Some Avenues for the Improvement of Price Forecasts Generated by Macroeconometric Models

Popkin, Joel

doi:10.2307/1238486

Cited by 6 publications

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“…These two economists' suggestions and the recent effects of the macrovariables, such as the exchange rate, on the farm sector have led to an increasing awareness among economists of the importance of the performance of the agricultural sector in relation to the macroeconomy, and conversely, of the effects of macroeconomic performance on agricul ture (see for example. King, 1975;Popkin, 1975;Roop and Zeitner, 1977;Johnson, 1977;Just, 1977;Chambers, 1981;Penson and Hughes, 1979;Van Duyne, 1979;Gardner, 1981;Starleaf, 1982;and McCalla, 1982).…”

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The impacts of monetary policies on US agriculture

Devadoss

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prices, livestock product prices, crop production and demand, exports, inventories, livestock production and demand, and farm incomes. 3. To evaluate and draw policy implications from the empirical findings. The present study is organized as follows: Chapter II presents a brief review of the relevant literature and the limitations of the past studies. In Chapter III, possible macrolinkages with agriculture and the transmission mechanisms are illustrated. The theoretical model is developed in Chapter IV to capture the impact of the monetary policies on the U.S. farm sector. Chapter V presents the appropriate estimation procedure, the final estimated equations, interpretations of the results, and validation of the model. Chapter VI is devoted to dynamic simulation and policy analysis. Conclusions and implications of the study and suggestions for further research are presented in Chapter VII. CHAPTER II. REVIEW OF THE LITERATURE A large increase in U.S. agricultural exports and volatile prices and income in the early 1970s caught the attention of many agricultural economists. Some observers explained that bad weather and associated crop failures in many parts of the world in 1972, along with rapid population growth, contributed to an increase in the demand for U.S. farm products and higher prices. Several other observers have argued that expansion in the U.S. and global money supply caused inflation, which was transmitted among countries and also raised both industrial and agricultural prices. Schuh (1974) suggested that the dollar devaluation was an omitted variable in these explanations. These arguments gave impetus to research to explore possible interrelationships among the agriculture, domestic, and international economies. In this chapter, past studies on the effect of exchange rates, interest rates, inflation, monetary policies on the farm sector, and previous farm sector models dealing with macroconnections are briefly reviewed. Exchange Rates and Agricultural Commodity Trade Like most relatively new areas of research where there is not even common agreement on what are the important problems, the relationship between exchange rates and agricultural trade has been the subject of a somewhat controversial literature. Schuh (1974) was among the first to suggest, using the induced technical change model of Hayami and Ruttan, that the magnitude of the exchange rate could have important implications

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The impacts of monetary policies on US agriculture

Devadoss

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“…The forecasting performance of agricultural commodity models has been critically scrutinized by numerous specialists following the extreme agricultural commodity price fluctuations of the early and mid 1970's.^ The impact of rapidly changing raw material prices upon the entire U.S. economy has been discussed by Popkin [1975].…”

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“…It is clear that we need better predictive models of crude materials prices, and that requires improving the specifi cation of the price determination mechanism in these ^See for example Cromarty and Myers [1975], King [1975], Labys [1975], Popkin [1975], and Johnson [1977]. markets....…”

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A semi-annual econometric model of the United States feed grain-livestock economy

Shonkwiler

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The forecasting performance of agricultural commodity models has been critically evaluated following the extreme agricultural commodity price fluctuations of the early and mid 1970's. One approach to improving intermediate run forecasting models involves the use of multicommodity simultaneous systems. Of the major domestic commodities, the feed and livestock subsectors form interdependent and integral parts of the U.S. agricultural economy. A feed-livestock sectoral model was formulated to permit analysis of the predictive value of a large scale econometric system for agriculture. Review of existing agricultural sectoral models points to a reliance on complex structural relationships to portray market operations. Structural specifications typically admit nonlinearities and rely on inconsistent, curve-fitting estimators. Essentially these models have few advancements vis-a-vis the numerous individual commodity models already in existence other than the explicit simultaneity incorporated into sectoral linkages. As an alternative approach a linear, fairly simple structural specification was adopted in an effort to avoid over modeling areas of structural imprecision. The available theory to support structural specifications in such large scale models is limited due to problems of aggregation, specification and choice of sampling period. For this reason, the model was recognized as an approximation and simple linear representations were employed as opposed to those which would, for example, recognize homogeneity restrictions from firm and consumer theory. Several commodity, subsectoral, and sectoral linkages were derived using underlying economic theory. Crop price determination mechanisms which recognized the non-perishable nature of the commodity and discontinuous production process were developed. Particular attention was directed toward integrating relevant physical information into the model structure. Because of the pronounced seasonality of crop and livestock production, a semi-annual observation period was adopted. Based on equal divisions of the feed crop year, the semi-annual observation period enhanced the possibility for representing the signaling mechanism between the subsectors and allowed the specification to capture stronger linkages between the livestock and feed grain sector. Several theoretical properties of simultaneous equation techniques were discussed as a preliminary to the selection of estimation method for the model. The iterated instrumental variables (IIV) estimator was chosen for application because it remains operational even when the number of predetermined variables exceeds the number of observations. It also assures consistent estimators for the structural and reduced form parameters. In structural and reduced form comparisons the IIV method demonstrated superiority over traditional inconsistent least squares techniques. Most large scale econometric models use the ordinary least squares estimation method. Because the skeletal model developed was recognized as inherently an approximation of the complex operation of the feed livestock sector, certain forecast improvement methods were developed and analyzed. Under the topic of updating, mixed estimation, varying parameter and Kalman filtering techniques were discussed and linked as members of the generalized least squares methods family. Adaptive regression was singled out for predictive interval forecast evaluation. As a second approach to the recalibration problem several composite forecasting schemes also were developed as approaches to forecast improvement. The incorporation of specialist's information appeared particularly attractive in the limited example applications. The commodities included in the structural representation were beef, pork, broilers, eggs and milk in the livestock subsector and corn, sorghum, soybeans, and soybean meal in the crop subsector. Forecast evaluation within the sample period showed that the average weighted (by market shares) fit of the reduced form accounted for ninety percent of the variance in the prices and output levels of these commodities. Evaluation of the model's ex ante predictive accuracy during the 1978 crop year supported its validity as a useful forecasting tool. The results established indicate that the approaches investigated provide powerful alternatives to current model building procedures.

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Modeling State Agriculture: An Application and Some Implications

Onafowora

D’Souza

Colyer

1990

Northeast. j. agric. resour. econ.

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A disaggregated econometric model of the agricultural sector at the state level is constructed. Using time series data on West Virginia agriculture and three-stage least squares in estimation, the model is employed to examine how various components of the state's agricultural sector adjust to changes in certain price and nonprice variables. Results reveal characteristics of the state's agricultural economy that are both unique and useful—characteristics that are usually masked in aggregate models but that have profound implications for modeling producer decision making and policy formulation.

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Some Avenues for the Improvement of Price Forecasts Generated by Macroeconometric Models

Cited by 6 publications

References 1 publication

The impacts of monetary policies on US agriculture

The impacts of monetary policies on US agriculture

A semi-annual econometric model of the United States feed grain-livestock economy

Modeling State Agriculture: An Application and Some Implications

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