High rents and the lack of politics

Forbes recently published a two part interview with law professor David Schleicher discussing his recent paper City Unplanning.  Schleicher discusses the perversity of zoning restrictions and begins by noting that, in many cases, rents and rental units available have nothing to do with each other:

In a number of big cities, new housing starts seem uncorrelated or only weakly correlated with housing prices and the result of increasing demand while holding supply steady is that price went up fast. The average cost of a Manhattan apartment is now over $1.4 million and the average monthly rent is over $3,300.

The only explanation is that zoning rules stop supply from increasing in the face of rising demand.

Effectively, Schleicher argues that new developments in big cities are subject to a form of NIMBYism which is effective to the extent it is apolitical:

Local legislators may prefer more development than we have now to less, but have stronger preferences for stopping development in their districts because these projects would hurt homeowners in their neighborhoods—either directly through things like increased traffic or indirectly through increasing the supply of housing, harming the value of existing houses.

This is a prisoner’s dilemma and absent a political party to organize the vote in local legislatures, one-by-one votes on projects will result in “defect” results, or situations where every legislator builds coalitions to block projects in their own district and nothing gets built [emphasis added].

I couldn’t quite understand Schleicher’s point from the interview, but it is much better explained in the full paper:

Importantly, most cities do not have competitive party politics – they either have formally nonpartisan elections and/or are entirely dominated by one party that rarely takes local-issue specific stances. Absent partisan competition, there is little debate over citywide issues in local legislative races and there is no party leadership to organize the legislature, making the procedural rules governing the manner in which the legislature considers land use issues far more important. The content of the land use procedure generates what one might call “localist” policy-making: seriatim [i.e., one-off] decisions about individual developments or rezonings in which the preferences of the most affected local residents are privileged against more weakly-held citywide preferences about housing.

It’s an intriguing thesis positively, but I’m not sure what I think of Schleicher’s point normatively.  Local voters generally do seem to prefer NIMBY outcomes in order to avoid threats (e.g., increased traffic, lowered property values) to their existing assets (i.e., homes and businesses).  But if local voters achieve this result through the mechanics of “weak” local politics, isn’t that an example of the political system “working”?

Put another way, high rents may be undesirable, but they are largely an outsider problem.  Current residents (insiders who can vote) first and foremost want to protect themselves from the problematic vicissitudes of new development (which will, if it is built, be populated with outsiders who obviously cannot vote unless it is built and they take up residence).  If current residents/voters achieve this goal through voting for “apolitical” council members, (1) isn’t this actually a highly political choice, and (2) isn’t this precisely how voting and elections are designed to work?

Predicting the fastest growing American cities for the next 40 years

Forbes has a new list of what they think will be the fastest growing cities in the United States in the next 40 years. Not surprisingly, the top 5 are all in the South and West. Perhaps surprisingly, these cities are “little big cities,” places that grown in the last few decades and are poised for new growth. Here are the top cities for growth: Raleigh-Durham, North Carolina; Austin, Texas; Salt Lake City, Utah; San Antonio, Texas; Oklahoma City, Oklahoma.

Forbes says they are using a different methodology to select these cities:

In developing this list we have focused on many criteria–affordability, ease of transport and doing business–that are often ignored on present and future “best places” lists. Yet ultimately it is these often mundane things, not grandiose projects or hyped revivals of small downtown districts, that drive talented people and companies to emerging places.

This methodology seems to emphasize “softer factors” like affordability and quality of life. I almost wish we could just fast forward forty years to see how accurate this is. What would others predict and what factors would they use?

But I can see some of the logic. These places offer some of the amenities of the big city and are vibrant places where things are happening. Couple this with affordable homes, some jobs, and less congestion and I could see how it is appealing. Additionally, 8 out of the top 10 are in the South and West – only Columbus, Ohio and Indianapolis, Indiana are outside these regions. It would make sense that the growing areas of the country are the places where these mid-sized cities are growing.

Determining the best colleges…using RateMyProfessor.com?

Forbes recent published another installment of their rankings of the best colleges in America. One of the question that arises with such a list is the methodology behind the rankings. To their credit, Forbes provides a lengthy explanation.

Even as the ranking is supposedly from the point of view of students, I initially had some questions about one of the major criteria which accounts for 17.5% of the score for a college: using student evaluations of professors at RateMyProfessor.com. At first, this sounded crazy to me – how representative is the data from RateMyProfessors.com and does it accurately reflect what is going on in the classroom?

Forbes sums up why they used this data:

In spite of some drawbacks of student evaluations of teaching, they apparently have value for the 86% of schools that have some sort of internal evaluation system. RMP ratings give similar results to these systems. Moreover, they are a measure of consumer preferences, which is what is critically important in rational consumer choice. When combined with the significant advantages of being uniform across different schools, not being subject to easy manipulation by schools, and being publicly available, RMP data is a preferred data source for information on student evaluations of teaching–it is the largest single uniform data set we know of student perceptions of the quality of their instruction.

To recap why these used data from RateMyProfessors.com:

1. RMP ratings are similar to evaluation scores gathered by colleges. There is some scholarly research to back this up.

2. RMP ratings are “a measure of consumer preference.” This is data generated voluntarily by students. If Forbes wants the students’ perspective, this website offers it. (Though it is still a question whether it is a representative measure – but point #1 may take care of that.)

3. RMP ratings are perhaps the only data source to answer the question of what students experience in the classroom. It may not be perfect data but it can be used as an approximation.

Overall, Forbes logic makes some sense: RateMyProfessor.com offers a unique dataset that when cleaned up (and they describe how they weighted and standardized the scores) offers some insights into the classroom experience.

However, I’m still leery of giving 17.5% of the total score over to RateMyProfessor.com evaluations. Perhaps the scholarly literature will continue to examine this website and determine the value of its ratings. And you can see that Forbes is tweaking their measurements: the 2009 methodology explanation has some differences and the RateMyProfessor.com score then counted for 25% of the total score (compared to 17.5% in the 2010 edition).

Measuring celebrity

Forbes has released its annual list of the 100 most powerful celebrities. See Forbes’ website for a full portal that includes profiles of some of the celebrities and the full rankings (including rankings on subcategories). Topping the list is Oprah followed by Beyonce and James Cameron.

Buried at the bottom of the story is the methodology by which Forbes developed its list (the methodology is mentioned in this reposted story at Yahoo):

The Celebrity 100 is a measure of power based on money and fame. Earnings estimates, which include income from films, television shows, endorsements, books, and other entertainment ventures, are calculated between June 2009 and June 2010. Figures were rounded off where appropriate. Additional sources include Billboard, Pollstar, Adams Media Research, The Nielsen Company, and SNL Kagan. Fame is calculated using web hits on Google, Blog Search, TV/radio mentions on LexisNexis, overall press mentions on Factiva, and the number of times a celebrity’s image appeared on the cover of 25 consumer magazines. Social rank is calculated using metrics like Facebook friends and fans as well as Twitter followers.

I would be very interested in knowing the weights applied to each of these measures and broader categories (such as social rank). Take Lady Gaga for example: she is new to the list this year, does not have the media empires like some of the others on the list (Oprah’s big money advantage comes from an involvement in a multitude of media outlets), and yet benefits from a #1 ranking in the social rankings.

After a quick glance, money appears most important here. Perhaps having money prompts more media (of all kinds) mentions. Or perhaps the media mentions help build the money which then leads to a reinforcing cycle. Regardless, just having money may be a sign that you are a true celebrity. We as Americans may like our celebrities because they host a TV show or can do amazing things with a golf ball or can direct exciting movies, but just having money seems pretty interesting in itself.