Thesis (Ph. D.)--University of Missouri-Columbia, 1996. / Vita. Includes bibliographical references (leaves 538-567). Also available on the Internet.

Thesis (doctoral)--Freie Universität, Berlin, 2003.

Thesis (M.A.)--Regent University, 1999. / Includes abstract. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--Oklahoma State University, 1985. / Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 359-379).

Thesis (Ph. D.)--University of Wisconsin--Madison, 1967. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 241-254).

Thesis--Departmental honors in Political Science. / Includes bibliographical references (leaves 193-214).

Orientador: Maria Lygia Quartim de Moraes / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Filosofia e Ciencias Humanas / Made available in DSpace on 2018-08-10T14:25:27Z (GMT). No. of bitstreams: 1 Scuro-Somma_MariaLucia_M.pdf: 587497 bytes, checksum: 99a972af0d06e769d5d5f2243ee3c6ae (MD5) Previous issue date: 2008 / Resumo: O presente trabalho pretende investigar as trajetórias políticas e de vida das atuais legisladoras uruguaias. Durante o processo de pesquisa, foram realizadas entrevistas com deputadas e senadoras eleitas no período 2005-2010, no intuito de conhecer suas histórias, as dificuldades e desafios com que se depararam no sistema político uruguaio, no seu percurso até ter acesso a uma cadeira no Parlamento. O estudo parte da premissa de que não é igual o caminho percorrido por uma mulher do que o transitado por um homem quando resolve dedicar-se à carreira política. À procura dessas diferenças é que são delineadas as trajetórias dessas mulheres. O trabalho apresenta uma discussão teórica e alguns dos conceitos chaves em termos de sociologia das relações de gênero, bem como um mapa comparativo da situação do Uruguai e da região em termos de posicionamento das mulheres na esfera econômica e educativa para, posteriormente, ver as posições que elas ocupam nos cargos políticos e, mais precisamente, nos parlamentos dos países latino-americanos. A análise do discurso das parlamentares coloca três eixos centrais de discussão: a) a militância e o processo de ditadura, pelo qual, de uma ou outra maneira, essas mulheres passaram; b) o feminismo e a consciência de gênero no trabalho político; c) a conciliação entre família e política / Resumen: El presente trabajo pretende indagar en las trayectorias políticas y de vida de las actuales legisladoras uruguayas. Durante el proceso de investigación se realizaron entrevistas con diputadas y senadoras electas en el período 2005-2010, con la finalidad de conocer sus historias, las dificultades y desafíos que encontraron el en sistema político uruguayo para acceder a una banca en el Parlamento. El trabajo parte de la premisa de que no es igual el camino que recorre una mujer que el que recorre un hombre cuando decide dedicarse a la carrera política. En busca de esas diferencias es que se delinean las trayectorias de estas mujeres. El trabajo plantea una discusión teórica y algunos de los conceptos claves en términos de sociología de relaciones de género. También un mapa comparativo de la situación de Uruguay y la región en términos de posicionamiento de las mujeres en la esfera económica y educativa para luego ver las posiciones que estas ocupan en los cargos políticos y, más precisamente, en los parlamentos de los países latinoamericanos. El análisis del discurso de las parlamentarias coloca tres ejes centrales de discusión: a) la militancia y el proceso de dictadura, por el cual de una u otra manera estas mujeres pasaron; b) el feminismo y la conciencia de género en el trabajo político; c) la conciliación familia-política / Mestrado / Sociologia / Mestre em Sociologia

This research article studies the factors that are likely to affect the visible part of human resource development (HRD)– the use of HRD activities in the Legislature Sector. It is argued that the active use of HRD activities as such does not indicate the role HRD plays in a Legislature’s business: rather, one has to pay attention to HRD orientation that captures the paradigm of an organization as regards the development of people. In this empirical study of Legislature Sector, several factors related to the organization, strategy, HRD function, and HRD person are identified as meaningful predictors of HRD orientation. Results imply that the outcomes of HRD are also dependent on factors outside the traditional authority of HRD function. The model that is formed based on the results helps those involved in HRD to understand the inherent linkages and holistic nature of people development in organizations.

