Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.495857
Title: Economic applications of nonparametric methods
Author: Baiocchi, Giovanni
Awarding Body: University of York
Current Institution: University of York
Date of Award: 2006
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Abstract:
This thesis deals with the subject of nonparametric methods, focusing on application to economic issues. Chapter 2 introduces the basic nonparametric methods underlying the applications in the subsequent chapters. In Chapter 3 we propose some basic standards to improve the use and reporting of nonparametric methods in the statistics and economics literature for the purpose of accuracy and reproducibility. We make recommendations on four aspects of the application of nonparametric methods: computational practice, published reporting, numerical accuracy, and visualization. In Chapter 4 we investigate the effect of life-cycle factors and other demographic characteristics on income inequality in the UK. Two conditional inequality measures are derived from estimating the cumulative distribution function of household income, conditional upon a broad set of explanatory variables. Estimation of the distribution is carried out using a semiparametric approach. The proposed inequality estimators are easily interpretable and are shown to be consistent. Our results indicate the importance of interfamily differences in the analysis of income distribution. In addition, our estimation procedure uncovers higher-order properties of the income distribution and non-linearities of its moments that cannot be captured by means of a "standard" parametric approach. Several features of the conditional distribution of income are highlighted. Chapter 5 we reexamine the relationship between openness to trade and the environment, controlling for economic development, in order to identify the presence of multiple regimes in the cross-country pollution-economic relationship. We first identify the presence of multiple regimes by using specification tests which entertain a single regime model as the null hypothesis. Then we develop an easily interpretable measure, based on an original application of the Blinder-Oaxaca decomposition, of the impact on the environment due to differences in regimes. Finally we apply a nonparametric recursive partitioning algorithm to endogenously identify various regimes. Our conclusions are threefold. First, we reject the null hypothesis that all countries obey a common linear model. Second, we find that quantitatively regime differences can have a significant impact. Thirdly, by using regression tree analysis we find subsets of countries which appear to possess very different environmental/economic relationships. In Chapter 6 investigate the existence of the so called environmental kuznets curve (EKC), the inverted-U shaped relationship between income and pollution, using nonparametric regression and a threshold regression methods. We find support for threshold models that lead to different reduced-form relationships between environmental quality and economic activity when early stages of economic growth are contrasted with later stages, There is no evidence of a common inverted U-shaped environment/economy relationship that all country follow as they grow. We also find that changes that might benefit the environment occur at much higher levels of income than those implied by standard models. Our findings support models in which improvements are a consequence of the deliberate introduction of policies addressing environmental concerns. Moreover, we find evidence that countries with low-income levels have a far greater variability in emissions per capita than high-income countries. This has the implication that it may be more difficult to predict emission levels for low-income countries approaching the turning point. A summary of the main findings and further research directions are presented in Chapter 7 and in Chapter 8, respectively.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.495857  DOI: Not available
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