No description available.

Made available in DSpace on 2014-12-17T14:34:44Z (GMT). No. of bitstreams: 1 DaniellaMC_DISSERT.pdf: 1692550 bytes, checksum: e212e3f341ea3787c7d8be0581fc73e4 (MD5) Previous issue date: 2013-02-28 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / This study aims to verify the impact of the Bolsa Fam?lia Program (BFP) in income and school attendance of poor Brazilian families. It is intended to also check the existence of a possible negative effect of the program on the labor market, titled as sloth effect. For such, microdata from the IBGE Census sample in 2010 were used. Seeking to purge possible selection biases, methodology of Quantilic Treatment Effect (QTE) was applied, in particular the estimator proposed by Firpo (2007), which assumes an exogenous and non-conditional treatment. Moreover, Foster- Greer-Thorbecke (FGT) index was calculated to check if there are fewer households below the poverty line, as well as if the inequality among the poor decreases. Human Opportunity Index (HOI) was also calculated to measure the access of young people / children education. Results showed that BFP has positively influenced the family per capita income and education (number of children aged 5-17 years old attending school). As for the labor market (worked hours and labor income), the program showed a negative effect. Thus, when compared with not benefiting families, those families who receive the BFP have: a) a higher family income (due to the shock of the transfer budget money) b) more children attending school (due to the conditionality imposed by the program); c) less worked hours (due to sloth effect in certain family groups) and d) a lower income from work. All these effects were potentiated separating the sample in the five Brazilian regions, being observed that the BFP strongly influenced the Northeast, showing a greater decrease in income inequality and poverty, and at the same time, achieved a greater negative impact on the labor market / Este estudo tem como objetivo verificar o impacto do Programa Bolsa Fam?lia (PBF) na renda e na frequ?ncia escolar das fam?lias pobres brasileiras. Pretende-se, ainda, verificar a exist?ncia de um poss?vel efeito negativo do programa no mercado de trabalho, intitulado como efeito-pregui?a. Para tanto, foi utilizado os microdados do Censo amostral do IBGE em 2010. Visando expurgar poss?veis vieses de sele??o, aplicou-se a metodologia do Efeito Quant?lico do Tratamento (EQT), em especial o estimador proposto por Firpo (2007), no qual assume um tratamento ex?geno e n?o condicional. Ademais, foi calculado o ?ndice Foster-Greer-Thorbecke (FGT) para verificar se h? menos domic?lios abaixo da linha de pobreza, bem como se a desigualdade entre os pobres diminui. Foi calculado, ainda, o ?ndice de Oportunidades Humanas (IOH) para medir o acesso de jovens/crian?as educa??o. Os resultados mostraram que o PBF influenciou positivamente a renda familiar per capita e a educa??o (n?mero de filhos de 5 a 17 anos que frequentam a escola). Quanto ao mercado de trabalho (horas trabalhadas e renda do trabalho), o programa mostrou um efeito negativo. Assim, quando comparada com as fam?lias n?o beneficiadas, aquelas fam?lias que recebem o PBF possuem: a) uma maior renda familiar (devido ao choque or?ament?rio do repasse monet?rio); b) mais filhos frequentando a escola (devido ? condicionalidade imposta pelo programa); c) menos horas trabalhadas (devido ao efeito-pregui?a em alguns grupos familiares) e; d) uma menor renda oriunda do trabalho. Todos esses efeitos foram diferenciados ao separar a amostra nas cinco regi?es brasileiras, sendo observado que o PBF influenciou mais fortemente o Nordeste e a zona rural, que mostraram um maior impacto negativo no mercado de trabalho e, ao mesmo tempo, obteve uma maior diminui??o da desigualdade de renda e pobreza

<h2><br></h2> <p>This dissertation consists of distinct but related essays that delve into the impacts of changing economic conditions and climate mitigation policies on household consumption, health, and welfare outcomes. The first essay examines the effect of variations in economic factors, such as home values, on unhealthy consumption behaviors in the U.S. The second essay examines the distributional effects and possible health advantages of climate mitigation policies in India. The findings in this dissertation have significant implications for preventive health and environmental justice policies, particularly concerning vulnerable populations. </p> <p>The first essay of this dissertation investigates the impact of home value fluctuations on household tobacco and alcohol consumption in the U.S., specifically focusing on consumption based on homeownership status. First, we utilize high-frequency household transaction panel data and ZIP code-level home values to estimate the causal effect of home value fluctuations (or the housing wealth effect) on household tobacco and alcohol consumption for all U.S. households. Second, we predict household homeownership status by supplementing our primary household panel transaction data with a secondary household survey dataset; this allowed us to estimate the housing wealth effect separately for homeowners and renters. Home values are a leading economic indicator and effectively represent variation in housing wealth, whereas prior literature mainly focuses on lagging economic indicators, such as the unemployment rate. Housing wealth is a significant component of household net worth in the U.S. We leverage temporal and geographic fluctuations in household transactions and local home values to show that changes in housing wealth have a causal effect on household tobacco and alcohol consumption. Our findings show that declining home values increase tobacco and alcohol consumption among homeowners, with no effect on renters. Beer and cigarettes mainly drive this effect. Declining home values substantially increase annual consumption of nicotine, tar, carbon monoxide, and alcohol by volume, exacerbating public health concerns. In contrast, unemployment shocks increase tobacco and alcohol consumption among homeowners and decrease it among renters. The housing wealth effect is most pronounced among bubble states households, heavy-use consumers, low-income, and white households. The study emphasizes the importance of targeted policy interventions to mitigate the negative effects of fluctuations in housing wealth on unhealthy consumption, especially amid the current unpredictable economic environment and volatile real estate market. </p> <p>The second essay of this dissertation analyzes the distributional impacts of climate mitigation policies consistent with India’s 2030 Nationally Determined Contribution and 2070 net-zero target, using a dynamic global computable general equilibrium (CGE) model with heterogeneous Indian households. Specifically, we expand the CGE model to incorporate ten rural and ten urban household income deciles. Additionally, we link the CGE model with a global atmospheric source-receptor model to derive health co-benefits from reduced premature mortality due to lower air pollution. Several policy levers are considered in this study, including carbon pricing, enhanced coal consumption tax (or coal cess), and fossil subsidies phaseout. These are further combined with five alternative revenue recycling options. Our results suggest the potential welfare costs of such mitigation policies are rather moderate and do not exceed 0.5% over 2023-2050, not accounting for health and environmental co-benefits and damages avoided by successfully limiting global temperature rise to well below 2°C. However, health co-benefits from lower air pollution can potentially outweigh the mitigation costs. Combining carbon pricing and fossil subsidy removal is more efficient than carbon pricing alone, generating progressive medium-term welfare gains due to reduced market distortions. Raising coal cess rates is the least efficient policy. Inequality and distributional impacts vary significantly based on the chosen revenue recycling approach. Equal transfer of tax revenue across households proves to be the most efficient and equitable, followed by labor tax subsidies, leading to a Gini index and S20/S80 ratio reduction of 0.01%-1.7% and 0.1%-7%, respectively. Recycling revenues to stimulate green energy investments yields the least favorable distributional impacts and worsens inequality. Trade-offs exist between reducing inequality and fostering investment-driven economic growth when choosing revenue recycling options. Policymakers should prioritize policy mixes and revenue-recycling methods based on their objectives to effectively combat climate change while promoting sustainable growth and reducing income inequality in India. </p>