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Accounting for Unobservable Heterogeneity in Cross Section Using Spatial First Differences

Hannah Druckenmiller, Solomon Hsiang

arXiv 16 Oct 2018 · Econometrics · 4 citations (OpenAlex)

arXiv:1810.07216 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We develop a cross-sectional research design to identify causal effects in the presence of unobservable heterogeneity without instruments. When units are dense in physical space, it may be sufficient to regress the "spatial first differences" (SFD) of the outcome on the treatment and omit all covariates. The identifying assumptions of SFD are similar in mathematical structure and plausibility to other quasi-experimental designs. We use SFD to obtain new estimates for the effects of time-invariant geographic factors, soil and climate, on long-run agricultural productivities --- relationships crucial for economic decisions, such as land management and climate policy, but notoriously confounded by unobservables.

Citation extraction

39
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in-text mentions
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distinct cited
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main-text words

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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Yatchew, Adonis (1997) An elementary estimator of the partial linear model0.87472100%
2Conley, Timothy G (1999) GMM estimation with cross sectional dependence0.87452100%
3Robinson, Peter M (1988) Root-N-consistent semiparametric regression0.81142100%
4Schlenker, Wolfram and Michael J Roberts (2009) Nonlinear temperature effects indicate severe damages to US crop yields under climate change0.69351100%
5Mendelsohn, Robert, William D Nordhaus, and Daigee Shaw (1994) The impact of global warming on agriculture: a Ricardian analysis0.64441100%
6Newey, Whitney K. and Kenneth D. West (1987) A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix0.64441100%
7Anselin, Luc (1988) Spatial econometrics: methods and models, vol. 40.58531100%
8Black, Sandra E (1999) Do better schools matter? Parental valuation of elementary education0.58531100%
9Burke, Marshall and Kyle Emerick (2016) Adaptation to Climate Change: Evidence from US Agriculture0.58531100%
10Deschênes, Oliver and Michael Greenstone (2007) The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather0.58531100%

Showing the top 10 of 39 scored citations.