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Trang 3ESSAYS ON ‘TOTAL FACTOR PRODUCTIVITY AND HUMAN CAPITAL
BY
SHEKHAR ATYAR
M.A., UNIVERSITY OF TORONTO, 1997 B.A., OXFORD UNIVERSITY, 1994
B.A.(HONS.), ST STEPHEN’S COLLEGE (UNIVERSITY OF DELHI), 1992
A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
IN THE DEPARTMENT OF ECONOMICS AT BROWN UNIVERSITY, PROVIDENCE, RHODE ISLAND
Trang 4®
UMI
UMI Microform 3006682
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Bell & Howell Information and Learning Company 300 North Zeeb Road
Trang 6Department of Economics as satisfying the dissertation requirement for the degree of Doctor of Philosophy
Date 3 AY c©x2/⁄2.z
David N Weil, Director
Recommended to the Graduate School
Date se] DJ Ns
—
Oded Galor, Reader
na 0° (or _ ý/Z=—=zÊ^
Anthony Lancaster, Reader
Approved by the Graduate School
pate //27//0/ bs 7
Peter J Estrup
Dean of the Graduate School and Research
Trang 7Curriculum Vitae
Shekhar Aiyar
Department of Economics Date of Birth: May, 5, 1971 Brown University Place of Birth: New Delhi, India Providence, RI 02912
Ph: (401) 421-5938
e-mail: s.aiyar@yahoo.com
EDUCATION
Brown University, Providence, Rhode Island, USA
e Ph.D Program in Economics (Degree Expected May 2001)
e Areas of specialization: Macroeconomics, Economic Growth, Econometrics e Recipient of Teaching Fellowship and Ehrlich Fellowship
University of Toronto, Toronto, Canada
e MA in Economics (July 1997)
e Recipient of Simcoe Special Fellowship and International Fellowship St Edmund Hall, Oxford University, Oxford, UK
e BA in Philosophy and Economics (PPE) (May 1994)
e Recipient of Inlaks Scholarship and St Edmund Hall Open Exhibition e Received First Class Degree
St Stephen’s College, University of Delhi, Delhi, India
* B.A (Honors) in Economics (July 1992)
e Received First Division Degree
Trang 8Essays on Total Factor Productivity and Human Capital ACADEMIC PUBLICATIONS AND MANUSCRIPTS
e “A Contribution to the Empirics of Total Factor Productivity”, with James Feyrer, Manu- script, Brown University, September 2000
e “Convergence Across the Indian States: A Panel Study”, in Callen, T et al, eds., India at the Crossroads: Sustaining Growth and Reducing Poverty, IMF, Washington, D.C., February 2001
e “Total Factor Productivity Revisited: A Dual Approach to Levels-Accounting”, with Carl- Johan Dalgaard, Manuscript, Brown University, December 2000
e “Econometric Analysis of Dynamic Models: A Growth Theory Example”, with Tony Lan- caster, in Bunzel, H et al, eds., Panel Data and Structural Labour Market Models, North Holland,
Elsevier, 2000
e “The Human Capital Constraint: Of Increasing Returns, Education Choice, and Co- ordination Failure”, Manuscript, Brown University, August 2000 (Presented at the NEUDC Con- ference, Cornell University, October 2000)
e “Why Does Technology Sometimes Regress? A Model of Knowledge-Diffusion and Popula- tion Density”, with Carl-Johan Dalgaard, Manuscript, Brown University, April 2001
OTHER PUBLICATIONS
e “Who’s Afraid of Population Growth ?”, Op-Ed opinion piece, Times of India, September
2000
Trang 10e Instructor, Department of Economics, Brown University, 1999-2001 e Consultant, Oxus Investments and Research, New Delhi, Summer 2000 * Intern, International Monetary Fund, Washington, D.C., Summer 1999
Referee: Journal of Economic Growth, European Econamic Review, 1999- e Economics Don, Trinity College, University of Toronto, 1996-97
Trang 12A Ph.D thesis is both a labour of love and a miracle of compression First comes the labour of love; the endless stream of lectures, articles, internet-searches, conversa- tions and seminar presentations; the beer-soaked late-night dialogues reconciling venerable frameworks with what one fondly hopes are fresh insights Then comes the miracle of compression; the stripping away of the inessential, the concentration of four years of rela- tively free-ranging thought into a handful of short chapters that are expected to bear some linear relation to one another Often the latter exercise obliterates all traces of the former The complex influence of all the people without whom one’s dissertation would not have been started, sustained or completed is quite obscured behind the inscrutable theorems
and cursory literature reviews Luckily prefaces were invented to redress the balance - to
remember, to recount, and above all, to give thanks
I was extremely fortunate in my choice of advisors David Weil walked me through the maze of graduate economics with Socratic forbearance and an unerring ability to tell the escape route from the blind alley Oded Galor taught a course in growth theory so superb that it made my choice of specialization easy Tony Lancaster gave me the confidence to embark on independent research by co-authoring a paper with me in my second year, and by reminding me that Time’s Winged Charriot Hurries Near
