Macroeconomics II (Growth)
The Macroeconomic Facts
It is, of course, helpful, to know what are the main facts to be explained. We begin by briefly surveying some of the main features of the macro-economic data that we would like to explain.
Required reading
Parente, Stephen, and Ed Prescott (1993): "Changes in the wealth of nations." Federal Reserve Bank of Minneapolis Quarterly Review, Spring.
Pritchett, Lant (1997): "Divergence, big time." Journal of Economic Perspectives, 11(3):3-17.
Easterly, William, and Ross Levine (2001): "It's not factor accumulation: stylized facts and growth models." World Bank Economic Review, 15:177-219.
Klenow, Pete (2001): "Comment on 'It's Not Factor Accumulation: Stylized Facts and Growth Models.'" World Bank Economic Review, 15:221-224.
Online sources
Heston and Summers: Penn World Tables, Mark 5.6 (dataset).
You should also familiarize yourself with Jonathan Temple's comprehensive page on Economics Growth Resources.
Supplementary Reading
Abramowitz, Moses (1986): "Catching Up, Forging Ahead, and Falling Behind." Journal of Economic History, 46:385-406.
Barro, Robert J. (1992): "Economic Growth in a Cross-Section of Countries." Quarterly Journal of Economics,106:407-443.
Baumol, William J. (1986): "Productivity growth, convergence, and welfare: what the long-run data show." American Economic Review, 76(5):1072-1085.
Baumol, William J., Edward N. Wolff (1988): "Productivity growth, convergence, and welfare: reply." American Economic Review, 78:1155-1159.
Ben-David, Dan (1993): "Equalizing exchange: trade liberalization and convergence." Quarterly Journal of Economics, 108(3):653-79.
De Long, Bradford (1988): "Productivity growth, convergence and welfare: comment." American Economic Review, 78:1138-1154.
Dowrick, Steve and Duc-Tho Nguyen (1989): "OECD Comparative Economic Growth 1950-85: Catch-up and Convergence." American Economic Review, 79:1010-1030.
Kormendi, Roger C., and Phillip G. Meguire (1985): "Macroeconomic Determinants of Economic Growth: Cross-Country Evidence." Journal of Monetary Economics, 16:141-163.
Maddison, Angus (1994): "Explaining the economic performance of nations 1820-1989." In W.J. Baumol et al. (eds.), Convergence and Productivity. Oxford: Oxford University Press, pp. 20-61.
Maddison, Angus (1995): Monitoring the World Economy, 1820-1992. Paris: OECD.
Perotti, Roberto (1996): "Growth, Income Distribution and Democracy: What the Data Say." Journal of Economic Growth, 1(2):149-188.
Model Uncertainty
Having just talked about the facts of aggregate growth, we must acknowledge that many of these facts may turn out to be fiction. We look at two papers, one pessimistic and one optimistic, about the prospects for finding out what actually determines growth. The pessimistic paper, Levine and Renelt (1992), adopts Ed Leamer's bounds analysis to argue that few if any of the significant partial correlations found in the literature are robust to model specification. They do, however, identify a positive, robust correlation between growth and the share of investment in GDP, and between the investment share and the ratio of international trade to GDP. Sala-i-Martin's paper is more optimistic and argues that, by taking a less extreme position about what constitutes a robust result, one can identify some variables that appear to have a robust influence on economic growth. Specifically, Sala-i-Martin studies the whole distribution of parameter estimates that are obtained as a result of varying the model specification, rather than just the upper and lower extremes studied by Levine and Renelt. He finds that a "substantial number of variables can be found to be strongly related to growth."
A number of the papers in the section on further reading expand on Sala-i-Martin's approach; they add some intellectual justification for the exercise undertaken in "I just ran two million regressions."
Required reading
Levine, Ross and David Renelt (1992): "A sensitivity analysis of cross-country growth regressions." American Economic Review, 82(4):942-963.
Sala-i-Martin, Xavier (1997): "I just ran two million regressions." American Economic Review, 87(2):178-183.
Durlauf, Steven N. (2001): "Manifesto for a growth econometrics." Journal of Econometrics, 100(1):65-69.
Supplementary Reading
Fernandez, C., Ley, Eduardo and Steel, Mark F. J. (2001): Model uncertainty in cross-country growth regressions. Journal of Applied Econometrics, 16(5):563-576.
