Investigating how lending programs of the International Monetary Fund (IMF) affect poverty and inequality, we explicitly address model uncertainty. We control for endogenous selection into IMF programs using data on 86 low- and middle income countries for the 1982-2009 period and analyze program effects on various poverty and inequality measures. The results rely on averaging over 90 specifications of treatment effect models and indicate adverse short-run effects of IMF agreements on poverty and inequality for the whole sample, while for a 2000-2009 subsample the results are reversed. There is evidence that significant short-run effects might disappear in the long-run. (author's abstract)

This dissertation consists of three essays related to the effects of welfare reform on the intergenerational transmission of welfare participation as well as effects on labor supply and childcare arrangements. States implemented welfare reform at different times from 1992 to 1996, and these policies notably introduced work requirements and other restrictions intended to limit dependency of needy families. One mechanism reforms were intended to address was childhood exposure to a "culture" of ongoing welfare receipt. In Essay 1, I estimate the effect of reform on the transmission of welfare participation for 2961 mother-daughter pairs in the Panel Study of Income Dynamics (PSID) over the period 1968-2013. I find that a mother's welfare participation increased her daughter's odds of participation as an adult by roughly 30 percentage points, but that welfare reform attenuated this transmission by at least 50 percent, or at least 30 percent over the baseline odds of participation. While I find comparable-sized transmission patterns in daughters' adult use of the broader safety net and other outcomes such as educational attainment and income, there is no diminution of transmission after welfare reform. In Essay 2, I estimate behavioral labor supply responses to reforms using experimental data from Connecticut's Jobs First welfare waiver program in 1996. Recent studies have used a distributional analysis of Jobs First suggesting evidence that some individuals reduce hours in order to opt into welfare, an example of behavioral-induced participation. However, estimates obtained by a semi-parametric panel quantile estimator allowing women to vary arbitrarily in preferences and welfare participation costs indicate no evidence of behavioral-induced participation. These findings show that a welfare program imposes an estimated cost up to 10 percent of quarterly earnings, and these costs can be heterogeneous throughout the conditional earnings distribution. Lastly, in Essay 3, I return to PSID data to examine the relationship between welfare spending on childcare assistance and the care arrangements chosen by low-income families. Experimental evidence has shown that formal child care can result in long-term socioeconomic gains for disadvantaged children, and work requirements after welfare reform have necessitated increased demand for child care among single mothers. I find that an increase of a thousand dollars in state-level childcare assistance per child in poverty increases the probability of formal care among low-earnings single-mother families by about 27 to 30 percentage points. When public assistance makes child care more affordable, families within the target population reveal a higher preference for formal care relative to informal, which may be related to perceived quality improvements for child enrichment and development.

Indiana University-Purdue University Indianapolis (IUPUI) / The main motivation for nearly all empirical economic research is to provide scientific evidence that can be used to assess causal relationships of interest. Essential to such assessments is the rigorous specification and accurate estimation of parameters that characterize the causal relationship between a presumed causal variable of interest, whose value is to be set and altered in the context of a relevant counterfactual and a designated outcome of interest. Relationships of this type are typically characterized by an effect parameter (EP) and estimation of the EP is the objective of the empirical analysis. The present research focuses on cases in which the regression outcome of interest is a vector that has count-valued elements (i.e., the model under consideration comprises a multi-equation system of equations). This research examines the importance of account for nonlinearity and cross-equation correlations in correlated count regression systems from the perspective of causal estimation and inference. We evaluate the efficiency and accuracy gains of estimating bivariate count valued systems-of-equations models by comparing three pairs of models: (1) Zellner’s Seemingly Unrelated Regression (SUR) versus Count-Outcome SUR - Conway Maxwell Poisson (CMP); (2) CMP SUR versus Single-Equation CMP Approach; (3) CMP SUR versus Poisson SUR. We show via simulation studies that it is more efficient to estimate jointly than equation-by-equation, it is more efficient to account for nonlinearity. We also apply our model and estimation method to real-world health care utilization data, where the dependent variables are correlated counts: count of physician office-visits, and count of non-physician health professional office-visits. The presumed causal variable is private health insurance status. Our model results in a reduction of at least 30% in standard errors for key policy EP (e.g., Average Incremental Effect). Our results are enabled by our development of a Stata program for approximating two-dimensional integrals via Gauss-Legendre Quadrature.

