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Topic: Consistent estimator

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	Estimator - Wikipedia, the free encyclopedia
		In statistics, an estimator is a function of the known data that is used to estimate an unknown parameter; an estimate is the result from the actual application of the function to a particular set of data.
		The standard deviation of an estimator of θ (the square root of the variance), or an estimate of the standard deviation of an estimator of θ, is called the standard error of θ.
		A consistent estimator is an estimator that converges in probability to the quantity being estimated as the sample size grows.
	en.wikipedia.org /wiki/Estimator (347 words)

	Stata help for hausman
		The default is the matrix rank of the variance of the difference between the coefficients of the two estimators.
		Hausman's test is based on estimating the variance var(b-B) of the difference of the estimators by the difference var(b)-var(B) of the variances.
		Under the assumptions (1) and (3), var(b)-var(B) is a consistent estimator of var(b-B), but it is not necessarily positive definite "in finite samples", i.e., in your application.
	www.stata.com /help.cgi?hausman (827 words)

	Ha_Consistent_Estimator (Site not responding. Last check: 2007-11-03)
		Nonparametric estimators of frequency response functions are usually biased when the system to be identified has unknown, possibly correlated, additive noise on both the inputs and outputs.
		In this communication, it is shown how the use of a specific type of input force (random with periodic second-order statistics) leads to a simple but unbiased estimator, even in the presence of high levels of additive stationary noise at the inputs and the outputs.
		Finally the predicted performance of the proposed estimator is validated with the aid of experimental results.
	www.utc.fr /~antoni/Ha_Consistent_Estimator.htm (177 words)

	Key Definition (Site not responding. Last check: 2007-11-03)
		Consistent estimators are appealing since estimation errors associated with such point estimators are close to zero with high probability when sample sizes are sufficiently large.
		An estimator is consistent if its mean squared error tends to zero as n tends to infinity.
		The consistency of the sample mean is also a consequence of the Weak Law of Large Numbers.
	www.geocities.com /qmstats99/pe07.htm (103 words)

	[No title]
		Dynamic model In contrast to the static, model, not all estimators are consistent in the dynamic case, even when T is large.
		But the sum of the lagged dependent variable coefficients of 0.65 using the aggregate estimator is the same as that using the Swamy estimator (the dynamics differ a lot, though - for example, the pattern among the lagged dependent variables differs: 0.49+0.16 for the aggregate estimator vs. 0.79-0.14 for the Swamy).
		The estimates of the long-run coefficients from the aggregate cointegrating regression are close to the mean of those from the individual industry cointegrating regressions.
	www.warwick.ac.uk /staff/Jennifer.Smith/panel/3dyna.doc (2418 words)

	[No title]
		It is possible to skip storing the second model and refer to the last estimation results by a period ({cmd:.}).
		{p 4 8 2}{cmd:sigmamore} allows you to specify that the (co)variance matrices used in the test be based on a common estimate of disturbance variance (sigma2), namely the variance from the efficient estimator.
		This is illustrated in the comparison of the OLS estimator and the estimator of the {cmd:regress} part of the {cmd:heckman} model {p 8 12 2}{cmd:.
	www.stata.com /updates3/ado/hausman.hlp (972 words)

	Minimum distance factor analysis of time series: Theory and application.
		An estimate of the factor scores is obtained as a by-product.
		For stationary sequences, an MD estimator is consistent and uniformly asymptotically normal (CUAN) under mild conditions on dependence and moments.
		Given an estimate of the model parameters, the generalized least squares (GLS) estimator of the factor scores is applicable.
	repository.upenn.edu /dissertations/AAI9953573 (371 words)

