Replication data for: Some Evidence on the Importance of Sticky Wages

Name: Replication data for: Some Evidence on the Importance of Sticky Wages
Published: 2014-01-01
License: This work is licensed under an Other license created by the data depositor. Please refer to the LICENSE file, which should be located alongside the project data and documentation.
Keywords: Measurement Error

Principal Investigator(s): View help for Principal Investigator(s) Alessandro Barattieri; Susanto Basu; Peter Gottschalk

Version: View help for Version V1

Name	File Type	Size	Last Modified
2011_0215_Programs-and-data			10/25/2021 02:08:PM
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Project Citation:

Barattieri, Alessandro, Basu, Susanto, and Gottschalk, Peter. Replication data for: Some Evidence on the Importance of Sticky Wages. Nashville, TN: American Economic Association [publisher], 2014. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-12. https://doi.org/10.3886/E114290V1

Project Description

Summary: We present evidence on the frequency of nominal wage adjustment using SIPP data adjusted for measurement error. The SIPP is a representative sample of the US population. Our main results are: (i) The average quarterly probability of a nominal wage change is between 21.1 and 26.6 percent, depending on the assumptions used. (ii) Wage changes are much more likely when workers change jobs. (iii) The frequency of wage adjustment does not display significant seasonal patterns. (iv) The hazard of a nominal wage change first increases and then decreases, with a peak at 12 months.

Scope of Project

Subject Terms: Measurement Error

JEL Classification:
      E24 Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
      E32 Business Fluctuations; Cycles
      E52 Monetary Policy
      J31 Wage Level and Structure; Wage Differentials

Geographic Coverage: Unites States

Time Period(s): 1996 – 2000

Data Type(s): survey data

Methodology

Data Source: SIPP

Unit(s) of Observation: Hourly workers,

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Published Versions

V1 [2019-10-12]

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