Maryann O. Keating, Ph.D., a resident of South Bend and an adjunct scholar of the Indiana Policy Review Foundation, is co-author of “Microeconomics for Public Managers,” Wiley/Blackwell. Her column appears in Indiana newspapers.

Is there a link between good local governance and the self-reported well-being of residents? An article in the summer Indiana Policy Review surveys the research and outlines existing data for 45 cities and towns across Indiana in 2013-2014 to weigh factors associated with self-reported levels of well-being. The goal of the study is to find patterns between Indiana towns to assist officials and the general public in realistically assessing and effectively addressing the needs and preferences of Hoosiers.

John Helliwell, an economist and co-author of the World Happiness Report (WHP) and a Canadian municipality study, justifies the validity and worth of analyzing self- reported measures of well-being. The WHP authors conclude, that although average differences in life satisfaction across communities within the same nation is lower than the differences between countries, there is enough variation between regions to make meaningful comparisons. In the Canadian study, social dimensions dominate geographical differences. The life that matters most to people is personal, reflecting the levels of trust and the quality of social connections in their neighborhood and workplaces.

Is there anything like the Canadian metropolitan study measuring the life satisfaction of Hoosiers? Actually, the Gallup-Healthways Well-Being Index does survey U.S. well-being by state. In 2016, residents of West Virginia, Kentucky, Oklahoma and Indiana reported the lowest levels of well-being. By state, Indiana residents ranked 47th on having a self-reported sense of purpose, 49th in social relationships, 30th in financial security, 38th in community relations and 44th in physical health (www.well-beingindex.com). 

Although several locations in Indiana reflect a high level of well-being, these reports for the state in general are discouraging. Rather than simply ignoring or wasting resources to attain higher rankings in polls, it may be best to focus on in-state variation in quality of life and what this implies for local governance. 

Unlike much research using regression analysis, this study does not pre-select factors deemed significant and, using existing data, implies no causality between town characteristics and well-being. The methodology is based on two analytic algorisms: classification and clustering. The classification algorism identifies characteristics of towns with reported high levels of distress. The clustering algorisms divides Indiana towns into groups that share similar characteristics. 

The towns in Indiana with higher percentages of "People Feeling Badly About Themselves" are associated with higher mean time traveling to work, a lower percentage in service and professional and occupations, poor health and a higher cost of living combined with lower median house values. 

These factors come as no surprise to local officials trying to allocated limited local revenue. However, several towns with similar economic characteristics report higher levels of well-being, stable or increasing populations, and, ironically, more debt per capita and per assessed property values. Governance matters.  
 
Indiana towns differ considerably with respect to economic, health and educational levels. However, these attributes do not always point in the same direction and it would be foolish to identify one type of town as ideal and seek to emulate its attributes. The goal is to move beyond an ideal town, accept the uniqueness of a particular location and pursue what is best in terms of local well-being. 

The clustering algorism identifies Bloomington and West Lafayette as being quite similar, having the lowest per-capita income of any cluster and highest percentage of those with advanced degrees. Obviously, the challenges in providing local government services differ in these towns from those in the Hammond-Gary-East Chicago cluster and those in the Carmel-Fishers-etc. cluster.  

Both the classification and clustering algorithms strongly suggest that Indiana towns differ by occupational sectors. People and firms are attracted to certain towns because of their unique opportunities, over which local government has little control. Although development is easily thwarted by bad policy, those who believe that planers and development agencies are capable of directing local economies are deceived. At most, they can nudge local economies in a specific direction.  Economies consist of people and firms locating and doing their best to maintain and improve their level of well-being. The wealth of any town depends on its residents; how well it functions depends on trust and participation.  

Good democratic governance is not about changing the occupational structure or population of a town in order to improving its rankings or to mimic amenities preferred by affluent communities. It would seem that good democratic governance is about responding to the needs of and providing essential services to residents regardless of present circumstances. The divide between towns reflects past circumstances, but present impoverishment does not guarantee perpetual dysfunction. Towns, like people, experience good and bad times. 

Data, particularly that associated with social connectedness, is needed to fully understand the interplay of factors that determine the inequality of well-being across towns in Indiana. However, classification and clustering assist in identifying challenges facing particular towns.

One result would be to shift the focus away from seeking that which is beyond the realm of local governance towards improving the well-being of current residents. International and cross-metropolitan studies suggest that this is achieved through acceptance of present circumstances and better delivery of basic services.