Several professors at Brown University commented on the papers that I wrote Peter Howitt encouraged me greatly by always being available to discuss ideas old and new I received much guidance from John Driscoll, Pravin Krishna and Andrew Foster My second summer in graduate school was spent at the IMF, where Chris Towe and Patricia Reynolds, with unusual kindness, put me to work on an independent project connected with
Trang 14who taught me the practical value of triple-checking one’s data-set for inconsistencies before even thinking of running regressions
From my friends and colleagues in the department I learned more than any book has ever taught me Brown University enjoys considerable economies of scale in the large number of aspiring growth theorists that it produces; of these economies I was a grate- ful beneficiary Areendam Chanda, Kyung-Mook Lim, Len Erickson, Seiro Ite, Azam Chaudhry, Phil Garner and several others conspired to make lunch in the Blue Room a source of intellectual inspiration Jim Feyrer and Carl-Johan Dalgaard went a step further and wrote considerable bits of my dissertation for me
My thanks must also wing their way to my families, who have supported me through thick and thin, wherever in the world I have found myself and however limitless my time in school has seemed to grow Papa, Mum, Naiyya, Shahnaz, Gang: to you I owe far more than this Ph.D
Trang 16Contents 1 A Contribution to the Empirics of Total Factor Productivity 1.1 1.2 1.3 1.5 1.6 lntroducfion - ee ee ee ee
Literature Review .- 0.0202 ee eee ee ee ee ee es
1.2.1 Growth Empirics 2.2 2.2 eee ee ee TY
1.2.2 Technological Spillovers and Human Capital - - Calculating Total Factor Productivity 2 0.2 202. 0-2-0044 1.3.1 Methodology and Data .2 -22 0.202220 - +0200 2 1.3.2 Variance Decomposition .-.0 2.22.02 ee eee eee
The Model 2 2.2.02 02 0 0.20000 2 ce tee ee te te eee ee
16.1 Base Results 2.2.0 ee ee ee eee
Trang 181.7.1 FullSample - - 2.-0-.-2.-0.-2-2-2.-0-0-22 - 24 1.7.2 Mining Correction . -2.20 .0.-02 02-20-0200 + 00585 26 1.7.3 Human Capital Specification .-.- -2.-. 2 0500- 27 1.7.4 Disaggregated Human Capital .2.-.- - -2 - 28
1.8 Conclusion 2-2 2 ee ees 29
1.9 Appendix A:Data on the Share of Mining .- - -.-. 33 1.10 Appendix B: GMM Estimation .- -. .-2.-.-2 . 0 36
1.11 References 2 2 fe ee eee ee 38
The Human Capital Constraint: Of Increasing Returns, Education Choice
and Coordination Failure 42
2.1 Introduction 2.2 2 eee ee ee eee 42
2.1.1 Three Hypotheses anda Puzzle .- 20 00 .- 42 2.1.2 Outline and Literature Review .- -2 0 43 2.2 The Two-Sector Model 2 0-002 eee eee ee ee ee 48
2.2.1 Production 2 2 eee ee ee ee ee 48
2.2.2 Individuals and Education Choice . - 50
2.2.3 Equilibrium .-0.-.-.-.22.02-2-2022.204-.-220-00-8 52
2.2.4 Minimum Scale and Co-ordination Falure - 55
2.3 The Three Sector Model .-. . - 2.200 2-000 2 ee eee 57
2.3.1 Production 2 eee ee ee ee ee 57
Trang 202.3.4 Equilibrium With Three Sectors .- - 2 -2.2.005 60
2.3.5 Discussion .- 2 2 ee ee ee ee eee 62
2.3.6 Equilibrium With Two Sectors -.- - 63
2.3.7 Co-ordination and Subsidies .-2 2. 2-22.0 64
2.4 Conclusion 2 ee ee ee 69
2.6 References 2 -.-.- 0-20.20 0-20.22 ee eee te te eee 72 Total Factor Productivity Revisited: A Dual Approach to Levels Ac-
counting 75
3-l Introduction 2 ee ee te te ee 75
P “hAMN\ aaiNlNNiiiắaiiẳẮẢ 79
33 Data ee ee ee 81
3.4 Results: Primal vs Dual - - ee ee ee eee 84
3.5 Income Shares and The Cobb-Douglas Hypothesis 87 3.6 Total vs Multi-Factor Productivity .2 0 200 20202086 91 3.7 Concluding Remarks 2 2.20.02 0202.2 ee eee ee es 95
3.8 References 0 ee ee ee ee ee 105
The Econometric Analysis of Dynamic Panel Models: A Growth Theory
Example 109
4.1 Introduction 2 ee ee 109
Trang 22Results 2 2 ee ee et ee 117
Concluding Remarks 0-2 0 ee eee ee eee ee ee ee 120
Trang 24List of Tables
1.1 The Evolution of TFP for a Selection of Countries . 2 10 1.2 Variance Decomposition of Log Incomes by Year - - 12 1.3 Regression Results - non-OECD countries 2 ee ee ee 19 1.4 Variance Decomposition of Steady State Productivity 24 1.5 esults Íor the Full SampÌl - Q ee ee ee ee 25 1.6 Results With and Without Adjusting for Natural Resource-Extraction 26 1.7 Results With an alternative human capital specification .- 27
18 Results With Disaggregated Schoolng - ‹ Q kh Ra 28
3.1 Primal Vs Dual TFP Q ee ee ee ee 97
Š.2 TP VsMEP Q Q Q Q Q Q Q Q TK Ty UY Kia 98
3.3 Factor Shares and Factor Returns .- -.-22.0-2-2-2-.2.- 99
Trang 26List of Figures 11 1.2 1.3 3.1 3.2 3.3 3.4 3.5 4.1 4.2 43 4.4 4.5 4.6
The Effect of Shocks to Human Capital on Productivity Growth Rates 31 The Effect of Shocks to Human Capital on Productivity Levels .- 32 The Effect of Shocks to Human Capital on Output .0 - 33
Primal Vs Dual TFP 2 2.2 ee ee ee ee ee ee ee eee 101 Calibrated Vs Cobb-Douglas (Primal) 102 National Accounts Vs Cobb-Douglas (Pnmal) 103
Trang 28A Contribution to the Empirics of Total Factor Productivity With James Feyrer
1.1 Introduction
