Improving Crop Estimates by Integrating Multiple Data Sources (2017) / Chapter Skim
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1 Introduction
1 Introduction
Pages 5-16
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From page 5... ...
The challenge of integrating multiple data sources to improve crop estimates needs to be accomplished in a way that brings NASS into conformance with the statistical standards promulgated by the 1 See https://www.nass.usda.gov/About_NASS/index.php [July 11, 2017]
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From page 6... ...
Multiple sources of data are potentially available for county-level crop estimates, including NASS surveys, data from other agencies, and automated field-level information collected by farm equipment dealers. The panel will explore methods for combining the information from these and other sources to produce more precise county-level estimates with valid measures of uncertainty.
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From page 7... ...
Complementing the data on agricultural production, NASS has long estimated rental rates for farmland at the state level. Between 1950 and 1994, state-level cash rents were estimated using a list survey of real estate appraisers.
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In 2009, FSA began using results from the NASS statistical survey of county average rental rates for cropland and pastureland to establish the rental rates used for the CRP. Federally subsidized crop insurance programs, such as the ARC-CO and group risk options, use NASS county yields in setting the guaranteed yield levels for policies based on outcomes in a farmer's county (as opposed to the farmer's personal experience)
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From page 9... ...
, "In the event that there is neither a NASS county estimate nor enough data to estimate an RMA county yield, the FSA State Committee will determine the county yield using best available data, including such possibilities as the NASS or RMA yield for a neighboring county, the NASS district yield estimate, or 70 percent of the transitional yield (or t-yield)
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From page 10... ...
Figure 1-1c indicates the significance of ARC-CO payments when they are added to market revenue, showing that revenue in many of those Upper Plains counties subsequently topped historical averages. The Congressional Research Service has noted "wide discrepancies" in the yield estimates8 for adjacent counties, some with and some without NASS estimates, which presumably only exacerbated producers' concerns about the credibility of the estimates used to calculate ARC-CO payments (Congressional Research Service, 2017)
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From page 11... ...
Less than 70% Revenue 70% - 80% Below Historic 80% - 90% Average 90% - 100% 100% Revenue at or 100% - 125% Above Historic Average Over 125% No Data FIGURE 1-1b 2015 crop wheat revenue without Agricultural Risk Coverage-County Option safety net. SOURCE: Understanding Agricultural Risk Coverage/Price Loss Coverage, Farm Service Agency, U.S.
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From page 12... ...
The federal statisticians consider direct survey results and their associated quality measures, as well as a range of additional information, including data from previous surveys and censuses, and, when appropriate, administrative data collected from farmers by FSA and RMA, remote sensing data on crop production, and estimates from statistical models. For the cash rents estimates, separate "indications"9 are drawn from the Cash Rents Survey, past surveys and censuses, and a model that combines 2 years of data from the Cash Rents Survey with information on relevant crop condition and agronomic factors.
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From page 13... ...
Likewise, increases in the sophistication and capabilities of farm machinery have made it possible to gather field-level data on input application and crop output, which are examples of measurements used in precision agriculture, a crop management approach utilizing data from GPS systems and sensors on such equipment as tractors and combine harvesters. Both remotely sensed and ground observations can enhance analysts' ability to monitor, predict, and measure crop conditions and outputs.
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From page 14... ...
This vision is motivated by the imperatives for a modern statistical agency to be responsive to its data users, to adopt the most robust technologies for data management, and to utilize nontraditional data sources and statistical methods. Chapter 3 describes the multiple data sources that are available to enhance NASS's county-level estimates of planted acres, harvested acres, production, and yield by commodity; describes how these sources are currently used; and suggests improvements for the future.
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From page 15... ...
The report also includes four appendixes. Appendix A describes the survey methodology of the Cash Rents Survey and the CAPS.
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