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Renewable energy is at the forefront of countries’ concerns due to its global economic and environmental impacts. Previous studies have thoroughly examined the impact of renewable energy on overall national income, and this paper aims to shed light on an indicator that has received insufficient attention in research regarding its impact on economic growth, using data from 2000 to 2018.

This study examines the causal relationship between trade balance, renewable energy consumption and CO₂ emissions per capita in Organization for Economic Cooperation and Development (OECD) countries using an auto regression distributed lag model (ARDL) and Johansen Cointegration Test.

The findings reveal that there is evidence of a long-run and short-run cointegrating relationship and that renewable energy consumption in the long run impacts the trade balance positively and in the short run negatively.

Therefore, bioenergy trade between countries and local investment should be prioritized to increase the trade balance surplus, since many of OECD countries suffer from deficit problems.

The argument whether gold is a hedge or haven is a debatable issue. Mainly, hedge is a class of asset that is negatively correlated with another asset or portfolio on average. On the other hand, a safe haven is an asset or portfolio which is negatively correlated with another asset or portfolio at the time of market turmoil. Therefore, the purpose of this research is to take Saudi Arabia as an example to examine the relationship of gold price in Saudi Arabia with key determinants such as the stock market index, oil prices, exchange rate, interest rate and consumer price index (CPI) by application of the autoregressive distributed lag model (ARDL).

The ARDL analysis was employed by using six variables based on the application of monthly time series data that were collected from 2011 to 2015.

From the present analysis, it has been discovered that gold is useful as a portfolio hedge and as a hedge against inflation because it is not affected by the CPI. External factors, for example, financial crisis, may be harmful to the CPI, thus adding a certain percentage of gold in the investment portfolio may assist in decreasing the level of risk at the time of financial turmoil.

Because gold seems to be a useful portfolio hedge, as well as an inflation hedge, government policies to curb the import of gold may be futile. The present research suggests that policies that directly address the causes of inflation and provide alternative investment opportunities for retail investors may better serve the objective of decreasing gold imports.

The purpose of this paper is to investigate the tourism-led growth hypothesis in Laos.

The authors test the tourism-led growth hypothesis using autoregressive distributed lag (ARDL) cointegration estimation (Pesaran et al., 2001) and Granger causality tests.

The results of this paper show that when tourism is forcing variable, there is no long-run relationship between tourism development and economic growth. The Granger causality test demonstrates that there is a uni-directional causality running from economic growth in tourism.

The empirical results and policy recommendation may be useful for other small developing countries.

This study is the first study to investigate the relationship between tourism development and growth in Laos, using a relatively new econometric approach – ARDL bound testing.

The climate change effects on agricultural output in different regions of the world and have been debated in the literature of emerging economies. Recently, the agriculture sector has influenced globally through climate change and also hurts all sectors of economies. This study aims to examine and explore the impact of global climate change on agricultural output in China over the period of 1982-2014.

Different unit root tests including augmented Dickey–Fuller, Phillips–Perron and Kwiatkowski, Phillips, Schmidt and Shin are used to check the order of integration among the study variables. The autoregressive distributed lag (ARDL) bounds testing approach to cointegration and the Johansen cointegration test are applied to assess the association among the study variables with the evidence of long-run and short-run analysis.

Unit root test estimations confirm that all variables are stationary at the combination of I(0) and I(1). The results show that CO₂ emissions have a significant effect on agricultural output in both long-run and short-run analyses, while temperature and rainfall have a negative effect on agricultural output in the long-run. Among other determinants, the land area under cereal crops, fertilizer consumption, and energy consumption have a positive and significant association with agricultural output in both long-run and short-run analysis. The estimated coefficient of the error correction term is also highly significant.

China’s population is multiplying, and in the coming decades, the country will face food safety and security challenges. Possible initiatives are needed to configure the Chinese Government to cope with the adverse effects of climate change on agriculture and ensure adequate food for the growing population. In concise, the analysis specifies that legislators and policy experts should spot that the climate change would transmute the total output factors, accordingly a county or regional specific and crop-specific total factor of production pattern adaptation is indorsed.

The present empirical study is the first, to the best of the authors’ knowledge, to investigate the impact of global climate change on agricultural output in China by using ARDL bounds testing approach to cointegration and Johansen cointegration test.

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.

The purpose of this paper is to examine whether innovation plays a significant role in the total factor productivity (TFP) growth in India at an aggregate level.

This study first estimates the TFP growth using a growth accounting framework. In the second stage, the authors examine the long-run and short-run impact of innovation on TFP growth using the ARDL bound testing approach.

