2 Results enter search term Search Reset filter Suchfilter Content Type Publications (2) Topics Business Cycle (2) Business Cycle World (2) Behavioral Economics (1) Publication Type Journal Article (2) Research Forecasting and Business Cycle Analysis (2) Macroeconomic Research (2) Macroeconomic Policies over the Business Cycle (1) Experts Stephen Sacht (2) Tae-Seok Jang (2) Reiner Franke (1) Date Last Month Last Year Select Period start date to end date Sort by Relevance Date Aktive Filter Topics: Business Cycle Experts: Stephen Sacht Experts: Tae-Seok Jang Remove all filters Publication Animal Spirits and the Business Cycle: Empirical Evidence from Moment Matching 01.02.2016 In this article, we empirically examine a hybrid New-Keynesian model with heterogeneous bounded rational agents who may adopt an optimistic or pessimistic attitude—so called animal spirits—toward future movements of the output and inflation gap. The... Publication Moment Matching versus Bayesian Estimation: Backward-Looking Behaviour in the New-Keynesian Baseline Model 01.01.2015 The paper considers an elementary New-Keynesian three-equation model and compares its Bayesian estimation based on conventional priors to the results from the method of moments (MM), which seeks to match a finite set of the model-generated second...
Publication Animal Spirits and the Business Cycle: Empirical Evidence from Moment Matching 01.02.2016 In this article, we empirically examine a hybrid New-Keynesian model with heterogeneous bounded rational agents who may adopt an optimistic or pessimistic attitude—so called animal spirits—toward future movements of the output and inflation gap. The...
Publication Moment Matching versus Bayesian Estimation: Backward-Looking Behaviour in the New-Keynesian Baseline Model 01.01.2015 The paper considers an elementary New-Keynesian three-equation model and compares its Bayesian estimation based on conventional priors to the results from the method of moments (MM), which seeks to match a finite set of the model-generated second...