The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Random Coefficient Models for Time-Series—Cross-Section Data: Monte Carlo Experiments
Abstract
This article considers random coefficient models (RCMs) for time-series—cross-section data. These models allow for unit to unit variation in the model parameters. The heart of the article compares the finite sample properties of the fully pooled estimator, the unit by unit (unpooled) estimator, and the (maximum likelihood) RCM estimator. The maximum likelihood estimator RCM performs well, even where the data were generated so that the RCM would be problematic. In an appendix, we show that the most common feasible generalized least squares estimator of the RCM models is always inferior to the maximum likelihood estimator, and in smaller samples dramatically so.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Mixed-Effects Models in S and S-PLUS
(2001) · Technometrics · doi:10.1198/tech.2001.s574 · Cited by 9,278
Hsiao, C. (2014) · doi:10.1017/cbo9781139839327 · Cited by 7,869
Mixed-Effects Models in S and S-PLUS
(2000) · Statistics and Computing · doi:10.1007/b98882 · Cited by 930
Cited by
Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data
Bell, A., & Jones, K. (2015) · Political Science Research and Methods · doi:10.1017/psrm.2014.7 · Cited by 1,515
Fixed and random effects models: making an informed choice
Bell, A., Fairbrother, M., & Jones, K. (2019) · Quality & Quantity · doi:10.1007/s11135-018-0802-x · Cited by 1,085
Modeling Dynamics in Time-Series–Cross-Section Political Economy Data
Beck, N., & Katz, J. N. (2011) · Annual Review of Political Science · doi:10.1146/annurev-polisci-071510-103222 · Cited by 825
Self-citationA General Panel Model with Random and Fixed Effects: A Structural Equations Approach
Bollen, K. A., & Brand, J. E. (2010) · Social Forces · doi:10.1353/sof.2010.0072 · Cited by 318
The case for welfare state universalism, or the lasting relevance of the paradox of redistribution
Jacques, O., & Noël, A. (2018) · Journal of European Social Policy · doi:10.1177/0958928717700564 · Cited by 108
Metadata
- Authors
- Beck, N., & Katz, J. N.
- Venue
- Political Analysis
- Publisher
- Cambridge University Press (CUP)
- Published
- 2007
- Volume
- 15
- Issue
- 2
- Pages
- 182-195
- ISSN
- 1047-1987 (ISSN-L)
- 1476-4989
- OpenAlex
- W2160503536
- Cited by
- 176
- References
- 3
- FWCI
- 11.15
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Random Coefficient Models for Time-Series—Cross-Section Data: Monte Carlo Experiments. https://app.cochat.ai/papers/10.1093/pan/mpl001
- The paper
- Beck, N., & Katz, J. N. (2007). Random Coefficient Models for Time-Series—Cross-Section Data: Monte Carlo Experiments. Political Analysis. https://doi.org/10.1093/pan/mpl001
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
