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We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...
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This study estimates Climate Adjusted Total Factor Productivity (CATFP) for agriculture in Latin America and Caribbean (LAC) countries, while also providing comparisons with several regions of the world. Climatic variability is introduced in Stochastic Production Frontier (SPF) models by...
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This paper proposes a forecasting model that combines a factor augmented VAR (FAVAR) methodology with the Nelson and … variables. Our forecasting model significantly improves the predicting accuracy of extant models in the literature, particularly …
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even exclude important information. This paper develops a new underlying inflation gauge (UIG) for China which … China in modelling inflation. The paper is the first application of this type of dynamic factor model for inflation to any … information. Finally, when forecasting the headline CPI, our UIG for China outperforms traditional core measures over different …
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This paper describes a dynamic factor model for the Maltese economy. The model mainly serves as a tool to timely … product, which in turn are used as an input in the forecasting process. Such forecasts reflect and incorporate the flow of … in a synchronous way. The forecasting power of the dynamic factor model is compared with those of several other models …
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