Made available in DSpace on 2017-07-10T18:15:07Z (GMT). No. of bitstreams: 1 Fagner M Avelar.pdf: 1643779 bytes, checksum: a893f92463d6ccd952c7698632d7b714 (MD5) Previous issue date: 2016-11-30 / The present study aimed to analyze the dynamics and effects of the National Program for Strengthening Family Agriculture (PRONAF) in the western region of Paraná. Currently, policies directed to the agricultural sector have two approaches: on the one hand, the strengthening of the competitiveness of business agriculture, focused on the external sector, and on the other, the strengthening of family agriculture in order to contribute to the generation of employment and income in rural areas And urban areas. To evaluate the effects of PRONAF, the Panel Data Model was used in view of its superiority in relation to the Cross-Section and Pure Time Series. It was verified that the PRONAF is a sectorial policy capable of generating positive effects both in the growth of the product and in the generation of income, employment and tax revenue of the region. Through a better orientation of the agents involved, policies such as PRONAF can help in the development of regions with characteristics similar to those studied. / A presente pesquisa objetivou analisar a dinâmica e os efeitos do Programa Nacional de Fortalecimento da Agricultura Familiar (PRONAF) na região Oeste do Paraná. Atualmente a políticas direcionadas ao setor agropecuário tem dois enfoques: de um lado o fortalecimento da competitividade da agricultura empresarial, voltada para o setor externo, e de outro o fortalecimento da agricultura familiar de forma a contribuir para a geração de emprego e renda nas áreas rurais e urbanas. Para avaliar os efeitos do PRONAF utilizou-se do Modelo de dados em painel tendo em vista sua superioridade em relação à Seção-Cruzada e Series Temporais puras. Verificou-se que o PRONAF é uma política setorial capaz de gerar efeitos positivos tanto no crescimento do produto quanto na geração de renda, emprego e receita tributária da região. Através de uma melhor orientação dos agentes envolvidos, políticas como o PRONAF, podem auxiliar no desenvolvimento de regiões com características semelhantes á estudada.

Ao longo dos anos, desde a concepção do CAPM, o modelo vem passando por um rigoroso escrutínio por parte da comunidade científica e dos agentes de mercado interessados na sua utilização prática. Evidências tanto a favor quanto contra a sua adequação foram surgindo. Várias foram as causas levantadas para o fraco desempenho do CAPM: omissão de variáveis no modelo, variação no tempo da medida de risco (β) ou, ainda, a ausência de outros momentos tais como assimetria e curtose. Esta pesquisa teve como objetivo a investigação empírica da relação entre momentos sistêmicos (covariância, coassimetria e cocurtose) e a taxa de retorno de ativos financeiros negociados no mercado brasileiro. Foi utilizada uma amostra de 179 empresas brasileiras regularmente negociadas na Bovespa entre os anos de 2003 e 2007. Para o teste do modelo de apreçamento, foi utilizado um procedimento em duas etapas. Na primeira, os comomentos de cada ativo foram estimados usando-se dados longitudinais de taxas de retorno. Os coeficientes estimados foram, então, utilizados em uma segunda etapa, na qual uma regressão com dados em painel buscou determinar a relação entre o prêmio pelo risco dos ativos e os comomentos estimados na primeira etapa. Foram estimados modelos com dados agrupados, efeitos aleatórios e efeitos fixos. A determinação do modelo mais adequado foi feita por meio de testes de especificação. Os dados mostraram evidências de que a distribuição de probabilidade das taxas de retorno da maioria das empresas não segue uma distribuição normal, e que tanto a covariância como a cocurtose são fatores de risco relevantes em modelos de apreçamento, mesmo controlados por fatores como: tamanho, alavancagem, liquidez, relação entre preço de mercado e preço contábil e relação entre valor de mercado e valor contábil. / Since the development of the CAPM, the model has been tested with a rigorous scrutiny by academic community and market practitioners who are interested in its practical utilization. Evidence for and against the adequacy of the model has arisen. Various reasons for the failure of the CAPM were raised: omission of variables, time-varying risk factors (β), or the absence of other moments like skewness and kurtosis. This research aimed at empirical investigation of the relationship between systematic moments (covariance, coskewness and cokurtosis) and the rate of return of financial assets traded in the Brazilian market. The sample consisted of 179 stocks regularly traded at Bovespa from 2003 to 2007. The test of the pricing model was run in a two-pass procedure. In the first pass, the comoments for every stock were estimated using a longitudinal series of rates of returns. The estimated coeficients were then used in the second pass, in a panel data regression that intended to establish a relationship between the risk premium and the comoments estimated in the first pass. Panel data models with pooled data, random effects and fixed effects were estimated. The adequacy of each model was tested by specification procedures. Data showed evidence that the rates of return were not normally distributed, and that covariance and cokurtosis were significant risk factors in pricing models, even after controlling for factors like: size, leverage, liquidity, price-earning ratio and

