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I’ve been talking about what I make as a freelancer on Twitter today. Here’s the thread if you missed it. For some reason I felt like editors would be mad at me for saying what I make at each place, but that’s kind of weird isn’t it? One reason some people gave for that is that they may not want other writers they work with knowing other people get paid more. I don’t think everyone should be paid the same amount for every story at a specific publication. Some people are better than others. Many people are better than me! Many are not.

I made about $60k in 2013 as a fulltime freelancer. I work every day, with norare non-working weekends and vacations. I have been doing this for about 14 years. I waited tables for many of those years on the side. In 2012 I made about $50k. In 2011 around $40k. Next year I will make $0k when all my editors fire me.

I’d say I do about 50/50 print/web stuff now. Print still pays much better. Longer, reported features obviously take a lot longer to do than blog posts, and still, for the most part, the difference in pay is worth it. Some stories I might work on for a couple weeks and make only $500 bucks. Sometimes I’ll spend 3 minutes on a blog post and make $50.

I originally posted this on my own blog, but then once it started to take off I figured I better post it here so I can get paid for it.

Last year I wrote about the joys of freelancing here.

These are the 20 odd places I’ve worked for in past year and half or so. I’m probably forgetting a couple.

Boston Globe
roughly 50 cents a word usually, $75-150 shorter, $250-$600 for feature

Esquire
$150-300 for web, $1000 for digital feature

Wall Street Journal
$1 a word print

Mediaite
$50-100 blog post

MTV.com
$50 blog post

Dazed
$75-150 web

Slate
$200-300

Village Voice
$100-150 web, 50 cents a word print

Boston Magazine
$1 a word print, $100ish web

BDC Wire (Boston.com)
$50 blog post

Complex
$75-150 web

Vice
$50-150 web

Metro
$125 print

Bullett
$30-50 blog post, $150 web feature

The New Republic
$200-250 web

LA Times Opinion
$100 web

Gawker
$100 freelance post, $150 a day of blogging (6-8 posts)

Alternative Press
$150 web feature

Interview Magazine
$20 web

Black Balloon blog
$150

Edible Boston
$500 feature

Follow me on Twiter @lukeoneil47

Affordable housing policies have a long history of hurting the very people they are said to help. Past decades’ practices of building Corbusian public housing that concentrates low-income people in environments that support crime or pursuing “slum clearance” to eliminate housing deemed to be substandard have largely been abandoned by housing affordability advocates for the obvious harm that they cause stated beneficiaries. While rent control remains an important feature of the housing market in New York and San Francisco, even Bill de Blasio’s deputy mayor acknowledges the negative consequences of strong rent control policies. In the U.S. and abroad, politicians and pundits are beginning to vocalize the fact that maintaining and improving housing affordability requires housing supply to increase in response to demand increases.

While support for older housing affordability policies has dissipated, the same isn’t true of inclusionary zoning.  From New York to California, housing affordability advocates tout IZ as a cornerstone of successful  housing policy. IZ has emerged as the affordable housing policy of choice because it has the benefit of supporting socioeconomic diversity, and its costs are opaque and dispersed over many people. However, IZ has several key downsides including these hidden costs and a failure to meaningfully address housing affordability for a significant number of people. Shaila Dewan of the New York Times captures the strangeness of IZ’s popularity:

New York needs more than 300,000 units by 2030. By contrast, inclusionary zoning, a celebrated policy solution that requires developers to set aside units for working and low-income families, has created a measly 2,800 affordable apartments in New York since 2005.

DC’s City Center includes 92 affordable units. Image via Foster and Partners.

Montgomery County, a Maryland suburb of DC,  has perhaps the most well-established IZ policy in the country. After 30 years, the program has produced about 13,000 units. Montgomery County is home to over one million people, 20 percent of whom have a household income of less than $43,000 annually. While this is an extraordinarily high income distribution relative to the rest of the country, this makes the county’s median apartment rental of nearly $2,300 out of reach for many more people than even an aggressive IZ policy can serve.

