Econometric analysis of productivity with measurement error: Empirical application to the US Railroad industry

Arbeitspapier

This paper analyzes the productivity in the US rail industry for the period 1980 - 2006. I propose a value-added production framework to circumvent the problem of measurement error in one input. I find evidence showing that aggregate productivity gains can be attributed to returns to scale and the reshuffling of resources to more efficient firms. However, productivity slows down for the period 1995 - 2000 after important concentrations. I also look at the correlations between firm-level productivity and the operating environment. My results show that failing to control for the omitted price variable bias leads to an overestimation of productivity gains.

Object Details

• ISBN: 978-3-86304-094-9
• Language: Englisch

References and Relationships

• Bibliographic citation: Series: DICE Discussion Paper ; No. 95

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Truncated and Censored Models; Switching Regression Models; Threshold Regression Models ; Production, Pricing, and Market Structure; Size Distribution of Firms ; Regulation and Industrial Policy: General ; Railroads and Other Surface Transportation ; Industry Studies: Utilities and Transportation: Government Policy
• Subject: industry dynamics ; measurement error ; productivity ; selection ; simultaneity ; railroad industry

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Coublucq, Daniel
• Event: Veröffentlichung
• (who): Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE)
• (where): Düsseldorf
• (when): 2013

Further information

• Handle: http://hdl.handle.net/10419/75216
• Last update: 10.03.2025, 11:44 AM CET