Hoeting, Jennifer A., et al. (1999): "Bayesian model averaging: a tutorial." Statistical Science, 14(4):382-417
Hoover, Kevin D. and Perez, Stephen J. (2004): "Truth and robustness in cross-country growth regressions." Oxford Bulletin of Economics and Statistics, forthcoming.
Sala-i-Martin, Xavier, Doppelhofer, Gernot and Miller, Ronald (2004): "Determinants of long-run growth: a Bayesian averaging of classical estimates (BACE) approach." American Economic Review, 94(4):813-835. Link to NBER working paper version.
Temple, Jonathan (2000): "Growth regressions and what the textbooks don't tell you." Bulletin of Economic Research, 52(3):181-205.
Solow (1956)
Solow's purpose was to show the consequences of technical change for economic growth. It was convenient for him to take no particular positions on the nature of technology or on the source of technical change. The purpose of reviewing the model is therefore didactic rather than critical: by seeing how the omissions of the model limit our understanding of technical change, we can more readily see what sort of models we might need. The paper by Chad Jones is a helpful exposition of a well-known way to solve the Solow model explicitly when the production function is Cobb-Douglas.
Solow (1956) became sidelined by the new growth literature beginning in the 1980s. However, the early 1990s saw a brief attempt at a resurrection. The key reference is a cross-sectional study of post-war income levels and growth rates by Mankiw, Romer and Weil (1992), who open their paper with the lovely phrase: "This paper takes Robert Solow seriously." (So should we all, although it is an open question whether we should take Solow [1956] or Solow [1960] seriously. I once opened a paper with "This paper takes Paul Romer seriously." My coauthor deleted the line before publication. Read into that what you will.)
Mankiw Romer and Weil's strong support of Solow (1956) has attracted much criticism. In particular, Klenow and Rodriguez-Clare (1997) and Dinopoulos and Thompson (1999) have found fault with the measures of human capital employed, while Temple has found that the parameter estimates on which Mankiw et al.'s support rests are not at all robust to measurement error. At the heart of criticism is the question of whether it is reasonable to assume the state of technical knowledge is identical all over the world. If one does not make that assumption, cross-sectional regressions are biased. One way to overcome this is by panel techniques, but these have turned out to generate much less reliable parameter estimates.
Required reading
Solow, Robert M. (1956): "A Contribution to the Theory of Economic Growth." Quarterly Journal of Economics, 70:65-94.
Lucas, Robert E. (1990): "Why Doesn't Capital Flow from Rich to Poor Countries?" American Economic Review, Papers and Proceedings, 80(2): 92-96.
Mankiw, N. Gregory, David Romer and David N. Weil (1992): "A Contribution to the Empirics of Economic Growth." Quarterly Journal of Economics, 107(2):407-437.
Dinopoulos, Elias, and Peter Thompson (1999): "Reassessing the Empirical Validity of the Human-Capital Augmented Neoclassical Growth Model." Journal of Evolutionary Economics, 9:135-154.
Supplementary Reading
Jones,Charles I. (2000): "A note on the closed-form solution of the Solow model." Unpublished, Stanford University.
Klenow, Peter, and Andre Rodriguez-Clare (1997): "The Neoclassical Revival in Growth Economics: Has it Gone Too Far?" NBER Macroeconomics Annual 1997, 73-103.
Temple, Jonathan R. (1998): "Robustness tests of the augmented Solow model." Journal of Applied Econometrics, 13:361-375.
Solow (1957)
Solow (1957). One year after he showed that long-run growth depends fundamentally on continued technical change, Solow gave us a way to measure it. Growth accounting allows us to decompose the sources of growth into technical change and the growth of physical inputs. It is this extremely useful technique which opens the door to questions that are the concern of this course.
Required reading
Solow, Robert (1957): "Technical Change and the Aggregate Production Function." Review of Economics and Statistics, 39:312-320.
Solow (1960)
Less familiar than his 1956 paper, Solow (1960) offers a growth model in which new technology is embodied in new durable goods. Embodied technical change models, aka investment-specific technical change models, aka vintage capital models, imply that investment in physical capital is necessary for technology to progress. The readings here show that: it appears to be an important phenomenon; the framework produces a more reasonable estimate of the time-path of postwar technical change than does the disembodied growth accounting framework; growth accounting that ignores investment -specific technical change will produce an exaggerated role for disembodied technical change. This review of embodied technical change is preliminary, we will study models incorporating it in more detail later.
