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Bayesian mode inference for discrete distributions in economics and finance

Cross, Jamie; Hoogerheide, Lennart; Labonne, Paul; … - 2023

Detecting heterogeneity within a population is crucial in many economic and financial applications. Econometrically, this requires a credible determination of multimodality in a given data distribution. We propose a straightforward yet effective technique for mode inference in discrete data...

Persistent link: https://www.econbiz.de/10014313693

Empirical measurement of credit rationing in agriculture: a methodological survey

Petrick, Martin - 2003

-classical equilibrium theory. The fourth approach takes an intermediate position, since spill-over on segmented loan markets reveals a …

Persistent link: https://www.econbiz.de/10010299438

Comparing Risk Attitudes of Organic and Non-Organic Farmers with a Bayesian Random Coefficient Model

Gardebroek, Cornelis - 2013

farmers compared with that of conventional farmers has not been studied. Using a non-structural approach to risk estimation, a … of Dutch organic and non-organic arable farmers. The model is estimated using Gibbs sampling. The results indicate that … organic farmers are significantly less risk averse than their non-organic colleagues …

Persistent link: https://www.econbiz.de/10012753576

Bayesian Herders : Asymmetric Updating of Rainfall Beliefs in Response to External Forecasts

Lybbert, Travis J.; Barrett, Christopher B.; McPeak, John G. - 2004

Temporal climate risk weighs heavily on many of the world's poor. Model-based climate forecasts could benefit such populations, provided recipients use forecast information to update climate expectations. We test whether pastoralists in southern Ethiopia and northern Kenya update their...

Persistent link: https://www.econbiz.de/10014075990

The bayesian additive classification tree applied to credit risk modelling

Zhang, Junni L. (contributor); Härdle, Wolfgang (contributor) - 2008

We propose a new nonlinear classification method based on a Bayesian "sum-of-trees" model, the Bayesian Additive Classification Tree (BACT), which extends the Bayesian Additive Regression Tree (BART) method into the classification context. Like BART, the BACT is a Bayesian nonparametric additive...

Persistent link: https://www.econbiz.de/10003635971

Solving, estimating and selecting nonlinear dynamic models without the curse of dimensionality

Winschel, Viktor (contributor); Krätzig, Markus (contributor) - 2008

We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids. The Smolyak operator underlying the sparse grids approach frees global approximation from the curse of dimensionality and we apply it to a Chebyshev approximation of the...

Persistent link: https://www.econbiz.de/10003636133

Bayesian demographic modeling and forecasting : an application to U.S. mortality

Reichmuth, Wolfgang H. (contributor); … - 2008

We present a new way to model age-specific demographic variables with the example of age-specific mortality in the U.S., building on the Lee-Carter approach and extending it in several dimensions. We incorporate covariates and model their dynamics jointly with the latent variables underlying...

Persistent link: https://www.econbiz.de/10003770767

Modeling and forecasting age-specific mortality : a Bayesian approach

Reichmuth, Wolfgang H. (contributor); … - 2008

We present a new way to model age-specific demographic variables, using the example of age-specific mortality in the United States, building on the LeeCarter approach and extending it in several dimensions. We incorporate covariates and model their dynamics jointly with the latent variables...

Persistent link: https://www.econbiz.de/10003770768

Metropolis-Hastings prefetching algorithms

Strid, Ingvar (contributor) - 2008 - Rev. December 2, 2009

Prefetching is a simple and general method for single-chain parallelisation of the Metropolis-Hastings algorithm based on the idea of evaluating the posterior in parallel and ahead of time. Improved Metropolis-Hastings prefetching algorithms are presented and evaluated. It is shown how to use...

Persistent link: https://www.econbiz.de/10003779724

Optimal Prediction Pools

Geweke, John; Amisano, Gianni - 2009

A prediction model is any statement of a probability distribution for an outcome not yet observed. This study considers the properties of weighted linear combinations of n prediction models, or linear pools, evaluated using the conventional log predictive scoring rule. The log score is a concave...

Persistent link: https://www.econbiz.de/10003831826