arXiv 28 Feb 2023 · Econometrics · 6 citations (OpenAlex)
arXiv:2303.00083 · PDF · DOI · OpenAlex · Extracted main text
Dynamic logit models are popular tools in economics to measure state dependence. This paper introduces a new method to derive moment restrictions in a large class of such models with strictly exogenous regressors and fixed effects. We exploit the common structure of logit-type transition probabilities and elementary properties of rational fractions, to formulate a systematic procedure that scales naturally with model complexity (e.g the lag order or the number of observed time periods). We detail the construction of moment restrictions in binary response models of arbitrary lag order as well as first-order panel vector autoregressions and dynamic multinomial logit models. Identification of common parameters and average marginal effects is also discussed for the binary response case. Finally, we illustrate our results by studying the dynamics of drug consumption amongst young people inspired by Deza (2015).
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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 | Deza, M (2015) Is there a stepping stone effect in drug use? separating state dependence from unobserved heterogeneity within and between illic… | 1.000 | 11 | 3 | 100% |
| 2 | Kitazawa, Y (2022) Transformations and moment conditions for dynamic fixed effects logit models | 1.000 | 10 | 4 | 100% |
| 3 | Dobronyi, C., Gu, J., et al (2021) Identification of dynamic panel logit models with fixed effects | 1.000 | 10 | 4 | 100% |
| 4 | Magnac, T (2000) Subsidised training and youth employment: distinguishing unobserved heterogeneity from state dependence in labour market histories | 1.000 | 8 | 3 | 100% |
| 5 | Honoré, B. E. and Kyriazidou, E (2000) Panel data discrete choice models with lagged dependent variables | 0.971 | 12 | 4 | 92% |
| 6 | Chamberlain, G (1985) Heterogeneity, omitted variable bias, and duration dependence, page 3–38 | 0.928 | 5 | 4 | 80% |
| 7 | Bonhomme, S (2012) Functional differencing | 0.843 | 3 | 3 | 100% |
| 8 | Honoré, B. E. and Weidner, M (2020) Moment conditions for dynamic panel logit models with fixed effects | 0.827 | 23 | 6 | 57% |
| 9 | Card, D. and Hyslop, D. R (2005) Estimating the effects of a time-limited earnings subsidy for welfare-leavers | 0.811 | 4 | 2 | 100% |
| 10 | Hahn, J (2001) The information bound of a dynamic panel logit model with fixed effects | 0.737 | 4 | 2 | 75% |
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