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Olley–Pakes productivity decomposition: computation and inference
Author(s) -
Hyytinen Ari,
Ilmakunnas Pekka,
Maliranta Mika
Publication year - 2016
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/rssa.12135
Subject(s) - inference , heteroscedasticity , econometrics , microdata (statistics) , computer science , computation , statistics , mathematics , statistical inference , productivity , algorithm , artificial intelligence , economics , population , demography , sociology , census , macroeconomics
Summary We show how a moment‐based estimation procedure can be used to compute point estimates and standard errors for the two components of the widely used Olley–Pakes decomposition of aggregate (weighted average) productivity. When applied to business level microdata, the procedure allows for autocovariance and heteroscedasticity robust inference and hypothesis testing about, for example, the coevolution of the productivity components in different groups of firms. We provide an application to Finnish firm level data and find that formal statistical inference casts doubt on the conclusions that one might draw on the basis of a visual inspection of the components of the decomposition.