Na teoria clássica de finanças, o sentimento do investidor não é considerado um fator importante sobre os preços das ações. Embora a existência do sentimento do investidor não seja negada, as teorias normalmente partem do princípio de que, em mercados financeiros competitivos, comportamentos de agentes quase-racionais são rapidamente eliminados. Esta tese tem o objetivo de investigar a relação entre o sentimento de mercado e as taxas de retorno futuras das ações. É proposta uma metodologia para a criação de um índice de sentimento específico para o mercado brasileiro com uso da análise de componentes principais. Com o objetivo de verificar a relação deste índice de sentimento com as taxas de retorno das ações, foi estimado um modelo de apreçamento em que esta variável foi incluída, para o período de 1999 a 2008. A amostra foi composta por empresas não-financeiras com ações listadas na BOVESPA, com uma negociabilidade mínima que garantisse observações suficientes e representativas para validar os resultados encontrados na pesquisa. O modelo de apreçamento foi estimado por GMM, levando em consideração o índice de sentimento de mercado, o risco sistêmico das empresas (medido pelo beta) e fatores como tamanho, índice market-to-book, alavancagem, momentum e crescimento da receita. Empregaram-se diferentes procedimentos para estimar os parâmetros dos modelos empíricos formulados, com o propósito de isolar influências espúrias, ocasionadas pela presença de heterogeneidade não-observada, pela existência de eventuais observações extremas ou mesmo pela possível endogeneidade dos regressores. Os resultados deste estudo empírico sugerem que o sentimento é um fator relevante no apreçamento das ações no mercado brasileiro. A relação negativa e significante entre o índice de sentimento e as taxas de retorno, encontrada consistentemente em diferentes modelos, indica um padrão de reversão nas taxas de retornos, ou seja, após um período de sentimento positivo, o impacto nas taxas de retorno no período seguinte é negativo, e vice-versa. / In classical finance theory investor sentiment is not considered an important factor in asset pricing. Although the existence of investor sentiment is not denied, theories assume that in competitive markets quasi-rational behavior is quickly offset by rational agents. The main goal of this thesis is to investigate the relationship between investor sentiment and future stock return rates. It is proposed a methodology to create a sentiment index specifically to the Brazilian market using principal components analysis. In order to analyze the relationship between this sentiment index and the future stock returns, it was estimated a pricing model including this variable for the period comprehending 1999 to 2008. Considering a negotiability restriction to assure representative and sufficient observations to validate a pricing model, the sample consisted of non-financial firms listed at BOVESPA. The pricing model was estimated by GMM considering the sentiment index, systematic risk (market beta) and factors as firm size, market-to-book ratio, leverage and return predictability measured by momentum or income growth. Different estimation procedures were applied to find empirical models coefficients which are less affected by spurious influence such as unobserved heterogeneity, outliers or possible regressors endogeneity. Results of the empirical study suggest that sentiment is a relevant factor in Brazilian asset pricing models. A negative and statistically significant relationship between the sentiment index and stock returns was consistently found in different models specifications. These findings suggest the existence of a reversion pattern in stock returns, meaning that after a positive sentiment period, the impact on subsequent stock returns is negative and vice-versa.

This paper investigates the impact of knowledge capital stocks on total factor productivity through the lens of the knowledge capital model proposed by Griliches (1979), augmented with a spatially discounted cross-region knowledge spillover pool variable. The objective is to shift attention from firms and industries to regions and to estimate the impact of cross-region knowledge spillovers on total factor productivity (TFP) in Europe. The dependent variable is the region-level TFP, measured in terms of the superlative TFP index suggested by Caves, Christensen and Diewert (1982). This index describes how efficiently each region transforms physical capital and labour into output. The explanatory variables are internal and out-of-region stocks of knowledge, the latter capturing the contribution of cross-region knowledge spillovers. We construct patent stocks to proxy regional knowledge capital stocks for N=203 regions over the 1997- 2002 time period. In estimating the effects we implement a spatial panel data model that controls for the spatial autocorrelation due to neighbouring regions and the individual heterogeneity across regions. The findings provide a fairly remarkable confirmation of the role of knowledge capital contributing to productivity differences among regions, and add an important spatial dimension to the discussion, by showing that productivity effects of knowledge spillovers increase with geographic proximity. (authors' abstract)

In recent years there were many debates and different opinions whether R&D spillover effects exist or not. In 1995 Coe and Helpman published a study about this phenomenon, based on a panel dataset, that supports the position that such R&D spillover effects are existent. However, this survey was criticized and many different suggestions for improvement came from the scientific community. Some of them were selected and analysed and finally led to a new model. And even though this new model is well compatible with the data, it leads to different conclusions, namely that there does not exist an R&D spillover effect. These different results were the motivation to run a spatial analysis, which can be done by considering the countries as regions and using an adequate spatial link matrix. The used methods from the field of spatial econometrics are described briefly and quite general, and finally the results from the spatial models (the ones which correspond to the non-spatial ones) are compared with the results from the non-spatial analysis. The preferred model supports the position that R&D spillover effects exist.

