Statistical Inference in Economics in the 1920s and 1930s
回顾了20世纪20年代美国经济学家对统计推断的独特理解，他们不依赖概率论，而是通过实际预测农业产量来检验推断方法，对理解统计推断在经济学中的早期发展有参考价值。
Statistical inference is the process of drawing conclusions from samples of statistical data about things not fully described or recorded in those samples. During the 1920s, economists in the United States articulated a general approach to statistical inference that downplayed the value of the inferential measures derived from probability theory that later came to be central to the idea of statistical inference in economics. This approach is illustrated by the practices of economists of the Bureau of Economic Analysis of the US Department of Agriculture, who regularly analyzed statistical samples to forecast supplies of various agricultural products. Forecasting represents an interesting case for studying the development of inferential methods, as analysts receive regular feedback on the effectiveness of their inferences when forecasts are compared with actual events.