Search Results
Showing results 1 to 10 of approximately 30.
(refine search)
Working Paper
Social networks and vaccination decisions
We combine information on social networks with medical records and survey data in order to examine how friends affect one's decision to get vaccinated against the flu. The random assignment of undergraduates to residential halls at a large private university allows us to estimate how peer effects influence health beliefs and vaccination choices. Our results indicate that social exposure to medical information raises people's perceptions of the benefits of immunization. The average student's belief about the vaccine's health value increases by $5.00 when an additional 10 percent of her friends ...
Working Paper
Stochastic volatility
Given the importance of return volatility on a number of practical financial management decisions, the efforts to provide good real- time estimates and forecasts of current and future volatility have been extensive. The main framework used in this context involves stochastic volatility models. In a broad sense, this model class includes GARCH, but we focus on a narrower set of specifications in which volatility follows its own random process, as is common in models originating within financial economics. The distinguishing feature of these specifications is that volatility, being inherently ...
Working Paper
Estimating dynamic equilibrium models with stochastic volatility
We propose a novel method to estimate dynamic equilibrium models with stochastic volatility. First, we characterize the properties of the solution to this class of models. Second, we take advantage of the results about the structure of the solution to build a sequential Monte Carlo algorithm to evaluate the likelihood function of the model. The approach, which exploits the profusion of shocks in stochastic volatility models, is versatile and computationally tractable even in large-scale models, such as those often employed by policy-making institutions. As an application, we use our algorithm ...
Working Paper
Estimation and evaluation of DSGE models: progress and challenges
Estimated dynamic stochastic equilibrium (DSGE) models are now widely used for empirical research in macroeconomics as well as for quantitative policy analysis and forecasting at central banks around the world. This paper reviews recent advances in the estimation and evaluation of DSGE models, discusses current challenges, and provides avenues for future research.
Journal Article
Take your model bowling: forecasting with general equilibrium models
During the past two decades, dynamic stochastic general equilibrium (DSGE) models have taken center stage in academic macroeconomics. Nonetheless, these models are still rarely used in policy-making and forecasting. ; This article describes the workings of the DSGE-VAR, a procedure that combines DSGE models and vector autoregressions (VARs). The procedure uses DSGE models as priors to restrict the VAR?s parameters. Since the VAR?s parameters are imprecisely estimated unless a very long time series of data is available, using DSGE priors can improve the VAR?s forecasting performance. Moreover, ...
Report
The macroeconomic effects of large-scale asset purchase programs
The effects of asset purchase programs on macroeconomic variables are likely to be moderate. We reach this conclusion after simulating the impact of the Federal Reserve?s second large-scale asset purchase program (LSAP II) in a DSGE model enriched with a preferred habitat framework and estimated on U.S. data. Our simulations suggest that such a program increases GDP growth by less than half a percentage point, although the effect on the level of GDP is very persistent. The program?s marginal contribution to inflation is very small. One key reason for our findings is that we estimate a small ...
Working Paper
The Chicago Fed DSGE model
The Chicago Fed dynamic stochastic general equilibrium (DSGE) model is used for policy analysis and forecasting at the Federal Reserve Bank of Chicago. This article describes its specification and estimation, its dynamic characteristics and how it is used to forecast the US economy. In many respects the model resembles other medium scale New Keynesian frameworks, but there are several features which distinguish it: the monetary policy rule includes forward guidance, productivity is driven by neutral and investment specific technical change, multiple price indices identify inflation and there ...
Report
The term structure of inflation expectations
We present estimates of the term structure of inflation expectations, derived from an affine model of real and nominal yield curves. The model features stochastic covariation of inflation with the real pricing kernel, enabling us to extract a time-varying inflation risk premium. We fit the model not only to yields, but also to the yields' variance-covariance matrix, thus increasing identification power. We find that model-implied inflation expectations can differ substantially from break-even inflation rates when market volatility is high. Our model's ability to be updated weekly makes it ...
Working Paper
Business cycles and remittances: can the Beveridge-Nelson decomposition provide new evidence?
In this paper, I analyze the business cycle properties of remittances and output series for three pairs of countries: United States-Mexico, United States-El Salvador, and Germany-Turkey. Using an unobserved components state-space model (via the Beveridge-Nelson decomposition), I decompose the remittances and output series into stochastic permanent and cyclical components. I then use the resulting stationary cyclical components to estimate co-movements between remittances and output series. Empirical results indicate that remittances are countercyclical with all the home countries: Mexico, El ...
Working Paper
Frequentist inference in weakly identified DSGE models
The authors show that in weakly identified models (1) the posterior mode will not be a consistent estimator of the true parameter vector, (2) the posterior distribution will not be Gaussian even asymptotically, and (3) Bayesian credible sets and frequentist confidence sets will not coincide asymptotically. This means that Bayesian DSGE estimation should not be interpreted merely as a convenient device for obtaining asymptotically valid point estimates and confidence sets from the posterior distribution. As an alternative, the authors develop a new class of frequentist confidence sets for ...