This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation, and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.

Seasonality in economic time series can "obscure" movements of other components in a series that are operationally more important for economic and econometric analyses. In practice, one often prefers to work with seasonally adjusted data to assess the current state of the economy and its future course. This book presents a seasonal adjustment program called CAMPLET, an acronym of its tuning parameters, which consists of a simple adaptive procedure to extract the seasonal and the non-seasonal component from an observed series. Once this process is carried out, there will be no need to revise these components at a later stage when new observations become available. The authors describe the main features of CAMPLET, evaluate the outcomes of CAMPLET and X-13ARIMA-SEATS in a controlled simulation framework using a variety of data generating processes, and illustrate CAMPLET and X-13ARIMA-SEATS with three time series: US non-farm payroll employment, operational income of Ahold and real GDP in the Netherlands. Furthermore they show how CAMPLET performs under the COVID-19 crisis, and its attractiveness in dealing with daily data. This book appeals to scholars and students of econometrics and statistics, interested in the application of statistical methods for empirical economic modeling.

A comprehensive, up-to-date textbook on nonparametric methods for students and researchers Until now, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis. Nonparametric Econometrics fills a major gap by gathering together the most up-to-date theory and techniques and presenting them in a remarkably straightforward and accessible format. The empirical tests, data, and exercises included in this textbook help make it the ideal introduction for graduate students and an indispensable resource for researchers. Nonparametric and semiparametric methods have attracted a great deal of attention from statisticians in recent decades. While the majority of existing books on the subject operate from the presumption that the underlying data is strictly continuous in nature, more often than not social scientists deal with categorical data-nominal and ordinal-in applied settings. The conventional nonparametric approach to dealing with the presence of discrete variables is acknowledged to be unsatisfactory. This book is tailored to the needs of applied econometricians and social scientists. Qi Li and Jeffrey Racine emphasize nonparametric techniques suited to the rich array of data types-continuous, nominal, and ordinal-within one coherent framework. They also emphasize the properties of nonparametric estimators in the presence of potentially irrelevant variables. Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems.

This book explains in simple settings the fundamental ideas of financial market modelling and derivative pricing, using the no-arbitrage principle. Relatively elementary mathematics leads to powerful notions and techniques - such as viability, completeness, self-financing and replicating strategies, arbitrage and equivalent martingale measures - which are directly applicable in practice. The general methods are applied in detail to pricing and hedging European and American options within the Cox-Ross-Rubinstein (CRR) binomial tree model. A simple approach to discrete interest rate models is included, which, though elementary, has some novel features. All proofs are written in a user-friendly manner, with each step carefully explained and following a natural flow of thought. In this way the student learns how to tackle new problems.

This econometrics textbook fills a gap between introductory undergraduate texts and advanced texts for the research student. Presenting the methods and techniques for problem solving, the author also examines their mathematical foundations, and presents an intuitive, largely geometric understanding of the structure of classical econometrics. The text will help students to develop strategies, not just tools, for solving econometrics problems.

This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.

Econophysics is an emerging interdisciplinary field that takes advantage of the concepts and methods of statistical physics to analyse economic phenomena. This book expands the explanatory scope of econophysics to the real economy by using methods from statistical physics to analyse the success and failure of companies. Using large data sets of companies and income-earners in Japan and Europe, a distinguished team of researchers show how these methods allow us to analyse companies, from huge corporations to small firms, as heterogeneous agents interacting at multiple layers of complex networks. They then show how successful this approach is in explaining a wide range of recent findings relating to the dynamics of companies. With mathematics kept to a minimum, the book is not only a lively introduction to the field of econophysics but also provides fresh insights into company behaviour.

This book addresses the underlying foundational elements, both theoretical and methodological, of sponsored search. As such, the contents are less affected by the ever-changing implementation aspects of technology. Rather than focusing on the how, this book examines what causes the how. Why do certain keywords work, while others do not? Why does that ad work well, when others that are similar do not? Why does a key phrase cost a given amount? Why do we measure what we do in keyword advertising? This book speaks to that curiosity to understand why we do what we do in sponsored search. The content flows through the major components of any sponsored search effort, regardless of the underlying technology or client or product. The book addresses keywords, ads, consumers, pricing, competitors, analytics, branding, marketing, and advertising, integrating these separate components into an incorporated whole. The focus is on the critical elements, with ample illustrations, and with enough detail to lead the interested reader to further inquiry.