	[No title]
		The principle differences are: a) choice of instruments and b) some of the estimators estimate all of the coefficients jointly.
		In the overidentified case 2SLS is a consistent estimator and is asymptotically efficient.
		Among the k-class estimators, the optimal value of k appears to be between.8 and.9.g.
	www.econ.kuleuven.ac.be /public/NDBAE76/econometrics/6.doc (600 words)

	hw6.htm
		The convention generalized method of moment (GMM) estimator utilizes an analogy principle theory, thereby minimizing the distance between the sample moment conditions and their hypothesized values.
		The EL estimator, in contrast to the GMM estimator, utilizes an alternative form of the analogy principle, minimizing a distance between probability measures rather than the distance of the population moment conditions from their sample counterparts.
		The semiparametric efficient estimator of the expectation function may be written in a simpler form.
	www.maxwell.syr.edu /maxpages/faculty/cdkao/teaching/ecn720/2003/hw6.htm (513 words)

	[No title]
		The residual variance estimator from this step is a consistent estimator of ((2.
		The estimator is BIV= EMBED Equation.DSMT4 The Returns to Schooling The economic returns to schooling have been a frequent topic of study by econometricians.
		The schooling coefficient ie estimated at 0.067, a value which the authors suspected was far too small.
	pages.stern.nyu.edu /~wgreene/Econometrics/display/trix18.doc (1653 words)

	Generalized Least Squares, Heteroscedasticity and Autocorrelation
		Since this is the least squares estimator it remains unbiased, although the computer has given it to you inadvertantly.
		The variance of the OLS estimator must be greater than that of the GLS estimator by the Gauss-Markov Theorem.
		Note that you are using the maximum likelihood estimate of the error variance under the null hypothesis.
	isc.temple.edu /economics/notes/genlstsqrs/genlstsqrs.HTM (2462 words)

	GAUSS Programming for Econometricians: Chapter VII (Site not responding. Last check: 2007-11-03)
		The consequence of ordinary least squares estimation with an autocorrelated error structure is loss of efficiency, that is, statistical inference using t and F test statistics cannot be trusted.
		Combining both problems of heteroscedasticity and autocorrelation, the Newey-West estimator of heteroscedasticity autocorrelation consistent covariance matrix is a simple approach to deal with an unspecified structure of heteroscedasticity and autocorrelation.
		For a regression model with an unspecified structure of heteroscedasticity and autocorrelation, the consistent estimator of the variance-covariance matrix is
	eclab.econ.pdx.edu /gpe/chap7.htm (2397 words)

	Contents of Estimation of the variance-covariance matrix (Site not responding. Last check: 2007-11-03)
		Since we need to estimate so many components if we are to take the parametric approach, it is unlikely that we would arrive at a correct parametric specification.
		This estimator is inconsistent in general, since the number of parameters to estimate is more than the number of observations, and increases more rapidly than
		A disadvantage of this estimator is that it may not be positive definite.
	pareto.uab.es /omega/Project_001/notes/node139_ct.html (198 words)

	[No title]
		To check for heteroskedasticity related to population, separate regressions were run for the 17 states with the lowest populations and the 17 states with the highest populations.
		The estimator of the standard error of EMBED Equation.3 is biased downward.
		inconsistent and biased away from zero (that is, the estimator’s probability limit is farther from zero than the true value of the coefficient).
	www.econ.iastate.edu /classes/econ571/wboal/exams/rq3.doc (1267 words)

	XploRe Help : neweywest (Site not responding. Last check: 2007-11-03)
		Calculation of the Newey and West Heteroskedastic and Autocorrelation Consistent estimator of the variance.
		The first argument of the quantlet represents the series and the second optional argument the vector of truncation lags of the autocorrelation consistent variance estimator.
		;Calculation of the Newey and West variance estimator of ;the first 1000 observations of the series dmus58.dat ;This estimator is calculated for the vector of truncation ;orders m = 10, 15, 20 provided by the user.
	www.xplore-stat.de /help/neweywest.html (237 words)

	No Title
		The 2-stage least squares estimator is a better estimator than the OLS estimator because it has two stages and is therefore twice as efficient.
		is a vector of coefficients determining the agent's utility to be estimated.
		can be consistently estimated by nonlinear least squares by writing down the least squares problem and sketching a proof for its consistency.
	gemini.econ.umd.edu /jrust/econ551/exams/01/final/final.html (1973 words)

