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. Before joining Uconn, I was a postdoc associate at the MIT Center for Energy and Environmental Policy Research. I received my Ph.D. in Economics from Iowa State University.
Welcome to My Space
My Research
My research primarily explores the economic applications of mobility data, employing a comprehensive approach that involves various methodologies such as econometric analysis, empirical IO, and machine learning. This multifaceted approach is applied to address significant questions in the realms of environmental and food fields.
Food Access Disparity
grasping nutritional health disparities and refining the precision of food aid targeting;
Bringing the Neighborhood Farm to the Table: Can Farmers’ Markets Help Reduce Food Access Disparity?
with Cristina Connolly and Sandro Steinbach
Neighborhood disparities in food outlet access pose a significant concern for the US food system. Numerous attempts have been made in the past to address this concern, including farmer's markets. Farmers' markets offer potential benefits by providing direct access to fresh, locally sourced produce, however, the overall effectiveness of farmers’ markets in fully mitigating these disparities remains. Here, leveraging the cellphone mobility data on farmers' market visits nationwide, we quantify the extent of travel behavior to farmers' markets from 2019-2022. We link cell phone users with the socio-economic and food access characteristics of their residential areas to assess disparities in accessability and utilization of farmers’ markets across different communities. We note that low-access communities are less likely to visit farmer’s markets, travel longer distance, and experience elevated levels of income isolation, relative to their counterparts. To identify strategies that could improve market utilization, we developed a discrete choice model to analyze consumer preferences concerning farmers' market characteristics and to identify optimal locations for new farmers' markets in communities with limited access. Our results provide valuable insights for policy strategies designed to enhance food security in low food access communities.
The application of human mobility data in applied economic research holds considerable potential for deepening insights into diverse economic phenomena. This paper explores the motivations and methodologies driving the use of mobility data in economics. We begin by examining the motivations behind integrating this data source, highlighting its capacity to enhance the granularity and accuracy of economic models and theories. We continue with a comprehensive review of existing research utilizing mobility data that details its impact on understanding travel patterns, social interactions, health implications, and employment dynamics. Challenges inherent in leveraging this data, such as measurement errors, sampling biases, and data privacy concerns, are critically analyzed. The paper concludes by identifying future research opportunities that could leverage advanced computational techniques and interdisciplinary approaches to maximize the utility of mobility data in economic analyses, suggesting a robust framework for advancing our understanding of various economic phenomena.
Human Mobility
developing economic methodologies for mobility data applications;
Environmental (Dis)amenities
understanding individual behavior and preferences regarding environmental amenities and climate hazards;
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
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 $0.09 million 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
Environmental justice research has predominately focused on disparities in exposure to pollution, with comparatively less attention to inequities in access to and benefits derived from natural amenities. This study examines socioeconomic disparities in recreational preferences and welfare gains from water quality improvements using five waves of household data from the Iowa Lakes Valuation Project from 2004 to 2019. Applying a repeated random utility model, we find that low-socioeconomic-status households are consistently more sensitive to travel costs, while both low- and high-socioeconomic status (SES) groups exhibit positive marginal willingness to pay (MWTP) for water quality. The gap in MWTP follows a U-shaped trend over time, while disparities in non-marginal welfare gains show an inverse U-shape, peaking in 2009 and declining by 2019. Scenario analyses reveal that universal water quality improvements deliver larger recreational benefits to high-SES households, whereas site closures, such as the hypothetical closure of West Okoboji Lake, may impose greater welfare losses on low-SES households in some years. Models that ignore heterogeneous preferences underestimate both total welfare gains and distributional disparities. These findings underscore the need for equity-focused policies in both ex post program evaluations and ex ante site prioritization, ensuring inclusive access and more equitable distribution of environmental benefits.
Abstract
Analyses of policies that improve water quality often suggest that the costs far exceed the benefits. Keiser and Shapiro (2019a) suggests that this partially arises from the difficulty of accurately measuring the benefits. Measuring these benefits is often complicated by the lack of data on visitations. In this paper, we study the value of recreation amenities nationwide using data from mobile devices about aggregate visitor counts and dwell time at each water recreation site by home census block group. We combine the mobile movement data with data on water quality and weather to construct a comprehensive, novel, and detailed dataset of roughly 30k water-based recreational sites with linkage to recreation visits made by 22 million representative residents. Using these data, we construct aggregate share data of recreation visits from each census block group to each site. We develop a random coefficient logit model of site choice to estimate the welfare effects of water quality improvements in the US. Our results suggest recreators are willing to pay an average of $8.2 per trip for a 1-meter increase in Secchi depth in the sites they visited, ranging from $6.8 to $18.2 across census regions. We estimate that raising the water quality of all sites to match the cleanest site would yield $56.3 billion in benefits, while the annual welfare losses from the closure of the most popular and most polluted sites would amount to $18.6 billion and $2.6 billion, respectively. Our model provides a practical framework for water quality integrated assessment models, offering a spatially detailed and economically grounded approach to evaluate the benefits and costs of water quality policies.
Abstract
While a theoretically consistent cost of floods is a welfare loss from the event, existing estimates are primarily based on asset losses due to measurement challenges. In this paper, we leverage variations in the occurrence of High-tide flooding (HTF), highly disruptive, yet rarely destructive small-scale coastal floods, to estimate the economic cost of floods. Our analysis reveals that on the day of HTF, the average number of visitors per point of interest reduces by 5%, suggesting significant disruptions in daily lives. Further, we show that exposure to one additional day of HTF in the past 12 months reduces rental rates by 0.25% or $51. Using this parameter, we show that a lower bound economic cost of Presidential Disaster Declaration floods is $4 billion per year, suggesting that asset losses alone may substantially underestimate the true cost of floods.
