Domestic Financial Participation and ExternalVulnerability in Emerging Economies1
Alan Finkelstein ShapiroTufts University
Victoria NuguerIADB-RES
IT Conference, BCBMay 24, 2019
1The views in this paper are solely the responsibility of the authors and should not beinterpreted as representing the views of the Inter-American Development Bank, itsExecutive Boards, or its Management.
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 1 / 35
Introduction
Firm financial participation in EMEs is very low: only 20% of firmshave access to and use bank credit (vs. 70% in AEs)
In general, models do not include the extensive margin of financialparticipation; effects shown might be different when financialinclusion varies
Additionally, EME are vulnerable to external shocks
How does financial participation of firms / financial development ofan economy affect its sensitivity to external financial shockstransmitted via the banking system?
I Do shocks similar to the global financial crisis affect countries withmore/less financial participation differently?
Financial inclusion: access to financial services = financialparticipation = financial development = credit-to-GDP ratio =deposits-to-GDP ratio
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 2 / 35
What we do in this paper
1 Two-country RBC modelI banking frictions (Gertler and Kiyotaki, 2010) and AE banks lend to
EME banks (Cuadra and Nuguer, 2018)I financially integrated and excluded firmsI endogenous firm entry– extensive marginI quality of capital shocks in the AE transmitted to the EME through
cross-border bank flows
2 Empirical evidenceI impact of U.S. banks’ net charge-offs on cross-border bank flows of
EMEsI relevance of the degree of EME domestic financial participationI impact of U.S. increase in interest rate (working on it)
Higher firm financial participation in EMEs shows smaller domesticpropagation of adverse financial shocks in AEs (in the model and inthe data!)
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 3 / 35
What we do in this paper
1 Two-country RBC modelI banking frictions (Gertler and Kiyotaki, 2010) and AE banks lend to
EME banks (Cuadra and Nuguer, 2018)I financially integrated and excluded firmsI endogenous firm entry– extensive marginI quality of capital shocks in the AE transmitted to the EME through
cross-border bank flows
2 Empirical evidenceI impact of U.S. banks’ net charge-offs on cross-border bank flows of
EMEsI relevance of the degree of EME domestic financial participationI impact of U.S. increase in interest rate (working on it)
Higher firm financial participation in EMEs shows smaller domesticpropagation of adverse financial shocks in AEs (in the model and inthe data!)
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 3 / 35
IntuitionA negative quality of K shock emanating from AE, ↓ Ψt ,
I ↓ cross-border bank flows to EME, EME ↓ banks’ net worth, ↓ EMEdomestic credit –financial mechanism
I EME currency depreciates and consumption ↓ –RER mechanism
I financially-included firms face ↓ credit, ↓ n. firms, ↓ output (bothincluded and excluded firms)
What is the different impact across EMEs of a financial AE shockgiven 6= credit-to-GDP ratio? (higher credit-to-GDP)
I without endog. firm entry: ↓↓ in cross-border bank flows and a largerreaction of the RER mechanism
I with endog. firm entry: ↓ cost of entry, households adjust better to theshock and react less, smoother reaction of the economy (firms areconsidered assets), cross-border bank flows react less, fall in credit islower
Under endogenous firm entry: higher firm financial participation inEMEs is negatively associated with the size of the domesticpropagation of adverse foreign financial shocks emanating from AEs
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 4 / 35
IntuitionA negative quality of K shock emanating from AE, ↓ Ψt ,
I ↓ cross-border bank flows to EME, EME ↓ banks’ net worth, ↓ EMEdomestic credit –financial mechanism
I EME currency depreciates and consumption ↓ –RER mechanism
I financially-included firms face ↓ credit, ↓ n. firms, ↓ output (bothincluded and excluded firms)
What is the different impact across EMEs of a financial AE shockgiven 6= credit-to-GDP ratio? (higher credit-to-GDP)
I without endog. firm entry: ↓↓ in cross-border bank flows and a largerreaction of the RER mechanism
I with endog. firm entry: ↓ cost of entry, households adjust better to theshock and react less, smoother reaction of the economy (firms areconsidered assets), cross-border bank flows react less, fall in credit islower
Under endogenous firm entry: higher firm financial participation inEMEs is negatively associated with the size of the domesticpropagation of adverse foreign financial shocks emanating from AEs
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 4 / 35
Related Literature
Effects of foreign shocks in EMEs via the banking system – Aoki,Benigno and Kiyotaki (2015); Cuadra and Nuguer (2018)
Financial inclusion and monetary policy or labor markets – Galı,Lopez-Salido and Valles (2004); Mehrotra and Yetman (2014);Yetman (2017); Alberola and Urrutia (2019); Epstein and FinkelsteinShapiro (2019)
Firm entry and macro fluctuations – seminal work of Bilbiie, Ghironiand Melitz (2012), applied to two-country model Ghironi and Melitz(2005), Cacciatore, Ghironi and Sebunovs (2015), Cacciatore, Fioriand Ghironi (2016)
Our contribution: mix of these three elements comparing differentdegrees of domestic firm financial participation
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 5 / 35
Layout of the presentation
1 Why do we say firm financial participation or domestic financialdevelopment (scarcity of data to measure financial participation)?
