- Email: [email protected]
How do capital controls affect international trade?
Journal Pre-proof How do capital controls affect international trade? Dahai Fu, Li Cao
PII: DOI: Reference:
S0165-1765(19)30382-9 https://doi.org/10.1016/j.econlet.2019.108761 ECOLET 108761
To appear in:
Economics Letters
Received date : 12 August 2019 Revised date : 1 October 2019 Accepted date : 11 October 2019 Please cite this article as: D. Fu and L. Cao, How do capital controls affect international trade?. Economics Letters (2019), doi: https://doi.org/10.1016/j.econlet.2019.108761. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
© 2019 Published by Elsevier B.V.
*Highlights (for review)
Journal Pre-proof
Highlights This paper examines the impact of capital controls on international trade.
The capital controls are correlated more with exports rather than imports.
Inward capital controls reduce exports, while outward capital controls promote
pro of
exports.
urn a
lP
re-
The role of capital controls is conditional on the volume of trade flows.
Jo
*Title Page
Journal Pre-proof Title page
How do capital controls affect international trade?
a
pro of
Dahai Fua and Li Caoa School of International Trade and Economics, Central University of Finance and
Economics, Beijing 100081, China
Corresponding author: Dahai Fu (Email: [email protected]) Present address: School of International Trade and Economics 39 South College Road, Haidian Beijing 100081, China Acknowledgement
re-
Central University of Finance and Economics
lP
Dahai Fu acknowledges the financial support of the National Natural Science Foundation of China (No.71603275, 71941011) and CUFE First Class Research Project (No.
Jo
urn a
GMYL2019008).
*Manuscript Click here to view linked References
Journal Pre-proof How do capital controls affect international trade? Abstract Trade effects of capital controls have not been thoroughly examined empirically. Using a new dataset of capital controls on both inflows and outflows, we study the impact of capital controls on international trade by augmenting the gravity model with capital controls. The
pro of
results consistently show that capital controls are correlated more with exports rather than imports. Inward capital controls reduce exports, while outward capital controls promote exports.
Keywords: capital controls, international trade, gravity model JEL classification: F38; F14; F32
1. Introduction
re-
Capital controls have been widely used to protect economies from severe financial shocks. However, multinational enterprises typically prefer the freedom to move capital cross the border in order to optimize their operations. While the impact of capital controls or its counterpart, financial openness, on economic growth (Bekaert et al., 2005, 2011),
lP
capital mobility (Younas, 2011), inflation (Gruben and McLeod, 2002) and income inequality (Ni and Liu, 2019) have attracted much attention in recent studies, the effect of capital controls on international trade have not been thoroughly examined empirically. Tamirisa (1999) among very few related papers examines the effect of exchange and capital controls on trade for 1996 using gravity model and find that exchange and capital
urn a
controls shows significantly negative impact on bilateral exports. Different from earlier studies, we use a large sample of cross-country dataset, in which we can adopt panel data approach to deal with omitted variable bias by controlling for country fixed effects. We further distinguish the effects of inward and outward capital controls by utilizing a new dataset of capital controls from Fernández et al. (2016). To our best knowledge, this study is the first comprehensive cross-country analysis on the trade effects of capital controls, thereby offering practical implications for policymakers in
Jo
designing a roadmap of opening the capital account. Our results indicate a significant influence by capital controls on trade flows between a specific pair of countries. However, the capital controls are correlated more with exports rather than imports. The inward capital controls have negative impact on its exports, while outward capital controls have positive effects. This finding is robust in various specifications. 2. Data We use a new dataset of capital controls from Fernández et al. (2016) on both inflows
Journal Pre-proof and outflows for 100 countries over the period 1995 to 2015. It provides more granularity by distinguishing the direction and category of capital flows compared with the other two indicators commonly used to measure capital account liberalization proposed by Quinn and Toyoda (2008) and Chinn and Ito (2008). The bilateral trade, GDP and population data at the country-level are taken from World Development Indicator (WDI) database. The bilateral distance, language dummy, border dummy, landlocked dummy, and colony-related dummies are from CEPII
pro of
database. 3. Empirical specification
We conduct our investigation by using gravity model of international trade. A minor revision of the present paper is a modification of gravity equation by embedding the
(1)
re-
capital controls into it,
The dependent variable is the log of export flow for country i to j at time t, the vector contains other control variables that include country-specific variables such as gross domestic product (GDP) per capita and population of country i at time t, GDP per capita
lP
and population of country j at time t, as well as symmetric variables such as, distance between two countries, whether speaking the same language, whether having the same border, colony-related dummies. The main determinants of interest are the log of the inward capital controls (ICC) and outward capital controls (OCC) in countries i and j. The and
country i, while We let
capture the permanent exporting effect of the capital controls for
urn a
coefficients
and
provide information of permanent importing effect for country j.
