薪資的性別歧視問題, 一直是勞動經濟學者所關心的議題, 一但存在薪資上的性別歧視, 將會影響到勞動市場的有效運作。 在完全競爭的勞動市場中, 受雇於類似工作, 而且生產力類似的工人, 應得到類似的工資。 但我們發現在現實生活中, 因為性別不同而造成勞動市場普遍存在著同工不同酬的情況, 我們稱為薪資的性別歧視。 在台灣, 已經有很多實證研究利用橫斷面的資料來證實台灣的勞動市場存在著性別歧視的現象。 但是似乎較少相關文獻使用追蹤資料 ( Panel data ) 來做類似的研究, 主要原因可能是國內目前尚缺乏完整的追蹤資料庫可供使用, 因為追蹤資料的形成極耗費時間及成本。 不過, 追蹤資料的使用價值極為豐富, 除了可以得到經濟個體的跨時選擇行為的資訊, 而且使用追蹤資料可以控制個人不隨時間變動且無法被觀察到的特性。 本論文使用中央研究院調查研究專題中心所製作的台灣擬追蹤調查資料庫 ( Taiwan Quasi Longitudinal Data Archive ) 中的人力運用擬 - 追蹤調查資料庫 ( 年資料 ), 由於人力運用擬-追蹤調查資料庫的產生, 使得用追蹤資料來分析的研究變的可行, 故本論文嘗試使用此擬追蹤資料庫, 來探討薪資的性別歧視問題。 本論文透過薪資差異分解方程式, 了解不同性別之間的薪資差異中, 可解釋的部分是受到本身教育程度、工作經驗、居住地區、職業別、行業別的差異所造成, 其餘不可解釋的部分則歸因於勞動市場的性別歧視。 本論文發現台灣自1979年到2000年, 男性平均薪資所得較女性為高, 兩性薪資差異有逐漸縮小的趨勢, 但性別歧視的問題卻越來越嚴重, 且造成台灣男女薪資差異縮小的原因, 可能為男女生產力差異的縮小, 而非性別歧視的減輕。

<p>Osnovni cilj istraživanja predstavlja identifikovanje faktora<br />koji utiču na uspešnost poslovanja proizvodnih preduzeća, i to<br />korišćenjem metodologije iz oblasti analize panel podataka.<br />Kao mera uspešnosti poslovanja korišćena je profitabilnost.<br />Istraživanjem je obuhvaćena analiza uticaja nekoliko internih i<br />eksternih faktora. Utvrđen je značajan uticaj kako internih<br />(veličina preduzeća, finansijska zaduženost, efikasnost<br />korišćenja imovine i stopa opipljivosti imovine) tako i<br />eksternih (inflacija, BDP i kamatne stope) faktora na<br />uspešnost poslovanja proizvodnih preduzeća.</p> / <p>The main goal of this research is identifying factors that have an impact on<br />business success of the manufacturing companies, by using the<br />methodology of panel models analysis. Profitability is used as a measure of<br />business success. Research involves analysis of several internal and<br />external factors.<br />Significant influence of several internal (size, financial leverage, efficiency of<br />assets usage and tangibility of assets) and external factors (inflation, GDP<br />and interest rates) on business success of manufacturing companies has<br />been identified.</p>

Managers are coming under increasing pressure from a wide array of stakeholders to improve the environmental performance of their firms while still achieving financial performance objectives. One of the most researched questions in the business and the natural environment (B&NE) literature is whether it pays to be green. Despite more than three decades of research, scholars have been unable to clearly answer this question. The purpose of this dissertation was to attempt to identify the antecedents that lead to increased, firm-level environmental performance and the conditions in which firms are then able to profit from enhanced environmental performance. First, I assessed three intra-organizational factors of top management teams (i.e. female representation, concern for non-financial stakeholders, and risk-seeking propensity) that theory indicated are associated with increased corporate environmental performance (CEP). Theory also leads us to believe that top management teams with these attributes should perform better in dynamic settings, so I tested to see if industry dynamism moderates these relationships. Second, I then examined industry-level forces that theory indicates would moderate the relationship between CEP and corporate financial performance (CFP). These moderating forces include industry profitability, industry dynamism, and the degree of industry environmental regulation. Hypotheses were tested using panel data obtained from the KLD, Compustat, and Environmental Protection Agency databases for the years 2000 to 2011. The sample consists of firms comprising the Standard and Poor’s 500 and was analyzed using fixed-effect regression and moderating variables were analyzed using the Johnson-Neyman technique.

