Econometric models and economic forecasts pindyck rubinfeld pdf

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econometric models and economic forecasts pindyck rubinfeld pdf

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CARE Conference: Macroeconomic Forecasting and Nowcasting

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We describe a method for quantifying the uncertainty in statistical forecasts using belief functions. This method consists in two steps. In the estimation step, uncertainty on the model parameters is described by a consonant belief function defined from the relative likelihood function. In the prediction step, parameter uncertainty is propagated through an equation linking the quantity of interest to the parameter and an auxiliary variable with known distribution. This method allows us to compute a predictive belief function that is an alternative to both prediction intervals and Bayesian posterior predictive distributions.

Halkos, George and Tsilika, Kyriaki : Stability analysis in economic dynamics: A computational approach. Modern microeconomics and macroeconomics study dynamic phenomena. Dynamics could predict future states of an economy based on its structural characteristics. Economic dynamics are modeled in discrete and continuous time context, mainly via autonomous difference and differential equations. In this study, we use Xcas and Mathematica as software tools, in order to generate results concerning the dynamic properties of the solutions of the difference and differential equation s models and determine whether an economic equilibrium exists.

Request PDF on ResearchGate | Econometric Models and Economic Forecasts / R.S. Pindyck, D.L. Rubinfeld. | Contenido: Introducción al modelo de regresión;.
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