Daniele Ballinari, Alexander Wehrli
arXiv 15 Nov 2024 · Econometrics
arXiv:2411.10009 · PDF · DOI · OpenAlex · Extracted main text
We introduce a double/debiased machine learning (DML) estimator for the impulse response function (IRF) in settings where a time series of interest is subjected to multiple discrete treatments, assigned over time, which can have a causal effect on future outcomes. The proposed estimator can rely on fully nonparametric relations between treatment and outcome variables, opening up the possibility to use flexible machine learning approaches to estimate IRFs. To this end, we extend the theory of DML from an i.i.d. to a time series setting and show that the proposed DML estimator for the IRF is consistent and asymptotically normally distributed at the parametric rate, allowing for semiparametric inference for dynamic effects in a time series setting. The properties of the estimator are validated numerically in finite samples by applying it to learn the IRF in the presence of serial dependence in both the confounder and observation innovation processes. We also illustrate the methodology empirically by applying it to the estimation of the effects of macroeconomic shocks.
appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.
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 | Chernozhukov, Victor and Chetverikov, Denis and Demirer, Mert and Du… (2018) Double/debiased machine learning for treatment and structural parameters | 1.000 | 17 | 5 | 100% |
| 2 | Joshua D. Angrist and Òscar Jordà and Guido M. Kuersteiner (2018) Semiparametric Estimates of Monetary Policy Effects: String Theory Revisited | 1.000 | 15 | 5 | 100% |
| 3 | Davidson, James (2021) Stochastic Limit Theory: An Introduction for Econometricians | 1.000 | 6 | 3 | 100% |
| 4 | Whitney K. Newey and Kenneth D. West (1994) Automatic Lag Selection in Covariance Matrix Estimation | 1.000 | 5 | 5 | 100% |
| 5 | Òscar Jordà (2005) Estimation and Inference of Impulse Responses by Local Projections | 1.000 | 5 | 3 | 100% |
| 6 | Kiefer, Nicholas M and Vogelsang, Timothy J (2005) A new asymptotic theory for heteroskedasticity-autocorrelation robust tests | 0.928 | 4 | 3 | 100% |
| 7 | Whitney K. Newey and Kenneth D. West (1987) A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix | 0.874 | 6 | 2 | 100% |
| 8 | Semenova, Vira and Goldman, Matt and Chernozhukov, Victor and Taddy,… (2023) Inference on heterogeneous treatment effects in high-dimensional dynamic panels under weak dependence | 0.874 | 5 | 2 | 100% |
| 9 | Adamek, Robert and Smeekes, Stephan and Wilms, Ines (2024) Local Projection Inference in High Dimensions | 0.843 | 3 | 3 | 100% |
| 10 | Lazarus, E. and Lewis, D. J. and Stock, J. H. and Watson, M. W (2018) HAR Inference: Recommendations for Practice | 0.843 | 3 | 3 | 100% |
Showing the top 10 of 98 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.