Econometrics is an application of statistical methods to economic data in order to give empirical content to economic relationships. More precisely, it is "the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference." An introductory economics textbook describes econometrics as allowing economists "to sift through mountains of data to extract simple relationships." Jan Tinbergen is one of the two founding fathers of econometrics. The other, Ragnar Frisch, also coined the term in the sense in which it is used today.
Vernon Lomax Smith is an American economist and professor of business economics and law at Chapman University. He was formerly a professor of economics at the University of Arizona, professor of economics and law at George Mason University, and a board member of the Mercatus Center. Along with Daniel Kahneman, Smith shared the 2002 Nobel Memorial Prize in Economic Sciences for his contributions to behavioral economics and his work in the field of experimental economics. He worked to establish 'laboratory experiments as a tool in empirical economic analysis, especially in the study of alternative market mechanisms'.
Lawrence Robert Klein was an American economist. For his work in creating computer models to forecast economic trends in the field of econometrics in the Department of Economics at the University of Pennsylvania, he was awarded the Nobel Memorial Prize in Economic Sciences in 1980 specifically "for the creation of econometric models and their application to the analysis of economic fluctuations and economic policies." Due to his efforts, such models have become widespread among economists. Harvard University professor Martin Feldstein told the Wall Street Journal that Klein "was the first to create the statistical models that embodied Keynesian economics," tools still used by the Federal Reserve Bank and other central banks.
David Edward Card is a Canadian-American labour economist and the Class of 1950 Professor of Economics at the University of California, Berkeley, where he has been since 1997. He was awarded half of the 2021 Nobel Memorial Prize in Economic Sciences "for his empirical contributions to labour economics", with Joshua Angrist and Guido Imbens jointly awarded the other half.
In statistics, homogeneity and its opposite, heterogeneity, arise in describing the properties of a dataset, or several datasets. They relate to the validity of the often convenient assumption that the statistical properties of any one part of an overall dataset are the same as any other part. In meta-analysis, which combines the data from several studies, homogeneity measures the differences or similarities between the several studies.
Christopher Albert Sims is an American econometrician and macroeconomist. He is currently the John J.F. Sherrerd '52 University Professor of Economics at Princeton University. Together with Thomas Sargent, he won the Nobel Memorial Prize in Economic Sciences in 2011. The award cited their "empirical research on cause and effect in the macroeconomy".
Susan Carleton Athey is an American economist. She is the Economics of Technology Professor in the School of Humanities and Sciences at the Stanford Graduate School of Business. Prior to joining Stanford, she has been a professor at Harvard University and the Massachusetts Institute of Technology. She is the first female winner of the John Bates Clark Medal. She served as the consulting chief economist for Microsoft for six years and was a consulting researcher to Microsoft Research. She is currently on the boards of Expedia, Lending Club, Rover, Turo, Ripple, and non-profit Innovations for Poverty Action. She also serves as the senior fellow at Stanford Institute for Economic Policy Research. She is an associate director for the Stanford Institute for Human-Centered Artificial Intelligence and the director of Golub Capital Social Impact Lab.
Structural estimation is a technique for estimating deep "structural" parameters of theoretical economic models. The term is inherited from the simultaneous equations model. Structural estimation is extensively using the equations from the economics theory, and in this sense is contrasted with "reduced form estimation" and other nonstructural estimations that study the statistical relationships between the observed variables while utilizing the economics theory very lightly. The idea of combining statistical and economic models dates to mid-20th century and work of the Cowles Commission.
Joshua David Angrist is an Israeli–American economist and Ford Professor of Economics at the Massachusetts Institute of Technology. Angrist, together with Guido Imbens, was awarded the Nobel Memorial Prize in Economics in 2021 "for their methodological contributions to the analysis of causal relationships".
In statistics, econometrics, political science, epidemiology, and related disciplines, a regression discontinuity design (RDD) is a quasi-experimental pretest–posttest design that aims to determine the causal effects of interventions by assigning a cutoff or threshold above or below which an intervention is assigned. By comparing observations lying closely on either side of the threshold, it is possible to estimate the average treatment effect in environments in which randomisation is unfeasible. However, it remains impossible to make true causal inference with this method alone, as it does not automatically reject causal effects by any potential confounding variable. First applied by Donald Thistlethwaite and Donald Campbell (1960) to the evaluation of scholarship programs, the RDD has become increasingly popular in recent years. Recent study comparisons of randomised controlled trials (RCTs) and RDDs have empirically demonstrated the internal validity of the design.
