capital mobility and business cycle synchronization

capital mobility and business cycle synchronization

1. IntroductionMethodologyEmpirical resultsConclusionReferences
Capital mobility and business cycle synchronization
in Sub-Saharan Africa: The role of the digital
economy
Simon Abendin, Duan Pingfang
Department of International Economics and Trade, Zhengzhou University Business
School, Zhengzhou City, Henan, PR China
May 10, 2024
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2. IntroductionMethodologyEmpirical resultsConclusionReferences
Outline
1
Introduction
2
Methodology
3
Empirical results
4
Conclusion
5
References
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3. IntroductionMethodologyEmpirical resultsConclusionReferences
Study background
Capital mobility, facilitated by foreign trade, monetary integration,
and financial market integration, is crucial for economic prosperity,
particularly in developing economies, according to various models
and policies
Trade concentration can cause diverging industrial structures, while
integration can induce higher synchronization
Economic theory provides no definitive guidance on the effect of
more significant trade on business cycle synchronization
Empirical studies show convergence in business cycle
synchronization
Research indicates that regions with greater financial integration
experience higher synchronized business cycles, while countries with
regulatory restrictions experience lower synchronization
However, low capital mobility in Sub-Saharan Africa leads to slow
economic progress (Abendin and Pingfang, 2021; Nguyen et al.,
2020; Zouri, 2020)
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4. IntroductionMethodologyEmpirical resultsConclusionReferences
Motivation
The literature on the relationship between capital mobility and
business cycle synchronization is inconclusive. Thus, they contain
both positive and negative impacts. Clarifying uncertainties and
providing new insights can contribute to the advancement of
knowledge.
The existing literature on capital mobility-business cycle
synchronization nexus has been centered on the implications of FDI
for business cycles without investigating the various transmission
channels of capital mobility on business cycles.
More importantly, how digitalization mediates the relationship
between capital mobility and business cycle synchronization remains
unexplored.
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5. IntroductionMethodologyEmpirical resultsConclusionReferences
Stylized Facts
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6. IntroductionMethodologyEmpirical resultsConclusionReferences
Stylized Facts
Figure 1:
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7. IntroductionMethodologyEmpirical resultsConclusionReferences
Data and Measurement
The dataset for this article covers 24 Sub-Saharan African (SSA)
countries for 2014-2019.
The dependent variable is business cycle synchronization between
country i and country j. It is measured using the economic activity
original series. Here, the real gross domestic product (GDP) growth
is used to proxy economic activity.
Our computation of business cycle synchronization (BCS) followed
Cerqueira and Martins (2009). A summarized form of Cerqueira
and Martins (2009)equation is stated as follows:
Where zjt and zit represent the real GDP of country i and country
j, compared with the correlation index based on the entire period.
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8. IntroductionMethodologyEmpirical resultsConclusionReferences
Data and Measurement
The main independent variables include:
The digital economy (DECON) . DECON is measured using the
following sub-indicators: Big Data Usage Per Capita(BDUPC)
E-government service(EGOV)per one thousand inhabitants fixed
broadband subscription per one thousand inhabitants(FBSPOTI)
mobile broadband subscription per one thousand inhabitants
(MBSPOTI) basic digital skills per hundred inhabitants
(BDSPHI)Electronic sharing ofinformation(ESI)by a country’s
businesses through social networks, clouds infrastructure among
others Selling online cross-border(SOCB)the number of
businesses doing cross-border online selling per hundred businesses
the number of internet user per capita(INTUPC).
We create the digital economy index using the principal component
analysis (PCA).
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9. IntroductionMethodologyEmpirical resultsConclusionReferences
Data and Measurement
The capital mobility (CAPMOB) . CAPMOB is measured
using the following channels:
Foreign direct investment flows(FDIF)
Portfolio equity flows(PEF)
Foreign direct investment stocks(FDIS)
Portfolio equity stocks(PES).
Control Variables:
Bilateral trade (BTRADE)
Fiscal policy (FISPOL)
Interest rate (INRATE)
Exchange rate stability (EXRASTA)
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10. IntroductionMethodologyEmpirical resultsConclusionReferences
Empirical model specification
We set up the business cycle synchronization equation as in Frankel and Rose
(1998). The empirical model for this article is stated as follows:
we extended Equation 6 to include the indirect effect of the digital economy
measured by :
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11. IntroductionMethodologyEmpirical resultsConclusionReferences
Econometric Strategies
This study recruited thePanel Corrected Standard Errors (PCSE)
approach for the estimations to reduce the problems associated with these
econometric issues. In principle, the Panel Corrected Standard Errors (PCSE)
estimator could be more efficient than the traditional ordinary least squares
(OLS) estimators.
In order to address the endogeneity problem, the study used thetwo-step
system-GMM,which eliminates any possible endogeneity and ensures that
the estimates are consistent and theimproved panel Granger causality
test developed by Xiao et al. (2021)to run a more robust test.
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12. IntroductionMethodologyEmpirical resultsConclusionReferences
The PCSE results on capital mobility, the digital
economy, and business cycle synchronization
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13. IntroductionMethodologyEmpirical resultsConclusionReferences
System-GMM results Capital mobility, the digital
economy, and business cycle synchronization.
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Panel Granger causality tests
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Marginal effects of CAPMOB on BCS as the DECON
increase.
Figure 2:
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16. IntroductionMethodologyEmpirical resultsConclusionReferences
Conclusion
Capital mobility leads to business cycle synchronization in sub-Saharan Africa
(SSA) economies
The digital digital economy leads to business cycle synchronization in
sub-Saharan Africa (SSA) economies
The digital economy complements capital mobility to increase business cycle
synchronization in SSA countries. Capital mobility and the digital economy
have a causal relationship with business cycle synchronization
The study reveals an important novelty in that the marginal effects on
business cycle synchronization increase when capital mobility in the SSA
interacts with the digital economy
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17. IntroductionMethodologyEmpirical resultsConclusionReferences
Thank you for your attention
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18. IntroductionMethodologyEmpirical resultsConclusionReferences
References
Abendin, S., and Pingfang, D. (2021). International Trade and Economic Growth in
Africa: The Role of the Digital Economy. Cogent Economics and Finance, 9(1).
https://doi.org/10.1080/23322039.2021.1911767
Cerqueira, P. A., and Martins, R. (2009). Measuring the determinants of business
cycle synchronization using a panel approach. Economics Letters, 102(2), 106–108.
https://doi.org/10.1016/j.econlet.2008.11.016
Nguyen, V. T. H., Hoang, T. T. T., and Nguyen, S. M. (2020). The effect of trade
integration on business cycle synchronization in East Asia. Journal of Asian
Finance, Economics and Business, 7(8), 225–231.
https://doi.org/10.13106/JAFEB.2020.VOL7.NO8.225
Xiao, J., Juodis, A., Karavias, Y., and Sarafidis, V. (2021). Improved Tests for
Granger Non-Causality in Panel Data. MPRA Paper, 107180.
Zouri, S. (2020). Business cycles, bilateral trade and financial integration: Evidence
from Economic Community of West African States (ECOWAS). International
Economics, 163, 25–43. https://doi.org/10.1016/j.inteco.2020.04.001 18 / 18