relative risk aversion Time invariant capital stock Steady-state worldwide real interest rate Liquidity requirement at steady state Required reserve ratio at the steady state Inertia in the world-wide interest rate Inertia in the macro-prudential policies

0.364 1 0.027 0.316 2 0.342 2 1 1.016 0.74 0.14 0.93 0.75

YT b

g d

x r K R /

s qR qs ; q/

reduce their consumption of tradable goods relative to the case with perfect credit markets. A decline in the consumption of tradable goods leads to a further collapse in the relative price of non-tradable goods and a depreciation of the real exchange rate. As shown by lines with circles and stars in Fig. 1, a counter-cyclical reserve requirement policy suggests that monetary authorities should lower the required reserve ratio for the bank deposits when the rise in the worldwide interest rate boosts the effective interest rate. A decline in the required reserve ratio allows banks to make more loans from a certain amount of deposits, which partially offsets the rising funding costs and the rise of the bank lending rate. In addition, a comparison of lines with circles and lines with stars indicates that a stronger reaction of the reserve requirement to the effective interest rate leads to a lower increase in the bank lending rate, and, therefore, lowers declines in the relative price of non-tradable goods and the real exchange rate. As demonstrated by lines with circles and stars in Fig. 2, a counter-cyclical liquidity requirement policy means that the liquidity requirement would react negatively to the effective interest rate. A drop in the liquidity requirement allows households to finance a greater fraction of current expenditures and debt service obligations by borrowing, and, therefore, it mitigates the tightening of borrowing constraints caused by the rise in the world real interest rate and ensuing depreciation in the real exchange rate. As a result, under the model with counter-cyclical macro-prudential rules, the declines in the consumption of tradable goods and the relative price of non-tradable goods are muted, as is the depreciation of the real exchange rate. Furthermore, as a comparison of lines with circles and lines with stars indicates, the stronger the reaction of the liquidity requirement to the effective interest rate, the less impact the global liquidity shocks have on the relative price of non-tradable goods and the real exchange rate.

2.2.3. Responses to borrowing constraint shocks Fig. 3 demonstrates the impulse responses of selected macroeconomic variables to a positive borrowing constraint shock under different assumptions regarding the reaction of the reserve requirement to the effective interest rate. We first analyze the circumstance without macro-prudential policy (d ¼ 0 and c ¼ 0Þ as shown by the solid lines in Fig. 3. When a positive borrowing constraint shock hits the economy, households have to cut their debts by lowering their domestic consumption of tradable goods and increasing net exports. This adjustment generates a collapse in the relative price of non-tradable goods and, therefore, a depreciation in the real exchange rate. The shrinking income in terms of tradable goods further tightens the borrowing constraints and forces households to reduce their consumption of tradable goods. It is interesting to note that the tightening of borrowing constraint raises the effective interest rate even though the worldwide interest rate is fixed. As shown by lines with circles and stars in Fig. 3, a counter-cyclical reserve requirement policy suggests that monetary authorities should lower the required reserve ratio for the bank deposits, which lowers the domestic bank lending rate. The decline in the lending rate lowers households’ interest payments and allows them to cut less consumption of tradable goods, resulting in a less depreciation in the real exchange rate. Furthermore, as shown by Fig. 3(d), a less exchange rate depreciation mitigates the tightening of the borrowing constraint and leads to a less increase in the effective interest rate. We also consider a counter-cyclical liquidity requirement policy that requires the liquidity requirement react negatively to the effective interest rate. As demonstrated by lines with circles and stars in Fig. 4, when a positive exogenous borrowing constraint shock pushes up the effective interest rate, authorities conducting macro-prudential policies should ease the liquidity constraint on households correspondingly to counteract the tightening borrowing constraint caused by external shocks. In sum, the model simulation predicts that both counter-cyclical reserve requirements and liquidity requirements could ease the impact of global liquidity shocks on the real exchange rates. However, they work with different mechanisms: counter-cyclical reserve requirements manage to cushion the impact of global liquidities by adjusting domestic borrowing costs, while counter-cyclical liquidity requirements succeed in mitigating the tightening of the borrowing constraints.

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

153

Fig. 1. Responses to a worldwide interest rate shock with countercyclical reserve requirement. Note: The solid lines: reserve requirement does not react to effective interest rate (d = 0); the lines with circles: the reserve requirement reaction to effective interest rate is set to 10 (d = 10); the lines with stars: the reserve requirement reaction to effective interest rate is set to 20 (d = 20). The vertical axes are percentage deviations from the steady state.

2.2.4. The impacts of macro-prudential policies To clearly show the extent to which the counter-cyclical macro-prudential policies tame the responses of the domestic macroeconomic variables, we simulate the model with various assumptions on macro-prudential policies and report the

154

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

Fig. 2. Responses to a worldwide interest rate shock with countercyclical liquidity requirement. Note: The solid lines: liquidity requirement does not react to effective interest rate (c = 0); the lines with circles: the liquidity requirement reaction to effective interest rate is set to 0.1 (c = 0.1); the lines with stars: the liquidity requirement reaction to effective interest rate is set to 0.2 (c = 0.2). The vertical axes are percentage deviations from the steady state.

standard deviations of selected variables in Fig. 5. The first row shows the standard deviations of these variables in the economy where the reserve requirement responds to worldwide interest rate shocks for different values of d ðkeeping c ¼ 0Þ. The second row shows the standard deviations of real exchange rate, output, and effective interest rate in the economy where the liquidity requirement reacts to worldwide interest rate shocks with different values of c ðkeeping d ¼ 0Þ.

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

155

Fig. 3. Responses to a borrowing constraint shock with countercyclical reserve requirement. Note: The solid lines: reserve requirement does not react to effective interest rate (d = 0); the lines with circles: the reserve requirement reaction to effective interest rate is set to 10 (d = 10); the lines with stars: the reserve requirement reaction to effective interest rate is set to 20 (d = 20). The vertical axes are percentage deviations from the steady state.

Correspondingly, the third and fourth row in Fig. 5 illustrate the standard deviations of selected variables when the macroprudential policy reacts to borrowing constraint shocks by adjusting reserve requirement and liquidity requirement, respectively. In each subfigure, we also plot the results for different values of parameter g that governs the elasticity of the substitution between tradables and non-tradables: the solid lines denote the benchmark case where g ¼ 0:316; the lines

156

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

Fig. 4. Responses to a borrowing constraint shock with countercyclical liquidity requirement. Note: The solid lines: liquidity requirement does not react to effective interest rate (c = 0); the lines with circles: the liquidity requirement reaction to effective interest rate is set to 0.1 (c = 0.1); the lines with stars: the liquidity requirement reaction to effective interest rate is set to 0.2 (c = 0.2). The vertical axes are percentage deviations from the steady state.

with circles represent the case in which g ¼ 0:5; the lines with stars show the results for g ¼ 2. Fig. 5 shows that the stronger the reaction of the liquidity requirement or reserve requirement to the global liquidity measured by the effective interest rate, the lower the standard deviations of real exchange rate, output, and effective interest rate, and this result is not sensitive to the value of g.