2 Theoretical Model: banking frictions, fin. included and excluded firmsand endogenous firm entry
3 Why endogenous firm entry is relevant: matching the model with thedata
4 Robustness checks
5 Summary
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 6 / 35
Data Firm Financial Part. and Dom. Financial Dev.
10 20 30 40 50 60 70 800
5
10
15
20
25
30
35
40
45
BRA-2009
CHL-2006
CHL-2010
COL-2017
CZE-2009
HUN-2009
HUN-2013
IND-2014
POL-2009
POL-2013
RUS-2009
RUS-2012
ZAF-2007
TUR-2008
TUR-2013
ARG-2010
COL-2010
MEX-2010
=0.5116
ARG-2006ARG-2017
COL-2006
CZE-2013
IDN-2009
IDN-2015
MEX-2006
UGA-2006UGA-2013
Source: Authors’ calculations using data from the BIS and the WBES.
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 7 / 35
Data Firm Financial Part. and Dom. Financial Dev.
0 10 20 30 40 50 60 70 80 90 1000
5
10
15
20
25
30
35
40
45
=0.3171
Source: Authors’ calculations using data from the Global Financial DevelopmentDatabase and the WBES.
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 8 / 35
The Model Overview
Two-country RBC model
Banking frictions (Gertler and Kiyotaki, 2010)
AE banks lend to EME banks through cross-border bank flows
(Cuadra and Nuguer, 2018)
Firm financial participation: financially-included and -excluded firms
Endogenous firm entry (Bilbliie, Ghironi and Melitz, 2012) and
endogenous measure of both included and excluded firms
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 9 / 35
The Model Agents
AE (H) and EME (∗, F) – share of financial participation and bank
credit-GDP ratio differ, and AE banks lend to EME banks
Households
Domestic perfectly-competitive intermediate-goods firms (produce
using labor and capital – financially included and excluded firms)
Domestic monopolistically-competitive wholesale-goods firms (with
endogenous entry)
Final good firms (domestic and imported)
Capital producers
Banks – cross border bank flows
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 10 / 35
The Model Households and Firm Creation
A household chooses consumption, ct , labor supply, Le,t and Li ,t , realdomestic deposits, Bd ,t , the desired number of wholesalefinancially-included and -excluded firms, Ni ,t+1 and Ne,t+1, andmeasure of new wholesale firms needed to hit those targets, N i
E ,t andNeE ,t , max E0 ∑∞
t=0 βtu(ct , Le,t , Li ,t) subject to
ct + ψeNeE ,t + ψiN
iE ,t + Bd ,t = we,tLe,t + wi ,tLi ,t
+ Rt−1Bd ,t−1 + de,tNe,t + di ,tNi ,t + Πe,t + Πi ,t + Πk,t + Πb,t ,
and the evolution of each category of wholesale firms j ∈ e, i
Nj ,t+1 = (1− δ)(Nj ,t +N j
E ,t
)First-order conditions are standard for ct , Le,t , Lie,t , and Bd ,t
Firm creation conditions for each domestic wholesale firm category
ψj = (1− δ)EtΞt+1|t (dj ,t+1 + ψj )
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 11 / 35
The Model Domestic Production Structure
Financially included (i) and excluded (e) firms
1 perfectly-competitive intermediate-goods firms –measure 1
