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Title: Growth with cross-sectional heterogeneity
Author: Michelacci, Claudio
ISNI:       0000 0001 3397 4221
Awarding Body: London School of Economics and Political Science
Current Institution: London School of Economics and Political Science (University of London)
Date of Award: 1998
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Different agents experience different histories and pursue different economic functions. This implies that once a picture of the economic system is taken, a lot of cross-sectional heterogeneity appears. This thesis consists of four essays each one of them makes a case where the intrinsic heterogeneity of the economic system is crucial for understanding macroeconomic performance. Firstly, it shows when and how an increase in the level of business cycle volatility harms the growth process in a Keynesian world where the decision to free resources and to take advantage of them lies on different agents. Secondly, it analyses the effects of an increase in research effort in a Schumpeterian world where innovation requires an entrepreneur to implement a valuable invention. In this context the observed decreasing returns in R&D might be the outcome of lack of entrepreneurial skills rather than any vanishing of investment opportunities. Thirdly, it extends the Solow-Swan growth model allowing for cross-sectional heterogeneity. In doing so it reconciles apparently conflicting results on cross-sectional convergence and stochastic output dynamics. Finally, it argues that cross-sectional heterogeneity is an important transmission mechanism. In the context of a stylized vintage model it is shown how the mechanism generating heterogeneity in the real world also generates persistence in the aggregate fluctuations. Moreover, as aggregate shocks create very high degree of persistence without affecting either the number of firms in the market or technological progress, this degree of persistence is simply attributed to cross-sectional heterogeneity.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available