Overview
Magne Mogstad is a professor of economics at the University of Chicago and a research associate at NBER. A Norwegian economist, he works broadly on labor economics, public economics, and program evaluation, with a focus on causal inference and partial identification methods. He is a co-author of Deshpande, Kellogg, Mogstad, and Tseng (2025) on the bounds-based decomposition of SSDI enrollment dynamics, and of Autor, Kostøl, and Mogstad (2015/2019) on household consumption insurance and DI.
Key Contributions
- Kostøl, Andreas Ravndal, and Magne Mogstad. (2014). "How Financial Incentives Induce Disability Insurance Recipients to Return to Work." American Economic Review 104(2): 624–655. Uses Norwegian DI program variation to identify the causal effect of earnings-based return-to-work incentives on DI recipients' labor supply.
- Autor, David H., Andreas Ravndal Kostøl, and Magne Mogstad. (2015/2019). "Disability Benefits, Consumption Insurance, and Household Labor Supply." NBER WP 23466; American Economic Review 109(9): 2905–2946. Uses Norwegian judge-lottery IV to decompose the household-level welfare effects of DI denial; identifies the causal spousal AWE; finds DI's consumption-insurance value is ~3.4× higher for single than for married applicants (WTP ~9,100vs. 2,700/capita).
- Deshpande, Kellogg, Mogstad, and Tseng (2025) — "Explaining the Historical Rise and Recent Decline in Social Security Disability Insurance Enrollment." Co-developer of the interaction-aware bounds framework for decomposing sequential decision problems; the approach applies partial identification tools to prevent double-counting of interaction terms across the five enrollment margins.
- Friedman, Lurie, Mogstad, and Chetty (2016) — "Long-Run Drivers of Disability Insurance Rates." Co-author of the SSA DRC working paper establishing the 4.8× intergenerational DI hazard gradient and the "good places paradox" in young adult DI receipt; ~50% of cross-CZ DI variation is causal.
- Friedman, Kellogg, Lurie, and Mogstad (2018) — "Explaining Geographic Differences in Young Disability Insurance Rates." Extended analysis separating sorting from causal local effects; shows education and taxes causally predict DI, segregation and inequality are sorting artifacts; direct DI–income mobility relationship is null (−0.22 correlation). See Geographic Variation in Disability Insurance.
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