HIAS-E-133

Financial Integration, Excess Consumption
Volatility, and the World Real Interest Rate

Haruna Yamada
Hitotsubashi University

Sep 2023

Hitotsubashi Institute for Advanced Study, Hitotsubashi University
2-1, Naka, Kunitachi, Tokyo 186-8601, Japan
tel:+81 42 580 8668 http://hias.hit-u.ac.jp/
HIAS discussion papers can be downloaded without charge from:https://hdl.handle.net/10086/27202
https://ideas.repec.org/s/hit/hiasdp.html

Financial Integration, Excess Consumption
Volatility, and the World Real Interest Rate∗
Haruna Yamada†
September 26, 2023
Abstract
Contrary to classical macroeconomic theory, the volatility of consumption relative toincome has risen in emerging markets despite the international financial integration.
This study presents a theoretical mechanism of this phenomenon by developing a small
open economy model with an occasionally binding borrowing constraint, named theInterest Coverage Ratio-based borrowing constraint. Calibration exercises show that
financial integration improves consumption smoothing and mitigates income shocks.
Meanwhile, the foreign debt limit is more sensitive to changes in the world real interest
rate. An increase in the world real interest rate tightens the borrowing constraint anddecreases consumption significantly for the repayment. Financial integration would
make consumption more vulnerable to the world real interest rate changes, resulting
the higher volatility in emerging markets.
Keywords: Financial Integration, Excess Consumption Volatility, Emerging Market
Economy, World Real Interest Rate, Occasionally Binding Borrowing Constraint
JEL codes: E21, E41, E44, F62∗

I would like to thank Takashi Kano, Etsuro Shioji, Takeki Sunakawa, Masashige Hamano, Hidehiko Matsumoto, Kazuhiro Teramoto, Keiichi Morimoto, Akihiko Ikeda, and the members of Shioji’s
seminar and Hamano’s seminar. I thank participants at the Japan Society of International Economics
2022 Annual Meeting, the 5th Hitotsubashi Summer Institute, the Japan Economic Association 2023
Spring Meeting, the Waseda International Macro Workshop, and economic seminars at Meiji university
and at Seikei university. I am solely responsible for any errors and misinterpretations in this study.
†
Doctoral Student, the Graduate School of Economics, Hitotsubashi University.
Email: ed185010[at]g.hit-u.ac.jp1

1

Introduction

Can financial integration contribute to economic stability by reducing consumption
volatility? The classical macroeconomic theory suggests that financial integration (hereafter, FI) facilitates international financial transactions and thus allows households tosmoothen their consumption, which results in less consumption volatility relative toincome volatility. Previous theoretical exercises have also shown that consumption
volatility and its ratio to income volatility decrease as the degree of FI increases (Mendoza, 1991; Baxter and Crucini, 1995). However, empirical studies uncover that contrary to these theoretical predictions, in emerging market economies (hereafter, EMEs),consumption is excessively more volatile than income. This empirical finding is called
excess consumption volatility (ECV; Aguiar and Gopinath, 2007). Moreover, the sizeof the ECV is much worse in EMEs with higher FI degrees (Kose et al., 2003; Prasad
et al., 2003a). Then, a natural question is, “why does a deeper FI lead to worse ECVin EMEs?”
To answer this question, this study investigates a small-open economy (SOE) endowment model with an occasionally binding borrowing constraint, named the Interest
Coverage Ratio (ICR)-based borrowing constraint, which is derived from a one-periodinternational debt contract based on the borrower’s interest coverage ratio. The key
assumption in this borrowing constraint is that (1) the foreign debt limit depends negatively on a time-varying risk-free world real interest rate (WRI); (2) the borrowing
constraint is specified so that the changes in the WRI have a larger impact on the foreign debt limit than standard flow collateral constraints such as Bianchi (2011). These2