be a generic representation of country-pair fixed effects that capture all
time-invariant country-pair-specific characteristics and permanent differences, and
be
a generic representation of exporters’ fixed effects that capture all time-invariant exporter-specific characteristics and permanent differences, and
be a generic
representation of importers’ fixed effects capture all time-invariant importer-specific be a generic representation for
Jo
characteristics and permanent differences, and
time-varying macroeconomic shocks that affect the countries in the sample identically. Finally,
is the idiosyncratic error term.
4. Results
4.1 Basic results Our baseline results are presented in Table 1. In Columns (1)-(3), we successively present the estimates for no controls, adding controls and adding time effect. The estimates of four variables of capital controls are statistically significant. Columns (4)-(5)
Journal Pre-proof provide further analyses, adding combination of country-specific and country-pair-specific fixed effects. After adding export, import country and country-pair fixed effects, the importing effect of the capital controls,
and
, loses its significance. It implies that
capital controls are correlated more with exports rather than imports. According to the estimates in Column (5), the point estimates are -0.231 and 0.227 for
and
,
respectively, taken literally, suggesting that a 10 percent point increase in the level of inward capital controls leads to about 2.31 percent point decrease in its exports and a 10 increase in its exports. Table 1 Trade effects of capital controls log(1+ICCi)
log(1+OCCi)
log(1+ICCj)
(1)
(2)
-3.227***
-0.786***
(0.0739)
(0.0458)
1.821***
0.765***
(0.0625)
(0.0381)
-2.258*** (0.0721)
log(1+OCCj)
1.058*** (0.0604) No
Time effect Country fixed effect Country-pair fixed effect Observations
(5)
-0.831***
-0.296***
-0.231***
(0.0409)
(0.0594)
(0.0401)
1.129***
0.252***
0.227***
(0.0347)
(0.0498)
(0.0335)
-0.683***
0.0316
0.0410
(0.0433)
(0.0407)
(0.0594)
(0.0401)
0.238***
0.614***
0.0393
0.0327
(0.0363)
(0.0345)
(0.0501)
(0.0338)
Yes
Yes
Yes
Yes
No
No
Yes
Yes
Yes
No
No
No
Yes
Yes
No
No
No
No
Yes
184,625
183,982
183,982
183,982
183,745
0.019
0.677
0.698
0.779
0.906
urn a
R-squared
(4)
-0.620***
lP
Other controls
(3)
re-
Variables
pro of
percent point increase in the level of outward capital controls leads to about 2.27 percent
Note: Significance levels 0.1, 0.05 and 0.01 are denoted by *, ** and ***, respectively. Robust standard errors are in parentheses. Other controlled variables that include country-specific variable such as GDP per capita, population, distance between two countries, language, border, three colony-related dummies (colonies after the end of the Second World War with the same colonizer, currently a colony relationship with each other, a colony relationship in history), and an indicator for the same country currently or in the history.
Jo
4.2 More regressions
Table 2 presents the various analyses under different experiments, which is intended to reassure the skeptical reader that our results are essentially insensitive to minor changes in the exact samples. Each of rows in Table 2 corresponds to a different sensitivity check. We only report estimates for the coefficients of interest for capital controls; other controls in gravity equation and the country dummies, year dummies as well as country-pair fixed effects are included in the regressions as appropriate but not reported.
