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This study employs a suitable volatility model that examines the impact of COVID-19 new cases and deaths on the volatility of daily job loss in Malaysia. Autoregressive Distributed Lag (ARDL) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) were employed as the modelling strategy to estimate daily data from January to December 2020. In addition, the asymmetric GARCH-M (EGARCH-M, TGARCH-M, and PGARCH-M) were further applied. The findings from different versions of the ARDL(p,q1,q2)-(E,T,P)GARCH(1,1)-M model show that the ARDL-EGARCH-M model can capture the volatility and clustering of variability in job loss. The findings revealed asymmetry effects, suggesting that negative shocks (bad news) in a pandemic period increased volatility in job loss compared to positive shocks (good news). Policy implications relating to lockdown measures and news signals were provided.

Farmer hypothesised that there is a linear long-run relationship between the movement of the stock market and movement in the unemployment rate, and there is a unidirectional causality running from stock market to unemployment rate. In this study we test the Farmer hypothesis by using Malaysia’s daily data on stock price and unemployment rate during the COVID-19 pandemic. We performed unit root, cointegration and short-run as well long-run non-causality tests between the stock market and unemployment rate using high frequency data for the period January to October 2020. Our results suggest that both stock market and unemployment rate are non-stationary and cointegrated. The causality test results suggest that using shorter lag, Farmer hypothesis is rejected while at longer lags, Farmer hypothesis cannot be rejected.

This paper examines the distributional effect of lockdown measures on the loss of income. The significance of the study relates to the use of daily data on loss of income and lockdown measures arising from the unprecedented COVID-19 pandemic. A conditional variable of the total loss of income was evaluated using hypothesized variables of international restrictions, domestic movement restrictions, public events closure, restriction on gathering, stay at home restrictions, school closure, and workplace closure. For a robust result, the study applied four variants of regression such as Ordinary Least Squares (OLS), Fully Modified OLS, Dynamic OLS, and Autoregressive Distributed Lag (ARDL) as the empirical methods. The findings revealed that loss of income during the COVID-19 period has a positive and significant relationship with the lockdown measures in Malaysia. This implies that as the government strengthens the international and domestic movement restrictions to reduce the impact of COVID-19, the most vulnerable income groups lose their income. This finding is relevant to policymakers regarding plans to rebuild a resilient economy to withstand future pandemics. Policy strategies to reduce restriction measures and allow for opening up the economy to enable the vulnerable income groups to regain their jobs and hence the lost income was discussed.

In the United Arab Emirates (UAE), the community police have been tasked with fostering community development. This study, conducted in the district of Baniyas in Al Shamkhah, explores the links between the constructs of integrity, trust, and community satisfaction, with performance serving as the moderator in the setting of the UAE. A quantitative research design built on a pragmatic approach was adopted. The complicated correlations between the constructs were estimated using descriptive statistics and partial least squares structural equation modeling (PLS-SEM) to answer the research questions. Integrity and trust, essential for effective community policing, were found to have a significant association with community happiness. Performance's moderating influence is on the link between integrity and community happiness. Thus, the trust serves as a predictor of happiness. The findings demonstrated that the policy feedback theory (PFT), legitimacy theory, and conceptual model given in this study provide explanatory aspects for community happiness and policing and explain the effect of police integrity and trust on community happiness. Future research should include additional constructs and variables, investigate community police officers' perceptions of community happiness, and measure the interrelationship between constructs to manipulate and strengthen the applicability of the theoretical model proposed in this study.