Measuring Cross-Country Differences in Misallocation

23 Pages Posted: 15 Nov 2016

See all articles by Mitsukuni Nishida

Mitsukuni Nishida

Johns Hopkins University - Carey Business School

Amil Petrin

University of Minnesota - Duluth; National Bureau of Economic Research (NBER)

Martin Rotemberg

New York University (NYU)

T. White

Government of the United States of America - Bureau of the Census

Date Written: November 1, 2016

Abstract

In this paper, we discuss the role that data processing and collection have for the measurement of misallocation. First, we turn to the raw self-reported data for the US, reflecting what can be found in most developing countries. In the raw data, measured misallocation (following Hsieh and Klenow 2009) is substantially higher than for any other country for which we have census data. For instance, if Indian firms had the same dispersion of distortions as measured in the reported US data, TFP in the Indian manufacturing sector would decrease by around 2/3. Second, we follow a different strategy for editing and imputing missing data than what is used by the US Census Bureau, by using a method that seeks to replicate the true variance in the underlying data generating process known as Classification and Regression Trees (CART). This change raises the potential gains from removing misallocation in the United States manufacturing sector by around 10%.

Suggested Citation

Nishida, Mitsukuni and Petrin, Amil and Rotemberg, Martin and White, T., Measuring Cross-Country Differences in Misallocation (November 1, 2016). US Census Bureau Center for Economic Studies Paper No. CES-WP-16-50. Available at SSRN: https://ssrn.com/abstract=2869246 or http://dx.doi.org/10.2139/ssrn.2869246

Mitsukuni Nishida (Contact Author)

Johns Hopkins University - Carey Business School ( email )

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Amil Petrin

University of Minnesota - Duluth ( email )

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National Bureau of Economic Research (NBER)

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Martin Rotemberg

New York University (NYU) ( email )

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T. White

Government of the United States of America - Bureau of the Census

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