This book analyses the dynamics of Indian stock market with a special emphasis during the period following emergence of Covid-19. Coming from the instability in stock market following Covid-19, it delves deeper into the dynamics and unfolds the causal relationship between various economic fundamentals and the stock prices. Observing short-term herding in the stock market following Covid-19, the book's finding suggests that investors in the Indian stock market made investment choices irrationally during Covid-19 crisis periods. It also showcases how the stock market became inefficient following the emergence of pandemic and did not follow the fundamentals. Interestingly, the findings suggest no relationship between stock returns and real economic activities in India. The format of presentation makes the book well suited not only for students, academics, policy makers and investors in the stock markets, but also people engaged or interested in business and finance. The book would thus be of interest to both specialists and the laity. Analysis contained in this book will help different readership groups in different ways. Researchers from economics and finance disciplines will be able to learn about frontiers in the theoretical paradigms discussed in the book; advanced econometric techniques applied in the book will also be useful for their own research. The macroeconomic insights, and insights from behavioural economics, can expand the knowledge of corporate sector, useful in making real life decisions. Finally, it will help policy makers, like SEBI (Securities and Exchange Board of India), to formulate appropriate regulatory policies so as to minimize possibility of speculative bubbles as experienced during the pandemic period in the Indian stock markets.

The search for symmetry is part of the fundamental scientific paradigm in mathematics and physics. Can this be valid also for economics? This book represents an attempt to explore this possibility. The behavior of price-taking producers, monopolists, monopsonists, sectoral market equilibria, behavior under risk and uncertainty, and two-person zero- and non-zero-sum games are analyzed and discussed under the unifying structure called the linear complementarity problem. Furthermore, the equilibrium problem allows for the relaxation of often-stated but unnecessary assumptions. This unifying approach offers the advantage of a better understanding of the structure of economic models. It also introduces the simplest and most elegant algorithm for solving a wide class of problems.

This handbook presents emerging research exploring the theoretical and practical aspects of econometric techniques for the financial sector and their applications in economics. By doing so, it offers invaluable tools for predicting and weighing the risks of multiple investments by incorporating data analysis. Throughout the book the authors address a broad range of topics such as predictive analysis, monetary policy, economic growth, systemic risk and investment behavior. This book is a must-read for researchers, scholars and practitioners in the field of economics who are interested in a better understanding of current research on the application of econometric methods to financial sector data.

As real estate forms a significant part of the asset portfolios of most investors and lenders, it is crucial that analysts and institutions employ sound techniques for modelling and forecasting the performance of real estate assets. Assuming no prior knowledge of econometrics, this book introduces and explains a broad range of quantitative techniques that are relevant for the analysis of real estate data. It includes numerous detailed examples, giving readers the confidence they need to estimate and interpret their own models. Throughout, the book emphasises how various statistical techniques may be used for forecasting and shows how forecasts can be evaluated. Written by a highly experienced teacher of econometrics and a senior real estate professional, both of whom are widely known for their research, Real Estate Modelling and Forecasting is the first book to provide a practical introduction to the econometric analysis of real estate for students and practitioners.

Getting accurate data on less developed countries has created great problems for studying these areas. Yet until recently students of development economics have relied on standard econometrics texts, which assume a Western context. Econometrics and Data Analysis for Developing Countries solves this problem. It will be essential reading for all advanced students of development economics.

The aim of this publication is to identify and apply suitable methods for analysing and predicting the time series of gold prices, together with acquainting the reader with the history and characteristics of the methods and with the time series issues in general. Both statistical and econometric methods, and especially artificial intelligence methods, are used in the case studies. The publication presents both traditional and innovative methods on the theoretical level, always accompanied by a case study, i.e. their specific use in practice. Furthermore, a comprehensive comparative analysis of the individual methods is provided. The book is intended for readers from the ranks of academic staff, students of universities of economics, but also the scientists and practitioners dealing with the time series prediction. From the point of view of practical application, it could provide useful information for speculators and traders on financial markets, especially the commodity markets.

This second edition presents the advances made in finance market analysis since 2005. The book provides a careful introduction to stochastic methods along with approximate ensembles for a single, historic time series. The new edition explains the history leading up to the biggest economic disaster of the 21st century. Empirical evidence for finance market instability under deregulation is given, together with a history of the explosion of the US Dollar worldwide. A model shows how bounds set by a central bank stabilized FX in the gold standard era, illustrating the effect of regulations. The book presents economic and finance theory thoroughly and critically, including rational expectations, cointegration and arch/garch methods, and replaces several of those misconceptions by empirically based ideas. This book will be of interest to finance theorists, traders, economists, physicists and engineers, and leads the reader to the frontier of research in time series analysis.

This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.

This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.

This book proposes new solutions to the problem of poverty, and begins with providing analyses. It bases most of the analyses and solutions in the context of the digital era. The book also follows, in addition to a scientific distribution, a spatial-geographical one: analyses of countries of the European Union as well as South Africa, while it referring to two main variables, television and art, as agents of poverty alleviation. The book places particular focus on how poverty is understood in the framework of Industry 4.0. It introduces a new expanded Multidimensional Poverty Index with more than 20 dimensions; moreover, it provides a mathematically based solution for the disposal of perishable food. Finally, it does not disregard the crucial aspect of the issue of poverty: that of education planning. This book is of interest to specialists in poverty research, from students to professionals and from professors to activists, without excluding engineers.

