This volume examines the properties of statistics on household behavior in Japan. This work is an essential guide for all researchers who are interested in household decision making and the Japanese economy. Many household surveys are conducted in Japan reflecting the fact that household activities have various aspects such as income earning, timing and pattern choice of expenditure and consumption, asset portfolio choice, labor supply decision, time use, and health status. Moreover, the contents of each survey overlap in a complex manner to present a serious obstacle for potential survey users. In this book, the basic information from each survey such as sampling methods, survey techniques, and available variables is provided and then compared to check the consistency across the same variables reported in different surveys. Exploring strengths and weaknesses of each survey, this book is highly recommended to readers who seek comprehensive, up-to-date information about Japanese surveys and want to use appropriate data for their analysis.

Methods and perspectives to model and measure productivity and efficiency have made a number of important advances in the last decade. Using the standard and innovative formulations of the theory and practice of efficiency and productivity measurement, Robin C. Sickles and Valentin Zelenyuk provide a comprehensive approach to productivity and efficiency analysis, covering its theoretical underpinnings and its empirical implementation, paying particular attention to the implications of neoclassical economic theory. A distinct feature of the book is that it presents a wide array of theoretical and empirical methods utilized by researchers and practitioners who study productivity issues. An accompanying website includes methods, programming codes that can be used with widely available software like MATLAB (R) and R, and test data for many of the productivity and efficiency estimators discussed in the book. It will be valuable to upper-level undergraduates, graduate students, and professionals.

Structural vector autoregressive (VAR) models are important tools for empirical work in macroeconomics, finance, and related fields. This book not only reviews the many alternative structural VAR approaches discussed in the literature, but also highlights their pros and cons in practice. It provides guidance to empirical researchers as to the most appropriate modeling choices, methods of estimating, and evaluating structural VAR models. The book traces the evolution of the structural VAR methodology and contrasts it with other common methodologies, including dynamic stochastic general equilibrium (DSGE) models. It is intended as a bridge between the often quite technical econometric literature on structural VAR modeling and the needs of empirical researchers. The focus is not on providing the most rigorous theoretical arguments, but on enhancing the reader's understanding of the methods in question and their assumptions. Empirical examples are provided for illustration.

In Mathematical Finance, the authors consider a mathematical model for the pricing of emissions permits. The model has particular applicability to the European Union Emissions Trading System (EU ETS) but could also be used to consider the modeling of other cap-and-trade schemes. As a response to the risk of Climate Change, carbon markets are currently being implemented in regions worldwide and already represent more than $30 billion. However, scientific, and particularly mathematical, studies of these carbon markets are needed in order to expose their advantages and shortcomings, as well as allow their most efficient implementation. This Brief reviews mathematical properties such as the existence and uniqueness of solutions for the pricing problem, stability of solutions and their behavior. These fit into the theory of fully coupled forward-backward stochastic differential equations (FBSDEs) with irregular coefficients. The authors present a numerical algorithm to compute the solution to these non-standard FBSDEs. They also carry out a case study of the UK energy market. This involves estimating the parameters to be used in the model using historical data and then solving a pricing problem using the aforementioned numerical algorithm. The Brief is of interest to researchers in stochastic processes and their applications, and environmental and energy economics. Most sections are also accessible to practitioners in the energy sector and climate change policy-makers.

This book seeks new perspectives on the growing inequalities that our societies face, putting forward Structured Additive Distributional Regression as a means of statistical analysis that circumvents the common problem of analytical reduction to simple point estimators. This new approach allows the observed discrepancy between the individuals' realities and the abstract representation of those realities to be explicitly taken into consideration using the arithmetic mean alone. In turn, the method is applied to the question of economic inequality in Germany.

This is the first of two volumes containing papers and commentaries presented at the Eleventh World Congress of the Econometric Society, held in Montreal, Canada in August 2015. These papers provide state-of-the-art guides to the most important recent research in economics. The book includes surveys and interpretations of key developments in economics and econometrics, and discussion of future directions for a wide variety of topics, covering both theory and application. These volumes provide a unique, accessible survey of progress on the discipline, written by leading specialists in their fields. The first volume includes theoretical and applied papers addressing topics such as dynamic mechanism design, agency problems, and networks.