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

157

Fig. 5. Standard deviations and different macroprudential policies. Note: The first row: reserve requirement reacts to interest rate shock. The second row: liquidity requirement reacts to interest rate shock. The third row: reserve requirement reacts to borrowing constraint shock. The fourth row: liquidity requirement reacts to borrowing constraint shock. The solid lines: the elasticity of substitution between tradables and non-tradables g is set to 0.316. The lines with circles: g is set to -0.5. The lines with stars: g is set to 2.

3. Empirics 3.1. Empirical model To investigate whether our theoretical findings are supported by the real data, we examine how the real exchange rates in peripheral economies respond to a world interest rate shock, and to what extent macro-prudential policies can act as shock absorbers. The model specification is as below.

158

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

  US US Drerit ¼ qDrerit1 þ b1 Dit þ b2 Dit  DMPP it þ b3 DMPPit þ cX it þ ai þ eit

ð14Þ

where Drer it represents the change of the CPI-based bilateral real exchange rate of the U.S. dollar against the domestic currency. rer it is expressed as a logarithm. A rise in its value indicates the appreciation of the domestic currency against the U.S. dollar. The lagged value of the real exchange rate change, i.e. Drerit1 , is used to capture the momentum effect of US

real exchange rate change. The symbol Dit represents the change of U.S. federal funds rates, acting as the proxy of the world interest rate shock illustrated in our theoretical model. Both effective federal funds rate and the so-called ‘‘shadow federal funds rate4” are used in our paper. To check the robustness, we also use an U.S. monetary policy shock series ðMPSUS t Þ, constructed by Coibion (2012), to identify exogenous U.S. monetary policy shocks since the variation of federal funds rate may be largely driven by endogenous responses to the US business cycle and not exogenous. This exogenous monetary policy shock is constructed following the narrative approach of Romer and Romer (2004). DMPP it is a dummy variable (+1, 0, 1), constructed based on the aggregate macro-prudential index in Cerutti et al. (2017b), showing the changes in the intensity of macro-prudential policy implementation in that quarter, with +1 indicating a relatively tight policy, 1 indicating a relatively loose policy, and 0 indicating no policy change.5 Macro-prudential policy itself may have affected the real exchange rate by changing the direction of capital flows due to a portfolio rebalancing effect or a policy spillover effect. The interaction term of a change of in the U.S. interest rate and the macro-prudential policy implementation is used to examine whether a counter-cyclical macro-prudential policy implementation is effective in stemming the real exchange rate fluctuations caused by the world interest rate shock. The estimated coefficient for the interaction term should be negative if a counter-cyclical macro-prudential policy is effective. For example, we expect to find that a relatively loose macro-prudential circumstance (i.e., DMPP it equals 1) can at least offset part of the currency depreciation pressure in the emerging economies caused by the tightened monetary policy in the U.S. (for instance, a ‘‘taper tantrum”). ai is a country fixed effect to capture any non-time varying country specific condition; and eit is the error term. X it represents a group of control variables that also may have influenced real exchange rates. We use real GDP per capita (expressed as a logarithm) ðrgdppcit Þ to capture the Balassa-Samuelson effect — that high-income countries tend to have higher productivity growth in tradable sectors which spill over the higher wages to non-tradable sectors, resulting in real exchange rate appreciation. Stronger real GDP growth ðDrgdpit Þ may indicate a good economic fundamental and attract more capital flow into the economy, appreciating the real exchange rate. The change of trade openness (expressed as a logarithm) ðDTradit Þ influences the real exchange rate through both income and substitution effects, so the direction of the influence remains mixed. In general, openness to trade tends to depreciate the real exchange rate through the substitution effect but appreciates the currency through the income effect.6 Finally, we use the change of the implied volatility of the S&P 500 index options (expressed as a logarithm) ðDVIX t Þ to control for the global financial uncertainty originating from external shocks other than the U.S. monetary policy changes. 3.2. Data and methodology We employ a two-step system-GMM (Arellano and Bover, 1995; Blundell and Bond, 1998) to estimate Eq. (14) since the estimation using OLS with country fixed effects may lead to biased results due to the presence of a lagged dependent variable and country fixed effects. Also, one common concern in reduced-form regressions is the existence of endogeneity among explanatory variables, in particular the implementation of macro-prudential policies in our case. A movement of the real exchange rate may induce capital flows, change the level of domestic credit and influence financial authorities’ intentions to conduct a corresponding macro-prudential policy. However, we believe that the endogeneity bias will not be a large problem in our estimation since GMM technique mitigates some of these concerns given that the macro-prudential policy variable as well as other variables that may have endogeneity problems, such as real GDP growth and real GDP per capita, are all treated as endogenous in our model.7 Those endogenous regressors are instrumented with their lags for the difference equation and with lags of their first differences for level equation. Our empirics are based on a quarterly data set of 37 countries (including 28 emerging economies and 9 small advanced economies), covering the sample period from the first quarter of 2000 through the fourth quarter of 2014. The sample economies and the country classifications (based on the information at the last quarter in 2014) are listed 4

Wu and Xia (2015) employ a nonlinear term structure model to estimate the monetary stance for an economy operating with an interest rate near zero. Please refer to Sections 3.2.1 and 3.2.2 for the detail explanation for identification of world interest rate shocks and the macro-prudential index, respectively. 6 Openness to trade tends to reduce the price for tradable goods and hence substitutes the demand from non-tradable to tradable goods and lowers the price for non-tradable goods. The positive income effect resulting from the reduction in the prices of the tradable goods will increase the demand for both tradables and non-tradables and push up prices for non-tradables (Edwards, 1988). Using a sample of emerging economies in Asia from 2000 to 2009, Jongwanich and Kohpaiboon (2013) find that the income effect dominated the substitution effect so that trade openness was positively related to the real effective exchange rate. 7 Using Two-step system GMM, we treat all the explanatory variables but the change of U.S. interest rate, trade openness and VIX as endogenous. Time fixed effect is also included as IV. Those endogenous regressors are instrumented with their lags and with lags of their first differences. The lower and upper limits of lag are 2 and 4, respectively. The orthogonal deviations transform is used as well. 5

