San Diego's Downward Trends?

The success stories in San Diego's technology sector seem to cluster around biotech and defense technology. If, like me, you are more interested in the software business, there is less good news. "It's difficult to get ahead financially" is among the top ten complaints from San Diegans. I culled a few stories about life in San Diego, to begin to paint a picture of the situation.

San Diego unemployment edges up

North County Times, CA - Mar 24, 2006. The San Diego job market for January was dragged down by retail and construction, and the discouraged workers who stopped looking for jobs. Article is inconclusive on any long-term implications.

Unisys closes San Diego Operations

Unisys is the latest in a string of technology companies that have either shrunk operations in San Diego or announced plans to do so. Others include Kyocera Wireless, which cut 875 jobs, Newgen Results, which slashed 239 workers and Intel's wireless group, which moved 169 jobs to Portland.UNION-TRIBUNE - October 4, 2005

Tijuana tech firms hire scientific talent at half the salary

Miami Herald, FL - Mar 18, 2006 And guess what? The talent is in the same time zone as many clients, making outsourcing more managable.

San Diego City Government Site Bullish Through 2025

I don't see how anyone could predict a city's job growth rate over 19 years, but that's exactly what the government of San Diego, CA is touting. "Independent studies indicate San Diego is one of the top 10 cities in the country for job growth through 2025, and many of the high-tech jobs are being created by emerging high-tech companies in the region." Emphasis theirs. They do not identify the "independent studies", reveal any data, or disclose methodologies. A link that read "industry clusters" pointed to an article on water supply assurances.

www.SandiegoAtWork.com

This site appears to have a bit more credibility than Sandiego.gov. Their sources are The US Bureau of Labor Statistics and the State of California, Employment Development Dept., Labor Market Information Division. Their projections run through 2008.

Qualcomm Pushes Video on Cell Phones

[date on article is APRIL 3, 2006, impossible since I found it and read it March 25, 2006]

San Diego Bay Area Real Estate Slowdown

WebWire (press release), GA - Mar 18, 2006 San Diego real estate appreciation continues to slow down. ... Another sign of real estate appreciation slowing down is the decrease of population in San Diego. ...

How to detect plastic surgery in San Diegans

By Kate Kowsh, Vyuz.com Makeup sales traditionally rise when the economy is bad. I don't know if plastic surgery increases indicate likewise. There are apparently no shortage of permanently-surprised looking people in San Diego. Same as alien abductees, you look for the scar behind the ear. Chuckle.

TownScores™ Political Spectrum

Do you care about the political leaning of your neighbors? Your city? Your state? Before you relocate, it is worth checking on the voting climate of your prospective new home. Note that these figures come from voter registrant party affiliation, not voting records.

Voter Registration Percentage by Parties

Seattle
Democrat 64.95%	*	Republican 33.69%

Austin
Democrat 56.02%	*	Republican 42.00%

Atlanta
Democrat 59.28%	*	Republican 39.94%

Miami
Democrat 52.89%	*	Republican 46.61%

San Diego
Democrat 46.39%	*	Republican 52.52%

Tucson
Democrat 52.55%	*	Republican 46.56%

As is typical for urban areas, Blue (Democrats) generally rule. The one exception, which I in no way expected, was San Diego. Hold your mouse over the asterisks in yellow, to see the makeup of the independent fringe. No symbolism was intended by that color choice, but it does remind me of the pnemonic used to distinguish deadly coral snakes from harmless milk snakes:

Red touch yellow, kill a fellow
Red touch black, venom lack

Source: U.S. Census Bureau Voting And Registration

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Top stuff: Ken's Meme Deflector: XBlogThis!: An Extended BlogThis! Button

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The Dream of Relocation

Why would I give up a prosperous job position, proximity to my good friends, and a wonderful Craftsman house that is appreciating rapidly as it nears its hundredth birthday?

Sun

Moving to Seattle a dozen years ago was a good decision, but I underestimated my need for sunlight. I did not realize how much the Southern CA sun had to do with my energy and sense of well-being.

