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Nowcasting in Real Time Using Popularity Priors

Monokroussos, George - 2015

This paper proposes a Bayesian nowcasting approach that utilizes information coming both from large real-time data sets … and data uncertainty in real time, challenges which can be particularly relevant during turning points. It is shown, for a … good real-time nowcasts of GDP growth. …

Persistent link: https://www.econbiz.de/10015250180

Forecasting inflation in Mongolia: A dynamic model averaging approach

Doojav, Gan-Ochir; Luvsannyam, Davaajargal - 2017

set of predictors for inflation and marginal effects of predictors to change over time. Our empirical work resulted in … important role in forecasting inflation and change considerably over time and over forecast horizons. Second, among domestic …

Persistent link: https://www.econbiz.de/10015217259

Hierarchical shrinkage priors for dynamic regressions with many predictors

Korobilis, Dimitris - 2011

This paper builds on a simple unified representation of shrinkage Bayes estimators based on hierarchical Normal-Gamma priors. Various popular penalized least squares estimators for shrinkage and selection in regression models can be recovered using this single hierarchical Bayes formulation....

Persistent link: https://www.econbiz.de/10015226607

Endogenous derivation and forecast of lifetime PDs

Perederiy, Volodymyr - 2015

This paper proposes a simple technical approach for the derivation of future (forward) point-in-time PD forecasts, with …

Persistent link: https://www.econbiz.de/10015248414

Can we beat the Random Walk? The case of survey-based exchange rate forecasts in Chile

Pincheira, Pablo; Neumann, Federico - 2018

We examine the accuracy of survey-based expectations of the Chilean exchange rate relative to the US dollar. Our out-of-sample analysis reveals that survey-based forecasts outperform the Driftless Random Walk (DRW) in terms of Mean Squared Prediction Error at several forecasting horizons. This...

Persistent link: https://www.econbiz.de/10015262273

The Mean Squared Prediction Error Paradox

Pincheira, Pablo; Hardy, Nicolas - 2021

In this paper, we show that traditional comparisons of Mean Squared Prediction Error (MSPE) between two competing forecasts may be highly controversial. This is so because when some specific conditions of efficiency are not met, the forecast displaying the lowest MSPE will also display the...

Persistent link: https://www.econbiz.de/10015241474

Comparing Models of Macroeconomic Fluctuations: How Big Are the Differences?

Ghent, Andra - 2006

I generate priors for a VAR from four competing models of economic fluctuations: a standard RBC model, Fisher’s (2006) investment-specific technology shocks model, an RBC model with capital adjustment costs and habit formation, and a sticky price model with an unaccommodating monetary...

Persistent link: https://www.econbiz.de/10015218693

VAR forecasting using Bayesian variable selection

Korobilis, Dimitris - 2009

Carlo experiment, and in forecasting 4 macroeconomic series of the UK using time-varying parameters vector autoregressions …

Persistent link: https://www.econbiz.de/10015220713

High-dimensional macroeconomic forecasting using message passing algorithms

Korobilis, Dimitris - 2019

instabilities. First, it treats a regression model with time-varying coefficients, stochastic volatility and exogenous predictors … proceeds using Bayesian hierarchical priors that shrink the high-dimensional vector of coefficients either towards zero or time … time-varying parameter regressions with arbitrarily large number of exogenous predictors. In a forecasting exercise for U …

Persistent link: https://www.econbiz.de/10015265173

Les prévisions conditionnelles sont-elles plus précises que les prévisions inconditionnelles dans les projections de croissance et d’inflation en zone CEMAC ?

Ngomba Bodi, Francis Ghislain; Bikai, Landry - 2019

This study compares the predictive performance of the conditional forecasting technique against the unconditional technique. The conditional technique consist of taking into account the information available on an endogenous variable over part of the forecast horizon. We develop a Bayesian VAR...

Persistent link: https://www.econbiz.de/10015269551