The first chapter explores the extent to which campaign contributions to politicians in the financial sector can influence the economic performance of the banks. In this paper, I study the relationship between campaign contribution, probability of failure and portfolio investment. I find that there is a significant effect of campaign contributions on the probability of failure and riskier investment portfolio using U.S. state banks. This effect is more pronounced for smaller and less geographically diversified banks. The results are robust for the overall risk taking measure ($Z-score$ and volatility of the return). The result is also robust using the magnitude of contributions. Using bivariate model and Blundell-Bond estimate to control for endogeneity of campaign contributions, I find that the results are robust. Using US legislative data on congressmen from congress.gov, the second chapter (co-authored with Aggey Semenov) investigates the effect of U.S. Congress legislators' non roll--call activity in bill sponsorship and co--sponsorship on campaign contributions from the financial industry. We found that bill sponsorship has positive and significant effect on campaign contributions in both Chambers. Co--sponsorship has positive and significant effect on contributions in the House but not in the Senate. We link this observation to a longer term of senators compare to congressmen; senators have more time to engage in more profitable sponsorship than congressmen. Legislators' efficiency in promoting bills to laws is rewarded by the financial industry. We also conduct robustness checks. Motivated by a large literature on the determinants of Foreign Direct Investment (FDI), the third chapter (co-authored with Roland Pongou) is assigned to understand whether a leader's longevity in office promotes FDI inflows? We answer this question with a novel dataset on the personal characteristics of African leaders covering the period from 1960 to 2011. We find that political longevity increases FDI inflows. The effect is robust to controlling for leader heterogeneity using leader fixed effects. The results remain unchanged when using plausible instrumental variables for political longevity to address possible endogeneity issues, and when estimating a dynamic model. Importantly, the effect of longevity on FDI inflows is only positive for more democratic regimes. Exploring the mechanism, we find that longevity of leaders improves the rule of laws, bureaucracy, property rights, and infrastructure, and reduces corruption. We also find that unobserved characteristics of leaders such as his ability play a role in its longevity and the improvement of institutions.

Scholars have recognized the benefits to science of Bayesian inference about the relative plausibility of competing hypotheses as opposed to, say, falsificationism in which one either rejects or fails to reject hypotheses in isolation. Yet inference about causal effects — at least as they are conceived in the potential outcomes framework (Neyman, 1923; Rubin, 1974; Holland, 1986) — has been tethered to falsificationism (Fisher, 1935; Neyman and Pearson, 1933) and difficult to integrate with Bayesian inference. One reason for this difficulty is that potential outcomes are fixed quantities that are not embedded in statistical models. Significance tests about causal hypotheses in either of the traditions traceable to Fisher (1935) or Neyman and Pearson (1933) conceive potential outcomes in this way; randomness in inferences about about causal effects stems entirely from a physical act of randomization, like flips of a coin or draws from an urn. Bayesian inferences, by contrast, typically depend on likelihood functions with model-based assumptions in which potential outcomes — to the extent that scholars invoke them — are conceived as outputs of a stochastic, data-generating model. In this dissertation, I develop Bayesian statistical inference for causal effects that incorporates the benefits of Bayesian scientific reasoning, but does not require probability models on potential outcomes that undermine the value of randomization as the “reasoned basis” for inference (Fisher, 1935, p. 14). In the first paper, I derive a randomization-based likelihood function in which Bayesian inference of causal effects is justified by the experimental design. I formally show that, under weak conditions on a prior distribution, as the number of experimental subjects increases indefinitely, the resulting sequence of posterior distributions converges in probability to the true causal effect. This result, typically known as the Bernstein-von Mises theorem, has been derived in the context of parametric models. Yet randomized experiments are especially credible precisely because they do not require such assumptions. Proving this result in the context of randomized experiments enables scholars to quantify how much they learn from experiments without sacrificing the design-based properties that make inferences from experiments especially credible in the first place. Having derived a randomization-based likelihood function in the first paper, the second paper turns to the calibration of a prior distribution for a target experiment based on past experimental results. In this paper, I show that usual methods for analyzing randomized experiments are equivalent to presuming that no prior knowledge exists, which inhibits knowledge accumulation from prior to future experiments. I therefore develop a methodology by which scholars can (1) turn results of past experiments into a prior distribution for a target experiment and (2) quantify the degree of learning in the target experiment after updating prior beliefs via a randomization-based likelihood function. I implement this methodology in an original audit experiment conducted in 2020 and show the amount of Bayesian learning that results relative to information from past experiments. Large Bayesian learning and statistical significance do not always coincide, and learning is greatest among theoretically important subgroups of legislators for which relatively less prior information exists. The accumulation of knowledge about these subgroups, specifically Black and Latino legislators, carries implications about the extent to which descriptive representation operates not only within, but also between minority groups. In the third paper, I turn away from randomized experiments toward observational studies, specifically the Difference-in-Differences (DID) design. I show that DID’s central assumption of parallel trends poses a neglected problem for causal inference: Counterfactual uncertainty, due to the inability to observe counterfactual outcomes, is hard to quantify since DID is based on parallel trends, not an as-if-randomized assumption. Hence, standard errors and ?-values are too small since they reflect only sampling uncertainty due to the inability to observe all units in a population. Recognizing this problem, scholars have recently attempted to develop inferential methods for DID under an as-if-randomized assumption. In this paper, I show that this approach is ill-suited for the most canonical DID designs and also requires conducting inference on an ill-defined estimand. I instead develop an empirical Bayes’ procedure that is able to accommodate both sampling and counterfactual uncertainty under the DIDs core identification assumption. The overall method is straightforward to implement and I apply it to a study on the effect of terrorist attacks on electoral outcomes.