Development Patterns in Multi-Sector Growth Models

Abstract

Common patterns of structural change in the sectoral composition of production, consumption and labor force are observed across countries during the economic development process. These patterns of change consist mainly of a large shift of employment, production and consumption from agriculture to manufacturing, and then from manufacturing to the service sector. This process of structural transformation or structural change has been extensively documented. Empirical evidence shows that the decline in the employment share of agriculture and the increase in employment share of service is a systematic feature in both developed and developing countries. In this regard, there is a growing literature that investigates the economic factors explaining both economic growth and structural change in a general equilibrium framework. Based on their assumptions on the structure of preferences and the sectoral production technologies, models of structural change are classified in two broad approaches: the demand and the supply explanations of structural change. The demand-based explanation emphasizes the role of changes in the composition of the demand on structural change. In this branch of the literature, demand changes are based on the assumption of cross-sector differences in income-elasticity of the demand. Therefore, structural change is driven by the Engel law: as income rises, demand for agriculture goods decreases and less labor is demanded in the agriculture sector to produce goods. Thus, labor moves to those sectors that are facing an increasing demand for goods and services. Consequently, the shares of employment and value added in agriculture decrease as income increases, which is consistent with empirical evidence. The supply-based explanation emphasizes the role of technological differences across sectors to explain structural transformations. In this branch of the literature, sectoral differences in the growth rates of total factor productivity (TFP), on the one hand, and sectoral differences in physical capital intensity, on the other hand, drive structural change. In the first case, when there are only sectoral differences in the pace of technological progress, less labor is required to produce goods in the progressive sectors (those sectors with the highest TFP growth rates) and labor moves from the progressive to the stagnant sectors (those sectors with the lowest TFP growth rates). In the second case, as capital deepening takes place, less labor is demanded to produce goods in the capital-intensive sectors and labor moves from these sectors to the labor-intensive ones. This thesis contributes to the literature on economic growth and structural change by analyzing three novel mechanisms. The three self-contained chapters of this Thesis analyze the effects non-constant technological progress, human capital accumulation, and changes in the uses of time on structural change and their implications on economic growth. The first chapter analyses the effect of technological adoption on structural change. The observed differences in the patterns of industrialization are explained based on sectoral differences in the adoption of technologies. This chapter makes to clear contributions to related literature. First, a technological adoption function is estimated at the sectoral level. Second, the equilibrium of a model of structural change with non-constant biased technological change is characterized. The comparison with the results obtained in the literature show that this model with adoption has a better performance in explaining the patterns of structural change. The second chapter analyses the effect of human capital accumulation on the sectoral composition of employment. To this end, it develops a multisector growth model with human capital accumulation. The main contribution is to show that the initial imbalance between physical and human capital determines the patterns of structural change. The analysis of this chapter is challenging, which shows the huge capacity of Edgar to work with different growth models. The third chapter analyses how the increase in leisure time contributes to explain the rise of the service sector. This chapter makes three contributions. First, using input-output data, it measures the size and evolution of the sector of recreational services. These are services consumed during the leisure time. It is shown that the increase in the time devoted to leisure is parallel to the increase in the consumption of recreational services. Second, a multisector exogenous growth model is used to show that taking into account the interaction between leisure and recreational services improves the performance of multisector growth models in explaining the patterns of structural change. Finally, this model is used to show that labor income taxes may explain cross-country differences in both leisure time and the sectoral composition of employment.