Journal Pre-proof Table 2 Sensitivity analyses log(1+ICCj)
log(1+OCCj)
Observations
R-squared
-0.222*** (0.0504) -0.275*** (0.0403) -0.223*** (0.0401) -0.303*** (0.0439) -0.231*** (0.0405) -0.239*** (0.0408) -0.443*** (0.0417) -0.354*** (0.0385) -0.250*** (0.0466) -0.472*** (0.0506) -0.226*** (0.0583)
0.204*** (0.0443) 0.288*** (0.0342) 0.224*** (0.0336) 0.251*** (0.0381) 0.230*** (0.0339) 0.228*** (0.0340) 0.312*** (0.0344) 0.229*** (0.0319) 0.312*** (0.0418) 0.376*** (0.0364) 0.303*** (0.0583)
0.0214 (0.0502) 0.0353 (0.0402) 0.0378 (0.0402) 0.0378 (0.0454) 0.0440 (0.0410) 0.0409 (0.0416) -0.0057 (0.0409) 0.0856** (0.0394) 0.0794* (0.0480) -0.0706 (0.0448) 0.132** (0.0628)
0.0673 (0.0444) 0.0314 (0.0339) 0.0319 (0.0339) 0.0605 (0.0383) 0.0321 (0.0345) 0.0271 (0.0350) 0.0267 (0.0345) 0.0168 (0.0334) 0.0414 (0.0404) -0.0574 (0.0380) 0.0992* (0.0526)
112,250
0.922
181,892
0.906
182,570
0.906
158,320
0.897
179,663
0.904
175,834
0.905
157,085
0.914
160,495
0.914
149,839
0.891
81,788
0.935
101,957
0.874
pro of
Drop poorest (1%) countries Drop richest (1%) countries Drop East Asian countries Drop North American countries Drop South Asian countries Drop Middle East countries Drop Sub-Saharan African countries Drop Western European countries High-income countries Low-&Middle-income countries
log(1+OCCi)
re-
1995-2007
log(1+ICCi)
Note: Significance levels 0.1, 0.05 and 0.01 are denoted by *, ** and ***, respectively. Robust
lP
standard errors are in parentheses. Other controlled variables, time effect, country fixed effect and country-pair fixed effect are included in the regressions.
First, we do experiments selecting the sample before 2008 when the global financial crisis happened. We can see the results remain statistically negative for inward capital
urn a
controls and statistically positive for outward capital controls in country i. Next, we do the exercise to delete the observations of the poorest countries (in GDP per capita), richest countries (in GDP per capita) successively. We delete the observations at the lowest and the top one percentile of GDP per capita, respectively. However, our results do not seem to be affected sensitively by observations from a rich or poor country, suggesting the same findings on how the capital controls affect trade flows. Furthermore, we successively delete observations of East Asian, North American, South Asian, Middle East,
Jo
Sub-Saharan African and Western European countries. However, our results do not seem to depend sensitively on observations from a particular region of the world. Finally, we classify the sample according to the income level of the country based on the World Bank standard into high-income, low- and middle-income countries. We can find our previous results are not sensitive to the income level of the country. Our findings remain resilient: The inward capital controls have a negative effect on its exports while the outward capital controls have a positive effect. Nevertheless, it shows capital controls have a positive importing effect for low- and middle-income countries.
Journal Pre-proof Table 3 Quantile regressions log(1+ICCi)
log(1+OCCi)
log(1+ICCj)
log(1+OCCj)
Observations
0.2
-0.479***
0.227***
-0.0789
-0.0303
183,982
(0.0671)
(0.0498)
(0.0671)
(0.0537)
-0.351***
0.217***
-0.0410
0.0036
(0.0464)
(0.0345)
(0.0465)
(0.0372)
-0.233***
0.207***
-0.0060
0.0349
(0.0432)
(0.0320)
(0.0432)
(0.0346)
0.4
0.6
0.8
-0.123**
0.198***
(0.0568)
(0.0421)
pro of
Quantiles
0.0267
0.0642
(0.0568)
(0.0454)
183,982
183,982
183,982
Note: Significance levels 0.1, 0.05 and 0.01 are denoted by *, ** and ***, respectively. Robust standard errors are in parentheses. Controlled variables are included in each regression.
