Meta-Regression Analysis in Economics and Business is the first text devoted to the meta-regression analysis (MRA) of economics and business research.

The purpose of this book is to introduce novice researchers to the tools of meta-analysis and meta-regression analysis and to summarize the state of the art for existing practitioners. Meta-regression analysis addresses the rising "Tower of Babel" that current economics and business research has become. Meta-analysis is the statistical analysis of previously published, or reported, research findings on a given hypothesis, empirical effect, phenomenon, or policy intervention. It is a systematic review of all the relevant scientific knowledge on a specific subject and is an essential part of the evidence-based practice movement in medicine, education and the social sciences. However, research in economics and business is often fundamentally different from what is found in the sciences and thereby requires different methods for its synthesis—meta-regression analysis. This book develops, summarizes, and applies these meta-analytic methods.

Meta-analysis is a formal synthesis of results and findings of scientific studies, which can assist in gaining new insights, explaining differences between results of similar studies, or determine useful directions of research. In this book we focus on the use of meta-analysis in environmental economics and related fields of study. The first part of the book covers the overall meta-approach methodology for social sciences and economics in particular. This is followed by technical and non-technical discussions of statistical and rough-set techniques for analysis. At appropriate places this is supplemented with reviews of applications in environmental economics and related fields. In the second part of the book a number of case studies show different aspects of the application of meta-analysis. The research areas considered include, among others, tourism multipliers, air pollution valuation, risk and value of life, pesticide price policy, travel time savings, and transport externality and policy issues. The benefits of the appropriate application of meta-analysis in environmental economics are a better use of existing information and knowledge, removal of some of the subjectivity from analysis and forecasting, and greater clarity as to where future efforts in environmental economic analysis can most gainfully be deployed.

Understanding Regression Analysis: An Introductory Guide by Larry D. Schroeder, David L. Sjoquist, and Paula E. Stephan presents the fundamentals of regression analysis, from its meaning to uses, in a concise, easy-to-read, and non-technical style. It illustrates how regression coefficients are estimated, interpreted, and used in a variety of settings within the social sciences, business, law, and public policy. Packed with applied examples and using few equations, the book walks readers through elementary material using a verbal, intuitive interpretation of regression coefficients, associated statistics, and hypothesis tests. The Second Edition features updated examples and new references to modern software output.

Richard B. Freeman and James L. Medoff’s now classic 1984 book What Do Unions Do? stimulated an enormous theoretical and empirical literature on the economic impact of trade unions. Trade unions continue to be a significant feature of many labor markets, particularly in developing countries, and issues of labor market regulations and labor institutions remain critically important to researchers and policy makers. The relations between unions and management can range between cooperation and conflict; unions have powerful offsetting wage and non-wage effects that economists and other social scientists have long debated. Do the benefits of unionism exceed the costs to the economy and society writ large, or do the costs exceed the benefits? The Economics of Trade Unions offers the first comprehensive review, analysis and evaluation of the empirical literature on the microeconomic effects of trade unions using the tools of meta-regression analysis to identify and quantify the economic impact of trade unions, as well as to correct research design faults, the effects of selection bias and model misspecification. This volume makes use of a unique dataset of hundreds of empirical studies and their reported estimates of the microeconomic impact of trade unions. Written by three authors who have been at the forefront of this research field (including the co-author of the original volume, What Do Unions Do?), this book offers an overview of a subject that is of huge importance to scholars of labor economics, industrial and employee relations, and human resource management, as well as those with an interest in meta-analysis.

This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-analysis; and meta-analysis of diagnostic studies.

Group liability is often portrayed as the key innovation that led to the explosion of the microcredit movement, which started with the Grameen Bank in the 1970s and continues on today with hundreds of institutions around the world. Group lending claims to improve repayment rates and lower transaction costs when lending to the poor by providing incentives for peers to screen, monitor, and enforce each other's loans. However, some argue that group liability creates excessive pressure and discourages good clients from borrowing, jeopardizing both growth and sustainability. Therefore, it remains unclear whether group liability improves the lender's overall profitability and the poor's access to financial markets. The authors worked with a bank in the Philippines to conduct a field experiment to examine these issues. They randomly assigned half of the 169 pre-existing group liability 'centers' of approximately twenty women to individual-liability centers (treatment) and kept the other half as-is with group liability (control). We find that the conversion to individual liability does not affect the repayment rate, and leads to higher growth in center size by attracting new clients.

This collection provides detailed descriptions of both standard and advanced meta-analytic methods and their implementation in Stata. Readers will gain access to the statistical methods behind the rapid increase in the number of meta-analyses reported in the social science and medical literature. The book shows how to conduct and interpret meta-analyses as well as produce highly flexible graphical displays. Using meta-regression, it examines reasons for between-study variability in effect estimates. The book also employs advanced methods for the meta-analysis of diagnostic test accuracy studies, dose-response meta-analysis, meta-analysis with missing data, and multivariate meta-analysis.

A practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective. Often a single study will not provide the answers and it is desirable to synthesise evidence from multiple sources, usually randomised controlled trials. This book takes an approach to evidence synthesis that is specifically intended for decision making when there are two or more treatment alternatives being evaluated, and assumes that the purpose of every synthesis is to answer the question "for this pre-identified population of patients, which treatment is 'best'?" A comprehensive, coherent framework for network meta-analysis (mixed treatment comparisons) is adopted and estimated using Bayesian Markov Chain Monte Carlo methods implemented in the freely available software WinBUGS. Each chapter contains worked examples, exercises, solutions and code that may be adapted by readers to apply to their own analyses. This book can be used as an introduction to evidence synthesis and network meta-analysis, its key properties and policy implications. Examples and advanced methods are also presented for the more experienced reader. Methods used throughout this book can be applied consistently: model critique and checking for evidence consistency are emphasised. Methods are based on technical support documents produced for NICE Decision Support Unit, which support the NICE Methods of Technology Appraisal. Code presented is also the basis for the code used by the ISPOR Task Force on Indirect Comparisons. Includes extensive carefully worked examples, with thorough explanations of how to set out data for use in WinBUGS and how to interpret the output. Network Meta-Analysis for Decision Making will be of interest to decision makers, medical statisticians, health economists, and anyone involved in Health Technology Assessment including the pharmaceutical industry.

A comprehensive analysis of merger outcomes based on all empirical studies, with an assessment of the effectiveness of antitrust policy toward mergers. In recent decades, antitrust investigations and cases targeting mergers—including those involving Google, Ticketmaster, and much of the domestic airline industry—have reshaped industries and changed business practices profoundly. And yet there has been a relative dearth of detailed evaluations of the effects of mergers and the effectiveness of merger policy. In this book, John Kwoka, a noted authority on industrial organization, examines all reliable empirical studies of the effect of specific mergers and develops entirely new information about the policies and remedies of antitrust agencies regarding these mergers. Combined with data on outcomes, this policy information enables analysis of, and creates new insights into, mergers, merger policies, and the effectiveness of remedies in preventing anticompetitive outcomes. After an overview of mergers, merger policy, and a common approach to merger analysis, Kwoka offers a detailed analysis of the studied mergers, relevant policies, and chosen remedies. Kwoka finds, first and foremost, that most of the studied mergers resulted in competitive harm, usually in the form of higher product prices but also with respect to various non-price outcomes. Other important findings include the fact that joint ventures and code sharing arrangements do not result in such harm and that policies intended to remedy mergers—especially conduct remedies—are not generally effective in restraining price increases. The book's uniquely comprehensive analysis advances our understanding of merger decisions and policies, suggests policy improvements for competition agencies and remedies, and points the way to future research.