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

159

in Table 2. Among these, 27 economies adopt a managed floating regime, 7 are firm fixers, and the rest are floaters.8 Trade openness is the total value of exports and imports over GDP. Most of the data are taken from the IMF International Financial Statistics (IFS) and World Development Indicator (WDI) database. VIX is the change of the implied volatility of the S&P 500 index options, taken from the Chicago Board Options Exchange’s (CBOE) website. Real exchange rate, effective federal funds rate, trade openness and VIX are seasonally adjusted using ARIMA X12.9 The summary statistics for all the variables are shown in Table 3.10

3.2.1. Identification of world interest rate shocks We use the change of the conventional effective federal funds rate and the shadow federal funds rate, estimated by Wu and Xia (2015), to proxy the world interest rate shocks illustrated in our theoretical model. The shadow rate can be used to identify the stance of U.S. unconventional monetary policy while the effective rate has been driven to near zero since the end of 2008. Fig. 6 shows that the Fed managed and continuously loosened its monetary stance from 2009 to mid-2014 by buying a large amount of government bonds and other financial assets – even though the effective federal funds rate was near zero and could fall no more. Anaya et al. (2017) emphasize that unconventional monetary policies also can result in an international portfolio flow through the portfolio balance channel, the risk-taking channel, and the signaling channel.11 To capture the effect of the unconventional monetary policies, we replace the U.S. effective federal funds rate with the shadow rate starting from 2009. Both federal funds rates are taken from Federal Reserve Bank of Atlanta’s website.12 Besides, some may question the validity of using the change of U.S. federal funds rates directly to measure the world interest rate shocks since they may be largely influenced by the U.S. business cycle, which is against our theoretical assumption that the determination of world interest rates is an exogenous process. Hence we also use the exogenous monetary policy shock series constructed by Coibion (2012) to act as a proxy of the world interest rate shocks. They follow the narrative approach of Romer and Romer (2004) to identify innovations to monetary policy excluding anticipatory effects related to economic conditions at each FOMC meeting (referred to as R&R monetary policy shock hereafter). The quarterly R&R monetary policy shock is measured by summing the orthogonalized innovations from each meeting within a quarter, and is updated to the last quarter of 2011 in Coibion et al. (2016).

3.2.2. Macro-prudential index With respect to the intensity of macro-prudential policy implementation, we use a new cross-country macro-prudential policy database constructed by Cerutti et al. (2017b). This database contains the change in the intensity in the usage of nine commonly-used prudential tools during the sample period from 2000 to 2014 at a quarterly frequency for 64 economies. Each prudential tool has an index recording the changes in that policy tool with +1 indicating tightened policies in a given quarter and 1 denoting loosened policies in a given quarter (and 0 denotes unchanged policies). The index is not limited to ±1 if the tool is used more than once in the same quarter. We use the aggregate macro-prudential index (i.e. MPPit ), which is the sum of the indices from the nine tools, to capture the stance of tightness (or looseness) of the macro-prudential policy implemented in the economy.13 Cerutti et al. (2017b) further regroup the nine tools into five prudential instruments: capital buffer (BUFFER), concentration limits (CONC), interbank exposure limits (IBEX), loan-to-value ratio limits (LTV) and reserve requirements (RR). The detail definition and the frequencies of these five prudential instruments can be found in Tables 4 and 5, respectively. We can see that the reserve requirement is the most commonly used instrument in our sample, followed by loan-to-value ratio limit and capital buffer. It is worth noting that reserve requirements have sometimes been used as one of monetary policy instruments. To avoid the confusion, Cerutti et al. (2017b) include the policy change in the database only if the reserve requirements are used to achieve macro-prudential objectives rather than monetary policy ones. While interbank exposure and concentration limits are mainly used to manage banks’ balance sheet, capital requirements, LTV ratio and reserve requirements are found to have significant influences on credit growth, leverage and housing prices (Lim et al., 2011; Bruno et al., 2017). 8 We classify the exchange rate regimes into three categories based on the course classification of Ilzetzki et al. (2017). We identify the country as having a fixed regime if its course classification code in Ilzetzki et al. (2017) is 1, a managed floating regime if the code is 2 or 3, and a floating regime otherwise. 9 We do not apply ARIMA X12 to other variables either due to negative values, such as real GDP growth, shadow federal funds rate and the U.S. monetary policy shock, or annual data, such as real GDP per capita. 10 We exclude two outliers that the real exchange rate depreciates over 50%, i.e. Argentina at 2002Q1 and 2014Q1. These outliers are below ten times of the standard deviation from the sample mean. 11 While the portfolio balance channel predicts that investors will rebalance their portfolios and ultimately affect the allocation of assets across countries due to the crowding out effect on private investments in a Fed purchase of US treasury bills, the signaling channel suggests that capital will flow toward high-yield emerging economies if the Fed’s measures are interpreted as keeping future interest rates low for a longer period than expected. Discussion of the risk-taking channel can be found in our introduction. 12 The average value of the monthly interest rates in a given quarter is used as our quarterly data. 13 It is worth noting that these indices do not capture the actual magnitude of policy changes, so they should be used with caution when making crosssectional comparisons.

160

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

Table 2 Sample classification. Advanced Economies (9)

Emerging Economies (28)

Fixed (7) Managed Floating (27)

Hong Kong Czech Republic, Iceland, Israel, South Korea, New Zealand, Singapore, Taiwan

Floating (3)

Australia

Bulgaria, Croatia, Kuwait, Lebanon, Romania, Saudi Arabia Argentina, Brazil, Chile, China, Colombia, Hungary, India, Indonesia, Malaysia, Mexico, Mongolia, Nigeria, Peru, Philippines, Poland, South Africa, Thailand, Turkey, Uruguay, Vietnam Russia, Ukraine

Table 3 Summary statistics. Variable

Obs.

Mean

Std. Dev.

Min

Max

rer it Drerit DiUS t (Effective) DiUS t (Shadow) MPSUS t rgdppcit Drgdpit DTradeit DVIX t MPP it DMPPit BUFFERit CONC it IBEX it LTV it RRit

2218 2218 2218 2218 1775 2218 2190 2117 2179 2218 2218 2218 1558 1378 2218 2218

4.6868 0.0036 0.0868 0.1359 0.0010 9.0921 0.0440 0.0008 0.0069 0.0803 0.0649 0.0361 0.0135 0.0080 0.0158 0.0140

0.2963 0.0434 0.4750 0.4957 0.3615 1.0228 0.0410 0.1106 0.2171 0.6392 0.4240 0.2558 0.1260 0.0968 0.1757 0.5231

3.0841 0.3494 1.5568 1.7267 0.9982 6.6354 0.1959 1.2767 0.4023 6 1 3 1 1 1 6

5.6339 0.1929 0.7582 1.0000 0.9470 10.9022 0.3081 1.0715 0.8734 5 1 3 1 1 1 5

Fig. 6. A comparison of the U.S. effective and shadow federal funds rates. Note: The data shows the interest rate on the last business day of the month, taken from the Federal Reserve Bank of Atlanta’s website.