This book discusses the nature of exogeneity, a central concept in standard econometrics texts, and shows how to test for it through numerous substantive empirical examples from around the world, including the UK, Argentina, Denmark, Finland, and Norway. Part I defines terms and provides the necessary background; Part II contains applications to models of expenditure, money demand, inflation, wages and prices, and exchange rates; and Part III extends various tests of constancy and forecast accuracy, which are central to testing super exogeneity.
About the Series
Advanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.

Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to extract trends and cycles from time series. In this second edition, Terence Mills expands on the research in the area of trends and cycles over the last (almost) two decades, to highlight to students and researchers the variety of techniques and the considerations that underpin their choice for modelling trends and cycles.

This book develops the theory of productivity measurement using the empirical index number approach. The theory uses multiplicative indices and additive indicators as measurement tools, instead of relying on the usual neo-classical assumptions, such as the existence of a production function characterized by constant returns to scale, optimizing behavior of the economic agents, and perfect foresight. The theory can be applied to all the common levels of aggregation (micro, meso, and macro), and half of the book is devoted to accounting for the links existing between the various levels. Basic insights from National Accounts are thereby used. The final chapter is devoted to the decomposition of productivity change into the contributions of efficiency change, technological change, scale effects, and input or output mix effects. Applications on real-life data demonstrate the empirical feasibility of the theory. The book is directed to a variety of overlapping audiences: statisticians involved in measuring productivity change; economists interested in growth accounting; researchers relating macro-economic productivity change to its industrial sources; enterprise micro-data researchers; and business analysts interested in performance measurement.

This book provides the ultimate goal of economic studies to predict how the economy develops-and what will happen if we implement different policies. To be able to do that, we need to have a good understanding of what causes what in economics. Prediction and causality in economics are the main topics of this book's chapters; they use both more traditional and more innovative techniques-including quantum ideas -- to make predictions about the world economy (international trade, exchange rates), about a country's economy (gross domestic product, stock index, inflation rate), and about individual enterprises, banks, and micro-finance institutions: their future performance (including the risk of bankruptcy), their stock prices, and their liquidity. Several papers study how COVID-19 has influenced the world economy. This book helps practitioners and researchers to learn more about prediction and causality in economics -- and to further develop this important research direction.

The contents of this volume comprise the proceedings of the conference, "Equilibrium theory and applications." Some of the recent developments in general equilibrium theory in the perspective of actual and potential applications are presented. The conference was organized in honor of Jacques Dreze on the occasion of his sixtieth birthday. Held at C.O.R.E., it was also the unanimous recognition, stressed by Gerard Debreu in his Address, of his role as "the architect and builder" of the Center for Operations Research and Econometrics. An introductory address by Gerard Debreu comprises Part 1 of the volume. The rest of the volume is divided into four parts spanning the scope of the conference. Part 2 is on incomplete markets, increasing returns, and information, Part 3 on equilibrium and dynamices, Part 4 on employment, imperfect competition, and macroeconomics, and Part 5 on applied general equilibrium models.

This monograph addresses the methodological and empirical issues relevant for the development of sustainable agriculture, with a particular focus on Eastern Europe. It relates economic growth to the other dimensions of sustainability by applying integrated methods. The book comprises five chapters dedicated to the theoretical approaches towards sustainable rural development, productivity analysis, structural change analysis and environmental footprint. The book focuses on the transformations of the agricultural sector while taking into account economic, environmental, and social dynamics. The importance of agricultural transformations to the livelihood of the rural population and food security are highlighted. Further, advanced methodologies and frameworks are presented to fathom the underlying trends in different facets of agricultural production. The authors present statistical methods used for the analysis of agricultural sustainability along with applications for agriculture in the European Union. Additionally, they discuss the measures of efficiency, methodological approaches and empirical models. Finally, the book applies econometric and optimization techniques, which are useful for the estimation of the production functions and other representations of technology in the case of the European Union member states. Therefore, the book is a must-read for researchers and students of agricultural and production economics, as well as policy-makers and academia in general.

The University of Oxford has been and continues to be one of the most important global centres for economics. With six chapters on themes in Oxford economics and 24 chapters on the lives and work of Oxford economists, this volume shows how economics became established at the University, how it produced some of the world's best-known economists, including Francis Ysidro Edgeworth, Roy Harrod and David Hendry, and how it remains a global force for the very best in teaching and research in economics. With original contributions from a stellar cast, this volume provides economists - especially those interested in macroeconomics and the history of economic thought - with the first in-depth analysis of Oxford economics.