Reference health
Estimating Regression Models in Which the Dependent Variable Is Based on Estimates
1 of 20 checkable references need attention · checked 2026-07-25
At the dated check, the references listed below either did not resolve in Crossref or DataCite, or carried a retraction notice. Each one is shown with the registry record that put it there.
35 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
References needing attention
does not resolve to a known work10.1111/1475-6765.00593
The 19 checked references that resolve
resolves10.1006/ssre.2000.0694
A Multilevel Analysis of the Determinants of Recycling Behavior in the European Countries
resolves10.2307/2111734
Prospections, Retrospections, and Rationality: The "Bankers" Model of Presidential Approval Reconsidered
resolves10.1023/B:POBE.0000022342.58335.cd
Economic Perceptions and Executive Approval in Comparative Perspective
resolves10.2307/1912934
A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
resolves10.1177/106591290305600301
Democratization and Political Tolerance in Seventeen Countries: A Multi-level Model of Democratic Learning
resolves10.1093/pan/mpi030
Applying a Two-Step Strategy to the Analysis of Cross-National Public Opinion Data
resolves10.1111/1540-5907.00007
Corruption, Political Allegiances, and Attitudes Toward Government in Contemporary Democracies
resolves10.1111/1475-6765.00100
The euro, economic interests and multi‐level governance: Examining support for the common currency
resolves10.1093/pan/11.1.44
Using Ecological Inference Point Estimates as Dependent Variables in Second-Stage Linear Regressions
resolves10.1016/0304-4076(85)90158-7
Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties
The 35 references without a DOI — listed, not checked
no DOI — not checkedDo Elections Matter?
no DOI — not checkedA Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data
no DOI — not checkedEfficient Estimators for Regressing Regression Coefficients
no DOI — not checkedThese GDP data come from the World Bank 2002 World Development Indicators data set.
no DOI — not checkedCohen codes the “old democracy” variable 1 for Canada, France, Germany, Great Britain, Italy, Japan, and the United States, and 0 otherwise; see also Cohen's footnote 5.
no DOI — not checkedThe economic retrospection and prospection questions are numbers 12 and 13, respectively. The model includes two interaction terms to capture the possibility that the effect of economic evaluations differs between countries that are “old” and those that are not.
no DOI — not checkedThe approval rating question—question 35b in the survey—was asked in 41 of the 44 study countries: all except China, Egypt, and Vietnam.
no DOI — not checkedThe data set is free to download from the Pew Research Center for the People and the Press data archive at http://people-press.org/dataarchive/. See the June 3, 2003, release of the report titled “Views of a Changing World.” The Pew Global Attitudes Project bears no responsibility for the analyses or interpretations of the data presented here.
no DOI — not checkedExceptions to this claim are C = 0 and C = 1, where OLS and WLS, respectively, would be efficient.
no DOI — not checkedThis result is similar to those typically found in the heteroscedasticity literature (Greene 2003, p. 505).
no DOI — not checkedThe usual WLS approach described above is often advocated for this case (Hanushek and Jackson 1977). The justification is as follows. Suppose that all the variables are measured as sample means. Then assume there is an underlying individual-level regression model,
no DOI — not checkedThe trace of a square matrix is the sum of its diagonal elements.
no DOI — not checkedIn this case, if the within-unit variance of the variable were constant, the sampling variances would be proportional to 1/ni where ni is the size of the sample from which the mean was calculated for observation i.
no DOI — not checkedGuidance on multilevel models is often derived from such well-cited sources as Steenbergen and Jones (2002) and Bryk and Raudenbush (1992).
no DOI — not checkedThis very short summary hardly scratches the surface of the breadth and depth of possible applications of EDV regression models. However, we do wish to highlight that with respect to EDVs generated using King's (1997) EI algorithm, Herron and Shotts (2003) point out that using the so-called precinct-level EI estimates as dependent variables in second-stage regressions will lead to attenuated estimates and more generally calls into question the validity of using precinct-level EI estimates in subsequent analysis. It should be noted the techniques we present below are predicated on the assumption that the data used are free of the features described by Herron and Shotts. In particular, we assume that the sampling or measurement error in the dependent variable (Y* – Y) is independent of the independent variables and error term (X and ∊) of the regression. Also, using district-level EI estimates (for example, estimates of black turnout at the Congressional district level made by applying EI to precinct-level data in each district) need not involve the same “logical inconsistency” identified by Herron and Shotts.