Money

There are also the financial costs of staying. Four years ago, I viewed my second house as large for my needs, but a great investment. Having spent the prior five years remodeling my first house, I shopped long and hard to find a house that some else had already fixed. Historical charm, a warm and well-connected neighborhood, and a short commute. It was affordable, given the blessings of steady work, and good pay.

Time

But, it turns out that even a house with recent updates takes a fair amount of work. Three floors and a yard are a lot for a single man with a full-time job. The job competes for time, and you can't throttle it back. You have mortgage payments twice the national average. They become your reason for being. Pressured by expenses, upkeep, and the demands of a career, other dreams go into a permanent holding pattern. Perhaps I would be better off in a two-bedroom townhouse, I thought. New construction, a lawn service, and lower payments sounded tempting. Don't get me wrong — I recognize that most of the world struggles with dire problems. I know that I am fortunate. However, time poverty becomes real, and can hollow out a lifetime. The voluntary simplicity and creative pursuits that I had yearned for were not going to happen in Seattle. When I got the idea to relocate, I first thought of San Francisco. I had visited for Java One last July. I found the temperate city by the bay to be full of beautiful people, and a booming tech sector with venture capital oozing out of every seam. Maybe I would pitch a business idea, and harness some of that capital. Then, after some research I discovered that the townhome in San Francisco would probably have a mortgage just as steep as the Seattle house.

Hope

So much for the complaining! You tuned in to hear the dream. I read Life 2.0 by Rich Karlgaard. His thesis, in a nutshell, is that the sophistication gap between urban and rural American is closing. He documents a trend wherein people with high-powered careers leave the giant metropoles and then live life on a grander scale in smaller cities. Options open up. Maybe one partner in a couple can stay at home. An entrepreneurial venture is much cheaper where salaries and square footage are reasonable.

Business

I also read industry news feeds such as Alarm:clock, and listened to hours of podcasts, particularly from VentureVoice.com. Venture capital was finding its way to small cities, incubators where the burn rates are lower. I found that not only was venture capital heating up, but there was a strong new trend: bootstrapping. Some entrepreneurs, instead of wrestling with VC agendas and exit strategies, were going it alone at very low cost. The successful bootstrapper typically chooses a small city or university town, opens shop in a private home, and uses free open-source technologies to support the product. They experience low turnover, because people are typically rooted in the community, and there are fewer competing employers.

The Dream

After some weeks, this fresh information began to gel into a dream. It goes like this:

1. Sell the Seattle house.
2. Get a job in another city.
3. Buy a smaller, lower maintenance home in a market with a lower median house cost. Pay cash for it.
4. Use the resulting surplus time and income to pursue ambitions besides work and remodeling:
• Write more
• Volunteer more time
• Spend time with family
• Start a business
• Travel
• Earn another degree
• Enjoy hiking, sun, dating

When I consider these possibilities, I feel like I can breathe again. That's why I'm committed, and why I am going on record: I will do this. What is your relocation dream?

TownScores™ Real Costs of Transporation

Let's compare transportation in some U.S. Cities. Statistical data can be dry, so I will add in a wet Seattle commute and stir vigorously.

My Commute home begins near downtown Seattle.

Average Hours Commuted per Year

Seattle 216 hours

Austin 191 hours

Atlanta 243 hours

Miami 259 hours

San Diego 209 hours

Tucson 188 hours

US Average 228 hours

Los Angeles 242 hours

Washington DC 275 hours

New York City 325 hours

San Francisco 242 hours

Dallas 233 hours

I added in a few larger cities, to see whether the commutes were substantially longer.


My windshield wiper slashes left, about to take a slice from the beloved "Canned Ham" building.

Under the I-5 "lid".

Ways People Traveled

Single Occupant Vehicle

Seattle 57%

Austin 74%

Atlanta 64%

Miami 64%

San Diego 73%

Tucson 70%

US Average 71%

Looks like a snap from an alien sighting video or a "dangers of drinking" PSA...

