Estimating Macroeconomic Models: A Likelihood Approach

This paper shows how particle filtering allows us to undertake likelihood-based inference in dynamic macroeconomic models. The models can be nonlinear and/or non-normal. We describe how to use the output from the particle filter to estimate the structural parameters of the model, those characterizing preferences and technology, and to compare different economies. Both tasks can be implemented from either a classical or a Bayesian perspective. We illustrate the technique by estimating a business cycle model with investment-specific technological change, preference shocks, and stochastic volatility.

Estimating Nonlinear Dynamic Equilibrium economies: A Likelihood Approach

This paper presents a framework to undertake likelihood-based inference in nonlinear dynamic equilibrium economies. We develop a Sequential Monte Carlo algorithm that delivers an estimate of the likelihood function of the model using simulation methods. This likelihood can be used for parameter estimation and for model comparison. The algorithm can deal both with nonlinearities of the economy and with the presence of non-normal shocks. We show consistency of the estimate and its good performance in finite simulations. This new algorithm is important because the existing empirical literature that wanted to follow a likelihood approach was limited to the estimation of linear models with Gaussian innovations. We apply our procedure to estimate the structural parameters of the neoclassical growth model.Likelihood-Based Inference, Dynamic Equilibrium Economies, Nonlinear Filtering, Sequential Monte Carlo)

Estimating Dynamic Equilibrium Economies: Linear versus Nonlinear Likelihood

This paper compares two methods for undertaking likelihood-based inference in dynamic equilibrium economies: a Sequential Monte Carlo filter proposed by Fernández-Villaverde and Rubio-Ramírez (2004) and the Kalman filter. The Sequential Monte Carlo filter exploits the nonlinear structure of the economy and evaluates the likelihood function of the model by simulation methods. The Kalman filter estimates a linearization of the economy around the steady state. We report two main results. First, both for simulated and for real data, the Sequential Monte Carlo filter delivers a substantially better fit of the model to the data as measured by the marginal likelihood. This is true even for a nearly linear case. Second, the differences in terms of point estimates, even if relatively small in absolute values, have important effects on the moments of the model. We conclude that the nonlinear filter is a superior procedure for taking models to the data.Likelihood-Based Inference, Dynamic Equilibrium Economies, Nonlinear Filtering, Kalman Filter, Sequential Monte Carlo

MEDEA: A DSGE Model for the Spanish Economy

In this paper, we provide a brief introduction to a new macroeconometric model of the Spanish economy named MEDEA (Modelo de Equilibrio Dinámico de la Economía EspañolA). MEDEA is a dynamic stochastic general equilibrium (DSGE) model that aims to describe the main features of the Spanish economy for policy analysis, counterfactual exercises, and forecasting. MEDEA is built in the tradition of New Keynesian models with real and nominal rigidities, but it also incorporates aspects such as a small open economy framework, an outside monetary authority such as the ECB, and population growth, factors that are important in accounting for aggregate fluctuations in Spain. The model is estimated with Bayesian techniques and data from the last two decades. Beyond describing the properties of the model, we perform different exercises to illustrate the potential of MEDEA, including historical decompositions, long-run and short-run simulations, and counterfactual experiments.DSGE Models, Likelihood Estimation, Bayesian Methods

Convergence Properties of the Likelihood of Computed Dynamic Models

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 show that as the approximated policy function converges to the exact policy, the approximated likelihood also converges to the exact likelihood. Second, we prove that the approximated likelihood converges at the same rate as the approximated policy function. Third, we find that the error in the approximated likelihood gets compounded with the size of the sample. Fourth, we discuss convergence of Bayesian and classical estimates. We complete the paper with three applications to document the quantitative importance of our results.computed dynamic models, likelihood inference, asymptotic properties

Comparing Solution Methods for Dynamic Equilibrium Economies

This paper compares solution methods for dynamic equilibrium economies. We compute and simulate the stochastic neoclassical growth model with leisure choice using Undetermined Coefficients in levels and in logs, Finite Elements, Chebyshev Polynomials, Second and Fifth Order Perturbations and Value Function Iteration for several calibrations. We document the performance of the methods in terms of computing time, implementation complexity and accuracy and we present some conclusions about our preferred approaches based on the reported evidence.Dynamic Equilibrium Economies, Computational Methods, Linear and Nonlinear Solution Methods

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 an econometrician. We review circumstances under which the impulse response of the VAR resembles the impulse response associated with the economic model. We give four examples that illustrate a simple condition for checking whether the mapping from VAR shocks to economic shocks is invertible. The condition applies when there are equal numbers of VAR and economic shocks.VARs , Invertibility, Estimation of Dynamic Equilibrium Models, economic shocks, innovations

Computing DSGE Models with Recursive Preferences

This paper compares different solution methods for computing the equilibrium of dynamic stochastic general equilibrium (DSGE) models with recursive preferences such as 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 complexity, and accuracy. Our main finding is that a third-order perturbation is competitive in terms of accuracy with Chebyshev polynomials and value function iteration, while being an order of magnitude faster to run. Therefore, we conclude that perturbation methods are an attractive approach for computing this class of problems.DSGE Models, Recursive Preferences, Perturbation

Lead free piezoelectric ceramics based on Bi0.5(Na0.8K0.2)0.5TiO3 y K0.5Na0.5NbO3 systems

Los materiales cerámicos basados en circonato-titanato de plomo, Pb(Zr,Ti)O3(PZT), son muy conocidos por sus excelentes propiedades piezoeléctricas. Si bien, estos materiales se producen generalmente a partir de la técnica de mezcla de óxidos, la cual es relativamente simple y económica, en su formulación se emplea un alto contenido de óxido de plomo (aprox. 70%). Dado que el plomo y sus compuestos son considerados tóxicos y peligrosos, no sólo por la polución directa que genera el proceso de manufactura y maquinado de los compuestos, sino también porque los productos que contienen PZT no pueden ser reciclados, recientemente se han comenzado a investigar diferentes composiciones piezoeléctricas para su reemplazo. En este trabajo, se analizan algunos desarrollos propios en el campo de los materiales piezoeléctricos libres de plomo donde se enfatiza la correlación existente entre las propiedades finales, la microestructura desarrollada y la estructura estabilizada.Ceramics based on lead zirconium titanate Pb(Zr,Ti)O3 (PZT) are well known for their excellent piezoelectric properties. These materials are generally produced by solid reaction technique, which is relatively simple and economical; however their production needs high lead oxide content (approx. 70%). Lead and its compounds are considered toxic and dangerous, due to direct pollution generated by the manufacturing process and machining of the compounds, and the inability to recycle products containing PZT. Therefore, other piezoelectric compositions based on lead free materials have begun investigated. In this paper, some developments in the field of lead-free piezoelectric materials, correlating the structure and microstructure with the properties materials properties are analyzed.Fil: Castro, Miriam Susana. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mar del Plata. Instituto de Investigación en Ciencia y Tecnología de Materiales (i); ArgentinaFil: Camargo, Javier Eduardo. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mar del Plata. Instituto de Investigación en Ciencia y Tecnología de Materiales (i); ArgentinaFil: Taub, Jonathan. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mar del Plata. Instituto de Investigación en Ciencia y Tecnología de Materiales (i); ArgentinaFil: Fernandez, J. F.. Instituto de Ceramica y Vidrio de Madrid; EspañaFil: Rubio-Marcos, F.. Instituto de Ceramica y Vidrio de Madrid; EspañaFil: Ramajo, Leandro Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mar del Plata. Instituto de Investigación en Ciencia y Tecnología de Materiales (i); Argentina. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentin