About

Mona Ahmadiani is a Research Assistant Professor in the Department of Agricultural Economics at Texas A&M University. She holds a B.S. in Economics from the University of Tehran, an M.S. in Environmental Economics from the University of Tehran, and a Ph.D. in Agricultural and Applied Economics from the University of Georgia. Her areas of expertise include Environmental and Resource Economics and Well-being Economics. She is a member of Texas A&M AgriLife, which encompasses Texas A&M AgriLife Extension Service, Texas A&M AgriLife Research, Texas A&M Forest Service, Texas A&M Veterinary Medical Diagnostic Lab, and the College of Agriculture & Life Sciences.

Research topics

• Sociology
• Political Science
• Economics
• Geography
• Finance
• Business
• Psychology
• Demographic economics
• Actuarial science
• Meteorology
• Economic growth
• Demography
• Social psychology

Selected publications

• Disaggregating the Well-Being Effects of Creative Destruction: The Roles of Cross- and Within-Sector Job Reallocation

  Applied Research in Quality of Life · 2026-03-20

  articleOpen access1st authorCorresponding

  Abstract We investigate how labor market dynamism associated with Schumpeterian creative destruction affects individuals’ subjective well-being (SWB), using data from the Gallup U.S. Daily Poll and the U.S. Census Quarterly Workforce Indicators from 2009 to 2016. By decomposing job turnover into within-sector and cross-sector reallocation which is indicative of labor market frictions and structural unemployment respectively, and by accounting for variation across 884 Core-Based Statistical Areas (CBSAs), we provide a nuanced analysis of how business dynamism is associated with SWB across worker groups and geographic space. Our approach accounts for heterogeneity in labor force participation and worker characteristics, offering a richer perspective on the interaction between local labor markets and individual well-being. We find that a 1% change in measures of creative destruction (e.g., total job turnover, within-sector turnover, and cross-sector turnover) corresponds to a 0.54 to 0.65 point change on a 0–10 SWB scale, underscoring the importance of distinguishing among labor market metrics when analyzing well-being impacts. We also find that distinguishing between cross-sector and within-sector turnover is critical to understanding the differential impacts of creative destruction, as each dimension affects workers in distinct ways. Moreover, the magnitude and direction of these effects vary by education, employment status, and gender, highlighting the importance of accounting for socio-demographic heterogeneity in analyses of labor market dynamism.

  PublisherOA PDFDOI

• Valuing Offshore Habitat to Recreational Anglers Using Cellphone Location Data

  Land Economics · 2026-02-20

  articleOpen access1st authorCorresponding

  <h3>Abstract</h3> Offshore structures, including operational and reefed energy platforms, strengthen marine habitats and generate economic value, motivating interest in quantifying their net benefits. We combine a Random Utility Model with Murdock9s (2006) site-choice approach to estimate the nonmarket value of offshore structures to recreational anglers in the Western Gulf of Mexicoi (2019-2022). Recreational fishing trips are identified in cellphone location data using a machine learning classifier trained on Automatic Identification System data. Location choices indicate that anglers value destinations farther offshore, particularly those with operating and reefed energy platforms, while other artificial reefs generate smaller and spatially variable benefits.

  PublisherOA PDFDOI

• Valuing Offshore Manmade Structures for Recreational Fishing: A Joint Estimation of Stated and Revealed Preferences

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access
  PublisherDOI

• Fishing for Anglers in a Sea of Data: Using Mobility Data to Identify and Track Marine Recreational Fishing

  Fish and Fisheries · 2025-12-01

  articleOpen access1st author

  ABSTRACT Analysing recreational anglers in marine waters presents several challenges. First, while there are well‐established approaches to estimate fishing effort, they are only as good as the coverage of the underlying data, which invariably has blind spots that can bias estimates. Additionally, tracking anglers' movements over time and their fishing locations in the open water is nearly impossible. This paper demonstrates the potential value of passively collected mobility data, GPS coordinates with timestamps from smartphones, for the analysis of marine recreational fishing. Using a classification process that includes supervised machine learning algorithms, we identify over 16,000 recreational fishing trips in the Gulf of Mexico from 2019 to 2022. We then categorise the identified trips into two groups: ‘station trips’, which are from places where creel surveys are conducted, and ‘non‐station trips’, which originate from locations not covered by creel data. We find that about 75% of all trips in the Gulf are station trips, though there is substantial variation across states. We examine differences in the on‐water behaviour of the two groups and study the spatial and temporal nature of these fishing trips. For validation of our proposed method, we compare the spatial and temporal variation of our identified trips based on mobility data with administrative data from Texas, Alabama, and Mississippi collected by government agencies. Correlations range from 0.63 to 0.94, providing strong evidence that our algorithm yields valid measures of recreational fishing effort, which can inform marine resource managers where such data are not available.