4. Results 4.1. Baseline results We employ a two-step system-GMM to estimate Eq. (14). While the Hansen J test of over-identifying restrictions is used to test the validity of the instruments, the Arellano-Bond first-order and second-order serial autocorrelation tests are used to test the moment conditions. We cannot reject the null that the instruments are valid for all the cases as well as the null of no

161

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167 Table 4 The definition of macro-prudential instruments. Instruments

Tools

Definition

BUFFER

General Capital Requirement SSCB—Real Estate Loans SSCB—Consumer Loans SSCB—Other Loans Concentration limits Interbank Exposures Loan-to-value Ratio limits RR—Foreign Currency RR—Local Currency

Requires banks to finance a larger fraction of these exposures with capital and the implementation of Basel capital agreements, including a general capital requirement index and three sector specific capital buffer indices

CONC IBEX LTV RR

Limits banks’ exposures to specific borrowers or sectors Limits banks exposures to other banks Limits on loans to residential borrowers Reserve requirement on foreign currency-denominated accounts Reserve requirement on local currency-denominated accounts

Note: SSCB stands for sector specific capital buffer and RR for reserve requirements. All the definitions are taken from Cerutti et al. (2017b).

Table 5 The use frequency of the macro-prudential instruments.

Tight

No Change Loosened

Value

BUFFER

CONC

IBEX

LTV

RR

10 5 4 3 2 1 0 1 2 3 4 5 6

0 0 0 2 8 73 2128 5 3 1 0 0 0 2,220

0 0 0 0 0 23 1535 23 0 0 0 0 0 1,560

0 0 0 0 0 12 1367 1 0 0 0 0 0 1,380

0 0 0 0 0 52 2151 17 0 0 0 0 0 2,220

1 1 2 0 39 102 1961 76 32 4 1 0 1 2,220

Total Note: Authors’ calculation.

second-order autocorrelation. Table 6 presents the estimates of Eq. (14) and summarizes the results on the impact of the world interest rate shock — originating from the U.S. monetary policy changes — on the emerging economies’ real exchange rate against the U.S. dollar. We use an interaction term of the U.S. interest rate and a prudential indicator to investigate whether the macro-prudential policies can mitigate the effect of this shock. The estimated coefficients of b1 are all negative and statistically significant, indicating that a tightening U.S. monetary policy (i.e., a rise of the U.S. interest rate) tends to depreciate the emerging economies’ currency against the U.S. dollar, consistent to the global financial cycle hypothesis. The results also suggest that a counter-cyclical macro-prudential policy is effective in mitigating the real exchange rate fluctuation caused by the external shock since the estimated coefficients of b2 are all negative and statistically significant as well. The results are robust no matter which measure of U.S. federal funds rate is used, indicating that both conventional and unconventional monetary policies have a significant impact on emerging economies’ real exchange rates, and the counter-cyclical macro-prudential policies serve as a cushion. As a robustness check, we re-estimate Eq. (14) by using the exogenous U.S. monetary policy shock (i.e. R&R monetary policy shock). The results are consistent to the previous findings. 4.2. U.S. tightening versus U.S. easing It is interesting to assess the asymmetric policy effects in monetary tightening and easing, and to what extent this asymmetric effects influence the response of real exchange rates to a world interest rate shock. For example, Han and Wei (2018) argue that peripheral countries with flexible exchange rates follow interest rate decreases in the central country, but not interest rate increases. This argument may suggest a stronger real exchange rate response in periphery economies to a monetary contractionary shock than an expansionary shock from the center country.  To examine this question, we use two dummy variables, Dþ t and Dt , to identify U.S. monetary policy tightening and easþ ing, respectively. Dt takes a value of one if the change of federal funds rates (or monetary policy shock) is positive and zero þ otherwise. D t ¼ 1  Dt . The results in Table 7 show that both U.S. contractionary and expansionary shocks have significant impacts on the real exchange rates, but the relative magnitude is ambiguous depending on which shock measures are used. If

162

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

Table 6 The effectiveness of macro-prudential policies serving as real exchange rate shock absorbers. Dependent Variable ¼ Drer it

DiUS t ¼ Effectiv e rate Drerit1

DiUS t  DMPP it

0.419*** (0.0239) 0.00314*** (0.000540) –

DMPPit

–

DTradeit

0.136*** (0.0164) 0.00266 (0.00169) 0.134*** (0.0128) 0.0642*** (0.00383)

0.553*** (0.0179) 0.00891*** (0.00102) 0.0243*** (0.00329) 0.00495 (0.00469) 0.108*** (0.0247) 0.000037 (0.00317) 8.63e-05 (0.0261) 0.0692*** (0.00382)

2022 37 575 0.000023 0.167 1.00

2022 37 807 0.000017 0.116 1.00

DiUS t

rgdppcit

Drgdpit DVIX t Observations Number of id Instrument number Ar(1) Test (p-value) Ar(2) Test (p-value) Hansen J Test (p-value)

US

DiUS t ¼ Shadow rate 0.414*** (0.0243) 0.00536*** (0.000430) –

DiUS t ¼ MPSt 0.585*** (0.0143) 0.0170*** (0.00116) –

0.134*** (0.0156) 0.00273* (0.00146) 0.143*** (0.0129) 0.0658*** (0.00396)

0.490*** (0.0135) 0.0131*** (0.00112) 0.0259*** (0.00371) 0.00168 (0.00505) 0.0941*** (0.0158) 0.000535 (0.00328) 0.0569** (0.0254) 0.0708*** (0.00471)

0.142*** (0.0198) 0.00121 (0.00198) 0.0292* (0.0166) 0.127*** (0.00336)

0.563*** (0.0265) 0.0195*** (0.00139) 0.0296*** (0.00897) 0.0127** (0.00470) 0.103*** (0.0134) 0.00277 (0.00215) 0.0486** (0.0183) 0.119*** (0.00485)

2022 37 575 0.000024 0.165 1.00

2022 37 807 0.000022 0.118 1.00

1603 36 454 0.000017 0.343 1.00

1603 36 639 0.000022 0.643 1.00

–

–

Note: The estimates are obtained using two-step system GMM method which treats all the explanatory variables but interest rate shock, trade openness and VIX as endogenous. Time fixed effect is included as IV. The p-value of Arellano-Bond tests for null hypothesis of no first order and second-order autocorrelation and the Hansen J test for null hypothesis of over-identifying restrictions are also reported. Robust standard errors are in parentheses. * p < 0.1. ** p < 0.05. *** p < 0.01.

