With many college students already graduating and many more to follow in the coming weeks, I decided to do my part and help them in their post graduation process.
After graduating university, one of the hardest decisions I had to make was deciding where to relocate to. For each city I looked into, I had to consider a ton of variables such as job opportunities, cost of living, entertainment prospects, and the age demographics.
Ultimately, a very stressful process culminated in me choosing to begin my career in Philadelphia. For my first few years as a postgraduate, I became comfortable in Philly, met a ton of new friends, and learned to love the City of Brotherly Love.
I want newly minted alumni and more specifically, millennials, to have the same experience I had when they begin their new journey after college.
In honor of Philadelphia providing some of the best years of my life, I have put together a list of the best 250 places to live in Pennsylvania for millennials.
Pennsylvania is anchored by two major cities, Pittsburgh and Philadelphia, that are able to provide thousands of jobs to millennials fresh out of college. Additionally, Pennsylvania is home to more than 150 colleges and universities.
Put those two facts together and you have a state that is loaded with postgraduate job opportunities and enough ambitious millennials to fill those positions.
After looking at nearly 1,000 Pennsylvania towns and cities, I narrowed my list down to the best 250 places for millennials by evaluating the following parameters:
- Cost of Living Score (30%, listed in table as COLS)
- Crime Score (10%, listed in table as CS)
- Transportation Score (15%, listed in table as TS)
- Income Score (10%, listed in table as IS)
- Age Score (20%, listed in table as AS)
- Unemployment Score (15%, listed in table as US)
The 2 Pennsylvania towns and cities featured below are the best places in the Keystone State for any millennial looking to find their own place.
Harrisburg and Pittsburgh.
All data used in this study was pulled from various datasets I licensed personally. I needed to collect data on a number of statistics including the most recent population figures, age demographics, unemployment numbers, income statistics, transportation data, crime statistics, and cost of living statistics. My original spreadsheet had nearly 1,000 Pennsylvania towns and cities. I was able to narrow that list down considerably when I implemented a population cutoff of 5,000. Any towns or cities with a population below 5,000 were immediately eliminated from further analysis.
The dataset I had access to listed the general cost of living statistics for every place in Pennsylvania. This statistic was stand alone and manipulation was not necessary. The respective cost of living statistics for every city were ranked against each other on a percent scale from 0 to 100. Each individual percent rank was multiplied by its weight of 30% to produce the value score. The maximum possible value score was thirty points.
In regards to each Pennsylvania town’s crime statistics, I was able to gather the crime index for every city as a stand alone statistic. This score accounted for the number of murders, rapes, burglaries, vehicle thefts, assaults, etc., in a given town. The resulting Crime Scores for each town were ranked against each other on a percent scale from 0 to 100. Each individual percent rank was multiplied by its weight of 10% to produce the value score. The maximum possible value score was ten points. Each town and city was also given a Transportation Score according to how many commuting options they presented residents and how accessible the city was for commuters. The resulting Transportation Scores were ranked against each other on a percent scale from 0 to 100. Each percent rank was then multiplied by its weight of 15% to produce the value score which had a maximum of 15 points. The Unemployment Score was tabulated by simply finding the unemployment rate in each town and city in Pennsylvania. The unemployment rates for each town were ranked against each other on a percent scale from 0 to 100, and the percent ranks were then multiplied by its weight of 15% to produce the value score, which had a maximum value of 15 points.
The final two parameters were the Income Score and the Age Score. For the Income Score, I was able to find the projected median incomes in five years for every single town and city in Pennsylvania. The projected five year incomes were weighed against each other on a percent scale from 0 to 100. Each individual percent rank was then multiplied by its weight of 10% to produce the value score, which had a maximum value of 10 points. The final parameter, Age Score, was found by taking the amount of a city’s residents between the ages of 25 and 34 and dividing that number by the city’s total population. Those numbers for each city were ranked against each other on a 0 to 100 percent scale, and that resulting number was multiplied by its weight of 20% to get the value score. The Age Score had a maximum value of 20 points.
Once each town and city in Pennsylvania had a weighted score for each of the parameters, we were able to move forward and discover the final rankings. Each city’s weighted parameter scores were summed together and the resulting sum was the Final Score. The greater the Final Score for a city the better ranking they were given and vice versa.
Project CRediT sources data from Wealthy Genius including net worth, earnings, and various wealth statistics.