assumptions make the shadow price of the borrowing constraint, which can be interpreted as the country-specific risk premium of SOE, depend positively and significantly
on the WRI. This theoretical property of the borrowing constraint is consistent with
Uribe and Yue’s finding that fluctuations in the U.S. real interest rate affect the EMEs’
business cycles mainly through changing risk premiums.
This study emphasizes the sensitivity of the foreign borrowing limit of the SOE
to the WRI as the key to explaining the question of why the size of ECV increases
in the degree of FI, motivated by numerous past studies advocating the importanceof WRI movements to business cycles in SOEs. Some previous exercises with small
open economy real business cycle (SOE-RBC) models reveal the role of the WRI shockin business cycle fluctuations of developed SOEs (Blankenau et al., 2001; Kano, 2009).
Moreover, other past studies show that the WRI shock has significant effects on businesscycles in the EMEs (Uribe and Yue, 2006; Sarquis, 2008; Muhanji and Ojah, 2011),
sudden stops (Arellano and Mendoza, 2002; Mendoza, 2010; Davis et al., 2023) anddefault risks (Foley-Fisher and Guimaraes, 2013).
Moreover, we illustrate the ECV is associated with the negative skewness of consumption in the EMEs. The size of ECV is larger in EMEs with large negative skewness
of consumption which indicates consumption declines a lot occasionally. To obtain theskewness in the long-run, we solve our model by a nonlinear method developed by
Mendoza and Villalvazo (2020).
Our calibrated model successfully accounts for the ECV observed in the postwar
quarterly data of Argentina. The model also implicates that a deeper FI, represented

3

by a looser borrowing constraint, causes a higher ECV and a larger negative skewness
of consumption. These successful outcomes of our model steam from the following novel
mechanism that this study proposes. A higher degree of FI lowers the probability ofbinding the borrowing constraint, then households can smooth their consumption morethrough international financial transactions. As a result, foreign debt increases on average. However, as foreign debt increases, the foreign debt repayment also becomes larger,
and therefore consumption must be reduced more when the borrowing constraint willbind. Because the WRI significantly affects the tightness of the borrowing constraint,
foreign debt and consumption will be more vulnerable to a change in the WRI. Hence,the ECV increases in the degree of FI.
Our calibration results suggest that the deeper FI facilitates international financial transactions and allows more households’ consumption-smoothing activities, butwhether the consumption-smoothing is possible depends more on the level of WRI.
Previous studies, including Pancaro (2010) and Faia (2011), approached the puzzling
relationship between the FI and the ECV differently from our research; they consideredcollateral constraints á la Kiyotaki and Moore (1997) and abstract from the crucial
effects of the WRI on international financial transactions. Contrary to our calibration
results, their results indicate that the deeper FI (i.e., the relaxation of collateral constraints) does not promote households’ consumption-smoothing behavior. The central
mechanisms proposed by these studies highlight how deepening FI amplifies the consumption response against the country-specific productivity shock. A positive countryspecific productivity shock increases the demand for collateral for production. It thus4

increases the price of capital, which results in the relaxed collateral constraint and afurther increase in production, inducing a more increase in permanent income. Then, as
the permanent income hypothesis predicts, consumption increases more than the current income increase, resulting in the ECV. A deeper FI relaxes collateral constraints
and amplifies the effect of the productivity shock on the SOE, causing the worse ECV.
Other previous studies examine the impact of FI on the ECV by modeling the FI as
the opening of a closed country to the international financial market (Levchenko, 2005;
Leblebiciouglu, 2009; Bhattacharya and Patnaik, 2016; Evans and Hnatkovska, 2007,2014). These studies illustrate how FI worsens ECV, based on the permanent income
hypothesis. FI allows consumption respond more than current income increase against
an increase in the permanent income, thus consumption becomes more volatile thanincome.
The remainder of this paper is organized as follows. Section 3 describes the model.
Section 2 discuss empirically the relationship between ECV and skewness of consumption. Section 4 presents the quantitative analysis and evaluates the model. Finally,
Section 5 concludes the paper.

