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This study scrutinizes the impact of economic globalization on ecological footprint while endogenizing economic growth and energy consumption during 1990–2018 in India.

For time series analysis, the standard unit root test has been employed to unveil the integration order. Then, the cointegration was confirmed using autoregressive distributed lag (ARDL) analysis. Further, the study executed the dynamic ARDL simulation model to estimate long-run and short-run results along with simulation and robotic prediction.

The cointegration analysis confirms the existence of a long-run association among variables. Further, economic globalization reduces the ecological footprint in the long-run. Similarly, energy consumption decreases the ecological footprint. In contrast, economic growth spurs the ecological footprint in India.

The present study makes valuable and original contributions to the literature by applying a multivariate ecological footprint function, assessing the impact of economic globalization on ecological footprint while considering economic growth and energy consumption in India.

The purpose of this study is to analyze short- and long-run market-sensitive drivers of housing affordability. The study highlights an ongoing housing affordability crisis in an emerging market context by also providing an empirical tool to combat the crisis.

To investigate determinants of uniquely constructed effective housing affordability index and house price to income ratio index, the author uses a bound testing approach to cointegration and error correction models, besides causality tests, variance decompositions and impulse response functions. This study uses Turkish data for the period of 2007 M06 and 2017 M12.

The evidence suggests that the housing affordability crisis is mainly driven by credit expansion, rent and construction costs. A sensible housing policy response would target these variables. This evidence suggests that housing affordability mostly depends on housing market dynamics rather than policies because of the exogeneous/cyclical natures of the drivers.

Data constraints shape the study. A regional or an aggregate-level panel study cannot be developed because of a lack of data. This limitation inevitably results in the exclusion of relevant socio-economic/political factors and is also the main reason for the lack of comparative analysis in a cross-country setting.

This study argues that dependency on neoliberal housing market practices seems the underlying reason for the lack of efficient policy answers and the ongoing affordability crisis. From a policymaking perspective, the study suggests that necessary policy measures to resolve the housing affordability crisis may give a specific emphasis on housing rent, housing credit volume and construction costs as the major components of the crisis.

This study develops a novel measure and presents a new conceptual framework by combining quantitative research methods and policymaking in housing affordability. In this respect, to the best of the author’s knowledge, this is the first work to comparatively investigate the determinants of uniquely developed monthly housing affordability measurements.

The purpose of this paper is to re‐examine the stock market integration and short‐run dynamic interactions between the Malaysian stock market and the stock markets of its major trading partners (the USA, Japan, Singapore, China and Thailand).

Weekly stock indices spanning from January 1992 to May 2008 is analysed using autoregressive distributed lag (ARDL) bound testing approach and vector autoregression (VAR) framework.

Stock markets of Malaysia and its major trading partners are found to be integrated. To some extent, it is found that trade does matter for stock market integration. Additional, geographical proximity and close relationship between the countries further contributes towards a greater integration between them. To move forward to a greater financial integration among these countries, trade liberalisation, including reduction or removal of trade and investment barriers would be necessary.

This paper is among the first attempts to use ARDL and VAR frameworks to examine integration among the stock markets of Malaysia and its major trading partners. The findings of the study would shed some empirical lights for the purpose of policy making.

The purpose of this paper is to examine how specific macroeconomic indicators and conditions impact short- and long-run loan delinquency rates among US commercial banks under various economic episodes.

The study employs an autoregressive distributed lag framework (ARDL) and error correction model in its examination of how loan delinquency rates are impacted by specific macroeconomic variables and conditions.

This study finds that in both the short and long run, a percentage growth in macroeconomic indicators, such as industrial productivity and private domestic investments, reduces loan delinquency rates among commercial banks, given all things being equal. Additionally, this study also finds that adverse macroeconomic conditions, such as inflation, economic policy uncertainty and volatility, associated with specific macroeconomic variables, such as investment growth, etc., tend to worsen loan delinquency rates. Empirical results further suggest that among the various macroeconomic conditions examined, inflationary pressures tend to have the most significant heightening impact on loan delinquency rates among commercial banks.

The uniqueness of this study, compared to similar studies found in the literature, has to do with its verification of potential association between loan delinquency rates and specific hitherto unexamined macroeconomic conditions. Compared to similar studies on loan delinquency, this study collectively examines how conditions of uncertainty, volatility and expectations of macroeconomic conditions shape loan delinquency rates among commercial banks.

