英文文献：Can the Federal Reserve Bank’s Survey of Agricultural Credit Conditions Forecast Land Values?-联邦储备银行的农业信贷状况调查能预测土地价值吗?土地价值主导着大多数美国农业生产公司的财务结构，土地价值是长期农业规划和风险管理的重要因素
英文文献作者：Zakrzewicz, Christopher J.,Brorsen, B. Wade,Briggeman, Brian C.
英文文献摘要：
The value of land dominates the financial structure of most American agricultural production firms, and land values are an important factor in long-term agricultural planning and risk management. As the primary source of collateral for farm loans, farmland values have significant implications for both producers as well as bankers financing agricultural loans. The Federal Reserve Bank of Kansas City’s Survey of Agricultural Credit Conditions is an expert opinion survey in which agricultural bankers provide land value forecasts. As the survey has drawn increased attention, the survey has drawn criticism regarding its use qualitative data to forecast land values. Our research examines the value of the survey data with respect to its ability to forecast movement in land values. Three techniques are used in the analysis. Interpreting the aggregate forecasts as probability estimates, Brier’s probability scores are used to evaluate aggregate bankers’ predictions. Next, turning points are evaluated using contingency tables. Finally, Granger causality tests are used to determine the dynamic relationship between land value predictions and actual land value changes reported by bankers. Bankers’ forecasts predict land values for irrigated and ranchland well, but non-irrigated forecasts were only marginally helpful in prediction non-irrigated farmland values. Forecasts provided in the survey may be beneficial, especially considering the scarcity of other publicly available data.

作为农业贷款抵押品的主要来源，农田价值对生产者和为农业贷款融资的银行家都有重大影响。堪萨斯城联邦储备银行的农业信贷状况调查是一项农业银行家提供土地价值预测的专家意见调查。随着这项调查引起越来越多的关注，这项调查也引起了人们对它使用定性数据来预测土地价值的批评。我们的研究检验了调查数据在预测土地价值变动方面的价值。分析中使用了三种技术。将总体预测解释为概率估计，用Brier的概率分数来评估银行家的总体预测。接下来，使用列联表评估转折点。最后，格兰杰因果检验用于确定土地价值预测与银行家报告的实际土地价值变化之间的动态关系。银行家的预测可以很好地预测灌溉和牧场的土地价值，但非灌溉预测对预测非灌溉农田价值的帮助不大。调查中提供的预测可能是有益的，特别是考虑到其他公开数据的稀缺。