Les Mesures agro-environnementales territorialisées (MAEt) ont été introduites en France pour la programmation 2007-2013 de la Politique Agricole Commune (PAC). La perspective de la réforme de la PAC offre l'opportunité de proposer des pistes d'amélioration de ces mesures. Cette thèse évalue dans une première partie ce dispositif MAEt avec une attention particulière portée aux enjeux de lutte contre les pollutions de l'eau d'origine agricole. Nous étudions dans le premier chapitre la décentralisation croissante du dispositif agro-environnemental, le ciblage et l'adaptation aux territoires à enjeux prioritaires. Cette analyse est illustrée par les résultats d'une enquête menée à l'échelle nationale auprès des agriculteurs éligibles et des agents responsables de la mise en œuvre des MAEt, avec deux focus sur l'Eure et Loir et le Languedoc-Roussillon. Ces analyses complémentaires nous permettent d'apporter des éléments d'explication au trop faible taux d'adoption des mesures de réduction d'intrants. Dans le deuxième chapitre nous estimons avec des méthodes économétriques d'évaluation des effets de traitement si ces mesures, basées sur une auto-sélection des participants, permettent effectivement de réduire l'utilisation d'herbicides par les viticulteurs engagés dans la région Languedoc-Roussillon. La seconde partie de la thèse propose deux dispositifs innovants qui pourraient améliorer l'acceptabilité des MAE par les agriculteurs. Nous étudions dans le chapitre 3 l'effet de l'introduction d'une dimension collective dans les contrats, par la méthode de modélisation des choix appliquée au cas des viticulteurs du Languedoc Roussillon. Cette dimension collective se concrétise par un ‘bonus' monétaire versé à chaque viticulteur engagé à condition qu'un objectif de surfaces engagées soit atteint collectivement. Pour finir, nous analysons dans le chapitre 4 la possibilité d'utiliser des appels à projets pour allouer les contrats agro-environnementaux, sur la base de l'expérience pilote menée par l'Agence de l'Eau Artois-Picardie. Ce mécanisme laisse aux agriculteurs la liberté d'adapter le cahier des charges et les montants des mesures en fonction de leur propre consentement à recevoir. / Territorialized agri-environmental measures (MAEt) were introduced in France for the 2007-2013 Common Agricultural Policy program. The forthcoming CAP reform is an opportunity to improve the design of existing agri-environmental schemes. The first part of this thesis assesses this scheme (MAEt), with special attention paid to water pollution issues. In the first chapter we analyse theadvantages and limits of the partial decentralization of decision-making in the setting-up of agrienvironmentalprojects and of improved targeting through the identification of eligible priority areas.This analysis is illustrated by the results of a national survey conducted with eligible farmers andagents in charge of the implementation of the scheme and by two case studies conducted in Eure etLoir and Languedoc-Roussillon. These surveys help us to identify the reasons for the too low adoptionrates of pesticides reduction measures by farmers. In the second chapter, we estimate the impact ofherbicide reduction measures adopted by winegrowers in the Languedoc-Roussillon region using atreatment effects approach. The second part of the thesis proposes two innovative designs aiming atincreasing the acceptability of agri-environmental measures by farmers. In chapter 3 we study theintroduction of a collective dimension in the contracts. This collective dimension relies on a monetary‘bonus’ paid to each farmer who has signed a contract, provided that the proportion of landcollectively enrolled in the agri-environmental scheme reaches a predefined threshold. We finallyanalyse in chapter 4 the possible use of reverse auctions for the allocation of agri-environmentalcontracts, on the basis of the pilot experiment implemented by the Water Agency in Artois-Picardie.This mechanism enables farmers to adapt the practices they commit to and the payment that they receive to their own willingness to accept.

Enterprise risk management (ERM) has emerged as a distinct model for managing a sophisticated portfolio of corporate risks. The purpose of this study was to determine the impact of ERM on firm value for companies on the Johannesburg Securities Exchange. The sample comprised forty-five firms from different industries over the period 2000-2016. Most studies used five or ten-year periods, using data derived from only one industry. Tobin’s Q was used as a proxy for firm value. Multivariate regression analysis was employed to determine statistical relationships. The findings indicate a significant correlation between ERM and Tobin’s Q, indicating that ERM significantly contributes to firm value. These findings may be used to develop and shape ERM policy frameworks for firms and countries. The study provides new insights, from an African emerging market context on the value effects of ERM. Larger and international samples may improve future studies. / Business Management / M. Com. (Business Management)

Cluster robust models are a kind of statistical models that attempt to estimate parameters considering potential heterogeneity in treatment effects. Absent heterogeneity in treatment effects, the partial and average treatment effect are the same. When heterogeneity in treatment effects occurs, the average treatment effect is a function of the various partial treatment effects and the composition of the population of interest. The first chapter explores the performance of common estimators as a function of the presence of heterogeneity in treatment effects and other characteristics that may influence their performance for estimating average treatment effects. The second chapter examines various approaches to evaluating and improving cluster structures as a way to obtain cluster-robust models. Both chapters are intended to be useful to practitioners as a how-to guide to examine and think about their applications and relevant factors. Empirical examples are provided to illustrate theoretical results, showcase potential tools, and communicate a suggested thought process. The third chapter relates to an open-source statistical software package for the Julia language. The content includes a description for the software functionality and technical elements. In addition, it features a critique and suggestions for statistical software development and the Julia ecosystem. These comments come from my experience throughout the development process of the package and related activities as an open-source and professional software developer. One goal of the paper is to make econometrics more accessible not only through accessibility to functionality, but understanding of the code, mathematics, and transparency in implementations.

