Purpose: This research paper aims to explore asymmetric market efficiency of the 13 Euro countries, i.e. Austria, Belgium, Finland, France, Germany, Greece, Ireland, Italy, Netherland, Portugal, Slovakia, Slovenia and Spain, concerning the period before global financial crisis (GFC), after GFC and period of COVID-19 pandemic. Design/methodology/approach: Multifractal detrended fluctuation analysis (MF-DFA) is applied to examine the persistence and anti-persistency. It also discusses the random walk behavior hypothesis of these 13 countries non-stationary time series. Additionally, generalized Hurst exponents are applied to estimate the relative efficiency between short- and long-run horizons and small and large fluctuations. Findings: The current study results suggest that most countries' markets are multifractal and exhibit long-term persistence in the short and long run. Moreover, the results with respect to full sample confirm that Portugal is the most efficient country in short run and Austria is the least efficient country. However, in long run, Austria appeared to be highly efficient, and Slovakia is the least efficient. In the pre-GFC period, Greece is said to be the relatively most efficient market in the short run, whereas Austria is the most efficient market in the long run. In the case of Post-GFC, Netherland and Ireland are the most efficient markets in short and long run, respectively. Lastly, COVID-19 results indicate that Finland's stock market is the most efficient in short run. Whereas, in the long run, the high efficiency is illustrated by Germany. In contrast, the most affected stock market due to COVID-19 is Belgium. Originality/value: This study will add value to the present knowledge on efficient market hypothesis (EMH) with the MF-DFA approach. Also, with the MF-DFA approach, potential investors will be capable of ranking the stock markets of Eurozone countries based on their efficiency in the period before and after GFC and then specifically in the period of COVID-19.

The purpose of this study to contribute to the existing literature by investigating at the impact of remittances on Pakistan’s poverty, both in the long run and over the short run over the period from 1980 to 2018. Poverty is the dependent variable, and independent variables are inflation, education, trade openness, domestic growth product per capita, and remittance. For this purpose, ARDL bound testing technique is used to examine the effect of remittances on Pakistan’s poverty in multidimensional form. To confirm the results' robustness, this study used two proxies of poverty. For Model 1, consumption of household (HHC) used as poverty's proxy. For 2nd model, the rate of infant mortality (IMR) is taken as a proxy of poverty. Unit roots' outcomes indicate appropriateness to apply the ARDL bond testing to conclude on co-integration and (ARDL) regression analysis. Co-integration test results indicate that relationships of long run are present among the study variables of models 1 and 2 because both models' the value of F-statistics is greater than the serious value. In model 1 (long-run and short-run), results represent the impact of remittance (REM) is negative on poverty (HHC). From previous studies, remittance has an adverse influence on poverty. In model 2 (long-run), results represent the impact of remittance (REM) is negative on poverty (IMR). However, short-run results represent that remittance (REM) is positive on poverty (IMR). The negative relationship between remittances and poverty implies that remittance increases can decrease the poverty level in Pakistan. The results show that remittances have an important role in reducing poverty in the country.

The balance between economic and ecological well-being has become one of the primary concerns of the governments in the world. The need to achieve sustainable growth is emphasized in the contemporary world economies and especially those that are underdeveloped. This paper investigates the dynamic impacts of the Foreign Direct Investment (FDI), economic growth (EG), the consumption of renewable energy (RE) and trade openness (TO) on the environmental degradation (CO2 emissions) in the BRICS countries (Brazil, Russia, India, China, South Africa). The analysis that will be conducted utilizes annual panel data covering the years 1995 to 2023 to implement the Panel Autoregressive Distributed Lag (ARDL) methodology to analyse the short and long-term correlation. We are all paying the opportunity cost of economic development by accelerated environmental degradation all over the world. In order to curb the devastating realities of climate change and save nature, countries need to reshape their energy usage policies through renewable energy technologies and research, thus creating sustainable development in the world. The findings show that economic growth has a significant positive impact on the increase in CO2 emissions in the long-run and the use of renewable energy has significant positive impact on the reduction of the CO2 emissions in short and long-term. The effect of Foreign Direct Investment (FDI) is dynamic, increasing emissions over the short term and decreasing them significantly over time, therefore, supporting the Pollution Halo Hypothesis in the long term. The openness to trade showed a statistically significant yet insignificant positive impact on the long-term emissions. These findings bring about the need to develop renewable energy and wisely utilize foreign direct investment coupled with green growth strategies to reduce environmental degradation as well as develop the economy of the BRICS countries.

The study aims to examine the time-varying causality between political stability and economic growth. Secondly, study also evaluates the effect of political stability on economic growth of the United Kingdom and the United States. Therefore, a time-series model is proposed to assess the framework’s constancy with time, which assumes that the coefficients are stable throughout time. A rolling window technique has been applied to the dataset from the year 2002 to 2019, respectively. The results indicate that the time-varying positive bidirectional causality is present between political stability and economic growth for a particular subsample, verifying the effect of political stability on economic growth and vice versa. Hence, our results exhibit that the connection between two-series would benefit the economy due to the positive yet significant relationship. Therefore, uncertain political conditions would directly affect the economy’s growth rate in terms of tourism, currency value, investment, and other growth factors. Whereas, if the uncertainty regarding the political environment reduces, it would be advantageous for economic development.