2

The ECV and skewness of consumption

Figure 1 shows the cross-country scatter plots regarding the relative standard deviationof consumption to real GDP, the measurement of ECV, and the negative skewness of
consumption and of real GDP. In both panels of A and B of figure 1, the y-axis is
the relative standard deviation of consumption to real GDP in each countries. If the5Figure 1: The relative standard deviation of consumption to real GDP and skewness of
consumption and of eal GDP

Note: Y-axis is the relative standard deviation of consumption to real GDP, x-axis in
the panel A is skewness of consumption and that in panel B is skewness of real GDP.
The blue-triangle points are for the emerging market economies, and orange-circle ones
are for the advanced economies. Sample countries and sample periods are listed inAppendix.
relative standard deviation exceeds to 1, the consumption is more volatile than the real
GDP; ECV is observed. The x-axis is the skewness of consumption in the panel A, andthe skewness of real GDP, respectively. The blue-triangle points are for the emerging
market economies, and orange-circle ones are for the advanced economies.
Figure 1 shows that in the emerging market economies, the relative standard deviation associates with the negative skewness of consumption, not with the skewnessof the real GDP. In panel A of figure 1, there is a clear negative relationship between
the relative standard deviation and the skewness of consumption in emerging market
economies. In other words, the consumption must be excessively volatile than GDP
because consumption tends to decline largely and the distribution of consumption has
a long tail to the left. In contrast, there is no clear relationship between the relative

6

volatility and the skewness of real GDP in the emerging market economies, as shownin the panel B of figure 1. The ECV is considered to be caused by the occasional large
decline in consumption in the emerging economies.
Previous studies, Pancaro (2010); Faia (2011), did not take into account the negative
relationship between the relative standard deviation and the skewness of consumption.
Their results do not have a skewness of consumption in the long-run because theysolved their model by linear approximation around the steady state that the borrowing
constraint binds. To illustrate the skewness of consumption in the long-run, we solve
the model by non-linear method, developed by Mendoza and Villalvazo (2020).

3

A SOE endowment model with an ICR-based borrowing constraint

3.1

The household problem

Consider an SOE with a single good. An infinitely lived representative household receives exogenous income yt which varies stochastically. There is a state non-contingent
bond traded in international financial markets. The representative household can borrow for one period from foreign countries at the time-varying WRI rt , which is exogenous
to the SOE.
The household faces the following period-by-period budget constraint

yt + bt+1 = (1 + rt−1 )bt + ct ,7(1)

where ct is consumption and bt+1 is the foreign debt level in period t + 1.
The household also faces the following the borrowing constraintτ
bt+1 ≤ max b̄, Et yt+1 ,rt(2)

where b̄ > 0 is the minimum debt limit and τ ≥ 0 is a parameter that determines thetightness of the borrowing constraint, as we will discuss bellow.3
The second term in the bracket of the borrowing constraint (2) implies that (i) the
foreign debt limit depends negatively on the WRI, and (ii) a higher τ makes the foreign
borrowing limit more sensitive to the WRI; a lower (higher) rt tightens (relaxes) the
borrowing constraint.
More precisely, the borrowing constraint is derived from foreign lenders’ assessmentyt.
of the borrower’s default risk evaluated based on the interest coverage ratio (ICR), rt−1bt

We assume that foreign investors lend out to the SOE under the following condition on
the ICRyt
rt−1 bt≥ τ̄ ,(3)

where τ̄ is the threshold value imposed by foreign lenders. Condition (3) implies thatytforeign debt level bt needs to satisfy that the ICR ( rt−1
) exceeds the threshold valuebtτ̄ .
We relay the economic rationale behind the condition on practical and empiricalfacts. The financial covenant with ICR is one of the common covenants in corporate3

It is necessary to set this minimum borrowing b̄ for the existence of the optimal solution. Intuitively,
if the initial b is small enough, there is no optimal solution depending on the realized value of shocks.
For details, see Chapter 18 of Ljungqvist and Sargent (2012).

