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John Denis Sargan
John Denis Sargan, FBA (23 August 1924 – 13 April 1996) was a British econometrician who specialized in the analysis of economic time-series. Sargan was born in Doncaster, Yorkshire in 1924, and was educated at Doncaster Grammar School and St John's College, Cambridge. He made many contributions, notably in instrumental variables estimation, Edgeworth expansions for the distributions of econometric estimators, identification conditions in simultaneous equations models, asymptotic tests for overidentifying restrictions in homoskedastic equations and exact tests for unit roots in autoregressive and moving average models. At the LSE, Sargan was Professor of Econometrics from 1964–1984. Sargan was President of the Econometric Society, a Fellow of the British Academy and an (honorary foreign) member of the American Academy of Arts and Sciences. His influence on econometric methodology is evident in several fields including in the development of Generalized Method of Moments ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Doncaster
Doncaster ( ) is a city status in the United Kingdom, city in South Yorkshire, England. Named after the River Don, Yorkshire, River Don, it is the administrative centre of the City of Doncaster metropolitan borough, and is the second largest settlement in South Yorkshire after Sheffield. Noted for its Horse racing in Great Britain, racing and History of rail transport in Great Britain , railway history, it is situated in the Don Valley on the western edge of the Humberhead Levels and east of the Pennines. It had a population of 87,455 at the 2021 United Kingdom census, 2021 census, whilst its urban area, built-up area had a population of 160,220, and the wider metropolitan borough had a population of 308,100. Adjacent to Doncaster to its east is the Isle of Axholme in Lincolnshire, which contains the towns of Haxey, Epworth, Lincolnshire, Epworth and Crowle, Lincolnshire, Crowle, and directly south is Harworth Bircotes in Nottinghamshire. Also, within the city's vicinity are Bar ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Edgeworth Expansion
In probability theory, the Gram–Charlier A series (named in honor of Jørgen Pedersen Gram and Carl Charlier), and the Edgeworth series (named in honor of Francis Ysidro Edgeworth) are series that approximate a probability distribution over the real line (-\infty,\infty) in terms of its cumulants. The series are the same; but, the arrangement of terms (and thus the accuracy of truncating the series) differ. The key idea of these expansions is to write the characteristic function of the distribution whose probability density function is to be approximated in terms of the characteristic function of a distribution with known and suitable properties, and to recover through the inverse Fourier transform. Gram–Charlier A series We examine a continuous random variable. Let \hat be the characteristic function of its distribution whose density function is , and \kappa_r its cumulants. We expand in terms of a known distribution with probability density function , characteristic func ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Generalized Method Of Moments
In econometrics and statistics, the generalized method of moments (GMM) is a generic method for estimating parameters in statistical models. Usually it is applied in the context of semiparametric models, where the parameter of interest is finite-dimensional, whereas the full shape of the data's distribution function may not be known, and therefore maximum likelihood estimation is not applicable. The method requires that a certain number of ''moment conditions'' be specified for the model. These moment conditions are functions of the model parameters and the data, such that their expectation is zero at the parameters' true values. The GMM method then minimizes a certain norm of the sample averages of the moment conditions, and can therefore be thought of as a special case of minimum-distance estimation. The GMM estimators are known to be consistent, asymptotically normal, and most efficient in the class of all estimators that do not use any extra information aside from that conta ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
American Academy Of Arts And Sciences
The American Academy of Arts and Sciences (The Academy) is one of the oldest learned societies in the United States. It was founded in 1780 during the American Revolution by John Adams, John Hancock, James Bowdoin, Andrew Oliver, and other Founding Fathers of the United States. It is headquartered in Cambridge, Massachusetts. Membership in the academy is achieved through a nominating petition, review, and election process. The academy's quarterly journal, '' Dædalus'', is published by the MIT Press on behalf of the academy, and has been open-access since January 2021. The academy also conducts multidisciplinary public policy research. Laurie L. Patton has served as President of the Academy since January 2025. History The Academy was established by the Massachusetts legislature on May 4, 1780, charted in order "to cultivate every art and science which may tend to advance the interest, honor, dignity, and happiness of a free, independent, and virtuous people." The sixty-tw ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
British Academy
The British Academy for the Promotion of Historical, Philosophical and Philological Studies is the United Kingdom's national academy for the humanities and the social sciences. It was established in 1902 and received its royal charter in the same year. It is now a fellowship of more than 1,000 leading scholars spanning all disciplines across the humanities and social sciences and a funding body for research projects across the United Kingdom. The academy is a self-governing and independent registered charity, based at 10–11 Carlton House Terrace in London. The British Academy is primarily funded with annual government grants. In 2022, £49.3m of its £51.7m of charitable income came from the Department for Business, Energy, and Industrial Strategy – in the same year it took in around £2.0m in trading income and £0.56m in other income. This funding is expected to continue under the new Department for Business and Trade. Purposes The academy states that it has five fundam ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Econometric Society
