Jan Ditzen, Francesco Ravazzolo
arXiv 12 Dec 2022 · Econometrics · 1 citations (OpenAlex)
arXiv:2212.05841 · PDF · DOI · OpenAlex · Extracted main text
For western economies a long-forgotten phenomenon is on the horizon: rising inflation rates. We propose a novel approach christened D2ML to identify drivers of national inflation. D2ML combines machine learning for model selection with time dependent data and graphical models to estimate the inverse of the covariance matrix, which is then used to identify dominant drivers. Using a dataset of 33 countries, we find that the US inflation rate and oil prices are dominant drivers of national inflation rates. For a more general framework, we carry out Monte Carlo simulations to show that our estimator correctly identifies dominant drivers.
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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 | |
|---|---|---|---|---|---|
| Meinshausen2006 | unmatched citation key Meinshausen2006 | 1.000 | 11 | 3 | 100% |
| 2 | Sulaimanov \ Koeppl (2016) Graph reconstruction using covariance-based methods | 1.000 | 10 | 3 | 100% |
| 3 | Kapetanios, Pesaran \ Reese (2021) Detection of units with pervasive effects in large panel data models | 1.000 | 7 | 4 | 100% |
| 4 | Brownlees \ Mesters (2021) Detecting granular time series in large panels | 0.971 | 12 | 5 | 92% |
| 5 | Ahn \ Horenstein (2013) Eigenvalue Ratio Test for the Number of Factors | 0.928 | 4 | 3 | 100% |
| 6 | Friedman, Hastie \ Tibshirani (2008) Sparse inverse covariance estimation with the graphical lasso | 0.928 | 4 | 3 | 100% |
| 7 | Ciccarelli \ Mojon (2010) Global inflation | 0.874 | 7 | 2 | 100% |
| 8 | Zou (2006) The adaptive lasso and its oracle properties | 0.843 | 3 | 3 | 100% |
| 9 | Ahrens, Aitken, Ditzen, Ersoy, Kohns \ Schaffer (2020) A Theory-Based Lasso for Time-Series Data | 0.737 | 3 | 2 | 100% |
| 10 | Belloni, Chernozhukov, Hansen, Kozbur, Belloni, Chernozhukov, Hansen… (2016) Inference in High-Dimensional Panel Models With an Application to Gun Control | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 36 scored citations. 1 of these could not be matched to a bibliography entry, so only the citation key is shown.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Forecasting Oil Consumption: The Statistical Review of World Energy Meets Machine Learning | 0.644 | 2 | 2 |