This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models. The authors provide a detailed and extensive study of impulse responses and forecasting in the stationary and non-stationary context, considering small sample correction, volatility and the impact of different orders of integration. Models with expectations are considered along with alternate methods such as Singular Spectrum Analysis (SSA), the Kalman Filter and Structural Time Series, all in relation to cointegration. Using single equations methods to develop topics, and as examples of the notion of cointegration, Burke, Hunter, and Canepa provide direction and guidance to the now vast literature facing students and graduate economists.

Maths for Economics provides a comprehensive and solid foundation in core mathematical principles and methods used in economics, beginning with revisiting basic skills in arithmetic, algebra, equation solving, and slowly building to more advanced topics. Suitable for those with a range of prior school-level expereince or more generally for those who feel they need to go back to the very basics, students can learn with confidence. Drawing on his extensive experience of teaching in the area, the author appreciates that maths can be a daunting topic for many. As such the text is fully supports the reader by using a combination of engaging learning features including summary sections, examples to show how theory is used in practice and progress exercises, which encourage independent study. Each chapter ends with a conclusion check list to allow students to reflect on topics as they master them. Digital formats and resources The fifth edition is available for students and institutions to purchase in a variety of formats, and is supported by online resources. The e-book offers a mobile experience and convenient access along with functionality tools, navigation features, and links that offer extra learning support: www.oxfordtextbooks.co.uk/ebooks Online resources supporting the book include, For Students: - Ask the author forum - Excel tutorial - Maple tutorial - Further exercises - Answers to further questions - Expanded solutions to progress exercises For Lecturers: - Test exercises - Graphs from the book - Answers to test exercises

High-dimensional probability offers insight into the behavior of random vectors, random matrices, random subspaces, and objects used to quantify uncertainty in high dimensions. Drawing on ideas from probability, analysis, and geometry, it lends itself to applications in mathematics, statistics, theoretical computer science, signal processing, optimization, and more. It is the first to integrate theory, key tools, and modern applications of high-dimensional probability. Concentration inequalities form the core, and it covers both classical results such as Hoeffding's and Chernoff's inequalities and modern developments such as the matrix Bernstein's inequality. It then introduces the powerful methods based on stochastic processes, including such tools as Slepian's, Sudakov's, and Dudley's inequalities, as well as generic chaining and bounds based on VC dimension. A broad range of illustrations is embedded throughout, including classical and modern results for covariance estimation, clustering, networks, semidefinite programming, coding, dimension reduction, matrix completion, machine learning, compressed sensing, and sparse regression.

Nonlinear models have been used extensively in the areas of economics and finance. Recent literature on the topic has shown that a large number of series exhibit nonlinear dynamics as opposed to the alternative--linear dynamics. Incorporating these concepts involves deriving and estimating nonlinear time series models, and these have typically taken the form of Threshold Autoregression (TAR) models, Exponential Smooth Transition (ESTAR) models, and Markov Switching (MS) models, among several others. This edited volume provides a timely overview of nonlinear estimation techniques, offering new methods and insights into nonlinear time series analysis. It features cutting-edge research from leading academics in economics, finance, and business management, and will focus on such topics as Zero-Information-Limit-Conditions, using Markov Switching Models to analyze economics series, and how best to distinguish between competing nonlinear models. Principles and techniques in this book will appeal to econometricians, finance professors teaching quantitative finance, researchers, and graduate students interested in learning how to apply advances in nonlinear time series modeling to solve complex problems in economics and finance.