The Econometric Society is an international society of academic economists interested in applying statistical tools in the practice of econometrics. It is an independent organization with no connections to societies of professional mathematicians or statisticians. It was founded on December 29, 1930, at the Statler Hotel in Cleveland, Ohio. Its first president was Irving Fisher. As of 2014, there are about 700 elected fellows of the Econometric Society, making it one of the most prevalent research affiliations. New fellows are elected each year by the current fellows. The sixteen founding members were Ragnar Frisch, Charles F. Roos, Joseph A. Schumpeter, Harold Hotelling, Henry Schultz, Karl Menger, Edwin B. Wilson, Frederick C. Mills, William F. Ogburn, J. Harvey Rogers, Malcolm C. Rorty, Carl Snyder, Walter A. Shewhart, Øystein Ore, Ingvar Wedervang and Norbert Wiener. The Econometric Society sponsors the economics academic journal ''Econometrica ''Econometrica ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
List Of Presidents Of The Econometric Society
In the scientific discipline of economics, the Econometric Society is a learned society devoted to the advancement of economics by using mathematical and statistical methods. This article is a list of its (past and present) presidents. List *2024: Eliana La Ferrara *2023: Rosa Matzkin *2022: Guido Tabellini *2021: Pinelopi Koujianou Goldberg *2020: Orazio Attanasio *2019: Stephen Morris *2018: Tim Besley *2017: Drew Fudenberg *2016: Eddie Dekel *2015: Robert Porter *2014: Manuel Arellano *2013: James J. Heckman *2012: Jean-Charles Rochet *2011: Bengt R. Holmström *2010: John Hardman Moore *2009: Roger B. Myerson *2008: Torsten Persson *2007: Lars Peter Hansen *2006: Richard Blundell *2005: Thomas J. Sargent *2004: Ariel Rubinstein *2003: Eric Maskin *2002: *2001: Avinash Dixit *2000: Elhanan Helpman *1999: Robert B. Wilson *1998: Jean Tirole *1997: Robert E. Lucas, Jr. *1996: Roger Guesnerie *1995: Christopher Sims *1994: Takashi Negishi *1993: Andreu Mas-Colell * ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Moving Average
In statistics, a moving average (rolling average or running average or moving mean or rolling mean) is a calculation to analyze data points by creating a series of averages of different selections of the full data set. Variations include: #Simple moving average, simple, #Cumulative moving average, cumulative, or #Weighted moving average, weighted forms. Mathematically, a moving average is a type of convolution. Thus in signal processing it is viewed as a low-pass filter, low-pass finite impulse response filter. Because the boxcar function outlines its filter coefficients, it is called a boxcar filter. It is sometimes followed by Downsampling (signal processing), downsampling. Given a series of numbers and a fixed subset size, the first element of the moving average is obtained by taking the average of the initial fixed subset of the number series. Then the subset is modified by "shifting forward"; that is, excluding the first number of the series and including the next value in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Autoregressive
In statistics, econometrics, and signal processing, an autoregressive (AR) model is a representation of a type of random process; as such, it can be used to describe certain time-varying processes in nature, economics, behavior, etc. The autoregressive model specifies that the output variable depends linearly on its own previous values and on a stochastic term (an imperfectly predictable term); thus the model is in the form of a stochastic difference equation (or recurrence relation) which should not be confused with a differential equation. Together with the moving-average (MA) model, it is a special case and key component of the more general autoregressive–moving-average (ARMA) and autoregressive integrated moving average (ARIMA) models of time series, which have a more complicated stochastic structure; it is also a special case of the vector autoregressive model (VAR), which consists of a system of more than one interlocking stochastic difference equation in more than one ev ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Unit Root
In probability theory and statistics, a unit root is a feature of some stochastic processes (such as random walks) that can cause problems in statistical inference involving time series models. A linear stochastic process has a unit root if 1 is a root of the process's characteristic equation. Such a process is non-stationary but does not always have a trend. If the other roots of the characteristic equation lie inside the unit circle—that is, have a modulus (absolute value) less than one—then the first difference of the process will be stationary; otherwise, the process will need to be differenced multiple times to become stationary. If there are ''d'' unit roots, the process will have to be differenced ''d'' times in order to make it stationary. Due to this characteristic, unit root processes are also called difference stationary. Unit root processes may sometimes be confused with trend-stationary processes; while they share many properties, they are different in m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Exact Test
An exact (significance) test is a statistical test such that if the null hypothesis is true, then all assumptions made during the derivation of the distribution of the test statistic are met. Using an exact test provides a significance test that maintains the type I error rate of the test (\alpha) at the desired significance level of the test. For example, an exact test at a significance level of \alpha = 5\%, when repeated over many samples where the null hypothesis is true, will reject at most 5\% of the time. This is in contrast to an ''approximate test'' in which the desired type I error rate is only approximately maintained (i.e.: the test might reject > 5% of the time), while this approximation may be made as close to \alpha as desired by making the sample size sufficiently large. Exact tests that are based on discrete test statistics may be conservative, indicating that the actual rejection rate lies below the nominal significance level \alpha. As an example, this is th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Homoskedastic
In statistics, a sequence of random variables is homoscedastic () if all its random variables have the same finite variance; this is also known as homogeneity of variance. The complementary notion is called heteroscedasticity, also known as heterogeneity of variance. The spellings ''homoskedasticity'' and ''heteroskedasticity'' are also frequently used. “Skedasticity” comes from the Ancient Greek word “skedánnymi”, meaning “to scatter”. Assuming a variable is homoscedastic when in reality it is heteroscedastic () results in Biased estimator, unbiased but Efficiency (statistics), inefficient point estimates and in biased estimates of standard errors, and may result in overestimating the goodness of fit as measured by the Pearson product-moment correlation coefficient, Pearson coefficient. The existence of heteroscedasticity is a major concern in regression analysis and the analysis of variance, as it invalidates statistical hypothesis testing, statistical tests ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
