Muhammad Azmat Hayat

Tax revenue is playing a vital part in determining an economy’s structure in modern era. The primary goal of this research is to estimate the impact of economic determinants on the tax revenue. Economic determinants include inflation, Agricultural sector’s share in national output, industrial sector’s share in national output and service sector’s share in national output. The sample of the study is consists of 74 developing countries. The study used Ordinary Least Squares (OLS) model for estimation and employed the cross-sectional data for 2021. Using cross-sectional data is very important for the study this is because of several prominent reasons which make the study unique and rare. Worldwide when there is a big structural break happens during the pandemic, the economic relationships between the variables change dynamically which becomes the hot-cake for the economists to the check the strength of relationship between economic variables. So that, the policy makers make adjustments in the policy formulation process as well as reformations of policies which are made earlier to the structure break. The study found Inflation, agriculture share in Gross Domestic Product (GDP), industrial share in GDP and services share in GDP are significant negatively impacting tax revenue generation during the period. 1 percent increase in inflation decline revenue performance by 0.953 percent. The impact of inflation on revenue performance is significant at the 1% level with a negative coefficient. The theoretical reason behind it during the study period inflation rise all over the world while economic activity slow down due to massive structural break and its impacts on global economy. Unadjusted tax brackets and variations in purchasing power are also the same reason for warm up to inflation during the study period. Agriculture sectoral share in GDP contributing negatively and significantly in the performance of revenue generation for government. The composition of its negative effect is classified into direct and indirect tax revenue. The crux of the empirical analysis is composed by numerous factors. As the agriculture sector is non-formal and there are also very inadequate taxpayers with limited income and profits due to most of the agricultural sector belongs to small- scale. Due to high consumption rate, significant portion of production become the part of consumption. There is a large part of production which is even not marketed. Traded agricultural products are largely exempt from indirect taxes. 1 percent increase in industrial share in GDP decline revenue performance by 0.531 percent and is significant at the 1% level with a negative coefficient. During the pandemic, many industrial sectors faced disruptions in production due to lockdowns, supply chain interruptions, and decreased consumer demand. As industrial output decreases, tax revenue generated from these sectors could also decline, reflecting reduced taxable profits or sales. 1 percent increase in services share in GDP decline revenue performance by 0.416 percent and is significant at the 1% level with a negative coefficient. Services sector revenue performance depends upon the nature of Services: Services encompass a wide range of economic activities. Digital Economy: Often operate across borders, posing challenges for tax authorities in terms of identifying taxable transactions and enforcing compliance.

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.

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.

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.

This paper contributes empirically to the long-debated issue of the legitimacy of the European Central Bank (ECB) with regard to European polities. Using micro-level data from the Eurobarometer survey, we shed light on the socio-demographic determinants of public-opinion support for the ECB. We find that people with higher level of education and income and centre to right-wing political orientation tend to support the ECB, as well as people with optimistic expectations on the economic situation. By contrast, the unemployed tend to distrust the ECB. The policy relevance of such results is important for ECB's communication strategy with the general public.