	A Consistent Estimator For The Binomial Distribution In The Presence Of "Incidental Parameters": An Application To ...
		In this paper a consistent estimator for the Binomial distribution in the presence of incidental parameters, or fixed effects, when the underlying probability is a logistic function is derived.
		The consistent estimator is obtained from the maximization of a conditional likelihood function in light of Andersen's work.
		Finally, this new estimator is applied to an original dataset that allows the estimation of the probability of obtaining a patent.
	ideas.repec.org /p/cte/werepe/we031905.html (378 words)

	X
		So at the very least this estimator is unbiased and linear in Y.
		it may be possible to estimate it consistently.
		That is, there is a linear unbiased estimator with smaller variance.
	astro.temple.edu /~buck/notes/genlstsqrs/genlstsqrs.HTM (2449 words)

	6
		cannot be consistently estimated because some of the variables on the RHS are correlated with the error term.
		From the last line we can see that in IV we are really using a set of fitted values of the dependent variable that have been created by projecting the dependent variable onto the space spanned by the instrumental variables.
		The consequence is that we cannot use either ILS or the simple IV estimator outlined in the sections preceding the earlier discussion of what IV does.
	astro.temple.edu /~buck/notes/sysestimat/sysestimat.HTM (2141 words)

	[No title] (Site not responding. Last check: 2007-11-03)
		Hence the estimator is consistent.¡ ¹ 22çÿçÿ%ªbC W ðx² ðL £ð
		It is correlated with p as one can see from the reduced form equation for p and, because it is exogenous, it is distributed independently of uw.
		In this variation, we hypothesize that p is a function of m, the rate of growth of the money supply, as well as w.
	www.oup.co.uk /powerpoint/bt/dougherty2e/student/c10d2.ppt (1179 words)

	[No title]
		Coin flipping example: What is your point estimate of p ?¡&##ó¨Interval Estimation¨¨Draw inference about a population by estimating the parameter using an interval (i.e., a range of values).
		Thus an unbiased estimator is consistent if its variance grows smaller as n grows larger.¡Zó¨ Efficiency¨`For two unbiased estimators, the one with the smaller variance is considered more efficient.
		Find an estimator for and determine whether it is unbiased and/or consistent.¡`Z`ó/ª ¨Let denote the number of customers observed in minute i (i=1..n).
	www-stat.wharton.upenn.edu /~cvenkata/stat101/lecture/lecture-21.ppt (834 words)

	Consistency
		A further desirable property of estimators is that of consistency, which is an asymptotic property.
		To understand consistency, it is necessary to think of
		Roughly speaking, an estimator is consistent if, as
	turing.une.edu.au /~stat354/notes/node64.html (114 words)

	[No title]
		Both the resulting instrumental variables estimators (known as Anderson-Hsiao): EMBED Equation.2 (16) and EMBED Equation.2 (17) are consistent when N EMBED Equation.2 or T EMBED Equation.2 or both.
		The Arellano-Bond estimator is now widely used in short dynamic panels, not least due to the fact that they wrote a Gauss-based regression package, DPD, which gives the standard OLS, fixed effects (Within or differences), random effects estimators, plus their own.
		The two-step estimators for b and g are given by: EMBED Equation.2 (26) where X is the N(T-2) EMBED Equation.2 K matrix of observations on EMBED Equation.2 .
	www.warwick.ac.uk /staff/Jennifer.Smith/panel/2dyna.doc (1032 words)

	LogEc: Access Statistics for Jeffrey Mackie-Mason
		A SIMPLE, CONSISTENT ESTIMATE FOR DISTURBANCE COMPONENTS IN FINANCIAL MODELS
		A Simple, Consistent Estimator for Disturbance Components in Financial Models
		Please see our explanation of how the statistics are collected or e-mail.
	logec.repec.org /RAS/pma1.htm (317 words)

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