Christoph Semken

Research

Climate change mitigation

“The Marginal Impact of Emission Reductions”

How much impact can one person have on climate change outcomes? This paper argues that it is likely much larger than commonly assumed and that changing beliefs can increase mitigation efforts. Mental models about the marginal impact of emission reductions are inconsistent with models used by climate scientists in three important ways. First, experimental subjects believe the expected impact of a small reduction in CO₂ emissions drops after passing certain global warming thresholds, whereas it is continuous in climate models. Second, they think that the impact is increasing in the reduction of others (strategic complementarity), while the opposite is true in most climate models. Third, they overestimate the change in emissions that is needed for a given impact. For example, if current national emission targets are implemented, climate models predict one additional ton of CO₂ emissions would put 8m² of vegetation at severe risk of ecosystem change and lead to the loss of 9 kiloliters of glacier ice. Subjects overestimate the amount of emissions that would lead to these outcomes by several orders of magnitude. Showing the climate model findings substantially increases both intentions to act on climate change and donations to offset emissions.

“Demand Responses to Pricing Food Item’s Environmental Externalities: Evidence from a Nationwide Field Experiment” (with Amelie Michalke, Tobias Gaukler and Susanne Stoll-Kleemann)
“Vegetarian*ism: Evidence from 200 Million Home Deliveries” (with Ruben Durante and Milan Quentel)

Methodology

“Specification analysis for technology use and teenager well-being: statistical validity and a Bayesian proposal” (with David Rossell), Journal of the Royal Statistical Society Series C (Applied Statistics), 2022.

A key issue in science is assessing robustness to data analysis choices, while avoiding selective reporting and providing valid inference. Specification Curve Analysis is a tool intended to prevent selective reporting. Alas, when used for inference it can create severe biases and false positives, due to wrongly adjusting for covariates, and mask important treatment effect heterogeneity. As our motivating application, it led an influential study to conclude there is no relevant association between technology use and teenager mental well-being. We discuss these issues and propose a strategy for valid inference. Bayesian Specification Curve Analysis (BSCA) uses Bayesian Model Averaging to incorporate covariates and heterogeneous effects across treatments, outcomes and sub-populations. BSCA gives significantly different insights into teenager well-being. It provides strong evidence that technology has relevant associations with teenager well-being: (1) well-being is negatively associated with electronic device usage, (2) social media use is negatively associated with self-assessed well-being but positively associated with parent-assessed well-being, and (3) has a stronger negative association with self-assessed well-being for girls compared to boys.

Social preferences

“Altruism under Endowment-Source Uncertainty”

Altruism depends on the source of one’s wealth: in the lab, participants give much less when an endowment is earned than when it comes as a windfall. In reality, however, there exists much uncertainty about the relative importance of effort and luck in determining income and wealth. In three experiments, I investigate altruism under endowment-source uncertainty. I find evidence that participants use different allocation rules under certainty and uncertainty, consistent with models of limited or costly cognition.

Pre-doctoral research

“Gauging the Gravity of the Situation: The Use and Abuse of Expertise in Estimating the Economic Costs of Brexit” (with Colin Hay), MaxPo Discussion Paper 21/3.

HM Treasury’s estimation of the economic consequences of Brexit – using standard macroeconomic models – during the EU referendum campaign represents a remarkable intervention in a highly politicized public debate. It raises a series of questions about the use of economic expertise. Through a detailed theoretical and empirical critique of the Treasury’s methodology – and a reassessment of the likely effects of Brexit in light of this – we cast doubt on the utility of their approach, highlighting methodological issues, unrealistic assumptions, and misrepresentations of established facts. In the process we seek to identify some of the wider implications for the use and potential abuse of economic expertise in highly charged political contexts, such as the EU referendum debate.

“Blue Mission Tracking: Real-Time Location of UN Peacekeepers” (with Walter Dorn), International Peacekeeping, 22(5): 545-64, 2015.

A basic but as yet unachieved goal for UN missions is to know the exact locations of their peacekeepers at any given time. Such tracking would help field missions plan operations, avoid and respond to ambushes, kidnappings and friendly fire incidents, rapidly send reinforcements and retrieve wounded peacekeepers, ultimately saving lives. Improved effectiveness could be obtained from ‘precision peacekeeping’, where soldiers, police and civilians are deployed to precise locations and events, while operational leaders follow their movements. Fortunately, tracking technology has improved considerably so that commercial solutions for real-time tracking of personnel and vehicles are now available at lower cost and increased accuracy and sophistication, while being more user-friendly. The advances in phone and vehicle tracking systems are reviewed here to identify the benefits, drawbacks and challenges, especially any political ones, for the United Nations. The world organization can benefit from modern blue mission tracking, without having to develop costly, customized solutions. Such initiatives have few technological or financial hurdles but the politics and institutionalization of continuous positional surveillance needs policy modernization, guided by a nuanced understanding of technological empowerment.