A test of the paradox of thrift is conducted throughout the lens of a business cycle model. To this aim, a simple extension of the neoclassical framework with concave frontier is developed which leads to a dramatic improvement on the prediction of the saving rate. Then, it is possible to isolate periods when saving changes are not a consequence of technology shocks. A VAR identified through these episodes suggests that a 1$\%$ increase in the saving rate leads to half a percentage point decrease in output growth.
Latest version March 2014.
The vast majority of the business cycle literature assumes a linear transformation frontier between consumption and investment goods. This assumption neglects a relationship, present in the data, between the relative price of investments and total factor productivity. This assumption also leads to counterfactual saving rates. A simple extension of the real business cycle model is proposed where the transformation frontier can be concave. Alternative identification strategies lead to similar estimates of the curvature with a dramatic improvement of the prediction of the saving rate.
With Martin Gervais
July 2013. Revision reqested, EER.
This paper studies optimal taxation in a version of the neoclassical growth model in which investment becomes productive within the period, thereby making the supply of capital elastic in the short run. Because taxing capital is distortionary in the short run, the government's ability/desire to raise revenues through capital income taxation in the initial period or when the economy is hit with a bad shock is greatly curtailed. Our timing assumption also leads to tractable Ramsey and Markov-perfect specifications without state-contingent debt. We find that the cyclical properties of taxes are robust to the commitment assumptions.
Latest version December 2013. Submitted.
Labor composition by gender, age, and education has undergone dramatic changes over the last forty years in the United States. Furthermore, the volatility of total market hours differs systematically between genders, age, and education groups. I develop a large-scale business cycle model which suggests that demographic changes by gender and education affect labor supply elasticities at the micro level. This has important repercussions on aggregate volatility. Changes in labor composition account for 30% of the observed changes in aggregate volatility over this period of time. To solve the model over this large transition, I develop a new algorithm which extends perturbation methods to the stochastic transition path and can be applied to a broad class of DSGE models. Matlab code is available in the page Codes.