Can You Afford to Work? Transport and Accessibility Poverty in Tuscany

A new study, presented at the SIS (Italian Statistical Society) 2025 conference in Genoa in collaboration with Luca Secondi, uses data from Google Maps and other sources to create an innovative index that measures "transport poverty" in Tuscany, identifying the areas where accessing work is most difficult and expensive

The Problem: When Commuting Becomes a Barrier

Access to an efficient and affordable transport system is a fundamental right. It directly impacts our ability to find a job, get an education, and access healthcare. When costs are too high, travel times are excessively long, or alternatives to a private car are inefficient, individuals can fall into a condition known as transport poverty.

This phenomenon not only limits individual opportunities but also exacerbates social and territorial inequalities. Our study aimed to measure this disadvantage scientifically, focusing on the Local Labour Systems (LLS) of Tuscany—the geographical areas where the majority of daily home-to-work commutes occur.

Data & Methodology: Weaving Together Maps, Income, and Commuter Flows

To build our analysis, we integrated a mosaic of diverse datasets:

• Commuter Flows: We used ISTAT 2011 census data to understand how many people travel between different municipalities in Tuscany for work.

• Income Data: Figures from the Ministry of Economy and Finance provided us with the average income per municipality, allowing us to assess the burden of transport costs on workers' budgets.

• Travel Times and Costs: Using the Google Maps and Michelin APIs, we calculated travel times and costs (fuel, tolls) for journeys by both private car and public transport (train, bus), simulating morning and evening peak hours.

• Public Transport Fares: We collected the official fare structures from Trenitalia and regional bus services to precisely calculate the cost of a journey on public transit.

By combining this information, we developed a composite index: the Daily Transport Poverty Index (DTPI). This index doesn't just measure monetary cost; it also integrates the time cost of travel, relating both to the average worker's income. In short, the DTPI tells us how "heavy" the daily commute is in terms of both financial and time resources.

Results: A Divided Tuscany

Applying the DTPI revealed a map of Tuscany that is sharply divided, with significant territorial inequalities.

The map below shows the DTPI: darker colors indicate greater disadvantage, where public transport fails to provide a viable alternative to the private car. It's clear that central areas around Florence, Prato, and Pisa benefit from a relatively efficient public transport system. In contrast, peripheral Local Labour Systems, especially in the southern part of the region, show high levels of critical disadvantage.

To delve deeper into this dynamic, we analyzed the direct comparison between cars and public transport. The following chart plots the difference in cost (Y-axis) against the difference in time (X-axis) between the two modes.

• The top-right quadrant is the "transport paradox zone": here, public transport is not only slower but also more expensive than driving.

• The ideal quadrant (bottom-left), where public transport is both faster and cheaper, is unfortunately sparsely populated.

Many routes, especially those connecting peripheral areas like Montepulciano and Cortona, fall squarely into the paradox zone. For workers in these areas who do not own a car, this translates into a double penalty: they spend more time and more money to get to work. 🚌 vs 🚗

4. Conclusion and Future Implications

Our study demonstrates that transport poverty is a structural barrier to accessing the labor market, particularly for low-income workers in internal and peripheral areas.

The DTPI is not just an academic exercise but a concrete tool for policymakers. It allows them to:

1. Identify critical routes where targeted investments in public transport (more frequent services, subsidized fares, better integration between modes) could yield the greatest social benefits.

2. Evaluate mobility policies not only in terms of efficiency but also of equity.

3. Prevent the depopulation of inland areas by ensuring they remain connected and accessible.

The methodology is scalable and could be extended to analyze all of Italy, providing a comprehensive map of accessibility poverty and guiding national strategies for a fairer and more sustainable transport system.