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Forecasting spatially dependent origin and destination commodity flows

Lesage, James P.; Llano Verduras, Carlos - In: Empirical economics : a journal of the Institute for … 47 (2014) 4, pp. 1543-1562

Persistent link: https://www.econbiz.de/10010461898

Using Bayesian Kriging for spatial smoothing of trends in non-normal yield densities

Niyibizi, Bart; Brorsen, B. Wade; Park, Eunchun - In: Agricultural finance review 82 (2022) 5, pp. 815-827

Persistent link: https://www.econbiz.de/10013428945

Parametric and nonparametric frequentist model selection and model averaging

Ullah, Aman; Wang, Huansha - In: Econometrics : open access journal 1 (2013) 2, pp. 157-179

the context of nonparametric models. In applications, estimation and inference are often conducted under the selected …

Persistent link: https://www.econbiz.de/10010237107

Forecasting the returns of cryptocurrency : a model averaging approach

Xiao, Hui; Sun, Yiguo - In: Journal of risk and financial management : JRFM 13 (2020) 11/278, pp. 1-15

This paper aims to enrich the understanding and modelling strategies for cryptocurrency markets by investigating major cryptocurrencies´ returns determinants and forecast their returns. To handle model uncertainty when modelling cryptocurrencies, we conduct model selection for an autoregressive...

Persistent link: https://www.econbiz.de/10012388749

Forecasting regional labour market developments under spatial heterogeneity and spatial autocorrelation

Longhi, Simonetta; Nijkamp, Peter - 2005

error models – to correct for misspecification due to neglected spatial autocorrelation in the data set. Our empirical … spatial structure that is required for the estimation of spatial models improves the forecasting performance of non …

Persistent link: https://www.econbiz.de/10011343272