While Montgomery County’s IZ housing does not reach a large percent of its population, it has provided many more units than other cities’ programs have. Washington, DC’s IZ law was passed in 2006, requiring developers to set aside 8-10% of units as affordable in all new projects with more than 10 units. As of the most recent 2012 report, DC’s IZ program has yet to reach a single beneficiary. The IZ units that have made it to market are sitting empty. This is in part because IZ units, priced to be affordable to those making between 50% and 80% of the Area Median Income, are not the most cost effective choice for many people in this income range, potential beneficiaries of owner-occupied IZ units may not be able to qualify for a mortgage. IZ units tend to be one- or two-bedroom apartments. Low- and moderate-income DC residents may be able to find housing that is much more affordable than what IZ provides by living in a larger apartment with a roommate(s), in a group house, or with family. By attaching these affordable units to new, often luxury buildings, IZ siphons affordable housing resources to the type of housing where it will buy the least.

Evidence on the benefits that mixed-income housing provides for low-income people is mixed, but it’s hard to deny that inclusionary zoning beneficiaries win a lottery. They live in new construction in desirable neighborhoods, housing that would cost several times as much at the market rate. However, IZ’s effects are not limited to beneficiaries, and its costs are not fully borne by developers. Because developers will lose money on the IZ units they build, this cost has to be made up in the market rate units in order for the project to go forward. This adds to construction costs and also incentivizes luxury units that can better absorb the cost of the IZ units relative to more affordable construction. While providing affordable housing to a few lucky low-income people, IZ also makes housing less affordable for everyone who doesn’t receive the benefit by reducing housing supply and skewing the market toward luxury housing that can subsidize the affordable units.

IZ appears free to everyone except developers because it’s not paid for out of city budgets. But ultimately housing consumers share in the cost of IZ units through a hidden tax. By making new construction more expensive, IZ also reduces the rate at which the prices of older or less desirable housing filters down to the point that it becomes affordable to low- and middle-income residents. Putting affordable housing in new construction ensures that it will benefit fewer people than the same amount of resources otherwise could. IZ supporters emphasize the importance of neighborhoods that are socioeconomically diverse but ignore the opportunity cost. Low-income people may be well-served by putting resources toward living in a diverse neighborhood, but this competes against many other places their resources could go, including investing in a business, pursuing education, or prioritizing nutritious food.

As economist Ben Powell explains, IZ can be designed not to have an effect on market-rate housing prices if developers are allowed to voluntarily trade the provision of IZ units for density bonuses. In that case the bonuses must be high enough to offset the cost of the below-cost units. However, as Stephen has pointed out, IZ creates an affordable housing lobby that opposes upzoning without affordability requirements. Eliminating IZ would put all housing affordability advocates on the same team. The same amount of resources currently providing for IZ units could be levied as a transparent tax and transferred to low-income people as cash rather than as luxury housing. This would also allow for resources to be distributed based on need, rather than giving a few households a jackpot.

Davide Cantoni, Yuyu Chen, David Y. Yang, Noam Yuchtman, Y. Jane Zhang, 29 May 2014

Schooling changes are associated with ideological ones but it is difficult to claim a causal relationship. This column attempts to analyse the causal effect of curriculum changes in China on shaping preferences of students. The new curriculum moves one’s belief about democracy by about 25% of a standard deviation in the direction desired by the government. The findings suggest the state can use education to promote socially-useful beliefs and cultivate good citizenship.

Full Article: Curriculum and ideology

Harun Onder, Pierre Pestieau, 20 May 2014

The world’s population is ageing, due to both increasing longevity and decreasing fertility. This column shows that the net effect of ageing on capital accumulation (and therefore growth) depends on which of these two factors dominates, and also on the structure of the pension system. Under a pension system with defined contributions, a reduction in fertility induces adjustments in savings and working life that unambiguously increase capital per worker.

