Muhammad Zahid Naeem

This research aims to quantify the linear and non-linear relationship between debt and economic growth in selected developing economies. Based on theoretical arguments and annual data considerations in modelling the debt and growth as a complex relationship across countries, our panel methodology is based on the fixed effect technique. Our core finding indicates that government debt lowers the GDP in selected developing economies. We also find that the urban population is a key factor that improves economic growth. Moreover, government expenditures on health and industrialization are helpful to enhance the growth of the economies. Our study also suggests increased exports, industrial development, and investment in education for growth. We also propose certain supporting strategies to reduce the adverse effects of debt-growth relation in the considered economies. Given developing economies’ status, the prerequisite for broad, dynamic and rule-based debt policy is of paramount importance, ensuring the factual choices among numerous possibilities, addressing financial constraints and ensuring intergenerational welfare impact.

The COVID-19 pandemic has brought rampant changes in skill needed in the labor market. It has accentuated technological disruption leaving millions in dire need of reskilling and upskilling. In this paper, we empirically analyze the impact of the COVID-19 pandemic related lockdown on the thrust of skills upgradation among people. By analyzing the Google trends data of 13 countries, we test the effect of the lockdown implementations on the urge to upgrade the skills through online searches for skills enhancement. Using difference-in-difference estimation approach, we found a substantial hike in the frequency of search terms related to skills upgradation. Our results suggest that people are utilizing the excess time, made available due to lockdowns, by exploring avenues to enhance their skills to accumulate human capital. The online educational platforms have been proven vital. The findings of this study establish the causal link between use of online education platforms and human capital development.

Education and health are considered a cornerstone for obtaining targeted development in any society. Moreover, both sectors promote prosperity greatly. In this changeable epoch, people are thought out as the real wealth of any nation and this wealth with good human capital serves the economy very efficiently and productively. This research study aims to analyse how Development Assistance Committee (DAC) aid commitment for education along with institutional quality is effective for the human development of selected Asian economies. A panel data set over 2011–2018 is used for this analysis in Asian countries. GMM results show a significant and positive relationship between aid commitment for education and the human development of these economies. A more interesting result is that financial development seems to boost up human deployment in the selected Asian economies. The development of the textile industry is significantly influenced by education, especially considering the effects of OECD's Development Assistance Committee (DAC) Aid Commitments for education on human development in Asian countries. There is a dire need to reconsider more allocation of resources and aid to education and health to utilize these inflows at the maximum level for targeted development.

This research is the earliest attempt to understand the impact of inflation and the interest rate on output growth in the context of Pakistan using the wavelet transformation approach. For this study, we used monthly data on inflation, the interest rate, and industrial production from January 1991 to May 2020. The COVID-19 pandemic has affected economies around the world, especially in view of the measures taken by governmental authorities regarding enforced lockdowns and social distancing. Traditional studies empirically explored the relationship between these important macroeconomic variables only for the short run and long run. Firstly, we employed the autoregressive distributed lag (ARDL) cointegration test and two causality tests (Granger causality and Toda–Yamamoto) to check the cointegration properties and causal relationship among these variables, respectively. After confirming the long-run causality from the ARDL bound test, we decomposed the time series of growth, inflation, and the interest rate into different time scales using wavelet analysis which allows us to study the relationship among variables for the very short run, medium run, long run, and very long run. The continuous wavelet transform (CWT), the cross-wavelet transform (XWT), cross-wavelet coherence (WTC), and multi-scale Granger causality tests were used to investigate the co-movement and nature of the causality between inflation and growth and the interest rate and growth. The results of the wavelet and multi-scale Granger causality tests show that the causal relationship between these variables is not the same across all time horizons; rather, it is unidirectional in the short-run and medium-run but bi-directional in the long-run. Therefore, this study suggests that the central bank should try to maintain inflation and the interest rate at a low level in the short run and medium run instead of putting too much pressure on these variables in the long-run.

Health has vital importance in maintaining economic development since it is essential for, and a result of, economic development. This indicates that health makes a large contribution in achieving sustainable development and health outcomes. The significance of health is shown in the millennium development goals (MDGs) and in the sustainable development goals (SDGs), where four of the seventeen objectives focus on improving health outcomes (UN, 2021). As compared to other countries, some Asian countries are still worse off regarding health outcomes and are facing challenges in achieving positive outcomes for such goals. This study mainly focuses on identifying the link between public health expenditures and health outcomes in nine Asian economies from 2000 to 2018. The study implements fixed effects panel data estimations by using the Hausman specification test to identify the fixed effects model as the suitable estimator for the study. The empirical results from the fixed effects technique show that immunization, GDP per capita, trade openness, and utilization of basic water service facilities improve under-five and infant mortality in Asian economies. However, ecological footprint increases under-five and infant deaths by damaging the environment.

Following the work of Kaminsky, Lizondo, and Reinhart (1997), Signals Extraction Approach has been adopted with some extensions for South-East Asian (SEA) region to investigate the performance of the technique as an Early Warning System (EWS) during Asian Financial Crisis (AFC) and Global Financial Crisis (GFC). This approach is very original in the context of investigating the impact on the dynamics of the textile industry in South-East Asia. Two additional approaches namely Signal to Noise Balance (STNB) and Kuipers Score (KS) have also been utilised. Outcome suggested that variables performed well both during AFC and GFC. However, predictive ability of variables was less during GFC compared to the AFC indicating that there may exist some complex phenomenon which requires composite statistical methods.

This paper investigates the determinants behind persistent and prolonged stays under the International Monetary Fund (IMF) program and its effectiveness, using panel data consisting of 70 countries that have requested IMF support multiple times, during the period 1980–2018. By employing panel survival analysis, we conclude that weak economic indicators, e.g., current account deficit, high debt service ratio, low GDP, are the main reasons that force a country to reach out to the IMF support program. We further extend our analysis to investigate the effectiveness of the IMF program by dividing our sample into two groups, based on income level. To overcome the issue of endogeneity, we implement the panel instrumental two-stage least squares (2SLS) fixed-effect model. In the light of our analysis, we find a contemporaneous positive impact of the IMF fund program on the economic growth of upper middle-income countries, while, for low-income countries, its contemporaneous impact is insignificant, but becomes visible over time.