Study sheds light on what makes a location a good place to live

A study constructed a quality-of-life index for 3,100 U.S. counties in 2019. The researchers determined that high-quality-of-life counties tend to have more people moving in, a higher likelihood of residents staying, shorter commutes, lower homeownership rates, and more entrepreneurs and families. The paper was published in Social Indicators Research.

Traditionally, economic policies have been based on the idea that if jobs are created, people will move to where those jobs are. More recently, however, attention has increasingly shifted toward the opposite possibility—that jobs may follow people who are attracted to places offering a high quality of life. This makes understanding what makes a community desirable increasingly important for both researchers and policymakers.

Quality of life can include many characteristics of a place, from economic opportunities and housing to natural surroundings, cultural amenities, and access to nearby communities. Yet measuring it is surprisingly difficult because people’s subjective assessments do not always correspond to the actual characteristics or livability of the places where they live.

Attempts to combine numerous characteristics into quality-of-life indices face another problem: researchers must decide which characteristics matter and how much weight each should receive. An alternative is to examine people’s actual choices based on the economic concept of “revealed preferences”—the idea that people reveal their underlying preferences and the desirability of a place through their behaviors rather than their stated opinions. Looking at a broader range of behaviors—including staying in a community, commuting, buying homes, starting businesses, and raising families—may therefore provide another window into how people value the places where they live.

With this in mind, study author Yang Cheng and colleagues set out to develop a quality-of-life index for U.S. counties using revealed preferences across three dimensions: moving, staying, and committing. They believed that it is possible to make inferences about the quality of life in a county based on indicators that show how people interact with it.

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These indicators include migration flows (high-quality-of-life places tend to have dynamic populations with both high in-migration and high out-migration, as popular places attract new people but can also price others out), whether residents stay there once they move in (residential retention), commuting out of the county for work (people are less likely to commute outside their county if they live in an area with a high quality of life), homeownership, business formation (high-quality-of-life places tend to attract entrepreneurs), the presence of families with school-age children, and birth rates.

The study authors drew the information they needed from the American Community Survey (an ongoing demographics survey conducted by the U.S. Census Bureau) using 2019 5-year estimates for U.S. counties. They decided to include 3,100 counties across the contiguous U.S. in their analyses. The authors created a statistical model, which they used to build a quality-of-life index and assign an index score to each county. They then proceeded to explore the differences between counties with high and low scores on the index.

Results indicated that high-quality-of-life counties tended to show dynamic migration patterns, strong residential retention (meaning people who moved there tended to stay), shorter commutes, a lower share of homeowners, more entrepreneurs, and more families with children. Of these, the study authors noted that residential retention, homeownership, in-migration, and commuting accounted for 87 percent of the index weight.

On average, urban counties tended to have a higher quality of life, but there were many rural counties with a high quality of life as well. The study authors noted that top-ranked counties tended to share features that explain why people move, stay, and commit there. These included the presence of higher education, critical institutions, dominant industries, a rich natural environment, and other local amenities.

Many of the top-ranking counties were located outside urban centers. They also tended to be characterized by strong civic engagement, often featuring more peaceful protests and higher levels of political contributions from both individuals and organizations. The study authors believe that this indicates active civic participation and proactive local governance that emphasizes transparency and accessibility.

“The Midwest and parts of the Northeast generally have the lowest-ranking counties, along with some areas in the national interior such as North Dakota, South Dakota, Nebraska, and Kansas, as well as historically disadvantaged regions like the Southern Delta and Appalachia. In contrast, the Far West, the Southwest, and the Rocky Mountain region tend to have higher quality-of-life rankings, with mild weather, natural amenities, and proximity to coastal areas being contributing factors,” the study authors added.

The study contributes to the scientific knowledge about factors defining quality of life. However, the study authors note that many counties had a single large institution (e.g., a military base or a university) with a natural inflow and outflow of people. This made it difficult to separate the migration driven by quality-of-life factors from the migration driven by the nature of the institution itself.

Additionally, the study did not measure the well-being or quality of life for different demographic groups within a community. Different groups within a community may experience radically different life qualities depending on their specific conditions.

The paper, “Move, Stay, and Commit: Place-based Quality of Life in the U.S.,” was authored by Yang Cheng, Tessa Conroy, and Steven C. Deller.