This is a thorough exploration of the models and methods of financial econometrics by one of the world's leading financial econometricians and is for students in economics, finance, statistics, mathematics, and engineering who are interested in financial applications. Based on courses taught around the world, the up-to-date content covers developments in econometrics and finance over the last twenty years while ensuring a solid grounding in the fundamental principles of the field. Care has been taken to link theory and application to provide real-world context for students. Worked exercises and empirical examples have also been included to make sure complicated concepts are solidly explained and understood.

This introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. In the experimental sciences and interdisciplinary research, data analysis has become an integral part of any scientific study. Issues such as judging the credibility of data, analyzing the data, evaluating the reliability of the obtained results and finally drawing the correct and appropriate conclusions from the results are vital. The text is primarily intended for undergraduate students in disciplines like business administration, the social sciences, medicine, politics, macroeconomics, etc. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R as well as supplementary material that will enable the reader to quickly adapt all methods to their own applications.

Volume 27 of "Advances in Econometrics", entitled "Missing Data Methods", contains 16 chapters authored by specialists in the field, covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; Consistent Estimation and Orthogonality; and Likelihood-Based Estimators for Endogenous or Truncated Samples in Standard Stratified Sampling.

Volume 27 of "Advances in Econometrics", entitled "Missing Data Methods", contains 16 chapters authored by specialists in the field, covering topics such as: Missing-Data Imputation in Nonstationary Panel Data Models; Markov Switching Models in Empirical Finance; Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; Consistent Estimation and Orthogonality; and Likelihood-Based Estimators for Endogenous or Truncated Samples in Standard Stratified Sampling.

This book studies the evolution of the middle class in Russia after the fall of the Soviet Union. Using data from the RLMS (Russian Longitudinal Monitoring Survey), the volume covers the period of transition (1991-2008) during which many fundamental economic reforms were implemented. The first part of the book is devoted to a discussion of the concept of middle class and a description of the economic situation in Russia during the transition period. Particular attention is given to variations in the distribution of Russian incomes and the estimated importance of the middle class. The second part of the book focuses on the link between the middle class and income bipolarization. The third and last section of the book uses the semiparametric "mixture model" to discover how many different groups may be derived from the income distribution in Russia, as well as what the main socio-economic and demographic characteristics of those groups are. The mobility of households into and out of the middle class during the transition period is also studied in hopes of determining the factors that contribute to such mobility. Using rigorous empirical methods, this volume sheds light on a relatively unstudied economic group and provides insight for countries which are about to enter a transition period. As such, this book will be of great interest to researchers in economics and inequality as well as professionals and practitioners working with international organizations.

This book explores the US economy from 1960 to 2010 using a more Keynsian, Cowles model approach, which the author argues has substantial advantages over the vector autoregression (VAR) and dynamic stochastic general equilibrium (DSGE) models used almost exclusively today. Heim presents a robust argument in favor of the Cowles model as an answer to the pressing, unresolved methodological question of how to accurately model the macroeconomy so that policymakers can reliably use these models to assist their decision making. Thirty-eight behavioral equations, describing determinants of variables such as consumption, taxes, and government spending, are connected by eighteen identities to construct a comprehensive model of the real US economy that Heim then tests across four different time periods to ensure that results are consistent. This comprehensive demonstration of the value of a long-ignored model provides overwhelming evidence that the more Keynesian (Cowles) structural models outperform VAR and DSGE, and therefore should be the models of choice in future macroeconomic studies.

Microeconometrics Using Stata, Second Edition is an invaluable reference for researchers and students interested in applied microeconometric methods. Like previous editions, this text covers all the classic microeconometric techniques ranging from linear models to instrumental-variables regression to panel-data estimation to nonlinear models such as probit, tobit, Poisson, and choice models. Each of these discussions has been updated to show the most modern implementation in Stata, and many include additional explanation of the underlying methods. In addition, the authors introduce readers to performing simulations in Stata and then use simulations to illustrate methods in other parts of the book. They even teach you how to code your own estimators in Stata. The second edition is greatly expanded—the new material is so extensive that the text now comprises two volumes. In addition to the classics, the book now teaches recently developed econometric methods and the methods newly added to Stata. Specifically, the book includes entirely new chapters on duration models randomized control trials and exogenous treatment effects endogenous treatment effects models for endogeneity and heterogeneity, including finite mixture models, structural equation models, and nonlinear mixed-effects models spatial autoregressive models semiparametric regression lasso for prediction and inference Bayesian analysis Anyone interested in learning classic and modern econometric methods will find this the perfect companion. And those who apply these methods to their own data will return to this reference over and over as they need to implement the various techniques described in this book.

