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1984•RePEc: Research Papers in EconomicsOpen access

COMBINING ANNUAL ECONOMETRIC FORECASTS WITH QUARTERLY ARIMA FROECASTS: A HEURISTIC APPROACH

Gordon L. Myer, John F. Yanagida, Myer, Gordon L., Yanagida, John F.

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Abstract

Data limitations often limit the time framework in which agricultural commodities are modeled and prices forecasted. Our research provides a technique to alleviate this constraint. By combining an annual econometric model with a quarterly ARIMA model, quarterly forecasts can be made which utilize the theoretical and structural foundations in econometric modeling.

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What this paper is about

Data limitations often limit the time framework in which agricultural commodities are modeled and prices forecasted. Our research provides a technique to alleviate this constraint. By combining an annual econometric model with a quarterly ARIMA model, quarterly forecasts can be made which utilize the theoretical and structural foundations in econometric modeling.

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OpenAlex reports 14 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Data limitations often limit the time framework in which agricultural commodities are modeled and prices forecasted. Our research provides a technique to alleviate this constraint. By combining an annual econometric model with a quarterly ARIMA model, quarterly forecasts can be made which utilize the theoretical and structural foundations in econometric modeling.

Key concepts: Autoregressive integrated moving average, Econometrics, Econometric model, Economics, Constraint (computer-aided design), Computer science, Time series, Mathematics

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