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Identification and Estimation of 'Irregular' Correlated Random Coefficient Models
Graham, Bryan S. - 2010
In this paper we study identification and estimation of a correlated random coefficients (CRC) panel data model. The …
Persistent link: https://www.econbiz.de/10012758200
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Estimating the Covariates of Historical Heights
Trussell, James; Wachter, Kenneth - 2022
Data on human height can provide an index that may measure more accurately changes in the standard of living than the more conventional real wage index. Height data, like those on real wages, are relatively abundant and extend back to the seventeenth century. In a previous paper, we developed...
Persistent link: https://www.econbiz.de/10013310262
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A No-Arbitrage Approach to Range-Based Estimation of Return Covariances and Correlations
Diebold, Francis X. - 2003
We extend range-based volatility estimation to the multivariate case. In particular, we propose a range …
Persistent link: https://www.econbiz.de/10012786604
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Robust Covariance Matrix Estimation with Data-Dependent VAR Prewhitening Order
den Haan, Wouter J.; Levin, Andrew T. - 2021
This paper analyzes the performance of heteroskedasticity-and-autocorrelation-consistent (HAC) covariance matrix estimators in which the residuals are prewhitened using a vector autoregressive (VAR) filter. We highlight the pitfalls of using an arbitrarily fixed lag order for the VAR filter, and...
Persistent link: https://www.econbiz.de/10013212913
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When to Control for Covariates? Panel-Asymptotic Results for Estimates of Treatment Effects
Angrist, Joshua D.; Hahn, Jinyong - 2021
The problem of how to control for covariates is endemic in evaluation research. Covariate-matching provides an appealing control strategy, but with continuous or high-dimensional covariate vectors, exact matching may be impossible or involve small cells. Matching observations that have the same...
Persistent link: https://www.econbiz.de/10013214628
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How Much Should We Trust Differences-in-Differences Estimates?
Bertrand, Marianne; Duflo, Esther; Mullainathan, Sendhil - 2021
almost all these papers ignore the bias in the estimated standard errors that serial correlation introduce4s. This is … especially troubling because the independent variable of interest in DD estimation (e.g., the passage of law) is itself very … biased: with about 20 years of data, DD estimation finds an 'effect' significant at the 5% level of up to 45% of the placebo …
Persistent link: https://www.econbiz.de/10013244880
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A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelationconsistent Covariance Matrix
Newey, Whitney K.; West, Kenneth D. - 2021
This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix under fairly general conditions
Persistent link: https://www.econbiz.de/10013245333
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Selection on Observed and Unobserved Variables : Assessing the Effectiveness of Catholic Schools
Altonji, Joseph G.; Elder, Todd E.; Taber, Christopher - 2021
We develop estimation methods that use the amount of selection on the observables in a model as a guide to the amount …
Persistent link: https://www.econbiz.de/10013313323
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A Portmanteau Test for Serially Correlated Errors in Fixed Effects Models
Inoue, Atsushi; Solon, Gary - 2021
We propose a portmanteau test for serial correlation of the error term in a fixed effects model. The test is derived as …
Persistent link: https://www.econbiz.de/10013229087
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Testing the Correlated Random Coefficient Model
Heckman, James J. - 2012
The recent literature on instrumental variables (IV) features models in which agents sort into treatment status on the basis of gains from treatment as well as on baseline-pretreatment levels. Components of the gains known to the agents and acted on by them may not be known by the observing...
Persistent link: https://www.econbiz.de/10013116685