The veterinary profession supports animal health and agricultural production as well as local economies. Beyond providing clinical services in communities, veterinary practices generate employment opportunities, labor income, tax revenues, and downstream spending in regional supply chains and households (1, 2). Through purchases of pharmaceutical, diagnostics, medical equipment, and other local goods, veterinary practices generate upstream demand and induce household spending, creating multiplier effects that amplify regional impact (3, 4). The magnitude and structure of these effects likely vary across space. Rural veterinary practices operate in thinner labor markets characterized by lower veterinarian density (5) and documented recruitment and retention challenges (6), while urban practices exhibit higher service density and more specialization (7). Taken together, these contrasts motivate testing whether veterinary practices generate different levels of economic intensity across rural and urban counties.

Veterinary practice performance is influenced by broad macroeconomic conditions, including household income and inflationary pressures that affect willingness to pay for care (8). Yet most existing evidence is aggregated, and we have limited understanding of how veterinary economic activity—and the spillovers it generates—varies across rural and urban communities. Recent peer-reviewed work reinforces that contemporary access constraints in veterinary services are fundamentally place-based, operating through both workforce dynamics and spatial barriers. A large cross-sectional survey of U.S. veterinarians found that intent to stay/leave practice was broadly similar across rural and nonrural settings, but rural veterinarians reported longer work weeks, more on-call time, and different community-amenity tradeoffs—factors that can affect effective local service capacity even without differential “exit” rates (9). County-level mapping studies further document systematic geographic disparities in access to veterinary care, offering empirical evidence that travel time, provider distribution, and local socioeconomic conditions jointly shape the likelihood of receiving care (10). In parallel, recent syntheses on veterinarian burnout emphasize that reduced professional effort and workforce strain can translate demand pressure into capacity constraints, reinforcing the importance of measuring how local veterinary capacity links to broader community outcomes (11). Together, this emerging literature strengthens the case for county-level, rural–urban evidence that goes beyond headcounts to quantify the broader local economic stakes of veterinary service availability.

This literature gap matters because economic analyses of veterinarian location, spatial density, and shortage designations consistently point to geographic maldistribution (12), such that veterinarians cluster in larger markets, while rural coverage depends on local demand conditions, amenities, and policy incentives. This pattern creates comparative shortages that can constrain service capacity in rural communities (13, 14).

These frictions are often most acute in rural areas, where veterinarian density is lower and recruitment and retention challenges persist (5, 6). As a result, some rural communities have experienced contraction in local veterinary capacity. Policy initiatives such as the Veterinary Medical Loan Repayment Program (VMLRP) have sought to address shortages in rural and food animal medicine for more than a decade (15). However, stronger, place-based evidence on what a rural veterinary practice contributes to its county economy—relative to an urban or suburban practice—can inform the design and justification of federal, state, and local efforts to support rural veterinary services.

Conceptually, rural–urban differences in economic contribution can arise through several mechanisms. Rural practices often serve larger geographic catchments with higher travel and transaction costs, and they may act as essential service anchors in thinner markets where alternative providers and suppliers are limited. This can change both the scale of activity captured locally and the structure of spillovers: spending that is retained within the county may generate larger indirect and induced effects, while leakage to outside suppliers can dampen multipliers. At the same time, urban practices operate in denser markets with greater specialization and supplier networks, which may raise total scale but not necessarily standardized intensity.

To address these issues, this study analyzes rural–urban differences in the scale, structure, and intensity of veterinary economic activity in the United States. Regional input–output (I–O) models such as IMPLAN provide a systematic framework for estimating direct, indirect, and induced economic effects of veterinary services (2, 3). I–O methods have been used to assess service-sector contributions and regional spillovers in the economic literature (4, 16). Building on this literature, we use county-level data to estimate the economic contribution of veterinary practices in terms of employment and total economic output and then quantify rural–urban differences through standardized intensity measures and econometric comparisons.

Accordingly, we address two research questions:

(RQ1) How do the direct and total (direct + indirect + induced) economic contributions of veterinary services differ between rural and urban counties in the study states?

(RQ2) Is rural status associated with higher veterinary economic intensity (measured as employment and output per veterinary establishment per 1,000 residents) after controlling for county socioeconomic conditions and state effects?

To quantify the economic contributions of veterinary services at the county level, we employ a regional input–output (I–O) modeling framework using IMPLAN 2023 data. I–O models trace the flow of goods and services among industries, households, and institutions, providing a systematic accounting of how expenditures in one sector propagate through the broader regional economy (1). The IMPLAN system operationalizes Leontief-style I–O analysis and is grounded in Bureau of Economic Analysis benchmark tables, regional purchase coefficients, and trade-flow adjustments (2).

