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Professor Fernandez-Villaverde is a Research Associate for the National Bureau of Economic Research (NBER) and Penn's Population Studies Center, and a Research Affiliate for the Centre for Economic Policy Research. His research agenda is in macroeconomics and econometrics, with a focus on the computation and estimation of dynamic stochastic general equilibrium (DSGE) models.
His research agenda focuses on the computation and estimation of dynamic stochastic general equilibrium (DSGE) models; the standard tool of modern quantitative macroeconomics. In particular, Fernandez-Villaverde’s research has focused on how to evaluate the likelihood on non-linear and/or non-normal DSGE models and in exploring situations where those features are important to account for the data. His two most recent papers are examples of this line: an evaluation of the effects of fiscal uncertainty on economic activity, a study of asset pricing implications of DSGE models with Epstein-Zin preferences, and an investigation of the consequences of stochastic volatility for small open economies.
His research agenda focuses on the computation and estimation of dynamic stochastic general equilibrium (DSGE) models; the standard tool of modern quantitative macroeconomics. In particular, Fernandez-Villaverde’s research has focused on how to evaluate the likelihood on non-linear and/or non-normal DSGE models and in exploring situations where those features are important to account for the data. His two most recent papers are examples of this line: an evaluation of the effects of fiscal uncertainty on economic activity, a study of asset pricing implications of DSGE models with Epstein-Zin preferences, and an investigation of the consequences of stochastic volatility for small open economies.
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SSRN Electronic Journal (2024)
SSRN Electronic Journal (2024)
SSRN Electronic Journal (2024)
Working paper (Federal Reserve Bank of Philadelphia)no. 3 (2023): 287-319
SSRN Electronic Journal (2023)
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ECONOMETRICAno. 3 (2023): 869-901
SSRN Electronic Journal (2023)
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Social Science Research Network (2023)
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