Is Rising Returns to Scale a Figment of Poor Data?
AbstractWhile using detailed firm-level data from the private business sector, this study identifies two empirical puzzles: (i) returns-to-scale (RTS) parameter estimates rise at higher levels of data aggregation, and (ii) estimates from the firm level suggest decreasing returns to scale. The analysis shows that, although consistent with rising estimates, the Basu-Fernald (1997) aggregation-bias effect does not drive this result. Rather, rising and too low returns-to-scale estimates probably reflect a mixture of random errors in factor inputs. It turns out, in fact, that a 7.5-10 percent error in labor (hours worked) can explain both puzzles.
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Bibliographic InfoPaper provided by National Institute of Economic Research in its series Working Paper with number 91.
Length: 38 pages
Date of creation: 01 May 2004
Date of revision:
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More information through EDIRC
Business cycles; Data aggregation; External economies; Factor hoarding; Firm-level data; Monte Carlo simulation; Random errors; Returns to scale;
Find related papers by JEL classification:
- D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
- L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
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