This book empirically analyzes the vulnerability of poor households in rural areas of Mexico and the effects of the conditional cash transfer (CCT) program called PROGRESA-Oportunidades by adopting the two most recent sets of rural household panel data for 2003 2007. The period covered by this book coincides with the unexpected reversal of the poverty trend observed in 2006 to the present which raised a question of vulnerability to poverty of Mexican households that had emerged from poverty in the early 2000s under a stable economic condition. The author applies different methodologies in defining vulnerable households in each chapter, enabling discussion of the multiple dimensions of vulnerability from varying perspectives, to identify the determinants of rural household vulnerability to poverty and the CCT effects. Empirical studies reported in this book confirmed a certain role played by PROGRESA-Oportunidades in mitigating vulnerability; however, the effect was rather partial and could not fully achieve poverty reduction during the surveyed period. By combining the existent discussions and empirical results of the CCT impacts, the author concludes that a possible limitation of PROGRESA-Oportunidades may be the excessive focus on the labor supply side, thus complementary policies must enhance the demand side, especially in creating decent employment opportunities for youth.

This book focuses on economic inequality, its measurement, and its relationship with economic growth and development. The current literature uses multiple points of view, ranging from ethical, legal, philosophical, to political and economic, to understand the nature of (in)equality. Presenting the problem objectively, this book shows how to measure the phenomenon statistically along with an international comparison of the level of income inequality and economic growth and of their complex relationship. The book also analyzes three decades of theoretical and empirical evidence to understand this phenomenon and discusses a number of political measures to reduce economic disparities while stimulating economic growth.

This book provides advanced theoretical and applied tools for the implementation of modern micro-econometric techniques in evidence-based program evaluation for the social sciences. The author presents a comprehensive toolbox for designing rigorous and effective ex-post program evaluation using the statistical software package Stata. For each method, a statistical presentation is developed, followed by a practical estimation of the treatment effects. By using both real and simulated data, readers will become familiar with evaluation techniques, such as regression-adjustment, matching, difference-in-differences, instrumental-variables and regression-discontinuity-design and are given practical guidelines for selecting and applying suitable methods for specific policy contexts.

A number of clubs in professional sports leagues exhibit winning streaks over a number of consecutive seasons that do not conform to the standard economic model of a professional sports league developed by El Hodiri and Quirk (1994) and Fort and Quirk (1995). These clubs appear to display what we term "unsustainable runs", defined as a period of two to four seasons where the club acquires expensive talent and attempts to win a league championship despite not having the market size to sustain such a competitive position in the long run. The standard model predicts that clubs that locate in large economic markets will tend to acquire more talent, achieve more success on the field and at the box office than clubs that are located in small markets. This book builds a model that can allow unsustainable runs yet retains most of the features of the standard model. The model is then subjected to empirical verification. The new model we develop in the book has as its central feature the possibility of generating two equilibria for a club. In the empirical sections of the book, we use time-series analysis to attempt to test for the presence of unsustainable runs using historical data from National Football League (NFL), National Basketball Association (NBA), National Hockey League (NHL) and Major League Baseball (MLB). The multiple equilibria model retains all of the features of the standard model of a professional sports league that is accepted quite universally by economists, yet it offers a much richer approach by including an exploration of the effects of revenues that are earned at the league level (television, apparel, naming rights, etc.) that are then shared by all of the member clubs, making this book unique and of great interest to scholars in a variety of fields in economics.

This book reflects the state of the art on nonlinear economic dynamics, financial market modelling and quantitative finance. It contains eighteen papers with topics ranging from disequilibrium macroeconomics, monetary dynamics, monopoly, financial market and limit order market models with boundedly rational heterogeneous agents to estimation, time series modelling and empirical analysis and from risk management of interest-rate products, futures price volatility and American option pricing with stochastic volatility to evaluation of risk and derivatives of electricity market. The book illustrates some of the most recent research tools in these areas and will be of interest to economists working in economic dynamics and financial market modelling, to mathematicians who are interested in applying complexity theory to economics and finance and to market practitioners and researchers in quantitative finance interested in limit order, futures and electricity market modelling, derivative pricing and risk management.

This book is designed for self study. The reader can apply the theoretical concepts directly within R by following the examples.