Required reading
Greenwood, Jeremy, Zvi Hercowitz, and Per Krusell (1997): "Long-run implications of investment specific technological change." American Economic Review, 87(3):342-362.
Solow, Robert (1960): "Investment and technological progress." In Kenneth Arrow, Samuel Karlin and Patrick Suppes, eds., Mathematical Methods in the Social Sciences 1959. Stanford, CA: Stanford University Press, pp. 89-104.
Supplementary Reading
Optimal Control
Growth theory makes heavy use of both dynamic programming and optimal control. Dynamic programming was covered in Macroeconomics I. For variety we will do most of our analysis in continuous time, and hence we study in some detail here the technique of optimal control.
Required reading
Thompson, Peter (2004). Lecture Notes on Dynamic Modeling. Chapter 2.
Human Capital
Theory. If long-run growth requires continued technical change, we need some models that generate it rather than assume it. One can readily do this very much in the neoclassical tradition. Perhaps the best-known such model is the Lucas-Uzawa model of technical change, especially in the form made popular by Lucas (1988).
Evidence. During the mid-1990s researchers were having a hard time producing consistent evidence that education enhanced growth (see Lant Pritchett, [1996], for example). The paper by de la Fuente and Domenech addresses the question of data quality. The authors find, for the OECD, that improved data lead to "improved results" in the sense that the new data provide evidence of a link between income growth and education. The paper is also a valuable guide to the literature. Bils and Klenow (2000) continue their skeptical look at human capital models with a paper that analyzes causality. Is education an investment good that stimulates worker earnings and growth, or is it a consumption good that rises when incomes rise? The answer is both, but which one explains most of the correlation between income growth and education?
Required reading
Lucas, Robert E. (1988): "On the Mechanics of Economic Development." Journal of Monetary Economics, 22:3-42.
de la Fuente, Angel and Rafael Domenech (2000): "Human capital in growth regressions: How much difference does data quality make?" CEPR Discussion Paper no. 2466.
Bils, Mark and Peter J. Klenow (2000): "Does schooling cause growth?" American Economic Review, 90(5):1160-1183.
Supplementary Reading
Barro, Robert J., and Jong-Wha Lee (1997): "Schooling quality in a cross-section of countries." NBER working paper no. 6198.
Benhabib, Jess, and Mark M. Spiegel (1994): "The role of human capital in economic development: Evidence from aggregate cross-country data." Journal of Monetary Economics, 34:143-173.
Nehru, V., E. Swanson, and A. Dubey (1995): "A new database on human capital stocks in developing and industrial countries: sources, methodology, and results." Journal of Development Economics, 46(2):379-401.
Pritchett, Lant (1996): "Where has all the education gone?" World Bank working paper no. 1581.
Romer, Paul M. (1990): "Human capital and growth: theory and evidence." Carnegie-Rochester Conference Series on Public Policy, 32:251-286.
Rosenzweig, M.R. (1990): "Population growth and human capital investments: theory and evidence." Journal of Political Economy, 98:S38-S69.
Tallman, Ellis W., and Ping Wang (1994): "Human capital and endogenous growth: evidence from Taiwan." Journal of Monetary Economics, 34:101-124.
R&D-Based Models of Growth: Theory
Beginning in the late 1980s, a number of working papers incorporating R&D, imperfect competition and endogenous long-run growth, appeared more or less simulatneously. These began to appear in print from about 1990, and an explosion of models followed in the decade following. We will look at a very small selection of these. Grossman and Helpman (1991, chapters 3 and 4) present models of variety expansion and quality growth. They are not my favorite models, (for reasons we can discuss in class, I like Aghion and Howitt [1992]) but they are wonderfully concise and well-written presentations of the main features of the first generation of R&D-driven models of growth). The first half of Ruffin's review is a nice paper explaining where the pieces of this class of models come from. It turns out that these models are a lot less original than one might think.
Required Reading
Grossman and Helpman (1991): Innovation and Growth in the Global Economy, Cambridge, MA: MIT Press, chapters 3 and 4.
Ruffin, Roy (1994): "Endogenous Growth and International Trade." Review of International Economics, 2(1):27-39.
Supplementary Reading
Aghion, Philippe and Peter Howitt (1992): "A Model of Growth Through Creative Destruction." Econometrica, 60(2):323-351.
Aghion, Philippe, and Peter Howitt (1994): "Endogenous Technical Change: The Schumpeterian Perspective." in L. Pasinetti and R, Solow, eds., Economic Growth and the Structure of Long-Term Development. London: Macmillan.
