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The ABCs of RBCs
An Introduction to Dynamic Macroeconomic Models
George McCandless
Harvard University Press, 2008

The ABCs of RBCs is the first book to provide a basic introduction to Real Business Cycle (RBC) and New-Keynesian models. These models argue that random shocks—new inventions, droughts, and wars, in the case of pure RBC models, and monetary and fiscal policy and international investor risk aversion, in more open interpretations—can trigger booms and recessions and can account for much of observed output volatility.

George McCandless works through a sequence of these Real Business Cycle and New-Keynesian dynamic stochastic general equilibrium models in fine detail, showing how to solve them, and how to add important extensions to the basic model, such as money, price and wage rigidities, financial markets, and an open economy. The impulse response functions of each new model show how the added feature changes the dynamics.

The ABCs of RBCs is designed to teach the economic practitioner or student how to build simple RBC models. Matlab code for solving many of the models is provided, and careful readers should be able to construct, solve, and use their own models.

In the tradition of the “freshwater” economic schools of Chicago and Minnesota, McCandless enhances the methods and sophistication of current macroeconomic modeling.

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Accounting for Tastes
Gary S. Becker
Harvard University Press, 1996
Economists generally accept as a given the old adage that there’s no accounting for tastes. Nobel Laureate Gary Becker disagrees, and in this lively new collection he confronts the problem of preferences and values: how they are formed and how they affect our behavior. He argues that past experiences and social influences form two basic capital stocks: personal and social. He then applies these concepts to assessing the effects of advertising, the power of peer pressure, the nature of addiction, and the function of habits. This framework promises to illuminate many other realms of social life previously considered off-limits by economists.
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Advanced Econometrics
Takeshi Amemiya
Harvard University Press, 1985

Advanced Econometrics is both a comprehensive text for graduate students and a reference work for econometricians. It will also be valuable to those doing statistical analysis in the other social sciences. Its main features are a thorough treatment of cross-section models, including qualitative response models, censored and truncated regression models, and Markov and duration models, as well as a rigorous presentation of large sample theory, classical least-squares and generalized least-squares theory, and nonlinear simultaneous equation models.

Although the treatment is mathematically rigorous, the author has employed the theorem-proof method with simple, intuitively accessible assumptions. This enables readers to understand the basic structure of each theorem and to generalize it for themselves depending on their needs and abilities. Many simple applications of theorems are given either in the form of examples in the text or as exercises at the end of each chapter in order to demonstrate their essential points.

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Big Data for Twenty-First-Century Economic Statistics
Edited by Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro
University of Chicago Press, 2022
The papers in this volume analyze the deployment of Big Data to solve both existing and novel challenges in economic measurement. 

The existing infrastructure for the production of key economic statistics relies heavily on data collected through sample surveys and periodic censuses, together with administrative records generated in connection with tax administration. The increasing difficulty of obtaining survey and census responses threatens the viability of existing data collection approaches. The growing availability of new sources of Big Data—such as scanner data on purchases, credit card transaction records, payroll information, and prices of various goods scraped from the websites of online sellers—has changed the data landscape. These new sources of data hold the promise of allowing the statistical agencies to produce more accurate, more disaggregated, and more timely economic data to meet the needs of policymakers and other data users. This volume documents progress made toward that goal and the challenges to be overcome to realize the full potential of Big Data in the production of economic statistics. It describes the deployment of Big Data to solve both existing and novel challenges in economic measurement, and it will be of interest to statistical agency staff, academic researchers, and serious users of economic statistics.
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A Course in Econometrics
Arthur S. Goldberger
Harvard University Press, 1991

This text prepares first-year graduate students and advanced undergraduates for empirical research in economics, and also equips them for specialization in econometric theory, business, and sociology.

