Christina Maschmann, Joakim Westerlund
arXiv 3 Dec 2025 · Econometrics
arXiv:2512.03693 · PDF · DOI · OpenAlex · Extracted main text
Panel data models with unobserved heterogeneity in the form of interactive effects standardly assume that the time effects - or "common factors" - enter linearly. This assumption is unnatural in the sense that it pertains to the unobserved component of the model, and there is rarely any reason to believe that this component takes on a particular functional form. This is in stark contrast to the relationship between the observables, which can often be credibly argued to be linear. Linearity in the factors has persevered mainly because it is convenient, and that it is better than standard fixed effects. The present paper relaxes this assumption. It does so by combining the common correlated effects (CCE) approach to standard interactive effects with the method of sieves. The new estimator - abbreviated "SCCE" - retains many of the advantages of CCE, including its computational simplicity, and good small-sample and asymptotic properties, but is applicable under a much broader class of factor structures that includes the linear one as a special case. This makes it well-suited for a wide range of empirical applications.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Chen, Xiaohong (2007) Large sample sieve estimation of semi-nonparametric models | 1.000 | 10 | 4 | 100% |
| 2 | Pesaran, M Hashem (2006) Estimation and inference in large heterogeneous panels with a multifactor error structure | 1.000 | 10 | 4 | 100% |
| 3 | Voigtländer, Nico (2014) Skill bias magnified: Intersectoral linkages and white-collar labor demand in US manufacturing | 1.000 | 9 | 3 | 100% |
| 4 | Su, Liangjun and Jin, Sainan (2012) Sieve estimation of panel data models with cross section dependence | 0.874 | 8 | 2 | 100% |
| 5 | Whitney K. Newey (1997) Convergence rates and asymptotic normality for series estimators | 0.811 | 4 | 2 | 100% |
| 6 | Belloni, Alexandre and Chernozhukov, Victor and Chetverikov, Denis a… (2015) Some new asymptotic theory for least squares series: Pointwise and uniform results | 0.737 | 3 | 2 | 100% |
| 7 | Yin, Shou-Yung and Liu, Chu-An and Lin, Chang-Ching (2021) Focused information criterion and model averaging for large panels with a multifactor error structure | 0.693 | 7 | 1 | 100% |
| 8 | Juodis, Artūras (2022) A regularization approach to common correlated effects estimation | 0.693 | 6 | 1 | 100% |
| 9 | Chen, Xiaohong and Hong, Han and Tamer, Elie (2005) Measurement Error Models with Auxiliary Data | 0.585 | 3 | 1 | 100% |
| 10 | Freeman, Hugo and Weidner, Martin (2023) Linear panel regressions with two-way unobserved heterogeneity | 0.585 | 3 | 1 | 100% |
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