The results indicate a cointegrating relationship between innovation and TFP growth. Further, coefficients of long-run elasticity show that the increase in overall innovation activities improves the TFP growth. Other factors such as human capital, financial development and FDI do not affect the TFP growth in the long run; however, these variables significantly affect the productivity growth in the short run.

Findings of the study suggest that the innovation-friendly policies such as the strengthening of intellectual property rights, R&D subsidies and innovation rebates may spur the productivity growth, and hence, good growth and prosperity as well.

Having devoted a large volume of literature to address the sources of economic growth, the present study focuses on the determinants of TFP growth in India which may fall in similar category but differ in several angles: First, the authors construct a TFP index using a growth accounting framework. Second, the authors construct an innovation index using principal component analysis which is new to the literature and also an innovation index. Third, given the scanty innovation activities in low developed countries like India and its widening role in the contemporary literature, special emphasis will be given to this aspect. Finally, the effect of the examined relationship on TFP growth in the long run and short run provides several implications for policy purpose to the developing nations like India.

The purpose of this paper is to examine the relationship between tourism sector development and poverty reduction in India using annual data from 1970 to 2018. The paper attempts to answer the critical question: Is tourism pro-poor in India?

Stationarity properties of the series are checked by using the ADF unit root test. The paper uses the Auto Regressive Distributed Lag (ARDL) bound testing approach to cointegration to examine the existence of long-run relationships; error-correction mechanism for the short-run dynamics, and Granger non-causality test to test the direction of causality.

The cointegration test confirms a long-run relationship between tourism development and poverty reduction for India. The ARDL test results suggest that tourism development and economic growth reduces poverty in both the long run and the short run. Furthermore, inflation had a negative and significant short-run impact on the poverty reduction variable. The causality test confirms that there is a positive and unidirectional causality running from tourism development to poverty reduction confirming that tourism development is pro-poor in India.

This study implies that poverty in India can be reduced by tourism sector growth and price stability. For a fast-growing economy with respect to economic growth and tourism sector growth, this may have far-reaching implications toward inclusive growth in India.

This paper is the first of its kind to empirically examine the causal relationship between tourism sector development and poverty reduction in India using modern econometric techniques.

This study attempts to come in help for Morocco by investigating rigorously the linkage between environmental degradation, measured by ecological footprint (EF), and the gross domestic product growth (EG), the human capital (HC) index and the natural resources (NR) depletion over the period of 1980:Q1 to 2021:Q1. The paper examines the validity of environmental Kuznets curve (EKC) hypothesis in the Moroccan context.

Unlike previous studies, which are based only on the autoregressif dynamic linear (ARDL) model, this paper investigates two recent models: the novel DYNARDL simulation approach and the Kernel-based regularized least squares (KRLS) technics and uses in addition the frequency domain causality (FDC) test.

Models output say a significant and negative association between HC and the EF and a significant and positive interplay between economic growth and environmental quality in the long term. In the short term, findings reveal a significant and negative association between NR and the EF. Based on the FDC test, results conclude about a unidirectional causality from NR to the EF in short-, medium-, and long-term. Moreover, results validate the EKC hypothesis for the Moroccan environment sustainability.

In this study, the researchers use the “ecological footprint” as dependent variable to obtain more accurate and comprehensive assessment of environmental deterioration. Based on time series data investigations, this study is the first paper, which validates the EKC hypothesis and develops important policy implications for Morocco context to achieve sustainable development targets.

Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.

This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.

The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.

The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

This paper aims to examine the effects of CO₂ emissions, energy consumption, cultivated area and the labour force on the production of cereal crops in Pakistan from the period 1971-2014.

The study used the Johansen cointegration test, the autoregressive distributed lag (ARDL) approach and Granger causality test to estimate the long-run cointegration and direction of the relationship between the dependent and independent variables.

The outcomes of the Johansen cointegration test confirmed the existence of a long-term cointegrating relationship between the production of cereal crops, CO₂ emissions, energy consumption, cultivated area and the labour force. The results of the long-run coefficients of CO₂ emissions, energy consumption, cultivated area and labour force have a positive impact on cereal crops production. The long-run relationships reveal that a 1 per cent increase in CO₂ emissions, energy consumption, cultivated area and labour force will increase cereal crops production by 0.20, 0.11, 0.56 and 0.74 per cent, respectively. Moreover, the findings show that there is a bidirectional causality running from CO₂ emissions and cultivated area to cereal crops production. Moreover, there is a unidirectional causality running from energy consumption to cereal crops production.

The present study also fills the literature gap for applying the ARDL procedure to examine this relevant issue for Pakistan.