2 monopolistically-competitive wholesale firms –with endogenous entry
and exit, and endogenous measure
Intermediate-goods e firms use internal resources to purchase capital
and they are intensive in labor
Intermediate-goods i firms borrow funds from banks to purchase
capital from capital producers
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 12 / 35
The Model Intermediate-Goods Firms e vs. i
Financially-excluded firms
maxLe,t ,ke,t+1
E0
∞
∑t=0
Ξt|0mce,tze,t(ke,t)
αe (Le,t)1−αe − we,tLe,t
−Qe,t [ke,t+1 − (1− δ)ke,t ]
Financially-included firms (si ,t = ki ,t+1/Ψt+1), αi > αe
maxLi ,t ,ki ,t+1,si ,t
E0
∞
∑t=0
Ξt|0
mci ,tzi ,t (ki ,t)
αi (Li ,t)1−αi − wi ,tLi ,t
−Qi ,t [ki ,t+1 − (1− δ) ki ,t ] +Qi ,tsi ,t − Rki ,tQi ,t−1si ,t−1
Combining the FOCs for physical capital demand and bank-credit
demand
Rki ,t+1 = Ψt+1
[αimci ,tzi ,t(ki ,t)αi−1(Li ,t)1−αi +Qi ,t+1 (1− δ)
]Qi ,t
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 13 / 35
The Model Monopolistically-Competitive Wholesale Firms
Firm-creation decision is part of the household’s problem
Ωj denotes the potential mass of firms in firm category j
Each incumbent firm produces a single differentiated good ωj (good
produced and firm) j ∈ e, i
Total output for each domestic wholesale firm category
Yj ,t =
[∫ωj∈Ωj
yj ,t(ωj )ε−1
ε dωj
] εε−1
Each incumbent firm purchases inputs from their intermediate-goods
counterparts at price mcj ,t , with the real price of their output given
by ρj ,t(ωj ) = pj ,t(ωj )/Pt
The optimal pricing condition is ρj ,t(ωj ) = [ε/(ε− 1)]mcj ,t
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 14 / 35
The Model Total Domestic Production
Total output from financially-excluded and financially-included
wholesale firms, Ye,t and Yi ,t
Firms maximize profits
YP,tPP,t − Yi ,tPi ,t − Ye,tPe,t
We assume a perfectly-competitive domestic output aggregator, with
a CES production function
YP,t =
[(1− αy )
1φy Y
φy−1φy
i ,t + (αy )1
φy Yφy−1
φye,t
] φyφy−1
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 15 / 35
The Model Capital Producers
Choose investment in both sector, i and e, to maximize profits
Et
∞
∑s=t
Ξt|s Qe,s ie,s − ie,s [1 + Φ (ie,s/ie,s−1)] +Qi ,s ii ,s−
ii ,s [1 + Φ (ii ,s/ii ,s−1)]
subject to ie,s = ke,s − (1− δ)ke,s−1
and ii ,s = si ,s − (1− δ)ki ,s−1
The first order conditions yield the price of capital goods Qj ,t for eachfirm category j ∈ e, i:
Qj ,t = 1 + Φ(
ij ,tij ,t−1
)ij ,t + ij ,t−1Φ′
(ij ,t
ij ,t−1
)−EtΞt+1|t
(ij ,t+1
ij ,t
)2
Φ(ij ,t+1
ij ,t
)
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 16 / 35
The Model AE BanksGertler and Kiyotaki (2010) with cross-border bank flows
raise deposits from AE households, bd ,t
lend
I to AE non-financial firms, si ,tI to EME banks, bt
Assets Liabilities
Qi ,tsi ,t bd ,t
Qbtbt nwt
Incentive compatibility constraint
V (si ,t , bt , bd ,t) ≥ θ (Qi ,tsi ,t +Qb,tbt) .
Aggregate net worth of AE banks
NWt = (σ + ξ) (Rki ,tQi ,t−1Si ,t−1 + Rb,tQb,t−1Bt−1)− σRt−1Bd ,t−1.