To investigate whether the relationship between capital controls and trade flows is conditional on the volume of international trade, we have estimated the quantile
re-
regression with quantiles of 0.2, 0.4, 0.6, and 0.8 respectively. The results are displayed in Table 3. As illustrated in Table 3, our previous findings do not change with quantiles. Inward capital controls and exports are all negatively correlated in all quantiles, while outward capital controls are positively correlated with exports in all quantiles. However, the coefficients have shown a clear pattern: the magnitude of coefficients of inward and
lP
outward capital controls are decreasing from low quantiles to higher quantiles. Therefore, the quantile regression results support that the role of capital controls is conditional on the volume of trade flows.
urn a
5. Conclusions
This article explored the impact of capital controls on international trade. We distinguish the inward capital controls from outward capital controls. We are the first in the existent literature finding a robust and consistent results, that is, inward capital controls have negative impact on the exports while outward capital controls have positive impact on the exports. This finding is not sensitive to the different samples although the role of
Jo
capital controls is conditional on the volume of trade flows.
References
Bekaet, G., Harvey, C.R., Lundblad, C., 2005. Does financial liberalization spur growth? Journal of Financial Economics 77(1), 3-55. Bekaet, G., Harvey, C.R., Lundblad, C., 2011. Financial openness and productivity. World Development 39(1), 1-19. Chinn, M.D., Ito, H. 2008. A new measure of financial openness. Journal of Comparative Policy Analysis: Research and Practice 10: 309-322.
Journal Pre-proof Fernández, A., Klein, M.W., Rebucci, A., Schindler, M., Uribe, M., 2016. Capital control measures: A new dataset. IMF Economic Review 64(3), 548-574.
Gruben, W.C., McLeod, D., 2002. Capital account liberalization and inflation. Economics Letters 77(2), 221-225. Ni, N., Liu, Y., 2019. Financial liberalization and income inequality: A meta-analysis based on cross-country studies. China Economic Review 56, forthcoming. Quinn, D., Toyoda, A.M., 2008. Does capital account liberalization lead to economic
pro of
growth? An empirical investigation. Review of Financial Studies 21(3), 1403-1449. Tamirisa, N.T. 1999. Exchange and capital controls as barriers to trade. IMF Staff Papers 46(1), 69-88.
Younas, J., 2011. De facto financial openness and capital mobility. Economics Letters
Jo
urn a
lP
re-
112(1), 60-62.
PII: DOI: Reference:
S0165-1765(19)30382-9 https://doi.org/10.1016/j.econlet.2019.108761 ECOLET 108761
To appear in:
Economics Letters
Received date : 12 August 2019 Revised date : 1 October 2019 Accepted date : 11 October 2019 Please cite this article as: D. Fu and L. Cao, How do capital controls affect international trade?. Economics Letters (2019), doi: https://doi.org/10.1016/j.econlet.2019.108761. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
© 2019 Published by Elsevier B.V.
*Highlights (for review)
Journal Pre-proof
Highlights This paper examines the impact of capital controls on international trade.
The capital controls are correlated more with exports rather than imports.
Inward capital controls reduce exports, while outward capital controls promote
pro of
exports.
urn a
lP
re-
The role of capital controls is conditional on the volume of trade flows.
Jo
*Title Page
Journal Pre-proof Title page
How do capital controls affect international trade?
a
pro of
Dahai Fua and Li Caoa School of International Trade and Economics, Central University of Finance and
Economics, Beijing 100081, China
Corresponding author: Dahai Fu (Email: [email protected]) Present address: School of International Trade and Economics 39 South College Road, Haidian Beijing 100081, China Acknowledgement
re-
Central University of Finance and Economics
lP
Dahai Fu acknowledges the financial support of the National Natural Science Foundation of China (No.71603275, 71941011) and CUFE First Class Research Project (No.
