A contribution to the determinants of total factor productivity growth

Abstract

Why do some countries grow and others stagnate? The Science magazine considers this question as one of the 125 "most compelling puzzles and questions facing scientists today'' (Science magazine (2005)). Indeed, the successful identification of key policies that foster economic growth and development makes it possible to implement optimal growth strategies that could cut world poverty, affect income inequalities across countries, and improve the standards of living of individuals. <br /> While the importance to identify the key determinants of economic growth and development is obvious, a unified theory that matches empirical facts is still missing. Instead, the emergence of endogenous growth theory since the early 90s induced a vast strand of literature covering numerous potential determinants of economic growth ranging from macroeconomic policies over trade and industrial policies to deep-seated institutional factors, and initial conditions. Clearly, policymakers have direct control over some of these factors, but only limited (long-term) or no control over others. Consequently, it appears that we need to take some care in isolating growth-enhancing strategies. Nevertheless, recent advances in development accounting are pointing the way for future research. Caselli (2005) concludes that fluctuations in factor accumulation (labor, physical and human capital) account only for 1/3 of the fluctuations of income across countries. Thus, the bulk of international income differences is due to variations in the residual measure which is labelled total factor productivity (TFP). It follows that a successful growth theory needs to explain international differences in aggregate TFP-growth? In the following, I provide three supplementary approaches that contribute to the explanation of differences in TFP-growth across countries and over time. <br /> The first chapter analyzes the impact of infrastructure capital on different sources of economic growth. Starting with the contribution of Barro (1990), the literature on infrastructure and growth mainly focuses on the relationship between private and public capital investments. In contrast, I demonstrate a link between (telecommunication) infrastructure capital and endogenous technological change in the context of an dynamic panel estimation applying aggregate country- as well as U.S. firm-level data. The main empirical finding is that the increase in telecommunication infrastructure during the last 30 years enhanced R&D investments but did not affect the accumulation of physical or human capital in our sample. Moreover, I provide an extended R&D growth model, which emphasizes a cost-reducing feature of infrastructure capital, to demonstrate a potential link between the level of infrastructure capital and endogenous technological change. Finally, I show that the link between infrastructure and R&D can lead to multiple balanced growth pathes if one endogenizes the provision of infrastructure capital. <br /> The second chapter demonstrates a negative relationship between inflation and long-run productivity growth. Inflation generates long-run real effects due to a link from the short-run interplay between nominal and financial frictions to a firm's qualitative investment portfolio. First, I employ country panel data to investigate the robustness of a negative causal effect of inflation on long-run TFP-growth. Second, I develop an endogenous growth model whose key ingredients are (i) a nominal short-run portfolio choice for households, (ii) an agency problem which gives rise to financial market incompleteness, (iii) a firm-level technology choice between a return-dominated but secure and a more productive but risky project. In this framework, inflation increases the costs of corporate insurance against productive but risky projects and hence a firm's choice of technology. It follows that economies (time periods) that feature a higher level of inflation are predicted to exhibit lower TFP-growth in the long-run as long as financial markets are incomplete. Finally, we apply U.S. industry as well as firm-level dynamic anel data to examine the relevance of our specific microeconomic mechanism. We find that (i) firms insure systematically against risky R&D investments by means of corporate liquidity holdings, (ii) periods of higher inflation restrain firm-level R&D investments by reducing corporate liquidity holdings. <br /> The third chapter proposes a growth model for an economy consisting of firms which are heterogeneous in technologies and input demands. I show that the growth rate in this economy depends not only on changes in the aggregate level of capital and labor, but also on changes in the allocation of these inputs across firms. As the latter effects are neglected in conventional growth models, they are misleadingly captured by the residual TFP measure. In contrast, I am able to quantify the influence of these components. Our empirical analysis, which is based on structural estimation from firm-level data, reveals that changes in allocation of capital and labor have pronounced effects on GDP-growth for most European countries. Further, I take cross-country differences in the distributional effects into account to improve conventional growth accounting exercises. In particular, Is find that they explain additionally up to 17% of growth differences among 19 European countries. Consequently, allowing for heterogeneity in firm-level technologies and input demands increases the explanatory power of the inputs.