• East Asian Economic Review
• /
• v.19 no.1
• /
• pp.39-70
• /
• 2015

This paper examines the effects of foreign direct investment (FDI) on South Asian economies' output growth, utilizing recent panel cointegration testing and estimation techniques. Annual panel data on eight SAARC (South Asian Association for Regional Cooperation) member countries' macroeconomic variables over the period 1960- 2013 are employed in empirical analysis. Using various heterogeneous panel cointegration and panel causality tests, a bi-directional relationship between FDI and growth is found. We find evidence for both FDI-led growth and growth-induced FDI hypotheses for the South Asian economies over the sample period. Individual member countries exhibit heterogeneity in terms of the direction or existence of causality subject to their idiosyncratic economic conditions. Among various regressors, FDI, financial development, human capital, and government consumption show the most significant positive effects on output growth. As determinants of FDI, GDP, financial development, human capital, and government consumption are found significant in the region. The bi-directional causality between FDI and growth is found robust to the inclusion of other control variables and using different estimation techniques.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.2
• /
• pp.99-109
• /
• 2021

This study aims to examine the causal links between the fiscal components, i.e., government expenditures (GE) and government revenues (GR), and their impact on the economic growth of the Association of Southeast Asian Nations (ASEAN) region. This analysis considered secondary panel data from 1990 to 2019 at an annual frequency. The data is obtained from the Asian Development Bank (ADB) and World Bank Database. A panel cointegration and panel DH causality (Dumitrescu and Hurlin) approach was employed on financial data at an annual frequency from 1990 to 2019. The findings from panel unit root and panel cointegration tests demonstrate that, at first, all the variables are stationary and cointegrated. The panel ARDL disclosed that GE has a long-run connection with GDP, is significantly and positively associated with economic growth in the long run, whereas GR is significant in the short run. The contribution of GE is high in sustaining economic growth as compared to GR. Also, cointegration regression disclosed that GE is more sensitive toward GDP, while GR is less elastic. Lastly, the findings reveal that bidirectional causality exists between GE and GR variables. These results have policy implications for sustainable economic growth in the ASEAN region.

• International Commerce and Information Review
• /
• v.14 no.3
• /
• pp.307-322
• /
• 2012

The purpose of this paper is to examine determinants of export to the East Asia region, using panel unit root, panel cointegration framework, panel VECM (vector error correction model), panel FMOLS (fully modified OLS). Different panel unit root tests confirm that the data series are integrated processes with unit roots. When applying cointegration tests to long-run effect for aggregate panel data, a primary concern is to construct the estimators in a way that does not constrain the transitional dynamics to be similar among different countries of the panel. The regression equations are estimated by various panel cointegration estimators. The panel data causality results reveal that exchange rates has unidirectional effects on export and GDP, and there exists bidirectional causality between export and GDP. Also, the results from the panel FMOLS tests overwhelmingly reject the null hypothesis of zero coefficient. The panel cointegrating vectors show that the export has positive relationship with the GDP and ODI (overseas direct investment).

• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.4
• /
• pp.173-183
• /
• 2022

The objective of this research is to examine the influence of the COVID-19 pandemic on stock markets in a few developing and developed countries. This study uses daily data from January 2020 to May 2021 and obtained from World Health Organization and Thomson Reuters. The secondary data was evaluated through panel econometric methodology that includes different unit root tests, and to analyze the long-run relationship between variables, panel cointegration techniques were applied. The long-run causality among variables was examined through Panel Vector Error Correction Model. The overall findings of this study suggest a long-run association exists between several cases and death with the stock returns of the GCC and other stock markets. Furthermore, the VECM model also identified a long-run causality running from COVID cases and death towards the stock rerun of both sets of stock markets. However, a subsequent Wald test yielded mixed results, indicating no short-run causality between cases and deaths and stock returns in both groups; however, in the case of GCC, several COVID-19 cases are having a causal impact on stock markets, which is notable in light of the fact that the death rate in GCC is significantly lower than in many developed and developing countries.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.9
• /
• pp.165-176
• /
• 2021