We implement an economic contribution analysis, rather than an economic impact analysis, because the veterinary sector is an existing and geographically distributed industry embedded within all U.S. counties. Contribution analysis does not answer the counterfactual question of what economic activity would occur in the absence of veterinary practices. Instead, it measures the extent to which the industry currently contributes to the size and structure of local economies. This is consistent with practices to analyze mature, existing sectors with broad geographic dispersion in regional economics (16).

Following Miller et al. (1), who analyze Michigan's beer value chain using IMPLAN to estimate direct, indirect, and induced economic contributions, the total economic contributions of the veterinary sector are expressed as the sum of:

Total Effect=Direct Effect+Indirect Effect+Induced Effect Direct effects represent the economic activity directly attributable to the veterinary sector itself. Indirect effects capture inter-industry transactions that arise from veterinary practices' demand for inputs such as pharmaceuticals, laboratory diagnostics, equipment, and business services. Induced effects arise from additional economic activity generated through household spending of labor income earned in both the direct and indirect channels (e.g. groceries, rent, childcare, restaurants, healthcare, and transportation). Because these interdependencies are linear, the total effect can be expressed as a multiplier applied to the direct effect: Total Effect = k × Direct Effect where k ≥ 1 measures the scale of indirect and induced effects. Industries with deeper local supply chains exhibit larger multipliers, while industries that rely more heavily on imports exhibit lower multipliers.

The veterinary services sector is defined using IMPLAN Industry 54194. For each county, IMPLAN provides estimates of employment (full- and part-time jobs) and output (gross receipts or sales). These direct effects represent the economic activity of veterinary practices, including general practice, specialty/emergency care, mobile services, and mixed-animal operations. IMPLAN then applies industry-specific production functions to estimate indirect effects and induced effects. Indirect effects are expenditures on upstream inputs (e.g., wholesale drugs, diagnostic labs, software, professional services, utilities) and reflect the structure of the veterinary supply chain in each county. Induced effects reflect household spending by veterinary employees and workers in upstream industries, generating activity in retail, services, housing, and other sectors. To inform the IMPLAN estimation, starting values on veterinary business counts and baseline industry activity were extracted from DataAxle (17). DataAxle provides establishment-level business listings; we used full-year 2023 records (received in 2025), filtered to NAICS 541940, and aggregated to the county level to construct county establishment counts used in the intensity denominators and to support IMPLAN's initial county-level calibration.

As with all I–O models, the IMPLAN framework relies on several standard assumptions: constant returns to scale, fixed production technology, perfectly elastic supply and fixed price for the year, and linear inter-industry relationships (3). Constant returns to scale implies a doubling of veterinary output requires a proportional doubling of all inputs. Fixed production technology denotes no substitution among inputs, and increases in demand require proportional increases in each specific input. Perfectly elastic supply and fixed prices means industries expand output without supply constraints or price changes. Linear inter-industry relationships assumes that indirect and induced effects are proportional to direct effects. These assumptions are well documented in the I–O literature and should be considered when interpreting results (3).

This study provides new evidence on how veterinary practices contribute to local economies across rural and urban counties, using a consistent county-level input–output framework applied across 331 counties in 10 states. The results confirm that veterinary services generate substantial economic activity beyond the practice, with indirect and induced spillovers that meaningfully expand employment and output relative to direct effects (21). At the same time, the rural–urban distribution of that activity differs sharply across states. The intensity of veterinary economic activity, once standardized for population and business counts, appears systematically higher in rural counties after accounting for state context and local economic conditions.

A central finding is the large aggregate scale of the sector in the sampled states: 75,438 direct jobs and 97,912 total jobs, alongside $7.20B in direct output and $11.94B in total output. These totals reinforce that veterinary services are not only a healthcare-related industry but also a meaningful contributor to regional labor markets and commercial activity (22). State-level patterns are consistent with expected population and market size effects: New York, North Carolina, and New Jersey account for the largest totals, while smaller states exhibit smaller totals but still substantial total effects relative to direct effects. This aligns with the conceptual basis of contribution analysis: mature industries embedded across regions can generate large aggregate contributions, even when the counterfactual “absence of the industry” is not the question of interest.

The rural–urban decomposition highlights that rural counties account for a smaller share of total sector activity in the multi-state sample, but with pronounced heterogeneity by state. Some states (e.g., Massachusetts) have relatively little rural activity in this dataset, whereas others (e.g., Vermont, Maine, and New Hampshire) show a much larger rural share. Importantly, New Jersey and Rhode Island have no counties classified as rural under the RUCC-based definition used here, emphasizing that rurality is a classification outcome and does not map uniformly across states. These patterns suggest that state-wide discussions of veterinary workforce needs and economic importance can mask where the sector is actually concentrated—often in specific rural counties rather than evenly across the state (5). From a policy standpoint, this reinforces the value of place-based strategies (23): where rural counties account for a large share of veterinary employment and output, local economic exposure to workforce shortages is likely more pronounced.