A Course in Econometrics is likely to be the text most thoroughly attuned to the needs of your students. Derived from the course taught by Arthur S. Goldberger at the University of Wisconsin–Madison and at Stanford University, it is specifically designed for use over two semesters, offers students the most thorough grounding in introductory statistical inference, and offers a substantial amount of interpretive material. The text brims with insights, strikes a balance between rigor and intuition, and provokes students to form their own critical opinions.

A Course in Econometrics thoroughly covers the fundamentals—classical regression and simultaneous equations—and offers clear and logical explorations of asymptotic theory and nonlinear regression. To accommodate students with various levels of preparation, the text opens with a thorough review of statistical concepts and methods, then proceeds to the regression model and its variants. Bold subheadings introduce and highlight key concepts throughout each chapter.

Each chapter concludes with a set of exercises specifically designed to reinforce and extend the material covered. Many of the exercises include real microdata analyses, and all are ideally suited to use as homework and test questions.

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The Economic Analysis of Substance Use and Abuse
An Integration of Econometric and Behavioral Economic Research
Edited by Frank J. Chaloupka, Michael Grossman, Warren K. Bickel, and Henry Saffer
University of Chicago Press, 1999
Conventional wisdom once held that the demand for addictive substances like cigarettes, alcohol, and drugs was unlike that for any other economic good and, therefore, unresponsive to traditional market forces. Recently, however, researchers from two disparate fields, economics and behavioral psychology, have found that increases in the overall price of an addictive substance can significantly reduce both the number of users and the amounts those users consume. Changes in the "full price" of addictive substances—including monetary value, time outlay, effort to obtain, and potential penalties for illegal use—yield marked variations in behavioral outcomes and demand.

The Economic Analysis of Substance Use and Abuse brings these distinctive fields of study together and presents for the first time an integrated assessment of their data and results. Unique and innovative, this multidisciplinary volume will serve as an important resource in the current debates concerning alcohol and drug use and abuse and the impacts of legalizing illicit drugs.

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The Economics of Information and Uncertainty
Edited by John J. McCall
University of Chicago Press, 1982

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Elements of Econometrics
Second Edition
Jan Kmenta
University of Michigan Press, 1997
This classic text has proven its worth in university classrooms and as a tool kit in research--selling over 40,000 copies in the United States and abroad in its first edition alone. Users have included undergraduate and graduate students of economics and business, and students and researchers in political science, sociology, and other fields where regression models and their extensions are relevant. The book has also served as a handy reference in the "real world" for people who need a clear and accurate explanation of techniques that are used in empirical research.
Throughout the book the emphasis is on simplification whenever possible, assuming the readers know college algebra and basic calculus. Jan Kmenta explains all methods within the simplest framework, and generalizations are presented as logical extensions of simple cases. And while a relatively high degree of rigor is preserved, every conflict between rigor and clarity is resolved in favor of the latter. Apart from its clear exposition, the book's strength lies in emphasizing the basic ideas rather than just presenting formulas to learn and rules to apply.
The book consists of two parts, which could be considered jointly or separately. Part one covers the basic elements of the theory of statistics and provides readers with a good understanding of the process of scientific generalization from incomplete information. Part two contains a thorough exposition of all basic econometric methods and includes some of the more recent developments in several areas.
As a textbook, Elements of Econometrics is intended for upper-level undergraduate and master's degree courses and may usefully serve as a supplement for traditional Ph.D. courses in econometrics. Researchers in the social sciences will find it an invaluable reference tool.
A solutions manual is also available for teachers who adopt the text for coursework.
Jan Kmenta is Professor Emeritus of Economics and Statistics, University of Michigan.
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Elements of Time Series Econometrics
An Applied Approach - Third Edition
Evzen Kocenda and Alexandr Cerný
Karolinum Press, 2017
A time series is a sequence of numbers collected at regular intervals over a period of time. Designed with emphasis on the practical application of theoretical tools, Elements of Time Series Econometrics is an approachable guide for the econometric analysis of time series. The text is divided into five major sections. The first section, “The Nature of Time Series,” gives an introduction to time series analysis. The next section, “Difference Equations,” describes briefly the theory of difference equations, with an emphasis on results that are important for time series econometrics. The third section, “Univariate Time Series,” presents the methods commonly used in univariate time series analysis, the analysis of time series of a single variable. The fourth section, “Multiple Time Series,” deals with time series models of multiple interrelated variables. The final section, new to this edition, is “Panel Data and Unit Root Tests” and deals with methods known as panel unit root tests that are relevant to issues of convergence. Appendices contain an introduction to simulation techniques and statistical tables.
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The End of Cheap Labour?
Industrial Transformation and "Social Upgrading" in China
Florian Butollo
Campus Verlag, 2014
The Chinese government and international observers argue that China’s economy must overcome its excessive dependence on exports if substantial growth in domestic consumption is to be achieved and sustained in the future. But this shift can only occur if China also lessens its reliance on cheap migrant labor and encourages investment in its own labor force.

