http://individual.utoronto.ca/zheli/sa1.pdf

On the mechanics of economic development

This paper examines whether the Solow growth model is consistent with the international variation in the standard of living. It shows that an augmented Solow model that includes accumulation of human as well as physical capital provides an excellent description of the cross-country data. The paper also examines the implications of the Solow model for convergence in standards of living, that is, for whether poor countries tend to grow faster than rich countries. The evidence indicates that, holding population growth and capital accumulation constant, countries converge at about the rate the augmented Solow model predicts. This paper takes Robert Solow seriously. In his classic 1956 article Solow proposed that we begin the study of economic growth by assuming a standard neoclassical production function with decreasing returns to capital. Taking the rates of saving and population growth as exogenous, he showed that these two vari- ables determine the steady-state level of income per capita. Be- cause saving and population growth rates vary across countries, different countries reach different steady states. Solow's model gives simple testable predictions about how these variables influ- ence the steady-state level of income. The higher the rate of saving, the richer the country. The higher the rate of population growth, the poorer the country. This paper argues that the predictions of the Solow model are, to a first approximation, consistent with the evidence. Examining recently available data for a large set of countries, we find that saving and population growth affect income in the directions that Solow predicted. Moreover, more than half of the cross-country variation in income per capita can be explained by these two variables alone. Yet all is not right for the Solow model. Although the model correctly predicts the directions of the effects of saving and

/pdf/a-contribution-to-the-empirics-of-economic-growth-27cl5gkqam.pdf

A Contribution to the Empirics of Economic Growth

Growth in this model is driven by technological change that arises from intentional investment decisions made by profit-maximizing agents. The distinguishing feature of the technology as an input is that it is neither a conventional good nor a public good; it is a nonrival, partially excludable good. Because of the nonconvexity introduced by a nonrival good, price-taking competition cannot be supported. Instead, the equilibrium is one with monopolistic competition. The main conclusions are that the stock of human capital determines the rate of growth, that too little human capital is devoted to research in equilibrium, that integration into world markets will increase growth rates, and that having a large population is not sufficient to generate growth.

/pdf/endogenous-technological-change-4yzdlw043b.pdf

Endogenous Technological Change

Existing strategies for econometric analysis related to macroeconomics are subject to a number of serious objections, some recently formulated, some old. These objections are summarized in this paper, and it is argued that taken together they make it unlikely that macroeconomic models are in fact over identified, as the existing statistical theory usually assumes. The implications of this conclusion are explored, and an example of econometric work in a non-standard style, taking account of the objections to the standard style, is presented. THE STUDY OF THE BUSINESS cycle, fluctuations in aggregate measures of economic activity and prices over periods from one to ten years or so, constitutes or motivates a large part of what we call macroeconomics. Most economists would agree that there are many macroeconomic variables whose cyclical fluctuations are of interest, and would agree further that fluctuations in these series are interrelated. It would seem to follow almost tautologically that statistical models involving large numbers of macroeconomic variables ought to be the arena within which macroeconomic theories confront reality and thereby each other. Instead, though large-scale statistical macroeconomic models exist and are by some criteria successful, a deep vein of skepticism about the value of these models runs through that part of the economics profession not actively engaged in constructing or using them. It is still rare for empirical research in macroeconomics to be planned and executed within the framework of one of the large models. In this lecture I intend to discuss some aspects of this situation, attempting both to offer some explanations and to suggest some means for improvement. I will argue that the style in which their builders construct claims for a connection between these models and reality-the style in which "identification" is achieved for these models-is inappropriate, to the point at which claims for identification in these models cannot be taken seriously. This is a venerable assertion; and there are some good old reasons for believing it;2 but there are also some reasons which have been more recently put forth. After developing the conclusion that the identification claimed for existing large-scale models is incredible, I will discuss what ought to be done in consequence. The line of argument is: large-scale models do perform useful forecasting and policy-analysis functions despite their incredible identification; the restrictions imposed in the usual style of identification are neither essential to constructing a model which can perform these functions nor innocuous; an alternative style of identification is available and practical. Finally we will look at some empirical work based on an alternative style of macroeconometrics. A six-variable dynamic system is estimated without using 1 Research for this paper was supported by NSF Grant Soc-76-02482. Lars Hansen executed the computations. The paper has benefited from comments by many people, especially Thomas J. Sargent