Aghion, Philippe, and Peter Howitt (1996): "Research and Development in the Growth Process." Journal of Economic Growth, 1:49-73.
Arrow, Kenneth J. (1962): "Economic Welfare and the Allocation of Resources for Invention." in NBER, The Rate and Direction of Inventive Activity: Economic and Social Factors, Princeton, Princeton University Press.
Helpman, Elhanan (1992): "Endogenous Macroeconomic Growth Theory." European Economic Review, 36:237-267.
Romer, Paul M. (1990): "Endogenous Technological Change." Journal of Political Economy, 98(5, pt. 2):S71-S102.
Schumpeter, Joseph A. (1942): "Creative Destruction." Chapter 8 of Capitalism, Socialism and Democracy. New York: Harper and Brothers.
Segerstrom, Paul S. (1991): "Innovation, Imitation, and Economic Growth." Journal of Political Economy, 99(4):807-827.
Segerstrom, Paul S., T.C.A. Anant and Elias Dinopoulos (1990): "A Schumpeterian Model of the Product Life Cycle." American Economic Review, 80:1077-1091.
Thompson , Peter, and Doug Waldo (1994): "Growth and Trustified Capitalism." Journal of Monetary Economics, 34:445-462.
R&D Models: Empirics
Gavin Cameron's paper surveys the evidence on the link between innovation and economic growth. It considers a number of different measures of innovation, such as R&D spending, patenting, and innovation counts, as well as the effect of technological spillovers between firms, industries, and countries. Much of the evidence reviewed is in fact microeconomic evidence that Cameron interprets in the light of macroeconomic theory. This was, I think, a wise strategy because the microeconomic evidence is much richer.
The supplementary readings contain two attempts to estimate structural macroeconomic models. Most economists quite sensibly do not try to do this.
Required Reading
Cameron, Gavin (1998): "Innovation and growth: A survey of the empirical evidence." Ph.D. Thesis: Oxford University. Chapter 2.
Supplementary Reading
Caballero, Ricardo J. and Adam B. Jaffe (1994): "How High are the Giant's Shoulders? An Empirical Assessment of Knowledge Spillovers and Creative Destruction in a Model of Economic Growth." NBER Macroeconomics Annual.
Dinopoulos, Elias, and Peter Thompson (2000): "Endogenous Growth in a Cross-Section of Countries." Journal of International Economics, 51(2):335-362.
R&D-Based Models: Scale Effects
In 1995, Chad Jones published an insightful paper pointing out that many endogenous growth models (not just R&D-based models) predict that (1) larger economies grow faster than smaller ones, (2) growth rates accelerate over time in the face of population growth; these predictions are inconsistent with the evidence. Jones' criticism of these models became known as the scale effects problem. This led to a number of reformulated models designed to remove scale effects. It turned out, however, that the behavior of models minus scale effects was rather different from those that kept them.
Required Reading
Jones, Charles I. (1995): "Time Series Tests of Endogenous Growth Models." Quarterly Journal of Economics, 110:495-525.
Dinopoulos, Elias, and Peter Thompson (1999): "Scale Effects in Schumpeterian Models of Economic Growth." Journal of Evolutionary Economics, 9:157-185.
Jones, Charles I. (1999): "Growth: With or Without Scale Effects." American Economic Review, Papers and Proceedings, 89(2):139-144.
Supplementary Reading
Backus, David K., Patrick J. Kehoe and Timothy J. Kehoe (1992): "In Search of Scale Effects in Trade and Growth." Journal of Economic Theory, 58:377-409.
Jones, Charles I. (1995): "R&D-Based Models of Economic Growth." Journal of Political Economy, 103(4):759-784.
Peretto, Pietro (1998): "Technological Change and Population Growth." Journal of Economic Growth, 3(4):283-312.
Dinopoulos, Elias, and Peter Thompson (1998): "Schumpeterian Growth Without Scale Effects." Journal of Economic Growth, 3(4):313-336.
Segerstrom, Paul S. (1998): "Endogenous Growth Without Scale Effects." American Economic Review, 88:1290-1310.
Young, Alwyn (1998): "Growth Without Scale Effects." Journal of Political Economy, 106:41-63.
Howitt, Peter (1999): "Steady Endogenous Growth with Population and R&D Inputs Growing." Journal of Political Economy, 107(4):715-730.