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Using annual data from 1970 to 2013 for China and India, this paper aims to examine the impact of globalization and financial development on economic growth by endogenizing capital and inflation and drawing comparisons between the two fastest growing emerging market economies.

In the long run, co-integration test results indicate that financial development increases economic growth in China and India.

The results also reveal that globalization accelerates economic growth in India but, surprisingly, impairs economic growth in China, as it increases competition for exports. The results furthermore disclose that acceleration in capitalization and inflation, as a proxy for aggregate demand, are positively linked to economic growth in China and India.

Causality test results indicate that both financial development and economic growth are interdependent. In contrast, causality runs from higher economic growth to increased globalization in India, while the results do not support long-term causality between globalization and economic growth in China.

The study is intended to find out the relationship between housing prices and the inflow of foreign capital in Pakistan. There is a shortage of housing units due to rising population and rural–urban migration since its inception; on the other hand, there is also a lack of housing finances. The urban sprawl has created the demand for housing units, but the supply of housing has not been increased up to the required level, the major reason is a deficiency of housing finances.

The analysis was carried out from 1973 to 2018, on an annual, quarterly and monthly basis; the structural changes are captured by the Zivot–Andrews unit root test. Gregory–Hansen test is used for cointegration, the combined cointegration also validates the results. In addition, the rolling window is used to capture timely changes between data sets. Finally, wavelet analysis is used to prove volatility.

The rising prices of housing in the country is alarming; Pakistan is a developing country, and it is facing many problems along with a housing shortage. The domestic sources of housing finances are inadequate, so foreign funds are welcomed. The rolling window regression proves that domestic factors along with the foreign capital inflow affect housing prices positively, and the wavelet analysis finds out that foreign direct investment is more volatile than workers’ remittances in financing the housing market.

This is a pioneering study to find out the impact of foreign capital inflows on the housing prices in the economy of Pakistan. The inadequacy of housing finances from domestic sources attracted foreign funds financing this sector. This study has used new techniques like rolling window and wavelet transformation, such techniques have not been used before.

This paper aims to empirically examine the impact of economic development and energy consumption in Saudi Arabia (the leading OPEC giant and the Arab energy icon country) between 1971 and 2015, whilst incorporating globalization, financial development and capital accumulation.

This study uses econometric tools and the analytical framework based on the autoregressive distributed lag (ARDL) model.

The study found that, unlike economic development, globalization and financial development increased energy consumption. Also, capital accumulation created a boost in the country’s energy consumption. Results of variance decomposition indicate that the innovative shocks in globalization and financial development affected energy consumption at the rates of 15.28% and 28.98%, respectively, over 15 years’ period, while shocks in capital accumulation affected energy consumption at a rate of only about 1.24%. In addition, the results of impulse response function show that globalization and economic development were highly responsive to shocks in financial development, and capital accumulation greatly spurred financial development.

The findings of this study have implication for promoting an efficient and sustainable energy systems that enhance sustainable development based on the accrued benefits of globalization, financial development and capital accumulation.

Given the increasing level of globalization, financial development and energy consumption, our study uses econometric tools and the analytical framework based on the ARDL model to revisit how energy consumption is influenced by economic development in Saudi Arabia by incorporating other determinants of energy consumption such as globalization, financial development and capital accumulation. The results were validated based on the innovative accounting.

This study aims to examine the relationships between aggregated and disaggregated energy use in the industrial sector, carbon emissions and industrial output in China.

The study utilizes annual frequency data for the period of 1984-2015. The unit root properties of data are tested using augmented Dickey–Fuller and Phillips and Perron unit root tests. Furthermore, the Zivot–Andrew structural breaks unit root test is used to detect the structural breaks steaming into series. The autoregressive distributed lag bound test and newly developed Bayer–Hanck combined cointegration are used to check the existence of a cointegration relationship between underlying variables. Last, the direction of causality is determined applying vector error correction model (VECM) Granger causality.

The results confirm the existence of a long-run relationship in the presence of structural breaks. The authors conclude that aggregated and disaggregated energy consumption in the industrial sector increases CO₂ emission in both long and short run. The VECM Granger causality analysis indicates the bidirectional relationships between CO₂ emission, industrial growth and aggregated and disaggregated (coal, oil and natural gas) energy consumption.

Based on the empirical results mentioned above, the study proposes the recommendation that China should focus on the use of natural gas in the industrial sector instead of coal and oil consumption. The most potent reasons for such a transformation are twofold: natural gas is much more environment-friendly, thus being a much lesser polluting source of energy, and, most significantly, such a change would have no adverse impact upon the output level.