the shocks are measured by the change of effective rates, then U.S. contractionary shocks tend to have larger effects on the real exchange rates than expansionary ones, but the results are opposite if the shadow rates are used. This may be because the shadow rates can reflect the monetary expansionary effect of U.S. quantitative easing policies after 2008 while the effective rate cannot fall below zero. The results also show that U.S. expansionary shocks tend to have more significant impacts on the periphery economies’ real exchange rates if R&R monetary policy shock is used. With regards to the effectiveness of macro-prudential policies, we do find strong evidences that counter-cyclical macroprudential policies are much more effective in mitigating U.S. expansionary shocks than contractionary ones. The estimated coefficients of the interaction terms in the case of U.S. tightening are either statistically insignificant or with wrong signs. But in U.S. easing, the interaction terms of macro-prudential policies and U.S. interest rate shocks are all negative and statistically significant, indicating that macro-prudential policies work more effectively in U.S. easing. This finding is also consistent to the literature that macro-prudential policies tend to be more effective and commonly used during credit booms than credit crunches (Cerutti et al., 2017a; Altunbas et al., 2018).

4.3. The effectiveness of macro-prudential instruments Next we examine if a counter-cyclical reserve requirement or a counter-cyclical liquidity requirement is effective in mitigating the real exchange rate fluctuations caused by a world interest rate shock, as demonstrated in our theoretical model. In this paper, we only focus on three of the macro-prudential instruments, i.e. reserve requirements, loan-to-value limits and capital requirements since they are the most commonly used instruments in our sample economies and function similarly to our theoretical setting. While loan-to-value limits influence the maximum amount that an individual or firm can borrow against their collateral, capital requirements decide how much capital banks need to hold relative to their risk-weighted assets. A loosening LTV limits or capital requirements policy tends to release the liquidity requirement while the economy faces a tightening world interest rate shock, similar to the liquidity requirement instrument in our theoretical model. Using a similar methodology, we construct a dummy of (+1, 1, 0) for capital buffer, loan-to-value limits and reserve requirements based on the macro-prudential indices constructed in Cerutti et al. (2017b), respectively. We re-estimate Eq. (14) using each of these instrument dummies. The results in Table 8 show that the reserve requirement is effective in mitigating the impact of the U.S. interest rate shock, as our theoretical model suggests.14 This may be because most of the emerging economies have commonly used the reserve requirement instrument to mitigate the impact of external shocks to 14 To save the space, we only report the results for two measures of world interest rate shocks, i.e., shadow federal funds rate and exogenous U.S. monetary policy shock in Tables 8 And 9.

163

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167 Table 7 U.S. tightening versus U.S. easing. Dependent Variable ¼ Drer it

Drerit1 þ DiUS t  Dt  DiUS t  Dt þ DiUS t  Dt  DMPP it  DiUS t  Dt  DMPP it

DMPPit

DTradeit rgdppcit

Drgdpit DVIX t Observations Number of id Instrument number Ar(1) Ar(2) Hansen

US

DiUS t ¼ Effectiv e rate

DiUS t ¼ Shadow rate

DiUS t ¼ MPSt

0.541*** (0.0205) 0.0104*** (0.00310) 0.00927*** (0.00112) 0.0512* (0.0298) 0.0412*** (0.00555) 0.00210 (0.00579) 0.114*** (0.0340) 0.000449 (0.00326) 0.0244 (0.0341) 0.0637*** (0.00547)

0.489*** (0.0179) 0.00816* (0.00471) 0.0148*** (0.00156) 0.0309 (0.0464) 0.0398*** (0.00604) 0.00427 (0.00580) 0.110*** (0.0254) 0.000339 (0.00370) 0.0544* (0.0289) 0.0672*** (0.00561)

0.595*** (0.0286) 0.00383 (0.00239) 0.0282*** (0.00414) 0.0290 (0.0219) 0.0654*** (0.0220) 0.0163*** (0.00553) 0.0834*** (0.0256) 0.00556* (0.00326) 0.0916*** (0.0283) 0.105*** (0.00878)

2022 37 808 0.000018 0.121 1.00

2022 37 808 0.000022 0.131 1.00

1603 36 640 0.000037 0.842 1.00

 Note: Dþ t indicates U.S. monetary tightening; Dt indicates U.S. monetary easing. The estimates are obtained using two-step system GMM method which treats all the explanatory variables but interest rate shock, trade openness and VIX as endogenous. Time fixed effect is included as IV. The p-value of Arellano-Bond tests for null hypothesis of no first order and second-order autocorrelation and the Hansen J test for null hypothesis of over-identifying restrictions are also reported. Robust standard errors are in parentheses. * p < 0.1. ** p < 0.05. *** p < 0.01.

the domestic economy. The results remain robust if the R&R monetary policy shock is used. Loan-to-value limits is also effective but with weakly statistical significance if the R&R monetary policy shock is used to proxy the external shock. A capital buffer instrument is another commonly used macro-prudential instrument in the periphery economies, but it tends to have a direct impact on the real exchange rate. Our results show that a tightening bank capital buffer tends to depreciate the periphery economies’ currency, but it does not have a statistically significant impact on the response of the real exchange rate to the U.S. interest rate change. 4.4. Fixed vs. managed floating regime To investigate whether exchange rate regimes make a difference, we divide the sample into fixed and managed floating regimes based on the course classification of a de facto exchange rate regime as in Ilzetzki et al. (2017). We include free floating into the managed floating sample due to too few observations for free floating regime. The observation numbers in Table 9 show that most of our sample economies have conducted a relatively flexible exchange rate regime, mostly managed floating regime, during the sample period. We find that a positive world interest rate shock tends to depreciate the currency for managed floaters, but the results for fixed regime are statistically insignificant in general. Our findings are consistent with Frankel (2019), in which the external shocks tend to cause more real exchange rate fluctuation in managed floaters but not at all for most firm fixers. Our results, however, are inconsistent with Aizenman et al. (2016), in which they find that an economy that pursues greater exchange rate stability tends to face a stronger link with the center economies through the policy interest rate and REER movements. We are more interested in the relative effectiveness of macro-prudential policies in different exchange rate regimes. As shown by the interaction terms in Table 9, the macro-prudential policies work more effectively in mitigating the world interest rate shock in a more flexible regime than in a fixed regime. The results remain robust if we exclude the free floaters, and consider the managed floating sample only. 4.5. The persistent of macro-prudential policies It is also interesting to know whether the impact of macro-prudential policies on world interest rate shocks is persistent. To examine this question, we employ the Jordà (2005) local projection method to a dynamic fixed effects model with robust

