We document five stylized facts of economic growth. (1) The “residual ” rather than factor accumulation accounts for most of the income and growth differences across nations. (2) Income diverges over the long run. (3) Factor accumulation is persistent while growth is not persistent and the growth path of countries exhibits remarkable variation across countries. (4) Economic activity is highly concentrated, with all factors of production flowing to the richest areas. (5) National policies closely associated with long-run economic growth rates. We argue that these facts do not support models with diminishing returns, constant returns to scale, some fixed factor of production, and that highlight the role of factor accumulation. Empirical work, however, does not yet decisively distinguish among the different theoretical conceptions of “total factor productivity growth.” Economists should devote more effort towards modeling and quantifying total factor productivity.

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We explore the effect of computerization on productivity and output growth using data from 527 large US firms over 1987-1994. We find that computerization makes a contribution to measured productivity and output growth in the short term (using one year differences) that is consistent with normal returns to computer investments. However, the productivity and output contributions associated with computerization are up to five times greater over long periods (using five to seven year differences). The results suggest that the observed contribution of computerization is accompanied by relatively large and time-consuming investments in complementary inputs, such as organizational capital, that may be omitted in conventional calculations of productivity. The large long-run contribution of computers and their associated complements that we uncover may partially explain the subsequent investment surge in computers in the late 1990s.

Abstract: This paper presents a simple R&D-driven endogenous growth model to shed light on some puzzling economic trends. The model can account for why patent statistics have been roughly constant even though R&D employment has risen sharply over the last 30 years. The model also illuminates why steadily increasing R&D effort has not lead to any upward trend in economic growth rates, as is predicted by earlier R&D-driven endogenous growth models with the “scale effect ” property.

their helpful suggestions. This paper develops the empirical and theoretical case that differences in economic institutions are the fundamental cause of differences in economic development. We first document the empirical importance of institutions by focusing on two “quasi-natural experiments” in history, the division of Korea into two parts with very different economic institutions and the colonization of much of the world by European powers starting in the fifteenth century. We then develop the basic outline of a framework for thinking about why economic institutions differ across countries. Economic institutions determine the incentives of and the constraints on economic actors, and shape economic outcomes. As such, they are social decisions, chosen for their consequences. Because different groups and individuals typically benefit fromdifferent economic institutions, there is generally aconflict over these social choices, ultimately resolved in favor of groups with greater political power. The distribution of political power in society is in turn determined by political institutions and the distribution of resources. Political institutions allocate de

The role that investment-specific technological change played in generating postwar U.S. growth is investigated here. The premise is that the introduction of new, more efficient capital goods is an important source of productivity change, and an attempt is made to disentangle its effects from the more traditional Hicks-neutral form of technological progress. The balanced-growth path for the model is characterized and calibrated to U.S. National Income and Product Account data. The quantitative analysis suggests that investment-specific technological change accounts for the major part of growth.

Abstract: This handbook chapter studies the theoretical microfoundations of urban agglomeration economies. We distinguish three types of micro-foundations, based on sharing, matching, and learning mechanisms. For each of these three categories, we develop one or more core models in detail and discuss the literature in relation to those models. This allows us to give a precise characterisation of some of the main theoretical underpinnings of urban agglomeration economies, to discuss modelling issues that arise when working with these tools, and to compare different sources of agglomeration economies in terms of the aggregate urban outcomes they produce as well as in terms of their normative implications. Key words: cities, agglomeration, increasing returns, micro-foundations jel classification: r12, r13, r32 ∗ This is a working draft of a chapter written for eventual publication in the Handbook of Regional and Urban Economics, Volume 4, edited by J. Vernon Henderson and Jacques-François Thisse, to be published by North-Holland. We are grateful to the editors, Masa Fujita, Mike Peters, and the participants at the the 2002 narsa meetings for comments and suggestions.

several years has seen a revival. Unfortunately, little progress has been made on empirical estimation of such interactions and testing for their presence, on the development of policy interventions which work through social interactions, or on the evaluation of such interventions because several basic identification and estimation problems have not been seriously confronted.