Carpooling

Seattle 11%

Austin 14%

Atlanta 13%

Miami 17%

San Diego 12%

Tucson 16%

US Average 15%

The sign, were you awake enough to see it, reads "Lynnwood 36 minutes, Everett 46 minutes." I guess all the people going there are above average.

Mass Transit, Monorail, Light Rail, Bus, etc.

Seattle 18%

Austin 4%

Atlanta 15%

Miami 11%

San Diego 4%

Tucson 4%

US Average 2%

Nothing like a little motion blur achieved by waving a camera phone about in a moving car. I assure you, it's perfectly safe.

Telecommute or Work from Home

Seattle 5%

Austin 3%

Atlanta 4%

Miami 2%

San Diego 4%

Tucson 3%

US Average 5%

Telecommuters still seem to be among the lucky few. Advantage: catch fewer colds. Downside: no social interaction.


Darkness falls. The Highway lights flicker on, illuminating the rain-slicked pavement of I-5.

Brakelights ablaze just north of downtown Seattle.

Unknown, No Data

Seattle 10%

Austin 5%

Atlanta 5%

Miami 6%

San Diego 6%

Tucson 8%

US Average 7%

Your work-addled brain detects a pattern.


Approaching the University District.

I hope you have enjoyed the ride. We'll have to put the top down next time.

Sources: Bureau of Transportation Statistics' Transportation Statistics Annual Report September 2004 Sperling's Best Places

TownScores™ Cost of Living Comparison

Cost of Living

Figures are shown as a percentage of the National Average.

I was surprised to see that all cost differences in the group were incremental, except housing. Seattle, San Diego, and Miami had housing costs at or near twice the national average.

Overall Cost of Living

Seattle 146%

Austin 91%

Atlanta 96%

Miami 136%

San Diego 157%

Tucson 96%

US Average 100%

Food Costs

Seattle 110%

Austin 87%

Atlanta 99%

Miami 107%

San Diego 114%

Tucson 104%

US Average 100%

Housing Costs

Seattle 221%

Austin 81%

Atlanta 89%

Miami 186%

San Diego 236%

Tucson 84%

US Average 100%

Utility Costs

Seattle 73%

Austin 91%

Atlanta 93%

Miami 105%

San Diego 126%

Tucson 105%

US Average 100%

Health Care Costs

Seattle 127%

Austin 106%

Atlanta 104%

Miami 122%

San Diego 130%

Tucson 110%

US Average 100%

Transportation Costs

Seattle 109%

Austin 95%

Atlanta 104%

Miami 111%

San Diego 113%

Tucson 106%

US Average 100%

Miscellaneous Costs

Seattle 100%

Austin 103%

Atlanta 99%

Miami 105%

San Diego 104%

Tucson 95%

US Average 100%

Sources: ACCRA Cost of Living Index Sperling's Best Places

TownScores™ Housing Comparison

Median Years Since a Home Was Built

Seattle 45.7 years

Austin 21.8 years

Atlanta 36.9 years

Miami 35.8 years

San Diego 27.4 years

Tucson 26.8 years

US Average 27.2 years

Median Home Cost

Seattle $459,800

Austin $167,900

Atlanta $185,100

Miami $387,800

San Diego $491,000

Tucson $175,100

US Average $208,500

Home Appreciation Rate

Seattle 12.15%

Austin 1.96%

Atlanta 4.86%

Miami 21.00%

San Diego 9.00%

Tucson 15.64%

US Average 13.62%

Apartment Rent

Seattle $840

Austin $804

Atlanta $818

Miami $967

San Diego $1,158

Tucson $746

US Average $653

It's stunning to me that Seattle and Austin rents are almost equal, whereas a house in Seattle costs 2.7 times as much! Seems like the sensible thing to do is sell the Seattle house, and buy two houses in Austin — one to occupy, and one to rent out...

