econometrics - People, Software

A branch of economics which seeks to test and measure economic relationships through mathematical and statistical methods for the purposes of assessing and choosing among alternative policies. It is widely used in economic forecasting. Econometrics now provides the standard of proof across the full range of applied microeconomics, which studies everything from household spending and investment by firms to the organization of industries, labour markets, and the effects of public policy. In 2000 the economists James Heckman and Daniel McFadden were jointly awarded the Nobel Prize for Economics for their contribution to the field of econometrics.

Econometrics literally means 'economic measurement'.

The two main purposes of econometrics are to give empirical content to economic theory and to subject economic theory to potentially falsifying tests.

The most important statistical method in econometrics is regression analysis.

Econometric analysis is divided into time-series analysis and cross-sectional analysis. When time-series analysis and cross-sectional analysis are conducted simultaneously on the same sample, it is called panel analysis. Multi-dimensional panel data analysis is conducted on data sets that have more than two dimensions.

Econometric analysis may also be classified on the basis of the number of relationships modelled. Single equation methods model a single variable (the dependent variable) as a function of one or more explanatory variables. In many econometric contexts such single equation methods may not be able to recover estimates of causal relationships because either the dependent variable causes changes in one of the explanatory variables or because variables not included in the model cause both the dependent and at least one of the independent variables.

Much larger econometric models are used in an attempt to explain or predict the behavior of national economies.

A simple example of a relationship in econometrics is:

wage = constant + (rate of return to education) * education + random error

In this equation, a person's wage is a linear function of the number of years of education he has. The econometric goal is to estimate the expected change in wages a person would receive if she obtained one more year of education.

If the researcher could randomly assign people to differing levels of education, the correlation between education and wages would reveal the causal effect of education on wages. Instead the econometrician only observes how many years of education people obtain, and the wages they receive. The correlation between wages and education reflects both the effect of education on wages and unobserved variables which may affect both outcomes. For example, more intelligent people may tend to obtain more education and may also earn more at any level of education than less intelligent people. Econometric methods could be used to overcome these problems and estimate the underlying causal effect of education on wages. "The Causal Effect of Education on Earnings."

People

Nobel Memorial Prize in Economics recipients in the field of econometrics:

Jan Tinbergen and Ragnar Frisch were awarded in 1969 (the first Nobel Prize for Economic Sciences) for having developed and applied dynamic models for the analysis of economic processes Lawrence Klein, Professor of Economics at the University of Pennsylvania, was awarded in 1980 for his computer modeling work in the field.

The Econometric Author Links of the Econometrics Journal provides personal links to recent articles and working papers of econometric authors via the RePEc system in EconPapers

Software

Software packages that are widely used by professional statisticians include SAS, Stata, RATS, TSP, SPSS, and WinBugs.