Many economic and social surveys are designed as panel studies, which provide important data for describing social changes and testing causal relations between social phenomena. This textbook shows how to manage, describe, and model these kinds of data. It presents models for continuous and categorical dependent variables, focusing either on the level of these variables at different points in time or on their change over time. It covers fixed and random effects models, models for change scores and event history models. All statistical methods are explained in an application-centered style using research examples from scholarly journals, which can be replicated by the reader through data provided on the accompanying website. As all models are compared to each other, it provides valuable assistance with choosing the right model in applied research. The textbook is directed at master and doctoral students as well as applied researchers in the social sciences, psychology, business administration and economics. Readers should be familiar with linear regression and have a good understanding of ordinary least squares estimation.

Over the past 25 years, applied econometrics has undergone tremen dous changes, with active developments in fields of research such as time series, labor econometrics, financial econometrics and simulation based methods. Time series analysis has been an active field of research since the seminal work by Box and Jenkins (1976), who introduced a gen eral framework in which time series can be analyzed. In the world of financial econometrics and the application of time series techniques, the ARCH model of Engle (1982) has shifted the focus from the modelling of the process in itself to the modelling of the volatility of the process. In less than 15 years, it has become one of the most successful fields of 1 applied econometric research with hundreds of published papers. As an alternative to the ARCH modelling of the volatility, Taylor (1986) intro duced the stochastic volatility model, whose features are quite similar to the ARCH specification but which involves an unobserved or latent component for the volatility. While being more difficult to estimate than usual GARCH models, stochastic volatility models have found numerous applications in the modelling of volatility and more particularly in the econometric part of option pricing formulas. Although modelling volatil ity is one of the best known examples of applied financial econometrics, other topics (factor models, present value relationships, term structure 2 models) were also successfully tackled."

This second edition of Design of Observational Studies is both an introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies. An observational study is an empiric investigation of effects caused by treatments when randomized experimentation is unethical or infeasible. Observational studies are common in most fields that study the effects of treatments on people, including medicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design. Design of Observational Studies is organized into five parts. Chapters 2, 3, and 5 of Part I cover concisely many of the ideas discussed in Rosenbaum's Observational Studies (also published by Springer) but in a less technical fashion. Part II discusses the practical aspects of using propensity scores and other tools to create a matched comparison that balances many covariates, and includes an updated chapter on matching in R. In Part III, the concept of design sensitivity is used to appraise the relative ability of competing designs to distinguish treatment effects from biases due to unmeasured covariates. Part IV is new to this edition; it discusses evidence factors and the computerized construction of more than one comparison group. Part V discusses planning the analysis of an observational study, with particular reference to Sir Ronald Fisher's striking advice for observational studies: "make your theories elaborate." This new edition features updated exploration of causal influence, with four new chapters, a new R package DOS2 designed as a companion for the book, and discussion of several of the latest matching packages for R. In particular, DOS2 allows readers to reproduce many analyses from Design of Observational Studies.

This is an essential how-to guide on the application of structural equation modeling (SEM) techniques with the AMOS software, focusing on the practical applications of both simple and advanced topics. Written in an easy-to-understand conversational style, the book covers everything from data collection and screening to confirmatory factor analysis, structural model analysis, mediation, moderation, and more advanced topics such as mixture modeling, censored date, and non-recursive models. Through step-by-step instructions, screen shots, and suggested guidelines for reporting, Collier cuts through abstract definitional perspectives to give insight on how to actually run analysis. Unlike other SEM books, the examples used will often start in SPSS and then transition to AMOS so that the reader can have full confidence in running the analysis from beginning to end. Best practices are also included on topics like how to determine if your SEM model is formative or reflective, making it not just an explanation of SEM topics, but a guide for researchers on how to develop a strong methodology while studying their respective phenomenon of interest. With a focus on practical applications of both basic and advanced topics, and with detailed work-through examples throughout, this book is ideal for experienced researchers and beginners across the behavioral and social sciences.