Full Article: The source of population ageing matters: Longevity versus fertility

BUYING ‘Fairtrade’ coffee is not really helping the very poor, new research suggests. By comparing living standards in Fairtrade-certified producing areas in Ethiopia and Uganda with similar non-Fairtrade regions, four development economists from the School of Oriental and African Studies (SOAS) in London found that Fair Trade agricultural workers often earned lower incomes.

After four years of fieldwork in the coffee, tea and flower sectors in Ethiopia and Uganda, where they gathered 1,700 survey responses and conducted more than 100 interviews, the SOAS researchers found people living in ordinary rural communities enjoyed a higher standard of living than seasonal and casual agricultural workers who received an apparently subsidised wage for producing Fairtrade exports. Women’s wages were especially low among producers selling into Fairtrade markets, according to the researchers.

Comparing areas where the same crops were produced by similar, though not Fairtrade-certified employers, they found that workers received higher wages and benefited from better conditions. This...Continue reading

An anonymous reader writes "In 2010 the state of public education in Newark, New Jersey was dire. The city's school system was a disaster, replete with violence, run-down buildings, and a high-school graduation rate of only 54%. Newark's mayor at the time, Cory Booker, teamed up with governor Chris Christie to turn the schools around. At the same time, Mark Zuckerberg was looking to get his feet wet in big-time philanthropy. The three hatched a plan, and Zuckerberg committed $100 million to reforming the schools. Four years later, most of the money is gone, and Newark's children are still struggling. Tens of millions were spent on consulting groups, and yet more went to union negotiations. Plans to change how teacher seniority affected staffing decisions — in order to reward results rather than persistence — were dashed by political maneuvering. The New Yorker provides a detailed account in a lengthy piece of investigative journalism, and MSN provides a summary."

Read more of this story at Slashdot.

What accounts for the sharp spike in unemployment during recessions? And why did the unemployment rate recover so slowly after recent recessions? I’ve been looking into these questions with UCSD Ph.D. candidate Hie Joo Ahn, and we’ve just finished a new research paper summarizing some of our findings.

One of the interesting details behind the unemployment numbers reported by the Bureau of Labor Statistics is a question that asks unemployed individuals how long they’ve been looking for work. The graph below plots the number of Americans each month who say they’re newly unemployed (U¹), are unemployed and have been looking for 2-3 months (U^2.3), and those who have been looking 4-6 months. Note that longer-term unemployment rises more sharply during recessions.

If you’ve been looking for a job for 2-3 months, it means you would have been newly unemployed 1 or 2 months ago. From the average values of (U¹) and (U²), you can calculate that on average about half of those who are newly unemployed either found a job or dropped out of the labor force the following month. On the other hand, by comparing (U^2.3) with (U^4.6), you find that on average something like 63% of those who have been looking for work for 2-3 months will still be looking the following month.

The number of people who have been looking for work for 7-12 months (U^7.12) and more than a year (U¹³⁺) skyrocketed in the Great Recession, and is still higher than it had been even at the worst point of any previous postwar recession.

Why do people who have been looking for work a longer period have more trouble finding a job? One key possibility we consider is that those individuals started out in different circumstances. For example, workers who are permanently laid off have a harder time finding new jobs than those who quit voluntarily (Bednarzik, 1983; Fujita and Moscarini, 2013). Quitters might have been a big part of the original group of newly unemployed. But if most of them find a new job quickly, they will represent a smaller fraction of the group the longer that the group has been unemployed.

Suppose you divided workers into two groups, which we designate as type H and type L, and conjectured that the number of newly unemployed workers each month represents a mixture of the two types and further that there are differences in the probabilities that each of the two types will be successful in finding jobs. By keeping track of the dynamic accounting identities (somebody who’s been unemployed for 3 months at time t and doesn’t find a job will be unemployed for 4 months at t+1), observations on the 5 variables in the two graphs above are more than enough to determine 4 unknown magnitudes (inflows of type H and type L workers each month and fraction of each type who exit the pool of unemployed each month). Our statistical model also allows for measurement error (the true numbers may be different from those that are reported) and assumes that inflow and outflow probabilities for the two types change smoothly over time. We also use the extra information in the fifth observed variable to allow for the possibility that the process of being unemployed for a longer duration actually changes the individual, even if he or she started out initially just like everyone else.

