主讲人简介：

Eugene Tan is an Assistant Professor of Economic Analysis and Policy at the Rotman School of Management. He graduated with a PhD in economics from Duke University, and did his undergraduate at the University of Michigan. His general research lies in firm investment dynamics as broadly applied to macroeconomics. In recent work, he has studied the implications of capital resale frictions for startup growth and gains from trade, capital budgeting frictions for information allocation across firms, and capital supply and consumer demand frictions as a source of racial disparities in startup growth.

Abstract

We develop an investment model with capital budgeting, where firms endogenously learn about firm fundamentals and make partially flexible investment plans. In the model, high-productivity firms have an incentive to acquire better information, giving rise to a novel channel of improved information allocation that reduces capital misallocation. However, net gains hinge on the cost of learning. We quantify the importance of this channel by calibrating our model to data on firms’ expectations and planned investment. Misallocation is substantially mitigated when only learning incentives are accounted for, but these net gains are reduced because learning costs empirically increase in productivity.