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This paper empirically examines the relationship between foreign direct investment, financial development and other macroeconomic variables like trade openness, domestic investment and labour force and that of GDP per capita in select South Asian countries, i.e. India, Sri Lanka and Pakistan for the period 1990–2018.

The study uses various econometrics tools such as Pedroni, Kao and Johansen–Fisher panel cointegration test, Panel FMOLS and DOLS and Granger causality in order to analyse the long-run and short-run dynamics among the variables under consideration.

The results of the panel data estimation techniques employed imply that there is a short-run causality running from GDP per capita to FDI and financial development, and results from FMOLS and DOLS indicate that FDI and financial development have positive impacts on GDP per capita in the countries under consideration.

In this paper, we use a dynamic macroeconomic modelling framework to examine the effect of FDI and financial development on per capita income in three major south Asian economies, which are categorized as three Non-Least Developed Contracting States under the South Asian Free Trade Area (SAFTA), 2006, established with an aim to facilitate free trade among them. Considering the diversity of the level of growth experienced by these economies, the study uses appropriate panel regression techniques. Therefore, in addition to proper formulation of policies directed towards scaling up of export and import levels, the respective authorities should also take care that the political stability and institutional quality are maintained.

The purpose of this paper is to examine whether remittance inflow stimulate electricity consumption in India with other macroeconomic variables such as FDI, trade openness and urbanization in energy demand function from 1975–2017.

We have applied structural break and co-integration tests for stationarity and long-run relationship between the variables. The Toda–Yamamatoo causality is employed for investigation of causal relationship between the variables, and robustness of causality linkages is also tested by applying innovative accounting approach (IAA).

Our empirical analysis shows there is presence of long-run relationship among the variables. We find that remittance inflows stimulate electricity consumption in India. Industrialization is positively linked with electricity demand. However, trade openness declines the electricity consumption, but urbanization increases it. Furthermore, remittances inflows cause electricity consumption.

On the basis of findings, we conclude that due to positive impacts of remittances inflows, trade openness and urbanization, policymakers in the Indian economy need to be careful while designing sustainable environment policy. Otherwise, any sustainable environment policy in the name of protecting green environment will hamper the growth of remittance inflows, urbanization and FDI. If this exists, it may be argued that sustainable growth in India will not be possible in the face of sustainable environment policy.

The purpose of this paper is to empirically examine the effectiveness of foreign aid in improving economic growth prospects in the South Asian region from 1996 to 2017.

A sample of eight South Asian countries for the period 1996–2017 is being considered for this study. This study uses various econometrics tools such as Pedroni and Johansen–Fisher panel cointegration test, panel fully modified ordinary least square and panel dynamic ordinary least square (PDOLS) to ascertain the long-run and short-run dynamics among the variables under consideration.

The empirical results found that long-run, as well as the short-run relationship, exist among foreign aid, economic growth, investment, financial deepening, price stability and trade openness of the South Asian economies. The authors also found unidirectional causality running from foreign aid to economic growth. Both the long-run relationship as well as short-run causality between foreign aid and economic growth is unequivocally positive.

This study uses a dynamic macroeconomic modeling framework to assess the impact of aid flows on economic growth in South Asian economies. Taking into account the diversity of level of growth experienced by the eight countries in the Asian region, this study uses an appropriate regression technique, i.e. PDOLS whose results are robust. Therefore, the policymakers in these countries are well-advised to implement suitable policy measures to ensure optimum utilization of foreign capital resources garnered by way of receipt of foreign aid and build on for stronger future economic growth.

The purpose of this paper is to empirically investigate whether inward remittance leads to export performance in selected South Asian economies over the time period of 1993–2017.

The stationarity of the variables is checked by Levin, Lin and Chu t, Breitung t-stat., Im, Pesaran and Shin W-stat., ADF–Fisher and Philips–Perron–Fisher panel unit root tests. Panel Granger Causality is used to verify the short-run causality. Pedroni’s, Kao’s and Johansen–Fisher panel cointegration approaches are employed to examine the long-run relationship among the variables. Panel VECM is used to confirm the existence of a long-run relationship among the variables.

Panels FMOLS and DOLS show that remittance inflows have negatively impacted the export performance of the selected South Asian countries during the study period. Granger Causality and VECM test confirm the existence of short-run and long-run relationship among the variables. The authors conclude that inward remittance is affecting export performance negatively during the study period. Furthermore, inward remittances occupy a major source of development finance for selected South Asian countries.

The study uses a dynamic macroeconomic modeling framework to assess the inward remittance on export performance in South Asian countries. Taking into account the diversity of the level of growth experienced by the five countries in the Asian region, the study uses an appropriate regression technique, i.e. panel dynamic OLS whose results are robust. As exports are a proven way to further economic growth, this study fills a vital gap in the literature by ascertaining the degree of impact of remittances in influencing outbound exports from the South Asian region.

The purpose of this paper is to empirically examine the effectiveness of foreign aid in improving economic growth prospects in the sub-Saharan Africa (SSA) region from 1993 to 2017.

A sample of 45 SSA countries for the period 1993–2017 is considered for this study. The study uses various econometrics tools such as Pedroni and Kao’s cointegration test, Johansen-Fisher Panel cointegration test, FMOLS and PDOLS in order to ascertain the long-run and short-run dynamics among the variables under consideration.

The empirical results find that long-run and short-run relationships exist among foreign aid, economic growth, investment, financial deepening, price stability and trade openness of the SSA economies. The authors also find unidirectional causality running from foreign aid to economic growth. The policymakers in these countries are well-advised to implement suitable policy measures to build on the growth momentum created by foreign aid inflows.

