This note gives a fairly complete statistical description of the Hodrick-Prescott Filter (1997) which has been proposed in the context of my seasonal adjustment method (Schlicht 1981, 1984). A statistics estimator for the smoothing parameter is proposed that is asymptotically equivalent to the...

Recent thinking has emphasized the importance of consistency in a firm?s compensation policy. By starting from Williamson?s ideas about idiosyncratic exchange, this view can be supplied with some theoretical foundation. At the same time, the consistency view can be applied to a number of...

It has been claimed that the market fosters selfishness and thereby undermines the moral basis of society. This thesis has been developed with an emphasis on market exchange. Everyday life is, however, predominantly shaped by interactions in the workplace rather than by shopping behaviour. This...

Consider a labour market with heterogeneous workers. Firms recruit workers by fixing a hiring standard and a wage offer simultaneously. A more demanding hiring standard necessitates a better wage offer in order to attract enough qualified applicants. As a result, an efficiency wage effect is...

This papers describes an estimator for a standard state-space model with coefficients generated by a random walk that is statistically superior to the Kalman filter as applied to this particular class of models. Two closely related estimators for the variances are introduced: A maximum...

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Offering higher wages may enable firms to attract more applicants and screen them more carefully. If firms compete in this way in the labor market, selection wages emerge. This note illustrates this wage-setting mechanism. Selection wages may engender unconventional results, such as a pre-tax...

Internal organization relies heavily on psychological consistency requirements. This thought has been emphasized in modern compensation theory, but has not been extended to organization theory. The perspective sheds new light on several topics in the theory of the firm, like the boundaries of...