This paper studies how demand for labor reacts to financial technology (fintech) shocks based on comprehensive databases of fintech patents and firm job postings in the U.S. during the past decade. We first develop a measure of fintech exposure at the occupation level by intersecting the textual...

This dissertation with the title “The Valuation of River Ecosystem Services” consists of three papers. It begins with the retrospect of the historical development of cost-benefit analysis and the non-market valuation techniques (Paper 1 and 2). We highlight that the origin of cost-benefit...

Based on a survey of AFA members, we analyze how demographics, time allocation, production mechanisms, and institutional factors affect research production during the pandemic. Consistent with the literature, research productivity falls more for women and faculty with young children....

Using both a linear regression method and a probability-based method, we find that on average, analysts place larger than efficient weights on (i.e., they overweight) their private information when they forecast corporate earnings. We also find that analysts overweight more when issuing...

Using both a linear regression method and a probability-based method, we find that on average analysts place larger than efficient weights on (i.e., they over-weight) their private information when they forecast corporate earnings. We also find that analysts over-weight more when issuing...

We propose a tractable model of dynamic investment, division sales (spinoffs), financing, and risk management for a multi-division firm that faces costly external finance. The model highlights the importance of considering the intertwined nature of the different policies. Our main results are as...

This paper analyzes how corporate disclosure has been reshaped by machine processors, employed by algorithmic traders, robot investment advisors, and quantitative analysts. Our findings indicate that increasing machine and AI readership, proxied by machine downloads, motivates firms to prepare...