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This study investigates the interactions between the US daily public debt and currency power under impacts of the Covid-19 crisis.

The authors employ the multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) modeling to explore the interactions between daily changes in the US Debt to the Penny and the US Dollar Index. The data sets are from April 01, 1993, to May 27, 2022, in which noticeable points include the Covid-19 outbreak (January 01, 2020) and the US vaccination campaign commencement (December 14, 2020).

The authors find that the daily change in public debt positively affects the USD index return, and the past performance of currency power significantly mitigates the Debt to the Penny. Due to the Covid-19 outbreak, the impact of public debt on currency power becomes negative. This effect remains unchanged after the pandemic. These findings indicate that policy-makers could feasibly obtain both the budget stability and currency power objectives in pursuit of either public debt sustainability or power of currency. However, such policies should be considered that public debt could be a negative influencer during crisis periods.

The authors propose a pioneering approach to explore the relationship between leading and lagging indicators of an economy as characterized by their daily data sets. In accordance, empirical findings of this study inspire future research in relation to public debt and its connections with several economic indicators.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2022-0581

This study unravels an attempt to investigate the dynamic connectedness of agri-commodity (wheat) of Russia with 10 financial markets of wheat importing counties during the Russia–Ukraine invasion.

This study took the daily prices of Wheat FOB Black Sea Index (Russia) along with stock indices of 10 major wheat-importing nations of Russia and Ukraine. The time frame for this study ranges from February 24, 2022 to July 31, 2022. This time frame was selected since it fully examines all of the effects of the crisis. The conditional correlations and volatility spillovers of these indices are predicted using the DCC-GARCH model, Diebold and Yilmaz (2012) and Baruník and Křehlík (2018) models.

It is found that there is dynamic linkage of agri-commodity of with stock markets of Iraq, Pakistan and Tanzania in short run while stock markets of Egypt, Turkey, Bangladesh, Pakistan, Brazil and Iraq are spilled by agri-commodity in long run. In addition, it documents that there is large spillover in short run than medium and long run comparatively. This signifies that investors have more diversification opportunity in short run then long run contemplating to invest in these markets.

To the best of the authors’ understanding this is the first study to undertake the dynamic linkage of agri-commodity (wheat) of Russia with financial market of select importing counties during the Russia–Ukraine invasion.