Jo
urn a
GMYL2019008).
*Manuscript Click here to view linked References
Journal Pre-proof How do capital controls affect international trade? Abstract Trade effects of capital controls have not been thoroughly examined empirically. Using a new dataset of capital controls on both inflows and outflows, we study the impact of capital controls on international trade by augmenting the gravity model with capital controls. The
pro of
results consistently show that capital controls are correlated more with exports rather than imports. Inward capital controls reduce exports, while outward capital controls promote exports.
Keywords: capital controls, international trade, gravity model JEL classification: F38; F14; F32
1. Introduction
re-
Capital controls have been widely used to protect economies from severe financial shocks. However, multinational enterprises typically prefer the freedom to move capital cross the border in order to optimize their operations. While the impact of capital controls or its counterpart, financial openness, on economic growth (Bekaert et al., 2005, 2011),
lP
capital mobility (Younas, 2011), inflation (Gruben and McLeod, 2002) and income inequality (Ni and Liu, 2019) have attracted much attention in recent studies, the effect of capital controls on international trade have not been thoroughly examined empirically. Tamirisa (1999) among very few related papers examines the effect of exchange and capital controls on trade for 1996 using gravity model and find that exchange and capital
urn a
controls shows significantly negative impact on bilateral exports. Different from earlier studies, we use a large sample of cross-country dataset, in which we can adopt panel data approach to deal with omitted variable bias by controlling for country fixed effects. We further distinguish the effects of inward and outward capital controls by utilizing a new dataset of capital controls from Fernández et al. (2016). To our best knowledge, this study is the first comprehensive cross-country analysis on the trade effects of capital controls, thereby offering practical implications for policymakers in
Jo
designing a roadmap of opening the capital account. Our results indicate a significant influence by capital controls on trade flows between a specific pair of countries. However, the capital controls are correlated more with exports rather than imports. The inward capital controls have negative impact on its exports, while outward capital controls have positive effects. This finding is robust in various specifications. 2. Data We use a new dataset of capital controls from Fernández et al. (2016) on both inflows
Journal Pre-proof and outflows for 100 countries over the period 1995 to 2015. It provides more granularity by distinguishing the direction and category of capital flows compared with the other two indicators commonly used to measure capital account liberalization proposed by Quinn and Toyoda (2008) and Chinn and Ito (2008). The bilateral trade, GDP and population data at the country-level are taken from World Development Indicator (WDI) database. The bilateral distance, language dummy, border dummy, landlocked dummy, and colony-related dummies are from CEPII
pro of
database. 3. Empirical specification
We conduct our investigation by using gravity model of international trade. A minor revision of the present paper is a modification of gravity equation by embedding the
(1)
re-
capital controls into it,
The dependent variable is the log of export flow for country i to j at time t, the vector contains other control variables that include country-specific variables such as gross domestic product (GDP) per capita and population of country i at time t, GDP per capita
lP
and population of country j at time t, as well as symmetric variables such as, distance between two countries, whether speaking the same language, whether having the same border, colony-related dummies. The main determinants of interest are the log of the inward capital controls (ICC) and outward capital controls (OCC) in countries i and j. The and
country i, while We let
capture the permanent exporting effect of the capital controls for
urn a
coefficients
and
provide information of permanent importing effect for country j.
be a generic representation of country-pair fixed effects that capture all
time-invariant country-pair-specific characteristics and permanent differences, and
be
a generic representation of exporters’ fixed effects that capture all time-invariant exporter-specific characteristics and permanent differences, and
be a generic
representation of importers’ fixed effects capture all time-invariant importer-specific be a generic representation for
Jo
characteristics and permanent differences, and
time-varying macroeconomic shocks that affect the countries in the sample identically. Finally,
is the idiosyncratic error term.
