Data and Code for: Convex Supply Curves

Principal Investigator(s): View help for Principal Investigator(s) Christoph Boehm, University of Texas-Austin; Nitya Pandalai-Nayar, University of Texas-Austin

Version: View help for Version V1

Name	File Type	Size	Last Modified
disclosed from census			10/20/2022 10:53:AM
empirics			10/20/2022 10:53:AM
model			10/20/2022 03:28:PM
output			10/20/2022 03:28:PM
README.pdf	application/pdf	264.4 KB	10/20/2022 06:52:AM
documentation.xlsx	application/vnd.openxmlformats-officedocument.spreadsheetml.sheet	20.5 KB	10/20/2022 06:52:AM

Project Citation:

Boehm, Christoph, and Pandalai-Nayar, Nitya. Data and Code for: Convex Supply Curves. Nashville, TN: American Economic Association [publisher], 2022. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-11-21. https://doi.org/10.3886/E172781V1

Project Description

Summary: We provide evidence that industries' supply curves are convex. To guide our empirical analysis, we develop a model in which capacity constraints at the firm level generate supply curves that are convex in logs at the industry level. The industry's capacity utilization rate is a sufficient statistic for the supply elasticity. Using data on capacity utilization and three different instruments, we estimate the supply curve and find robust evidence for an economically sizable degree of convexity. The nonlinearity we identify has several macroeconomic implications, including that responses to shocks are state-dependent and that the Phillips curve is convex.

Funding Sources: European Central Bank (Lamfalussy Fellowship 2016)

Scope of Project

Subject Terms: Slack; Utilization; Capacity; Supply Curves; State-Dependence; Fiscal Policy; Monetary Policy

JEL Classification:
      E22 Investment; Capital; Intangible Capital; Capacity
      E23 Macroeconomics: Production
      E32 Business Fluctuations; Cycles
      E52 Monetary Policy
      E62 Fiscal Policy

Geographic Coverage: USA

Time Period(s): 1972 – 2011

Universe: US 3-digit NAICS Manufacturing Industries

Data Type(s): aggregate data

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Published Versions

V1 [2022-11-21]

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