{"title":"Evaluating USDA’s farm balance sheet forecasts","authors":"Pedro Antonio Díaz Cachay, Todd Kuethe","doi":"10.1108/afr-10-2023-0138","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>The United States Department of Agriculture Farm Balance Sheet forecasts provide important, timely information on the financial assets and debt in the U.S. farm sector. Despite their prominent role in policy and decision making, the forecasts have not been rigorously evaluated. This research examines the degree to which the USDA’s Farm Balance Forecasts are optimal predictors of subsequent official estimates.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>Following prior studies of USDA’s farm income forecasts, archived asset and debt forecasts from 1986 through 2021 are used in regression-based tests of bias and efficiency.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>Forecasts from 1986–2021 are found to be unbiased but inefficient. The forecasts have a tendency to over-react to new information early in the revision process.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>These findings can be helpful for forecast users in adjusting their expectations and for forecasters in adjusting the current forecasting methods.</p><!--/ Abstract__block -->","PeriodicalId":46748,"journal":{"name":"Agricultural Finance Review","volume":"14 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural Finance Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/afr-10-2023-0138","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRICULTURAL ECONOMICS & POLICY","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
The United States Department of Agriculture Farm Balance Sheet forecasts provide important, timely information on the financial assets and debt in the U.S. farm sector. Despite their prominent role in policy and decision making, the forecasts have not been rigorously evaluated. This research examines the degree to which the USDA’s Farm Balance Forecasts are optimal predictors of subsequent official estimates.
Design/methodology/approach
Following prior studies of USDA’s farm income forecasts, archived asset and debt forecasts from 1986 through 2021 are used in regression-based tests of bias and efficiency.
Findings
Forecasts from 1986–2021 are found to be unbiased but inefficient. The forecasts have a tendency to over-react to new information early in the revision process.
Originality/value
These findings can be helpful for forecast users in adjusting their expectations and for forecasters in adjusting the current forecasting methods.
期刊介绍：
Agricultural Finance Review provides a rigorous forum for the publication of theory and empirical work related solely to issues in agricultural and agribusiness finance. Contributions come from academic and industry experts across the world and address a wide range of topics including: Agricultural finance, Agricultural policy related to agricultural finance and risk issues, Agricultural lending and credit issues, Farm credit, Businesses and financial risks affecting agriculture and agribusiness, Agricultural policies affecting farm or agribusiness risks and profitability, Risk management strategies including the use of futures and options, Rural credit in developing economies, Microfinance and microcredit applied to agriculture and rural development, Financial efficiency, Agriculture insurance and reinsurance. Agricultural Finance Review is committed to research addressing (1) factors affecting or influencing the financing of agriculture and agribusiness in both developed and developing nations; (2) the broadest aspect of risk assessment and risk management strategies affecting agriculture; and (3) government policies affecting farm profitability, liquidity, and access to credit.
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