4. Results
4.1 Basic results Our baseline results are presented in Table 1. In Columns (1)-(3), we successively present the estimates for no controls, adding controls and adding time effect. The estimates of four variables of capital controls are statistically significant. Columns (4)-(5)
Journal Pre-proof provide further analyses, adding combination of country-specific and country-pair-specific fixed effects. After adding export, import country and country-pair fixed effects, the importing effect of the capital controls,
and
, loses its significance. It implies that
capital controls are correlated more with exports rather than imports. According to the estimates in Column (5), the point estimates are -0.231 and 0.227 for
and
,
respectively, taken literally, suggesting that a 10 percent point increase in the level of inward capital controls leads to about 2.31 percent point decrease in its exports and a 10 increase in its exports. Table 1 Trade effects of capital controls log(1+ICCi)
log(1+OCCi)
log(1+ICCj)
(1)
(2)
-3.227***
-0.786***
(0.0739)
(0.0458)
1.821***
0.765***
(0.0625)
(0.0381)
-2.258*** (0.0721)
log(1+OCCj)
1.058*** (0.0604) No
Time effect Country fixed effect Country-pair fixed effect Observations
(5)
-0.831***
-0.296***
-0.231***
(0.0409)
(0.0594)
(0.0401)
1.129***
0.252***
0.227***
(0.0347)
(0.0498)
(0.0335)
-0.683***
0.0316
0.0410
(0.0433)
(0.0407)
(0.0594)
(0.0401)
0.238***
0.614***
0.0393
0.0327
(0.0363)
(0.0345)
(0.0501)
(0.0338)
Yes
Yes
Yes
Yes
No
No
Yes
Yes
Yes
No
No
No
Yes
Yes
No
No
No
No
Yes
184,625
183,982
183,982
183,982
183,745
0.019
0.677
0.698
0.779
0.906
urn a
R-squared
(4)
-0.620***
lP
Other controls
(3)
re-
Variables
pro of
percent point increase in the level of outward capital controls leads to about 2.27 percent
Note: Significance levels 0.1, 0.05 and 0.01 are denoted by *, ** and ***, respectively. Robust standard errors are in parentheses. Other controlled variables that include country-specific variable such as GDP per capita, population, distance between two countries, language, border, three colony-related dummies (colonies after the end of the Second World War with the same colonizer, currently a colony relationship with each other, a colony relationship in history), and an indicator for the same country currently or in the history.
Jo
4.2 More regressions
Table 2 presents the various analyses under different experiments, which is intended to reassure the skeptical reader that our results are essentially insensitive to minor changes in the exact samples. Each of rows in Table 2 corresponds to a different sensitivity check. We only report estimates for the coefficients of interest for capital controls; other controls in gravity equation and the country dummies, year dummies as well as country-pair fixed effects are included in the regressions as appropriate but not reported.
Journal Pre-proof Table 2 Sensitivity analyses log(1+ICCj)
log(1+OCCj)
Observations
R-squared
-0.222*** (0.0504) -0.275*** (0.0403) -0.223*** (0.0401) -0.303*** (0.0439) -0.231*** (0.0405) -0.239*** (0.0408) -0.443*** (0.0417) -0.354*** (0.0385) -0.250*** (0.0466) -0.472*** (0.0506) -0.226*** (0.0583)
0.204*** (0.0443) 0.288*** (0.0342) 0.224*** (0.0336) 0.251*** (0.0381) 0.230*** (0.0339) 0.228*** (0.0340) 0.312*** (0.0344) 0.229*** (0.0319) 0.312*** (0.0418) 0.376*** (0.0364) 0.303*** (0.0583)
0.0214 (0.0502) 0.0353 (0.0402) 0.0378 (0.0402) 0.0378 (0.0454) 0.0440 (0.0410) 0.0409 (0.0416) -0.0057 (0.0409) 0.0856** (0.0394) 0.0794* (0.0480) -0.0706 (0.0448) 0.132** (0.0628)
0.0673 (0.0444) 0.0314 (0.0339) 0.0319 (0.0339) 0.0605 (0.0383) 0.0321 (0.0345) 0.0271 (0.0350) 0.0267 (0.0345) 0.0168 (0.0334) 0.0414 (0.0404) -0.0574 (0.0380) 0.0992* (0.0526)
112,250
0.922
181,892
0.906
182,570
0.906
158,320
0.897
179,663
0.904
175,834
0.905
157,085
0.914
160,495
0.914
149,839
0.891
81,788
0.935
101,957
0.874
pro of
Drop poorest (1%) countries Drop richest (1%) countries Drop East Asian countries Drop North American countries Drop South Asian countries Drop Middle East countries Drop Sub-Saharan African countries Drop Western European countries High-income countries Low-&Middle-income countries
log(1+OCCi)
re-
1995-2007
log(1+ICCi)
Note: Significance levels 0.1, 0.05 and 0.01 are denoted by *, ** and ***, respectively. Robust
lP
standard errors are in parentheses. Other controlled variables, time effect, country fixed effect and country-pair fixed effect are included in the regressions.