8

firms (Private Placement Enhancement Project, 1996; Dothan, 2006). In addition, theICR is used for default risk evaluations in firms. For example, rating agencies, such as
Standard and Poor’s, include the ICR in the construction of their ratings (Standard
and Poor’s , 2013). Furthermore, Gray et al. (2006) show that the ICR has a dominant
effect on credit ratings.
We then derive the borrowing constraint (2) by rearranging Eq.(3) and setting τ ≡1/τ̄ . Here, the parameter τ can be interpreted as the degree of FI. A deeper FI reflectedin, for example, enhancement of information disclosure to foreign investors and/or many
local branches of international banks, can reduce monitoring costs of foreign lenders andincrease the credibility of the SOE. This higher credibility can lower the threshold valueτ̄ , thus increasing τ . As a result, a higher degree of FI can increase the foreign debt
limit, as the borrowing constraint (2) implies.
Given the exogenous income yt , the WRI rt and initial foreign debt level b0 , thehousehold chooses the sequence of consumption ct and the foreign debt level bt+1 by
maximizing the following lifetime expected utility

E0

∞
X

c1−γ − 1
βt t
,
1−γ
t=0

(4)

subject to the budget constraint (1) and the borrowing constraint (2).
The Euler equation of the household’s problem presented above is

λt = βRt Et λt+1 + λB
t ,

9

(5)

where λt = c−γ
is the marginal utility of consumption at period t, λB
tt is the Lagrange
multiplier for the borrowing constraint (2) at period t, and Rt = (1 + rt ) is the gross
WRI. If λB
t = 0, Eq.(5) is equivalent to the Euler equation in the standard SOEmodel without borrowing constraints. λB
t represents the additional cost, evaluated interms of utility, imposed when households increase current consumption through foreign
borrowing in the binding borrowing constraint. If the borrowing constraint binds, themarginal utility gain from increasing consumption by foreign borrowing (λt ) equals themarginal utility loss from reducing consumption associated with the increase in interest
payments (βRt Et λt+1 ) and the additional cost due to the binding borrowing constraint(λBt > 0). Thus, when the borrowing constraint binds, current consumption is smaller
than in the case of the standard SOE model without borrowing constraints.
The WRI affects consumption through two channel. The first channel is the intertemporal substitution effect, the first term in the Euler equation (5), which is thestandard effect of real interest rate on consumption in the real business cycle model. The
second channel is that through the Lagrange multiplier for the borrowing constraint,
λB
t . Since the borrowing constraint (2) assumes borrowing limit depends negatively
on the WRI, a high WRI tighten the borrowing constraint, then λBt increases, which
results in reduction of consumption.
We assume that the WRI follows an AR(1) process

rt = (1 − ρr )r∗ + ρr rt−1 + ert , ert ∼ N (0, σr2 ),(6)

where r∗ and ρr are the mean and the AR root of rt . The WRI shock er is on i.i.d.
10normal random variate the zero mean and the standard deviation σr .
We also assume that the income follows the process

ln yt = (1 − ρyy ) ln y ∗ + ρyy ln yt−1 + ρyr rt−1 + eyt , eyt ∼ N (0, σy2 ).

(7)

where y ∗ and ρyy are the mean and the AR root of yt and ρyr is the sensitivity of thecurrent income yt to the one period past WRI, rt−1 . The country-specific income shock
ey is on i.i.d. normal random variate with the zero mean and the standard deviation
σy . The current income yt depends on rt−1 because if we consider an AR(1) income
process independent of rt , consumption volatility which depends on the multiple shocks
in equilibrium should exceed income volatility by construction. Thus, we consider areduced-form income process, driven by the two shocks to obtain the volatility ratio ofconsumption and income consistent with the data.

3.2

The steady state

We assume that the degree of FI in EMEs is sufficiently low that the borrowing constraint binds at the steady state. Lower τ leads to a smaller foreign borrowing limit
and tighter borrowing constraint. The sufficiently low τ indicates that the borrowing
constraint mostly limits foreign borrowing, resulting in the borrowing constraint binds
at the steady state. Past studies assume the borrowing constraints unbind at the steadystate to investigate the role of borrowing constraints in financial crises. Because our focus is on the effect of FI on the ECV as a whole business cycle, we analyze consumptionin EMEs in the case the borrowing constraint binds at the steady state.
11

Table 1: Calibrated parameter values (baseline case)Parameter
Value
Source/targetβγτsubjective discount factor

