Xavier D'Haultfoeuille, Stefan Hoderlein, Yuya Sasaki
arXiv 29 Apr 2021 · Econometrics · publishedJournal of Econometrics (2022) · 30 citations (OpenAlex)
arXiv:2104.14458 · PDF · DOI · OpenAlex · Extracted main text
This paper studies the identification of causal effects of a continuous treatment using a new difference-in-difference strategy. Our approach allows for endogeneity of the treatment, and employs repeated cross-sections. It requires an exogenous change over time which affects the treatment in a heterogeneous way, stationarity of the distribution of unobservables and a rank invariance condition on the time trend. On the other hand, we do not impose any functional form restrictions or an additive time trend, and we are invariant to the scaling of the dependent variable. Under our conditions, the time trend can be identified using a control group, as in the binary difference-in-differences literature. In our scenario, however, this control group is defined by the data. We then identify average and quantile treatment effect parameters. We develop corresponding nonparametric estimators and study their asymptotic properties. Finally, we apply our results to the effect of disposable income on consumption.
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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 | Athey \ Imbens (2006) `Identification and inference in nonlinear difference-in-differences models', Econometrica 74, 431–497 | 1.000 | 13 | 4 | 100% |
| 2 | de Chaisemartin \ D'Haultfuille (2018) `Fuzzy differences-in-differences', Review of Economic Studies 85, 999–1028 | 0.928 | 5 | 3 | 80% |
| 3 | Graham \ Powell (2012) `Identification and estimation of average partial effects in `irregular' correlated random coefficient panel data models', Econo… | 0.644 | 2 | 2 | 100% |
| 4 | Hsieh (2003) `Do consumers react to anticipated income changes? evidence from the alaska permanent fund', American Economic Review 93(1), 397… | 0.644 | 2 | 2 | 100% |
| 5 | Johnson, Parker \ Souleles (2006) `Household expenditure and the income tax rebates of 2001', American Economic Review 96(5), 1589–1610 | 0.644 | 2 | 2 | 100% |
| 6 | Florens, Heckman, Meghir \ Vytlacil (2008) `Identification of treatment effects using control functions in models with continuous, endogenous treatment and heterogeneous e… | 0.511 | 2 | 1 | 100% |
| 7 | Imbens \ Newey (2009) `Identification and estimation of triangular simultaneous equations models without additivity', Econometrica 77, 1481–1512 | 0.511 | 2 | 1 | 100% |
| 8 | Kasy (2011) `Identification in triangular systems using control functions', Econometric Theory 27, 663–671 | 0.511 | 2 | 1 | 100% |
| 9 | Chernozhukov, Fernandez-Val, Hahn \ Newey (2013) `Average and quantile effects in non separable panel data models', Econometrica 81, 535–580 | 0.405 | 1 | 1 | 100% |
| 10 | Heckman \ Vytlacil (1998) `Instrumental variables methods for the correlated random coefficient model: Estimating the average return to schooling when the… | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 32 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Machine Learning for Staggered Difference-in-Differences and Dynamic Treatment Effect Heterogeneity | 0.405 | 1 | 1 |
| 2 | 1420 Identification with possibly invalid IVs | 0.405 | 1 | 1 |
| 3 | A quantile-based nonadditive fixed effects model | 0.405 | 1 | 1 |