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The purpose of this paper is to measure the unidimensional and multidimensional inequality in the case of Pakistan and compare their results at the provincial as well as regional (urban and rural areas) level. The authors collected data from Pakistan Social and Living Standard Measurement and Household Integrated Economic Survey for fiscal years of 1998–1999 and 2013–2014.

The authors used Gini coefficient for unidimensional inequality and multidimensional indexing approach of Araar (2009) for multidimensional inequality.

The findings predicted that unidimensional inequality is relatively high in the urban area due to uneven dissemination of income, but multidimensional inequality is quite high in rural areas because of higher disparities among all dimensions. At the provincial level, Punjab has relatively high-income inequality followed by Sindh, KPK and Baluchistan.

This study is a pioneering effort to compare two time periods to explore unidimensional and multidimensional inequality in all provinces of Pakistan and their representative rural-urban regions by applying Araar and Duclos’s (2009) approach. Further, this study opens some new insights for policy makers.

This study aims to compare the safe-haven properties of different asset markets such as gold, dollar, oil and disaggregated real estate sector (house, plot and residential) against equity returns in Pakistan over the monthly period of January 2011–December 2020.

The authors use wavelet coherence to encapsulate the overall dependence and correlation of asset classes. Further, the authors also study the potential of diversification at the tail of returns distribution by applying the wavelet value-at-risk (VaR) framework.

The results of wavelet coherence show that the dependence is weaker (stronger) in the short (long)-term investment horizon. Moreover, the findings of wavelet VaR reveal that the degree of co-movement between gold and equity returns greatly affects the portfolio risk followed by residential property and oil.

The findings are beneficial for the individual investor, fund managers and financial advisors looking for the optimal portfolio combination that hedges the excessive negative movements in equity returns subject to the heterogeneity in the investment horizon.

This is a primary effort to estimate safe-haven investments opportunities at a large spectrum, including disaggregated real estate sector against stock returns in Pakistan. Moreover, this study uses wavelet coherence and wavelet VaR which have an advantage over traditional analysis for diversification.

Governance quality has been a dominant factor to formulate policies for the development of financial institutions in the world. Therefore, this study aims to explore the impact of governance quality on financial institutions along with globalization in the case of Pakistan.

Time series data from 1996 to 2018 are considered for analysis. The NG-Perron is applied to check the order of integration. In addition, Kim and Perron (2009) structural break unit root test is used to identify break years. The autoregressive distributive lags (ARDL) bound testing approach is used to detect the long-run association among governance quality, financial institutions and globalization.

The results of unit root analysis show that all series are stationary at a different level of integration, I(0)/I(1). However, the long-run association is detected in the presence of break years. The authors find a positive impact of governance quality to determine financial institutions in the long-short-run. Similarly, globalization also enhances financial institutions but only in long run.

This study fills the gap in the economic literature by exploring the linkages between the financial institution and disaggregated governance indicators in the case of Pakistan. Moreover, a role of structural break is also captured during analysis. This study also opens some new insights for policymaking.

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.

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.

The purpose of this paper is to examine the non-linear impact of defence spending on economic growth for the USA, the UK and Russia by using quarterly frequency from 1992 to 2014.

The unit root property is tested by ADF and PP unit root test. Further, BDS test is applied to test the linear independence. To verify the results of BDS test, we apply short and long-run symmetry test. The cointegration non-linear relationship is examined by NARDL approach. Further, Multipliers predict the speed of adjustments by considering the nonlinearity.

The short and long-run symmetry test confirms the existence of asymmetry in all countries. Further, asymmetric cointegration is confirmed through Wald statistics of Pesaran and Banerjee for all countries. The long-run asymmetric coefficient predicts negative and significant impact of defence spending on economic growth for the USA and the UK, but, these impacts were positive and significant in the case of Russia. The multiplier effect of defence spending on economic growth confirms the findings of NARDL model.

This study contributes in existing literature by applying newly developed non-linear ARDL approach, including a Wald test for long and short-run symmetry, asymmetric cointegration and asymmetric long run parameters in case of the USA, the UK and Russia.

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.

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.

Over the past few decades, the flow around circular cylinders has been one of the highly researched topics in the field of offshore engineering and fluid-structure interaction (FSI). In the current study, numerical simulations for flow around a fixed circular cylinder are performed at Reynolds number (Re) = 3900 with the LES method using the ICEM-CFD and ANSYS Fluent tool for meshing and analysis, respectively. Previously, similar studies have been conducted at the same Reynolds number, but there have been discrepancies in the results, particularly in calculating the recirculation length and angle of separation. In addition, the purpose of this study is to address the impact of time interval averaging to obtain the fully converged solution.

This study presents the LES method, using the ICEM-CFD and ANSYS fluent tool for meshing and analysis.

In the current study, turbulence statistics are sampled for 25, 50, 75 and 100 vortex-shedding cycles with the CFL value O (1). The recirculation length, angle of separation, hydrodynamic coefficients and the wake behind the cylinder are investigated up to ten diameters. The drag coefficient and Strouhal number are observed to be less sensitive, whereas the recirculation length appeared to be highly dependent on the average time statistics and the non-dimensional time step. Similarly, the mean streamwise and cross-flow velocity are observed to be sensitive to the average time statistics and non-dimensional time step in the wake region near the cylinder.

In the current investigation, turbulence statistics are sampled for 25, 50, 75 and 100 vortex-shedding cycles with the CFL value O (1), using large eddy simulation method at Re = 3900 around a circular cylinder. The impact of time interval averaging to obtain the fully converged mean flow field is addressed. No such consideration is yet published in the literature.

This study empirically investigates the relationship between goodwill assets and capital structure (i.e. debt ratio) of firms and the moderating effect of financial market development on the relationship between goodwill assets and capital structure.

This research applied a quantitative method. The article collects large samples of listed firms from 23 developing and nine developed countries and applied the panel data techniques. This research used firm-level data from the DataStream database for both developed and developing countries. The study uses 4,912 firm-level data from 23 developing countries and 4,303 firm-level data from nine developed countries.

The findings reveal a significant positive relationship between goodwill assets and capital structure in developing countries, but goodwill assets have a significant negative relationship with capital structure in developed countries. Moreover, financial market development positively moderates the relationship between goodwill assets and the capital structure of firms in developing countries. The results inform firm managers that goodwill assets serve as additional collateral to secure debt financing. Moreover, policymakers should formulate a debt market policy that recognizes goodwill assets as additional collateral for the purpose of obtaining debt capital.

The study has several implications. First, goodwill assets are identified as a factor of capital structure in this study. Fixed assets have been identified as one of the drivers of capital structure in previous research, although goodwill assets are seldom included. Second, this article shows that along with demand-side determinants, supply-side determinants also play an important role in terms of the firms' choice about the capital structure. Therefore, firms should take both the demand-side and supply-side factors into consideration when sourcing for external financing (i.e. debt capital).

The study considered goodwill as a component of capital structure. The study analysis includes a large sample of enterprises, including 4,912 big firms from 23 developing countries and 4,303 large firms from nine industrialized or developed countries, which adds to the current capital structure information. Furthermore, a large sample size increases the results' robustness and generalizability.