This unorthodox book derives and tests a simple theory of economic time series using several well-known empirical economic puzzles, from stock market bubbles to the failure of conventional economic theory, to explain low levels of inflation and unemployment in the US.Professor Stanley develops a new econometric methodology which demonstrates the explanatory power of the behavioral inertia hypothesis and solves the pretest/specification dilemma. He then applies this to important measures of the world's economies including GDP, prices and consumer spending. The behavioral inertia hypothesis claims that inertia and randomness (or 'caprice') are the most important factors in representing and forecasting many economic time series. The development of this new model integrates well-known patterns in economic time series data with well-accepted ideas in contemporary philosophy of science. Academic economists will find this book interesting as it presents a unified approach to economic time series, solves a number of important empirical puzzles and introduces a new econometric methodology. Business and financial analysts will also find it useful because it offers a simple, yet powerful, framework in which to study and predict financial market movements.

Nonlinear and nonnormal filters are introduced and developed. Traditional nonlinear filters such as the extended Kalman filter and the Gaussian sum filter give biased filtering estimates, and therefore several nonlinear and nonnormal filters have been derived from the underlying probability density functions. The density-based nonlinear filters introduced in this book utilize numerical integration, Monte-Carlo integration with importance sampling or rejection sampling and the obtained filtering estimates are asymptotically unbiased and efficient. By Monte-Carlo simulation studies, all the nonlinear filters are compared. Finally, as an empirical application, consumption functions based on the rational expectation model are estimated for the nonlinear filters, where US, UK and Japan economies are compared.

Halbert White has made a major contribution to key areas of econometrics including specification analysis, specification testing, encompassing and Cox tests and model selection. This book presents his most important published work supplemented with new material setting his work in context.Together with new introductions to each of the chapters, the articles cover work from the early 1980s to 1996 and provide an excellent overview of the breadth of Professor White's work and the evolution of his ideas. Using rigorous mathematical techniques Halbert White develops many of the central themes in econometrics concerning models, data generating processes and estimation procedures. Throughout the book the unifying vision is that econometric models are only imperfect approximations to the processes generating economic data and that this has implications for the interpretation of estimates, inference and selection of econometric models. This unique collection of some of Halbert White's important work, not otherwise readily accessible, will be welcomed by researchers, graduates and academics in econometrics and statistics.

Hardbound. This book is a result of recent developments in several fields. Mathematicians, statisticians, finance theorists, and economists found several interconnections in their research. The emphasis was on common methods, although the applications were also interrelated.The main topic is dynamic stochastic models, in which information arrives and decisions are made sequentially. This gives rise to what finance theorists call option value, what some economists label quasi-option value. Some papers extend the mathematical theory, some deal with new methods of economic analysis, while some present important applications, to natural resources in particular.

Zvi Griliches has made many seminal contributions to econometrics during the course of a long and distinguished career. His work has focused primarily on the economics of technological change and the econometric problems that arise in trying to study it. This major collection presents Professor Griliches's most important essays and papers on method, applied econometrics and specification problems. It reflects his interests in data-instigated contributions to econometric methodology, developments in and exposition of specification analysis, statistical aggregation, distributed lag models, sample selection bias and measurement error and other unobservable variance component models. These methods are applied to important substantive questions such as the estimation of the returns to education, the measurement of quality change, and productivity and economies of scale. Practicing Econometrics provides an essential reference source to the work of one of the most influential econometricians of the late 20th century.

This book discusses market microstructure environment within the context of the global financial crisis. In the first part, the market microstructure theory is recalled and the main microstructure models and hypotheses are discussed. The second part focuses on the main effects of the financial downturn through an examination of market microstructure dynamics. In particular, the effects of market imperfections and the limitations associated with microstructure models are discussed. Finally, the new regulations and recent developments for financial markets that aim to improve the market microstructure are discussed. Well-known experts on the subject contribute to the chapters in the book. A must-read for academic researchers, students and quantitative practitioners.

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.