/pdf/macroeconomics-and-reality-3v6kkpl8jz.pdf

Macroeconomics and reality

Growth in this model is driven by technological change that arises from intentional investment decisions made by profit maximizing agents. The distinguishing feature of the technology as an input is that it is neither a conventional good nor a public good; it is a nonrival, partially excludable good. Because of the nonconvexity introduced by a nonrival good, price-taking competition cannot be supported, and instead, the equilibriumis one with monopolistic competition. The main conclusions are that the stock of human capital determines the rate of growth, that too little human capital is devoted to research in equilibrium, that integration into world markets will increase growth rates, and that having a large population is not sufficient to generate growth.

https://papers.ssrn.com/sol3/Delivery.cfm/nber_w3210.pdf?abstractid=226703&mirid=1

This Note has two objectives: one expository and one analytical. I am afraid that many readers will be put off by the apparent mathematical difficulty of Uzawa’s paper. I say “ apparent ” advisedly, because the paper is in part very easy; it requires only a little arithmetic and the bare elements of the calculus of functions of one variable. Any economist who cannot read it ought at least to insist that his students do so. My first objective is to describe in plain English how the model works, because I think it is an interesting extension of earlier work in this branch of macro-economics.

Note on Uzawa's Two-Sector Model of Economic Growth

I came to Harvard College as a 16-year-old freshman in September 1940. So far as I had any coherent plan at all, it was to study plant genetics. I can no longer remember where that idea came from; my best guess is that I had heard there were jobs to be had in the US Forest Service. Today’s students cannot imagine how large a factor that was in our minds as the decade of the thirties came to a close.

Goodwin’s Growth Cycle: Reminiscence and Rumination

Some Recent Developments in the Theory of Production

Law of Production and Laws of Algebra: The Humbug Production Function: A Comment

As a purely theoretical matter, aggregate production functions exist only under conditions too stringent to be believed satisfied by the diverse technological relationships of actual economies. There is a summary discussion and bibliography in Fisher [2]. Yet aggregate production functions estimated from real data do appear to give good results, at least sometimes, and to do so in an apparently non-trivial way. Not only do such estimated relationships give good fits to input and output data, but also the calculated marginal products appear to be related to observed factor payments. Alternatively, production functions with parameters estimated from factor payments turn out to fit input and output data pretty well sometimes. It is not a simple matter to decide why this should be so as a matter of theory. Indeed, the problem is sufficiently complicated that perhaps the most promising mode of attack on it is through the construction and analysis of simulation experiments. By constructing simplified economies in which the conditions for aggregation are known not to be satisfied, we can hope to find out inductively the circumstances under which aggregate production functions appear to give good results in the double sense just discussed. Moreover, such experiments can cast light on other aspects of the estimation of aggregate production functions from underlying non-aggregatable data. The related papers of Houthakker [4], Levhari [6] and Sato [8] do not bear directly on the problems here addressed. Those papers show what aggregate production functions can be expected when the distribution of capital over firms with related technologies is fixed (or changes in very restricted ways). Such fixity of distribution, however, can hardly be expected in the real world and is certainly not true in the world of simulation experiments reported below and in Fisher [3]. Here the issue is that of why aggregate production functions should appear to exist at all, rather than that of what form they will take given that a constant distribution of capital over firms ensures their existence. See Fisher [2, pp. 571-574]. The books by Johansen [5] and Sato [9] give excellent discussions of aggregation from several points of view. This programme of research was begun in Fisher [3]; individual firms (with a single homogeneous output and single homogeneous labour but different capital types) were given different Cobb-Douglas production functions, underlying capital and labour data were generated in various ways, and labour was assigned to firms to maximize output. An aggregate Cobb-Douglas production function was then estimated and its wage predictions examined. A number of subsidiary results were found in these experiments, and we shall comment

/pdf/aggregate-production-functions-some-ces-experiments-qz2ym1jhoh.pdf

Robert M. Solow

Papers

Note on Uzawa's Two-Sector Model of Economic Growth

Goodwin’s Growth Cycle: Reminiscence and Rumination

Some Recent Developments in the Theory of Production

Law of Production and Laws of Algebra: The Humbug Production Function: A Comment

Aggregate production functions: some CES experiments