Hello, I'm
XIBO WAN(万溪博)
I am a postdoc associate in the Department of Agricultural and Resource Economics in University of Connecticut. I received my Ph.D. in Economics from Iowa State University. My research focus on understanding individual decision-making and valuation in environmental and food systems to inform evidence-based policy design. I am on the job market in academic year 2025-26 and available for interviews.
Email: xibo.wan@uconn.edu
Welcome to My Space
My Research
My research uses economic frameworks to study how individuals and firms respond to changing constraints—particularly in the environmental and food domains—with the goal of informing more effective and equitable policy design.
Environmental (Dis)amenities
understanding individual behavior and preferences regarding environmental amenities and climate hazards;
I Love That Dirty Water? Value of Water Quality in Recreation Sites
With Christopher R. Knittel and Jing Li (Job Market Paper)
Abstract
Analyses of U.S. water quality regulations often find that the estimated costs of improving surface water exceed the measured benefits. One explanation is that the benefits, particularly those related to recreation, are difficult to measure accurately due to limited data on where and how people engage in water-based activities. This paper provides new national evidence on the recreational benefits of cleaner water by linking large-scale mobility data with measures of water quality and weather conditions. Using anonymized mobile device data, we observe aggregate visitor counts and dwell times for roughly 22 million residents visiting 30,000 water recreation sites across the contiguous United States between 2018 and 2022. We develop a random-coefficients logit model of site choice to estimate how water quality affects recreation demand and welfare. The results indicate that recreators are willing to pay an average of $8.20 per trip for a one-meter increase in Secchi depth, with regional estimates ranging from $6.80 to $18.20. Improving all sites to match the cleanest observed site would yield total annual benefits of approximately $56.3 billion, while the closure of the most popular and most polluted sites would generate welfare losses of $18.6 billion and $2.6 billion, respectively. The framework provides a scalable and behaviorally grounded foundation for evaluating the welfare effects of water quality policies in integrated assessment models.
Abstract
Outdoor recreation plays a pivotal role in improving people’s physical and mental health, serving as a popular form of entertainment and a significant economic contributor. Limited access to these resources not only exacerbates health disparities but also deprives underserved areas of essential benefits like stress relief and community bonding, both of which are crucial for enhancing overall quality of life. This paper provides one of the first detailed analyses of water-based recreation at over 61,000 inland and coastal sites across the United States. We aim to explore disparities in recreational behavior across race, ethnicity, income, and socioeconomic status. Using Advan cellphone data from more than 70 million outdoor trips, representing 215,000 census block groups, we find that communities of color, rural areas, and socioeconomically disadvantaged groups are significantly underrepresented in water-based recreational visits. Despite living similar distances from recreational sites, these groups show notably different patterns in travel distance for water-based recreation. Additionally, we find Native Americans from underserved areas have to travel 3-5 times longer distances than other groups for water-based recreation. Our findings show that the extensive and frequent cellphone mobility data could reveal policy-relevant patterns especially those made by underserved Americans often overlooked in traditional household surveys.
Abstract
This paper examines the impact of fish consumption advisories on recreational behavior and visitor welfare using large-scale mobility data from Michigan. By integrating cellphone-based location data with a discrete choice modeling framework, we estimate the causal effects of advisories on recreation site selection and quantify the associated welfare benefits of disclosing risks. To address potential endogeneity, we employ an instrumental variable approach using the number of Toxic Release Inventory facilities in upstream watersheds. Our findings show that advisories significantly deter recreational visits, with an average visitor willing to pay approximately $72 per quarter to avoid sites under advisory. The deterrent effect is most pronounced during peak recreational seasons, particularly in the summer, when willingness to pay to avoid advisory sites rises to over $87 per quarter. We also find that full disclosure on advisories led to aggregated welfare benefits of $3.4 million annually, highlighting the broader recreational benefits of fish consumption advisories and emphasizing the need to account for these benefits when assessing the overall impact of advisories.