Previous studies have mostly estimated there to be a symmetric effect in the Foreign direct investment (FDI) inflow regarding the economic growth of Central, East and Southeast European (CESEE) countries. However, for the CESEE countries, as well as for the majority of countries around the world, there has been no study that has estimated the symmetric and asymmetric effect of outward FDI on economic growth. The main objective of this study is to estimate whether the relation between outward FDI and economic growth in CESEE countries is symmetric or asymmetric.

This study includes a sample based on eight CESEE countries. The authors used the linear and non-linear autoregressive distributed lag (ARDL) model and annual data for the period from 1990 to 2020.

In the long run, in the linear ARDL model, a significant symmetrical effect due to OFDI on the economic growth of Romania and Slovenia was found, while in the non-linear ARDL model, a significant asymmetric effect of OFDI on the economic growth of Bulgaria, Poland, Romania, Russia, Slovenia and Slovakia was found. In six out of the eight countries, asymmetry was found while symmetry was found in the other two. Poorer symmetry results can be ascribed to the lack of linear model neglecting the asymmetric behaviour of the positive and negative change decomposition as part of the OFDI movement, which leads to the wrong conclusion.

This is the first study to evaluate the asymmetric effect of outward FDI on the economic growth of eight CESEE countries.

This paper aims to reexamine the relationship between financial openness and financial development in Ghana.

The study applied maximum likelihood estimation and autoregressive distributed lag approach and tested Granger causality using quarterly data from 1990:1 to 2020:4.

This study revealed a long-run equilibrium relationship between financial openness and development, indicating that financial openness is a critical factor in Ghana’s financial development. Therefore, the study recommends with caution that policies aimed at promoting financial openness could be an effective way to encourage sustainable financial development in Ghana, as financial openness alone may not bring the desired outcome.

The study contributes to the existing body of knowledge by providing empirical evidence of the link between financial openness and financial sector development in Ghana. Future research could delve deeper into the mechanisms through which financial openness affects financial development, exploring potential channels and transmission mechanisms.

The findings suggest that policymakers, particularly the Ministry of Finance and the Bank of Ghana, should prioritize policies aimed at promoting financial openness. This includes continued efforts toward financial liberalization and creating an environment conducive to domestic and international financial transactions. Moreover, policies aimed at increasing trade openness, boosting real GDP and maintaining moderate real interest rates are essential for fostering financial sector development.

Enhancing financial sector development can have significant implications for society, including increased access to financial services, improved economic opportunities and enhanced overall economic stability. By promoting financial openness and development, policymakers would contribute to poverty reduction, job creation and overall socio-economic development. The study bridges the gap between theory and practice by providing empirical evidence supporting the theoretical proposition that financial openness stimulates financial sector development.

This study fills a crucial gap in the literature on the effects of financial openness on Ghana’s financial sector development. It focuses on Ghana, which liberalized its financial sector in 1988 as part of the overall economic reforms in 1983, and this justifies the starting point of this paper in 1990, as there are no adequate data before 1990. The study uses principal component analysis to construct an index that measures financial development. The study considers the recent financial crises in Ghana in 2017 and underscores the importance of understanding the link between financial openness and financial development, which becomes useful for policymakers and researchers studying financial system development in sub-Saharan Africa which includes Ghana.

This study aims to empirically examine how economic policy uncertainty emanating from three major global economic blocks (the US, the Chinese and the European Union) and volatility in global oil prices influence international trade.

The study uses quarterly data spanning the period between 1995 and 2014 in an autoregressive distributed lag framework.

This study finds that economic policy uncertainty conditions associated with the US and the Chinese economies tend to have significant negative or constraining impact on key components of international trade. Further analysis suggests that between the two leading economies (the US and the Chinese economies), economic policy uncertainty emanating from the US economy tend to have much more constraining impact on dynamics of international trade than the Chinese economy all things being equal.

This study’s findings carry significant strategic planning and policy implications for international trade dependent firms or corporations and economies. For instance, for multi-national corporations or firms whose products and services depend heavily on cross-border trade, understanding and taking into consideration prevailing economic policy dynamics emanating from the US and the Chinese economies in product and services demand forecast, and other strategic moves could be critical in minimizing potential adverse effects on projected performance or growth targets.