0.95
20.0408risk aversion
degree of FI

Pancaro (2010)
Mendoza (2010)
std. ratio of consumption to real

GDP per capita in Argentinar∗ln y ∗

steady state value of WRI
steady state value of income (logarithm)

0.0356
4.460

mean of U.S. real interest ratemean of per capita real GDP

in Argentina
The steady state of this model is characterized as follows:

y ss = y ∗ , rss = r∗ , bss =τ ss
y , tbss = rss bss = τ y ss ,rss

css = y ss − rss bss = (1 − τ )y ss , λBss = [1 − β(1 + rss )] > 0.
A higher τ increases the steady state foreign debt level bss and trade-balance tbss .
Because this model is for an endowment economy, an increase in bss decreases thesteady-state level of consumption css . Since the Lagrange multiplier for the borrowing
constraint λBss does not depend on τ , a fall in css decreases the risk premium S ss .

3.3

Calibration

Table 1 reports the calibrated values of the model’s structural parameters. The modelis calibrated at a quarterly frequency. We set the parameter β = 0.95 so that λBss > 0,that is, the borrowing constraint binds at the steady state. τ is set to 0.0408 so thatthe standard ratio of consumption to real GDP per capita obtained from the model fits
its data in Argentina for the period 1993Q1-2008Q3. ln y ∗ is set to the sample average12

of real GDP per capita in Argentina, 4.46.4 We assume that the WRI is approximatedby the U.S. real interest rate. Hence r∗ is set to the sample average of the U.S. realinterest rate for the period 1993Q1-2008Q3.5
We calibrate the stochastic processes of the two exogenous shocks by estimating
Eqs.(6) and (7) with the U.S. real interest rate and the deviation from the cubic trendof real GDP per capita in Argentina for 1993Q1-2008Q3, respectively. We obtainρr = 0.937, ρyr = −0.100, ρyy = 0.9485, σr = 0.0055, and σy = 0.0194 from thecorresponding point estimates. Subsequently, we approximate the bivariate vector autoregression (VAR), which is implied by Eeqs.(6) and (7), by a finite Markov processwith nine states of yt and rt , using the multi-Tauchen method developed by Tauchen
and Hussey (1991). The generated discrete grids of y has a minimum value of 79.93
and a maximum value of 93.51, while r has a minimum value of 0.0165, and maximum
value of 0.0547.
We test the effect of FI on the SOE by changing the value of τ . We recalibrate themodel with the four different values of τ = [0.5τ ∗ , 0.75τ ∗ , τ ∗ , 1.25τ ∗ ], where τ ∗ is thebaseline value of τ set above.

4

Results of the quantitative analysis

The model is solved using the fixed-point iteration method proposed by Mendoza andVillalvazo (2020), which is one of the nonlinear global solution methods with occasionally binding constraints. The endogenous state variable is b, which is chosen from4
5

The real GDP per capita is the deviation from the cubic trend.
The U.S. real interest rate is constructed following Neumeyer and Perri (2005).

13

evenly spaced discrete grids with size nb , B = {b1 < b2 < · · · < bnb }. The state spaceof the model is defined as (b, s) ∈ B × S. We set B with nb = 200, b1 = −0.3bss , andb200 = 2.1bss for the baseline τ ∗ case, where bss is the deterministic steady state valueof bt . In case τ is smaller than the baseline value of 0.0408, we change b1 to −0.8bss .
The maximum value of B, b200 , is set to different values depending on τ value. For
τ = 0.5τ ∗ , b200 = 1.5bss ; for τ = 0.75τ ∗ , b200 = 1.9bss ; for τ = 1.25τ ∗ , b200 = 2.45.6
Because each exogenous state variables rt and yt has nine states, there are 200 × 81
coordinates in the state space of this model.

