The advancement in fintech technological development in emerging countries has accelerated the role of digital finance in economic development. Digital finance assists in financial inclusion; however, it may also increase the chances of financial instability due to systematic risks. Emerging countries are also in the clutches of shadow economic growth, which reduces taxable income revenue and creates pressure on financial inclusion prospects. The current study attempts to measure the impact of digital finance on the shadow economic growth and financial stability among the selected South Asian emerging countries. We have used the CUP-FM and CUP-BC estimation methods to measure the above relationship on two model frameworks from 2004 to 2018, with the former measuring the influence of digital finance on the shadow economy and the latter examining the relationship between digital finance and financial stability. In addition, the second-generation unit root test, and the Westerlund cointegration analysis are also employed to confirm the stationarity and cointegration among the variables. The result of the Westerlund’s cointegration confirms a long cointegration between the explanatory and outcome variables. Furthermore, the long-run estimation results conclude that an increase in digital finance helps in reducing the growth of the shadow economy among the selected sample countries. However, it also increases the likelihood of systematic risks and increases financial instability. The study also reveals that the control variables like unemployment and industrial productivity also have a significant influence on financial stability and the shadow economy. The findings will assist readers in comprehending how digital finance influences the shadow economy and promotes financial inclusion and stability in emerging nations.

This research aims to improve the efficiency in estimating the Hurst exponent in financial time series. A new procedure is developed based on equality in distribution and is applicable to the estimation methods of the Hurst exponent. We show how to use this new procedure with three of the most popular algorithms (generalized Hurst exponet, total triangles area, and fractal dimension) in the literature. Findings show that this new approach improves the accuracy of the original methods, mainly for longer series. The second contribution of this study is that we show how to use this methodology to test whether the series is self-similar, constructing a confidence interval for the Hurst exponent for which the series satisfies this property. Finally, we present an empirical application of this new procedure to stocks of the S &P500 index. Similar to previous contributions, we consider this to be relevant to financial literature, as it helps to avoid inappropriate interpretations of market efficiency that can lead to erroneous decisions not only by market participants but also by policymakers.

This study intends to examine the impact of current health expenditure, domestic government health expenditure, government education expenditure, social protection, population growth, and foreign direct investment (FDI) on human capital formation in the context of Pakistan. This study utilized skill and health to measure human capital. The study utilized annual data for the period of 1990–2020 and data has been extracted from World Development Indicators (WDI) and World Bank. The study utilized auto-regressive distributed lag (ARDL) bound test to examine long-run co-integration among defined variables. Furthermore, the study employed ARDL Model to obtain long-run and short-run empirical estimates for modeled variables. The results of this study indicated that current health expenditure (CHE), domestic government health expenditure (DGHE), government education expenditures (GEE), foreign direct expenditure (FDI), and social protection program (SP) have a positive and significant association with human capital in term of primary, secondary, and tertiary education attainment and life expectancy at birth. Moreover, domestic government spending on health and education, and social protection program significantly decreases child mortality in Pakistan. Furthermore, this study found that population growth has a negative and significant association with primary attainment. The findings of this study suggest that the Government of Pakistan should allocate more of its budget for health, education, and social protection programs to uplift its human capital.