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Data and Code for: Small and Large Firms over the Business Cycle

Principal Investigator(s): View help for Principal Investigator(s) Nicolas Crouzet, Kellogg School of Management, Northwestern University; Neil Mehrotra, Federal Reserve Bank of New York

Version: View help for Version V1

Name	File Type	Size	Last Modified
code			07/17/2020 12:33:AM
input			07/17/2020 12:33:AM
data_overview.xlsx	application/vnd.openxmlformats-officedocument.spreadsheetml.sheet	13 KB	07/16/2020 08:33:PM
readme.txt	text/x-matlab	14.3 KB	08/03/2020 07:59:AM

Project Citation:

Crouzet, Nicolas, and Mehrotra, Neil. Data and Code for: Small and Large Firms over the Business Cycle. Nashville, TN: American Economic Association [publisher], 2020. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-10-26. https://doi.org/10.3886/E119865V1

Project Description

Summary: This paper uses new confidential Census data to revisit the relationship between firm size, cyclicality, and financial frictions. First, we find that large firms (the top 1% by size) are less cyclically sensitive than the rest. Second, high and rising concentration implies that the higher cyclicality of the bottom 99% of firms only has a modest impact on aggregate fluctuations. Third, differences in cyclicality are not simply explained by financing, and in fact appear largely unrelated to proxies for financial strength. We instead provide evidence for an alternative mechanism based on the industry scope of the very largest firms.

Scope of Project

Subject Terms: Firm size; Business cycles; Financial accelerator

JEL Classification:
      E32 Business Fluctuations; Cycles
      E44 Financial Markets and the Macroeconomy
      G31 Capital Budgeting; Fixed Investment and Inventory Studies; Capacity

Geographic Coverage: USA

Time Period(s): 1977 – 2014

Collection Date(s): 1977 – 2014

Universe: US manufacturing firms with more than $250k in assets, 1977-2014; US retail and trade firms with more than $50m in assets, 1977-2014.

Data Type(s): administrative records data; census/enumeration data; program source code; survey data

Methodology

Response Rate: Varies over time; documented in the QFR press releases, available at https://www.census.gov/econ/qfr/.

Sampling:

The QFR target population consists of all corporations engaged primarily in manufacturing with total assets of $250,000 and over, and all corporations engaged primarily in mining; wholesale trade; retail trade; information; or professional and technical services (except legal services) industries with total assets of $50 million and over. More information on sampling frame and sampling methodology are available at https://www.census.gov/econ/qfr/collection.html

Data Source: The QFR sampling frame is developed from a file received annually from the IRS. This file contains select information for corporations required to file Form 1120, 1120A, or 1120S. Once this file is received, the QFR examines the information and assigns an initial NAICS industry code to each corporation. Then this file is stratified based on the NAICS code, size of total assets and size of receipts. More information on sampling frame and sampling methodology are available at https://www.census.gov/econ/qfr/collection.html

Collection Mode(s): mail questionnaire; record abstracts

Scales: n.a.

Weights: Weights internally developed by Census and made available to the researchers as part of the primary data are used in the analysis. More information on sampling frame and sampling methodology are available at https://www.census.gov/econ/qfr/collection.html

Unit(s) of Observation: Firm

Geographic Unit: USA

Related Publications

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Published Versions

V2 [2021-12-12]

V1 [2020-10-26]

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