4.1

Effect of financial integration on the SOE

Table 2 shows the sample moments in Argentina for 1993Q1-2008Q2 (Column 2) andthe business cycle moments derived from the stationary distributions of bt and policy
functions under four different values of τ . Here, τ ∗ = 0.0408 is the baseline value of τ .
The sample moments in Argentina show high volatility and the ECV. Instead, thestandard deviations of trade balance, consumption, and income are over five percentage
points. Moreover, the relative standard deviation of consumption to income exceeds
1, which signifies the ECV. These observations are consistent with the characteristics
of emerging market business cycles, found by Aguiar and Gopinath (2007). In addition, the sample moments show that consumption in Argentina is characterized as alarge negative skewness. Hence, high consumption volatility is associated with a large
negative skewness of consumption.
6

The minimum and maximum value of B are chosen so that the Euler equation error is sufficiently
small.

14

Table 2: Business cycle moments: effect of τ change
Model
∗
Data
0.5τ
0.75τ ∗
τ∗

1.25τ ∗

Mean
Foreign debt
45.52
65.53
84.58 102.92
TB-GDP ratio
0.02
0.02
0.03
0.03
0.04
Consumption
4.26
4.44
4.43
4.42
4.42
(log)
Real GDP (log)
4.46
4.46
4.46
4.46
4.46
Standard deviation (in percent, except for foreign debt)
Foreign debt
10.96
13.85
16.10
17.87
TB-GDP ratio
5.40
3.18
3.75
4.18
4.52
Consumption
6.82
5.94
6.42
6.83
7.19
(log)
Real GDP (log)
5.10
5.10
5.10
5.10
5.10
Relative std. to GDP
Consumption
1.34
1.17
1.26
1.34
1.41
(log)
Skewness
Foreign debt
0.39
0.36
0.33
0.30
TB-GDP ratio
1.00
1.80
1.91
1.96
1.98
Consumption−0.97 −0.69 −0.94 −1.13
−1.29
(log)
Probability of binding (%)
16.28
12.04
9.56
8.22
Euler eq. error (log10)
Max. value−7.86 −7.87 −7.92−7.87
Mean. value−9.50 −9.59 −9.67−9.73
Note: Moments are calculated from the stationary distribution in Appendix 5. The
probability of binding borrowing constraint means intuitively that how many positive
grids, which can be the solution with the positive probability, are in λBt .
Our proposed model performs well at accounting for these observations. In thebaseline τ ∗ case shown in Column 5 in Table 2, the standard deviation of consumption,
the size of ECV, and the skewness of consumption are close to the data counterparts.
Moreover, the size of ECV reported as the relative standard deviation of consumption
to GDP in Table 2 increases in τ . This calibration result shows that a deeper FI worse
the ECV in Argentina, which is consistent with the findings of Kose et al. (2003) and15

Prasad et al. (2003b). In addition, the higher consumption volatility is associated with alarger negative skewness of consumption. In addition, a larger τ reduces the probabilityof binding borrowing constraints and increases the average amount of foreign debt.
These calibration results indicate that a deeper FI allows more international borrowing,whereas it increases the volatility and the negative skewness of consumption.

4.2

The source of high volatility

This subsection explains why the model predicts the higher consumption volatility as
FI deepens even if deeper FI relaxes the borrowing constraint and increases theaverage amount of foreign debt. We discuss the source of higher consumption
volatility by policy functions under baseline case (τ = τ ∗ ).

Figure 2 shows the policy functions sliced at the steady state value of income,yt = y ss (A), and these are sliced at the deterministic steady state value of the foreign
borrowing, bt = bss (B). The left plot is the policy function of foreign borrowing; themiddle plot is that of consumption; and the right plot is that of the Lagrange multiplierfor the borrowing constraints. We examine the policy functions under different levelsof the WRI. The blue dashed line is the policy functions under the low value of rt , thesolid red line is those under the steady state value of rt , and the yellow dashed-dottedline and the purple dotted line are those under the high value of rt .
The upper-right panel of Figure 2A shows that when rt = rlow , λBt remains zero,no matter how much the income is. This implies that the borrowing constraint neverbinds in the low WRI period. Thus, during the rlow periods, households can borrow
16