Home Ownership vs. Renting

Owners, Seattle 46.97%

Renters, Seattle 49.48%

Owners, Austin 43.75%

Renters, Austin 53.30%

Owners, Atlanta 39.28%

Renters, Atlanta 50.63%

Owners, Miami 31.46%

Renters, Miami 58.59%

Owners, San Diego 46.45%

Renters, San Diego 47.02%

Owners, Tucson 49.96%

Renters, Tucson 43.70%

Owners, US Average 64.07%

Renters, US Average 21.45%

Sources: Factfinder.census.gov - Housing - Financial Charactersitics Sperling's Best Places

The TownScores™ Method

TownScores™ Method

After spending hours pouring over several statistical resources on metropolitan areas, I wanted to make the data more easily scannable. The data were displayed in various tables, maps, graphs and charts. Units were in dollars, percentages, per capita ratios, and some scoring systems. For some scoring systems, a higher number is better, and for others (usually ranks, not scores), lower is better.

In order to digest the plethora of resources, human readers must hold complex rules in their minds, while scanning thousands of data points. The rules might be stated "for air quality scores, higher is better", and "bigger climate scores are better", and "a lower cost of living index is better", etc. IMHO, this slow down the process of comparing different cities.

What I have set out to do with TownScores™ is make a unified scoring system. Because higher scores are always "better", the system is easily scannable. This involves some subjective hand-waving, and a rather naive but pragmatic version of data manipulation. Data expressions are subjective in that they contain assumptions about what is "better". While these assumptions will not hold true for all readers, at least they are revealed explicitly. A reader who disagrees with the assumptions would need to fall back on the old way — that of holding complex rules in memory.

http://www.blogger.com/blog-options-basic.g?blogID=24268505 Settings

The data manipulation involves inverting some data measures, such that higher numbers are "better". For example, a source might give two climate metrics, annual inches of snowfall and annual sunny days:

City Name    Snowfall (in.)    Sunny Days/Year
---------    --------------    ---------------
Seattle      10.4              152
Austin       0.5               228

Were I to graph these numbers, readers would need to look at the bar chart, and remember that "more sunny days are better", and "fewer inches of snow are better". Simple enough, until you combine 7 towns and six metrics, for 54 data points and six rules. The problem quickly becomes unwieldy for the rapid data consumer.

Here's my workaround, applied to our two example metrics. To add these to a data view, I make my assumptions, adjust units if necessary, and then invert data expression while leaving the other alone.

Assumptions

1. Sunny days are better than cloudy days
2. Snow-free weather is better than snowy weather

Clearly, these assumptions are debatable. However, making them allows me to re-scale the data view as follows.

One graph receives the label "Percentage of sunny days." The label on the snowfall graph becomes "Freedom from Snow". The maximum possible "Sunny Day" count is 365. So, Seattle's 152 days, divided by 365, times 100, give us about 42%. Austin gets 62% Sunny Days.

Freedom from Snow requires further manipulation, since it is expressed in inches, of which there could be any number. I set a minimum of zero inces, and a maximum of 109 inches, that experienced by Syracuse, NY.

Percentage((max-actual)/max) or
Percentage((109-10.4)/109)   or
90.4%

Now, I know that "90% Snow-Free" sounds like nonsense. Consider, though, it's value in comparison. Austin is 99.5% snow-free, whereas Syracuse is 0% snow-free. Which would you rather have?

Give a similar treatment to "days of rain", add in more cities, and we can build a bar graph that lends itself to rapid scanning:

Freedom From Snow

Seattle 90%

Austin 100%

Atlanta 99%

Miami 100%

Tucson 98%

San Diego 99%

US Average 78%

Dry Days / Year

Seattle 58%

Austin 77%

Atlanta 69%

Miami 100%

Tucson 98%

San Diego 99%

US Average 78%

Days of Sun / Year

Seattle 42%

Austin 62%

Atlanta 59%

Miami 68%

Tucson 78%

San Diego 73%

US Average 56%

For further examples, read the full TownScores™ City Climate Comparison

City Resources, Career

Research the employers — private and public — in your desired town

Employment listing feeds from your relocation city

Get a "My Yahoo" account, and add feeds to page

Hoover's Online

Company profiles

Jobtrak.com

Company profiles

www.thomasregister.com

150K US/Canadian company profiles

www.ebri.com

– Employee Benefits

Research Institute

www.homefair.com

Home price calculator

www.libraryspot.com

www.inc.com/500

Inc. Magazine's list of fastest growing private companies

New York Public Library

Site section on how to find a U.S. Company

www.chamber-of-commerce.com

Chambers of Commerce listings

www.worldchambers.com

www.bizweb.com

www.smartbiz.com

www.siteselection.com

–

"Site Net" Magazine helps select location for a new business

www.vaultreports.com

"The most trusted name in career information"