no DOI — not checkedEfron standard errors (also known as HC3 standard errors) are based upon the jackknife techniques of Efron (1982) and are typically more accurate (as well as more conservative) than Huber-White standard errors in samples smaller than 250 observations
no DOI — not checkedsee Long and Ervin (2000) and MacKinnon and White (1985). Estimated Dependent Variable Regressions
no DOI — not checkedThese conclusions are not specific only to the EDV case, but generalize to other cases in which WLS is applied using incorrect weights (see Greene 2003).
no DOI — not checkedUsing Heteroscedasticity Consistent Standard Errors in the Linear Regression Model
no DOI — not checkedEconometric Analysis
no DOI — not checkedThe first FGLS approach described below is trivially extended to the case in which the estimates are not independent.
no DOI — not checkedEstimated Parameters as Dependent Variables
no DOI — not checkedStatistical Methods for Social Scientists
no DOI — not checkedProbability and Statistics
no DOI — not checkedThat is, 0.995 = 1 – (2.8/513.7).
no DOI — not checkedThe parameterization of the gamma distribution used here follows DeGroot and Schervish (2002). We define the density of gamma distribution as f(z | α, β) = [Γ(α)]–1 βα z α–1 e –βz for α > 0, β > 0, and z > 0. Given this parameterization, E(Z) = α/β and Var(Z) = α/β2 In the simulations, the density of ω2 i is f(ω2 i | C/θ, 1/θ).
no DOI — not checkedFor example, reported average state income may be based on a much larger sample in California than it is in Rhode Island, leading California's mean income to be more precisely estimated than Rhode Island's. Some surveys, such as the 1988 Senate Election Study, intentionally draw samples of roughly equal size from each aggregate unit, thus avoiding much of the heteroscedasticity that is generally present when sample means are used as a dependent variable. In these cases, the heteroscedasticity from sampling error would only enter from inter-unit heterogeneity in the intra-unit variance of the variable being sampled.
no DOI — not checkedThe “explained” variance will be β2Var(X) = 1 and the “unexplained” variance Var(v) = 1, thus the R 2 will be approximately 1/(1 + 1) = 1/2.
no DOI — not checkedNote that vi = ui + εi . Because ε i · is assumed to be independent of ui , Var(vi ) = Var(ui ) + Var(εi ) = C + (1 – C) = 1.
no DOI — not checkedThe approximate where Sy* is the sample variance of the observed dependent variable across the observations on the dependent variable.
no DOI — not checkedR functions implementing both of these procedures are available from the authors.
no DOI — not checkedHierarchical Linear Models: Applications and Data Analysis Methods
no DOI — not checkedHandbook of the Normal Distribution
no DOI — not checkedWhen we ran the same simulation with a larger n – 500, OLS was more efficient than WLS until about 90% of the total error variance was the result of sampling error in the dependent variable.
no DOI — not checkedIntroduction to Econometrics
What this badge says. CiteStamped means the CHECKABLE references of this
work were clean at the dated check: each resolved to a known work in a public registry, and none
carried a retraction notice at that time. It says nothing about the quality, findings,
or importance of the work itself, and nothing about references deposited without a DOI.
checked 2026-07-25 — re-checked daily as this page is visited; titles and statuses come from Crossref and DataCite and are not part of the signed record
Embed this badge
Both snippets point at the live badge image and link back to this page. The badge re-renders from the daily check, so an embed never goes stale by more than a day of visits.
<a href="https://citestamp.com/citestamped/10.1093/pan/mpi026"><img src="https://citestamp.com/citestamped/10.1093/pan/mpi026/badge.svg" alt="CiteStamped reference-health badge" width="460" height="64"></a>
[](https://citestamp.com/citestamped/10.1093/pan/mpi026)