Abstract

Agricultural markets, compared to other sectors, are typically characterized by uncertainty and high price fluctuations. High price volatility in livestock markets leads to inefficient resource allocation and production planning. Expert price forecasts are not always affordable for all market players, so readily available public forecasts have risen in popularity. This study uses accuracy-based testing methods to evaluate the accuracy of the United States Department of Agriculture (USDA) livestock price forecasting by utilizing the World Agricultural Supply and Demand Estimates (WASDE) quarterly data for slaughter cattle, hogs, and broilers. The study also employs a vector error correction (VEC) model to compare USDA price forecasts. Results suggest that the USDA forecast was more accurate than the competing VEC model across three sectors, suggested by low RMSE and MAE. The beta efficiency test results showed that USDA price forecasts were efficient for all three price series, whereas VEC forecasts were biased for hogs and broiler prices. The findings of the study also confirm that USDA price forecasts are biased for cattle prices with a tendency to repeat past forecast error in all three markets. Results from the forecast encompassing tests showed that USDA cattle and broiler forecasts captured the information contained in VEC forecasts. However, because the hog prices did not show any improvement over time, there is room for improvement of the USDA price forecasts. Overall, results suggest that USDA price forecasts for slaughter cattle, hogs and broilers provide useful information to the market. However, the results also indicate that USDA price forecasts reduce forecast error by economically significant levels.

Highlights

  • Agricultural commodity prices are the key determinants of cost, revenue, and profitability of large- and small-scale agricultural operations, meaning agricultural price forecasts are vital for farmers, policymakers, and agricultural industries (Jha and Sinha, 2013)

  • A high variation in cattle prices was observed between the United States Department of Agriculture (USDA) forecast and the vector error correction (VEC) forecast, accounting for approximately 27% of the standard deviation in actual prices

  • Test results showed that the forecasting errors of the USDA forecast were statistically smaller than the errors of the VEC model

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Summary

Introduction

Agricultural commodity prices are the key determinants of cost, revenue, and profitability of large- and small-scale agricultural operations, meaning agricultural price forecasts are vital for farmers, policymakers, and agricultural industries (Jha and Sinha, 2013). Price forecasting captures the attention of market participants because future market for commodities and contract maturity dates relies on expert forecast information (Brandt and Bessler, 1991). The purpose of agricultural price forecasting is to increase social welfare through resource allocation (Brorsen and Irwin, 1996), the uncertainty of future prices and production can adversely affect the agricultural market by changing market strategies and investment planning (Brandt and Bessler, 1983), resulting in resource misallocation (Sanders and Manfredo, 2003). Agricultural producers who do not have resources or expertise in forecasting can use these public forecasts to make production and planning decisions, meaning social welfare of agricultural producers’ increases due to forward-looking forecasts rather than naïve forecasts (Brorsen and Irwin, 1996)

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