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Journal Article•DOI•

Why do Some Countries Produce So Much More Output Per Worker than Others

Robert E. Hall1, Charles I. Jones1•
National Bureau of Economic Research1
01 Feb 1999-Quarterly Journal of Economics (Oxford University Press)-Vol. 114, Iss: 1, pp 83-116
TL;DR: This article showed that the differences in capital accumulation, productivity, and therefore output per worker are driven by differences in institutions and government policies, which are referred to as social infrastructure and called social infrastructure as endogenous, determined historically by location and other factors captured by language.
Abstract: Output per worker varies enormously across countries. Why? On an accounting basis our analysis shows that differences in physical capital and educational attainment can only partially explain the variation in output per worker—we find a large amount of variation in the level of the Solow residual across countries. At a deeper level, we document that the differences in capital accumulation, productivity, and therefore output per worker are driven by differences in institutions and government policies, which we call social infrastructure. We treat social infrastructure as endogenous, determined historically by location and other factors captured in part by language. In 1988 output per worker in the United States was more than 35 times higher than output per worker in Niger. In just over ten days the average worker in the United States produced as much as an average worker in Niger produced in an entire year. Explaining such vast differences in economic performance is one of the fundamental challenges of economics. Analysis based on an aggregate production function provides some insight into these differences, an approach taken by Mankiw, Romer, and Weil [1992] and Dougherty and Jorgenson [1996], among others. Differences among countries can be attributed to differences in human capital, physical capital, and productivity. Building on their analysis, our results suggest that differences in each element of the production function are important. In particular, however, our results emphasize the key role played by productivity. For example, consider the 35-fold difference in output per worker between the United States and Niger. Different capital intensities in the two countries contributed a factor of 1.5 to the income differences, while different levels of educational attainment contributed a factor of 3.1. The remaining difference—a factor of 7.7—remains as the productivity residual. * A previous version of this paper was circulated under the title ‘‘The Productivity of Nations.’’ This research was supported by the Center for Economic Policy Research at Stanford and by the National Science Foundation under grants SBR-9410039 (Hall) and SBR-9510916 (Jones) and is part of the National Bureau of Economic Research’s program on Economic Fluctuations and Growth. We thank Bobby Sinclair for excellent research assistance and colleagues too numerous to list for an outpouring of helpful commentary. Data used in the paper are available online from http://www.stanford.edu/,chadj.

Summary (3 min read)

Jump to: [1 Introduction] – [2 Levels Accounting] – [2.1 Productivity Calculations by Country] – [3 Determinants of Economic Performance] – [4.1 Measurement] – [4.2 Identification] – [4.3 Instruments] – [5 Basic Results] – [5.1 Reduced-Form Results] – [5.2 Results by Component] – [6 Robustness of the Results] and [7 Conclusion]

1 Introduction

  • In 1988, output per worker in the United States was more than 35 times higher than output per worker in Niger.
  • In particular, however, their results emphasize the key role played by productivity.
  • Expropriation, confiscatory taxation, and corruption are examples of public diversion.
  • These studies emphasize that differences in growth rates are transitory: countries grow more rapidly the further they are below their steady state.
  • The authors can summarize their analysis of the determinants of differences in economic performance among countries as: Output per Worker ←− (Inputs, Productivity) ←− Social Infrastructure.

2 Levels Accounting

  • The authors analysis begins by examining the proximate causes of economic success.
  • The authors present results based on the simplest Cobb-Douglas approach.
  • To measure productivity and decompose differences in output per worker into differences in capital intensity, human capital per worker, and productivity, the authors use data on output, labor input, average educational attainment, and physical capital for the year 1988.
  • Because of inadequate data, their correction is quite coarse: the authors subtract value added in the mining industry (which includes oil and gas) from GDP in computing their measure of output.
  • 5We limit their sample to countries with investment data going back at least to 1970 and use all available investment data.the authors.the authors.

