Josh T. Smith

Building a Quality of Life Index

This chapter outlines how an index measuring quality of life should be developed and then applies that work at the county level in the United States. The index we create is a unique and data‐driven approach to calculating quality of life. In the chapter, we explain the process that leads us to selecting our five indicators: public safety, health, economic development, infrastructure, and education. Each indicator breaks apart into subindicators. This chapter theoretically and statistically verifies our chosen indica‐ tors. First, we develop theoretical arguments explaining the connections between qual‐ ity of life and our indicators. Then, we perform confirmatory factor analyses on our index to empirically verify our theoretical arguments for why each component should be included in the index. Further, we finally verify our theory and index using survey results. We use only publicly available data to facilitate replication by others. The results of our confirmatory factor analysis provide statistical evidence for our choice of indica‐ tors in measuring quality of life. Our findings indicate that those measuring quality of life must account for the roles of: public safety, health, economic development, infra‐ structure, and education. Most importantly, our results indicate that our index is a valid measure of quality of life.

Quality of Life in Theory and Practice

Voters approached the polls on November 5, 2016, with the hopes of improving their quality of life just as they had done every election prior. The common election question, “Are you better off than you were four years ago?” explicitly primes voters with just this thinking as well. It is clear that many voters think and view voting as a potential avenue to improve their lives. We, however, think the underlying logic they are applying to the question of who they vote for is likely much more complicated than a simple calculation of costs and benefits. In the course of this book we cover several empirical examples that demonstrate distinct modes of thought about how quality of life interacts with an individual’s decision-making.

Local Tax Ballot Measures and Quality of Life

The previous chapter empirically showed how ballot measures are both less likely to garner support and to pass in areas with high life quality and was focused on state level ballot measures across a variety of subjects. This finding looked at all ballot measures regardless of content or subject. We treated ballot measures about legalizing marijuana as if they were the same as ballot measures on any other subject. In this chapter, we refine that and concentrate on only local ballot measures involving a tax increase. Our interest in this narrower set of ballot measures is twofold. First, we are interested in ballot measures where the quality of life is more homogeneous to better test the effect, and second we are interest in better understanding the impact of quality of life on decisions that have a direct and more immediate effect on the voter.

Introduction: Quality of Life Studies; Our Dulling and Rusting Tools

The notion of what it means to have a high quality of life, to lead the good life, or simply to be happy has become increasingly the focus of social scientists. Its roots, however, extend much farther, at least to the foundations of the western world in philosophical treatises, the platonic dialogues, and perhaps most significantly in the Aristotelian conception of eudaimonia and questions of the proper social and political order (Russel, 2014). These philosophical foundations are all rooted in the commonality of what seems to be a near universal longing for a life well lived, and as a corollary a society organized in such a way as to achieve that life.

Federal Spending and Quality of Life

The 2016 presidential election’s campaign and result are interesting in part because of the societal cleavages they revealed. In particular, the differences it revealed in conceptions of how liberal democracies ought to function. Although all elections do this to some extent, Senator Sanders’s campaign brought the question to the forefront of national dialogue. His thoughts about government’s role in healthcare and breaking up economic power centralized in large banks while advocating for limiting the power of corporations rallied many to his camp, especially young voters. Sanders’s position reveals a clear picture of government as a power for good. While his stance as a Democratic Socialist likely places him on the outskirts of this view, the heart of his position is not far from the main thrust of government’s role. Social contract theorist Thomas Hobbes believed that without government life would be little but a short and nasty affair. That government is needed to bring out the saint and tame the brute and care for those in need is a common view (Finer, 1997). This theory of government is intertwined with the well-being of individuals. Government is, along with other important factors like consent, justified because it makes people better off.

Quality of Life and Trust

Skepticism and outright distrust of government have become the watchword of the political process in recent decades (Newton & Norris, 1999; Twenge et al., 2014). Though still too early to know the full effect, the 2016 election appears to have done little to alleviate that skepticism and likely did much to increase citizen concern over whether political institutions can be trusted. Indeed, it is possible that no single concept has launched more political campaigns than the vanguard call that we must not trust government. Political rhetoric of this sort has been of particular interest whenever a political party of minority status and the perennial repetition of the American electoral system have created an environment where trust in government is viewed as the purview of the naive and ignorant.

Using Quality of Life in Public Policy

Every discussion of public policy could begin with a story, more illustrative than concrete, of a town plagued by rats. The rats, which had not been a problem at first, slowly evolved from nuisance to full vexation. The problem grew worse and worse as the rats broke into food stores and brought disease into the town. In an attempt to solve the problem, the city government offered a bounty for each rat tail brought to city hall. Soon people began bringing rat tails and walking out with their bounty. As the tails piled up, it seemed hard to doubt the program would soon solve the rat problem, but months went by with little improvement. The city’s council met again to consider additional solutions and to consider the flaws in their previous plan. At their meeting one member brought out a cage of rats, one mother and several younger specimens. The reason for the bounty’s failure, she explained, was simple. The reward had not prompted people to hunt rats, but to breed them instead.

Understanding Quality of Life

Despite the clear importance of life quality to both individuals and public policy, defining and measuring quality of life is a difficult affair. The general concept includes much that is clear and easily measured, such as income or education level, but it’s also clear that there are other factors that are more ethereal and therefore difficult to capture. We believe the index we develop captures both those easily measurable factors and many of those that are more difficult to account for.

Exploring the Components of Our Quality of Life Index

As we explored the components of each indicator that would eventually be included in our index, we bore in mind our central purpose of investigating the political implications of quality of life as well as the theory behind our work. There are also, of course, statistical justifications, checks, and validations we discussed while developing the index, but the theory drove and guided our inclusions and brought us to the relevant statistical tests. Mathematical work without a guiding theory adds little of value to policy issues. This chapter builds on our previous work with a wider and better streamlined dataset, greater depth on each indicator we discuss, as well as more forms of validation. It is largely an extension of previous work where we provided fewer details and justified an earlier version of our index using fewer statistical methods (Yonk, Smith, & Wardle, 2017).

Constructing a Measure of Well-Being

Any index’s quality is based on its contents. A good index is based on what matters, clearly delineates what the data sources are, and the methods used in creating the index. The saying, “garbage in, garbage out, is common among social scientists who either work with or critique indexes. Because we define quality of life as, “The measured fulfillment of human wants and needs,” determining how and what to include is of particular importance. Including ideas that are incorrect, garbage, in our index will produce only one thing, more garbage. It is easy to make an index, but it is tremendously difficult to build a valid one. In fact, it is likely impossible to have a perfect index, which is part of the reason we include only data that is widely and freely available because we think any other index based on private data is too much of a black box to rely on in policymaking or scholarly analysis. Our index, like any other, is certainly imperfect. We console ourselves with a firm belief that scientific progress is largely found in marginal improvements to existing models and methods.