Figure 2: Policy functions
A. IncomeB. Foreign debt

Note: Policy functions in subplot A are calculated with spline completion and sliced at
b = bss (the deterministic steady-state level of foreign borrowing) and those in subplot
B are sliced at y = y ss (the deterministic steady-state level of income). In subplot A,
both ends of the income grid are dropped. rlow , rss , rhigh1 , rhigh2 mean the states (grids)
for the WRI in both subplots A and B. rlow is the second level from the bottom of WRI.
rhigh2 and rhigh1 are the second and third levels from the top of WRI, respectively.
from foreign countries freely and smooth their consumption against the income shock.
Because the income shock is temporal, the households increase foreign borrowing tosmooth their consumption when the income is low, and reduce it when the income ishigh, as shown in the left panel of Figure 2A.
The tightness of the borrowing constraint varies largely depending on the value of the17

WRI. As shown in the right panel of Figure 2A, λBt for the borrowing constraint is highly
volatile; it varies from zero to near 0.15%, depending on the level of rt . Such a highdependence of λBt on the WRI makes foreign borrowing and consumption depend on
the WRI. A lower (higher) rt relaxes (tightens) the borrowing constraint and facilitates(limits) foreign borrowing, which results in increasing (reducing) consumption by thebudget constraint (1).
Figure 2B indicates that if the foreign debt in the previous period, bt , is high enough,then the foreign debt and consumption will fluctuate significantly with changes in the
WRI. When the WRI is lower than rss , the borrowing constraint never binds (λBt = 0),
not depending on bt as shown in the right panel in Figure 2(B). As the WRI increases,
B
B
λB
t varies more depending on bt ; higher bt increases λt and an increase in λt grows

with a higher WRI. The more foreign debt in the previous period, the more likely itis that the current foreign debt will be severely limited, depending on the level of the
WRI. As a result, a larger bt with a high WRI reduces consumption more than with alow WRI.
The simulation result in Figure 3, highlighted by the gray shadow, illustrates how
the large bt and high WRI cause a downward spike in consumption associated with thebinding borrowing constraint. During the low-WRI period, the borrowing constraint
does not bind, causing the accumulation of foreign borrowing. Then, if the WRI rises
sharply, the borrowing constraint binds, and the foreign debt is limited. However,households must repay the large amount of foreign borrowing accumulated during thelow-WRI period. As a result, consumption decreases significantly to repay the foreign

18Figure 3: Simulation result

Note: The simulation is conducted by the following steps; (1) Generate Markov chain
simulations of exogenous shocks (y, r) with 200 periods, (2) Calculate responses ofb, c, λB from policy functions with spline completion. We start the simulation at themean value of the stationary distribution of b and the deterministic steady state valueof y and r.
debt, leading to higher consumption volatility than income volatility.
Now we answer the question, why does the degree of ECV increase as the FI deepens?
Accordingly, a larger τ reduces the probability of binding borrowing constraints andincreases the average amount of foreign borrowing. However, it also makes borrowing
and consumption more volatile because a larger τ amplifies the effect of the WRI on the19borrowing limit.7 If τ is small (i.e., the FI level is low), the borrowing constraint mostly
binds even if the WRI is low. The implied higher probability of binding constraint does
not allow foreign borrowing to adjust fully against the income shock and results in thesmaller volatilities of foreign debt and consumption.

5

Concluding remarks

This study investigates why deeper FI increases the ECV in EMEs. We construct ansmall open, endowment economy model with a occasionally binding borrowing constraint in which the borrowing limit depends on expected future income and the WRI.
The quantitative analysis shows that the model fits better to the actual consumption
volatility and the volatility ratio of consumption to income in Argentina.
The mechanism presented in this paper is as follows. Under the baseline calibration,
the borrowing constraint does not bind when the WRI is low. Hence, foreign borrowing
increases. Large repayments reduce consumption if the WRI increases and the borrowing constraint becomes tight. This reduction in consumption is much larger than that
under the standard borrowing constraint model. Consumption smoothing is possible
when the borrowing constraint does not bind, but only against income shocks. As aresult, consumption under the borrowing constraint model depends more on the WRI
shock, which mainly determines whether the borrowing constraint binds or not.
A higher degree of FI reduces the probability of binding the borrowing constraint
and increases the average amount of foreign borrowing. However, it also makes foreign
7

Recall that the borrowing constraint forms bt+1 ≤ rτt Et yt+1 .

