How much nominal rigidity is there in the US economy? Testing a new Keynesian DSGE model using indirect inference

Zhou

2015

Ital Econ J

Self Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract Out-of-sample forecasting tests of DSGE models against time-series benchmarks such as an unrestricted VAR are increasingly used to check a) the speci…cation b) the forecasting capacity of these models. We carry out a Monte Carlo experiment on a widely-used DSGE model to investigate the power of these tests. We …nd that in speci…cation testing they have weak power relative to an in-sample indirect inference test; this implies that a DSGE model may be badly mis-speci…ed and still improve forecasts from an unrestricted VAR. In testing forecasting capacity they also have quite weak power, particularly on the lefthand tail. By contrast a model that passes an indirect inference test of speci…cation will almost de…nitely also improve on VAR forecasts. Terms of use: Documents in JEL categories: E10, E17

Section: Reviewing the Evidence Of Osf Testssupporting

confidence: 89%

How Good are Out of Sample Forecasting Tests on DSGE Models?

Zhou

2015

Ital Econ J

Self Cite

“…In further work on the US, Le et al (2011) proposed a hybrid model that merged the NK and NC models by assuming that wage and price setters …nd themselves supplying labour and intermediate output partly in a competitive market with price/wage ‡exibility, and partly in a market with imperfect competition. The price and wage setting equations in the hybrid model are assumed to be a weighted average of the corresponding NK and NC equations; this is similar to including many 'Calvo sectors'of di¤erent degrees of rigidity as in Dixon and Kara (2012).…”

Section: The Sw Model Of the Us And Ea Economymentioning

confidence: 99%

“…The BGG …nancial sector produces certain changes in the model of Smets and Wouters (2007) in the form used here as modi…ed by Le et al (2011) but much remains unchanged. The key di¤erence in BGG lies in the nature of entrepreneurs.…”

Section: The Bgg Model Of the Banking Sector Together With The Sw Modelmentioning

confidence: 99%

“…They still produce intermediate goods, but now they do not rent capital from households (who do not buy capital but only buy bonds or deposits) but must buy it from capital producers and in order to buy this capital they have to borrow from a bank which converts household savings into lending; the terms of this borrowing are set by a contract governed by the costly state veri…cation set-up of Townsend (1979). On their production side, entrepreneurs face the same situation as in Le et al (2011). They hire labour from households for wages that are partly set in monopolistic, partly in competitive labour markets; and they buy capital from capital producers at prices of goods similarly set in a mixture of monopolistic and competitive goods markets.…”

Section: The Bgg Model Of the Banking Sector Together With The Sw Modelmentioning

confidence: 99%

“…The model incorporates monetary linkages that can be thought of as a form of informal policy coordination; these have been found by Hong and Minford (2012) to greatly improve the …t of the model to the data and incidentally reduce the improbable 'orthogonality'found by Le, Meenagh, Minford and Wickens (Le et al, 2010) between the US and the EA under monetary independence. We also integrate the familiar Bernanke et al (1999) banking sector model into the widely-used Smets-Wouters-style DSGE model (as adapted by Le et al, 2011) for each economy. We test the model unconditionally against the data and re-estimate it to enable it to …t as closely as possible; this is important as it ensures that the Tamas Csaba… provided research assistance for which we are grateful.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

What Causes Banking Crises? An Empirical Investigation for the World Economy

Meenagh

et al. 2013

Open Econ Rev

Self Cite

We add the Bernanke-Gertler-Gilchrist model to a world model consisting of the US, the Eurozone and the Rest of the World in order to explore the causes of the banking crisis. We test the model against linear-detrended data and reestimate it by indirect inference; the resulting model passes the Wald test only on outputs in the two countries. We then extract the model's implied residuals on un…ltered data to replicate how the model predicts the crisis. Banking shocks worsen the crisis but 'traditional' shocks explain the bulk of the crisis; the non-stationarity of the productivity shocks plays a key role. Crises occur when there is a 'run' of bad shocks; based on this sample Great Recessions occur on average once every quarter century. Financial shocks on their own, even when extreme, do not cause crises -provided the government acts swiftly to counteract such a shock as happened in this sample.

Evaluation and indirect inference estimation of inattentive features in a New Keynesian framework

Chou

Cao

2023

Journal of Forecasting

Self Cite

We test the standard New Keynesian (NK) Dynamic Stochastic General Equilibrium (DSGE) model under the condition with and without inattentive features, where inattentiveness is modelled in the form of sticky information and imperfect information data revision. All models are tested with the Indirect Inference method, and our test result based on real-time data suggests that the model with sticky information passes the test and consistently outperforms the baseline NK model with full information and rational expectation, while the model with imperfect information data revision fails to pass the test. Furthermore, we show that none of the models passes the test when Survey of Professional Forecaster data are used for model evaluation. Overall, our findings provide important implications on the modelling of expectation formation in the DSGE framework.