This edited volume, with contributions by area experts, offers discussions on a range of evolving topics in economics and social development. At center are important issues central to sustainable development, economic growth, technological change, the economics of climate change, commodity markets, long wave theory, non-linear dynamic models, and boom-bust cycles. This is an excellent reference for academic and professional economists interested in emerging areas of empirical macroeconomics and finance. For policy makers and curious readers alike, it is also an outstanding introduction to the economic thinking of those who seek a holistic and all-compassing approach in economic theory and policy. Looking into new data and methodology, this book offers fresh approaches in a post-crisis environment. Set in a profound understanding of the diverse currents within the many traditions of economic thought, this book pushes the established frontiers of economic thinking. It is dedicated to a leading scholar in the areas covered in this book, Willi Semmler.

This is the second volume in a two-part series on frontiers in regional research. It identifies methodological advances as well as trends and future developments in regional systems modelling and open science. Building on recent methodological and modelling advances, as well as on extensive policy-analysis experience, top international regional scientists identify and evaluate emerging new conceptual and methodological trends and directions in regional research. Topics such as dynamic interindustry modelling, computable general equilibrium models, exploratory spatial data analysis, geographic information science, spatial econometrics and other advanced methods are the central focus of this book. The volume provides insights into the latest developments in object orientation, open source, and workflow systems, all in support of open science. It will appeal to a wide readership, from regional scientists and economists to geographers, quantitatively oriented regional planners and other related disciplines. It offers a source of relevant information for academic researchers and policy analysts in government, and is also suitable for advanced teaching courses on regional and spatial science, economics and political science.

This volume is a collection of methodological developments and applications of simulation-based methods that were presented at a workshop at Louisiana State University in November, 2009. The first two papers are extensions of the GHK simulator: one reconsiders the computation of the probabilities in a discrete choice model while another example uses an adaptive version of sparse-grids integration (SGI) instead of simulation. Two studies are focused specifically on the methodology: the first compares the performance of the maximum-simulated likelihood (MSL) approach with a proposed composite marginal likelihood (CML) approach in multivariate ordered-response situations, while the second examines methods of testing for the presence of heterogeneity in the heterogeneity model. Further topics examined include: education savings accounts, parent contributions and education attainment; estimating the effect of exchange rate flexibility on financial account openness; estimating a fractional response model with a count endogenous regressor; and modelling and forecasting volatility in a bayesian approach.

This book presents recent research on robustness in econometrics. Robust data processing techniques - i.e., techniques that yield results minimally affected by outliers - and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.

This proceedings volume presents the latest scientific research and trends in experimental economics, with particular focus on neuroeconomics. Derived from the 2016 Computational Methods in Experimental Economics (CMEE) conference held in Szczecin, Poland, this book features research and analysis of novel computational methods in neuroeconomics. Neuroeconomics is an interdisciplinary field that combines neuroscience, psychology and economics to build a comprehensive theory of decision making. At its core, neuroeconomics analyzes the decision-making process not only in terms of external conditions or psychological aspects, but also from the neuronal point of view by examining the cerebral conditions of decision making. The application of IT enhances the possibilities of conducting such analyses. Such studies are now performed by software that provides interaction among all the participants and possibilities to register their reactions more accurately. This book examines some of these applications and methods. Featuring contributions on both theory and application, this book is of interest to researchers, students, academics and professionals interested in experimental economics, neuroeconomics and behavioral economics.

This book examines discrete dynamical systems with memory-nonlinear systems that exist extensively in biological organisms and financial and economic organizations, and time-delay systems that can be discretized into the memorized, discrete dynamical systems. It book further discusses stability and bifurcations of time-delay dynamical systems that can be investigated through memorized dynamical systems as well as bifurcations of memorized nonlinear dynamical systems, discretization methods of time-delay systems, and periodic motions to chaos in nonlinear time-delay systems. The book helps readers find analytical solutions of MDS, change traditional perturbation analysis in time-delay systems, detect motion complexity and singularity in MDS; and determine stability, bifurcation, and chaos in any time-delay system.

