arXiv 26 Jun 2023 · Econometrics
arXiv:2306.15000 · PDF · DOI · OpenAlex · Extracted main text
Social disruption occurs when a policy creates or destroys many network connections between agents. It is a costly side effect of many interventions and so a growing empirical literature recommends measuring and accounting for social disruption when evaluating the welfare impact of a policy. However, there is currently little work characterizing what can actually be learned about social disruption from data in practice. In this paper, we consider the problem of identifying social disruption in an experimental setting. We show that social disruption is not generally point identified, but informative bounds can be constructed by rearranging the eigenvalues of the marginal distribution of network connections between pairs of agents identified from the experiment. We apply our bounds to the setting of Banerjee et al. (2021) and find large disruptive effects that the authors miss by only considering regression estimates.
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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 | Banerjee, Breza, Chandrasekhar, Duflo, Jackson and Kinnan (2021) Changes in social network structure in response to exposure to formal credit markets | 1.000 | 19 | 4 | 100% |
| 2 | Finke, Burkard and Rendl (1987) Quadratic assignment problems | 0.843 | 5 | 4 | 60% |
| 3 | Cela (2013) | 0.843 | 3 | 3 | 100% |
| 4 | Whitt (1976) Bivariate distributions with given marginals | 0.794 | 6 | 5 | 50% |
| 5 | Molinari (2020) Microeconometrics with partial identification | 0.737 | 3 | 3 | 67% |
| 6 | Graham (2020) Network data | 0.673 | 23 | 4 | 30% |
| 7 | Lovász (2012) | 0.659 | 7 | 4 | 29% |
| 8 | Fréchet (1951) Sur les tableaux de corrélation dont les marges sont données | 0.644 | 2 | 2 | 100% |
| 9 | Heckman, Smith and Clements (1997) Making the most out of programme evaluations and social experiments: Accounting for heterogeneity in programme impacts | 0.644 | 2 | 2 | 100% |
| 10 | Hoeffding (1940) Masstabinvariante korrelationstheorie | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 60 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Endogenous Interference in Randomized Experiments | 0.405 | 1 | 1 |