In The End of Cheap Labour?, Florian Butollo investigates the recent transformation of the garment and LED lighting industries in the Pearl River Delta, China’s largest industrial hub. He reveals that industrial upgrading rarely supports improvements in working conditions and the basic employment pattern; and this failure of “social upgrading” threatens to undermine the desired rebalancing of the Chinese economy. Butollo demonstrates that the implementation of collective labor rights remains an important obstacle in the future of the Chinese growth model.
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Hard-to-Measure Goods and Services
Essays in Honor of Zvi Griliches
Edited by Ernst E. Berndt and Charles R. Hulten
University of Chicago Press, 2007

The celebrated economist Zvi Griliches’s entire career can be viewed as an attempt to advance the cause of accuracy in economic measurement. His interest in the causes and consequences of technical progress led to his pathbreaking work on price hedonics, now the principal analytical technique available to account for changes in product quality.

Hard-to-Measure Goods and Services, a collection of papers from an NBER conference held in Griliches’s honor, is a tribute to his many contributions to current economic thought. Here, leading scholars of economic measurement address issues in the areas of productivity, price hedonics, capital measurement, diffusion of new technologies, and output and price measurement in “hard-to-measure” sectors of the economy.  Furthering Griliches’s vital work that changed the way economists think about the U.S. National Income and Product Accounts, this volume is essential for all those interested in the labor market, economic growth, production, and real output.

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Histories on Econometrics, Volume 43
Marcel Boumans, Ariane Dupont-Kieffer, Dou Qin, editors
Duke University Press
This volume considers the history of econometrics, a field of economics that combines statistics, mathematics, and economic theory. Contributors scrutinize accounts of the field’s shifting boundaries and the development of a cohesive scholarly community of econometricians. These essays consider applied research and methodologies in context and connect the history of econometrics to contemporary developments in related disciplines and technologies. Analyzing the practice of econometrics around the world since its introduction in the 1920s, contributors examine the relationship between sociology and welfare in Italian econometrics, the extraordinary investment in macroeconometric models and input-output models in Japan, practices of econometrics in relation to computation and philosophy, and the recognition of unusual methodological stances in both theoretical and applied work. Reinterpreting the accepted history of econometrics allows historians to focus on new alliances, methods, and entrepreneurial models that resolve past obscurities and open up new areas for future inquiry.

Contributors: John Aldrich, Jeff E. Biddle, Olav Bjerkholt, Marcel Boumans, Chao-Hsi Huang, Robert W. Dimand, Duo Qin, Ariane Dupont-Kieffer, Hsiang-Ke Chao, Aiko Ikeo, Francisco Louçã, Mary S. Morgan, Daniela Parisi, Alain Pirotte, Charles G. Renfro, Thomas Stapleford, Sofia Terlica

Marcel Boumans is Associate Professor of Economics at the University of Amsterdam. Ariane Dupont-Kieffer is a Researcher at the French National Institute of Research on Transport and Safety. Duo Qin is Reader of Economics at the University of London.

