[PDF] Top 20 Posterior Predictive Analysis for Evaluating DSGE Models
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Posterior Predictive Analysis for Evaluating DSGE Models
... Bayesian analysis have long criticized moment ...likelihood analysis may show, for example, that posterior odds favor DSGE model A over DSGE model ...the analysis suggested by ... See full document
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A Forecasting Metric for Evaluating DSGE Models for Policy Analysis
... the posterior predictive analysis described in Faust and Gupta ...policy analysis as being divided into two steps: first, estimating the first and second moments of the FE’s and, second, ... See full document
46
Evaluating Predictive power of Data Envelopment Analysis Technique Compared with Logit and Probit Models in Predicting Corporate Bankruptcy
... Probit models, Multiple-discriminant analysis, neural network,fuzzy logic,genetic algorithms,and etc to predict bankruptcy likelihood all of which have some strengths and ...envelopment analysis ... See full document
9
A Bayesian posterior predictive framework for weighting ensemble regional climate models
... CCCMA3.1, and CSIRO-Mk3.0) with three versions of the WRF modelling framework (which we call R1, R2, and R3, Skamarock et al., 2008) that differ in parameterisations of radiation, cumulus physics, surface physics, and ... See full document
12
Equilibrium Models of Macroeconomic Science: What to Look For in (DSGE) Models?
... a predictive model can be judged by how accurately it is able to forecast future trends which are ...dynamic. Models are by far abstract approximations of the reality; they include certain degree of ... See full document
24
Assessing quality of spatial models using the structural similarity index and posterior predictive checks
... space-time models of dynamic processes such as infectious disease or invasive species spread, utilize spatially distributed model parameters to account for spatial heterogeneity in epidemic waves ...Statistical ... See full document
37
Predictive Models in Brain Connectivity Analysis
... Evaluating the models, Linear discriminant technique had a good performance using the optimal prior, but it fell down in the cross-validation procedure going from 88.28 to 49.08 percent accuracy rate. For ... See full document
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Evaluating point and density forecasts of DSGE models
... no DSGE model continuously dominates the other models in terms of forecasting ...and predictive content of different forecasting methods is well known and surveyed in detail in Rossi ...several ... See full document
56
Bayesian Analysis of DSGE Models with Regime Switching
... subsample analysis. Although the posterior mean of the coeffi- cient under the passive regime from Lubik and Schorfheide’s (2004) estimation is below one and my estimate of the posterior mean is ... See full document
38
Survey on Financial Market Frictions and DSGE models
... Even if pre-crisis operational macroeconomic models did not have a detailed specification of the financial sector, in the related literature there were attempts to tackle this problem. The most representative ... See full document
7
Collateral Constraints in DSGE Models: Theory and Empirics
... This paper contributes to the literature on financial frictions in general equilibrium models. Notable papers that examine the effect of exogenous shocks to the ability of borrowers to obtain financing are Gertler ... See full document
108
Unravelling the Cipher of Indian Rupee’s Volatility: Testing the Forecasting Efficacy of the Rolling Symmetric and Asymmetric GARCH Models
... GARCH models to the USDINR and EURINR daily exchange rates for a period spanning April 1, 2006 through January 31, 2018, resulting in total observations of ...(1,1) models, the data window is rolled over ... See full document
30
How accounting accuracy affects DSGE models
... These hot potato effects may show how the government deficit might be ef- fective when the economy is demand-deficient, either because of self-fulfilling belief problems associated with many multiple equilibria ... See full document
13
How accounting accuracy affects DSGE models
... affects DSGE models. As many DSGE models descended from real business cycle models, I ex- plore a simple labor-only RBC model with an exogenous external sector ...introduced, ... See full document
6
Walras' Law in the steady state of DSGE models
... Courses and textbooks on this macroeconomic approach neglect the economic intuition involved in the steady state. On the one hand, some steps from the resolution of these mod- els are strongly consolidated in the ... See full document
9
DSGE models for developing economies: an application to Morocco
... According to Lubik and Schorfheide (2006), a Bayesian estimation approach has three advantages over limited information approaches. First, Bayesian estimation is system- based and uses all the information provided by the ... See full document
84
Requirements Analysis: Evaluating KAOS Models
... and right features. Numbers will be assigned to each symbol indicating the correct proposition or fact from the key list. Finally, after the existence of real arguments, the evaluation process should start. The ... See full document
6
Global Solutions to DSGE Models as a Perturbation of a Deterministic Path
... Perturbation methods are the most widely-used approach to solve nonlinear DSGE models owing to their ability to deal with medium and large-size models for reasonable computational time. Perturbations ... See full document
27
Patchwork Kriging for Large-scale Gaussian Process Regression
... The remainder of the paper is organized as follows. Section 2 briefly reviews the general GP regression problem and notational convention. Section 3 presents the core methodology of the patchwork kriging approach, ... See full document
43
Randomness, Determinism and Undecidability in the Economic cycle Theory
... The fact the Keynesian models are divided because of introducing exogenous and endogenous factors comes from Keynes´ thought. Keynes (1936) explained the cause of the economic cycles was the movement in the ... See full document
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