The side-effects of chemotherapy treatment are an increasingly important research focus as more cancer patients are reaching survivorship. While treatment allows for survival, it can also lead to problems which can significantly affect quality of life. Cognitive impairments after chemotherapy treatment are one such factor. First presented as anecdotal patient reports, over the last decade empirical evidence for this cognitive concern has been obtained. Much attention has been focused on post-chemotherapy research, yet little attention has been granted to these same patients’ cognition before treatment commences. Breast cancer (BC) patients face many obstacles before chemotherapy treatment such as: surgery and side-effects of anesthesia, increased cytokine activity, stress of a new disease diagnosis and upcoming challenges, and emotional burdens such as depression and anxiety. Many of these factors have independently been shown to affect cognitive abilities in both healthy populations as well as other patient groups. Therefore, the pre-treatment (or baseline) BC patient status warrants systematic study. This would then reduce mistakenly attributing carried-over cognitive deficits to side effects of chemotherapy. As well, it is possible that certain confounding variables may have neural manifestations at baseline that could be exacerbated by chemotherapy agents. The following thesis first presents a review paper which critically describes the current literature examining chemotherapy-related cognitive impairments (CRCIs), as well as possible confound variables affecting this population. Subsequently, three original research papers present pre-chemotherapy data showing significant neuroanatomical and neurofunctional differences in BC patients compared to controls. In particular, these neural differences are present in brain regions that have been reported in post-chemotherapy papers. This, as well as the effects of variables such as the number of days since surgery, depression and anxiety scores and more, support the initiative that research attention should increase focus on these patients at baseline in order to better understand their post-chemotherapy results.

The side-effects of chemotherapy treatment are an increasingly important research focus as more cancer patients are reaching survivorship. While treatment allows for survival, it can also lead to problems which can significantly affect quality of life. Cognitive impairments after chemotherapy treatment are one such factor. First presented as anecdotal patient reports, over the last decade empirical evidence for this cognitive concern has been obtained. Much attention has been focused on post-chemotherapy research, yet little attention has been granted to these same patients’ cognition before treatment commences. Breast cancer (BC) patients face many obstacles before chemotherapy treatment such as: surgery and side-effects of anesthesia, increased cytokine activity, stress of a new disease diagnosis and upcoming challenges, and emotional burdens such as depression and anxiety. Many of these factors have independently been shown to affect cognitive abilities in both healthy populations as well as other patient groups. Therefore, the pre-treatment (or baseline) BC patient status warrants systematic study. This would then reduce mistakenly attributing carried-over cognitive deficits to side effects of chemotherapy. As well, it is possible that certain confounding variables may have neural manifestations at baseline that could be exacerbated by chemotherapy agents. The following thesis first presents a review paper which critically describes the current literature examining chemotherapy-related cognitive impairments (CRCIs), as well as possible confound variables affecting this population. Subsequently, three original research papers present pre-chemotherapy data showing significant neuroanatomical and neurofunctional differences in BC patients compared to controls. In particular, these neural differences are present in brain regions that have been reported in post-chemotherapy papers. This, as well as the effects of variables such as the number of days since surgery, depression and anxiety scores and more, support the initiative that research attention should increase focus on these patients at baseline in order to better understand their post-chemotherapy results.

Investigating how lending programs of the International Monetary Fund (IMF) affect poverty and inequality, we explicitly address model uncertainty. We control for endogenous selection into IMF programs using data on 86 low- and middle income countries for the 1982-2009 period and analyze program effects on various poverty and inequality measures. The results rely on averaging over 90 specifications of treatment effect models and indicate adverse short-run effects of IMF agreements on poverty and inequality for the whole sample, while for a 2000-2009 subsample the results are reversed. There is evidence that significant short-run effects might disappear in the long-run. (author's abstract) / Series: Department of Economics Working Paper Series

The side-effects of chemotherapy treatment are an increasingly important research focus as more cancer patients are reaching survivorship. While treatment allows for survival, it can also lead to problems which can significantly affect quality of life. Cognitive impairments after chemotherapy treatment are one such factor. First presented as anecdotal patient reports, over the last decade empirical evidence for this cognitive concern has been obtained. Much attention has been focused on post-chemotherapy research, yet little attention has been granted to these same patients’ cognition before treatment commences. Breast cancer (BC) patients face many obstacles before chemotherapy treatment such as: surgery and side-effects of anesthesia, increased cytokine activity, stress of a new disease diagnosis and upcoming challenges, and emotional burdens such as depression and anxiety. Many of these factors have independently been shown to affect cognitive abilities in both healthy populations as well as other patient groups. Therefore, the pre-treatment (or baseline) BC patient status warrants systematic study. This would then reduce mistakenly attributing carried-over cognitive deficits to side effects of chemotherapy. As well, it is possible that certain confounding variables may have neural manifestations at baseline that could be exacerbated by chemotherapy agents. The following thesis first presents a review paper which critically describes the current literature examining chemotherapy-related cognitive impairments (CRCIs), as well as possible confound variables affecting this population. Subsequently, three original research papers present pre-chemotherapy data showing significant neuroanatomical and neurofunctional differences in BC patients compared to controls. In particular, these neural differences are present in brain regions that have been reported in post-chemotherapy papers. This, as well as the effects of variables such as the number of days since surgery, depression and anxiety scores and more, support the initiative that research attention should increase focus on these patients at baseline in order to better understand their post-chemotherapy results.