DSGE models

August 28, 2010

In a two-country DSGE model, the effects of foreign demand shocks on the home country are greatly amplified if the home economy is constrained by the zero lower bound for policy interest rates. This result applies even to countries that are relatively closed to trade such as the United States. Departing from many of the existing closed-economy models, the duration of the liquidity trap is determined endogenously. Adverse foreign shocks can extend the duration of the trap, implying more contractionary effects for the home country; conversely, large positive shocks can prompt an early exit, implying effects that are closer to those when the zero bound constraint is not binding.

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April 1, 2009

DSGE models are currently estimated with a two step approach: data is first filtered and then DSGE structural parameters are estimated. Two step procedures have problems, ranging from trend misspecification to wrong assumption about the correlation between trend and cycles. In this paper, I present a one step method, where DSGE structural parameters are jointly estimated with filtering parameters. I show that different data transformations imply different structural estimates; the two step approach lacks a statistical-based criterion to select among them. The one step approach allows to test hypothesis about the most likely trend specification for individual series and/or use the resulting information to construct robust estimates by Bayesian averaging. The role of investment shock as source of GDP volatility is reconsidered.

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September 1, 2004

This Paper estimates the effects of technology shocks in VAR models of the United States, Japan and Germany, identified imposing restrictions on the sign of impulse responses. These restrictions are motivated with priors on the parameters of a class of DSGE models with both real and nominal frictions. Estimated technology shocks lead to substantial and persistent increases in labour productivity, real wages, consumption, investment and output. In contrast with most results in the VAR literature, hours worked are much more likely to increase, displaying a hump-shaped pattern. These results are shown to stem primarily from the identification strategy proposed in the Paper, which substitutes theoretical restrictions for the atheoretical assumptions on the time series properties of the data, that are the hallmark of long-run restrictions.

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January 1, 2005

The Paper provides new tools for the evaluation of DSGE models, and applies it to a large-scale New Keynesian dynamic stochastic general equilibrium (DSGE) model with price and wage stickiness and capital accumulation. Specifically, we approximate the DSGE model by a vector autoregression (VAR), and then systematically relax the implied cross-equation restrictions. Let delta denote the extent to which the restrictions are being relaxed. We document how the in- and out-of-sample fit of the resulting specification (DSGE-VAR) changes as a function of delta. Furthermore, we learn about the precise nature of the misspecification by comparing the DSGE model’s impulse responses to structural shocks with those of the best-fitting DSGE-VAR. We find that the degree of misspecification in large-scale DSGE models is no longer so large to prevent their use in day-to-day policy analysis, yet it is not small enough that it cannot be ignored.

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February 1, 2007

In Bayesian analysis of dynamic stochastic general equilibrium (DSGE) prior distributions for some of the taste-and-technology parameters can be obtained from microeconometric or pre-sample evidence, but it is difficult to elicit priors for the parameters that govern the law of motion of unobservable exogenous processes. Moreover, since it is challenging to formulate beliefs about the correlation of parameters, most researchers assume that all model parameters are independent of each other. We provide a simple method of constructing prior distributions for (a subset of) DSGE model parameters from beliefs about the moments of the endogenous variables. We use our approach to investigate the importance of nominal rigidities and show how the specification of prior distributions affects our assessment of the relative importance of different frictions.

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July 1, 2007

We estimate the approximate nonlinear solution of a small DSGE model on euro area data, using the conditional particle filter to compute the model likelihood. Our results are consistent with previous findings, based on simulated data, suggesting that this approach delivers sharper inference compared to the estimation of the linearised model. We also show that the nonlinear model can account for richer economic dynamics: the impulse responses to structural shocks vary depending on initial conditions selected within our estimation sample.

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