This restructured, updated Third Edition provides a general overview of the econometrics of panel data, from both theoretical and applied viewpoints. Readers discover how econometric tools are used to study organizational and household behaviors as well as other macroeconomic phenomena such as economic growth. The book contains sixteen entirely new chapters; all other chapters have been revised to account for recent developments. With contributions from well known specialists in the field, this handbook is a standard reference for all those involved in the use of panel data in econometrics.

In 1945, very early in the history of the development of a rigorous analytical theory of probability, Feller (1945) wrote a paper called "The fundamental limit theorems in probability" in which he set out what he considered to be "the two most important limit theorems in the modern theory of probability: the central limit theorem and the recently discovered ... 'Kolmogoroff's cel ebrated law of the iterated logarithm' ". A little later in the article he added to these, via a charming description, the "little brother (of the central limit theo rem), the weak law of large numbers", and also the strong law of large num bers, which he considers as a close relative of the law of the iterated logarithm. Feller might well have added to these also the beautiful and highly applicable results of renewal theory, which at the time he himself together with eminent colleagues were vigorously producing. Feller's introductory remarks include the visionary: "The history of probability shows that our problems must be treated in their greatest generality: only in this way can we hope to discover the most natural tools and to open channels for new progress. This remark leads naturally to that characteristic of our theory which makes it attractive beyond its importance for various applications: a combination of an amazing generality with algebraic precision.

The main purpose of this book is to resolve deficiencies and limitations that currently exist when using Technical Analysis (TA). Particularly, TA is being used either by academics as an "economic test" of the weak-form Efficient Market Hypothesis (EMH) or by practitioners as a main or supplementary tool for deriving trading signals. This book approaches TA in a systematic way utilizing all the available estimation theory and tests. This is achieved through the developing of novel rule-based pattern recognizers, and the implementation of statistical tests for assessing the importance of realized returns. More emphasis is given to technical patterns where subjectivity in their identification process is apparent. Our proposed methodology is based on the algorithmic and thus unbiased pattern recognition. The unified methodological framework presented in this book can serve as a benchmark for both future academic studies that test the null hypothesis of the weak-form EMH and for practitioners that want to embed TA within their trading/investment decision making processes.

​ The goal of this book is to assess the efficacy of India’s financial deregulation programme by analyzing the developments in cost efficiency and total factor productivity growth across different ownership types and size classes in the banking sector over the post-deregulation years. The work also gauges the impact of inclusion or exclusion of a proxy for non-traditional activities on the cost efficiency estimates for Indian banks, and ranking of distinct ownership groups. It also investigates the hitherto neglected aspect of the nature of returns-to-scale in the Indian banking industry. In addition, the work explores the key bank-specific factors that explain the inter-bank variations in efficiency and productivity growth. Overall, the empirical results of this work allow us to ascertain whether the gradualist approach to reforming the banking system in a developing economy like India has yielded the most significant policy goal of achieving efficiency and productivity gains. The authors believe that the findings of this book could give useful policy directions and suggestions to other developing economies that have embarked on a deregulation path or are contemplating doing so.

