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This research examines the impact of lockdown stringency measures and COVID-19 cases on food and healthcare prices in six Brazil, Russia, India, China, South Africa and Turkey (BRICST) countries. This research is conducted in these countries since previous studies failed to examine the effect of COVID-19 reported cases on food and healthcare prices.

To achieve the objectives of this study, food and healthcare services were regressed against CVC and lockdown stringency measures using the dynamic autoregressive distributed lag (DARDL) model. For this purpose, we used daily data for BRICST countries such as Brazil, Russia, India, China, South Africa and Turkey.

The empirical evidence indicates that, in the long run, COVID-19 cases significantly and positively affect both food and healthcare prices in India, South Africa and China. In contrast, in the short run, COVID-19 positively affects food and healthcare prices in all countries except Russia and Turkey. Similarly, in the long run, the government stringency index (GSI) and Containment and Health Index (CHI) significantly affect health prices in India and South Africa. In contrast, GSI and CHI significantly affect healthcare prices in South Africa only in the short run. Finally, GSI and CHI significantly affect the food prices in the long run in India, South Africa and China and in the short run in South Africa only.

The widespread impact of the new Coronavirus (COVID-19) has made the world panic. COVID-19 affected all spheres of life, including food supplies and healthcare services. However, most of the empirical research failed to examine the impact of COVID-19 cases on food and healthcare prices which is the main focus of this study. Moreover, in the given context, the authors use a recently developed model that the previous studies failed to use.

This study examines the short-run and long-run impact of macroeconomic variables such as industrial production index, inflation, exchange rate, interest rate, foreign direct investment and trade balance, on KSE 100 index and sectorial stock indices under bearish, bullish and normal states of the stock market prices. Moreover, we take into account the effect of three crises observed from 2005 to 2009.

This study uses quantile autoregressive distributed lag (QARDL) model for examining the short-run and long-run effect across various quantiles of the dependent variables and compare its' results standard autoregressive distributed lag (ARDL) model.

ARDL estimates indicate that, in the long-run, industrial production index, trade balance and foreign direct investment significantly affect stock prices. These findings remain same when three crises have been taken into consideration. In addition, estimates from QARDL model indicate that, in the short-run, the effect of exchange rate, interest rate, consumer price index and foreign direct investment, varies across bearish, bullish and normal states of the overall stock prices. Moreover, the short-run findings for Auto Assembler, Cement, Commercial Banks sector are consistent with overall stock indices, whereas other sectors, such as, Oil and Gas and Power Generation and distribution are asymmetrically affected by all macroeconomic variables. In the long-run, the effect of all macro-variables varies across different states of the stock markets except industrial production index for Auto Assembler sector, Oil and Gas sector and composite index of KSE 100 index.

We take into account the effect of three crises observed from 2005 to 2009 and also examine the macroeconomic effect across bullish, bearish and normal states of the sectorial stock indices and composite index of Pakistan stock exchange. Finally, we use novel approach, called QARDL model, which has several advantages over other techniques.