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.
The following outline is provided as an overview of and topical guide to statistics:
Geostatistics is a branch of statistics focusing on spatial or spatiotemporal datasets. Developed originally to predict probability distributions of ore grades for mining operations, it is currently applied in diverse disciplines including petroleum geology, hydrogeology, hydrology, meteorology, oceanography, geochemistry, geometallurgy, geography, forestry, environmental control, landscape ecology, soil science, and agriculture. Geostatistics is applied in varied branches of geography, particularly those involving the spread of diseases (epidemiology), the practice of commerce and military planning (logistics), and the development of efficient spatial networks. Geostatistical algorithms are incorporated in many places, including geographic information systems (GIS).
An inverse problem in science is the process of calculating from a set of observations the causal factors that produced them: for example, calculating an image in X-ray computed tomography, source reconstruction in acoustics, or calculating the density of the Earth from measurements of its gravity field. It is called an inverse problem because it starts with the effects and then calculates the causes. It is the inverse of a forward problem, which starts with the causes and then calculates the effects.
Ridge regression is a method of estimating the coefficients of multiple-regression models in scenarios where the independent variables are highly correlated. It has been used in many fields including econometrics, chemistry, and engineering. Also known as Tikhonov regularization, named for Andrey Tikhonov, it is a method of regularization of ill-posed problems. It is particularly useful to mitigate the problem of multicollinearity in linear regression, which commonly occurs in models with large numbers of parameters. In general, the method provides improved efficiency in parameter estimation problems in exchange for a tolerable amount of bias.
Calyampudi Radhakrishna Rao was an Indian-American mathematician and statistician. He was professor emeritus at Pennsylvania State University and research professor at the University at Buffalo. Rao was honoured by numerous colloquia, honorary degrees, and festschrifts and was awarded the US National Medal of Science in 2002. The American Statistical Association has described him as "a living legend" whose work has influenced not just statistics, but has had far reaching implications for fields as varied as economics, genetics, anthropology, geology, national planning, demography, biometry, and medicine." The Times of India listed Rao as one of the top 10 Indian scientists of all time.
In statistics, multicollinearity or collinearity is a situation where the predictors in a regression model are linearly dependent.
Econometric models involving data sampled at different frequencies are of general interest. Mixed-data sampling (MIDAS) is an econometric regression developed by Eric Ghysels with several co-authors. There is now a substantial literature on MIDAS regressions and their applications, including Ghysels, Santa-Clara and Valkanov (2006), Ghysels, Sinko and Valkanov, Andreou, Ghysels and Kourtellos (2010) and Andreou, Ghysels and Kourtellos (2013).
Christian Gouriéroux is an econometrician who holds a Doctor of Philosophy in mathematics from the University of Rouen. He has the Professor exceptional level title from France. Gouriéroux is now a professor at University of Toronto and CREST, Paris [Center for Research in Economics and Statistics].
Eric Ghysels is a Belgian economist with interest in finance and time series econometrics, and in particular the fields of financial econometrics and financial technology. He is the Edward M. Bernstein Distinguished Professor of Economics at the University of North Carolina and a Professor of Finance at the Kenan-Flagler Business School. He is also the Faculty Research Director of the Rethinc.Labs at the Frank Hawkins Kenan Institute of Private Enterprise.
In econometrics and statistics, a structural break is an unexpected change over time in the parameters of regression models, which can lead to huge forecasting errors and unreliability of the model in general. This issue was popularised by David Hendry, who argued that lack of stability of coefficients frequently caused forecast failure, and therefore we must routinely test for structural stability. Structural stability − i.e., the time-invariance of regression coefficients − is a central issue in all applications of linear regression models.
Jacques H. Drèze was a Belgian economist noted for his contributions to economic theory, econometrics, and economic policy as well as for his leadership in the economics profession. Drèze was the first President of the European Economic Association in 1986 and was the President of the Econometric Society in 1970.
Nowcasting in economics is the prediction of the very recent past, the present, and the very near future state of an economic indicator. The term is a portmanteau of "now" and "forecasting" and originates in meteorology. Typical measures used to assess the state of an economy, such as gross domestic product (GDP) or inflation, are only determined after a delay and are subject to revision. In these cases, nowcasting such indicators can provide an estimate of the variables before the true data are known. Nowcasting models have been applied most notably in Central Banks, who use the estimates to monitor the state of the economy in real-time as a proxy for official measures.
The Center for Operations Research and Econometrics (CORE) is an interdisciplinary research institute of the University of Louvain (UCLouvain) located in Louvain-la-Neuve, Belgium. Since 2010, it is part of the Louvain Institute of Data Analysis and Modeling in economics and statistics (LIDAM), along with the Institute for Economic and Social Research (IRES), Louvain Finance (LFIN) and the Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
Jean-François Richard is a Belgian-American economist, who is currently the distinguished university professor of Economics at the University of Pittsburgh. He has taught and done research at five major universities, primarily in the field of econometrics. His interests are auctions, computational methods, collusions, Bayesian methods and econometric modeling. He has been extensively involved as author, editor, and advisor with scholarly publications in econometrics and related fields.
Victor Chernozhukov is a Russian-American statistician and economist currently at Massachusetts Institute of Technology. His current research focuses on mathematical statistics and machine learning for causal structural models in high-dimensional environments. He graduated from the University of Illinois at Urbana-Champaign with a master's in statistics in 1997 and received his PhD in economics from Stanford University in 2000.
Probabilistic numerics is an active field of study at the intersection of applied mathematics, statistics, and machine learning centering on the concept of uncertainty in computation. In probabilistic numerics, tasks in numerical analysis such as finding numerical solutions for integration, linear algebra, optimization and simulation and differential equations are seen as problems of statistical, probabilistic, or Bayesian inference.