164

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

Table 8 Macro-prudential instruments. Dependent Variable ¼ Drer it US

DiUS t ¼ Shadow rate BUFFER

Drerit1 DiUS t DiUS t  DMPP it DMPPit

DTradeit rgdppcit

Drgdpit DVIX t Observations Number of id Instrument # Ar(1) p-value Ar(2) p-value Hansen (P-value)

DiUS t ¼ MPSt LTV

***

RR ***

BUFFER ***

LTV

***

RR ***

0.408 (0.0242) 0.00823*** (0.000903) 0.0126 (0.0266) 0.00446 (0.00798) 0.127*** (0.0160) 0.00263 (0.00290) 0.158*** (0.0129) 0.0676*** (0.00499)

0.420 (0.0162) 0.00628*** (0.000610) 0.0175 (0.0202) 0.0112 (0.00697) 0.126*** (0.0235) 0.00179 (0.00237) 0.124*** (0.0350) 0.0659*** (0.00416)

0.513 (0.0171) 0.0113*** (0.00124) 0.0260*** (0.00495) 0.0116** (0.00547) 0.106*** (0.0154) 0.000733 (0.00205) 0.0198 (0.0211) 0.0711*** (0.00455)

0.712 (0.0254) 0.00942*** (0.00160) 0.0281 (0.0372) 0.0207*** (0.00750) 0.142*** (0.0261) 0.00183 (0.00271) 0.0205 (0.0206) 0.119*** (0.00721)

0.547 (0.0243) 0.0166*** (0.00125) 0.0532* (0.0268) 0.0143* (0.00731) 0.133*** (0.0243) 0.00216 (0.00248) 0.0317** (0.0156) 0.115*** (0.00737)

0.499*** (0.0259) 0.0193*** (0.00151) 0.0286* (0.0161) 0.0248*** (0.00652) 0.126*** (0.0166) 0.00430* (0.00249) 0.0267 (0.0198) 0.113*** (0.00648)

2022 37 709 0.00002 0.180 1.00

2022 37 727 0.000017 0.140 1.00

2022 37 805 0.000023 0.108 1.00

1603 36 548 0.000022 0.249 1.00

1603 36 563 0.000022 0.403 1.00

1603 36 639 0.00003 0.598 1.00

Note: The estimates are obtained using two-step system GMM method which treats all the explanatory variables but interest rate shock, trade openness and VIX as endogenous. Time fixed effect is included as IV. The p-value of Arellano-Bond tests for null hypothesis of no first order and second-order autocorrelation and the Hansen J test for null hypothesis of over-identifying restrictions are also reported. Robust standard errors are in parentheses. * p < 0.1. ** p < 0.05. *** p < 0.01.

Table 9 Fixed regime vs. managed floating regimes. Dependent Variable ¼ Drer it Fixed Regime

Managed Floating Regime

DiUS t ¼ Shadow rate Drerit1

DiUS t  DMPP it

0.124 (0.451) 0.0118* (0.00534) –

DMPPit

–

DiUS t

DTradeit rgdppcit

Drgdpit DVIX t Observations Number of id Instrument number Ar(1) p-value Ar(2) p-value Hansen J Test (P-value)

US

DiUS t ¼ MPSt

0.00990 (0.136) 0.0181 (0.0226) 0.0770 (0.129) 0.0306* (0.0148)

1.471 (1.560) 0.0873 (0.0715) 0.0865 (0.0556) 0.0262 (0.0779) 0.362 (0.322) 0.0720 (0.0612) 0.303 (0.266) 0.0942 (0.0749)

288 9 292 0.238 0.143 1.00

288 9 294 0.336 – 1.00

0.587 (0.464) 0.00501 (0.0128) –

0.0262 (0.225) 0.00755 (0.0307) 0.241 (0.249) 0.0539** (0.0191)

0.0611 (0.206) 0.0203 (0.0123) 0.0410 (0.0320) 0.0756* (0.0386) 0.0199 (0.0744) 0.000798 (0.0265) 0.240 (0.155) 0.00666 (0.0123)

364 11 366 0.404 0.176 1.00

364 11 367 0.0015 0.542 1.00

–

US

DiUS t ¼ Shadow rate ***

DiUS t ¼ MPSt 0.585 (0.0337) 0.0179*** (0.00176) –

0.146 (0.0387) 0.000853 (0.00249) 0.141*** (0.0206) 0.0768*** (0.00496)

0.420 (0.0285) 0.00991*** (0.00123) 0.0162** (0.00599) 0.00442 (0.00605) 0.135*** (0.0170) 0.000323 (0.00452) 0.113*** (0.0327) 0.0728*** (0.00698)

0.199*** (0.0292) 0.00240 (0.00397) 0.0480** (0.0205) 0.145*** (0.00661)

0.563*** (0.0431) 0.0268*** (0.00302) 0.0275* (0.0146) 0.0200*** (0.00708) 0.146** (0.0557) 0.00586 (0.00766) 0.109** (0.0446) 0.127*** (0.00969)

1654 31 637 0.000067 0.100 1.00

1654 31 863 0.000082 0.100 1.00

1313 30 456 0.000057 0.169 1.00

1313 30 635 0.0001 0.560 1.00

0.417 (0.0212) 0.00920*** (0.00129) – – ***

***

***

–

Note: The estimates are obtained using two-step system GMM method which treats all the explanatory variables but interest rate shock, trade openness and VIX as endogenous. Time fixed effect is included as IV. The p-value of Arellano-Bond tests for null hypothesis of no first order and second-order autocorrelation and the Hansen J test for null hypothesis of over-identifying restrictions are also reported. Robust standard errors are in parentheses. * p < 0.1. ** p < 0.05. *** p < 0.01.

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

165

Fig. 7. Persistence of macro-prudential policies. Note: The upper panels show the response of the periphery economies’ real exchange rate to a 100 bp U.S. interest rate shock, which is the estimation of b1h at horizon h. The bottom panels show to what extent macro-prudential policies can offset the impacts of U.S. interest rate shock on the real exchange rates, which is the estimation of b2h at horizon h. The shaded area corresponds to 90% confidence interval.

standard errors and estimate impulse responses of the real exchange rates. The model specification is similar to Eq. (14), but in the dynamic setting. This econometric framework has been widely used in recent literature to deal with similar research questions, such as Zeev (2017), Ramey and Zubairy (2018), and, etc.

