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Alternative procedures for converting qualitative response data to quantitative expectations: An application to Australian manufacturing
Author(s) -
Smith Jeremy,
McAleer Michael
Publication year - 1995
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.3950100206
Subject(s) - econometrics , aggregate (composite) , rational expectations , mean squared error , series (stratigraphy) , orthogonality , statistics , square root , regression , computer science , mathematics , paleontology , materials science , geometry , composite material , biology
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.