A Guide to Modern Econometrics, Fifth Edition has become established as a highly successful textbook. It serves as a guide to alternative techniques in econometrics with an emphasis on intuition and the practical implementation of these approaches. This fifth edition builds upon the success of its predecessors. The text has been carefully checked and updated, taking into account recent developments and insights. It includes new material on casual inference, the use and limitation of p-values, instrumental variables estimation and its implementation, regression discontinuity design, standardized coefficients, and the presentation of estimation results.

Coverage has been extended to include recent topics. The book again presents a unified treatment of economic theory, with the method of maximum likelihood playing a key role in both estimation and testing. Exercises are included and the book is suitable as a general text for final-year undergraduate and postgraduate students.

The maximum principle and dynamic programming are the two most commonly used approaches in solving optimal control problems. These approaches have been developed independently. The theme of this book is to unify these two approaches, and to demonstrate that the viscosity solution theory provides the framework to unify them.

Thorough presentation of the problem of portfolio optimization, leading in a natural way to the Capital Market Theory Dynamic programming and the optimal portfolio selection-consumption problem through time An intuitive approach to Brownian motion and stochastic integral models for continuous time problems The Black-Scholes equation for simple European option values, derived in several different ways A chapter on several types of exotic options and one on material on the management of risk in several contexts

Financial market volatility plays a crucial role in financial decision making, as volatility forecasts are important input parameters in areas such as option pricing, hedging strategies, portfolio allocation and Value-at-Risk calculations. The fact that financial innovations arrive at an ever-increasing rate has motivated both academic researchers and practitioners and advances in this field have been considerable. The use of Stochastic Volatility (SV) models is one of the latest developments in this area. Empirical Studies on Volatility in International Stock Markets describes the existing techniques for the measurement and estimation of volatility in international stock markets with emphasis on the SV model and its empirical application. Eugenie Hol develops various extensions of the SV model, which allow for additional variables in both the mean and the variance equation. In addition, the forecasting performance of SV models is compared not only to that of the well-established GARCH model but also to implied volatility and so-called realised volatility models which are based on intraday volatility measures.
The intended readers are financial professionals who seek to obtain more accurate volatility forecasts and wish to gain insight about state-of-the-art volatility modelling techniques and their empirical value, and academic researchers and students who are interested in financial market volatility and want to obtain an updated overview of the various methods available in this area.

The Handbook of U.S. Labor Statistics is recognized as an authoritative resource on the U.S. labor force. It continues and enhances the Bureau of Labor Statistics's (BLS) discontinued publication, Labor Statistics. It allows the user to understand recent developments as well as to compare today's economy with past history. This edition includes new tables on employee benefits and occupational safety and health. The Handbook is a comprehensive reference providing an abundance of data on a variety of topics including: *Employment and unemployment; *Earnings; *Prices; *Productivity; *Consumer expenditures; *Occupational safety and health; *Union membership; *Working poor *And much more! Features of the publication In addition to over 215 tables that present practical data, the Handbook provides: *Introductory material for each chapter that contains highlights of salient data and figures that call attention to noteworthy trends in the data *Notes and definitions, which contain concise descriptions of the data sources, concepts, definitions, and methodology from which the data are derived *References to more comprehensive reports which provide additional data and more extensive descriptions of estimation methods, sampling, and reliability measures

Statistics for Finance develops students' professional skills in statistics with applications in finance. Developed from the authors' courses at the Technical University of Denmark and Lund University, the text bridges the gap between classical, rigorous treatments of financial mathematics that rarely connect concepts to data and books on econometrics and time series analysis that do not cover specific problems related to option valuation. The book discusses applications of financial derivatives pertaining to risk assessment and elimination. The authors cover various statistical and mathematical techniques, including linear and nonlinear time series analysis, stochastic calculus models, stochastic differential equations, Ito's formula, the Black-Scholes model, the generalized method-of-moments, and the Kalman filter. They explain how these tools are used to price financial derivatives, identify interest rate models, value bonds, estimate parameters, and much more. This textbook will help students understand and manage empirical research in financial engineering. It includes examples of how the statistical tools can be used to improve value-at-risk calculations and other issues. In addition, end-of-chapter exercises develop students' financial reasoning skills.