This study contributes to the existing literature on estimating CO₂ emission by using aggregated and disaggregated energy consumption in case of China. Notwithstanding, it also adds to the existing applied literature by using newly developed combined cointegration to confirm and substantiate the cointegration relationship between the underlying variables. Moreover, this study incorporates the role of structural breaks while investigating CO₂ emission function, which helps in providing more valuable policy suggestions.

This research aims to inspect the existence of the “environmental Kuznets curve” (EKC) in the presence of foreign direct investment (FDI), financial development (FD) and urbanization throughout 1972–2018 for Pakistan.

For time series analysis, Phillips and Perron (PP) and Augmented Dickey–Fuller (ADF) unit root tests are used to confirm the level of integration. For robustness, Kim and Perron (2009)’s structural break unit root test is employed, which identifies the order of integration in the presence of structural break years. Further, combined cointegration analysis is performed to confirm the existence of a long-run association between underlying variables. Furthermore, autoregressive distributed lag (ARDL) analysis is employed for the robustness of the cointegration approach.

The cointegration analysis confirms the existence of a long-run association among variables. The authors find a positive and significant impact of urbanization, FD and foreign development on environmental degradation in the long run. Similarly, only FDI increases environmental degradation in the short run. In addition, the authors find an inverted U-shape relationship between economic growth and environmental quality which, further, confirms the presence of EKC in Pakistan.

This research contributes to applied economics in many ways: the combined effect of urbanization, FD, FDI and economic growth on carbon dioxide (CO₂) emission is checked simultaneously. To avoid ambiguity, this study constructs the FD index through the principal component analysis (PCA). Moreover, the role of structural breaks has been considered through the analysis. Novel Bayer-Hanck combined cointegration analysis is employed to detect the existence of long-run relationships among underlying variables.

In this paper, the authors investigate that the increasing level of fossil fuel combustion in the industrial sector has been considered the prime cause for the emissions of greenhouse gas. Meanwhile, the research focusing on the impact of fossil fuel consumption on the emission of CO₂ is limited for the developing countries containing Vietnam. This study applied the autoregressive distributed lag (ARDL) approach with structural breaks presence, and the Bayer–Hanck combined cointegration method to observe the rationality of the environmental Kuznets curve (EKC) hypothesis in the dynamic relationship between the industrialization and carbon dioxide (CO₂) emission in Vietnam, capturing the role of foreign direct investment (FDI) inflows and the fossil fuel consumption over the period of 1975–2019. The outcomes revealed the confirmation of cointegration among the variables and both short and long-run regression parameters indicated the evidence for the presence of a U-shaped association between the level of industrial growth and CO₂ emission that is further confirmed by employing the Lind and Mehlum U-test for robustness purpose. The results of Granger causality discovered a unidirectional causality from FDI and fossil fuel consumption to CO₂ emission in the short run. For the policy points, this study suggests the use of efficient and low carbon-emitting technologies.

In order to test for consistency and robustness of the cointegration analysis, this study also applied the ARDL bound testing method to find out long-run association among variables with the existence of the structural break in the dataset. The ARDL method was preferred to other traditional cointegration models; because of the smaller dataset, the results obtained from the ARDL method are efficient and consistent and equally appropriate for I(1) and I(0) variables.

The short-run and long-run causal associations among variables have been observed by employing the error correction term (ECT) augmented Granger-causality test that revealed the presence of the long-run causality among variables only when the CO₂ emission is employed as a dependent variable. The outcomes for short-run causality indicated the presence of unidirectional causality between consumption of fossil fuel and CO₂ emission, where the fossil fuel consumptions Granger-cause CO₂ emission. Industrial growth has also been found to have an impact on fossil fuel consumptions, however not the opposite. This advocates that the policies aimed at reducing the fossil fuel consumptions would not be harmful to industrial growth as other energy efficient and cleaner technology could be implemented by the firms to substitute the fossil fuel usage.

The study explored the dynamic relationship among FDI, consumption of fossil fuel, industrial growth and the CO₂ emission in Vietnam for the time period 1975–2019. The newly established Bayer–Hanck joint cointegration method and the ARDL bound testing were employed by taking into account the structural breaks in the dataset.

The primary objective of this study is to investigate the linkage of tourism and crime for Pakistan along with exchange rates, terrorism and domestic prices in the presence of structural breaks over the period 1984–2017.

The order of integration is tested through ADF and PP unit root tests. The robustness of unit root test is testified via structural break unit root test. Furthermore, the authors use Bayer and Hanck (2013) combined cointegration test to confirm the existence of a long-term theoretical relationship among the variables. For the robustness of cointegration analysis, the authors also employ ARDL bound testing in the presence of structural break years. Moving forward, the authors apply VECM Granger causality to find out the direction of causality. Subsequently, variance decomposition approach and impulse response function are used to distinguish leader from the followers.