First, we do experiments selecting the sample before 2008 when the global financial crisis happened. We can see the results remain statistically negative for inward capital
urn a
controls and statistically positive for outward capital controls in country i. Next, we do the exercise to delete the observations of the poorest countries (in GDP per capita), richest countries (in GDP per capita) successively. We delete the observations at the lowest and the top one percentile of GDP per capita, respectively. However, our results do not seem to be affected sensitively by observations from a rich or poor country, suggesting the same findings on how the capital controls affect trade flows. Furthermore, we successively delete observations of East Asian, North American, South Asian, Middle East,
Jo
Sub-Saharan African and Western European countries. However, our results do not seem to depend sensitively on observations from a particular region of the world. Finally, we classify the sample according to the income level of the country based on the World Bank standard into high-income, low- and middle-income countries. We can find our previous results are not sensitive to the income level of the country. Our findings remain resilient: The inward capital controls have a negative effect on its exports while the outward capital controls have a positive effect. Nevertheless, it shows capital controls have a positive importing effect for low- and middle-income countries.
Journal Pre-proof Table 3 Quantile regressions log(1+ICCi)
log(1+OCCi)
log(1+ICCj)
log(1+OCCj)
Observations
0.2
-0.479***
0.227***
-0.0789
-0.0303
183,982
(0.0671)
(0.0498)
(0.0671)
(0.0537)
-0.351***
0.217***
-0.0410
0.0036
(0.0464)
(0.0345)
(0.0465)
(0.0372)
-0.233***
0.207***
-0.0060
0.0349
(0.0432)
(0.0320)
(0.0432)
(0.0346)
0.4
0.6
0.8
-0.123**
0.198***
(0.0568)
(0.0421)
pro of
Quantiles
0.0267
0.0642
(0.0568)
(0.0454)
183,982
183,982
183,982
Note: Significance levels 0.1, 0.05 and 0.01 are denoted by *, ** and ***, respectively. Robust standard errors are in parentheses. Controlled variables are included in each regression.
To investigate whether the relationship between capital controls and trade flows is conditional on the volume of international trade, we have estimated the quantile
re-
regression with quantiles of 0.2, 0.4, 0.6, and 0.8 respectively. The results are displayed in Table 3. As illustrated in Table 3, our previous findings do not change with quantiles. Inward capital controls and exports are all negatively correlated in all quantiles, while outward capital controls are positively correlated with exports in all quantiles. However, the coefficients have shown a clear pattern: the magnitude of coefficients of inward and
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outward capital controls are decreasing from low quantiles to higher quantiles. Therefore, the quantile regression results support that the role of capital controls is conditional on the volume of trade flows.
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5. Conclusions
This article explored the impact of capital controls on international trade. We distinguish the inward capital controls from outward capital controls. We are the first in the existent literature finding a robust and consistent results, that is, inward capital controls have negative impact on the exports while outward capital controls have positive impact on the exports. This finding is not sensitive to the different samples although the role of
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capital controls is conditional on the volume of trade flows.
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