This book is an extension of the author's first book and serves as a guide and manual on how to specify and compute 2-, 3-, and 4-Event Bayesian Belief Networks (BBN). It walks the learner through the steps of fitting and solving fifty BBN numerically, using mathematical proof. The author wrote this book primarily for inexperienced learners as well as professionals, while maintaining a proof-based academic rigor. The author's first book on this topic, a primer introducing learners to the basic complexities and nuances associated with learning Bayes' theorem and inverse probability for the first time, was meant for non-statisticians unfamiliar with the theorem-as is this book. This new book expands upon that approach and is meant to be a prescriptive guide for building BBN and executive decision-making for students and professionals; intended so that decision-makers can invest their time and start using this inductive reasoning principle in their decision-making processes. It highlights the utility of an algorithm that served as the basis for the first book, and includes fifty 2-, 3-, and 4-event BBN of numerous variants.

This book presents an empirical investigation into the relationship between companies' short-term response to capital and labor market frictions and performance. Two different kinds of performance measures are considered, namely innovation performance and firm performance. The author focuses on two major topics: first, on the relation between innovation performance and the use of trade credit. Second, on the relation between firm performance and the use of temporary employment. The use of in-depth firm-level data and state-of-the-art microeconometric methods provide the scientific rigor to this important investigation to answer the questions currently being confronted by many companies in different economies.

This book provides a quantitative framework for the analysis of conflict dynamics and for estimating the economic costs associated with civil wars. The author develops modified Lotka-Volterra equations to model conflict dynamics, to yield realistic representations of battle processes, and to allow us to assess prolonged conflict traps. The economic costs of civil wars are evaluated with the help of two alternative methods: Firstly, the author employs a production function to determine how the destruction of human and physical capital stocks undermines economic growth in the medium term. Secondly, he develops a synthetic control approach, where the cost is obtained as the divergence of actual economic activity from a hypothetical path in the absence of civil war. The difference between the two approaches gives an indication of the adverse externalities impinging upon the economy in the form of institutional destruction. By using detailed time-series regarding battle casualties, local socio-economic indicators, and capital stock destruction during the Greek Civil War (1946-1949), a full-scale application of the above framework is presented and discussed.

The three volumes of the "Collected Scientific Works of David Cass" are ordered chronologically, which happens to coincide with the development of the three major advances in Cass' research agenda, the development of the neoclassical growth model, the discovery of sunspot equilibria, and the analysis of models of market incompleteness. This volume covers the period from the middle 1980's through the end of Cass' life in 2008. Cass' research during this period included definitive papers showing that competitive equilibrium is generically indeterminate when markets are incomplete, and on the relationship between market incompleteness and the existence of sunspot equilibrium. This period also saw the follow-on papers addressing the issue of how financial innovation affects economic welfare, showing in particular that innovation can lead to welfare losses as well as gains, depending on the nature of the innovation.

The three volumes of the "Collected Scientific Works of David Cass" are ordered chronologically, which happens to coincide with the development of the three major advances in Cass' research agenda, the development of the neoclassical growth model, the discovery of sunspot equilibria, and the analysis of models of market incompleteness. This volume consists of Cass' early work from his time in graduate school at Stanford University, studying under Hirofumi Uzawa, and as an assistant professor at Yale's Cowles Commission, and his tenure at Carnegie Mellon University's Graduate School of Industrial Administration. The work in this volume focuses primarily on Cass' contributions to what is now known as the Ramsey-Cass-Kooopmans neoclassical growth model, and the development of what is now known as the Cass criterion for determining whether intertemporal allocations are efficient. This period also includes Cass' early work on overlapping generation's models, asset pricing models, and methodological contributions in dynamic systems applications in economics.

The three volumes of the "The Collected Scientific Works of David Cass" are ordered chronologically, which happens to coincide with the development of the three major advances in Cass' research agenda, the development of the neoclassical growth model, the discovery of sunspot equilibria, and the analysis of models of market incompleteness. This volume consists of the work Cass completed after leaving Carnegie Mellon for the University of Pennsylvania's Economics Department (where he remained for the rest of his career). The work during this period encompasses his well-known collaboration with Karl Shell and Yves Balasko on overlapping generations models, and his development with Karl of the notion of 'sunspot equilibria' - rational expectations equilibria which are essentially self-fulfilling prophecies. This period also saw the beginnings of Cass' pioneering research into the theory of incomplete markets, which grew naturally form his early interest in models of asset pricing, and includes the paper which developed what is now known as the Cass trick for analyzing incomplete markets models.

