Annual Conference

|

Corporate Finance, Senior Fellows/Fellows

|

May 2023

Political Partisanship and the Transmission of Fiscal Policy

Francesco DACUNTO, Pulak GHOSH, Alberto G. ROSSI
We document that support for the ruling party (“partisanship”) increases the take-up of government programs in which participation is costly. The take-up rates of a large-scale Indian loan-guarantee program, Mudra loans, diverge across low- and high-partisanship electoral districts but only mont...
Keywords: Heterogeneous Beliefs, Political Finance, Government Spending, Loans, Fiscal Policy, Government Programs, Small Businesses, Media Economics, Information Economics
  • View
  • Download
  •    |   

Annual Conference

|

Corporate Finance

|

May 2023

Tax Incentives, Small Businesses, and Physical Capital Reallocation

Riddha BASU, Doyeon KIM, Manpreet SINGH
Our study presents novel evidence on the physical capital reallocation e↵ect of temporary federal tax incentives. Using data on equipment purchases by small businesses, we found that temporary tax subsidies on new equipment, specifically in accelerated depreciation, increase investment in old capi...
Keywords: Taxes, Bonus Depreciation, Old Capital, Capital Reallocation, Investment
  • View
  • Download
  •    |   

Annual Conference

|

Corporate Finance

|

May 2023

Nationalistic Labor Policies Hinder Innovation

Francesco DACUNTO, Hengyi HUANG, Michael WEBER, Jin XIE, Liu YANG
Hiring restrictions for high-skilled foreign nationals hinder domestic firms’ production of cutting-edge innovation. We document this fact using the Employ American Workers Act (EAWA), which banned US financial institutions participating in the Troubled Asset Relief Program (TARP) from hiring new ...
Keywords: FinTech, Cybersecurity, Labor and Finance, Financial Regulation, IO and Finance, High-skilled workforce, Immigration, TARP
  • View
  • Download
  •    |   

Annual Conference

|

Corporate Finance

|

May 2023

Learning Production Process Heterogeneity Across Industries: Implications of Deep Learning for Corporate M&A Decisions

Jongsub LEE, Hayong YUN
Using deep learning techniques, we introduce a novel measure for production process heterogeneity across industries. For each pair of industries during 1990-2021, we estimate the functional distance between two industries’ production processes via deep neural network. Our estimates uncover the und...
Keywords: Deep learning, production process heterogeneity, M&A’s, integration synergy, the boundaries of the firm
  • View
  • Download
  •    |   

Annual Conference

|

Corporate Finance

|

May 2023

Managerial Learning from Decoding Noisy Stock Prices: New(s) Evidence

Alan KWAN, Tse-Chun LIN, Po-Yu LIU
A long literature argues corporate managers learn from stock prices, but organizations’ learning process is challenging to observe. We present a novel test using firm-level readership of financial media articles as a manifestation of managerial learning. We hypothesize that reading financial media...
Keywords: big data, managerial learning, market feedback effects, financial news, R&D
  • View
  • Download
  •    |