Recent economic history suggests that a key element in economic growth and development for many countries has been an aggressive export policy and a complementary import policy. Such policies can be very effective provided that resources are used wisely to encourage exports from industries that can be com petitive in the international arena. Also, import protection must be used carefully so that it encourages infant industries instead of providing rents to industries that are not competitive. Policy makers may use a variety of methods of analysis in planning trade policy. As computing power has grown in recent years increasing attention has been give to economic models as one of the most powerful aids to policy making. These models can be used on the one hand to help in selecting export industries to encourage and infant industries to protect and on the other hand to chart the larger effects ofttade policy on the entire economy. While many models have been developed in recent years there has not been any analysis of the strengths and weaknesses of the various types of models. Therefore, this monograph provides a review and analysis of the models which can be used to analyze dynamic comparative advantage."

Extensive code examples in R, Stata, and Python Chapters on overlooked topics in econometrics classes: heterogeneous treatment effects, simulation and power analysis, new cutting-edge methods, and uncomfortable ignored assumptions An easy-to-read conversational tone Up-to-date coverage of methods with fast-moving literatures like difference-in-differences

This book presents the effects of integrating information and communication technologies (ICT) and economic processes in macroeconomic dynamics, finance, marketing, industrial policies, and in government economic strategy. The text explores modeling and applications in these fields and also describes, in a clear and accessible manner, the theories that guide the integration among information technology (IT), telecommunications, and the economy, while presenting examples of their applications. Current trends such as artificial intelligence, machine learning, and big data technologies used in economics are also included. This volume is suitable for researchers, practitioners, and students working in economic theory and the computational social sciences.

Updated to textbook form by popular demand, this second edition discusses diverse mathematical models used in economics, ecology, and the environmental sciences with emphasis on control and optimization. It is intended for graduate and upper-undergraduate course use, however, applied mathematicians, industry practitioners, and a vast number of interdisciplinary academics will find the presentation highly useful. Core topics of this text are: * Economic growth and technological development * Population dynamics and human impact on the environment * Resource extraction and scarcity * Air and water contamination * Rational management of the economy and environment * Climate change and global dynamics The step-by-step approach taken is problem-based and easy to follow. The authors aptly demonstrate that the same models may be used to describe different economic and environmental processes and that similar investigation techniques are applicable to analyze various models. Instructors will appreciate the substantial flexibility that this text allows while designing their own syllabus. Chapters are essentially self-contained and may be covered in full, in part, and in any order. Appropriate one- and two-semester courses include, but are not limited to, Applied Mathematical Modeling, Mathematical Methods in Economics and Environment, Models of Biological Systems, Applied Optimization Models, and Environmental Models. Prerequisites for the courses are Calculus and, preferably, Differential Equations.

Develop the analytical skills that are in high demand in businesses today with Camm/Cochran/Fry/Ohlmann's best-selling BUSINESS ANALYTICS, 4E. You master the full range of analytics as you strengthen descriptive, predictive and prescriptive analytic skills. Real examples and memorable visuals illustrate data and results for each topic. Step-by-step instructions guide you through using Microsoft (R) Excel, Tableau, R, and JMP Pro software to perform even advanced analytics concepts. Practical, relevant problems at all levels of difficulty further help you apply what you've learned. This edition assists you in becoming proficient in topics beyond the traditional quantitative concepts, such as data visualization and data mining, which are increasingly important in today's analytical problem solving. MindTap digital learning resources with an interactive eBook, algorithmic practice problems with solutions and Exploring Analytics visualizations strengthen your understanding of key concepts.

Volatility ranks among the most active and successful areas of research in econometrics and empirical asset pricing finance over the past three decades. This research review studies and analyses some of the most influential published works from this burgeoning literature, both classic and contemporary. Topics covered include GARCH, stochastic and multivariate volatility models as well as forecasting, evaluation and high-frequency data. This insightful review presents and discusses the most important milestones and contributions that helped pave the way to today's understanding of volatility.

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.