Central Bank Balance Sheet and Real Business Cycles argues that a deeper comprehension of changes to the central bank balance sheet can lead to more effective policymaking. Any transaction engaged in by the central bank-issuing currency, conducting foreign exchange operations, investing its own funds, intervening to provide emergency liquidity assistance and carrying out monetary policy operations-influences its balance sheet. Despite this, many central banks throughout the world have largely ignored balance sheet movements, and have instead focused on implementing interest rates. In this book, Mustapha Abiodun Akinkunmi highlights the challenges and controversies faced by central banks in the past and present when implementing policies, and analyzes the links between these policies, the central bank balance sheet, and the consequences to economies as a whole. He argues that the composition and evolution of the central bank balance sheet provides a valuable basis for understanding the needs of an economy, and is an important tool in developing strategies that would most effectively achieve policy goals. This book is an important resource for anyone interested in monetary policy or whose work is affected by the actions of the policies of central banks.

This book explores the role of national fiscal policies in a selected group of Euro-area countries under the European Economic and Monetary Union (EMU). In particular, the authors characterize the response of output to fiscal consolidations and expansions in the small Euro-area open economies affected by high public and private debt. It is shown that the macroeconomic outcome of fiscal shocks is strongly related to debt levels. The Euro-area countries included in the investigation are Greece, Ireland, Italy, the Netherlands, Spain, and Portugal, over the sample period 1999-2016, i.e., the EMU period. The main econometric tools used in this research are structural vector autoregressive (VAR) models, including panel VAR models. The available literature relating to the subject is also fully reviewed. A further closely investigated topic is the potential spillover effects of German fiscal policies on the selected small Euro-area economies. Moreover, in the perspective of the evolution of the Euro Area towards a full Monetary and Fiscal Union, the authors study the effects of area-wide government spending shocks on aggregate output and other macroeconomic variables during the EMU period. The closing chapter of the book considers evidence on the consequences of austerity policies for European labour markets during recent years.

Within the subprime crisis (2007) and the recent global financial crisis of 2008-2009, we have observed significant decline, corrections and structural changes in most US and European financial markets. Furthermore, it seems that this crisis has been rapidly transmitted toward the most developed and emerging countries and has strongly affected the whole economy. This volume aims to present recent researches in linear and nonlinear modelling of economic and financial time-series. The several discussions of empirical results of its chapters clearly help to improve the understanding of the financial mechanisms inherent to this crisis. They also yield an important overview on the sources of the financial crisis and its main economic and financial consequences. The book provides the audience a comprehensive understanding of financial and economic dynamics in various aspects using modern financial econometric methods. It addresses the empirical techniques needed by economic agents to analyze the dynamics of these markets and illustrates how they can be applied to the actual data. It also presents and discusses new research findings and their implications.

Ranked Set Sampling: 65 Years Improving the Accuracy in Data Gathering is an advanced survey technique which seeks to improve the likelihood that collected sample data presents a good representation of the population and minimizes the costs associated with obtaining them. The main focus of many agricultural, ecological and environmental studies is the development of well designed, cost-effective and efficient sampling designs, giving RSS techniques a particular place in resolving the disciplinary problems of economists in application contexts, particularly experimental economics. This book seeks to place RSS at the heart of economic study designs.

The book addresses the problem of calculation of d-dimensional integrals (conditional expectations) in filter problems. It develops new methods of deterministic numerical integration, which can be used to speed up and stabilize filter algorithms. With the help of these methods, better estimates and predictions of latent variables are made possible in the fields of economics, engineering and physics. The resulting procedures are tested within four detailed simulation studies.

This book grows from a conference on the state of the art and recent advances in Efficiency and Productivity. Papers were commissioned from leading researchers in the field, and include eight explorations into the analytical foundations of efficiency and productivity analysis. Chapters on modeling advances include reverse directional distance function, a new method for estimating technological production possibilities, a new distance function called a loss distance function, an analysis of productivity and price recovery indices, the relation of technical efficiency measures to productivity measures, the implications for benchmarking and target setting of imposing weight restrictions on DEA models, weight restrictions in a regulatory setting, and the Principle of Least Action. Chapters on empirical applications include a study of innovative firms that use innovation inputs to produce innovation outputs, a study of the impact of potential "coopetition" or cooperation among competitors on the financial performance of European automobile plants, using SFA to estimate the eco-efficiency of dairy farms in Spain, a DEA bankruptcy prediction model, a combined stochastic cost frontier analysis model/mixture hazard model, the evolution of energy intensity in nine Spanish manufacturing industries, and the productivity of US farmers as they age.