At the end of the period t − 1 the value of the banks satisfies
V (st−1, bt−1, bd ,t−1) = EtΞt|t−1
(1− σ)nwt + σ
[max
st ,bt ,bd ,t
V (st , bt , bd ,t)
]
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 17 / 35
The Model EME Banks
raise funds from
I EME households, b∗d ,t
I AE banks, b∗t
make loans to EME non-financial firms, s∗i ,t
Assets Liabilities
Q∗i ,ts∗i ,t b∗d ,t
Q∗btb∗t
nw∗t
Incentive compatibility constraint
V ∗(s∗i ,t , b
∗t , b∗d ,t
)≥ θ∗
(Q∗i ,ts
∗i ,t −Q∗b,tb
∗t
)Aggregate net worth of EME banks
NW ∗t = (σ∗ + ξ∗)R∗ki ,tQ
∗i ,t−1S
∗i ,t−1 − σ∗R∗b,tQ
∗b,t−1B
∗t−1 − σ∗R∗t−1B
∗d ,t−1
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 18 / 35
The Model Banks Summary
From the problem of AE banks
EtΞt+1|tΛt+1Rki ,t+1 = EtΞt+1|tΛt+1Rb,t+1 + Φ [exp(Bt − B)− 1]
H banks are indifferent between providing funds to intermediate goodsdomestic firms and to F banks because the expected return on both assetsis equalized in equilibrium.From the problem of EME banks
EtΞ∗t+1|tΛ∗t+1R
∗ki ,t+1 = EtΞ∗t+1|tΛ
∗t+1R
∗b,t+1
In this framework, the cross-border bank flows’ return transmits a shock ineconomy H economy to economy F through the impact on the return ondomestic assets. Additionally, the expected discounted rate of return onthe cross-border bank asset is equal to the one on loans tointermediate-goods i firms in H: Et(Rb,t+1) = Et(R∗b,t+1)
RERt+1
RERt
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 19 / 35
The Model Final Goods Production
Total domestically-produced output and imported output from the
EME
Yt =
[α
1φaa Y
φa−1φa
H,t + (1− αa)1
φa Yφa−1
φa
F ,t
] φaφa−1
Standard first-order conditions
YH,t = αa (ρH,t)−φa Yt
and
YF ,t = (1− αa) (ρF ,t)−φa Yt ,
where ρj ,t = Pj ,t/Pt with j ∈ (H,F )
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 20 / 35
The Model Market Clearing
Total demand for output produced in H must be equal to what is
produced, so that
YH,t +
(1−m
m
)Y ∗H,t = YP,t
Market clearing in each domestic firm category implies that
Ne,tye,t = ze,t(ke,t)1−αe (Le,t)
αe and Ni ,tyi ,t = zi ,t(ki ,t)1−αi (Li ,t)
αi
The resource constraint in H is given by
Yt = ct + ii ,t + ie,t + ψiNiE ,t + ψeN
eE ,t
The current account
RERtQb,tBt − RERtRb,tQb,t−1Bt−1 =
(1−m
m
)Y ∗H,t
PH,t
Pt− YF ,tToTt
PH,t
Pt
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 21 / 35
Quantitative Analysis
Calibration
Steady state comparison of high and low financial participation
Role of endogenous firm entry
Empirical validation of main results
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 22 / 35
Quan. Analysis CalibrationParameter Value Source or Target
Preferences and technology parametersβ Subjective discount factor 0.985 DSGE literatureσc Coefficient of relative risk aversion 2 DSGE literatureξ Inverse of Frisch elastisticity of labor supply 1 DSGE literatureκ AE labor weight on the ut. function 16.215 Match ave. hours workedκ∗ EME labor weight on the ut. function 9.809 Match ave. hours workedψi AE cost of creating an i firm 0.031 1% of GDP per capitaψ∗i EME cost of creating an i firm 0.253 10% of GDP per capitaψe AE cost of creating an e firm 0.001 Ni /N = 0.8ψ∗e EME cost of creating an e firm 0.032 N∗i /N∗ = 0.2αy AE Share of dom. produced goods 0.644 PiYi /PY = 0.80α∗y EME Share of dom. produced goods 0.433 P∗i Y
∗i /P∗Y ∗ = 0.70
αi Share of capital in the i prd. function 0.32 DSGE literatureαe Share of capital in the e prd. function 0.20 Endog. FE literatureδ Depreciation rate 0.025 DSGE literatureε Elasticity of substitution of wholesale firms 6 Endog. FE literatureφy Elasticity of substitution for total domestic output 5 Baseline assumptionφa Elasticity of substitution of imported goods 1.557 CN (2018)m Size of the AE 0.900 CN (2018)