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Identification for Prediction and Decision
Charles F. Manski
Harvard University Press, 2008

This book is a full-scale exposition of Charles Manski's new methodology for analyzing empirical questions in the social sciences. He recommends that researchers first ask what can be learned from data alone, and then ask what can be learned when data are combined with credible weak assumptions. Inferences predicated on weak assumptions, he argues, can achieve wide consensus, while ones that require strong assumptions almost inevitably are subject to sharp disagreements.

Building on the foundation laid in the author's Identification Problems in the Social Sciences (Harvard, 1995), the book's fifteen chapters are organized in three parts. Part I studies prediction with missing or otherwise incomplete data. Part II concerns the analysis of treatment response, which aims to predict outcomes when alternative treatment rules are applied to a population. Part III studies prediction of choice behavior.

Each chapter juxtaposes developments of methodology with empirical or numerical illustrations. The book employs a simple notation and mathematical apparatus, using only basic elements of probability theory.

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Identification Problems in the Social Sciences
Charles F. Manski
Harvard University Press, 1999

This book provides a language and a set of tools for finding bounds on the predictions that social and behavioral scientists can logically make from nonexperimental and experimental data. The economist Charles Manski draws on examples from criminology, demography, epidemiology, social psychology, and sociology as well as economics to illustrate this language and to demonstrate the broad usefulness of the tools.

There are many traditional ways to present identification problems in econometrics, sociology, and psychometrics. Some of these are primarily statistical in nature, using concepts such as flat likelihood functions and nondistinct parameter estimates. Manski's strategy is to divorce identification from purely statistical concepts and to present the logic of identification analysis in ways that are accessible to a wide audience in the social and behavioral sciences. In each case, problems are motivated by real examples with real policy importance, the mathematics is kept to a minimum, and the deductions on identifiability are derived giving fresh insights.

Manski begins with the conceptual problem of extrapolating predictions from one population to some new population or to the future. He then analyzes in depth the fundamental selection problem that arises whenever a scientist tries to predict the effects of treatments on outcomes. He carefully specifies assumptions and develops his nonparametric methods of bounding predictions. Manski shows how these tools should be used to investigate common problems such as predicting the effect of family structure on children's outcomes and the effect of policing on crime rates.

Successive chapters deal with topics ranging from the use of experiments to evaluate social programs, to the use of case-control sampling by epidemiologists studying the association of risk factors and disease, to the use of intentions data by demographers seeking to predict future fertility. The book closes by examining two central identification problems in the analysis of social interactions: the classical simultaneity problem of econometrics and the reflection problem faced in analyses of neighborhood and contextual effects.

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Improving the Measurement of Consumer Expenditures
Edited by Christopher D. Carroll, Thomas F. Crossley, and John Sabelhaus
University of Chicago Press, 2015
Robust and reliable measures of consumer expenditures are essential for analyzing aggregate economic activity and for measuring differences in household circumstances. Many countries, including the United States, are embarking on ambitious projects to redesign surveys of consumer expenditures, with the goal of better capturing economic heterogeneity. This is an appropriate time to examine the way consumer expenditures are currently measured, and the challenges and opportunities that alternative approaches might present.      

Improving the Measurement of Consumer Expenditures begins with a comprehensive review of current methodologies for collecting consumer expenditure data. Subsequent chapters highlight the range of different objectives that expenditure surveys may satisfy, compare the data available from consumer expenditure surveys with that available from other sources, and describe how the United States’s current survey practices compare with those in other nations.
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Introduction to Statistics and Econometrics
Takeshi Amemiya
Harvard University Press, 1994

This outstanding text by a foremost econometrician combines instruction in probability and statistics with econometrics in a rigorous but relatively nontechnical manner. Unlike many statistics texts, it discusses regression analysis in depth. And unlike many econometrics texts, it offers a thorough treatment of statistics. Although its only mathematical requirement is multivariate calculus, it challenges the student to think deeply about basic concepts.