Thesis advisor: Ina V. S. Mullis / TIMSS and PIRLS assess representative samples of students at regular intervals, measuring trends in student achievement and student contexts for learning. Because individual students are not tracked over time, analysis of international large-scale assessment data is usually conducted cross-sectionally. Gustafsson (2007) proposed examining the data longitudinally by analyzing relationships between country-level trends in background constructs and trends in student achievement. Through longitudinal analysis of international large-scale assessment data, it becomes possible to mitigate some of the confounding factors in the analysis. This dissertation extends this country-level approach to subpopulations within countries. Adapting a pseudo-panel approach from the econometrics literature (Deaton, 1985), the proposed approach creates subpopulations by grouping students based on demographic characteristics, such as gender or parental education. Following grouping, the subpopulations with the same demographic characteristics are linked across cycles and the aggregated subpopulation means are treated as panel data and analyzed through longitudinal data analysis techniques. As demonstrated herein the primary advantages of the subpopulation approach are that it allows for analysis of subgroup differences, and it captures within-country relationships in the data that are not possible to analyze at country level. Illustrative analysis examines the relationship between early literacy activities and PIRLS reading achievement using PIRLS 2001 and PIRLS 2011 data. Results from the subpopulation approach are compared with student-level and country-level cross-sectional results as well as country-level longitudinal results. In addition, within-country analysis examines the subpopulation-level relationship between early literacy activities and PIRLS reading achievement, multiple group analysis compares regression coefficient estimates between boys and girls and across parental education subgroups, and mediation analysis examines the extent that partaking in early literacy activities can explain differences between boys and girls in PIRLS reading achievement. / Thesis (PhD) — Boston College, 2017. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Research, Measurement and Evaluation.

African countries have over the last few decades, experienced a thorny path towards sustained economic growth. Quite a number of researchers have opined that a major factor responsible for their stunted growth path is the prevalence of corruption in the governments of many African countries. However, a group of scholars, called revisionists, have suggested that corruption actually acts as grease in the wheel that ensures the smooth running of an economy, by providing a mechanism to evade inefficient bureaucratic procedures and allow more equitable representation of minority members of the society. With the increasing exposure of African economies to the international community, there is a need to examine the obtainable evidence in relation to corruption and economic growth in African countries. This thesis, therefore, aims to establish the nature of the relationship between corruption and economic growth in the selected African countries. The growth rate of gross domestic product per capita is used to represent the variable, economic growth. The study employs the use of panel data fixed effects and random effect estimation techniques, across 18 countries, over the period of 1997 – 2016. The results show that corruption has a positive relationship with economic growth in the selected African countries. This is in line with the grease in the wheel argument for corruption proposed by revisionists. The results also indicate that corruption has a moderately significant impact on economic growth at 10% level of significance. The literature review suggests that corruption affects economic growth directly and indirectly through mechanisms such as investment (private and public), human capital, openness, and institutional mechanisms, among others.

In a Monte Carlo analysis of meta-analytic data, Type I and Type II error rates were compared for four homogeneity tests. The study controlled for violations of normality and homogeneity of variance. This study was modeled after Harwell (1997) and Kromrey and Hogarty's (1998) experimental design. Specifically, it entailed a 2x3x3x3x3x3x2 factorial design. The study also controlled for between-studies variance, as suggested by Hedges and Vevea's (1998) study. As with similar studies, this randomized factorial design was comprised of 5000 iterations for each of the following 7 independent variables: (1) number of studies within the meta-analysis (10 and 30); (2) primary study sample size (10, 40, 200); (3) score distribution skewness and kurtosis (0/0; 1/3; 2/6);(4) equal or random (around typical sample sizes, 1:1; 4:6; and 6:4) within-group sample sizes;(5) equal or unequal group variances (1:1; 2:1; and 4:1);(6)between-studies variance, tau-squared(0, .33, and 1); and (7)between-class effect size differences, delta(0 and .8). The study incorporated 1,458 experimental conditions. Simulated data from each sample were analyzed using each of four significance test statistics including: a)the fixed-effects Q test of homogeneity; b)the random-effects modification of the Q test; c) the conditionally-random procedure; and d)permuted Qbetween. The results of this dissertation will inform researchers regarding the relative effectiveness of these statistical approaches, based on Type I and Type II error rates. This dissertation extends previous investigations of the Q test of homogneity. Specifically, permuted Q provided the greatest frequency of effectiveness across extreme conditions of increasing heterogeneity of effects, unequal group variances and nonnormality. Small numbers of studies and increasing heterogeneity of effects presented the greatest challenges to power for all of the tests under investigation.