Banking parametersσ Survival rate 0.972 GK (2010)ξ Start-up fraction 0.002 GK (2010)θ fraction of divertable assets 0.5042 Rki − R = 110θ∗ fraction of divertable assets 0.8952 Rki − R = 110Φ Country-specific int rate premium 0.01 SGU (2003)
ShockΨ AE quality of capital shock -0.05 GK (2010)
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 23 / 35
Quan. Analysis High and low financial participation SS
↑ financial participation, ↓ sunk-entry cost, ↓ Mg.C. of creating ifirms, ↑ ki ,t , Li ,t↑ Y ∗, ↑ c∗, ↑ S∗, ↑↑ B∗d , and ↑ B∗
Variable Baseline 50 Percent FFP 80 Percent FFP
Output Y ∗ 1.69 2.292 2.836Consumption-to-Output ratio c∗/y ∗ 0.640 0.628 0.625Capital i-to-Output ratio k∗i /y ∗ 4.331 5.681 6.079Foreign claims-to-Output ratio B∗/y ∗ 0.039 0.051 0.055Deposits B∗d/y ∗ 0.259 0.340 0.364Included f. labor-to-capital ratio L∗i /k∗i 0.028 0.025 0.022Excluded f. labor-to-capital ratio L∗e/k∗e 0.050 0.043 0.039Net worth-to-Output ratio NW ∗/y ∗ 0.917 1.203 1.288Included to total firms ratio N∗i /(N∗i +N∗e ) 0.167 0.336 0.410Labor Prod∗i 5.733 6.575 7.269Labor Prod∗e 4.873 5.589 6.179
ψ∗i /Y ∗ 0.150 0.0218 0.007
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 24 / 35
Quan. Analysis Low financial participation IRFs
0 5 10 15 20 25-5
-4.5
-4
0 5 10 15 20 25-14
-12
-10
-8
-6
0 5 10 15 20 25
-1.5
-1
-0.5
0 5 10 15 20 25
-4
-3
-2
-1
0 5 10 15 20 25
-0.5
0
0.5
1
1.5
0 5 10 15 20 25-1.5
-1
-0.5
0 5 10 15 20 25
-2
-1.5
-1
-0.5
0
0 5 10 15 20 25
-1
-0.5
0
0 5 10 15 20 25
-3
-2
-1
0 5 10 15 20 25-1.4
-1.3
-1.2
-1.1
-1
0 5 10 15 20 25
-1
-0.5
0
0 5 10 15 20 25
0
0.2
0.4
Conditional on a financial shock in the AE, greater domestic financialparticipation by EME firms limits the adverse effect of the shock in theEME
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 25 / 35
Quan. Analysis High and low financial participation IRFs
0 5 10 15 20 25-5
-4.5
-4
0 5 10 15 20 25-14
-12
-10
-8
-6
0 5 10 15 20 25
-1.5
-1
-0.5
0 5 10 15 20 25
-4
-3
-2
-1
0 5 10 15 20 25
-0.5
0
0.5
1
1.5
0 5 10 15 20 25-1.5
-1
-0.5
0 5 10 15 20 25
-2
-1.5
-1
-0.5
0
0 5 10 15 20 25
-1
-0.5
0
0 5 10 15 20 25
-3
-2
-1
0 5 10 15 20 25-1.4
-1.3
-1.2
-1.1
-1
0 5 10 15 20 25
-1
-0.5
0
0 5 10 15 20 25
0
0.2
0.4
0.6
Conditional on a financial shock in the AE, greater domestic financialparticipation by EME firms limits the adverse effect of the shock in theEME
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 26 / 35
Quan. Analysis The Role of Endogenous Firm Entry
0 5 10 15 20 25-5
-4.5
-4
0 5 10 15 20 25
-15
-10
-5
0 5 10 15 20 25
-1.5
-1
-0.5
0 5 10 15 20 25
-4
-3
-2
-1
0
0 5 10 15 20 25
-2
-1.5
-1
-0.5
0
0 5 10 15 20 25
-4
-3
-2
-1
0
0 5 10 15 20 25
-2
-1
0
0 5 10 15 20 25
-3
-2
-1
0
0 5 10 15 20 25
-5
-4
-3
0 5 10 15 20 25
-1.6
-1.4
-1.2
-1
-0.8
-0.6
Conditional on a financial shock in the AE, a model without firm entryprompts that higher EME financial participation leads to a larger drop inB∗ and consumption: goes against what we find in the data
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 27 / 35
Quan. Analysis Empirical Validation
Using a sample of EMEs, we want to characterize the link between
the response of these economies to external shocks and the average
degree of participation of firms in the domestic banking system
Strong link between share of firms with bank credit and the bank
credit to GDP ratio across economies
⇒ we use bank credit to GDP ratio as a rough proxy for firm
financial participation
Financial shocks in the AE are interpreted U.S. commercial bank’s net
charge-offs
and the transmission of the shocks works through the cross-border
bank flows
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 28 / 35
Quan. Analysis Data