TownScores™ City Economy Comparison

Employment Rate

Seattle 95.4%

Austin 95.7%

Atlanta 93.7%

Miami 95.0%

San Diego 95.6%

Tucson 95.2%

US Average 95.0%

Recent Job Growth

Seattle 2.61%

Austin 3.67%

Atlanta 2.12%

Miami 4.12%

San Diego 2.98%

Tucson 1.68%

US Average 1.30%

Projected Job Growth

Seattle 12.08%

Austin 24.15%

Atlanta 11.18%

Miami 4.24%

San Diego 18.91%

Tucson 13.41%

US Average 9.06%

Household Income

Seattle $46,650

Austin $45,508

Atlanta $37,385

Miami $24,031

San Diego $51,382

Tucson $31,901

US Average $44,684

Income per capita

Seattle $30,912

Austin $25,759

Atlanta $27,710

Miami $15,481

San Diego $26,525

Tucson $16,807

US Average $24,020

Sources: U.S. Census Bureau State & County QuickFacts Sperling's Best Places

Wizard: Bestplaces

Wizard: Bestplaces.net "Your Best Places"

After filling out the bestplaces.net questionaire, my top ten cities for relocation looked like the list below. While I admire BestPlaces' coverage and systematic approach, there are cities on this list that I would never choose as relocation spots. San Francisco is too expensive and crowded, Boston is too cold, and Minneapolis has brief winter sunlight periods. This wizard did not quite hit the target for me.

Below you'll find your BestPlaces.

1 . San Francisco , CA Econ.:C, Housing:C, Educ.:A-, Health:A Crime:C+ Rec.:A+, Culture:A+, Trans.:A+

2 . Boston , MA-NH-ME Econ.:C+, Housing:C, Educ.:A, Health:A Crime:B Rec.:A+, Culture:A+, Trans.:A+

3 . Washington , DC-MD-VA-WV Econ.:C, Housing:C+, Educ.:A, Health:A Crime:C+ Rec.:A+, Culture:A+, Trans.:A+

4 . Los Angeles-Long Beach , CA Econ.:C, Housing:C+, Educ.:B, Health:B Crime:C+ Rec.:A+, Culture:A+, Trans.:A+

5 . New York , NY Econ.:C-, Housing:C, Educ.:B+, Health:B+ Crime:C+ Rec.:A+, Culture:A+, Trans.:A+

6 . San Diego , CA Econ.:C, Housing:C+, Educ.:B+, Health:B- Crime:C+ Rec.:A+, Culture:A+, Trans.:A

7 . Oakland , CA Econ.:C, Housing:C, Educ.:B+, Health:C Crime:C- Rec.:A+, Culture:A+, Trans.:A

8 . San Jose , CA Econ.:C, Housing:C, Educ.:B+, Health:B Crime:B Rec.:A+, Culture:A+, Trans.:B+

9 . Long Island , NY Econ.:C, Housing:C, Educ.:A, Health:A- Crime:A+ Rec.:A+, Culture:A+, Trans.:B+

10 . Minneapolis-St. Paul , MN-WI Econ.:B, Housing:C+, Educ.:A-, Health:A- Crime:C+ Rec.:A+, Culture:A+, Trans.:A

Geographic, Demographic, & Economic Profiles

www.locationguides.com

www.ajb.dni.us

America's Career InfoNet. Geo. profile

www.runzheimer.com

A cost of living index

www.pathfinder.com/money/bes tplaces

Money Magazine Best Places

www.bigbook.com

www.datamasters.com

www.city.net