Abstract
While a theoretically consistent measure of flood costs is welfare loss, existing estimates are primarily
based on asset losses. This paper leverages high tide flooding (HTF)—highly disruptive yet rarely
destructive small-scale coastal floods—to estimate the economic cost of floods. We find that on HTF
days, visits to places decrease by 5%. Further, each additional day of HTF in the past year reduces
rents by 0.25%, which we interpret, based on the hedonic model, as the marginal willingness-to-pay to
avoid disruptions from HTF. Using this parameter, we estimate a lower-bound annual economic cost of
Presidential Disaster Declaration floods at $4 billion.
Abstract
We quantify how environmental improvements shape recreational welfare between socioeconomic groups, drawing on Iowa Lakes Valuation Project household visitation data from 2004 to 2019. We estimate a repeated random utility model with socioeconomic status (SES) interactions to capture heterogeneous preferences in lake recreation. Simulations of three counterfactual policy scenarios reveal that low-SES households consistently gain less from water quality improvements despite valuing them. A decomposition analysis reveals that overall demand-side factors (e.g., household preferences and demographics) explain 80%--90% of the welfare gap, whereas geographic access accounts for 10%--20%. Building on both supply and demand factors, we assess the distributional impacts of the state’s current lake restoration prioritization and propose an equity-informed alternative that reduces the SES disparity. These findings underscore the need to integrate recognition justice into environmental planning by explicitly accounting for behavioral constraints that limit the ability of disadvantaged communities to benefit from public environmental investments.
Abstract
Air transportation underpins global connectivity and economic growth but generates localized environmental externalities, notably aircraft noise. We examine how aviation noise affects housing markets using quasi-experimental variation from runway reconfigurations and FAA's Performance-Based Navigation procedures at three major U.S. airports. Our hedonic difference-in-differences estimates show that a one-decibel increase in annual day-night average sound levels reduces housing prices by 0.6-1.0 percent. Among noise metrics, average exposure explains property value impacts best. We also document heterogeneity in willingness to pay for quiet, correlated with income and race, highlighting the distributional costs of aviation policy.
Abstract
How does wildfire smoke affect outdoor recreation across the United States and what are the associated economic costs? Using cellphone mobility data of daily visits to all outdoor nature parks in the contiguous United States during 2018--2019, we combine wildfire plume, pollution, and weather information to provide the first nationwide assessment. Four findings emerge. First, each additional smoke day reduces recreational visits by more than 13%, with the largest declines during heavy smoke episodes. Second, such deterrence effect on recreation is primarily driven by the presence of smoke rather than variations in typical background pollution. Third, responses are highly heterogeneous across contexts: public awareness and prior smoke experience amplify avoidance, trips to non-water-adjacent sites show larger declines, and visits to national parks - where trip flexibility is lower - are less affected. Fourth, visitors adapt through temporal and spatial substitutions but only partially offset economic loss. We estimate that wildfire smoke caused $21 billion (2018 dollars) annually in lost recreational benefits, revealing large and underrecognized social costs extending far beyond burned areas.
Food System
Examining how individuals and firms adjust consumption and access strategies in response to shocks in the food system;
Abstract
Farmers’ markets aim to expand healthy food access, yet we lack scalable evidence on who uses them and which policies work best. We link nationwide 2019–2022 cell-phone mobility to neighborhood socioeconomic data and food-desert (FD) status, estimate a structural destination-choice model, and value policies in dollars via compensating variation. Four findings emerge. First, FD residents visit less and travel farther, choosing markets that are economically similar—but not racially similar—relative to their neighborhoods. Second, a decomposition attributes roughly 70% of the FD–non-FD visitation gap to travel-preference (demand) differences, about 20% to supply availability, and about 10% to market attributes; urban gaps reflect both travel costs and socio-demographic fit, while rural gaps are driven mainly by high travel costs and sparse supply. Third, policy simulations indicate that universal SNAP acceptance would close about 18% of the gap, universal evening hours about 33%, and adding one representative market per FD CBG nearly 58%, with especially large rural gains. Fourth, the benefit–cost analysis shows SNAP delivers the highest return per public dollar, new markets generate large absolute benefits–particularly in rural areas–at higher cost, and evening hours are most valuable where evening demand is strong.
