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Non-Parametric Econometrics
This book allows those with a basic knowledge of econometrics to learn the main nonparametric and semiparametric techniques used in econometric modelling, and how to apply them correctly. It looks at kernel density estimation, kernel regression, splines, wavelets, and mixture models, and provides useful empirical examples throughout. Using empirical application, several economic topics are addressed, including income distribution, wage equation, economic convergence, the Phillipscurve, interest rate dynamics, returns volatility, and housing prices. A helpful appendix also explains how to implement the methods using R.This useful book will appeal to practitioners and researchers who need an accessible introduction to nonparametric and semiparametric econometrics. The practical approach provides an overview of the main techniques without including too much focus on mathematical formulas. It also serves as an accompanying textbook for a basic course, typically at undergraduate or graduate level.
Econometrics and Income Inequality
This book is a printed edition of the Special Issue "Econometrics and Income Inequality" that was published in Econometrics
Econometrics and Income Inequality
This Special Issue is devoted to the econometric analysis of income inequality and income distributions. Given the recent surge of inequality research, this Special Issue seeks to combine both theoretical and applied contributions which advance the econometric analysis of income inequality and income distributions. Possible topics include, but are not limited to, statistical inference for inequality measurement, inequality measurement with complex survey data, parametric or nonparametric modeling of income distributions, statistical decomposition methodology, methods to investigate the determinants of distributional change, causal inference in inequality measurement, and applications of such methods to substantive research questions in different fields of economics.
Productivity and Inequality
The volume highlights the state-of-the-art knowledge (including data analysis) of productivity, inequality and efficiency analysis. It showcases a selection of the best papers from the 9th North American Productivity Workshop. These papers are relevant to academia, but also to public and private sectors in terms of the challenges that firms, financial institutions, governments, and individuals may face when dealing with economic and education related activities that lead to increase or decrease of productivity. The volume also aims to bring together ideas from different parts of the world about the challenges those local economies and institutions may face when changes in productivity are ob...
Econometrics
The most authoritative and up-to-date core econometrics textbook available Econometrics is the quantitative language of economic theory, analysis, and empirical work, and it has become a cornerstone of graduate economics programs. Econometrics provides graduate and PhD students with an essential introduction to this foundational subject in economics and serves as an invaluable reference for researchers and practitioners. This comprehensive textbook teaches fundamental concepts, emphasizes modern, real-world applications, and gives students an intuitive understanding of econometrics. Covers the full breadth of econometric theory and methods with mathematical rigor while emphasizing intuitive ...
Optimal Transport Statistics for Economics and Related Topics
This volume emphasizes techniques of optimal transport statistics, but it also describes and uses other econometric techniques, ranging from more traditional statistical techniques to more innovative ones such as quantiles (in particular, multidimensional quantiles), maximum entropy approach, and machine learning. Applications range from general analysis of GDP growth, stock market, and consumer prices to analysis of specific sectors of economics (construction, credit and banking, energy, health, labor, textile, tourism, international trade) to specific issues affecting economy such as bankruptcy, effect of Covid-19 pandemic, effect of pollution, effect of gender, cryptocurrencies, and the e...
Inequality in the Developing World
Inequality has emerged as a key development challenge. It holds implications for economic growth and redistribution and translates into power asymmetries that can endanger human rights, create conflict, and embed social exclusion and chronic poverty. For these reasons, it underpins intense public and academic debates and has become a dominant policy concern within many countries and in all multilateral agencies. It is at the core of the 17 goals of the UN 2030 Agenda for Sustainable Development. This book contributes to this important discussion by presenting assessments of the measurement and analysis of global inequality by leading inequality scholars, aligning these to comprehensive reviews of inequality trends in five of the world's largest developing countries - Brazil, China, India, Mexico, and South Africa.
Advanced analysis of diffusion MRI data
Diffusion magnetic resonance imaging (diffusion MRI) is a non-invasive imaging modality which can measure diffusion of water molecules, by making the MRI acquisition sensitive to diffusion. Diffusion MRI provides unique possibilities to study structural connectivity of the human brain, e.g. how the white matter connects different parts of the brain. Diffusion MRI enables a range of tools that permit qualitative and quantitative assessments of many neurological disorders, such as stroke and Parkinson. This thesis introduces novel methods for diffusion MRI data analysis. Prior to estimating a diffusion model in each location (voxel) of the brain, the diffusion data needs to be preprocessed to ...
A Practical Guide to Price Index and Hedonic Techniques
This text introduces methods that are used to measure price trends for specific industries or goods, focusing on price index and hedonic techniques, the two methods most widely used by researchers and industry practitioners.
Machine Learning Toolbox for Social Scientists
Machine Learning Toolbox for Social Scientists covers predictive methods with complementary statistical "tools" that make it mostly self-contained. The inferential statistics is the traditional framework for most data analytics courses in social science and business fields, especially in Economics and Finance. The new organization that this book offers goes beyond standard machine learning code applications, providing intuitive backgrounds for new predictive methods that social science and business students can follow. The book also adds many other modern statistical tools complementary to predictive methods that cannot be easily found in "econometrics" textbooks: nonparametric methods, data...
