By Miguel Faria-e-Castro
I use a dynamic stochastic general equilibrium model to study the effects of the 2019-20 coronavirus pandemic in the United States. The pandemic is modeled as a large negative shock to the utility of consumption of contact-intensive services. General equilibrium forces propagate this negative shock to the non-services and financial sectors, triggering a deep recession. I use a calibrated version of the model to analyze different types of fiscal policies: (i) government purchases, (ii) income tax cuts, (iii) unemployment insurance benefits, (iv) unconditional transfers, and (v) liquidity assistance to services firms. I find that UI benefits are the most effective tool to stabilize income for borrowers, who are the hardest hit, while savers favor unconditional transfers. Liquidity assistance programs are effective if the policy objective is to stabilize employment in the affected sector.
I usually do not promote the papers of my colleagues on this blog, but this time I have to. This is a very timely paper looking at the policy options in the current context of the Covid-19 pandemic and its very high expected unemployment. It also shows that DGE models can be used to analyze economic phenomena for which we have no empirical history to draw from: theory is the only tool we have. And it can deliver its results very fast (the paper took one week to make it to NEP-DGE, in this context even to slow…).