Abstract
Political and economic tensions, which often jeopardize trade, are rising among the world’s major powers, and countries like China are more frequently using food-related trade actions to deal with deteriorating political relations. Using an event study approach, this paper investigates how importers respond to lasting political tensions by examining China’s seafood importers’ responses to the six-year Norway-China political tensions after Norway awarded Liu Xiaobo, a Chinese political dissident, a Nobel Peace Prize in 2010. Our results reveal firm-level responses at both the intensive and extensive margins. At the intensive margin, firms that imported Norwegian fresh salmon before the sanction saw a 20% persistent decline in their fresh salmon import value and an 80% decrease in the import share of Norwegian fresh salmon products over our study period. At the extensive margin, we find a trade diversion effect that firms imported fresh salmon from Norway to other countries and regions, but also a consistent "political hedging" effect three years after sanction with a 20% decline in the maximum import share from any particular country or region, even if not Norway.
Abstract
Shrinkflation, the downsizing of packages without proportional price cuts, raises effective prices in ways that are often difficult for consumers to detect under bounded attention. We exploit a documented episode of product downsizing, combined with preexisting state-level variation in unit price disclosure rules, to identify how information design affects consumer behavior and welfare. Using a matched sample of scanner data and a control function approach, we show that consumers in regulated states are 130% more responsive to unit price changes, consistent with disclosure increasing the salience of the relevant price metric. Counterfactual simulations indicate that nationwide disclosure would raise annual consumer surplus by $2.57 million in the short term and $5.82 million in the long term once retailers adjust prices strategically. At present, only 16 states regulate unit price labeling on food items. Our findings demonstrate that such labeling improves consumer decision making under shrinkflation.
Abstract
Human mobility data has emerged as a transformative tool for applied economic research, offering unprecedented granularity in analyzing human behaviors and spatial dynamics. This paper reviews how large-scale mobility data can enhance economic analyses, highlighting its contributions to understanding travel behavior, labor markets, social interactions, and health outcomes. We discuss its advantages over traditional mobility data sources, which include real-time location information and fine spatial resolution, while addressing key empirical challenges such as measurement errors, sampling biases, and privacy concerns. Additionally, we examine how machine learning and interdisciplinary approaches can enhance the usefulness of mobility data for applied economic research. By synthesizing previous studies and identifying future directions, our review provides a roadmap for leveraging human mobility data at scale to refine economic models and inform policy decisions, underscoring the potential of human mobility data to enhance empirical research across various economic research fields.
Abstract
Accurately estimating the welfare impacts of environmental changes in recreation demand modeling requires robust causal inference methods. However, a persistent challenge remains as the zero market share issue restricts the causal inference application to broader regions and longer periods. To address this, we integrate empirical Bayes posterior mean estimation into a two-step random coefficient logit model, ensuring that sites with low or zero visitation are properly incorporated without distorting demand estimates. We apply this framework to the 2021 Huntington Beach oil spill, using high-frequency cellphone data to track changes in beach visits. By combining the Synthetic Difference-in-Differences (SDID) approach with empirical Bayes-adjusted market shares, we isolate the causal effects of temporary beach closures on visitor welfare. Our findings reveal that Huntington Beach experienced the largest and most prolonged welfare loss, with an estimated aggregate loss of $1.03 million and weekly losses of $83k persisting beyond the initial closure. In contrast, Newport Beach and Laguna Beach exhibited faster recoveries. This study advances recreation demand modeling by refining demand estimation for low-visit sites and strengthening causal inference techniques for environmental disruptions, ultimately providing a more reliable framework for assessing the economic costs of beach closures and other environmental policy interventions.
Abstract
While mobility data has emerged as a promising alternative for assessing the economic value of recreation, the extent to which challenges such as measurement error, privacy-accuracy trade-offs, sampling biases, and choice set definition impact economic valuation remains unknown. In this paper, we evaluate the impact of precision, privacy, and representation in cell phone data on the accuracy of recreation demand estimation by applying a random utility model to analyze recreation visits at Cape Cod beaches from 2019-2022. Specifically, we estimate the marginal willingness to pay (MWTP) for avoiding fecal bacteria contamination under various data-handling practices. We find an average MWTP of $8.92 per visit when using the proposed practices, such as refined visit definitions, sampling weights, and long-term choice sets. Deviations from these practices introduce significant biases: relaxing the minimum dwell time and applying differential privacy reduce MWTP by 57% and 65%, respectively, while short-term choice set definition inflates it by 10%. Our findings underscore the need for judicious data processing to ensure accurate non-market valuations in mobility data applications and highlight the trade-offs between data privacy and estimation accuracy. These results provide valuable insights into effectively utilizing mobility data for environmental valuation and policymaking.
