An econometric evaluation of the firing of a coach on team performance

Firing the manager is a drastic measure employed by firms to deal with poor performance.However,data on within firm dynamics are scarce,and the firing of individual managers is rarely recorded in the firm level data currently available.This makes the val e of firing a manager difficult to assess. Data on sports offer a unique opportunity to study this phenomenon beca se the firing of a coach is usually well-publicized.Using data on soccer, the author evaluates the effect of the firing of a coach on team performance.As teams do not face the same opponents before and after a coach is fired, the issue of sample selectivity is addressed.

Testing the normality assumption in the sample selection model with an application to travel demand

In this paper we introduce a test for the normality assumption in the sample selection model.The test is based on a generalization of a semi-nonparametric maximum likelihood method.In this estimation method,the distribution of the error erms is approximated by a Hermite series,with normality as a special case.Because all parameters of the model are estimated both under normality and in the more general specification,we can est for normality using the likeli- hood ratio approach.This est has reasonable power as is shown by a simulation study.Finally,we apply the generalized semi-nonparametric maximum likeli- hood estimation method and the normality est o a model of car ownership and car use.The assumption of normal distributed error erms is rejected and we provide estimates of the sample selection model that are consisten .

Testing the normality assumption in the sample selection model with an application to travel demand

In this paper we introduce a test for the normality assumption in the sample selection model.The test is based on a generalization of a semi-nonparametric maximum likelihood method.In this estimation method,the distribution of the error erms is approximated by a Hermite series,with normality as a special case.Because all parameters of the model are estimated both under normality and in the more general specification,we can est for normality using the likeli- hood ratio approach.This est has reasonable power as is shown by a simulation study.Finally,we apply the generalized semi-nonparametric maximum likeli- hood estimation method and the normality est o a model of car ownership and car use.The assumption of normal distributed error erms is rejected and we provide estimates of the sample selection model that are consisten

Cosmic Rays during BBN as Origin of Lithium Problem

There may be non-thermal cosmic rays during big-bang nucleosynthesis (BBN) epoch (dubbed as BBNCRs). This paper investigated whether such BBNCRs can be the origin of Lithium problem or not. It can be expected that BBNCRs flux will be small in order to keep the success of standard BBN (SBBN). With favorable assumptions on the BBNCR spectrum between 0.09 -- 4 MeV, our numerical calculation showed that extra contributions from BBNCRs can account for the $^7$Li abundance successfully. However $^6$Li abundance is only lifted an order of magnitude, which is still much lower than the observed value. As the deuteron abundance is very sensitive to the spectrum choice of BBNCRs, the allowed parameter space for the spectrum is strictly constrained. We should emphasize that the acceleration mechanism for BBNCRs in the early universe is still an open question. For example, strong turbulent magnetic field is probably the solution to the problem. Whether such a mechanism can provide the required spectrum deserves further studies.Comment: 34 pages, 21 figures, published versio