Matching is a statistical technique that evaluates the effect of a treatment by comparing the treated and the non-treated units in an observational study or quasi-experiment. The goal of matching is to reduce bias for the estimated treatment effect in an observational-data study, by finding, for every treated unit, one non-treated unit(s) with similar observable characteristics against which the covariates are balanced out. By matching treated units to similar non-treated units, matching enables a comparison of outcomes among treated and non-treated units to estimate the effect of the treatment reducing bias due to confounding. Propensity score matching, an early matching technique, was developed as part of the Rubin causal model, but has been shown to increase model dependence, bias, inefficiency, and power and is no longer recommended compared to other matching methods. A simple, easy-to-understand, and statistically powerful method of matching known as Coarsened Exact Matching or CEM.
The methodology of econometrics is the study of the range of differing approaches to undertaking econometric analysis.
The Center for Effective Global Action (CEGA), earlier known as the Center of Evaluation for Global Action, is a research network based at the University of California that advances global health and development through impact evaluation and economic analysis. The Center's researchers use randomized controlled trials and other rigorous forms of evaluation to promote sustainable social and economic development around the world.
There have been many criticisms of econometrics' usefulness as a discipline and perceived widespread methodological shortcomings in econometric modelling practices.
Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed. The study of why things occur is called etiology, and can be described using the language of scientific causal notation. Causal inference is said to provide the evidence of causality theorized by causal reasoning.
Guido Wilhelmus Imbens is a Dutch-American economist whose research concerns econometrics and statistics. He holds the Applied Econometrics Professorship in Economics at the Stanford Graduate School of Business at Stanford University, where he has taught since 2012.
The experimentalist approach to econometrics is a way of doing econometrics that, according to Angrist and Krueger (1999): … puts front and center the problem of identifying causal effects from specific events or situations. These events or situations are thought of as natural experiments that generate exogenous variations in variables that would otherwise be endogenous in the behavioral relationship of interest. An example from the economic study of education can be used to illustrate the approach. Here we might be interested in the effect of effect of an additional year of education on earnings. Those working with an experimentalist approach to econometrics would argue that such a question is problematic to answer because, and this is using their terminology, education is not randomly assigned. That is those with different education levels would tend to also have different levels of other variables. And these other variable, many of which would be unobserved, also affect earnings. This renders the causal effect of extra years of schooling difficult to identify. The experimentalist approach looks for an instrumental variable that is correlated with X but uncorrelated with the unobservables.
Victor Chaim Lavy is an Israeli economist and professor at the University of Warwick and the Hebrew University of Jerusalem. His research interests include labour economics, the economics of education, and development economics. Lavy belongs to the most prominent education economists in the world.
In econometrics and related empirical fields, the local average treatment effect (LATE), also known as the complier average causal effect (CACE), is the effect of a treatment for subjects who comply with the experimental treatment assigned to their sample group. It is not to be confused with the average treatment effect (ATE), which includes compliers and non-compliers together. Compliance refers to the human-subject response to a proposed experimental treatment condition. Similar to the ATE, the LATE is calculated but does not include non-compliant parties. If the goal is to evaluate the effect of a treatment in ideal, compliant subjects, the LATE value will give a more precise estimate. However, it may lack external validity by ignoring the effect of non-compliance that is likely to occur in the real-world deployment of a treatment method. The LATE can be estimated by a ratio of the estimated intent-to-treat effect and the estimated proportion of compliers, or alternatively through an instrumental variable estimator.
The 2021 Nobel Memorial Prize in Economic Sciences was divided one half awarded to the American-Canadian David Card "for his empirical contributions to labour economics", the other half jointly to Israeli-American Joshua Angrist and Dutch-American Guido W. Imbens "for their methodological contributions to the analysis of causal relationships." The Nobel Committee stated their reason behind the decision, saying:
"This year's Laureates – David Card, Joshua Angrist and Guido Imbens – have shown that natural experiments can be used to answer central questions for society, such as how minimum wages and immigration affect the labour market. They have also clarified exactly which conclusions about cause and effect can be drawn using this research approach. Together, they have revolutionised empirical research in the economic sciences."
