As conceived by the founders of the Econometric Society, econometrics is a field that uses economic theory and statistical methods to address empirical problems in economics. It is a tool for empirical discovery and policy analysis. The chapters in this volume embody this vision and either implement it directly or provide the tools for doing so. This vision is not shared by those who view econometrics as a branch of statistics rather than as a distinct field of knowledge that designs methods of inference from data based on models of human choice ...
The Handbook is a definitive reference source and teaching aid for econometricians. It examines models, estimation theory, data analysis and field applications in econometrics.
As conceived by the founders of the Econometric Society, econometrics is a field that uses economic theory and statistical methods to address empirical problems in economics. It is a tool for empirical discovery and policy analysis. The chapters in this volume embody this vision and either implement it directly or provide the tools for doing so. This vision is not shared by those who view econometrics as a branch of statistics rather than as a distinct field of knowledge that designs methods of inference from data based on models of human choice behavior and social interactions. All of the essays in this volume and its companion volume 6B offer guidance to the practitioner on how to apply the methods they discuss to interpret economic data. The authors of the chapters are all leading scholars in the fields they survey and extend.*Part of the renowned Handbooks in Economics Series*Updates and expands the exisiting Handbook of Econometrics volumes*An invaluable reference written by some of the world's leading econometricians.
In the 18th century, statisticians sometimes worked as consultants to gamblers. In order to answer questions like "If a fair coin is flipped 100 times, what is the probability of getting 60 or more heads?", Abraham de Moivre discovered the so-called "normal curve". Independently, Pierre-Simon Laplace derived the central limit theorem, where the normal distribution acts as the limit for the distribution of the sample mean. Nowadays, statisticians sometimes work as consultants for economists, to whom the normal distribution is far from a satisfactory model. For example, one may need to model large-impact financial events in order to to answer questions like "What is the probability of getting into a crisis period similar to the credit squeeze in 2007 in the coming 10 years?". At first glance, estimating the chances of events that rarely happen or even have never happened before sounds like a "mission impossible". The development of Extreme Value Theory (EVT) shows that it is in fact possible to achieve this goal. Different from the central limit theorem, Extreme Value Theory starts from the limit distribution of the sample maximum. Initiated by M. Frechet, R. Fisher and R. von Mises, the limit theory completed by B. Gnedenko, gave the fundamental assumption in EVT, the "extreme value condition". Statistically, the extreme value condition provides a semi-parametric model for the tails of distribution functions. Therefore it can be applied to evaluate the rare events. On the other hand, since the assumption is rather general and natural, the semi-parametric model can have extensive applications in numerous felds.
Behavioral economics provides a rich set of explicit models of non-classical preferences and belief formation which can be used to estimate structural models of decision making. At the same time, experimental approaches allow the researcher to exogenously vary components of the decision making environment. The synergies between behavioral and experimental economics provide a natural setting for the estimation of structural models. This Element will cover examples supporting the following arguments 1) Experimental data allows the researcher to estimate structural models under weaker assumptions and can simplify their estimation, 2) many popular models in behavioral economics can be estimated without any programming skills using existing software, 3) experimental methods are useful to validate structural models. This Element aims to facilitate adoption of structural modelling by providing Stata codes to replicate some of the empirical illustrations that are presented. Examples covered include estimation of outcome-based preferences, belief-dependent preferences and risk preferences.
Applied Mathematics in Engineering and Reliability contains papers presented at the International Conference on Applied Mathematics in Engineering and Reliability (ICAMER 2016, Ho Chi Minh City, Viet Nam, 4-6 May 2016). The book covers a wide range of topics within mathematics applied in reliability, risk and engineering, including:- Risk and Relia
An invaluable account of how auctions workâand how to make them work Few forms of market exchange intrigue economists as do auctions, whose theoretical and practical implications are enormous. John Kagel and Dan Levin, complementing their own distinguished research with papers written with other specialists, provide a new focus on common value auctions and the "winner's curse." In such auctions the value of each item is about the same to all bidders, but different bidders have different information about the underlying value. Virtually all auctions have a common value element; among the burgeoning modern-day examples are those organized by Internet companies such as eBay. Winners end up cursing when they realize that they won because their estimates were overly optimistic, which led them to bid too much and lose money as a result. The authors first unveil a fresh survey of experimental data on the winner's curse. Melding theory with the econometric analysis of field data, they assess the design of government auctions, such as the spectrum rights (air wave) auctions that continue to be conducted around the world. The remaining chapters gauge the impact on sellers' revenue of the type of auction used and of inside information, show how bidders learn to avoid the winner's curse, and present comparisons of sophisticated bidders with college sophomores, the usual guinea pigs used in laboratory experiments. Appendixes refine theoretical arguments and, in some cases, present entirely new data. This book is an invaluable, impeccably up-to-date resource on how auctions work--and how to make them work.
This is Volume 3 of the Handbook of Industrial Organization series (HIO). Volumes 1 & 2 published simultaneously in 1989 and many of the chapters were widely cited and appeared on graduate reading lists. Since the first volumes published, the field of industrial organization has continued to evolve and this volume fills the gaps. While the first two volumes of HIO contain much more discussion of the theoretical literature than of the empirical literature, it was representative of the field at that time. Since then, the empirical literature has flourished, while the theoretical literature has continued to grow, and this new volume reflects that change of emphasis.Thie volume is an excellent reference and teaching supplement for industrial organization or industrial economics, the microeconomics field that focuses on business behavior and its implications for both market structures and processes, and for related public policies.*Part of the renowned Handbooks in Economics series*Chapters are contributed by some of the leading experts in their fields*A source, reference and teaching supplement for industrial organizations or industrial economists