The coverage of probability and statistics includes best prediction and best linear prediction, the joint distribution of a continuous and discrete random variable, large sample theory, and the properties of the maximum likelihood estimator. Exercises at the end of each chapter reinforce the many illustrative examples and diagrams. Believing that students should acquire the habit of questioning conventional statistical techniques, Takeshi Amemiya discusses the problem of choosing estimators and compares various criteria for ranking them. He also evaluates classical hypothesis testing critically, giving the realistic case of testing a composite null against a composite alternative. He frequently adopts a Bayesian approach because it provides a useful pedagogical framework for discussing many fundamental issues in statistical inference.

Turning to regression, Amemiya presents the classical bivariate model in the conventional summation notation. He follows with a brief introduction to matrix analysis and multiple regression in matrix notation. Finally, he describes various generalizations of the classical regression model and certain other statistical models extensively used in econometrics and other applications in social science.

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Introductory Econometrics
Arthur S. Goldberger
Harvard University Press, 1998

This is a textbook for the standard undergraduate econometrics course. Its only prerequisites are a semester course in statistics and one in differential calculus. Arthur Goldberger, an outstanding researcher and teacher of econometrics, views the subject as a tool of empirical inquiry rather than as a collection of arcane procedures. The central issue in such inquiry is how one variable is related to one or more others. Goldberger takes this to mean "How does the average value of one variable vary with one or more others?" and so takes the population conditional mean function as the target of empirical research.

The structure of the book is similar to that of Goldberger's graduate-level textbook, A Course in Econometrics, but the new book is richer in empirical material, makes no use of matrix algebra, and is primarily discursive in style. A great strength is that it is both intuitive and formal, with ideas and methods building on one another until the text presents fairly complicated ideas and proofs that are often avoided in undergraduate econometrics.

To help students master the tools of econometrics, Goldberger provides many theoretical and empirical exercises and real micro-and macroeconomic data sets. The data sets, available for download at www.hup.harvard.edu/features/golint/, deal with earnings and education, money demand, firm investment, stock prices, compensation and productivity, and the Phillips curve.

THE DATA SETS CAN BE FOUND HERE.

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The Measure of Economies
Measuring Productivity in an Age of Technological Change
Edited by Marshall B. Reinsdorf and Louise Sheiner
University of Chicago Press

Innovative new approaches for improving GDP measurement to better gauge economic productivity.

Official measures of gross domestic product (GDP) indicate that productivity growth has declined in the United States over the last two decades. This has led to calls for policy changes from pro-business tax reform to stronger antitrust measures. But are our twentieth-century economic methods actually measuring our twenty-first-century productivity?

The Measure of Economies offers a synthesis of the state of knowledge in productivity measurement at a time when many question the accuracy and scope of GDP. With chapters authored by leading economic experts on topics such as the digital economy, health care, and the environment, it highlights the inadequacies of current practices and discusses cutting-edge alternatives.

Pragmatic and forward-facing, The Measure of Economies is an essential resource not only for social scientists, but also for policymakers and business leaders seeking to understand the complexities of economic growth in a time of rapidly evolving technology.

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Measuring and Modeling Health Care Costs
Edited by Ana Aizcorbe, Colin Baker, Ernst R. Berndt, and David M. Cutler
University of Chicago Press, 2018
Health care costs represent a nearly 18% of U.S. gross domestic product and 20% of government spending. While there is detailed information on where these health care dollars are spent, there is much less evidence on how this spending affects health. 
           
The research in Measuring and Modeling Health Care Costs seeks to connect our knowledge of expenditures with what we are able to measure of results, probing questions of methodology, changes in the pharmaceutical industry, and the shifting landscape of physician practice. The research in this volume investigates, for example, obesity’s effect on health care spending, the effect of generic pharmaceutical releases on the market, and the disparity between disease-based and population-based spending measures. This vast and varied volume applies a range of economic tools to the analysis of health care and health outcomes.