The unit root test shows that the order of integration is one, I(1). The cointegration analysis confirms the long-run relationship between underlying variables. The authors find inverse and significant impact of crime and exchange rate on tourism in the long run. On contrary, domestic prices play a positive and significant role to determine tourism in short and long run. Also, terrorism is found to be insignificant with negative impact. Further, the bidirectional causality between crime and tourism is observed in the long run. Similarly, unidirectional causality from terrorism to exchange and exchange rate to domestic price is observed in the short run.

The contemporary studies on crime-tourism nexus offer limited evidence, as they frequently suffer from omitted variable bias and ignore possible endogeneity issues. This study uses vector autoregressive models to overcome these biases. Similarly, the authors accommodate the role of structural break years through their analysis. Hence, the results offer more credible evidence. Moreover, the authors contribute to the existing tourism demand literature by adding crime as a potential determinate in case of Pakistan.

To test the economic theory that economies with greater stability and diversity are also economies that are more insulated from economic shocks.

Uses persistence profiles derived from the cointegrated systems of two regional economies within the state of Oregon; the urban Portland Metropolitan Area (PMA) and the rural Southwest (SW) region.

The results of the above process illustrate that the more stable and diverse PMA responds with a smaller frequency and returns to equilibrium more quickly than the SW.

This paper only provides one set of observations, which is insufficient to prove the theory, but does enable a more extensive time series approach than that has been done previously. Also regional economies typically become more diversified over time, so the level of diversity can only be measured in relative terms not absolute.

The paper reveals the benefits a diversified a diversified economy has in creating stable employment opportunities, as deviations in unemployment rates decline as diversification increases.

The paper takes a widely accepted time series econometrics technique from macroeconomic literature, cointegration, and applies it at a regional level. Cointegration combined with persistence profiles enables the integration of both the time dynamics of an economy and their inter‐industry linkages to be analyzed. This methodology dramatically increases the depth of possible analysis into the stability/diversity debate that has been waged over the last 70 years.

In the presence of informal sector in the country, designing an energy policy and the pursuit of higher economic growth become challenging for emerging economies. These economies are usually resource starved, and the presence of underground economy leads to faulty estimates of energy demand. The authors explore the energy–growth nexus in the presence of underground economy for Pakistan, an emerging economy host to large informal sector and facing recurring energy crises.

The authors evaluate the impact of underground economy on energy demand in the presence of explanatory variables, including official gross domestic product (GDP), foreign direct investment and financial development. The authors first assess the influence of official economy on the consumption of energy. The authors investigate how energy consumption is influenced solely by underground economy. Finally, the authors evaluate the impact of true GDP on the energy consumption. The authors employ combined cointegration method of Bayer and Hanck (2013) and then apply vector error correction model.

The results reveal that official GDP, underground economy and true GDP positively and significantly affect energy consumption in both short and long run. Similarly, financial development as well as foreign direct investment enhance energy consumption. The authors find unidirectional causality between energy consumption and official GDP variables (OGDP → EC), underground economy (UE → EC) and true GDP variables (TGDP → EC) in the long run. The authors observe bidirectional causality in the short run between energy consumption and official GDP (OGDP ↔ EC) and true GDP (TGDP ↔ EC).

To the best of the authors' knowledge, no study examines the causal relationship of energy consumption and underground economy. Overall, the findings assist policymakers to consider and implement different energy-related policies considering the significant role of underground economy for energy consumption in Pakistan.

The use of exchange rate policies to stimulate economic growth (EG) has been the major macroeconomic policy of many economies. Hence, the attention of researchers and policymakers was drawn to the effect of undervaluation and/or overvaluation of currencies on sustainable EG. However, less attention has been paid to the importance of quality of economic institutions in shaping the relationship between exchange rate and EG. This study aims to explore the role of institutions of exchange rate and EG in South Africa

This study, therefore, examines the role of economic institutions in the real exchange rate economic growth nexus by using auto regressive distributed lags model and vector error correction model for causality during the period 1971 to 2018. Also, Bayer and Hank method has applied for cointegration between the variables.

The findings show that both real exchange rate and economic institutions have a negative effect on EG in both short-run and long-run. This implies that undervaluation has a negative effect on EG in South Africa. Therefore, the study concludes that undervaluation has a negative effect on EG in South Africa particularly when the quality of economic institutions is accounted for. The finding supports the J-curve hypothesis but is contrary to the Rodrik hypothesis. Hence, devaluation is not a desirable exchange rate policy for the South African economy.

The study, therefore, recommends that developing countries like South Africa should focus on other viable exchange rate policies such as rather than undervaluation of currency to enhance EG.