  Xn US US reri;tþh  rer i;t1 ¼ b1h Dit þ b2h Dit  DMPPit þ c Z þ ai;h þ v i;tþh p¼1 h i;tp

ð15Þ

where Z it includes the lagged terms of real exchange rate change, world interest rate shocks and the control variables that used in our Eq. (14) (i.e. X it ). We allow for 6 lags of control variables (i.e., n = 6).15 b1h in Eq. (15) reflects the dynamic responses of the real exchange rates of the periphery economies at horizon h to a world interest rate shock at time t. b2h is used to capture the persistence of the impact of macro-prudential policies on world interest rate shocks. The upper panels in Fig. 7 show that a tightening world interest rate shock tends to depreciate periphery economies’ real exchange rates for about a year, and the real exchange rates reach the trough around the second quarter. The estimated negative values of b2h in bottom panels indicate that counter-cyclical macro-prudential policies do offset part of depreciation pressures caused by the world interest rate shocks. The impact of macro-prudential policies on world interest rate shocks is persistent and lasts for about one year if the shock is measured by the change of federal funds rates (both effective and shadow rates). The persistence lasts longer for about two years if the R&R monetary policy shock is used to proxy the shock. 5. Conclusions This paper investigates how a global financial cycle originating from the monetary policy changes in center economies affects the real exchange rates in peripheral economies and to what extent a counter-cyclical macro-prudential policy can isolate peripheral economies’ real exchange rate from this external shock. We examine this question from both theoretical and empirical perspectives. Theoretically, we use a DSGE model to illustrate that the impact of an external financial shock 15 We only use the lagged values of control variables in our regression (up to n lags), except the change of trade openness and VIX. They are assumed to be exogenous and their contemporary values are also used as the control variables.

166

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

can be magnified by tightening households’ borrowing constraints in a small open economy. A counter-cyclical macroprudential policy can serve as a cushion and mitigate the real exchange rate fluctuations caused by this shock. Our empirical findings also demonstrate that a counter-cyclical macro-prudential policy is effective in mitigating the impact of world interest rate shocks, originating from the U.S. monetary policy change, on the real exchange rates in periphery economies. The effectiveness of macro-prudential policies serving as shock absorbers is persistent and last for at least one year. Among the five commonly used macro-prudential instruments, a reserve requirement is the most effective one in stemming the fluctuations in the real exchange rate. Loan-to-value ratio is also effective, but with weakly statistical significance. Moreover, the asymmetric effects of U.S. monetary policy on the periphery economies’ real exchange rates are ambiguous depending on which shock measures are used. However, we do find strong evidences that counter-cyclical macro-prudential policies work much more effectively in response to U.S. monetary expansionary shocks than contractionary shocks. Finally, our results suggest that macro-prudential policies are more effective in a more flexible regime in mitigating the world interest rate shock than in a fixed regime. In conclusion, we find evidence of the existence of a global financial cycle whereby a change in monetary policy in center economies has a significant impact on the peripheral economies’ real exchange rates, and counter-cyclical macro-prudential policies are effective in serving as shock absorbers of real exchange rate fluctuations, especially during U.S. easing. Since the exchange rate is the key variable that links the borrowing capacities of periphery economies to the external financial shocks, a macro-prudential policy successfully abating the exchange rate fluctuations can help strengthen the financial stability in these countries. Acknowledgements The authors would like thank the discussants and participants at the 93th America Western Economic Association International conference at Vancouver, Canada, Eric Pentecost and Thomas Willett for their useful comments. Usual disclaimer applies. Financial support from China National Social Science Fund (16BJY167) and the Fundamental Research Funds for Central University of Finance and Economics, China are gratefully acknowledged. References Adrian, T., Etula, E., Shin, H.S., 2009. Risk Appetite and Exchange Rate. Federal Reserve Bank of New York Staff Paper, p. 361. Adrian, T., Shin, H.S., 2010. Liquidity and leverage. J. Finan. Intermed. 19 (3), 418–437. Aizenman, J., 2013. The impossible trinity–from the policy trilemma to the policy quadrilemma. Glob. J. Econ. 2 (1), 1–17. Aizenman, J., Chinn, M.D., Ito, H., 2016. Monetary policy spillovers and the trilemma in the new normal: periphery country sensitivity to core country conditions. J. Int. Money Finan. 68, 298–330. Aizenman, J., Chinn, M.D., Ito, H., 2017. Financial Spillovers and Macroprudential Policies. NBER Working Paper, 24105. Akinci, O., Olmstead-Rumsey, J., 2018. How effective are macroprudential policies? An empirical investigation. J. Finan. Intermed. 33, 33–57. Akinci, O., Queralto, A., 2018. Balance Sheets, Exchange Rates, and International Monetary Spillovers. Federal Reserve Bank of New York Staff Reports, p. 849. Altunbas, Y., Binici, M., Gambacorta, L., 2018. Macroprudental policy and bank risk. J. Int. Money Finan. 81, 203–220. Anaya, P., Hachula, M., Offermanns, C.J., 2017. Spillovers of U.S. unconventional monetary policy to emerging markets: the role of capital flows. J. Int. Money Finan. 73, 275–295. Angeloni, I., Faia, E., 2013. Capital regulation and monetary policy with fragile banks. J. Monet. Econ. 60 (3), 311–324. Angelini, P., Neri, S., Panetta, F., 2014. The interaction between capital requirements and monetary policy. J. Money Cred. Bank. 46 (6), 1073–1112. Aoki, K., Benigno, G., Kiyotaki, N., 2016. Monetary and Financial Policies in Emerging Markets. mimeo. Arellano, M., Bover, O., 1995. Another look at the instrumental variable estimation of error-components models. J. Econometr. 68, 29–51. Bianchi, J., Liu, C., Mendoza, E.G., 2016. Fundamentals news, global liquidity and macroprudential policy. J. Int. Econ. 99 (1), 2–15. Blanchard, O., Adler, G., Filho, I.C., 2015. Can Foreign Exchange Intervention Stem Exchange Rate Pressures from Global Capital Flow Shocks?. PIIE Working Paper, 15-18. Blundell, R., Bond, S., 1998. Initial conditions and moment restrictions in dynamic panel data models. J. Econometr. 87, 115–143. Borio, C., Zhu, H., 2012. Capital regulation, risk-taking and monetary policy: a missing link in the transmission mechanism? J. Finan. Stabil. 8 (4), 236–251. Bruno, V., Shim, I., Shin, H.S., 2017. Comparative assessment of macroprudential policies. J. Finan. Stabil. 28, 183–202. Bruno, V., Shin, H., 2015a. Capital flows and the risk-taking channel of monetary policy. J. Monet. Econ. 71, 119–132. Bruno, V., Shin, H., 2015b. Cross-border banking and global liquidity. Rev. Econ. Stud. 82 (2), 535–564. Cerutti, E., Claessens, S., Laeven, L., 2017a. The use and effectiveness of macroprudential policies: new evidence. J. Finan. Stabil. 28, 203–224. Cerutti, E., Correa, R., Fiorentino, E., Segalla, E., 2017b. Changes in prudential policy instruments—a new cross-country database. Int. J. Centr. Bank. 13, 477– 503. Cetorelli, N., Goldberg, L.S., 2012. Banking globalization and monetary transmission. J. Finan. 67 (5), 1811–1843. Coibion, O., 2012. Are the effects of monetary policy shocks big or small? Am. Econ. J. Macroecon. 4 (2), 1–32. Coibion, O., Gorodnichenko, Y., Kueng, L., Silvia, J., 2016. Innocent Bystanders? Monetary Policy and Inequality in the U.S. mimeo. Edwards, S., 1988. Exchange Rate Misalignment in Developing Countries. The Johns Hopkins University Press, Baltimore, MD. Edwards, S., Rigobon, R., 2009. Capital controls on inflows, exchange rate volatility and external vulnerability. J. Int. Econ. 78 (2), 256–267. Farhi, E., Werning, I., 2014. Dilemma not trilemma? Capital controls and exchange rates with volatile capital flows. IMF Econ. Rev. 62, 569–605. Federico, P., Vegh, C., Vuletin, G., 2014. Reserve Requirement Policy over the Business Cycle. NBER Working Paper, No. 20612. Fendog˘lu, S., 2017. Credit cycles and capital flows: effectiveness of the macroprudential policy framework in emerging market economies. J. Bank. Finan. 79, 110–128. Frankel, J., 2019. Systematic managed floating. Open Econ. Rev. 30 (2), 255–295. Gourinchas, P., Jeanne, O., 2013. Capital flows to developing countries: the allocation puzzle. Rev. Econ. Stud. 80, 1484–1515. Gourinchas, P., Obstfeld, M., 2012. Stories of the twentieth century for the twenty-first. Am. Econ. J. Macroecon. 4 (1), 226–265. Han, X., Wei, S., 2018. International transmissions of monetary shocks: between a trilemma and a dilemma. J. Int. Econ., 205–219 Hofmann, B., Shim, I., Shin, H.S., 2016. Sovereign yields and the risk-taking channel of currency appreciation. BIS Working Papers, 538. Bank for International Settlements. Ilzetzki, E., Reinhart, C.M., Rogoff, K.S., 2017. Exchange Arrangements Entering the 21st Century: Which Anchor Will Hold?. NBER Working Paper, 23134. Jongwanich, J., Kohpaiboon, A., 2013. Capital flows and real exchange rates in emerging asian countries. J. Asian Econ. 24 (4), 138–146.

