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Estimating standard errors in finance panel data sets: comparing approaches.

by Mitchell A Petersen - Review of Financial Studies , 2009
"... Abstract In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solut ..."
Abstract - Cited by 890 (7 self) - Add to MetaCart
Abstract In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different

Standard errors:

by Bradley Harding, Christophe Tremblay A, Denis Cousineau A
"... A review and evaluation of standard error estimators using Monte Carlo simulations ..."
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A review and evaluation of standard error estimators using Monte Carlo simulations

Model-Based Analysis of Oligonucleotide Arrays: Model Validation, Design Issues and Standard Error Application

by Cheng Li, Wing Hung Wong , 2001
"... Background: A model-based analysis of oligonucleotide expression arrays we developed previously uses a probe-sensitivity index to capture the response characteristic of a specific probe pair and calculates model-based expression indexes (MBEI). MBEI has standard error attached to it as a measure of ..."
Abstract - Cited by 775 (28 self) - Add to MetaCart
Background: A model-based analysis of oligonucleotide expression arrays we developed previously uses a probe-sensitivity index to capture the response characteristic of a specific probe pair and calculates model-based expression indexes (MBEI). MBEI has standard error attached to it as a measure

and standard errors

by H Brenner, T Hakulinen
"... Age adjustment of cancer survival rates: methods, point estimates ..."
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Age adjustment of cancer survival rates: methods, point estimates

The standard error of equipercentile equating

by Frederic M. Lord - Journal of Educational Statistics , 1982
"... ABSTRACT. The standard error of an equipercentile equating is derived for four situations. Some numerical results are checked by Monte Carlo methods. Numerical standard errors are computed for two sets of real data. Standard errors of linear and equipercentile equating are compared. It is frequently ..."
Abstract - Cited by 11 (0 self) - Add to MetaCart
ABSTRACT. The standard error of an equipercentile equating is derived for four situations. Some numerical results are checked by Monte Carlo methods. Numerical standard errors are computed for two sets of real data. Standard errors of linear and equipercentile equating are compared

Clustered Standard Errors

by Erin Hartman, Ps Sp , 2010
"... “... analyses of group randomized trials that ignore clustering are an exercise in self-deception ” (Cornfield 1978 pg. 101) And, in the ever so enlightening words of Joshua Angrist: “Making a data set larger by copying a smaller one n times generates no new information ” (Angrist and Pischke 2009) ..."
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) Erin Hartman (PS239 Sp2010) Clustered Standard Errors March 10, 2010 2 / 17Clustering in the Modeling World When we use parametric models, what do we usually assume about the errors? Erin Hartman (PS239 Sp2010) Clustered Standard Errors March 10, 2010 3 / 17Clustering in the Modeling World When we use

Robust Standard Errors for Robust Estimators

by Christophe Croux, Geert Dhaene, Dirk Hoorelbeke, Christophe Croux, Geert Dhaene, Dirk Hoorelbeke , 2003
"... A regression estimator is said to be robust if it is still reliable in the presence of outliers. On the other hand, its standard error is said to be robust if it is still reliable when the regression errors are autocorrelated and/or heteroskedastic. This paper shows how robust standard errors can be ..."
Abstract - Cited by 16 (2 self) - Add to MetaCart
A regression estimator is said to be robust if it is still reliable in the presence of outliers. On the other hand, its standard error is said to be robust if it is still reliable when the regression errors are autocorrelated and/or heteroskedastic. This paper shows how robust standard errors can

On the Warnock-Halton quasi-standard error

by Art B. Owen , 2005
"... This paper investigates an error estimate proposed by Warnock and studied by Halton (2005). That error estimate is simply the sample standard error applied to certain non-randomized quasi-Monte Carlo points. This quasi-standard error (QSE) closely tracks the actual error in an example, and looks to ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
This paper investigates an error estimate proposed by Warnock and studied by Halton (2005). That error estimate is simply the sample standard error applied to certain non-randomized quasi-Monte Carlo points. This quasi-standard error (QSE) closely tracks the actual error in an example, and looks

Good Error-Correcting Codes based on Very Sparse Matrices

by David J.C. MacKay , 1999
"... We study two families of error-correcting codes defined in terms of very sparse matrices. "MN" (MacKay--Neal) codes are recently invented, and "Gallager codes" were first investigated in 1962, but appear to have been largely forgotten, in spite of their excellent properties. The ..."
Abstract - Cited by 750 (23 self) - Add to MetaCart
We study two families of error-correcting codes defined in terms of very sparse matrices. "MN" (MacKay--Neal) codes are recently invented, and "Gallager codes" were first investigated in 1962, but appear to have been largely forgotten, in spite of their excellent properties

How much should we trust differences-in-differences estimates?

by Marianne Bertrand, Esther Duflo, Sendhil Mullainathan , 2003
"... Most papers that employ Differences-in-Differences estimation (DD) use many years of data and focus on serially correlated outcomes but ignore that the resulting standard errors are inconsistent. To illustrate the severity of this issue, we randomly generate placebo laws in state-level data on femal ..."
Abstract - Cited by 828 (1 self) - Add to MetaCart
Most papers that employ Differences-in-Differences estimation (DD) use many years of data and focus on serially correlated outcomes but ignore that the resulting standard errors are inconsistent. To illustrate the severity of this issue, we randomly generate placebo laws in state-level data
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