Alternative procedures for converting qualitative response data to quantitative expectations: An application to Australian manufacturing
分析并扩展了将定性预期响应转换为定量预期的多种方法，包括概率模型和回归方法，发现预期模型在预测误差和转折点检测上优于简单时间序列模型，并检验了理性预期假设。
Abstract This paper analyses and extends alternative procedures for converting qualitative expectations responses to quantitative expectations. A number of conversion procedures is investigated, including the probability model, the time‐varying parameter probability model, and the regression approach. The informational content of the survey expectations is compared with simple time series models. It is found that the expectations models are superior for many series, both in terms of producing lower forecast root mean square error (RMSE) values and in detecting turning points in the actual data. Survey expectations are also tested for rational expectations in aggregate using the orthogonality test.