Competition, substitution, or discretion: an analysis of Palestinian and foreign guest workers in the Israeli labor market

This paper investigates the effects of foreign workers on labor market outcomes for Palestinian workers in the Israeli labor market. The paper utilizes a micro-dataset on the Palestinian labor force combined with time-series data on foreign workers in Israel. The data covers the period 1999–2003, a period in which Israel enforced a strict closure on labor (and goods) movement, particularly in 2001 and 2002. The evidence suggests that foreign workers in Israel do not affect Palestinian employment; however, an increase in the number of foreign workers in Israel tends to reduce Israeli wages paid to Palestinian workers from the Gaza Strip. The Israeli closure policy appears to be the main cause for the substantial reduction in long-run Palestinian employment levels in Israel, not the presence of foreign workers.     

Second order minimax estimation of the mean

In this study we consider the problem of the improvement of the sample mean in the second order minimax estimation sense for a mean belonging to an unrestricted mean parameter space R⁺${\mathbb{R}}^{+}$. We solve this problem for the class of natural exponential families (NEF's) whose variance functions (VF's) are regular at zero and at infinity. Such a class of VF's (or NEF's) is huge and contains (among others): Polynomial VF's (e.g., quadratic VF's in the Morris class, cubic VF's in the Letac&Mora class and VF's in the Hinde–Demétrio class); VF's belonging to the Tweedie class with power VF's, VF's belonging to the Babel class and many others. Moreover, we show that if the canonical parameter space of the corresponding NEF is R$\mathbb{R}$ (which is obviously the case if the support of the NEF is bounded), then the sample mean as an estimator of the mean cannot be further improved. This work presents an original constructive methodology and provides with constructive tools enabling to obtain explicit forms of the second order minimax estimators as well as the forms of the related weight functions. Our work establishes a substantial generalization of the results obtained so far in the literature. Illustrations of the resulting methods are provided and a simulation-based analysis is presented for the negative binomial case.