Practical and descriptive, this new volume in the Studies in Income and Wealth series is full of insights relevant to health policy students and specialists alike.
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Measuring Capital in the New Economy
Edited by Carol Corrado, John Haltiwanger, and Daniel Sichel
University of Chicago Press, 2005
As the accelerated technological advances of the past two decades continue to reshape the United States' economy, intangible assets and high-technology investments are taking larger roles. These developments have raised a number of concerns, such as: how do we measure intangible assets? Are we accurately appraising newer, high-technology capital? The answers to these questions have broad implications for the assessment of the economy's growth over the long term, for the pace of technological advancement in the economy, and for estimates of the nation's wealth.

In Measuring Capital in the New Economy, Carol Corrado, John Haltiwanger, Daniel Sichel, and a host of distinguished collaborators offer new approaches for measuring capital in an economy that is increasingly dominated by high-technology capital and intangible assets. As the contributors show, high-tech capital and intangible assets affect the economy in ways that are notoriously difficult to appraise. In this detailed and thorough analysis of the problem and its solutions, the contributors study the nature of these relationships and provide guidance as to what factors should be included in calculations of different types of capital for economists, policymakers, and the financial and accounting communities alike.
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Measuring Distribution and Mobility of Income and Wealth
Raj Chetty, John N. Friedman, Janet C. Gornick, Barry Johnson, and Arthur Kennickell
University of Chicago Press, 2022
A collection of twenty-three studies that explore the latest developments in the analysis of income and wealth distribution and mobility.

Economic research is increasingly focused on inequality in the distribution of personal resources and outcomes. One aspect of inequality is mobility: are individuals locked into their respective places in this distribution? To what extent do circumstances change, either over the lifecycle or across generations? Research not only measures inequality and mobility, but also analyzes the historical, economic, and social determinants of these outcomes and the effect of public policies. This volume explores the latest developments in the analysis of income and wealth distribution and mobility. The collection of twenty-three studies is divided into five sections. The first examines observed patterns of income inequality and shifts in the distribution of earnings and in other factors that contribute to it. The next examines wealth inequality, including a substantial discussion of the difficulties of defining and measuring wealth. The third section presents new evidence on the intergenerational transmission of inequality and the mechanisms that underlie it. The next section considers the impact of various policy interventions that are directed at reducing inequality. The final section addresses the challenges of combining household-level data, potentially from multiple sources such as surveys and administrative records, and aggregate data to study inequality, and explores ways to make survey data more comparable with national income accounts data.  
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Measuring Economic Sustainability and Progress
Edited by Dale W. Jorgenson, J. Steven Landefeld, and Paul Schreyer
University of Chicago Press, 2014
Since the Great Depression, researchers and statisticians have recognized the need for more extensive methods for measuring economic growth and sustainability. The recent recession renewed commitments to closing long-standing gaps in economic measurement, including those related to sustainability and well-being.

The latest in the NBER’s influential Studies in Income and Wealth series, which has played a key role in the development of national account statistics in the United States and other nations, this volume explores collaborative solutions between academics, policy researchers, and official statisticians to some of today’s most important economic measurement challenges. Contributors to this volume extend past research on the integration and extension of national accounts to establish an even more comprehensive understanding of the distribution of economic growth and its impact on well-being, including health, human capital, and the environment. The research contributions assess, among other topics, specific conceptual and empirical proposals for extending national accounts.
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Measuring Entrepreneurial Businesses
Current Knowledge and Challenges
Edited by John Haltiwanger, Erik Hurst, Javier Miranda, and Antoinette Schoar
University of Chicago Press, 2017
Start-ups and other entrepreneurial ventures make a significant contribution to the US economy, particularly in the tech sector, where they comprise some of the largest and most influential companies. Yet for every high-profile, high-growth company like Apple, Facebook, Microsoft, and Google, many more fail. This enormous heterogeneity poses conceptual and measurement challenges for economists concerned with understanding their precise impact on economic growth.
           