U.S. commercial banks’ net charge-offs (St. Louis Fed)
I value of those loans that commercial banks assume will not be paid
I the shock is associated to a fall in the value of banks’ assets that
corresponds to a quality of capital shock in the AE
I Lambertini and Uysal (2013) and Cuadra and Nuguer (2018)
Cross-border bank flows (BIS)
I foreign claims of U.S. banks for specific economies
I financial shocks in the U.S. were transmitted to EMEs via cross-border
bank flows –Cuadra and Nuguer (2018)
Bank-credit-to-GDP ratio (BIS), real exchange rate (Stein,
Fernandez, Rosenow, and Zuluaga, 2018), consumption (IFS)
Data are logged and HP-filtered
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 29 / 35
Quan. Analysis Specification
Bit
GDPit= β0 + β1NCOt ×
¯(Cri
GDPi
)+ ε i + ιt + uit
BitGDPit
quarterly cross-border bank flows from U.S. to i
NCOt net charge-offsCri
GDPicredit-to-GDP ratio of i at certain t
ιt time-fixed effect
ε i firm-fixed effect
Cit = δ0 + δ1RERit−1 ׯ(
CriGDPi
)+ δ2RERit−1 + ε i + ιt + zit
Cit quarterly real consumption of country i
RERit real-exchange rate
Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 30 / 35
Quan. Analysis Empirical Results EME
Dependent variable: Foreign claims to GDPBit
GDPitConsumption Cit
(1) (2) (3) (4) (5) (6)
US net charge-offs NCOt 0.102 0.102(0.070) (0.070)
Credit to GDPi ,2000:1−2018:3 0.001** 0.004***(0.001) (0.090)
Credit to GDPi ,2000:1−2018:3 × NCOt -0.149** -0.149** -0.149*(0.068) (0.068) (0.071)
Real Exchange Rate RERit−1 -0.230*** -0.192** -0.192**(0.074) (0.078) (0.077)
Credit to GDPi ,2000:1−2018:3 × RERit−1 0.198** 0.279** 0.279**(0.090) (0.122) (0.122)
Constant -0.001 -0.000 -0.006 -0.002 -0.005 0.002(0.001) (0.000) (0.014) (0.001) (0.007) (0.014)
Country FE No Yes Yes No Yes YesTime FE No No Yes No No Yes
Observations 1,022 1,022 1,022 873 873 873R-squared 0.012 0.013 0.176 0.283Number of countries 14 14 14 14 14 14
Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1Notes: Authors’ calculations using data from the Bank for International Settlements (BIS) and the St. Louis FRED database
for the period 2000Q1-2018Q3. NCOt , RERit , Cit andBit
GDPitare real, logged and detrended using the Hodrick-Prescott filter.
Credit to GDP2000:1−2018:3 is the average bank credit to GDP for the period 2000:1-2018:3. Foreign claims to GDP correspondto foreign claims of each country on U.S. banks to GDP ratio. The sample of EMEs used is comprised of: Argentina, Brazil,Chile, Colombia, India, Indonesia, Israel, Korea, Malaysia, Mexico, Russia, South Africa, Thailand, and Turkey.
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Quan. Analysis Empirical Results EME
Dependent variable: Foreign claims to GDPBit
GDPitConsumption Cit
(1) (2) (3) (4) (5) (6)
US net charge-offs NCOt 0.102 0.102(0.070) (0.070)
Credit to GDPi ,2000:1−2018:3 0.001** 0.004***(0.001) (0.090)
Credit to GDPi ,2000:1−2018:3 × NCOt -0.149** -0.149** -0.149*(0.068) (0.068) (0.071)
Real Exchange Rate RERit−1 -0.223*** -0.224*** -0.192**(0.034) (0.035) (0.047)
Credit to GDPi ,2000:1−2018:3 × RERit−1 0.167*** 0.168** 0.304**(0.046) (0.046) (0.092)
Constant -0.001 -0.000 -0.006 -0.002 0.001*** 0.002(0.001) (0.000) (0.014) (0.001) (0.000) (0.013)
Country FE No Yes Yes No Yes YesTime FE No No Yes No No Yes
Observations 1,022 1,022 1,022 871 871 871R-squared 0.012 0.013 0.176 0.087 0.088 0.279Number of countries 14 14 14 14 14 14
Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1Notes: Authors’ calculations using data from the Bank for International Settlements (BIS) and the St. Louis FRED database
for the period 2000Q1-2018Q3. NCOt , RERit , Cit andBit
GDPitare real, logged and detrended using the Hodrick-Prescott filter.