The multiplier results further contextualize veterinary practices as locally embedded economic contributors. Employment multipliers between 1.25 and 1.38 and output multipliers between 1.57 and 1.70 indicate meaningful supply-chain and household-spending spillovers (21, 24). In practical terms, a direct veterinary job supports an additional 0.25–0.38 jobs elsewhere in the state economy, and each dollar of direct output supports roughly $0.57–$0.70 in additional output through indirect and induced channels. While multipliers are sometimes treated as fixed “sector characteristics,” the observed variation across states is consistent with differences in supply-chain depth, the extent of local purchasing vs. imports (leakage), and regional industrial composition (3). These results support the broader argument motivating rural workforce programs: when a community loses veterinary capacity may not just impact clinical services but also interconnected economic activity that supports other local industries.

Regression results indicate differences in standardized veterinary economic contribution intensity measures between rural and urban counties after controlling for county poverty, unemployment, and state fixed effects. This finding suggests that, conditional on observed covariates, rural veterinary practices may play a disproportionately large role in local economic structure relative to county population. One plausible interpretation is that rural markets may have fewer veterinary providers and thinner service networks, so each practice represents a larger share of local service capacity (5). Another is that, at the practice level, rural practices may operate as broader “generalist” providers, offering a wider range of services with a larger catchment area, concentrating economic activity within fewer establishments. The negative association between unemployment and output intensity is consistent with macroeconomic constraints on household spending and local demand for discretionary or elective veterinary care, which may dampen output per business in weaker labor markets (25). Together, the results point to a distinction that is often lost in public discussion: urban counties account for the majority of veterinary activity in terms of size/scale. However, rural counties can rely more heavily on veterinary practices in terms of intensity on a per-business, per-resident basis. This difference supports the case for targeted rural workforce investments as these efforts should see a higher return per dollar spent.

These findings have direct implications for programs intended to address rural veterinary shortages, such as loan repayment initiatives and other retention incentives (15). If rural counties have higher standardized economic intensity, then the marginal economic consequences of reduced veterinary capacity may be larger than implied by number of veterinarians/businesses alone. Economic development stakeholders (county governments, regional planning bodies, and chambers of commerce) may therefore view veterinary workforce policy not only as an animal-health issue but as part of a broader rural economic resilience agenda (26). More generally, results support the case for integrating veterinary services into regional development planning, particularly in states where rural counties account for a large share of veterinary activity.

Several limitations should be considered when interpreting these results. First, the IMPLAN framework is an accounting-based input–output model that relies on standard assumptions (fixed technical coefficients, constant returns, no price adjustments, and linear inter-industry relationships). These assumptions are well suited for contribution accounting but limit inference about how relationships might change under supply constraints, price changes, or behavioral substitution. Second, multipliers and indirect/induced effects are model-based estimates derived from IMPLAN's regionalization procedures (e.g., RPCs and trade-flow adjustments) and therefore inherit uncertainty and potential measurement error that are not always reflected in conventional statistical tests. Third, the analysis covers 10 states rather than the full U.S., so external validity will depend on how representative these states are of broader rural–urban structures and veterinary market conditions. Fourth, the rural–urban classification uses RUCC codes, which are widely used but necessarily coarse and may mask important within-county variation (e.g., non-rural, non-metro counties) and cross-state differences in how “urban” counties function economically. Finally, while the regressions adjust for poverty and unemployment and include state fixed effects, the specification may still omit relevant confounders, and the results should be interpreted as associations rather than causal effects of rural status.

In addition, these estimates should be read as strong evidence for the study states rather than a claim that the same magnitudes hold nationally. The broader takeaway is the framework and the direction of the rural–urban contrast: when veterinary services are locally embedded, the contribution (and the economic exposure to workforce shortfalls) can be meaningfully different across places. Extending the analysis to additional regions is the next step for testing how general the pattern is.

The results indicate that veterinary services generate substantial direct and spillover economic activity across states, with meaningful multipliers in employment and output. Urban counties account for most activity in absolute terms, but rural counties appear more economically reliant on veterinary practices on a standardized basis after controlling for local economic conditions and state context. These findings strengthen the evidence base for rural veterinary workforce initiatives by linking workforce capacity to broader local economic contributions and resilience.

Future work can extend this contribution framework in several ways. Expanding to a nationally comprehensive dataset would allow stronger generalization and enable regional heterogeneity analyses (e.g., Appalachia, New England, Upper Midwest). Incorporating measures of clinic structure and service mix—particularly food animal vs. companion animal orientation—could help explain why rural intensity differs and how workforce shortages translate into economic vulnerability. Finally, linking IO-based contribution estimates with practice-level operational data (e.g., staffing, revenues, appointment volumes) could bridge the gap between macroeconomic contribution metrics and the micro-level constraints faced by rural practices, improving the design and targeting of workforce and economic development interventions.