Forecasting economic processes

Forecasting Economic Processes

When the assumption of constancy fails the in-sample fit of a model may be a poor guide to exante forecast performance. We exposit a number of models, methods and procedures that both illustrate the impact of structural breaks, or non-constancy, on forecast accuracy, and offer an improved forecast performance. We argue that a theory of forecasting that allows for strutural breaks is feasible, a...

Economic Forecasting *

Forecasts guide decisions in all areas of economics and finance and their value can only be understood in relation to, and in the context of, such decisions. We discuss the central role of the loss function in helping determine the forecaster’s objectives. Decision theory provides a framework for both the construction and evaluation of forecasts. This framework allows an understanding of the ch...

Advances in Economic Forecasting

Economic forecasting in agriculture

Forecasts of agricultural production and prices are intended to be useful for farmers, governments, and agribusiness industries. Because of the special position of food production in a nation’s security, governments have become both principal suppliers and main users of agricultural forecasts. They need internal forecasts to execute policies that provide technical and market support for the agr...

Forecasting Using TES Processes

Forecasting is of prime importance for accuracy in decision-making. For data sets containing high autocorrelations, failure to account for temporal dependence will result in poor forecasting. TES (Transform-Expand-Sample) is a class of stochastic processes to model empirical autocorrelated time series and is frequently used in Monte Carlo simulation. Its merit is to capture simultaneously both ...