Sylvain Barde, Rowan Cherodian, Guy Tchuente
arXiv 3 Apr 2024 · Econometrics
arXiv:2404.02584 · PDF · DOI · OpenAlex · Extracted main text
We propose a novel estimation procedure for models with endogenous variables in the presence of spatial correlation based on Eigenvector Spatial Filtering. The procedure, called Moran's $I$ 2-Stage Lasso (Mi-2SL), uses a two-stage Lasso estimator where the Standardised Moran's I is used to set the Lasso tuning parameter. Unlike existing spatial econometric methods, this has the key benefit of not requiring the researcher to explicitly model the spatial correlation process, which is of interest in cases where they are only interested in removing the resulting bias when estimating the direct effect of covariates. We show the conditions necessary for consistent and asymptotically normal parameter estimation assuming the support (relevant) set of eigenvectors is known. Our Monte Carlo simulation results also show that Mi-2SL performs well against common alternatives in the presence of spatial correlation. Our empirical application replicates Cadena and Kovak (2016) instrumental variables estimates using Mi-2SL and shows that in that case, Mi-2SL can boost the performance of the first stage.
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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 | Cadena \ Kovak (2016) `Immigrants equilibrate local labor markets: Evidence from the great recession', American Economic Journal: Applied Economics 8(… | 0.961 | 18 | 5 | 89% |
| 2 | Kojevnikov, Marmer \ Song (2021) `Limit theorems for network dependent random variables', Journal of Econometrics 222(2), 882–908 | 0.899 | 11 | 3 | 73% |
| 3 | Kelejian \ Prucha (1998) `A generalized spatial two-stage least squares procedure for estimating a spatial autoregressive model with autoregressive distu… | 0.843 | 3 | 3 | 100% |
| 4 | Barde, Cherodian \ Tchuente (2023) Moran’s I based Lasso for models with spatially correlated data, Working papers, unpublished | 0.811 | 4 | 2 | 100% |
| 5 | Lam \ Souza (2016) `Detection and estimation of block structure in spatial weight matrix', Econometric Reviews 35(8-10), 1347–1376 | 0.644 | 2 | 2 | 100% |
| 6 | Lam \ Souza (2020) `Estimation and selection of spatial weight matrix in a spatial lag model', Journal of Business & Economic Statistics 38(3), 693… | 0.644 | 2 | 2 | 100% |
| 7 | Ahrens \ Bhattacharjee (2015) `Two-Step Lasso Estimation of the Spatial Weights Matrix', Econometrics 3(1), 1–28 | 0.644 | 2 | 2 | 100% |
| 8 | Griffith (2003) Spatial autocorrelation and spatial filtering: gaining understanding through theory and scientific visualization, Springer Scien… | 0.644 | 2 | 2 | 100% |
| 9 | Griffith (2000) `A linear regression solution to the spatial autocorrelation problem', Journal of Geographical Systems 2(2), 141–156 | 0.644 | 2 | 2 | 100% |
| 10 | Ahrens (2015) `Civil conflicts, economic shocks and night-time lights', Peace Economics, Peace Science and Public Policy 21(4), 433–444 | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 31 scored citations.