A.Y. Ouyang, S. Guo / Journal of International Money and Finance 96 (2019) 147–167

167

Jordà, O., 2005. Estimation and inference of impulse responses by local projections. Am. Econ. Rev. 95 (1), 161–182. Kearns, J., Patel, N., 2016. Does the Financial Channel of Exchange Rates Offset the Trade Channel? BIS Quarterly Review, Bank for International Settlements. December. Lambertini, L., Mendicino, C., Punzi, M.T., 2013. Leaning against boom-bust cycles in credit and housing prices. J. Econ. Dyn. Contr. 37 (8), 1500–1522. Lane, P., Milesi-Ferretti, G.M., 2007. The external wealth of nations mark II: revised and extended estimates of foreign assets and liabilities, 1970–2004. J. Int. Econ. 73, 223–250. Lim, C.H., Columba, F., Costa, A., Kongsamut, P. Otani, A., Saiyid, M., Wezel, T., Wu, X., 2011. Macroprudential Policy: What Instruments and How Are They Used? Lessons from Country Experiences. IMF Working Paper 11/238. Lund-Jensen, K., 2012. Monitoring Systemic Risk Based on Dynamic Thresholds. IMF Working Paper, No. 12/159. Mendicino, C., Punzi, M.T., 2014. House prices, capital inflows and macroprudential policy. J. Bank. Finan. 49, 337–355. Mendoza, E.G., 2002. Credit, prices, and crashes: business cycles with a sudden stop. In: Edwards, Sebastian, Frankel, Jeffrey (Eds.), Preventing Currency Crises in Emerging Markets. University of Chicago Press for National Bureau of Economic Research. Mendoza, E.G., 2010. Sudden stops, financial crises, and leverage. Am. Econ. Rev. 100 (5), 1941–1966. Mendoza, E.G., 2016. Macroprudential Policy Promise and Challenges. NBER Working Paper, 22868. Mimir, Y., Sunel, E., 2019. External shocks, banks and optimal monetary policy in an open economy. Int. J. Centr. Bank. (Forthcoming) Miranda-Agrippino, S., Rey, H., 2015. World Asset Markets and the Global Financial Cycle. NBER Working Papers, 21722. Nier, E, Sedik, T.S., Tondino, T., 2014. Gross Private Capital Flows to Emerging Markets: Can the Global Financial Cycle be Tamed?. IMF Working Papers, 14/ 196. Obstfeld, M., 2015. Trilemmas and Trade-offs: Living with Financial Globalisation. BIS Working Papers, No. 480. Ostry, J., Ghosh, A.R., Chamon, M., Qureshi, M.S., 2012. Tools for managing financial-stability risks from capital inflows. J. Int. Econ. 88, 407–421. Passari, E., Rey, H., 2015. Financial flows and the international monetary system. Econ. J. 125 (584), 675–698. Ramey, V.A., Zubairy, S., 2018. Government spending multipliers in good times and in bad: evidence from US historical data. J. Polit. Econ. 126 (2), 850–901. Rey, H., 2015. Dilemma Not Trilemma: The Global Financial Cycle and Monetary Policy Independence. NBER Working Paper, 21162. Rey, H., 2016. International Channels of Transmission of Monetary Policy and the Mundellian Trilemma. NBER Working Paper, 21852. Romer, C.D., Romer, D.H., 2004. A new measure of monetary shocks: derivation and implications. Am. Econ. Rev. 94 (4), 1055–1084. Steiner, A., 2017. Central banks and macroeconomic policy choices: relaxing the trilemma. J. Bank. Finan. 77 (C), 283–299. Wu, J.C., Xia, F.D., 2015. Measuring the Macroeconomic Impact of Monetary Policy at the Zero Low Bound. Chicago Booth Research Paper No. 13-77. Zeev, N.B., 2017. Capital controls as shock absorbers. J. Int. Econ. 109, 43–67.