Over the last decade the literature has seen a lively debate as to whether it is differences in factor accumulation or in total factor productivity (TFP) that are mainly responsible for the observed variation in per capita incomes across countries This paper argues that the dichotomy is spurious, resting on a conflation of the proximate determinants of income variation with the ultimate determinants of the same
Two important recent contributions to the debate are Klenow and Rodriguez-Clare
(1997) and Hall and Jones (1999) They utilize microeconomic evidence on the private
Trang 30varia-This paper takes a different view about the linkages between factor accumulation and productivity We suggest that the key to understanding productivity growth in most countries is through technology spillovers from the handful of countries that perform R&D These spillovers are contingent on a domestic stock of human capital sufficient to take advantage of products and techniques developed elsewhere The spillovers are dynamic, so that increases in human capital intensity today will have an impact on productivity in all subsequent periods, not just the current one
Our model is based on three assumptions about spillovers First, for most countries the technological frontier is expanding exogenously Second, the ability of a country to take advantage of technological spillovers is a function of its stock of human capital In the long run, countries with more educated work forces will be closer to the technological frontier Third, movement to the balanced growth path of productivity is not immediate To use the language of the traditional empirical growth literature, our model is one of conditional convergence in productivity, where the long run level of productivity is determined by the
level of human capital
We find that human capital has a significant and positive effect on the long run pro- ductivity level.? This effect is not immediate; convergence toward the long run level is at a rate of about 3% per year Increases in human capital stocks will therefore significantly
‘In theory, panel growth studies should be capable of identifying these externalities if they exist In work by Knight, Loyaza and Villanueva (1993), Islam (1995) and Caselli, Esquivel and Lefort (1996), the coefficients on physical and human capital correspond to the social returns to factor accumulation These
coefficients they find are typically lower than the private returns utilized in the accounting work In fact,
these studies fail to find a positive and significant coefficient on human capital at all This seems to indicate
that simple externalities are not a problem for the accounting framework
Trang 32This result has significant consequences for the factor accumulation versus productivity debate While the proximate cause of differences between countries appears to be produc- tivity, we find that the ultimate cause of productivity differences may be different levels of human capital In fact, we find that human capital levels can account for the vast majority of the long run differences in productivity levels
1.2 Literature Review
1.2.1 Growth Empirics
Mankiw, Romer and Weil (1992}{MRW) purported to show that the Solow model, when augmented to include human capital as a factor of production, did a reasonable job of explaining the variations in per capita real income that are observed across a large and heterogeneous sample of countries They found that factor accumulation could account
for a majority of differences in income per capita under the assumption that all countries
shared a common level of productivity
Trang 34These panel results suggest that an analysis of why countries differ so much in their technologies and of how differences in technology between countries have evolved is es- sential Unfortunately, panel studies of the kind carried out by Islam and CEL cannot, by their nature, show the evolution of differences in technology, since only a single fixed effect is recovered for each country Although they allow for differences in productivity across nations, they are forced to assume that each country’s relative productivity remains entirely unchanged over the sample period
With the increased focus on productivity, several recent papers have concentrated on calculating TFP for a large sample of countries at a single point in time.? TFP is calculated as a (Solow) residual from real income per capita, after accounting for the contribution
of various factors of production Klenow and Rodriguez-Clare (1997) calculate TFP for a
sample of countries after accounting for the contributions made by labor, physical capital and human capital They then decompose the variance of per capita income into that attributable to differences in factors of production and that attributable to differences in TFP Using a number of formulations they conclude that, in general, differences in TFP play a greater role.*
3TFP is more or less synonymous with technology broadly defined, since both are a measure of the efficiency with which a country combines its factors of production to obtain goods and services The terms are used interchangeably in this paper