The uniqueness of this study’s approach stems from its assessment of how perception of uncertainty among economic agents about economic policies originating from three noted global economic blocks impacts international trade. In other words, instead of traditional factors or conditions surmised to influence variability in trend associated with international trade found in related studies, this study rather examines how perceptions of uncertainty about prevailing or yet to be enacted economic policy within specific global economic block impacts international trade.

The purpose of this paper is to test the dynamic linkages among the stock markets of four South Asian countries (India, Pakistan, Bangladesh and Sri Lanka) in the backdrop of trade interdependency.

Listed indices are used to serve the proxy of stock markets of four countries for the period: January 2000–December 2018. The study uses the autoregressive distributed lag model and Granger causality techniques in multivariate frameworks while focusing on intraregional trade as an exogenous factor for testing the long- and short-run causality in the given data set, hence raising the quality of statistical inference.

The results highlight that India and Pakistan are net exporters to the South Asian region, while Bangladesh and Sri Lanka are net importers from the region. While testing the stock markets linkages, the expanded intraregional trade volumes (exports plus imports) have occurred with the significant cointegration of stock markets of India and Pakistan with the other stock markets in the long run. In the short run, the stock markets of India, Pakistan and Sri Lanka report bidirectional causality without having significant spillovers of intraregional trade on the stock prices.

The study relies on the multivariate techniques with stock prices and regional trade share as the exogenous variables. Further the regulatory, political and economic conditions of sample countries are fundamentally different which in turn affect their degree of trade interdependency and integration between the stock markets.

Nonsignificant cointegration of the stock markets of Sri Lanka and Bangladesh highlights the possibility of portfolio diversification in the long run, while the significant bidirectional causalities between the stock markets highlight the lesser degree of portfolio diversifications in the short run.

Pioneer efforts are made to examine the dynamic linkages between the South Asian stock markets while focusing on regional trade interdependency. The results provide new insight in the dynamics of stock returns of South Asian stock markets in the backdrop of intraregional trade.

This study examines how specific micro-level macroeconomic indicators influence corporate performance volatility among US corporate bodies in the short run.

The study employs error correction autoregressive distributed lagged (ARDL) model (ECM) to examine how micro-level variables influence volatility associated with corporate performance in the short run.

This paper finds that disaggregated or micro-level variables examined, tend to exhibit features that are not readily apparent from the aggregate variable from which such variables are derived. For instance, reported empirical estimate suggests that, growth in expenditures on services and nondurable goods tend to lower volatility associated with corporate performance, whereas government expenditures and expenditures on durable goods rather worsens volatility associated with corporate performance, all things being equal. Additionally, presented empirical estimates further provide evidence suggesting that macroeconomic uncertainty and inflation uncertainty significantly moderate or influence the extent to which disaggregated variables impact corporate performance volatility.

Compared to related studies in the reviewed literature, this study rather examines volatility associated with corporate performance instead of the corporate performance indicator itself. Additionally, this paper also examines how disaggregated variable instead of aggregate variables impact such volatility. Finally, the moderating role of key macroeconomic conditions in such a relationship is also examined.

Higher education has a vital role to play in shaping the way in which future generations learn to cope with the complexities of sustainable development. Universities and higher education institutions educate highly qualified graduates and responsible citizens able to meet the needs of all sectors of human activity; they provide opportunities for higher learning and for learning throughout life; they advance, create and disseminate knowledge through research and provide, as part of their service to the community, relevant expertise to assist societies in cultural, social and economic development; they contribute to the development and improvement of education at all levels, including through the training of teachers. The objective of this study is to examine the relationship between higher education and economic growth in Iran.

First, a baseline survey analysis of Iran supported by tables and figures was conducted. Secondly, by using multivariable time series data on the variables: annual logarithmic gross domestic product, physical capital (K), human capital, research expenditures (R) and by using an autoregressive distributed lag (ARDL) model, the long‐ and short‐run relationship between the growth and higher education variable was investigated. The following steps were followed: test of a dynamic ARDL model, CUSUM and CUSUMQ test for stability, long‐run relationship and ECM test.

The results indicated that the higher education variable had a positive effect on the economic growth of Iran in both the short and long run.

The research in this paper has implications for government policy makers responsible for investment in higher education.