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- Working Papers | Penn Economics

of the real interest rate at which small open emerging economies borrow have a quantitatively important effect on real variables like output consumption investment and hours worked To motivate our investigation we document the strong evidence of time varying volatility in the real interest rates faced by a sample of four emerging small open economies Argentina Ecuador Venezuela and Brazil We postulate a stochastic volatility process for real interest rates using T bill rates and country spreads and estimate it with the help of the Particle filter and Bayesian methods Then we feed the estimated stochastic volatility process for real interest rates in an otherwise standard small open economy business cycle model We calibrate eight versions of our model to match basic aggregate observations two versions for each of the four countries in our sample We find that an increase in real interest rate volatility triggers a fall in output consumption investment and hours worked and a notable change in the current account of the economy Download Paper 03 005 Jess Benhabib Stephanie Schmitt Grohe Martín Uribe Backward Looking Interest Rate Rules Interest Rate Smoothing and Macroeconomic Instability The existing literature on the stabilizing properties of interest rate feedback rules has stressed the perils of linking interest rates to forecasts of future inflation Such rules have been found to give rise to aggregate fluctuations due to self fulfilling expectations In response to this concern a growing literature has focused on the stabilizing properties of interest rate rules whereby the central bank responds to a measure of past inflation The consensus view that has emerged is that backward looking rules contribute to protecting the economy from embarkingon expectations driven fluctuations A common characteristic of the existing studies that arrive at this conclusion is their focus on local analysis The contribution of

Original URL path: http://economics.sas.upenn.edu/pier/working-papers?wp_author_id=242 (2015-07-10)

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Print Email Share 05 018 Jesus Fernandez Villaverde Juan F Rubio Ramírez Thomas J Sargent A B C s And D s For Understanding VARS The dynamics of a linear or linearized dynamic stochastic economic model can be expressed in terms of matrices A B C D that define a state space system An associated state space system A K C Sigma determines a vector autoregression for observables available to

Original URL path: http://economics.sas.upenn.edu/pier/working-papers?wp_author_id=456 (2015-07-10)

Open archived version from archive - Working Papers | Penn Economics

This paper studies the econometrics of computed dynamic models Since these models generally lack a closed form solution economists approximate the policy functions of the agents in the model with numerical methods But this implies that instead of the exact likelihood function the researcher can evaluate only an approximated likelihood associated with the approximated policy function What are the consequences for inference of the use of approximated likelihoods First we

Original URL path: http://economics.sas.upenn.edu/pier/working-papers?wp_author_id=500 (2015-07-10)

Open archived version from archive - Working Papers | Penn Economics

General Equilibrium Approach Job security provisions are commonly invoked to explain the high and persistent European unemployment rates This belief has led several countries to reform their labor markets and liberalize the use of fixed term contracts Despite how common such contracts have become after deregulation there is a lack of quantitative analysis of their impact on the economy To fill this gap we build a general equilibrium model with

Original URL path: http://economics.sas.upenn.edu/pier/working-papers?wp_author_id=526 (2015-07-10)

Open archived version from archive - Working Papers | Penn Economics

a growing literature has studied intertemporal choice when individuals discount the future hyperbolically These preferences generate dynamically inconsistent choices in contrast with the usual assumption of exponential discounting where this issue cannot arise Hyperbolic discounting is justified based on experimental evidence of individual self control problems We argue that this interpretation depends crucially on the absence of uncertainty We show that once uncertainty is included the observed behavior is compatible

Original URL path: http://economics.sas.upenn.edu/pier/working-papers?wp_author_id=663 (2015-07-10)

Open archived version from archive - Working Papers | Penn Economics

keywords Options Print Email Share 01 037 Jesus Fernandez Villaverde Juan Francisco Rubio Rami rez Comparing Dynamic Equilibrium Models to Data This paper studies the properties of the Bayesian approach to estimation and comparison of dynamic equilibrium economies Both tasks can be performed even if the models are nonnested misspecified and nonlinear First we show that Bayesian methods have a classical interpretation asymptotically the parameter point estimates converge to their

Original URL path: http://economics.sas.upenn.edu/pier/working-papers?wp_author_id=704 (2015-07-10)

Open archived version from archive - “The Term Structure Of Interest Rates In A DSGE Model With Recursive Preferences” | Penn Economics

Model with Recursive Preferences We solve a dynamic stochastic general equilibrium DSGE model in which the representative household has Epstein and Zin recursive preferences The parameters governing preferences and technology are estimated by means of maximum likelihood using macroeconomic data and asset prices with a particular focus on the term structure of interest rates We estimate a large risk aversion an elasticity of intertemporal substitution higher than one and substantial

Original URL path: http://economics.sas.upenn.edu/pier/working-paper/2010/%E2%80%9C-term-structure-interest-rates-dsge-model-recursive-preferences%E2%80%9D (2015-07-10)

Open archived version from archive - "Computing DSGE Models With Recursive Preferences" | Penn Economics

those in Epstein and Zin 1989 and 1991 Models with these preferences have recently become popular but we know little about the best ways to implement them numerically To fill this gap we solve the stochastic neoclassical growth model with recursive preferences using four different approaches second and third order perturbation Chebyshev polynomials and value function iteration We document the performance of the methods in terms of computing time implementation

Original URL path: http://economics.sas.upenn.edu/pier/working-paper/2009/computing-dsge-models-recursive-preferences (2015-07-10)

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