Hakki Yazici
Slavík Ctirad
Kina Özlem
Tilman Graff
Tilman Graff
Yuri Ostrovsky
Martin Munk
Anton Heil
Maitreesh Ghatak
Robin Burgess
Oriana Bandiera
Claire Balboni
Jonna Olsson
Richard Foltyn
Minjie Deng
Iiyana Kuziemko
Elisa Jácome
Juan Pablo Rud
Bridget Hofmann
Sumaiya Rahman
Martin Nybom
Stephen Machin
Hans van Kippersluis
Anne C. Gielen
Espen Bratberg
Jo Blanden
Adrian Adermon
Maximilian Hell
Robert Manduca
Robert Manduca
Marta Morazzoni
Aadesh Gupta
David Wengrow
Damian Phelan
Amanda Dahlstrand
Andrea Guariso
Erika Deserranno
Lukas Hensel
Stefano Caria
Vrinda Mittal
Ararat Gocmen
Clara Martínez-Toledano
Yves Steinebach
Breno Sampaio
Joana Naritomi
Diogo Britto
François Gerard
Filippo Pallotti
Heather Sarsons
Kristóf Madarász
Anna Becker
Lucas Conwell
Michela Carlana
Katja Seim
Joao Granja
Jason Sockin
Todd Schoellman
Paolo Martellini
UCL Policy Lab
Natalia Ramondo
Javier Cravino
Vanessa Alviarez
Hugo Reis
Pedro Carneiro
Raul Santaeulalia-Llopis
Diego Restuccia
Chaoran Chen
Brad J. Hershbein
Claudia Macaluso
Chen Yeh
Xuan Tam
Xin Tang
Marina M. Tavares
Adrian Peralta-Alva
Carlos Carillo-Tudela
Felix Koenig
Joze Sambt
Ronald Lee
James Sefton
David McCarthy
Bledi Taska
Carter Braxton
Alp Simsek
Plamen T. Nenov
Gabriel Chodorow-Reich
Virgiliu Midrigan
Corina Boar
Sauro Mocetti
Guglielmo Barone
Steven J. Davis
Nicholas Bloom
José María Barrero
Thomas Sampson
Adrien Matray
Natalie Bau
Darryl Koehler
Laurence J. Kotlikoff
Alan J. Auerbach
Irina Popova
Alexander Ludwig
Hakki Yazici
Slavík Ctirad
Kina Özlem
Tilman Graff
Tilman Graff
Yuri Ostrovsky
Martin Munk
Anton Heil
Maitreesh Ghatak
Robin Burgess
Oriana Bandiera
Claire Balboni
Jonna Olsson
Richard Foltyn
Minjie Deng
Iiyana Kuziemko
Elisa Jácome
Juan Pablo Rud
Bridget Hofmann
Sumaiya Rahman
Martin Nybom
Stephen Machin
Hans van Kippersluis
Anne C. Gielen
Espen Bratberg
Jo Blanden
Adrian Adermon
Maximilian Hell
Robert Manduca
Robert Manduca
Marta Morazzoni
Aadesh Gupta
David Wengrow
Damian Phelan
Amanda Dahlstrand
Andrea Guariso
Erika Deserranno
Lukas Hensel
Stefano Caria
Vrinda Mittal
Ararat Gocmen
Clara Martínez-Toledano
Yves Steinebach
Breno Sampaio
Joana Naritomi
Diogo Britto
François Gerard
Filippo Pallotti
Heather Sarsons
Kristóf Madarász
Anna Becker
Lucas Conwell
Michela Carlana
Katja Seim
Joao Granja
Jason Sockin
Todd Schoellman
Paolo Martellini
UCL Policy Lab
Natalia Ramondo
Javier Cravino
Vanessa Alviarez
Hugo Reis
Pedro Carneiro
Raul Santaeulalia-Llopis
Diego Restuccia
Chaoran Chen
Brad J. Hershbein
Claudia Macaluso
Chen Yeh
Xuan Tam
Xin Tang
Marina M. Tavares
Adrian Peralta-Alva
Carlos Carillo-Tudela
Felix Koenig
Joze Sambt
Ronald Lee
James Sefton
David McCarthy
Bledi Taska
Carter Braxton
Alp Simsek
Plamen T. Nenov
Gabriel Chodorow-Reich
Virgiliu Midrigan
Corina Boar
Sauro Mocetti
Guglielmo Barone
Steven J. Davis
Nicholas Bloom
José María Barrero
Thomas Sampson
Adrien Matray
Natalie Bau
Darryl Koehler
Laurence J. Kotlikoff
Alan J. Auerbach
Irina Popova
Alexander Ludwig

Misallocation or mismeasurement?

What is this research about and why did you do it?

A determinant of aggregate productivity differences, both across countries and within countries over time, is how well resources such as capital and labour are allocated across firms. The importance of such resource misallocation for aggregate productivity is often inferred from the dispersion in average revenue products (revenues over inputs) in firm-level data. Measurement error, for example due to omitted or double-counted revenue or inputs, implies that measured gaps in average products do not reflect true gaps in marginal products. This could thereby amplify dispersion in measured average products and lead researchers to overstate the magnitude of misallocation.

How did you answer this question?

We propose a methodology to correct estimates of misallocation for measurement error in revenue and inputs. Our approach exploits how revenue growth is less sensitive to input growth when a plant’s average products are overstated by measurement error. The key assumption is that the measurement errors are orthogonal to (i.e., uncorrelated with) the true marginal products. We apply our methodology to data on Indian manufacturing plants from 1985 to 2013 and U.S. Census data on manufacturing plants from 1978 to 2013.

Data sources are the Indian ASI and U.S. LRD. The India sub-figure shows uncorrected and corrected allocative efficiency for years 1985 to 2013. Average uncorrected allocative efficiency is 47.7% while average corrected allocative efficiency is 53.4%. The U.S. sub-figure show uncorrected and corrected allocative efficiency for years 1978 to 2013. Average uncorrected allocative efficiency is 47.6% while average corrected allocative efficiency is 67.4%.

What did you find?

We find that our correction lowers the potential gains from reallocation by 20% in India, but that measurement error is even more severe in the U.S. On average, our correction lowers the potential gains from reallocation in the U.S. by 60% between 1978 and 2013. Strikingly, measured revenue productivity dispersion in the U.S. exhibits a sharp upward trend, seemingly implying that misallocation increased dramatically from 1978 to 2013. However, we find that rising measurement error in U.S. plant-level data accounts for most of this trend, and that corrected allocative efficiency declined by considerably less.

What implications does this have for the research on wealth concentration or economic inequality?

Many policy choices involve trade-offs between social goals, such as reducing inequality and economic efficiency. For example, flexible labor laws may make it easier for firms to hire and fire workers but may not be desirable for workers seeking job security. Our methodology shows that the estimated efficiency gains from reallocation can be overstated due to measurement error and provides researchers a set of tools to estimate these more accurately.

What are the next steps in your agenda?

Future research should further decompose dispersion in average products into distortions which result in misallocation and can be addressed by policy, and other factors which don’t reflect true misallocation, such as measurement error or unavoidable adjustment costs or transportation costs.

Citation

This paper can be cited as follows: Bils, M., Klenow, P. J., and Ruane, C. (2021) "Misallocation or mismeasurement?" Journal of Monetary Economics, 124 (Supplement), pp. S39-S56.

About the authors