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A Bayesian Approach to Inference on Probabilistic Surveys

Del Negro, Marco; Casarin, Roberto; Bassetti, Federico - 2022

We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We...

Persistent link: https://www.econbiz.de/10014080529

Sampling Properties of the Bayesian Posterior Mean With an Application to WALS Estimation

De Luca, Giuseppe - 2020

Many statistical and econometric learning methods rely on Bayesian ideas, often applied or reinterpreted in a frequentist setting. Two leading examples are shrinkage estimators and model averaging estimators, such as weighted-average least squares (WALS). In many instances, the accuracy of these...

Persistent link: https://www.econbiz.de/10012839923

Sampling properties of the Bayesian posterior mean with an application to WALS estimation

De Luca, Giuseppe; Magnus, Jan R.; Peracchi, Franco - 2020

Persistent link: https://www.econbiz.de/10012176861

Priors, Posterior Odds and Lagrange Multiplier Statistics in Bayesian Analysis of Cointegration

Kleibergen, Frank R.; Paap, Richard - 1998

Using the standard linear model as a base, a unified theory of Bayesian Analysis of Cointegration Models is constructed. This is achieved by defining (natural conjugate priors in the linear model and using the implied priors for the cointegration model

Persistent link: https://www.econbiz.de/10014069432

Chapter 1 Bayesian Forecasting

Geweke, John; Whiteman, Charles - 2006

Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach in general requires explicit formulation of a model, and conditioning on known quantities, in order to draw inferences about unknown ones. In Bayesian forecasting, one simply takes a subset of...

Persistent link: https://www.econbiz.de/10014023705

A Bayesian Beta Markov Random Field Calibration of the Term Structure of Implied Risk Neutral Densities

Casarin, Roberto - 2015

We build on Fackler and King (1990) and propose a general calibration model for implied risk neutral densities. Our model allows for the joint calibration of a set of densities at different maturities and dates. The model is a Bayesian dynamic beta Markov random field which allows for possible...

Persistent link: https://www.econbiz.de/10013031557

Inference using simulated neural moments

Creel, Michael D. - In: Econometrics : open access journal 9 (2021) 4, pp. 1-15

This paper studies method of simulated moments (MSM) estimators that are implemented using Bayesian methods, specifically Markov chain Monte Carlo (MCMC). Motivation and theory for the methods is provided by Chernozhukov and Hong (2003). The paper shows, experimentally, that confidence intervals...

Persistent link: https://www.econbiz.de/10012642418

Simulation Based Bayesian Econometric Inference : Principles and Some Recent Computational Advances

Hoogerheide, Lennart F. - 2007

In this paper we discuss several aspects of simulation based Bayesian econometric inference. We start at an elementary … level on basic concepts of Bayesian analysis; evaluating integrals by simulation methods is a crucial ingredient in Bayesian … inference. Next, the most popular and well-known simulation techniques are discussed, the Metropolis-Hastings algorithm and …

Persistent link: https://www.econbiz.de/10012729891

Simulation-Based Likelihood Inference for Limited Dependent Processes

Manrique, Aurora; Shephard, Neil G. - 1999

simulation to carry out either classical inference through a simulated score method (simulated EM algorithm) or Bayesian analysis …. The central tools we use to deal with the time series dimension of the models are the scan sampler and the simulation …

Persistent link: https://www.econbiz.de/10014197180

Efficient Bayesian Estimation and Combination of GARCH-Type Models

Ardia, David; Hoogerheide, Lennart F. - 2017

This chapter proposes an up-to-date review of estimation strategies available for the Bayesian inference of GARCH-type models. The emphasis is put on a novel efficient procedure named AdMitIS. The methodology automatically constructs a mixture of Student-t distributions as an approximation to...

Persistent link: https://www.econbiz.de/10014198683