20

borrowing and consumption more volatile because the higher degree of FI amplifies theeffect of the WRI on the foreign debt limit. A large amount of foreign borrowing canreduce consumption significantly once the borrowing constraint binds. Consequently,
foreign debt and consumption will be more volatile at higher FI levels, even if the FI
increases the average amount of foreign debt and provides a better opportunity for
consumption smoothing against income shocks. The FI would make consumption andforeign borrowing more vulnerable to the WRI shock.
Future research should evaluate the empirical validation of this model. Our results
indicate that it is necessary to discuss the consumption-smoothing ability in EMEs
by checking the consumption response against the identified country-specific income
shock. Additionally, our mechanism implies that the asymmetric response of consumption volatility against the WRI shock due to the existence of the borrowing constraint
generates high consumption volatility. Empirical exercises incorporating the nonlinear
relationship between the economic variables and exogenous shocks are needed to checkthe model’s validity.

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Appendix A. Data source and sample countries
A1. Data source and sample countries in section 2
Table 3 and Table 4 are the list of sample countries in emerging market economies andin advanced economies, respectively. The end of the sample is 2009Q4.

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Table 3: Sample countries: emerging market economies
Beginning of the sample
Country
Iso3c Annual
Quarterly
Bolivia
BOL
1991
1991Q1
Ecuador
ECU
1991
1991Q1
Uruguay
URY
1983
1983Q1
Argentina
ARG
1993
1993Q1
Brazil
BRA
1991
1991Q1
Chile
CHL
1996
1996Q1
Colombia
COL
1994
1994Q1
Hong Kong SAR, China HKG
1980
1980Q1IsraelISR
1980
1980Q1
Korea, Rep.
KOR
1980
1980Q1
MexicoMEX
1980
1980Q1
Malaysia
MYS
1991
1991Q1
Peru
PER
1980
1980Q1Thailand
THA
1993
1993Q1
TurkeyTUR
1980
1980Q1
South Africa
ZAF
1980
1980Q1
Bulgaria
BGR
1994
1994Q1
CyprusCYP
1995
1995Q1
Hungary
HUN
1995
1995Q126

Table 4: Sample countries: advanced economies
Beginning of the sample
Country
Iso3c Annual
Quarterly
Australia
AUS
1980
1980Q1
Austria
AUT
1980
1980Q1
Belgium
BEL
1980
1980Q1
CanadaCAN
1980
1980Q1
Switzerland
CHE
1980
1980Q1
Germany
DEU
1980
1980Q1
Denmark
DNK
1980
1980Q1
Spain
ESP
1980
1980Q1Finland
FIN
1980
1980Q1
France
FRA
1980
1980Q1
United Kingdom GBR
1980
1980Q1
GreeceGRC
2000
2000Q1
Italy
ITA
1980
1980Q1
Japan
JPN
1980
1980Q1
Netherlands
NLD
1980
1980Q1
NorwayNOR
1980
1980Q1New Zealand
NZL
1980
1980Q1
Portugal
PRT
1980
1980Q1
Sweden
SWE
1980
1980Q1
United StatesUSA
1980
1980Q127

A2. Source of Argentine data and construction of U.S. real interest rate
Sample period is from 1993Q1 to 2008Q3. The Argentine quarterly dataset is by Martín
Uribe that available at his homepage. For the real GDP per capita and consumption,
we use the deviations from the cubic trend.
The U.S. real interest rate is constructed by following Neumeyer and Perri (2005).
First, construct the monthly real interest rate = nominal interest rate - expected inflation. For nominal interest rate, we use 3-month U.S treasury bill. The expected
inflation is calculated as the average of past 3 month realization of CPI-based inflation.
Then we take an average of quarterly, obtained the quarterly U.S. real interest rates.

Appendix B. Stationary distribution under baseline calibration

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Figure 4: Stationary distribution under the baseline calibration

Note: Ergodic distribution under the baseline calibration. The x-axis is foreign debt,
b. Moments shown in Table 2 are calculated using this distribution.

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