Credit to GDP2000:1−2018:3 is the average bank credit to GDP for the period 2000:1-2018:3. Foreign claims to GDP correspondto foreign claims of each country on U.S. banks to GDP ratio. The sample of EMEs used is comprised of: Argentina, Brazil,Chile, Colombia, India, Indonesia, Israel, Korea, Malaysia, Mexico, Russia, South Africa, Thailand, and Turkey.
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Quan. Analysis Summary of results for EMEs
1 For countries with a higher credit-to-GDP ratio, a shock to U.S. NCO
affects their cross-border bank flows-to-GDP ratio less than for
countries with lower credit-to-GDP ratio
2 For countries with a higher credit-to-GDP ratio, a change in the RER
prompts a smaller effect on consumption than for countries with lower
credit-to-GDP ratio
Our model replicates these results
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Quan. Analysis Robustness checks
Other measures of credit-to-GDP ratio
Deposits-to-GDP ratio
Lag of RER
AE and deposits-to-GDP ratio
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Conclusion
We have presented empirical evidence of the implication of different
level of firm participation in the banking system in EMEs and the
consequences for the response to external financial shock, such as the
one of the global financial crisis
We build a two-country RBC model with banking frictions,
endogenous firm entry, and limited domestic financial participation by
firms
Higher financial participation in EMEs limits the effect of adverse
external financial shocks on EME financial and macro aggregates,
with endogenous firm entry playing a critical role in the
volatility-reducing effects of larger firm financial participation: results
are consistent with the data
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Finkelstein Shapiro and Nuguer Dom FinPart and Ext Vulnerability in EMEs 35 / 35
Additional Tables Empirical Results AEDependent variable: Foreign claims to GDP
BitGDPit
Consumption Cit
(1) (2) (3) (4) (5) (6)
US net charge-offs NCOt 0.314*** 0.314***(0.095) (0.095)
Credit to GDPi ,2000:1−2018:3 0.001** -0.001(0.001) (0.001)
Credit to GDPi ,2000:1−2018:3 × NCOt -0.247*** -0.247** -0.249**(0.090) (0.090) (0.091)
Real Exchange Rate RERit -0.029 -0.016 -0.016(0.041) (0.039) (0.039)
Credit to GDPi ,2000:1−2018:3 × RERit 0.039 0.018 0.019(0.044) (0.040) (0.039)
Constant -0.003** -0.001*** -0.174*** 0.000 0.004 -0.012**(0.001) (0.000) (0.049) (0.001) (0.004) (0.006)
Country FE No Yes Yes No Yes YesTime FE No No Yes No No Yes
Observations 1,521 1,521 1,521 1,551 1,551 1,551R-squared 0.029 0.298 0.497Number of countries 21 21 21 21 21 21
Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1Notes: Authors’ calculations using data from the Bank for International Settlements (BIS) and the St. Louis FRED database
for the period 2000Q1-2018Q3. NCOt , RERit , Cit andBit
GDPitare real, logged and detrended using the Hodrick-Prescott filter.
Credit to GDP2000:1−2018:3 is the average bank credit to GDP for the period 2000:1-2018:3. Foreign claims to GDP correspondto foreign claims of each country on U.S. banks to GDP ratio. The sample of AE used is comprised of: Australia, Austria,Belgium, Canada, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Japan, Luxembourg, Netherlands, New Zealand,Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom.
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Additional Figures
-1-.5
0.5
1H
P of
Log
U.S
. NC
O
1990q1 1992q1 1994q1 1996q1 1998q1 2000q1 2002q1 2004q1 2006q1 2008q1 2010q1 2012q1 2014q1 2016q1 2018q1
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