This paper investigates the effect of the COVID-19 and oil prices on the US partisan conflict. Using daily data on world COVID-19 and oil prices, monthly data on the US Partisan Conflict index, and the MIDAS method, the finding suggests that both COVID-19 and oil prices mitigate US political polarization. The finding implies that political leaders aim low for partisan gains during stressful times.

This paper examines the effect of Covid-19 pandemic on the Chinese stock market returns and their volatility using the generalized autoregressive conditionally heteroskedastic GARCHX model. The GARCHX model allows us to include Covid-19 information within the GARCH framework. The findings document that daily increases in total confirmed Covid-19 cases in China, measured as total daily deaths and cases, have a significant negative impact on stock returns, with the negative impact of the Covid-19 on stock returns being more pronounced when total deaths proxy the effect of this infectious disease. The results also document that Covid-19 has a positive and statistically significant effect on the volatility of these market returns. Overall, new evidence is offered that infectious diseases, such as Covid-19, can seriously impact market returns, as well as their volatility. The findings could be essential in understanding the implications of Covid-19 for the stock market in China.

The goal of this work is to explore the role of the Covid-19 pandemic event in the course of inflation expectations and their volatility through US inflation swap rates. The findings document that inflation expectations and their volatility are positively affected by the Covid-19 pandemic. These results have real activity implications, while close monitoring of inflation expectations could signal inflation expectations un-anchoring risks.

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Purpose The purpose of this paper is to explore the link between corruption and government debt through a regime-based approach. Design/methodology/approach The empirical analysis makes use of a panel of 120 countries, spanning the period 1999–2015. The study makes use of the Panel Smooth Transition Regression (PSTR) methodological approach, as well as two alternative measures of corruption. Findings The empirical results document that the relationship between corruption and debt is non-linear, while a strong threshold effect was present as well. Public debt appears to respond faster to a high corruption regime compared to a low corruption regime, while an increase in the size of the shadow economy, government expenses, the inflation rate, interest payments on debt and military expenditure all increased the debt to GDP ratio. By contrast, an increase in GDP per capita, the secondary school enrollment ratio and the ratio of tax revenues to GDP led to a fall in the debt to GDP ratio. The findings survive certain robust checks when the role of the 2008 financial crisis is explicitly considered, as well as when two separate country samples were considered, i.e. developed vs developing countries. Practical implications Governments should aim to control both corruption and the size of the shadow economy if they really wish to reduce any high levels of their public debt. As debt levels respond faster to high corruption regimes, it is necessary that measures to reduce corruption are complemented by higher GDP per capita growth rates, enrolment rates and higher tax revenues. Originality/value The novelty of the paper is that it investigates for the first time, to the best of the authors’ knowledge, the presence of non-linearity between corruption and government debt. It proposes non-linear panel cointegration and causality tests, as well as a non-linear panel error correction model that allows for smooth changes between regimes, hence, examining causal relationships in each regime separately.

This paper explores the impact on the macroeconomy for certain OECD economies exposed to the COVID-19 pandemic shock. The analysis employs a panel of OECD countries, spanning the period March 2020 to January 2021. It also uses two proxies for the COVID-19 shocks: i) total confirmed incidences/cases and ii) total deaths while using the Bayesian Panel Vector Autoregressive (BPVAR) method. The findings document that the COVID-19 shock exerts a strong negative effect on industrial production. Considering how such epidemic shocks affect the expectations of economic participants, the paper questions their absence in accounting for forthcoming growthrelated incidences.

The present analysis performs a Multinomial Probit Model in order to observe which mobile technology qualifies across individuals. The findings indicate that individuals in family businesses prefer to combine both tablets and smartphones in their purchases, rather than separately. Younger individuals report an adoption preference towards smartphones, while older individuals are inclined towards tablets. The theoretical contributions encompass both the technology acceptance model (TAM) and the social cognitive theory (SCT).Individuals working in a family business exhibit a curious behaviour and they are becoming early adopters. TAM helps explain this behaviour as they tend to try new novelties exploring the potential usefulness they might derive; these technological advancements allow them to connect with customers and partners. By contrast, SCT helps gain a better understanding on young by their peers with a tendency to technologies which are fun and allow them to build connections. Older individuals are equally influenced by their peers, with the difference that their social circle being more mature (e.g., business owners, professionals). This combined with the complexity of the technology orients them into adopting tablets more easily than smartphones.