Econophysics of Games and Social Choices.- Kolkata Paise Restaurant Problem in Some Uniform Learning Strategy Limits.- Cycle Monotonicity in Scheduling Models.- Reinforced Learning in Market Games.- Mechanisms Supporting Cooperation for the Evolutionary Prisoner's Dilemma Games.- Economic Applications of Quantum Information Processing.- Using Many-Body Entanglement for Coordinated Action in Game Theory Problems.- Condensation Phenomena and Pareto Distribution in Disordered Urn Models.- Economic Interactions and the Distribution of Wealth.- Wealth Redistribution in Boltzmann-like Models of Conservative Economies.- Multi-species Models in Econo- and Sociophysics.- The Morphology of Urban Agglomerations for Developing Countries: A Case Study with China.- A Mean-Field Model of Financial Markets: Reproducing Long Tailed Distributions and Volatility Correlations.- Statistical Properties of Fluctuations: A Method to Check Market Behavior.- Modeling Saturation in Industrial Growth.- The Kuznets Curve and the Inequality Process.- Monitoring the Teaching - Learning Process via an Entropy Based Index.- Technology Level in the Industrial Supply Chain: Thermodynamic Concept.- Discussions and Comments in Econophys Kolkata IV.- Contributions to Quantitative Economics.- On Multi-Utility Representation of Equitable Intergenerational Preferences.- Variable Populations and Inequality-Sensitive Ethical Judgments.- A Model of Income Distribution.- Statistical Database of the Indian Economy: Need for New Directions.- Does Parental Education Protect Child Health? Some Evidence from Rural Udaipur.- Food Security and Crop Diversification: Can West Bengal Achieve Both?.- Estimating Equivalence Scales Through Engel Curve Analysis.- Testing for Absolute Convergence: A Panel Data Approach.- Goodwin's Growth Cycles: A Reconsideration.- Human Capital Accumulation, Economic Growth and Educational Subsidy Policy in a Dual Economy.- Arms Trade and Conflict Resolution: A Trade-Theoretic Analysis.- Trade andWage Inequality with Endogenous Skill Formation.- Dominant Strategy Implementation in Multi-unit Allocation Problems.- Allocation through Reduction on Minimum Cost Spanning Tree Games.- Unmediated and Mediated Communication Equilibria of Battle of the Sexes with Incomplete Information.- A Characterization Result on the Coincidence of the Prenucleolus and the Shapley Value.- The Ordinal Equivalence of the Johnston Index and the Established Notions of Power.- Reflecting on Market Size and Entry under Oligopoly.

This book is a practical guide for theory-based empirical analysis in economics that guides the reader through the first steps when moving between economic theory and applied research. The book provides a hands-on introduction to some of the techniques that economists use for econometric estimation and shows how to convert a selection of standard and advanced estimators into MATLAB code. The book first provides a brief introduction to MATLAB and its syntax, before moving into microeconometric applications studied in undergraduate and graduate econometrics courses. Along with standard estimation methods such as, for example, Method of Moments, Maximum Likelihood, and constrained optimisation, the book also includes a series of chapters examining more advanced research methods. These include discrete choice, discrete games, dynamic models on a finite and infinite horizon, and semi- and nonparametric methods. In closing, it discusses more advanced features that can be used to optimise use of MATLAB, including parallel computing. Each chapter is structured around a number of worked examples, designed for the reader to tackle as they move through the book. Each chapter ends with a series of readings, questions, and extensions, designed to help the reader on their way to adapting the examples in the book to fit their own research questions.

This lively book lays out a methodology of confidence distributions and puts them through their paces. Among other merits, they lead to optimal combinations of confidence from different sources of information, and they can make complex models amenable to objective and indeed prior-free analysis for less subjectively inclined statisticians. The generous mixture of theory, illustrations, applications and exercises is suitable for statisticians at all levels of experience, as well as for data-oriented scientists. Some confidence distributions are less dispersed than their competitors. This concept leads to a theory of risk functions and comparisons for distributions of confidence. Neyman-Pearson type theorems leading to optimal confidence are developed and richly illustrated. Exact and optimal confidence distribution is the gold standard for inferred epistemic distributions. Confidence distributions and likelihood functions are intertwined, allowing prior distributions to be made part of the likelihood. Meta-analysis in likelihood terms is developed and taken beyond traditional methods, suiting it in particular to combining information across diverse data sources.

Pioneered by American economist Paul Samuelson, revealed preference theory is based on the idea that the preferences of consumers are revealed in their purchasing behavior. Researchers in this field have developed complex and sophisticated mathematical models to capture the preferences that are 'revealed' through consumer choice behavior. This study of consumer demand and behavior is closely tied up with econometrics (especially nonparametric econometrics), where testing the validity of different theoretical models is an important aspect of research. The theory of revealed preference has a very long and distinguished tradition in economics, but there was no systematic presentation of the theory until now. This book deals with basic questions in economic theory, such as the relation between theory and data, and studies the situations in which empirical observations are consistent or inconsistent with some of the best known theories in economics.