2007
DOI: 10.1016/j.jmoneco.2007.06.002
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Search frictions: Matching aggregate and establishment observations

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Cited by 127 publications
(149 citation statements)
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“…Our model is a version of the canonical Diamond-Mortensen-Pissarides random matching framework with decreasing returns in production and nonconvex hiring costs (Cooper, Haltiwanger, and Willis, 2007;Elsby and Michaels, 2013;Acemoglu and Hawkins, 2014). The model simultaneously features a realistic firm life cycle, consistent with its classic competitive setting counterparts (Jovanovic, 1982;Hopenhayn, 1992), and a frictional labor market with slack on both demand and supply sides.…”
Section: Notes: (I) Vacancies V T and Hires H T (Used To Compute Vacamentioning
confidence: 99%
“…Our model is a version of the canonical Diamond-Mortensen-Pissarides random matching framework with decreasing returns in production and nonconvex hiring costs (Cooper, Haltiwanger, and Willis, 2007;Elsby and Michaels, 2013;Acemoglu and Hawkins, 2014). The model simultaneously features a realistic firm life cycle, consistent with its classic competitive setting counterparts (Jovanovic, 1982;Hopenhayn, 1992), and a frictional labor market with slack on both demand and supply sides.…”
Section: Notes: (I) Vacancies V T and Hires H T (Used To Compute Vacamentioning
confidence: 99%
“…With regard to labor adjustment, he finds "high" fixed costs of labor adjustments in the U.S. (around 2.1% of a firm's annual revenue) and only "limited" per capita costs of hiring and firing. Cooper, Haltiwanger and Willis (2007), using a search model calibration, also reach a clear conclusion that the lumpy pattern of employment adjustments in the U.S. appears to be due to large fixed costs of hiring and/or firing. However, analysis in Davis, Faberman and Haltiwanger (2013) shows that hiring activities have very minimal returns to scale, which suggests that fixed costs of hiring are not the primary driver of lumpy employment patterns.…”
Section: Related Literaturementioning
confidence: 87%
“…11 Table 1 demonstrates that real GDP Granger causes markups, but markups do not Granger cause GDP. 12 That is, observations of GDP have predictive power for markups, but observations of markups 10 We show in Appendix 2 that using alternative measures of markups, e.g., the ratio of revenues to employee compensation, leads to similar results. 11 To detrend, we subtract a quadratic trend.…”
Section: Factmentioning
confidence: 89%