Comparison of Methods for Estimating Crop Yield at the County Level

County level estimates of various agricultural commodities published by USDA’s National Agricultural Statistics Service (NASS) are in heavy demand by users in government, the private sector and the academic community. In particular, accurate small area estimation of crop yields has become increasingly important over recent years. While NASS has traditionally used ratio estimation to derive yield numbers, model-based methods that make efficient use of available data sources hold the promise of significant improvement over the standard approach. Stasny, Goel and other researchers at the Ohio State University developed a Bayesian mixed-effects county yield estimation algorithm with a spatial component involving correlations among neighboring counties. Griffith (at Syracuse University) proposed an alternative method involving Box-Cox and Box-Tidwell transformations in conjunction with an autoregressive model. This report documents a simulation study where the Stasny-Goel method, Griffith method and standard ratio estimation were compared for twelve crops in ten geographically dispersed states. The Stasny-Goel method was found to be more efficient overall than either the ratio or Griffith method. The two model-based approaches and the simulation techniques used to compare them are described in some detail, followed by a discussion of results of the study. Convergence issues associated with the Stasny- Goel algorithm are also addressed, in particular the question of whether acceptable estimates can be produced in cases where the algorithm fails to converge within a preset upper limit on number of iterations

Comparison of Methods for Updating Census Based Estimates of Number of Farms to Non-Census Years

The National Agricultural Statistics Service (NASS) conducts the census of agriculture (a complete count of US farms and ranches) every five years. Sample surveys, including the June area survey (JAS), are carried out annually to obtain estimates of many of the same agricultural quantities as the census. Due to the large number of operators surveyed and the complete coverage provided by the census, its numbers are considered more accurate than those derived from the much smaller scale sample surveys. An interesting question is whether census figures for specific survey items can be used in conjunction with survey data to improve estimation accuracy for non-census years. Because of its relative stability over time, the survey item considered most likely to benefit from such an approach is number of farms in a state. Two proposed methods for projecting census counts of number of farms to subsequent non-census years are evaluated. The first method updates the census figure to the current year using JAS data only, while the second makes additional use of official NASS state level estimates of number of farms for the previous year (if it wasn’t a census year). The two methods are identical for the first post-census year. The proposed estimators are compared with area frame based and hybrid operational estimators for the years 2003-06 in a study covering most of the lower 48 states, both at the state level and within categories defined by farm value of sales. Variances are estimated using an extended delete-a-group jackknife method