Education-Occupation Mismatch and the Effect on Wages of Egyptian Workers

This study attempts to fill a void in the literature by examining education-occupation mismatches in Egypt. Using the Egypt Labor Market Panel Survey (ELMPS) 2006 and Egypt Labor Market Survey (ELMS) 1998, this paper investigates whether the empirical evidences of studies on over-education and under-education carry over to the private sector of the Egyptian labor market; evaluates the incidence and magnitude of the education-occupation mismatch by gender and by occupational categories; and determines whether the incidence of educational mismatches has increased over time. The main findings are as follows: there is evidence of an education-occupation mismatch in the Egyptian private sector. The incidence has declined from 51% to 42% during the eight year period, and males are more likely to be mismatched than females. The Egyptian labor market has witnessed a drop in the percentage of overeducated workers at the expense of an expansion in the share of under-educated workers. Empirical findings do not support the main stream literature. Returns to over-education for white collar and blue collar males are higher than those of adequately educated males and are greater in 2006 than in 1998. Females in white collar jobs, both over and undereducated, received higher returns than adequately educated females in 1998, but returns to over-education were higher and returns to under-education were lower than adequate education in 2006. Females in blue collar jobs are being penalized if they are inadequately matched, especially in 2006, and are rewarded less than males. These findings support the job competition model in a labor market with an imperfect information system whereby employers use education as an indicator of the cost of investing in job training. Workers, on the other hand, may accept these jobs while competing for a job

Does Wealth Influence Women’s Labor Participation Decision?: Evidence from Egypt

This study examines the behavior of labor supply of women at different levels of household wealth status. It is widely demonstrated in the literature that variables such as age and level of education, as well as the demographic, social, and financial characteristics of the household influence deciding to join the labor market. However, this study argues that these determinants work differently according to the level or the well-being of the household, adding another to the literature on women’s labor supply in MENA

On Low-rank Trace Regression under General Sampling Distribution

A growing number of modern statistical learning problems involve estimating a large number of parameters from a (smaller) number of noisy observations. In a subset of these problems (matrix completion, matrix compressed sensing, and multi-task learning) the unknown parameters form a high-dimensional matrix B*, and two popular approaches for the estimation are convex relaxation of rank-penalized regression or non-convex optimization. It is also known that these estimators satisfy near optimal error bounds under assumptions on rank, coherence, or spikiness of the unknown matrix. In this paper, we introduce a unifying technique for analyzing all of these problems via both estimators that leads to short proofs for the existing results as well as new results. Specifically, first we introduce a general notion of spikiness for B* and consider a general family of estimators and prove non-asymptotic error bounds for the their estimation error. Our approach relies on a generic recipe to prove restricted strong convexity for the sampling operator of the trace regression. Second, and most notably, we prove similar error bounds when the regularization parameter is chosen via K-fold cross-validation. This result is significant in that existing theory on cross-validated estimators do not apply to our setting since our estimators are not known to satisfy their required notion of stability. Third, we study applications of our general results to four subproblems of (1) matrix completion, (2) multi-task learning, (3) compressed sensing with Gaussian ensembles, and (4) compressed sensing with factored measurements. For (1), (3), and (4) we recover matching error bounds as those found in the literature, and for (2) we obtain (to the best of our knowledge) the first such error bound. We also demonstrate how our frameworks applies to the exact recovery problem in (3) and (4).Comment: 32 pages, 1 figur

On local compactness in quasilinear elliptic problems

One of the major difficulties in nonlinear elliptic problems involving critical nonlinearities is the compactness of Palais-Smale sequences. In their celebrated work \cite{BN}, Br\'ezis and Nirenberg introduced the notion of critical level for these sequences in the case of a critical perturbation of the Laplacian homogeneous eigenvalue problem. In this paper, we give a natural and general formula of the critical level for a large class of nonlinear elliptic critical problems. The sharpness of our formula is established by the construction of suitable Palais-Smale sequences which are not relatively compact

HAVE ECONOMIC REFORMS PAID-OFF? GENDER OCCUPATIONAL INEQUALITY IN THE NEW MILLENNIUM IN EGYPT

This study considers the impact of over a decade of structural adjustment policies in Egypt on gender wage and occupational inequality. Using newly released Labor Force Sample Surveys (LFSS) for the years 2000-2004, a slight drop in public sector employment and a comparable increase in private sector employment for women is observed. Regardless of sector of employment, women still earn less than men, with private sector workers being the worst. Wage discrimination in the private sector in favor of men is evident at three groups of occupations: white collars, blue collars and professionals. Results also indicate occupational segregation and crowding of women in specific job types is a more serious issue in pay differences for blue collars in recent years, while pure discrimination is dictating wage differentials for professionals and white collars. Elements of productivity in terms of human capital endowments are not directly responsible for wage inequality in the private sector. Despite having less education, men receive higher wages for their comparative advantage in years of experience. Contrary to years of education, experience, as a factor endowment and a proxy for productivity, is highly valued and compensated for in favor of men