Applied Microeconomics
Applied Microeconomics
The Applied Microeconomics research group unites researchers working on a broad array of topics within such areas as labour economics, economics of education, health economics, family economics, urban economics, environmental economics, and the economics of science and innovation. The group operates in close collaboration with the CAGE Research Centre.
The group participates in the CAGE seminar on Applied Economics, which runs weekly on Tuesdays at 2:15pm. Students and faculty members of the group present their ongoing work in two brown bag seminars, held weekly on Tuesdays and Wednesdays at 1pm. Students, in collaboration with faculty members, also organise a bi-weekly reading group in applied econometrics on Thursdays at 1pm. The group organises numerous events throughout the year, including the Research Away Day and several thematic workshops.
Our activities
Work in Progress seminars
Tuesdays and Wednesdays 1-2pm
Students and faculty members of the group present their work in progress in two brown bag seminars. See below for a detailed scheduled of speakers.
Applied Econometrics reading group
Thursdays (bi-weekly) 1-2pm
Organised by students in collaboration with faculty members. See the Events calendar below for further details
People
Academics
Academics associated with the Applied Microeconomics Group are:
Research Students
Events
Applied & Development Economics Seminar - Erzo Luttmer (Dartmouth)
Title: Living Large or Long? Preference Estimates from Completed-Life Stories (joint with Joshua Schwartzstein, Tom谩拧 Jagelka, Amitabh Chandra)
The paper will not be ready for sharing prior to the seminar, an abstract is as follows:
———Extended Abstract ———
The value of a year of life plays a crucial role in informing policy decisions related to healthcare, the environment, innovation, and safety regulations. Given the significance of a life year鈥檚 value for policymaking, estimates should accurately reflect people鈥檚 preferences. Currently, estimates are derived from individuals鈥� observed choices involving small risks of death and monetary compensation, such as their willingness to take riskier jobs for higher pay. However, these estimates have significant limitations: individuals may not correctly perceive small risks, may deviate from rationality for choices involving small probabilities, and those making such choices, like soldiers or firefighters, represent a non-representative sample. Furthermore, unobserved job characteristics related to risk can bias these estimates. Our paper introduces an alternative method for estimating the value of a life year, attempting to overcome these limitations. We present a broadly representative sample of U.S. respondents with choices between pairs of 鈥渃ompleted-life stories,鈥� asking which life they would prefer for themselves. By randomizing lifetime earnings and ages of death in each story, we estimate how the probability of choosing a particular story increases with higher lifetime earnings versus a later age of death. We find that a 7% increase in lifetime earnings increases the choice probability as much as a 1% increase in longevity, implying a Life Year Value (LYV) elasticity of 7. Consequently, a typical individual with median earnings of $80,000 annually values an additional life year at age 80 as equivalent to receiving an additional $5,700 per year for all working years, totaling approximately $225,000 over their lifetime. We validate our estimates by demonstrating high test-retest reliability across survey waves and establishing their robustness through a series of specification checks and additional randomizations. Furthermore, we estimate markedly higher LYV elasticities for individuals whose subjective attitudes indicate that they place an above-average value on an additional life year. A key methodological advantage of our approach is that respondents engage in a natural task—assessing whether a life was desirable—which avoids triggering cultural or social norms about paying for life extension. Moreover, our method does not entail decisions under uncertainty, thereby avoiding many known behavioral biases. An important substantive advantage of our approach is that it allows us to estimate how the Life Year Value varies with respondent characteristics, age of death, and lifetime earnings in a broadly representative population. We find that the LYV increases with lifetime earnings and decreases with later life years. Even when holding constant lifetime earnings and age of death, there is notable heterogeneity in the LYV across individuals. This suggests that tailoring policies to individual preferences can result in welfare improvements.
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