Pengaruh Kepemimpinan Kepala Sekolah, Stres Kerja dan Kompetensi Guru terhadap Kinerja Guru

This study aimed to determine the effect of school leadership, the stress ofwork and competence of teachers on teacher performance SMK inBanyuasin. So the problem is formulated in this study is there any influenceof school leadership, the stress of work and competence of teachers onteacher performance SMK in Banyuasin.The data used in this study are primary data from respondents as many as145 people Teachers SMK in Banyuasin. The analytical method used ismultiple linear regression and by testing the validity and reliability of data.Test data used to determine the characteristics of the data that is test ofnormality and linearity test. Test models used consists of multicollinearitytest and test heterokedastisitas, aided analysis tools SPSS for WindowsVersion 20.0 with a significant level of ? = 0.05.The results of multiple linear regression showed principal leadership, workstress, and teacher competence jointly have a significant influence on theperformance of teachers. Partially school leadership but very little effect onthe performance of teachers, job stress negatively affect the performanceand competence of teachers\u27 positive and significant impact on teacherperformance

Pertanggungjawaban Notaris Terhadap Keabsahan Akta Pengikatan Jual Beli Dimana Ada Pihak Yang Menggunakan Surat Kuasa Jual Yang Tidak Dilegalisasi

Land sales contract drawn up by a Notary is a sales agreement in buying and selling. The problem is that he makes a sales contract by using Sales Contract Deed with compensation in which the seller uses delegated power of attorney to sell. In its implementation, the seller uses delegated power of attorney to sell and, after it has been examined, it is only the copy of an underhanded power of attorney to sell from the land owner. The seller promises to bring the original one since it is being sent; both parties and the Notary agree to carry out the sale of the land. The Notary gives the opportunity a few days for the seller to bring the original one and to take the copy of the Sales Contract Deed with compensation which has been signed. The research used judicial normative method which is the presentation of legal provisions related to legal theories as the object of the research and the implementation of law in society related to the object of the research

Partial Idendification of Wage Effects of Training Programs

In an evaluation of a job-training program, the influence of the program on the in-dividual wages is important, because it reflects the program effect on human capital. Esti-mating these effects is complicated because we observe wages only for employed individuals, and employment is itself an outcome of the program. Only usually implausible assumptions allow identifying these treatment effects. Therefore, we suggest weaker and more credible assumptions that bound various average and quantile effects. For these bounds, consistent, nonparametric estimators are proposed. In a reevaluation of a German training program, we find that a considerable improvement of the long-run potential wages of its participants.Bounds; treatment effects; causal effects; program evaluation

Unconditional quantile treatment effects under endogeneity

This paper develops IV estimators for unconditional quantile treatment effects (QTE) when the treatment selection is endogenous. In contrast to conditional QTE, i.e. the effects conditional on a large number of covariates X, the unconditional QTE summarize the effects of a treatment for the entire population. They are usually of most interest in policy evaluations because the results can easily be conveyed and summarized. Last but not least, unconditional QTE can be estimated at pn rate without any parametric assumption, which is obviously impossible for conditional QTE (unless all X are discrete). In this paper we extend the Identification of unconditional QTE to endogenous treatments. Identification is based on a monotonicity assumption in the treatment choice equation and is achieved without any functional form restriction. Several types of estimators are proposed: regression, propensity score and weighting estimators. Root n consistency, asymptotic normality and attainment of the semiparametric efficiency bound are shown for our weighting estimator, which is extremely simple to implement. We also show that including covariates in the estimation is not only necessary for consistency when the instrumental variable is itself confounded but also for efficiency when the instrument is valid unconditionally. Monte Carlo simulations and two empirical applications illustrate the use of the proposed estimators.

