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This paper proposes and analyzes tests that can be used to compare the accuracy of alternative conditional density forecasts of a variable. The tests are also valid in the broader context of model selection based on out-of-sample predictive ability. We restrict attention to the case of density...
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The purpose of this paper is to compare the accuracy of the three types of models: Autoregressive Integrated Moving Average (ARIMA) models, Holt-Winters models and Neural Network Auto-Regressive (NNAR) models in forcasting the Harmonized Index of Consumer Prices (HICP) for the countries of...
Persistent link: https://www.econbiz.de/10012939069
Most economic series have been analyzed on the assumption that they are integrated of order d that is I(d), where d is an integer. Such series exhibit a short memory process characterized with exponential decay in the autocorrelation function (ACF) sometimes with alternating signs after dth...
Persistent link: https://www.econbiz.de/10013139343
In this paper, I apply univariate and vector autoregressive (VAR) models to forecast inflation in Vietnam. To investigate the forecasting performance of the models, two naive benchmark models (one is a variant of a random walk and the other is an autoregressive model) are first built based on...
Persistent link: https://www.econbiz.de/10011606109
This paper studies the comparative predictive accuracy of forecasting methods using mixed-frequency data, as applied to nowcasting Philippine inflation, real GDP growth, and other related macroeconomic variables. It focuses on variations of mixed-frequency dynamic latent factor models (DFM for...
Persistent link: https://www.econbiz.de/10014094788
This paper present a variety of approaches to estimating error-correction relationships between CPI inflation and selected commodity price indices, based on their ability to to forecast out-of-sample predictions of CPI inflation. Depending on specification, commodity prices have marginal value...
Persistent link: https://www.econbiz.de/10013403836
We first consider an extension of the generalized autoregressive conditional heteroskedasticity (GARCH) model that allows for a more flexible weighting of financial squared-returns for the filtering of volatility. The parameter for the squared-return in the GARCH model is time- varying with an...
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