Upcoming departmental seminars are listed below
All seminars will take place in Room 250A, Agricultural Administration Building (2120 Fyffe Rd.) from 10:30am-12:00pm unless otherwise noted. Light refreshments will be served from 10:00-10:30 in the reception area outside of room 250A. We look forward to seeing you!
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Upcoming seminars:
February 16: Dr. Nathan Hendricks (Kansas State University)
Title: "Local Economic Spillovers of Irrigation from the High Plains Aquifer to the Agricultural and Non-Agricultural Sectors"
Abstract:
Do improvements in agricultural productivity generate local economic spillovers? In this paper, we exploit historical changes in economic activity overlying the High Plains Aquifer compared to counties outside the Aquifer to estimate how crop productivity improvements due to irrigation affected the livestock, agribusiness, and non-agricultural sectors. We find that the improvement in crop productivity led to large and significant increases in livestock production and changes in farm structure. We replicate Hornbeck and Keskin's (2015) results that there are minimal average effects on non-agricultural sectors, but we also explore heterogenous treatment effects and find significant impacts in regions that are depleting the resource the fastest. Together, these results indicate that increases in agricultural productivity can generate significant local economic spillovers under certain conditions.
March 1: Dr. Shanjun Li (Cornell University)
Title: "Drive Down the Cost: Learning by Doing and Government Policy in the Electric Vehicle Battery Industry"
Abstract: The global battery industry has achieved significant cost savings: electric vehicle (EV) battery costs have dropped by more than 90% over the past decade. This study assesses the extent to which this sharp decline in lithium-ion battery prices is attributable to learning-by-doing in battery production, and quantifies the impact of two types of government policies (e.g., consumer subsidies and domestic content requirement) on learning, technology diffusion, and industry dynamics. Based on rich data consisting of model-level sales, prices, and attributes of EVs for 13 top EV countries, and information on battery suppliers and characteristics, we estimate a structural model of the global EV industry, accounting for consumer vehicle choices, EV makers' pricing decisions, and bilateral bargaining between EV manufacturers and battery suppliers over battery prices. Our estimates show that learning-by-doing explained a substantial portion of the observed battery cost reductions, and that learning-by-doing greatly magnified the impact of EV consumer subsidies on adoption. We then conduct simulations to examine the impacts of domestic content requirement, a strategy adopted by China and more recently the US., on market share dynamics and global EV adoption. Our results suggest that China's whitelist policy nearly doubled the market share of Chinese battery suppliers mostly at the expense of South Korean suppliers.
March 6: Dr. Martin Smith (Duke University)
Title: "Causality, Equimarginality, and Modeling in Renewable Resource Economics"
Time: Wednesday, March 6, 2024: 3:30-5:00pm
Location: Room 250A Ag Admin
Abstract:
The intersection of dynamic modeling and econometrics routinely produces surprises in renewable resource economics. In some settings, modeling can explain empirical results that are puzzling but otherwise causally well identified. In other settings, modeling can diagnose problems with causal identification strategies. In coupled human-natural systems—of which bioeconomic and other renewable resource systems are a subset—treated units are coupled pairings of the human system (e.g., a fishing fleet) and the natural system (e.g., a fish stock). Modeling these systems can reveal when counterfactuals fail to account for dynamic non-monotonic responses to treatment, such as cycling, or the plausible timing of treatment effects. Modeling can also call into question whether dependent variables meaningfully capture the outcome intended. In coupled human-natural systems, spatial differences in treatment status are often used to identify causal effects. However, in these systems, human mobility is a mechanism that can lead to statistical interference. Modeling can diagnose the severity of the problem and offer ways to bound the bias of associated treatment effects. Taken together, these insights question whether the field’s heavy emphasis on reduced-form causal inference approaches is consistent with the equimarginal principle.
March 22: Dr. Marco Gonzalez-Navarro (University of California, Berkeley)
Title: "Immigration and Slums"
Abstract: South-South international migration is an increasingly important phenomenon, yet we know little about its impact on housing dynamics in developing country cities, where informal housing supply in the form of slums is a key consideration. This paper investigates the causal effect of international immigration on slum formation and growth in Chile, a country that experienced a fourfold increase in immigration in the past decade. To do this, we create a unique panel dataset with information on all slums in Chile as well as the universe of international immigrants and their destination municipalities. Using both a high-frequency within-slum analysis as well as a long-difference shift-share instrumental variable approach at the municipal level, we find a robust positive relationship between international immigration and slum creation and growth. This is evident from observed increments in the number of slums, the population residing in slums (both native and migrant), and the expansion of slum footprints. Notably, international immigration can account for all of the observed slum expansion in the study period. We further provide evidence of the important role that the market for affordable housing plays in mediating the relationship between immigration and slums. The surge in demand for housing, unmet by a concomitant increase in affordable housing supply, resulted in increases in rental prices, which in turn compelled low-income households to seek accommodation in informal slum settlements. Consistent with the housing market mechanism, the effects of immigration on slums are stronger in more rugged municipalities, where we show housing supply elasticities are also lower. Alternative mechanisms such as immigration effects on wages, employment, or poverty rates do not explain these results.
April 5: Dr. Priya Mukherjee (University of Wisconsin—Madison)
Title: TBA
Abstract:
TBA
April 12: Dr. Timothy Beatty (University of California, Davis)
"AAEA Presidential Address Preview"
Abstract:
TBA