The pervasive effects of the novel coronavirus (COVID-19) have put the world to test. Its effects permeate all facets of life including healthcare services and food supplies. However, most empirical studies failed to investigate its effects on the prices of food and healthcare services, which by all standards, are essential commodities. On this background, this study evaluates the impact of COVID-19 reported cases and lockdown stringency measures on the food and healthcare prices in the six (6) worst-affected countries. For empirical purposes, daily prices of food and healthcare services between 22 nd January and 31 st December 2020 were regressed against daily cases of COVID-19 and lockdown stringency measures within the dynamic autoregressive distributed lag procedure. Empirical evidences reveal that prices of healthcare and food are cointegrated with COVID-19 cases and lockdown measures in all the selected countries except Italy. Equally, healthcare and food prices reinforced itself in the long-run in the US, the UK and France. Furthermore, COVID-19 cases lead to significant increases in food and healthcare prices in the US, whereas, food and healthcare prices in France and UK declined significantly as COVID-19 cases mount. Conversely, food and healthcare prices declined significantly in the US and soar in France and the UK in reactions to COVID-19 new cases. Likewise, government stringency measures and containment health measures contributed significantly to healthcare and food price hike in the US and France respectively. Meanwhile, healthcare and food prices in the other selected countries remained unaffected even as the pandemic ravages. Following this empirical discoveries, relevant policy guidelines have been communicated.
The purpose of this study is to proffer an explanation of comparative low per capita income in Nigeria using data on electricity loss. We hypothesized that per capita income is a function of electricity loss which we defined as the differential between actual electricity generated and actual electricity consumed. Using time series data from 1970 to 2005, we estimated a distributed lag model with Newey-West HAC standard errors. From the estimated model which was truncated at three lag lengths, we established an inverse relationship between per capita income and total electricity loss with all the distributed lag variables being statistically significant. The implication of this result is that electricity loss generally affect national output negatively which in turn reduces our per capita (income of the people). Policy measures that will ensure adequate protection and system stability of the existing fragile transmission and distribution network, the strengthening and expansion of the transmission and distribution infrastructure will reduce electricity loss and eventually improve our per capita income.
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