The literature addressing the resource curse has been extensive. Many studies have put forth theories to explain the curse, but these theories are often refuted by new studies. Recently, there has been a theory that natural resource abundance leads to decreased economic freedom, which causes slower economic growth. Many of these studies have using frequentist testing to arrive at their conclusions. Although frequentist testing is widely used, there are several drawbacks. In particular, there is no way of addressing model uncertainty. Unless a study is able to incorporate every significant explanatory variable, the results will suffer from omitted variable bias. Recently, researchers have been applying Bayesian statistics to address the problem of model uncertainty. In this study, we apply Bayesian Model Averaging (BMA) to build a growth model, and see if natural resources have a negative effect on growth. We take the implementation of BMA a step further to see if there is an indirect negative effect of natural resources on economic freedom. However, contrary to previous studies, we were not able to find a negative relationship between resource abundance and economic freedom.

Using static and dynamic panel data analysis, we examine how interest rates influenced equity prices of European banks and insurance companies between 2006 and 2015. Identification and quantification of effects of the low yield environment, which is a consequence of decreasing interest rates, are crucial for regulators and policy makers. Our static and dynamic models show that decreasing short-term interest rates had a negative impact both on banks and insurers. In this thesis, dynamic models are estimated by means of the Blundell- Bond system GMM estimator and we consider their results superior to the results of static models because all underlying assumptions of the dynamic models are met here. Results obtained by employing the Blundell-Bond system GMM estimator suggest that life insurers were effected more than banks, while banks were effected more than non-life insurers. In case of a 1 percentage point decrease in short-term interest rates, equity prices of life insurers are estimated to decrease on average by 18 %, equity prices of banks by 8 %, and equity prices of non-life insurers by 3 %. JEL Classification C33, C36, C61, E44, G21, G22 Keywords interest rates, equity prices, static panel analy­ sis, dynamic panel analysis, system GMM esti­ mator Author's e-mail jurena.filip.l@ gm ail.com...

The aim of this thesis is to investigate stock price sensitivity of 50 European companies to oil price changes using panel data analysis. Besides that, this Thesis compares sensitivities of different groups of companies. The first comparison is between Eastern and Western European companies. The second comparison is between different segments of the oil industry. Specifically, Upstream, Midstream, Downstream segment and integrated oil companies. The main finding of this thesis is that there is a positive dependence between oil price and stock prices of European oil companies. Moreover, there is a significant difference between sensitivity of Upstream and integrated companies. However, no significant difference in sensitivity of western and eastern European comapnies was found.

India’s National Rural Employment Guarantee Scheme (NREGS) is a unique initiative in the history of state sponsored social security interventions, which guarantees at least 100 days of employment on local public works to anyone who demands for it. NREGS is in operation since 2006. This is world’s largest public-works programme ever, covering around 45 million households every year. Launching of the NREGS indicates a renewal of importance of public-works programme in the global South during the last decade. After 9 years of its continued implementation, there seems to be a dearth of systematic and scientific studies based on grassroots primary survey on how this programme is being implemented and why there is a renewed interest around this programme among the academics and development practitioners across the world. This thesis therefore seeks to understand i) what impacts NREGS created at the household level and ii) the political economy behind its implementation. This thesis comprises of three essays or chapters. Chapter1 and Chapter 3 are based on a threewave household-level longitudinal primary dataset and Chapter 2 is based on a threewave village-level longitudinal primary dataset. All the surveys were conducted between the period 2009 and 2012 in West Bengal state of India. First core chapter of this thesis addresses the research question: what are the impacts of the NREGS participation on household level economic variables and whether participation in NREGS can work as a proxy for collateral in accessing the informal credit for consumption smoothing? Second core chapter addresses the research question: whether the Village Council level ruling political party preferentially allocates the NREGS fund to optimise its chances re-election. Third core chapter addresses the research question: whether there is any non-poor capture of NREGS and whether households’ explicit political affiliation with the ruling party matters in obtaining any extra dividend under NREGS.

This study provides a systematic description of the nature and evolution of major transactions in the U.S. apparel sector, using a theory that applies across sectors. This research investigates the determinants of the existence and magnitude of major inter-firm transactions, relying on a unique longitudinal dataset of over 2,000 of the largest transactional (buy-sell) relations between publicly traded firms in the U.S. apparel sector. The results indicate the importance of inter-firm complementarity, rather than inter-firm similarity, in explaining the sector architecture; thus contributing to the future improvement of industry classification systems. This study also contributes to a deeper understanding of the apparel sector focusing on the change in the relative importance of manufacturing activities versus service activities and in the involvement of firms from the outside apparel sector. Implications of inter-firm transactions are discussed regarding industry policies, and human and environmental welfare in manufacturing and raw materials industries.