The paper has used the Solow-Swan growth model to analyze the long-term impact of credit market development and stock market development on economic growth in Asia from 2000 to 2019. The empirical model is performed with panel cointegration analysis by Common Correlated Effects (CCE) method with cross-sectional dependencies. The results find that there exists a cointegration relationship among stock market, credit market development, and economic growth. These results also show that financial structure improves the exact impact of financial development on economic growth, namely the opposite effect of stock market development and credit market development. Moreover, the Granger causality test reveals a bi-directional relationship between credit market development and economic growth, while only unidirectional causality from stock market development to economic growth for the whole group panel. And it is different for a specific country, according to Kónya's test. The view of the new structuralism does not apply in the Asian financial system when we estimate the Nonlinear Autoregressive Distributed Lag model (NARDL) to analyze the asymmetric relationship between financial structure and economic growth. On the whole, policymakers can draw on the findings to provide policy implications to improve their country's financial system as well as pursue the goal of sustainable economic growth.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.2
• /
• pp.77-88
• /
• 2021

The stock markets in the BRICS (Brazil, Russia, India, China and South Africa) countries are the leading emerging markets globally. Therefore, it is pertinent to ascertain the critical drivers of stock market development in these economies. The currrent study empirically investigates to identify the linkages between stock market development, key macro-economic factors and institutional factors in the BRICS economies. The study covers the time period from 2000 to 2017. The dependent variable is the country's stock market development and the independent variables consist of six macroeconomic variables and five institutional variables. The study employs a panel cointegration test, Fully Modified OLS (FMOLS), a Pooled Mean Group (PMG) approach and a heterogeneous panel non-causality test.The findings of the study indicate co-integration among the selected variables across the BRICS stock markets. Long-run estimations reveal that five macroeconomic variables and four variables related to institutional quality are positive and statistically significant. Further, short-run causalities between stock market capitalization and selected variables are detected through the test of non-causality in a heterogeneous panel setting. The findings suggest that policymakers in the BRICS countries should enhance robust macroeconomic conditions to support their financial markets and should strengthen the institutional quality drivers to stimulate the pace of stock market development in their countries.

• Journal of the Korean Regional Science Association
• /
• v.36 no.3
• /
• pp.29-40
• /
• 2020

The aims of this study to identify the relationship between regional economic growth and intraregional regional disparities. The 16 metropolitan area, the Capital region and the southeastern region of Korea were put in the spatial scope and the time range from 2005 to 2016. Regional gross domestic product data were used to show regional growth and intraregional disparity. Panel data for each spatial unit were established, panel unit root test and panel cointegration test were conducted to check the stability of the data. The DOLS method was used to identify relationship between regional economic growth and intraregional disparity, and the VECM model and Granger causality test was conducted to verify causality. The result of analysis of 16 metropolitan area units showed that the intraregional disparity increases as regional economic growth progresses. When the regional gross domestic product increased by 1%, the intraregional disparity increased by 1.258%, and there are short-term and long-term causality. Both the Capital region and the southeastern region had a mutual relationship between regional economic growth and intraregional disparity, but the disparity in the Capital region showed an increase and the southeastern region showed a decrease. The results of this study show that the regional disparity is increasing nationwide, but the Capital region and the southeastern region showed different stages of growth.

• Journal of Korea Port Economic Association
• /
• v.36 no.2
• /
• pp.109-124
• /
• 2020

Using panel data on freight rates and ship prices in the dry freighter market from January 2015 to December 2019, this study investigates the characteristics of shipping industry fluctuations. The analysis aims at two aspects of academic contribution. First, this study analyzes the relationship between shipping indicators and ship price based on separate dry-bulk ships, while the previous research considered the overall shipping index and weighted average ship prices. Second, the VAR model for the causality test is extended to a heterogeneous mixed panel model capable of limiting coefficients. There is a peak estimated by removing the cross-correlation problem, which is mainly raised in panel data analysis, using bootstrap estimation and solving the problem of information loss due to differences in non-stationary data. An empirical investigation of the causal relationship between economic fluctuations and ship price shows that the effect on the ship price from the freight is significant at the 1% level. This implies that there is a one-way relationship with demand in the shipping industry rather than a bilateral relationship.