Martin Nybom
Jan Stuhler
Mattia Fochesato
Sam Bowles
Linda Wu
Tzu-Ting Yang
Thomas Piketty
Malka Guillot
Jonathan Goupille-Lebret
Bertrand Garbinti
Antoine Bozio
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
Jeffrey T. Denning
Sandra Black
Wei Cui
Mathieu Leduc
Philippe Jehiel
Shivam Gujral
Suraj Sridhar
Attila Lindner
Arindrajit Dube
Pascual Restrepo
Łukasz Rachel
Benjamin Moll
Kirill Borusyak
Michael McMahon
Frederic Malherbe
Gabor Pinter
Angus Foulis
Saleem Bahaj
Stone Centre at UCL
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James Baggaley
Xavier Jaravel
Richard Blundell
Parama Chaudhury
Dani Rodrik
Alan Olivi
Vincent Sterk
Davide Melcangi
Enrico Miglino
Fabian Kosse
Daniel Wilhelm
Azeem M. Shaikh
Joseph Romano
Magne Mogstad
Suresh Naidu
Ilyana Kuziemko
Daniel Herbst
Henry Farber
Lisa Windsteiger
Ruben Durante
Mathias Dolls
Cevat Giray Aksoy
Angel Sánchez
Penélope Hernández
Antonio Cabrales
Wendy Carlin
Suphanit Piyapromdee
Garud Iyengar
Willemien Kets
Rajiv Sethi
Ralph Luetticke
Benjamin Born
Amy Bogaard
Mattia Fochesato
Samuel Bowles
Guanyi Wang
CORE Econ
David Cai
Toru Kitagawa
Michela Tincani
Christian Bayer
Arun Advani
Elliott Ash
Imran Rasul

Firm-embedded productivity and cross-country income differences

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

Productivity is a crucial determinant of global income inequality, explaining about half of the variation in income per capita between countries. Our research introduces a novel framework to measure disparities arising from firm-embedded factors like blueprints, management practices, patents, and intangible capital, disentangle them from factors available to all firms in the economy, such as, natural amenities, institutions, infrastructure, and workers’ quality. Understanding these differences is vital for effective policy-making. Bridging the gap in firm-embedded productivity will prompt adoption of various policies, from research and development tax incentives to startup incubator programs, fostering productivity and narrowing income disparities.

How did you answer this question?

We analyse micro-level data on multinational enterprises, (MNEs), worldwide to measure the contribution of firm-embedded productivity on cross-country income disparities. Despite MNEs being able to transfer productivity globally, they encounter diverse competitors in each country of operation. Differences in market shares of the same MNE across nations spotlight differences in aggregate firm-embedded productivity. Our results show that MNEs hold market shares roughly four times larger in developing countries than in high-income ones, indicating a scarcity of firm-embedded productivity and diminished competition in the former. Remaining disparities in income per capita are attributed to country-embedded factors.

What did you find?

We show that there is a strong positive correlation between firm-embedded productivity and output per-worker and that differences in firm-embedded productivity account for about one-third of the cross-country variance in output per-worker. The relative importance of the differences in firm-embedded productivity varies considerably across countries. For example, firm-embedded productivity in Italy is 0.28 log-points higher than in Greece, accounting for three quarters of the observed differences in output per-worker between these two countries. In contrast, firm-embedded productivity is similar for Greece and Bulgaria, though output per-worker in Greece is 0.5 log points higher due to the difference in country-embedded factors between these two countries.

Developing accounting: firm-embedded productivity vs country-embedded factors

Note: Each circle (square) represents a country’s firm-embedded productivity (country-embedded factors) relative to France. The figure plots the decomposition in Equation (15), where Δyn is plotted in the x-axis and Δznand Δɸn  are plotted in the y-axis. The legend reports the slopes of a bivariate OLS regression of Δɸn (Δzn) on Δyn.

What implications does this have for the study (research and teaching) of wealth concentration or economic inequality?

These results underscore a key policy implication: reducing the gap in firm-embedded productivity between countries can markedly diminish cross-country income disparities. Understanding both firm-embedded and country-embedded factors is crucial for tackling global income inequalities. Policymakers can leverage this insight to craft strategies promoting firm-level productivity, fostering economic advancement and equitable development. Additionally, this research offers valuable educational content for courses in development economics, macroeconomics, and international economics, enriching students' understanding of productivity and economic inequality.

What are the next steps in your agenda?

Expanding our analysis to more developing countries is important. Our new procedure can be easily applied to more countries as new affiliate-parent matched data become available. Also, linking this data to firm-level measures of physical productivity would allow our procedure to be applied under more general assumptions. Finally, we aim to explore the impact of firm-embedded factors on cross-country economic growth differentials.

Citation

Alviarez, V., Cravino, J., & Ramondo, N.(2023). Firm-Embedded Productivity and Cross-Country Income Differences. Journal of Political Economy (Vol. 131, Issue 9, pp. 2289–2327). University of Chicago Press.

About the authors