The study uses a dynamic macroeconomic modeling framework to assess the impact of aid flows on economic growth in the SSA region. Taking into account the diversity of level of growth experienced by the 45 countries in the region, the study uses an appropriate regression technique, i.e., panel dynamic OLS whose results are robust. The finding is also supported by the Granger-causality test and robust cointegration techniques.

The purpose of this paper is to empirically investigate whether market size and its growth rate, along with financial development indicators, affect human capital in selected south Asian economies over the time period from 1984 to 2015.

The stationarity of the variables are checked by LLC, IPS, ADF and Phillips–Perron panel unit-root tests. Pedroni’s and Kao’s panel co-integration approaches are employed to examine the long-run relationship among the variables. To estimate the coefficients of co-integrating vectors, both PDOLS and FMOLS techniques are used. The short-term and long-run causalities are examined by panel granger causality.

From the empirical results, the authors found that both the market size and financial development play an important role in the development of human capital in the selected south Asian economies. It is evident that a large market size and faster degree of financial development in the selected countries result in better human capital formation.

There are a number of studies on the impact of financial development indicators on human capital and economic growth, but there is hardly any study that considers market size and its growth rate along with financial development indicators with human capital in the context of south Asian economies. The study fills this research gap.

The purpose of this paper is to investigate the dynamic relationship between 19 pandemic and government actions, such as governmental response index and economic support packages.

The authors use a panel dataset of 10 American and Latin countries for the period spanning from January 2020 to April 2021 to analyze the effect of government actions on stock market returns. The authors provide robust test results that improve the understanding of the impact of the pandemic on stock market indices through the break-up structure method and the new measure of Covid-19 extracted from Narayan et al. (2021) study.

Empirical results show the harmful effect of the corona virus on stock prices, hence the risk adverse behavior of investors. On the other hand, the quantitative approach reveals that the positive impact of government actions is degraded during Covid-19.

This article highlight that government actions may be effective in reducing new infections but could generate perverse economic impact through increasing uncertainty. The authors conclude that the adjustment of macroeconomic factors and the integration of financial news improve the forecasting performance of the model based on health news.

The purpose of this paper is to examine the relationship between financial inclusion (FI) and economic growth in India.

To measure FI, a multidimensional time-varying index is proposed following the Human Development Index method. The long-run relationship between FI and economic growth is examined by using the autoregressive distributed lag (ARDL) approach to cointegration and nonlinear ARDL approach. Further, the direction of causality is investigated by employing the Toda–Yamamoto Granger causality test.

The linear cointegration test confirms a long-run relationship between FI and economic growth for India. The improvement in both demand-side and supply-side financial services has a positive impact on economic growth. These results suggest that India can attain long-run economic growth by improving the coverage of FI. However, there is no evidence of nonlinear cointegration, indicating that there is no asymmetric effect of FI on economic growth. Further, the causality test shows that FI granger causes economic growth but not vice versa.

The major limitation of the study is the availability of time series data for all important variables. The index for both demand- and supply-side indicators can be extended with several other important variables in later date once the data are available for those variables.

As the study confirms that FI is one of the main drivers of economic growth, it is suggested that the policy maker emphasizing on financial sector reforms can enjoy economic growth in the long run, especially in developing countries. Therefore, the government and policy makers need to address the issues involved in access to financial services to spur economic growth.

The study examines the long-run relationship between FI and economic growth employing ARDL bound testing approach and nonlinear ARDL approach, separately for demand-side and supply-side indicators. Further, the study uses the Toda–Yamamoto granger causality to find the direction of causal flow between FI and economic growth.

The purpose of this study is to examine the impact of the COVID-19 pandemic on Association of Southeast Asian Nations (ASEAN) Islamic and conventional equities.

To study the impact of the COVID-19 pandemic on ASEAN Islamic and conventional equities, first, the authors calculated the volatility by using exponential generalized autoregressive conditional heteroscedasticity methodology and then used Wavelet methodology to see the co-movement between the volatility and returns of ASEAN equity market indicators and COVID-19 cases.

The authors find that until the beginning of August, COVID-19 adversely relates to the returns of both the indices. The conventional index seemed to have increased volatility during the time period, whereas the Islamic index seemed to have declined volatility.

To the best of the authors’ knowledge, this is one of the very few studies examining the impact of the COVID-19 pandemic on ASEAN Islamic and conventional equities. Additionally, this study adds value by comparing Islamic and conventional equities.

This paper aims to empirically examine the effect of Coronavirus disease 2019 (COVID-19) pandemic on cryptocurrency market returns with particular attention to top five cryptocurrencies and COVID-19 confirmed and death cases.

The study applies the linear Toda and Yamamoto and nonlinear Diks and Panchenko Granger causality test to know the causal relationship of cryptocurrencies with COVID-19 pandemic. The study also uses the Narayan and Popp endogenous two structural break tests to capture the break period of the sample.

The findings of the study confirm the existence of unidirectional causal relation from COVID-19 confirmed and death cases to cryptocurrency price returns. While examining the break periods, the post-break period result indicates the presence of unidirectional linear causality from COVID-19 confirmed cases to Bitcoin and Ethereum price returns. This shows that prior knowledge of COVID-19 pandemic growth helps to predict the return of cryptocurrencies.

The study suggests the investors or crypto lovers to observe the growth of COVID-19 situations during their investment in cryptocurrency markets.