Loss function‐based evaluation of DSGE models

By Frank Schorfheide. 2000

679 citations recorded by the source corpus.

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In Economics and Econometrics

Citations in the corpus

Bayesian Estimation of an Open Economy DSGE Model with Incomplete Pass-Through (2007, positive): “6 The price setting problem of the intermediate firms is similar to the one in Smets and Wouters (2003b), following Calvo (1983).”
The Pass-Through of Sovereign Risk (2016, methodology): “I next characterize the posterior density of ~v1 using the Random Walk Metropolis Hastings developed in Schorfheide (2000).”
Methods to Estimate Dynamic Stochastic General Equilibrium Models (2007, background): “Among early contributions are Schorfheide (2000) , DeJong et al. (2000), Chang et al. (2002), and Smets and Wouters (2003).”
Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy (2011, neutral): “As mentioned by Schorfheide (2000) , interestingly,”
The Role of Labor Markets for Euro Area Monetary Policy (2009, positive): “We complement Trigari’s (2006) right-to-manage model with Calvo type wage rigidities.”
DSGE Models in a Data-Rich Environment (2006, neutral): “Recent macroeconomic research has devoted considerable efforts to the development and estimation of dynamic stochastic general equilibrium (DSGE) models that are internally consistent, and based on first principles.1 Some recent micro-founded DSGEmodels, which involve numerous frictions and various…”
Do Central Banks Respond to Exchange Rate Movements? A Structural Investigation (2007, methodology): “(6) Draws from this posterior can be generated through Bayesian simulation techniques described in detail in Schorfheide (2000).”
Forecasting Performance of an Open Economy DSGE Model (2007, methodology): “Second, draws from the joint posterior are generated using the random walk Metropolis algorithm (see Schorfheide, 2000 for details).”
An estimated dynamic stochastic general equilibrium model of the euro area. NBB Working Paper Nr. 35 (2002, methodology): “This result also illustrates that it can be very useful to use the DSGE model as prior information for larger VAR systems (See Del Negro and Schorfheide 2002).”
The New Area-Wide Model of the Euro Area: A Micro-Founded Open-Economy Model for Forecasting and Policy Analysis (2008, methodology): “We adopt the empirical approach outlined in Schorfheide (2000) and An and Schorfheide (2007) and estimate the NAWM employing Bayesian inference methods.”
Comparing Shocks and Frictions in Us and Euro Area Business Cycles: A Bayesian DSGE Approach (2004, positive): “Overall, the relative contribution of productivity and labour supply shocks does conform to the analysis of Shapiro and Watson (1989), who use an identified VAR methodology for the US.”