  PublisherOA PDFDOI

• Estimating Deprivation Cost Functions for Power Outages During Disasters: A Discrete Choice Modeling Approach

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Heterogeneous impact of anti-bullying laws on school bullying in the State of Georgia

  PLoS ONE · 2025-09-26

  articleOpen access1st authorCorresponding

  The increasing prevalence of bullying behavior has made anti-bullying laws (ABL) and policies a public health priority in the United States. Using 2007-2016 data from the Georgia Student Health Survey 2.0 on 6-12 grade public school students, we examine the relationship between two ABLs-with different levels of stringency-and the prevalence of bullying behavior in the state of Georgia. We find that although the implementation of both Georgia's ABLs is associated with significant declines in the prevalence of bullying victimization, the more stringent ABL is associated with substantially larger reductions in reported cases. Our heterogeneity analysis based on external environment characteristics shows that the more stringent ABL is associated with smaller reductions in bullying victimization incidents in schools with a higher share of students enrolled in the federally subsidized school lunch program. The more stringent ABL is also associated with larger increases in bystanders' willingness to intervene in school districts with higher poverty rates among children aged 5-17. Lastly, we analyze disparities in bullying victimization reporting at the school level and find that students tend to report higher bullying victimization rates than school personnel, and that the two ABLs are associated with larger reductions in the student reporting than in personnel reporting. Our results also show that the reporting disparities fade away when ABLs are in place, providing further evidence of the role of ABLs in mitigating bullying victimization reporting discrepancies.

  PublisherDOI

• Disaggregating the Well-Being Effects of Creative Destruction: The Role of Sectoral and Within-Sector Job Reallocation

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Estimating deprivation cost functions for power outages during disasters: A discrete choice modeling approach

  International Journal of Disaster Risk Reduction · 2025-10-07 · 4 citations

  articleOpen access

  Systems for the generation and distribution of electrical power represents critical infrastructure and, when extreme weather events disrupt such systems, this imposes substantial costs on consumers. These costs can be conceptualized as deprivation costs—an increasing function of time without service—quantifiable through individuals' willingness to pay for power restoration. Despite widespread recognition of outage impacts, a gap in the research literature exists regarding the systematic measurement of deprivation costs. This study addresses this deficiency by developing and implementing a methodology to estimate deprivation cost functions for electricity outages, using stated preference survey data collected from Harris County, Texas. This study compares multiple discrete choice model architectures, including multinomial logit and mixed logit specifications, as well as models incorporating Box–Cox and exponential utility transformations for the deprivation time attribute. The analysis examines heterogeneity in deprivation valuation through sociodemographic interactions, particularly across income groups. Results confirm that power outage deprivation cost functions are convex and strictly increasing with time. Additionally, the study reveals both systematic and random taste variation in how individuals value power loss, highlighting the need for flexible modeling approaches. By providing both methodological and empirical foundations for incorporating deprivation costs into infrastructure risk assessments and humanitarian logistics, this research enables policymakers to better quantify service disruption costs and develop more equitable resilience strategies.

  PublisherDOI

• Discrete choice experiment estimates on the value of soil health attributes in Central Texas

  Ecological Economics · 2025-04-18 · 1 citations

  articleOpen access

  When farmers adopt conservation tillage, they are making a management change that is expected to improve manageable characteristics of soil health. The current literature on the value of soil health, however, primarily focuses on the value of inherent soil characteristics. In this paper we close the gap in the literature by estimating the value of improvements in soil health. Using a sample of farmers in Texas' Brazos River Watershed and a stated-preference discrete-choice experiment, we elicit preferences for improvements in water infiltration, surface compaction, and organic matter content, characteristics that can be realistically improved by adopting a conservation tillage. For soil improvements roughly equivalent to what could be achieved by adopting no-till, we find that, on average, farmers are willing to pay $50–100 per acre per year to improve water infiltration, $20–50 to reduce surface compaction, and $2–11 per acre to improve organic matter content. We examine preference heterogeneity using sub-samples of the population, latent class specifications, and mixed-logit models, and find substantial variation in willingness to pay across farmers. Our findings offer insights into the value farmers place on soil health, but also that there is a great deal of variation in those values, which may help explain why soil conservations practices are not widely used in our study region. • Farmers in the Brazos River Watershed value water infiltration improvements over organic matter. • Willingness to pay for soil health improvements varies by farmer characteristics and attitudes. • Farmers in the Brazos River Watershed would pay $92 for soil health gains from conservation tillage.

  PublisherDOI

• Fishing for Anglers in a Sea of Data: Using Mobility Data to Identify and Track Recreational Fishing in the Gulf of Mexico

  SSRN Electronic Journal · 2025-01-01 · 1 citations

  articleOpen accessSenior author
  PublisherDOI

Frequent coauthors

• Susana Ferreira

  University of Georgia

  11 shared

• Craig E. Landry

  University of Georgia

  6 shared

• Adam Hyde

  University of Illinois Urbana-Champaign

  4 shared

• Michael DeWitt

  3 shared

• Gregory Colson

  2 shared

• Jacqueline Kessler

  University of Georgia

  2 shared

• Christine Bliss

  Quincy University

  1 shared

• Cristine L.S. Morgan

  1 shared

Education

• Ph.D., Agricultural and Applied Economics

  University of Georgia

  2018

Awards & honors

• Tyrus R. Timm Honor Registry