2.1 Productivity Calculations by Country

  • Figure 1 shows productivity levels across countries plotted against output per worker.
  • To take maximum advantage of those low rates and to avoid higher U.S. rates, highest levels of productivity are Italy, France, Hong Kong, Spain, and Luxembourg.
  • The production function is not restricted to Cobb-Douglas and factor shares are allowed to differ across countries.
  • The authors productivity differences are larger in part because of their more standard treatment of human capital and in part because the authors do not impose orthogonality between productivity and the other factors of production.

3 Determinants of Economic Performance

  • At an accounting level, differences in output per worker are due to differences in physical and human capital per worker and to differences in productivity.
  • By social infrastructure, the authors mean the institutions and government policies that provide the incentives for individuals and firms in an economy.
  • There may be more than one equilibrium—for example, there may be a poor equilibrium where production pays little because diversion is so common, and diversion has a high payoff because enforcement is ineffective when diversion is common.
  • Potentially productive individuals spend their efforts influencing the government.

4.1 Measurement

  • The ideal measure of social infrastructure would quantify the wedge between the private return to productive activities and the social return to such activities.
  • Three categories relate to the government’s possible role as a diverter: (i) corruption, (ii) risk of expropriation, and (iii) government repudiation of contracts.
  • In addition, policies favoring free trade yield benefits associated with the trade itself.
  • Sachs and Warner (1995) have compiled an index that focuses on the openness of a country to trade with other countries.
  • In most of the results that the authors present, they will impose (after testing) the restriction that the coefficients for these two proxies for social infrastructure are the same.

4.2 Identification

  • Several features of this framework deserve comment.
  • Poor countries may have limited ability to collect taxes and may therefore be forced to interfere with international trade.
  • Alternatively, one might be concerned that the experts at Political Risk Services who constructed the components of the GADP index were swayed in part by knowledge of income levels.
  • The heart of their identifying assumptions is the restriction that the determinants of social infrastructure affect output per worker only through social infrastructure and not directly.
  • Therefore, both measurement error and endogeneity concerns are addressed.

4.3 Instruments

  • The authors choice of instruments considers several centuries of world history.
  • The authors instruments are positively correlated with social infrastructure.
  • Second, it appears that Western Europeans were more likely to settle in areas that were broadly similar in climate to Western Europe, which again points to regions far from the equator.
  • 16The latitude of each country was obtained from the Global Demography Project at U.C. Santa Barbara (http://www.ciesin.org/datasets/gpw/globldem.doc.html), discussed by Tobler, Deichmann, Gottsegen and Maloy (1995).

5 Basic Results

  • Figure 2 plots output per worker against their measured index of social infrastructure.
  • Then, (i) For each country i not in C, let W be the independent variables with data and V be the variables that are missing data.
  • The standard errors reported in the table are calculated as the standard deviation of the 10,000 observations of β̄.
  • Under the assumption that there is no true simultaneity problem, that is, is uncorrelated with S̃, the authors can calculate the standard deviation of true social infrastructure, σS , from the difference between the IV and OLS estimates.
  • RS̃,S = .707 suggests that differences in social infrastructure can account for a 25.2-fold difference in output per worker across countries.

5.1 Reduced-Form Results

  • Table 3 reports the two reduced-form regressions corresponding to their main econometric specification.
  • These are OLS regressions of log output per worker and social infrastructure on the four main instruments.
  • Interpreting these regressions calls for care: their framework does not require that these reduced forms be complete in the sense that all exogenous variables are included.
  • Rather, the equations are useful but potentially incomplete reduced-form equations.
  • Distance from the equator, the Frankel-Romer predicted trade share, and the fraction of the population speaking a European language (including English) combine to explain a substantial fraction of the variance of their index of social infrastructure.

5.2 Results by Component

  • Table 4 examines in more detail the sources of differences in output per worker across countries by considering why some countries have higher productivity or more physical or human capital than others.
  • While the U.S. ranks first in output per worker, second in educational attainment, and 13th in productivity, its capital-output ratio ranks 39th among the 127 countries.
  • The first row of the table documents the observed factor of variation between the maximum and minimum values of output per worker, capital intensity, and other variables in their data set.
  • 21 Interpreted through an aggregate production function, these differences are able to account for much of the variation in output per worker.