We find that in normal times, 90% of those who are newly unemployed would be characterized as type H, more than half of whom will likely no longer be unemployed the following month. But in most recessions, the single most important development is an increase in the number of newly unemployed type L individuals who end up having a more difficult time finding work. For example, here’s how our model interprets the changes during the recession of 1981-82.

The overwhelming story behind the Great Recession is newly unemployed type L workers.

And who are these type L workers? Our statistical model infers these magnitudes solely from the aggregate numbers of Americans who have been looking for work for different amounts of time (the 5 series plotted in Figures 1 and 2 above). But it is very interesting to compare our estimates of the number of newly unemployed type L workers (the red line in the graph below) with separate measures (in blue) of the number of newly unemployed workers who lost their jobs as a result of what was described as a permanent job loss or a temporary job that has now ended. Though the red and blue series were arrived at in completely different ways, they look remarkably similar. Notwithstanding, our series for W_L is on average only about half the size of the reported number of permanent separations. The indicated conclusion is that many of those experiencing permanent separations do not wait long before finding new work. Interestingly, Fujita and Moscarini (2013) found that significant numbers of those who initially reported their separations to have been permanent ended up going back to work for their old employer.

And here is our series for newly unemployed type H workers compared with those who were newly unemployed as a result of temporary layoffs, quits, or entrance to the labor force. Again the red and blue look like practically the same series but plotted on a different scale. Our conclusion is that the single most important difference between our designated type L and type H workers, and single most important feature distinguishing recessions from normal times, is the circumstances under which many people lose their jobs.

We also investigated an additional mechanism that could account for the differences in unemployment exit probabilities implicit in Figures 1 and 2 above, this being the possibility that the experience of being unemployed for a certain period of time actually changes the individual. Kroft, Lange, and Notowidigdo (2012) and Eriksson and Rooth (2014) reported interesting field experiments demonstrating that employers are less interested in hiring those who’ve been unemployed for a longer period of time. My research with Ahn finds evidence of different effects operating over different unemployment durations. If an individual has been unemployed for fewer than 6 months, an additional month of unemployment makes it less likely that the individual will exit unemployment the following month even when we condition on the worker’s type. This is consistent with what we call an “unemployment scarring” interpretation. On the other hand, we find that after 6 months, each additional month of unemployment makes it more likely the individual will exit unemployment, which we refer to as “motivational” effects.

It is interesting that this difference sets in around 6 months, which in normal times would be when unemployment insurance is exhausted. When we allowed potential scarring or motivational effects to be different depending on the eligibility for unemployment insurance that was likely to be in effect at each date, we found a significantly improved fit to the data. During times when most unemployment insurance would have been exhausted after 6 months, we found strong motivational effects beginning after 6 months, whereas during periods of extended eligibility, we failed to find much evidence of motivational effects until after 12 months. For additional supporting evidence, see Fujita (2011) and Farber and Valletta (2013).

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by Dan Malouff

There are more than 300 million people living in the United States today, but America is such a huge country that we still have staggeringly vast areas that are completely devoid of humans. This map illustrates those places. Everything colored green is a census block with zero population.

The eastern US is pretty well populated except for a few spots in mountains and swamps. But the west is a different story. It's covered with enormous stretches of land that are simply empty.

And Alaska's emptiness makes even the western contiguous states look densely populated. Those green areas near the Arctic Circle look bigger than most other states.

Cross-posted at BeyondDC.

34 comments

The draft blog post said to watch out for funny business in Melitopol and Mariupol, Ukraine. Those are the largest settlements along the coast between Russia and the Crimean peninsula, and sit astride the road that runs from Rostov-on-the-Don and the Crimea. Mariupol is the second-largest city in the Donetsk region, with a population of nearly half a million. Melitopol is also a crossroads: east to Russia, south to the Crimea, north to Zaporizhia and west to Kherson.

