The Demand for Housing: An Inverse Probability Approach
can take all the Sj and try to minimize the variance of vj via factor analysis. We could then find S and also see which Sj was most closely correlated with S. Unfortunately this technique requires that the Sj does not have common measurement error. Since none of the Sj are completely independent of all others (some common source of data is used), common error can creep in. In principle, if one data sourcebut not another -gave answers unacceptable in terms of the a priori considerations dictated by economics, we could eliminate the series. In the present instance, the only possibility would be the significance of NTW1 in the Sggc equations but not in the SOBi}B forms. The differences in cyclical behavior between series are disturbing. But none of the responses violate all saving theories especially since the more recent theoretical innovations, such as permanent income and the ratchet effect define saving to include purchases net of depreciation. Finally the relative quality of the data could be judged by a detailed examination of the primary data sources and subsequent manipulations. This cannot be done now since the last time the SEC and the OBE published detailed descriptions of their sources and manipulations was more than a decade ago and those descriptions in [3, 5] are out of date. Besides, the number of primary data sources used is quite large and diverse. Only a group of individuals familiar with the separate parts could hope to do a competent study. The conclusion, thus, is quite pessimistic. For the saving function, one of the most basic elements of macro-economics, the dynamic and cyclical characterization depends upon our choice of measurement of a given concept and we do not know which measurement is correct.
- DOI
- 10.2307/1927066
- Volume
- 50 (1)
- Pages
- 129
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