This study adopts a disaggregated regional focus to test for the human capital (HC)-growth nexus in selected nine Asian countries. It utilizes the Empirical Bayesian methodology which addresses not only the heterogeneity issue but it also utilizes the common structural priors of regional countries to yield ‘informationally’ efficient estimates of the impact of HC on the stock and levels of GDP. Various measures of HC are utilized to determine which of these produces a better explanation of economic growth in the two Asian regions. The study finds that primary and secondary education was more prominent in explaining the fluctuations of economic growth in East Asia, whereas tertiary and vocational education showed positive effects on economic growth in South Asia. Government expenditures on education were also found to positively affect economic growth in both regions. The results shed new evidence to establish that the differences in growth rates within East and South Asia are associated with differences in educational progression in the regions.

Monetary policy tools, including money supply and interest rate, are the most popular instruments to control inflation around the globe. It is assumed that a tight monetary policy, either in form of reduction in money supply or an increase in interest rate, will reduce inflation by reducing aggregate demand in an economy. However, monetary policy could be counterproductive if cost side effects of monetary tightening prevail. High energy prices may increase the cost of production by reducing aggregate supply in the economy. If tight monetary policy is used to reduce this cost push inflation, the cost side effect of energy prices will add to cost side effects of monetary tightening and will become dominant. In this case, the monetary policy could be counterproductive. Furthermore, simultaneous reduction in aggregate supply and aggregate demand will bring twofold reduction in output. Therefore greater care is needed in the use of monetary policy in the situation of cost push inflation. This article investigates the presence of cost side effect of monetary transmission mechanism, the role of international oil prices in domestic inflation, and implications for monetary policy. The findings suggest that both monetary policy and oil prices have cost side effects on inflation and monetary tightening could be counterproductive if used to reduce energy pushed inflationary trend.

This paper contributes to the social science literature when analyzing survey or time series data social scientists use spurious regression without due consideration of its assumptions and the data structure. This results in misinterpretation and misleading conclusions about the population. The paper reviews basic statistical and econometrics literature which led to the development of modern time series analysis in the presence of spurious regression. It concludes that the term ‘Spurious’ was well known before the Granger and Yule’s work in time series context rather than cross-sectional data. The same reasons can produce spurious regression today and surely the solution doesn’t exist in the cointegration analysis. Social scientists and applied econometrician investigators need more serious thinking and care to avoid spurious regression, if it is necessary even if data is stationary or cross-sectional. In this study, we extended the Ghouse experiment which is based on simulated data by employing real-world data to assess the effectiveness of the newly proposed Ghouse Equation in comparison to conventional approaches. The findings demonstrate that the Ghouse Equation produces the lowest probability of spurious regression as compared to its counterparts. Moreover, in forecasting performance, Ghouse Equation outperformed its counterparts. These results highlight the Ghouse Equation as a valuable and better tool for econometric analysis for nonstationary time series.

This paper explored the energy–environment–economy (EEE) causal nexus of Pakistan, thereby reporting the causal determinants of the EEE nexus by employing the newly developed modified Peter and Clark (PC) algorithm. The modified PC algorithm was employed to investigate the causal ordering of energy consumption, CO₂ emissions and economic growth across Pakistan’s domestic, industrial, transportation and agricultural sectors. An empirical comparison, i.e., following Monte Carlo simulation experiments demonstrates that the proposed modified PC algorithm is superior to the original PC proposition and can differentiate between true and spurious nexus causalities. Our results show that significant causality is running from energy consumption in industrial and agricultural sectors towards economic growth. There is no causal association between energy consumption and economic growth in the domestic and transportation sectors. On the other hand, causality runs from energy consumption in the transportation, domestic and industrial sectors towards CO₂ emissions. It is concluded that energy consumption in industrial and agricultural sectors leads to economic growth alongside the associated CO₂ emissions. On the other hand, the contribution of domestic and transportation sectors in economic growth is trivial with significant CO₂ emissions. This paper provides novel empirical evidence of impacts of energy mismanagement at sectoral levels, economic output and environmental consequences; alongside policy recommendations for sustainable energy-based development on the national scale.