*Klenow and Rodriguez-Clare (1997) find that productivity differences may account for 67% of differences
in income per worker, compared to only 22% for MRW Their results are corroborated by Hall and Jones
(1999), who find, again, that the lion’s share of the variation in incomes across the world is explained by
Trang 36This paper argues that differences in TFP indeed play a central role in the growth process, and that it is therefore both interesting and important to analyze how differences in TFP between countries have evolved over time There are several theoretical models in the literature concerning technological growth Grossman and Helman (1991) and Aghion and Howitt (1992) describe economies in which purposive research and development is the engine that drives technical progress
However, empirical evidence suggests that most research and development is concen- trated in a handful of rich countries, so that these models are of limited relevance in describing the evolution of TFP in the vast majority of nations It seems more promis- ing to consider models that emphasize the ability of “follower” countries to imitate the innovations carried out in “leader” countries Various factors may be thought to influence the efficacy with which such imitation may be carried out, such as the degree to which a country is open to dealings with the rest of the world (because an open country is able to take advantage of imports from countries that do perform R&D, and also to foreign direct investment from firms at the world technological frontier), and the social, legal and geo- graphical features peculiar to that country Another crucial factor in determining the ease of imitation, which this paper concentrates on, is the stock of human capital per worker in a given country
Trang 38technologies comes from Foster and Rosenzweig (1995), Wozniak (1984) and Bartel (1987)
More recently several empirical papers, such as Benhabib and Speigel (1994), have argued that the relationship between human capital and income growth is best viewed in the
context of the positive effect that human capital has on TFP, rather than its direct effect
as an accumulable factor in the production function
Bils and Klenow (2000) argue that microeconomic evidence on returns to schooling
is inconsistent with the large and positive coefficients on human capital found in growth regressions by Barro (1991); this, too, suggests that human capital impacts income through the separate channel of TFP Borensztein et al (1998) regress GDP growth rates on both
foreign direct investment (FDI) and a term that interacts FDI with human capital They find that while the coefficient on FDI by itself is negative, the coefficient on the interactive
term is positive and significant, suggesting that human capital is essential to the process
of technological diffusion through FDI
Our paper aims to contribute to the empirics of TFP by calculating Solow residuals for a large panel of countries over a thirty year period, and then examining the evolution of these residuals Particular attention will be paid to the issue of whether TFP is converging, and whether human capital stocks affect the steady state TFP level toward which each country
is converging Our working hypothesis is that the rate of growth of a country’s TFP is
a positive function of the gap between its actual TFP level at a point in time, and its potential (or steady-state) TF'P level
Trang 40frontier, and a country specific fixed effect From this hypothesis we derive an empirical specification that consists of a fixed-effects dynamic panel regression, which we proceed to
estimate using our panel of TFP figures To preview our results, we find that countries
converge to their individual steady states at about 3% per year Human capital stocks have a positive and significant effect on each country’s steady state TFP level We further find that a large share of the variation in steady state TFP across countries is attributable
to variation in human capital stocks
The next section of our paper describes the methodology we use to obtain our panel of TFP figures, the sources that we use in our calculations, and some of the patterns in the
data that become evident Section 3 lays out the theoretical framework from which our
empirical specification is derived Section 4 describes and briefly reviews the econometric techniques that we employ Section 5 contains our main empirical results Section 6 presents some additional results The subsequent section concludes
1.3 Calculating Total Factor Productivity
1.3.1 Methodology and Data
Our methodology for calculating TFP follows recent work by Klenow and Rodriguez-Clare (1997)(KRC) and Hall and Jones (1999) (HJ) We assume that the aggregate production function takes a simple Cobb-Douglas form and then calculate TFP as a Solow residual
Y;= KƑ(AH) 1e (1-1)