Across America, quality of life varies from city to city. This quality can be quantified using a series of nine indexes such as the pollution index and the safety index. In this project I decided to redefine and recalculate the Quality of Life index based on my own values. I first became interested in looking at this index when I read an article on poverty and the ways in which poverty distribution further affects one’s access to other important resources. I decided to look further into the quality of life in American cities, finding this article that calculates Quality of Life in a similar manner to Numbeo (where I collected my data). Dissatisfied with the weighting of each factor considered within the overarching index, I decided to come up with a new equation to calculate the Quality of Life Index.
index = 100 + purchasingPowerInclRentIndex / 2 – (housePriceToIncomeRatio * 2.0) – cpiIndex / 5 + safetyIndex / 2.0 + climateIndex / 2.0 + healthIndex / 1.5 – pollutionIndex * 1.5 – trafficTimeIndex / 2.0 – trafficInefficiencyIndex/ 4.0 + affordabilityIndex * 5
I based the above equation on the equations listed on the Numbeo website. I decided to divide the Purchasing Power with Rent Included Index by 2 rather than 2.5 because I consider someone’s ability to buy goods from place to place to be very important, yet I also recognize that if the index was not scaled down it would have a disproportionately significant weight. I also increased the weighting of House Price to income Ratio because this index indicates if the houses are affordable based on the jobs available/ held in the area. I also increased the weight of the climate index and pollution index. I consider environmental health to be a valuable aspect of a cities overall appeal and general condition. Finally, increased the weighting of the health index for the ability to access quality healthcare has a direct relation to one’s quality of life. I balanced this scaling by including two factors the normal index goes not consider: the Traffic Inefficiency Index and the Affordability Index. Traffic inefficiency plays a large role in an individual’s living experience just like ones ability to afford housing in the area based on available loans and other factors. I used this code to calculate the new index values and produce the bar graph below, which indicates Raleigh, NC the best city in which to live out of the 45 options according to my standards and to Newsweek. Columbus, Ohio was ranked 3rd by Newsweek and 2nd by this new standard, whereas news week ranked Madison, Wisconsin 2nd and my program ranked it 3rd. From there, the rankings have fewer similarities. This variation is due both to the limited set of cities in the model and my changes to the weighting of and number of factors.