On the Welfare Costs of Business-Cycle Fluctuations and Economic-Growth Variation in the 20th Century

Lucas (1987) has shown a surprising result in business-cycle research: the welfare cost ofbusiness cycles are very small. Our paper has several original contributions. First, in computingwelfare costs, we propose a novel setup that separates the effects of uncertainty stemming frombusiness-cycle fluctuations and economic-growth variation. Second, we extend the sample from which to compute the moments of consumption: the whole of the literature chose primarily to work with post-WWII data. For this period, actual consumption is already a result of counter-cyclical policies, and is potentially smoother than what it otherwise have been in their absence. So, we employ also pre-WWII data. Third, we take an econometric approach and compute explicitly the asymptotic standard deviation of welfare costs using the Delta Method. Estimates of welfare costs show major differences for the pre-WWII and the post-WWII era. They can reach up to 15 times for reasonable parameter values -β=0.985, and ∅=5. For example, in the pre-WWII period (1901-1941), welfare cost estimates are 0.31% of consumption if we consider only permanent shocks and 0.61% of consumption if we consider only transitory shocks. In comparison, the post-WWII era is much quieter: welfare costs of economic growth are 0.11% and welfare costs of business cycles are 0.037% - the latter being very close to the estimate in Lucas (0.040%). Estimates of marginal welfare costs are roughly twice the size of the total welfare costs. For the pre-WWII era, marginal welfare costs of economic-growth and business- cycle fluctuations are respectively 0.63% and 1.17% of per-capita consumption. The same figures for the post-WWII era are, respectively, 0.21% and 0.07% of per-capita consumption.

Especificação e simulação dinâmica de um modelo macroeconômico de pequeno porte para a economia brasileira

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City sizes and industry concentration

In a general equilibrium model of trade under transportation costsbetween two cities we show how the relative population sizes aresimultaneously detennined with the degree of geographic concentration ofindustries characterized by different elasticities of scale ofproduction. The effect on city size of the presence of nontraded goodsis also analyzed.