A new home for Santa Claus?

After the many years of commuting on Christmas Eve, jolly old St. Nicholas is reconsidering his home at the North Pole. Given his job description, extreme isolation has lost its appeal. In true Christmas spirit, the University of Toronto's Martin Prosperity Insititute is offering Santa a top 10 list of places that would best suit him and his needs.

U of T researchers looked at five variables important to his lifestyle: (1) the number of cookie factories per capita; (2) the number of milk producers per capita; (3) the number of doll, toy and game manufacturing establishments per capita; (4) the number of postal service workers/couriers per capita (to receive and reply to wish lists); and (5) department stores per capita.

Hard work creates quite an appetite, and common knowledge supposes that Santa’s snack of choice is cookies. We looked at the number of cookie (and cracker) manufacturing establishments per 100,000 people in an area. Terre Haute, IN was a landslide winner in this respect, with 2.4 per 100,000 people. Next on the list were Fond du Lac, WI (2), Lewiston, ID (1.7) and Guelph, ON (1.6). There were over 200 metropolitan areas with no cookie manufacturing establishments at all. If Santa were looking at the sheer number of cookie manufacturers, he should consider the New York area with 40 in total.

To wash down all of those cookies, Santa is going to need some milk. Researchers next looked next at the number of milk manufacturing establishments per 100,000 people. Saskatoon, SK is the leader in this category with 6.1 milk establishments per 100,000 people and 14 establishments in total. Up there with Saskatoon was Regina, SK with 4.7 per 100,000, St. Catharines/Niagara, ON with 2.9 and Abbotsford, BC with 2.6. Once again, there are some metro areas for Santa to avoid in terms of milk production as more than 150 of them have no reported milk manufacturers, including Charlotte, NC and San Jose, CA. In contrast, Toronto, ON has the most milk manufacturers with 25, followed by Vancouver, BC (19), Edmonton, AB (19) and Los Angeles, CA (17).

With the move also comes the need for a new toy factory and with 3.5 factories per 100,000 people, no other metro area beats Peterborough, ON. Victoria, BC sits in second place with 3.1 toy manufacturing establishments per 100,000 people. Next in the top 5 are Saint John, NB, Corvallis, OR and Ithaca, NY. In terms of the overall number of toy manufacturing establishments in the area, Toronto again ranks first with 77 toy manufacturers. Montreal, QC is next with 60, followed by Los Angeles with 54 and New York with 47.

While checking his list to see who has been naughty and who has been nice, Santa also needs a reliable postal/courier service to receive and reply to children’s wish lists. The metro area with the most postal service workers/couriers per 100,000 is Des Moines, IA with 495. The area with the second most postal workers is the Greater Sudbury area in Ontario with 460.4 per 100,000 followed by Trenton, NJ with 434.3, Saint John, NB with 430.2 and Lynchburg, VA with 424.7.

Large metros such as New York and Los Angeles had the most postal service workers/couriers in terms of overall number of personnel, but they had lower numbers per capita due to their large populations. Interestingly, despite a declining population, Detroit, MI had more overall postal workers/couriers than the larger areas of Houston, TX and Atlanta, GA. The metro with the least amount of postal service workers/couriers per 100,000 people was Farmington, NM with only 49. The next three lowest were Hanford, CA; Prescott, AZ; and Fairbanks, AK.

Department stores are a crucial meeting place to see children before Christmas. Therefore, it was important to examine the number of department stores per capita in a given area so that Santa could maximize his appearances. Children of Elmira, NY have the greatest chance of sitting on Santa’s knee, with an abundant 9.1 department stores per 100,000 people — the highest number relative to the population. The top 5 also includes Lima, OH with 8.6 per 100,000 people, Missoula, MT with 8.5, Lewiston, ID with 8.4 and Sandusky, OH with 7.8.

Of course, if Santa were looking for the area with the highest total number of department stores he could visit the fashion and shopping capitals of New York, Chicago and Los Angeles. In terms of congestion though, the largest cities tend to have a low number of department stores per 100,000 people, which could lead to crowding. There are a number of cities with a low number of department stores that Santa might want to steer clear of, especially Hinesville, GA, which has no reported department stores in the area at all.

By combining the five variables to give each area an overall score, U of T researchers were able to create a top 10 list of ideal places for Santa to live. According to this analysis, Guelph, ON is the best suited destination for Santa. Overall, Guelph is a metro which offers Santa a good balance of the elements that define his lifestyle. Guelph received the highest overall score, largely thanks to its high number of cookie manufacturing establishments per 100,000 people, coupled with a good postal and courier service.

Williamsport, PA came in second with only a slightly lower overall score than Guelph. Like Guelph, Williamsport received balanced scores in all 5 categories. Williamsport is followed by Sherbrooke, QC; London, ON; St. Johns, NL; Peoria, IL; Hamilton, ON; Winnipeg, MB; Kitchener, ON; and Trois-Rivieres, QC — all great choices for Santa.

Santa might want to avoid Hinesville, GA, with no reported cookie manufacturers, milk manufacturers, toy manufacturers or department stores — an overall score of zero. Pascagoula, MS and Houma, LA also neared the bottom of the list and neither would suit Santa’s unique lifestyle very well.

Don’t worry, Santa won’t consider a move until after he makes his rounds this year. Regardless
of where he chooses, have a safe and happy holiday season and all the best for 2012.

Data Sources:
US Census Bureau, 2008 County Business Patterns
Statistics Canada, 2006 Census of Population
Statistics Canada, 2008 Canadian Business Patterns
US Bureau of Labor Statistics, 2010 Occupational Employment Statistics Survey