6 Robustness of the Results

  • The central equation estimated in this paper has only a single fundamental determinant of a country’s output per worker, social infrastructure.
  • The result, consistent with previous overidentifying tests, is little change in the coefficient on social infrastructure and a small and insignificant coefficient on distance from the equator.
  • Specifically, these variables measure the fraction (on a [0,1] scale) of a country’s population affiliated with the Catholic, Muslim, Protestant, and Hindu religions.
  • This specification adds an indicator variable taking the value of 1 for countries that are categorized as capitalist or mixed-capitalist by the Freedom House (1994).
  • The odd result is that the regression coefficient implies that capitalist countries produce substantially less output per worker than otherwise similar noncapitalist countries.

7 Conclusion

  • Countries produce high levels of output per worker in the long run because they achieve high rates of investment in physical capital and human capital and because they use these inputs with a high level of productivity.
  • The authors empirical analysis suggests that success on each of these fronts is driven by social infrastructure.
  • A country’s long-run economic performance is determined primarily by the institutions and government policies that make up the economic environment within which individuals and firms make investments, create and transfer ideas, and produce goods and services.
  • The authors major findings can be summarized by the following points: 1. Many of the predictions of growth theory can be successfully consid- ered in a cross-section context by examining the levels of income across countries.
  • Differences in social infrastructure across countries cause large differ- ences in capital accumulation, educational attainment, and productivity, and therefore large differences in income across countries.

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Content maybe subject to copyright    Report

Output per Worker Across Countries 1
1 Introduction
In 1988, output per worker in the United States was more than 35 times
higher than output per worker in Niger. In just over ten days, the average
worker in the United States produced as much as an average worker in Niger
produced in an entire year. Explaining such vast differences in economic
performance is one of the fundamental challenges of economics.
Analysis based on an aggregate production function provides some in-
sight into these differences, an approach taken by Mankiw, Romer and Weil
(1992) and Dougherty and Jorgenson (1996), among others. Differences
among countries can be attributed to differences in human capital, physical
capital, and productivity. Building on their analysis, our results suggest
that differences in each element of the production function are important.
In particular, however, our results emphasize the key role played by pro-
ductivity. For example, consider the 35-fold difference in output per worker
between the United States and Niger. Different capital intensities in the two
countries contributed a factor of 1.5 to the income differences, while different
levels of educational attainment contributed a factor of 3.1. The remaining
difference — a factor of 7.7 — remains as the productivity residual.
The breakdown suggested by the aggregate production function is just
the first step in understanding differences in output per worker. Findings
in the production function framework raise deeper questions such as: Why
do some countries invest more than others in physical and human capital?
And why are some countries so much more productive than others? These
are the questions that this paper tackles. When aggregated through the
production function, the answers to these questions add up to explain the
differences in output per worker across countries.
Our hypothesis is that differences in capital accumulation, productivity,
and therefore output per worker are fundamentally related to differences
in social infrastructure across countries. By social infrastructure, we mean
Output per Worker Across Countries 2
the institutions and government policies that determine the economic envi-
ronment within which individuals accumulate skills, and firms accumulate
capital and produce output. A social infrastructure favorable to high lev-
els of output per worker provides an environment that supports productive
activities and encourages capital accumulation, skill acquisition, invention,
and technology transfer. Such a social infrastructure gets the prices right so
that, in the language of North and Thomas (1973), individuals capture the
social returns to their actions as private returns.
Social institutions to protect the output of individual productive units
from diversion are an essential component of a social infrastructure favor-
able to high levels of output per worker. Thievery, squatting, and Mafia
protection are examples of diversion undertaken by private agents. Para-
doxically, while the government is potentially the most efficient provider of
social infrastructure that protects against diversion, it is also in practice a
primary agent of diversion throughout the world. Expropriation, confisca-
tory taxation, and corruption are examples of public diversion. Regulations
and laws may protect against diversion, but they all too often constitute the
chief vehicle of diversion in an economy.
Across 127 countries, we find a powerful and close association be-
tween output per worker and measures of social infrastructure. Countries
with long-standing policies favorable to productive activities—rather than
diversion—produce much more output per worker. For example, our anal-
ysis suggests that the observed difference in social infrastructure between
Niger and the United States is more than enough to explain the 35-fold
difference in output per worker.
Our research is related to many earlier contributions. The large body
of theoretical and qualitative analysis of property rights, corruption, and
economic success will be discussed in Section 3. The recent empirical growth
literature associated with Barro (1991) and others shares some common
Output per Worker Across Countries 3
elements with our work, but our empirical framework differs fundamentally
in its focus on levels instead of rates of growth. This focus is important for
several reasons.
First, levels capture the differences in long-run economic performance
that are most directly relevant to welfare as measured by the consumption
of goods and services.
Second, several recent contributions to the growth literature point to-
ward a focus on levels instead of growth rates. Easterly, Kremer, Pritch-
ett and Summers (1993) document the relatively low correlation of growth
rates across decades, which suggests that differences in growth rates across
countries may be mostly transitory. Jones (1995) questions the empirical
relevance of endogenous growth and presents a model in which different
government policies are associated with differences in levels, not growth
rates. Finally, a number of recent models of idea flows across countries such
as Parente and Prescott (1994), Barro and Sala-i-Martin (1995) and Eaton
and Kortum (1995) imply that all countries will grow at a common rate in
the long run: technology transfer keeps countries from drifting indefinitely
far from each other. In these models, long-run differences in levels are the
interesting differences to explain.
Some of the cross-country growth literature recognizes this point. In par-
ticular, the growth regressions in Mankiw et al. (1992) and Barro and Sala-
i-Martin (1992) are explicitly motivated by a neoclassical growth model in
which long-run growth rates are the same across countries or regions. These
studies emphasize that differences in growth rates are transitory: countries
grow more rapidly the further they are below their steady state. Never-
theless, the focus of such growth regressions is to explain the transitory
differences in growth rates across countries.
1
Our approach is different—we
1
The trend in the growth literature has been to use more and more of the short-run
variation in the data. For example, several recent studies use panel data at 5 or 10-year
intervals and include country fixed effects. The variables we focus on change so slowly
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Frequently Asked Questions (12)
Q1. What is the main form of diversion in countries of all types?

