Standard Errors of Means in Sampling Surveys with Two-Stage Sampling

Following Wooldridge (2014, Journal of Econometrics 182: 226–234), we discuss and implement in Stata an efficient maximum-likelihood approach to the estimation of corrected standard errors of two-stage optimization models. Specifically, we compare the robustness and efficiency of the proposed method with routines already implemented in Stata to deal with selection and endogeneity problems. This strategy is an alternative to the use of bootstrap methods and has the advantage that it can be easily applied for the estimation of two-stage optimization models for which already built-in programs are not yet available. It could be of particular use for addressing endogeneity in a nonlinear framework.

Download Full-text

ASYMPTOTIC DISTRIBUTION OF JIVE IN A HETEROSKEDASTIC IV REGRESSION WITH MANY INSTRUMENTS

Econometric Theory ◽

10.1017/s0266466611000120 ◽

2011 ◽

Vol 28 (1) ◽

pp. 42-86 ◽

Cited By ~ 39

Author(s):

John C. Chao ◽

Norman R. Swanson ◽

Jerry A. Hausman ◽

Whitney K. Newey ◽

Tiemen Woutersen

Keyword(s):

Least Squares ◽

Instrumental Variables ◽

Standard Errors ◽

Asymptotic Covariance Matrix ◽

Limited Information ◽

Two Stage ◽

Asymptotically Normal ◽

Many Instruments ◽

Two Stage Least Squares ◽

The Many

This paper derives the limiting distributions of alternative jackknife instrumental variables (JIV) estimators and gives formulas for accompanying consistent standard errors in the presence of heteroskedasticity and many instruments. The asymptotic framework includes the many instrument sequence of Bekker (1994, Econometrica 62, 657–681) and the many weak instrument sequence of Chao and Swanson (2005, Econometrica 73, 1673–1691). We show that JIV estimators are asymptotically normal and that standard errors are consistent provided that $\root \of {K_n } /r_n \to 0$ as n→∞, where Kn and rn denote, respectively, the number of instruments and the concentration parameter. This is in contrast to the asymptotic behavior of such classical instrumental variables estimators as limited information maximum likelihood, bias-corrected two-stage least squares, and two-stage least squares, all of which are inconsistent in the presence of heteroskedasticity, unless Kn/rn→0. We also show that the rate of convergence and the form of the asymptotic covariance matrix of the JIV estimators will in general depend on the strength of the instruments as measured by the relative orders of magnitude of rn and Kn.

Download Full-text

Correcting Standard Errors in Two-stage Estimation Procedures with Generated Regressands*

Oxford Bulletin of Economics and Statistics ◽

10.1111/j.1468-0084.2005.00126.x ◽

2005 ◽

Vol 67 (3) ◽

pp. 421-433 ◽

Cited By ~ 27

Author(s):

Michel Dumont ◽

Glenn Rayp ◽

Olivier Thas ◽

Peter Willeme

Keyword(s):

Standard Errors ◽

Two Stage ◽

Estimation Procedures ◽

Stage Estimation

Download Full-text

CDSIMEQ: A Program to Implement Two-stage Probit Least Squares

The Stata Journal Promoting communications on statistics and Stata ◽

10.1177/1536867x0300300205 ◽

2003 ◽

Vol 3 (2) ◽

pp. 157-167 ◽

Cited By ~ 82

Author(s):

Omar M. G. Keshk

Keyword(s):

Least Squares ◽

Estimation Method ◽

Least Squares Estimation ◽

Simultaneous Equations ◽

The Other ◽

Endogenous Variable ◽

Standard Errors ◽

Two Stage ◽

Simultaneous Equations Models ◽

Endogenous Variables

The cdsimeq command implements the two-stage probit least squares estimation method described in Maddala (1983) for simultaneous equations models in which one of the endogenous variables is continuous and the other endogenous variable is dichotomous.1 The cdsimeq command implements all the necessary procedures for obtaining consistent estimates for the coefficients, as well as their corrected standard errors.

Download Full-text

A COMPARATIVE STUDY OF TEN ELECTRICAL METERS FOR DETERMINING MOISTURE CONTENT OF WHEAT

Canadian Journal of Research ◽

10.1139/cjr49f-041 ◽

1949 ◽

Vol 27f (10) ◽

pp. 382-397 ◽

Cited By ~ 7

Author(s):

I. Hlynka ◽

V. Martens ◽

J. A. Anderson

Keyword(s):

Moisture Content ◽

Comparative Study ◽

Spring Wheat ◽

Standard Error ◽

Temperature Effects ◽

Standard Errors ◽

Regression Equations ◽

Two Stage ◽

Vacuum Oven ◽

Hard Red Spring Wheat

Ten electrical moisture meters were tested with 159 samples of Canadian hard red spring wheat, of Grades 1, 2, 3, and 4 Northern, representing a moisture range of 11 to 17%. The two-stage vacuum oven and Brown–Duvel methods were used as bases of comparison. Regression equations, standard errors of estimate, and data on temperature effects are reported. The standard error of estimate of vacuum oven results was 0.15% for the Brown–Duvel method, 0.23% for the Tag–Heppenstall meter, and 0.28% for the Universal meter. Other meters had higher errors of estimate.

Download Full-text

Two-stage self-seeding method for preparation of single crystals of poly(phenylene sulfide)

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100153816 ◽

1989 ◽

Vol 47 ◽

pp. 368-369

Author(s):

Sengshiu Chung ◽

Peggy Cebe

Keyword(s):

Single Crystals ◽

High Performance ◽

Dilute Solution ◽

Two Stage ◽

Annealing Behavior ◽

High Performance Polymers ◽

Seeding Method ◽

Phenylene Sulfide

We are studying the crystallization and annealing behavior of high performance polymers, like poly(p-pheny1ene sulfide) PPS, and poly-(etheretherketone), PEEK. Our purpose is to determine whether PPS, which is similar in many ways to PEEK, undergoes reorganization during annealing. In an effort to address the issue of reorganization, we are studying solution grown single crystals of PPS as model materials.Observation of solution grown PPS crystals has been reported. Even from dilute solution, embrionic spherulites and aggregates were formed. We observe that these morphologies result when solutions containing uncrystallized polymer are cooled. To obtain samples of uniform single crystals, we have used two-stage self seeding and solution replacement techniques.

Download Full-text