Quantile Treatment Effects in the Regression Discontinuity Design: Process Results and Gini Coefficient

This paper shows nonparametric identification of quantile treatment effects (QTE) in the regression discontinuity design. The distributional impacts of social programs such as welfare, education, training programs and unemployment insurance are of large interest to economists. QTE are an intuitive tool to characterize the effects of these interventions on the outcome distribution. We propose uniformly consistent estimators for both potential outcome distributions (treated and non-treated) for the population of interest as well as other function-valued effects of the policy including in particular the QTE process. The estimators are straightforward to implement and attain the optimal rate of convergence for one-dimensional nonparametric regression. We apply the proposed estimators to estimate the effects of summer school on the distribution of school grades, complementing the results of Jacob and Lefgren (2004).quantile treatment effect, causal effect, endogeneity, regression discontinuity

Unconditional Quantile Treatment Effects under Endogeneity

This paper develops IV estimators for unconditional quantile treatment effects (QTE) when the treatment selection is endogenous. In contrast to conditional QTE, i.e. the effects conditional on a large number of covariates X, the unconditional QTE summarize the effects of a treatment for the entire population. They are usually of most interest in policy evaluations because the results can easily be conveyed and summarized. Last but not least, unconditional QTE can be estimated at √n rate without any parametric assumption, which is obviously impossible for conditional QTE (unless all X are discrete). In this paper we extend the identification of unconditional QTE to endogenous treatments. Identification is based on a monotonicity assumption in the treatment choice equation and is achieved without any functional form restriction. Several types of estimators are proposed: regression, propensity score and weighting estimators. Root n consistency, asymptotic normality and attainment of the semiparametric efficiency bound are shown for our weighting estimator, which is extremely simple to implement. We also show that including covariates in the estimation is not only necessary for consistency when the instrumental variable is itself confounded but also for efficiency when the instrument is valid unconditionally. Monte Carlo simulations and two empirical applications illustrate the use of the proposed estimators.instrumental variables, quantile treatment effects, nonparametric regression

Quantile Treatment Effects in the Regression Discontinuity Design

This paper shows nonparametric identification of quantile treatment effects (QTE) in the regression discontinuity design (RDD) and proposes simple estimators. Quantile treatment effects are a very helpful tool to characterize the effects of certain interventions on the outcome distribution. The distributional impacts of social programs such as welfare, education, training programs and unemployment insurance are of large interest to economists.quantile treatment effect, causal effect, endogeneity, regression discontinuity

Public Sector Pay Gap in France: New Evidence Using Panel Data

We estimate the public wage gap in France for the period 1990-2002, both at the mean and at different quantiles of the wage distribution, for men and women separately. We account for unobserved heterogeneity by using fixed effects estimations on panel data and, departing from usual practice, allow the public wage markup to vary over time. We also provide one of the very first applications of fixed effects quantile regressions. Contrary to common belief, results convey that monetary returns are not fundamentally different in the public sector. Firstly, public wage ‘premia’ (for women) or ‘penalties’ (for men) are essentially the result of selection. After controlling for unobserved heterogeneity, only small pay differences between sectors remain over time, reflecting fluctuations due to specific public policies and to the pro-cyclicality of private sector wages. The long-term difference is essentially zero. Secondly, the relative compression of the wage distribution by the public sector is also partly due to unobserved characteristics. The most natural explanation for these results is that the civil sector manages to attract better workers in the lower part of the distribution, in part because of non-monetary gains (including job protection), but fails to retain the most productive ones at the top.wage gap, public sector, selection, fixed effects, quantile regression

Quantile Regression in the Presence of Sample Selection

Most sample selection models assume that the errors are independent of the regressors. Under this assumption, all quantile and mean functions are parallel, which implies that quantile estimators cannot reveal any (per definition non-existing) heterogeneity. However, quantile estimators are useful for testing the independence assumption, because they are consistent under the null hypothesis. We propose tests for this crucial restriction that are based on the entire conditional quantile regression process after correcting for sample selection bias. Monte Carlo simulations demonstrate that they are powerful and two empirical illustrations indicate that violations of this assumption are likely to be ubiquitous in labor economics.Sample selection, quantile regression, independence, test

Traffic-related and socioeconomic indicators in association with low birth weight and preterm births in eastern Massachusetts between 1996 and 2002

Previous evidence has suggested that physical and social characteristics of places are important factors in determining human health. These characteristics may define gradients of exposure, and as result, they may define gradients of population health outcomes. Exposures to air pollution have been shown to affect indicators of health, for example, increasing risk of adverse birth outcomes. The present work was carried out with the main goal to study the association between indicators of city-specific gradients of traffic and socioeconomic measures and low birth weight and preterm births in eastern Massachusetts