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Forecasting Short‐Run Fed Beef Supplies with Estimated Data
Author(s) -
Trapp James N.
Publication year - 1981
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.2307/1240536
Subject(s) - aggregate (composite) , series (stratigraphy) , econometric model , econometrics , time series , statistics , computer science , mathematics , paleontology , materials science , composite material , biology
Unknown aggregate data series for the placement weight, growth rate, and sex composition of cattle placed on feed are estimated. The estimates are made by treating the unknown data as time‐varying parameters of a cattle‐on‐feed growth and inventory stimulation model. A nonlinear optimization algorithm is used to estimate the unknown parameter series that optimize the model's simulation accuracy. Incorporation of the estimated series into a traditional econometric fed‐beef‐supply forecast model improved the model's forecast accuracy. The methodology used provides a general procedure for estimating unknown aggregate data using simulation models based upon microrelationships.