We study the impact of the Covid-19 pandemic on Euro Area inflation and how it compares to the experiences of other countries, such as the United States, over the two-year period 2020-21. Our model-based calibration exercises deliver four key results: 1) Compositional effects - the switch from...

We study the aggregate effects of supply-chain disruptions in the post-pandemic period in a heterogeneous-firm, general equilibrium model with input-output linkages and a rich set of supply chain frictions: uncertain shipping delays, fixed order costs, and storage costs. Firms optimally hold...

"Climate change and the recent COVID-19 pandemic have exposed the vulnerability of global agricultural supply and value chains. There is a growing awareness of the importance of interactions within and between these supply chains for understanding the performance of agricultural markets. This...

Global supply chains have come under unprecedented stress as a result of US-China trade tensions, the Covid-19 pandemic, and geopolitical shocks. We document shifts in the pattern of US participation in global value chains over the last four decades, in terms of partner countries, products, and...

Prices are regulated in many markets, ranging from healthcare to labor to telecommunications. This paper reinterprets the variables in the basic supply-demand model so that both product-definition and quantity are equilibrium outcomes. Specifically, compliance with price controls is achieved by...

We document that value-to-price, the ratio of Residual-Income-Model-based valuation to market price, subsumes the power of book-to-market ratio and many other value or quality measures in predicting stock returns. Long-short value-to-price portfolios hedge against momentum, revitalize the...

The key purpose of corporate finance is to provide methods to compute the value of projects. The baseline textbook recommendation is to use the Present Value (PV) formula of expected cash flows, with a discount rate based on the CAPM. In this paper, we ask what is, empirically, the best...

Sparse models, though long preferred and pursued by social scientists, can be ineffective or unstable relative to large models, for example, in economic predictions (Giannone et al., 2021). To achieve sparsity for economic interpretation while exploiting big data for superior empirical...