Radio Free Europe/Radio Liberty’s daily summary noted:

By early evening there were reports of skirmishes between pro-Russia and pro-Ukraine groups in Kharkiv, a tense standoff in Zaporizhia, and the occupation by pro-Russian activists of local government buildings in Makiyivka and Mariupol. Pro-Russian activists were also reportedly moving on the Security Service building in Odessa.

So let’s go with a quick scoreboard from this weekend and last instead.

Kharkiv: occupation attempt repulsed
Zaporizhia: tense standoff
Kramotorsk: buildings occupied
Druzhkivka: buildings occupied
Yenakijeve: buildings occupied
Makiyivka: buildings occupied
Mariupol: buildings occupied
Luhansk: buildings occupied
Donetsk: buildings occupied
Slovyansk: buildings occupied
Mykolaiv: occupation attempt repulsed
Odessa: occupation attempt repulsed
Krasny Lyman: disturbances

The buildings that are being occupied are local city halls, police stations and administrative buildings. That most definitely includes any local arsenals.

This weekend has also seen the return of the “little green men,” so called during the occupation of the Crimea because their origins are so mysterious that they must be from Mars. Never mind that they wear Russian uniforms sans insignia, have equipment issued to Russian armed services, and use Russian words that are not generally used by Russian-speaking persons who live in Ukraine.

Ukraine’s acting president has not minced words. In a live televised address, Oleksandr Turchynov spoke of

…war that is being waged against Ukraine by the Russian Federation. The aggressor has not stopped and continues to organize disorders in eastern Ukraine.

This is not a war between Ukrainians. This is an artificially created situation of confrontation aimed at weakening and destroying Ukraine itself.

He also said that a large-scale counter-operation would begin Monday morning. Stay tuned.

Looking back at last month’s guide to revisiting the 1930s, further east:

Kharkiv, Donetsk: Sudetenland. Some real tension, mostly trumped up and stage-managed confrontations. ((Check.)) Pleas for “protection” from some parts of a particular nationality to the outside power. ((Check.)) Not fooling anyone. ((Check.)) In contrast to then, Kiev would try to defend the frontier region militarily. ((Check, as of April 14.)) (The great powers will not intervene, should it come to that.) ((Check.)) Whether that defense would succeed is rather an important question. There’s not a major defensible barrier until the Dniepr. Speaking of which…

Dnepropetrovsk, Zaporizhia: Poland. The great powers would not be able to overlook the dismemberment of a major European state. They wouldn’t be able to stop it, either.

Zaporizhia hasn’t seen much in the way of disturbances. Yet.

Also: Toomas Hendrik Ilves noted on Twitter, “After these several weeks, Europe’s M-F, 9-5 foreign policy establishment might perhaps recognise what’s happening next door weekends too.” Maybe all of the little green men and their associated crowds have day jobs, or maybe the powers-that-be on Mars have noticed that Saturday is not a big day for news, and are timing their operations accordingly. It’s not likely that they read John Scalzi’s blog, but he makes a point concerning publicity and next weekend:

But of all the Saturdays in all of the calendar year, the very worst possible Saturday to announce anything is the Saturday between Good Friday and Easter. Because it’s the Saturday between Good Friday and Easter, that’s why — the Saturday sandwiched between two major religious holidays, which means the “weekend” that week starts on Thursday and Sunday’s news cycle is swamped by the most important Christian holiday of the year — Christmas is noisier for longer, but Easter is concentrated. If you’re the Pope, Easter Sunday is great for you, news wise. If you’re not the Pope, not. …
If I were a crooked politician who had been caught murdering kittens while masturbating to a picture of Joseph Stalin, then the day I would choose to have that news go out into the world would be the Saturday between Good Friday and Easter.

That Western and Orthodox Easter align this year makes the news gap even larger. People in the wider world will not be paying attention next weekend. Don’t be surprised if the little green men are very active indeed.