This thesis consists of three self-contained essays about absenteeism. Essay I analyzes if the design of the insurance system affects work absence, i.e. the classic insurance problem of moral hazard. Several reforms of the sickness insurance system were implemented during the period 1991-1996. Using Negative binomial models with fixed effects, the analysis show that both workers and employers changed their behavior due to the reforms. We also find that the extent of moral hazard varies depending on work contract structures. The reforms reducing the compensation levels decreased workers’ absence, both the number of absent days and the number of absence spells. The reform in 1992, introducing sick pay paid by the employers, also decreased absence levels, which probably can be explained by changes in personnel policy such as increased use of monitoring and screening of workers. Essay II examines the background to gender differences in work absence. Women are found, as in many earlier studies, to have higher absence levels than men. Our analysis, using finite mixture models, reveals that there are a group of women, comprised of about 41% of the women in our sample, that have a high average demand of absence. Among men, the high demand group is smaller consisting of about 36% of the male sample. The absence behavior differs as much between groups within gender as it does between men and women. The access to panel data covering the period 1971-1991 enables an analysis of the increased gender gap over time. Our analysis shows that the increased gender gap can be attributed to changes in behavior rather than in observable characteristics. Essay III analyzes the difference in work absence between natives and immigrants. Immigrants are found to have higher absence than natives when measured as the number of absent days. For the number of absence spells, the pattern for immigrants and natives is about the same. The analysis, using panel data and count data models, show that natives and immigrants have different characteristics concerning family situation, work conditions and health. We also find that natives and immigrants respond differently to these characteristics. We find, for example, that the absence of natives and immigrants are differently related to both economic incentives and work environment. Finally, our analysis shows that differences in work conditions and work environment only can explain a minor part of the ethnic differences in absence during the 1980’s.

<p>Traditionally in human genetic linkage analysis, extended families were only used in the analysis of dichotomous traits, such as Disease/No Disease. For quantitative traits, analyses initially focused on data from family trios (for example, mother, father, and child) or sib-pairs. Recently however, there have been two very important developments in genetics: It became clear that if the disease status of several generations of a family is known and their genetic information is obtained, researchers can pinpoint which pieces of genetic material are linked to the disease or trait. It also became evident that if a trait is quantitative (numerical), as blood pressure or viral loads are, rather than dichotomous, one has much more power for the same sample size. This led to the&nbsp / development of statistical mixed models which could incorporate all the features of the data, including the degree of relationship between each pair of family members. This is necessary because a parent-child pair definitely shares half their genetic material, whereas a pair of cousins share, on average, only an eighth. The statistical methods involved here have however been developed by geneticists, for their specific studies, so there does not seem to be a unified and general description of the theory underlying the methods. The aim of this dissertation is to explain in a unified and statistically comprehensive manner, the theory involved in the analysis of quantitative trait genetic data from extended families. The focus is on linkage analysis: what it is and what it aims to do.&nbsp / There is a step-by-step build up to it, starting with an introduction to genetic epidemiology. This includes an explanation of the relevant genetic terminology. There is also an application section where an appropriate human genetic family dataset is analysed, illustrating the methods explained in the theory sections.</p>

The main idea of this thesis is studying the importance of the carry-over effects and interaction effects in statistical models. To investigate it, a hand-milking experiment in Burkina Faso was studied. In many no electricity access countries, such as Burkina Faso, the amount of milk and milk compositions are still highly  relying on hand-milking techniques and milkers. Moreover, the time effects also plays a important role in stockbreeding system. Therefore, falling all effects, carry-over effects and interaction effects into a linear mixed effects model, it is concluded that the carry-over effects of milker and hand-milking techniques cannot be neglected, and the interaction effects among hand-milking techniques, different milkers, days and periods can be substantial.

This paper investigates the determinants of excess returns using dividend yields as a proxy in a cross-sectional setting. First, we find that types of industry and the current business cycle are determining factors of returns. Second, our results suggest that dividend yield serves a signaling mechanism indicating “healthiness” of a firm among prospective investors. Third we see that there is a positive relationship between dividend yield and risk, especially in the utility and financial sectors. And finally, using actual excess returns, instead of dividend yield in our model shows that all predictors of dividend yield were also significant predictors of excess returns. This connection between dividend yield and excess returns support our use of dividend yield as a proxy for excess returns.