When Nature Turns Hazy: How Wildfire Smoke Affects Outdoor Recreation
With Wendong Zhang and Yau-Huo (Jimmy) Shr
Abstract
Leveraging the Safegraph cellphone foot traffic data on recreational visits to 130k sites nationwide, we quantify the extent of avoidance behavior in outdoor recreation in response to wildfire smokes from 2018-2019. By utilizing the year-over-year variation in smoke exposure and an instrument approach, our results show that wildfire smoke exposure is main driver for the decrease in recreational visits and dwell times: a one standard deviation increase in weekly smoke exposure results in a 5-6% decrease in weekly visits and total dwell times. We show that visibility and odor, information about smoke, and past experience are the underlying mechanisms of the smoke-recreation relationship. We find some evidence of substitution across counties but limited shifts from outdoor to indoor activities. Visitors may adjust the timing of their visits within the month, with nighttime visits being more significantly affected. Finally, a back-of-envelope calculation suggests recreational costs arising from the recent wildfire incidents in 2018-2019 are approximately 8.1 billion (in 2018 currency), which emphasizes the importance of considering social costs incurred in distant locations when formulating strategies for disaster mitigation and response.
Research
Beyond Mobility Data
In addition to utilizing cell phone data, my research also utilizes large datasets from sources like retail scanners, housing transactions, and customs data to evaluate policy effectiveness and derive behavioral insights crucial for environmental and food policy making.
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 has become a favored strategy among food manufacturers to subtly raise the unit price due to increasing production costs. However, the effectiveness of policies aimed at alerting consumers to these covert price hikes per unit remains underexplored. Leveraging the variations in unit price disclosure regulations across different states, this paper studies the reduction in tuna can sizes stemming from a collusive effort among the major tuna producers and estimates the impact of price per unit disclosure regulations on consumer welfare. By developing and estimating a logit model for the demand and size selection of canned tuna, our findings reveal that consumers in states with unit price disclosure regulations are more responsive to unit price changes compared to those in states without such regulations. Our analysis suggests that implementing unit price disclosure regulations on canned tuna could enhance consumer welfare by approximately $7.64 to $13.59 million dollars annually.
Planes Overhead: How Airplane Noise Impacts Your Home’s Value
With Florian Allroggen, R. John Hansman, Christopher R. Knittel, Jing Li, and Juju Wang
Abstract
Air transport has facilitated faster city connections and spurred economic growth, while also generating significant environmental externality through airport noise pollution causing disruptions in surrounding communities. In this paper, we investigate the impact of this externality on housing market around three US airports using a quasi-experimental approach. Specifically, we use flight tracks and housing transaction data from 2011 and 2016 to estimate the impact of airplane noise from a change in the flight navigation policy and runway operations. Our results indicate that for every additional decible increase in the annual average day-night average sound level (DNL), there is a corresponding decrease in sales prices of around 0.6-1.0 percent. We investigate different noise metrics and discover that DNL emerges as the most influential factor in explaining the observed decline in housing prices. Using the estimates from our reduced form, we find residents value quietness, varying significantly across different spatial contexts. We also observe considerable diversity in the economic impact of airplane noise on households living near these airports, a pattern that appears to be associated with income disparities and racial composition. Our findings underscore the importance of assessing the social costs of airplane noise externalities and developing policies to mitigate their negative impact on nearby residents.
Integrating Recreational Benefits into Hedonic Property Value Models: Evidence from Iowa
With Yongjie Ji, Wendong Zhang, and Pengfei Liu
Abstract
When assessing water quality impacts, most property value hedonic models focus on local effects and ignore broader regional benefits. We integrate a two-stage model considering recreational and housing demand based on panel-household surveys and property transaction data from 2011 to 2019 in Iowa. Using an instrumental variable approach, we address endogeneity and measurement errors and characterize regional benefits based on observed lake-based water quality activities. Homeowners demonstrate a willingness to pay $1,046 for a 1 mg/L increase in dissolved oxygen in nearby lakes for recreational opportunities and $5,604 in housing for the same increase in local water bodies. Additional analysis suggests these capitalization effects are sensitive to alternative recreational activities, highlighting the need to identify all recreational activities to fully capture all regional recreational benefits. Our finding suggests that taking into account recreational benefits and measurement errors would increase the overall benefits of water quality improvements by around four times.
Research
Ongoing Projects and Additional Works
Experience
Teaching, Services, and Skills
Teaching Experience
Teaching Assistant: Principles of Microeconomics (ISU, 2016-2019), Economics of Discrimination (ISU, 2017-2019), Intermediate Environmental and Resource Economics (ISU, 2018), Microeconomics Analysis I (ISU, 2019)
Guest lecturer: Principles of Microeconomics (Uconn, 2024)
Teaching certificate: Transforming Your Research Into Teaching (TYRIT) (ISU, 2020)
Services and Skills
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 Economics (JAERE), Agricultural & Applied Economics Association Annual Meeting Abstract (AAEA), Southern Economics Association Annual Meeting Abstract (SEA)
Campus and Department Services: Economics Graduate Student Association (President, 2018), Economics Graduate Student Seminar (Coordinator, 2018), China Center for Human Capital and Labor Market Research (President, 2014)
Skills: Python, Stata, Matlab, R, QGIS, SQL, Latex, Office, JavaScript
Contact Me
I Want To Hear From You
Please fill out the form on this section to contact with me. Or call between 9:00 a.m. and 8:00 p.m. ET, Monday through Friday
Address
Ratcliffe Hicks Arena, Unit 108, Storrs, CT 06269
xibo.wan@uconn.edu