Abstract
This study assessed the impact of Texas Senate Bill 8 (SB 8), a restrictive abortion law, on family care clinic utilization across Texas using large-scale GPS mobility data from Veraset, covering March 2021 to February 2022. By applying k-means clustering to visit frequency and dwell time, we categorized visitors into patients, night-shift practitioners, and day-shift practitioners or administrative staff, and compared their behaviors before and after SB 8 implementation. We found that following the law’s enactment, day-shift practitioners and staff experienced a significant increase in visit frequency (+8.74 visits per month) with little change in time spent at clinics, suggesting increased administrative or clinical demands. Urban patients increased their clinic visits (+1.65/month) but reduced their time spent per visit (-38.61 minutes), while visits from rural and suburban patients stagnated, despite no change in physical clinic access. These patterns indicate that SB 8 generated broader disruptions in family healthcare delivery and access, particularly burdening already underserved communities and highlighting how restrictive abortion legislation can trigger systemic ripple effects throughout the healthcare system.
Human Mobility
developing economic methodologies for mobility data applications;
This interactive dashboard expands our research by translating PFAS exposure estimates—across industrial, drinking water, recreational, and dietary pathways—into ZIP-level risk scores and enabling community-level analysis to support targeted environmental health policies.
Extensions
PFAS Exposure Risk Dashboard
Research
Ongoing Projects
Employment Effects of Environmental Regulations: Evidence from the Clean Water Act
Coauthors: Jianwei Ai, Anton Yang, Wendong Zhang
Environment
Out-of-sight, Out-of-mind? Distance Decay in Water Quality Value
Coauthors: Emmett Reynier
Human Mobility
Environment
Estimating the Value of Food Access using Cell Phone Data
Coauthors: Mike Vo, Cristina Connolly, Sandro Steinbach
Human Mobility
Food
Differential Privacy and Cellphone Mobility Data
Coauthors: Mike Vo, Cristina Connolly, Sandro Steinbach
Human Mobility
Disparities in Wildfire Evacuation
Coauthors: Juanxian Tang, Ruohao Zhang
Human Mobility
Environment
Business Spillover Effects of EV Chargers
Coauthors: Juanxian Tang, Ruohao Zhang
Human Mobility
Energy
Experience
Teaching, Services, and Skills
“
Teaching across microeconomics and environmental economics with guest lectures and pedagogy training.
Teaching
- Teaching Assistant: Principles of Microeconomics (ISU, 2016–2019); Economics of Discrimination (ISU, 2016–2019); Intermediate Environmental (2018); Resource Economics (2018); Microeconomic Analysis I (2019)
- Guest Lecturer: Principles of Microeconomics (UConn, 2024); Energy Economics (UConn, 2025) [slides]
- Certificate: TYRIT (ISU, 2020) [certificate] [syllabus]
“
Peer review for leading journals and NSF programs in environmental & resource economics.
Referee
- National Science Foundation (NSF, SBIR/STTR);
- Journal of Regional Science (JRS); Canadian Journal of Agricultural Economics (CJAE); Journal of the Association of Environmental and Resource Economists (JAERE); Journal of Environmental Economics and Management (JEEM); Land Economics; Economic Journal
- Climatic Change
“
Leadership and coordination in graduate associations and research centers.
Campus & Department
- President, Economics Graduate Student Association (2018)
- Coordinator, Graduate Student Seminar (2018)
- President, China Center for Human Capital & Labor Market Research (2014)
“
Quantitative and geospatial toolset for large-scale microdata and visualization.
Skills
- Python, R, Stata, Matlab
- QGIS, SQL, LaTeX, Office
- JavaScript (web/GEE)
Contact Me
Where You Can Find Me
Please feel free to reach out to schedule an in-person or Zoom meeting, or call anytime between 9:00 am – 8:00 pm ET, Monday through Friday.