Measuring Entrepreneurial Businesses brings together economists and data analysts to discuss the most recent research covering three broad themes. The first chapters isolate high- and low-performing entrepreneurial ventures and analyze their roles in creating jobs and driving innovation and productivity. The next chapters turn the focus on specific challenges entrepreneurs face and how they have varied over time, including over business cycles. The final chapters explore core measurement issues, with a focus on new data projects under development that may improve our understanding of this dynamic part of the economy.
 
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NBER Macroeconomics Annual 2017
Volume 32
Edited by Jonathan A. Parker and Martin Eichenbaum
University of Chicago Press Journals, 2018
Volume 32 of the NBER Macroeconomics Annual features six theoretical and empirical studies of important issues in contemporary macroeconomics, and a keynote address by former IMF chief economist Olivier Blanchard. In one study, SeHyoun Ahn, Greg Kaplan, Benjamin Moll, Thomas Winberry, and Christian Wolf examine the dynamics of consumption expenditures in non-representative-agent macroeconomic models. In another, John Cochrane asks which macro models most naturally explain the post-financial-crisis macroeconomic environment, which is characterized by the co-existence of low and nonvolatile inflation rates, near-zero short-term interest rates, and an explosion in monetary aggregates. Manuel Adelino, Antoinette Schoar, and Felipe Severino examine the causes of the lending boom that precipitated the recent U.S. financial crisis and Great Recession. Steven Durlauf and Ananth Seshadri investigate whether increases in income inequality cause lower levels of economic mobility and opportunity. Charles Manski explores the formation of expectations, considering the efficacy of directly measuring beliefs through surveys as an alternative to making the assumption of rational expectations. In the final research paper, Efraim Benmelech and Nittai Bergman analyze the sharp declines in debt issuance and the evaporation of market liquidity that coincide with most financial crises. Blanchard’s keynote address discusses which distortions are central to understanding short-run macroeconomic fluctuations.
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New Developments in Productivity Analysis
Edited by Charles R. Hulten, Edwin R. Dean, and Michael J. Harper
University of Chicago Press, 2001
The productivity slowdown of the 1970s and 1980s and the resumption of productivity growth in the 1990s have provoked controversy among policymakers and researchers. Economists have been forced to reexamine fundamental questions of measurement technique. Some researchers argue that econometric approaches to productivity measurement usefully address shortcomings of the dominant index number techniques while others maintain that current productivity statistics underreport damage to the environment. In this book, the contributors propose innovative approaches to these issues. The result is a state-of-the-art exposition of contemporary productivity analysis.

Charles R. Hulten is professor of economics at the University of Maryland. He has been a senior research associate at the Urban Institute and is chair of the Conference on Research in Income and Wealth of the National Bureau of Economic Research. Michael Harper is chief of the Division of Productivity Research at the Bureau of Labor Statistics. Edwin R. Dean, formerly associate commissioner for Productivity and Technology at the Bureau of Labor Statistics, is adjunct professor of economics at The George Washington University.
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Rational Expectations and Econometric Practice
Volume 1
Robert E. Lucas Jr. and Thomas J. Sargent, Editors
University of Minnesota Press, 1981

Rational Expectations and Econometric Practice was first published in 1981. Minnesota Archive Editions uses digital technology to make long-unavailable books once again accessible, and are published unaltered from the original University of Minnesota Press editions.

Assumptions about how people form expectations for the future shape the properties of any dynamic economic model. To make economic decisions in an uncertain environment people must forecast such variables as future rates of inflation, tax rates, government subsidy schemes and regulations. The doctrine of rational expectations uses standard economic methods to explain how those expectations are formed.

This work collects the papers that have made significant contributions to formulating the idea of rational expectations. Most of the papers deal with the connections between observed economic behavior and the evaluation of alternative economic policies.

Robert E. Lucas, Jr., is professor of economics at the University of Chicago. Thomas J. Sargent is professor of economics at the University of Minnesota and adviser to the Federal Reserve Bank of Minnesota.