Diversion takes the form of rent seeking in countries of all types, and is probably the main form of diversion in more advanced economies (Krueger 1974). 

A standard result in the econometrics of measurement error isthat OLS is biased toward zero by a multiplicative factor equal to the ratio of the variance of the true value of the right-hand variable to the variance of the measured value. 

In cross-country growth regressions that include the initial level of income and emphasize the transition dynamics interpretation, one can map the growth regression coefficients into effects on the long-run level of income. 

Because the authors believe that social infrastructure is measured with error, the authors need to investigate the magnitude of the errors in order to understand this number. 

Given the relatively small variation in inputs across countries and the small elasticities implied by neoclassical assumptions, it is hard to escape the conclusion that differences in productivity — the residual — play a key role in generating the wide variation in output per worker across countries. 

Their data set includes 127 countries for which the authors were able to construct measures of the physical capital stock using the Summers and Heston data set. 

For the developing countries in the table, differences in productivity are the most important factor in explaining differences in output per worker. 

Regulations and laws may protect against diversion, but they all too often constitute the chief vehicle of diversion in an economy. 

The extent to which different countries have adopted different socialinfrastructures is partially related to the extent to which they have been influenced by Western Europe. 

3. Differences in social infrastructure across countries cause large differ-ences in capital accumulation, educational attainment, and productivity, and therefore large differences in income across countries. 

While the simple association of this variable with output per worker is quite strong, the partial regression coefficient is small in magnitude (the variable is measured on a [0,1] scale) and statistically insignificant. 

The associated p-value testing the hypothesis of a zero coefficient on social infrastructure (computed from the bootstrap distribution of coefficients) is only 0.008.