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A Rational Expectations Approach to Macroeconometrics
Testing Policy Ineffectiveness and Efficient-Markets Models
Frederic S. Mishkin
University of Chicago Press, 1983
A Rational Expectations Approach to Macroeconometrics pursues a rational expectations approach to the estimation of a class of models widely discussed in the macroeconomics and finance literature: those which emphasize the effects from unanticipated, rather than anticipated, movements in variables. In this volume, Fredrick S. Mishkin first theoretically develops and discusses a unified econometric treatment of these models and then shows how to estimate them with an annotated computer program.
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R&D and Productivity
The Econometric Evidence
Zvi Griliches
University of Chicago Press, 1998
Zvi Griliches, a world-renowned pioneer in the field of productivity growth, has compiled in a single volume his pathbreaking research on R&D and productivity. Griliches addresses the relationship between research and development (R&D) and productivity, one of the most complex yet vital issues in today's business world. Using econometric techniques, he establishes this connection and measures its magnitude for firm-, industry-, and economy-level data.

Griliches began his studies of productivity growth during the 1950s, adding a variable of "knowledge stock" to traditional production function models, and his work has served as the point of departure for much of the research into R&D and productivity. This collection of essays documents both Griliches's distinguished career as well as the history of this line of thought.

As inputs into production increasingly taking the form of "intellectual capital" and new technologies that are not as easily measured as traditional labor and capital, the methods Griliches has refined and applied to R&D become crucial to understanding today's economy.

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Risk Quantification and Allocation Methods for Practitioners
Jaume Belles-Sampers, Montserrat Guillén, and Miguel Santolino
Amsterdam University Press, 2017
Risk Quantification and Allocation Methods for Practitioners offers a practical approach to risk management in the financial industry. This in-depth study provides quantitative tools to better describe qualitative issues, as well as clear explanations of how to transform recent theoretical developments into computational practice, and key tools for dealing with the issues of risk measurement and capital allocation.
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A Solutions Manual for General Equilibrium, Overlapping Generations Models, and Optimal Growth Theory
Truman F. Bewley
Harvard University Press, 2011
This Solutions Manual contains answers to most of the problems in General Equilibrium, Overlapping Generations Models, and Optimal Growth Theory. Truman F. Bewley’s indispensable textbook—a cornerstone of courses on microeconomics, general equilibrium theory, and mathematical economics—covers the main premises behind insurance, capital theory, growth theory, and social security. Detailed explanations provide guidance to advanced undergraduate and graduate students, leading to in-depth understanding of Bewley’s unified approach to macroeconomics theory.
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Solutions Manual to Elements of Econometrics
Jan Kmenta
University of Michigan Press, 1997

The Solutions Manual to Elements of Econometrics, Second Edition provides chapter solutions to the exercises in the college textbook: Elements of Econometrics, Second Edition by Jan Kmenta.

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Specification, Estimation, and Analysis of Macroeconomic Models
Ray Fair
Harvard University Press, 1984

This book gives a practical, applications-oriented account of the latest techniques for estimating and analyzing large, nonlinear macroeconomic models. Ray Fair demonstrates the application of these techniques in a detailed presentation of several actual models, including his United States model, his multicountry model, Sargent's classical macroeconomic model, autoregressive and vector autoregressive models, and a small (twelve equation) linear structural model. He devotes a good deal of attention to the difficult and often neglected problem of moving from theoretical to econometric models. In addition, he provides an extensive discussion of optimal control techniques and methods for estimating and analyzing rational expectations models.

A computer program that handles all the techniques in the book is available from the author, making it possible to use the techniques with little additional programming. The book presents the logic of this program. A smaller program for personal microcomputers for analysis of Fair's United States model is available from Urban Systems Research & Engineering, Inc. Anyone wanting to learn how to use large macroeconomic models, including researchers, graduate students, economic forecasters, and people in business and government both in the United States and abroad, will find this an essential guidebook.

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Spectral Methods in Econometrics
George S. Fishman
Harvard University Press, 1969


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