Tag Archives: labor

Northern Cities Need To Be Bold If They Want To Grow

Geography and climate have played a significant role in U.S. population growth since 1970 (see here, here, here, and here). The figure below shows the correlation between county-level natural amenities and county population growth from 1970 – 2013 controlling for other factors including the population of the county in 1970, the average wage of the county in 1970 (a measure of labor productivity), the proportion of adults in the county with a bachelor’s degree or higher in 1970 and region of the country. The county-level natural amenities index is from the U.S. Department of Agriculture and scores the counties in the continental U.S. according to their climate and geographic features. The county with the worst score is Red Lake, MN and the county with the best score is Ventura, CA.

1970-13 pop growth, amenities

As shown in the figure the slope of the best fit line is positive. The coefficient from the regression is also given at the bottom of the figure and is equal to 0.16, meaning a one point increase in the score increased population growth by 16 percentage points on average.

The effect of natural amenities on population growth is much larger than the effect of the proportion of adults with a bachelor’s degree or higher, which is another strong predictor of population growth at the metropolitan (MSA) and city level (see here, here, here, and here). The relationship between county population growth from 1970 – 2013 and human capital is depicted below.

1970-13 pop growth, bachelors or more

Again, the relationship is positive but the effect is smaller. The coefficient is 0.026 which means a 1 percentage point increase in the proportion of adults with a bachelor’s degree or higher in 1970 increased population growth by 2.6 percentage points on average.

An example using some specific counties can help us see the difference between the climate and education effects. In the table below the county where I grew up, Greene County, OH, is the baseline county. I also include five other urban counties from around the country: Charleston County, SC; Dallas County, TX; Eau Claire County, WI; San Diego County, CA; and Sedgwick County, TX.

1970-13 pop chg, amenities table

The first column lists the amenities score for each county. The highest score belongs to San Diego. The second column lists the difference between Green County’s score and the other counties, e.g. 9.78 – (-1.97) = 11.75 which is the difference between Greene County’s score and San Diego’s score. The third column is the difference column multiplied by the 0.16 coefficient from the natural amenity figure e.g. 11.75 x 0.16 = 188% in the San Diego row. What this means is that according to this model, if Greene County had San Diego’s climate and geography it would have grown by an additional 188 percentage points from 1970 – 2013 all else equal.

Finally, the last column is the actual population growth of the county from 1970 – 2013. As shown, San Diego County grew by 135% while Greene County only grew by 30% over this 43 year period. Improving Greene County’s climate to that of any of the other counties except for Eau Claire would have increased its population growth by a substantial yet realistic amount.

Table 2 below is similar to the natural amenities table above only it shows the different effects on Greene County’s population growth due to a change in the proportion of adults with a bachelor’s degree or higher.

1970-13 pop chg, bachelor's table

As shown in the first column, Greene County actually had the largest proportion of adults with bachelor’s degree or higher in 1970 – 14.7% – of the counties listed.

The third column shows how Greene County’s population growth would have changed if it had the same proportion of adults with a bachelor’s degree or higher as the other counties did in 1970. If Greene County had the proportion of Charleston (11.2%) instead of 14.7% in 1970, its population growth is predicted to have been 9 percentage points lower from 1970 – 2013, all else equal. All of the effects in the table are negative since all of the counties had a lower proportion than Greene and population education has a positive effect on population growth.

Several studies have demonstrated the positive impact of an educated population on overall city population growth – often through its impact on entrepreneurial activity – but as shown here the education effect tends to be swamped by geographic and climate features. What this means is that city officials in less desirable areas need to be bold in order to compensate for the poor geography and climate that are out of their control.

A highly educated population combined with a business environment that fosters innovation can create the conditions for city growth. Burdensome land-use regulations, lengthy, confusing permitting processes, and unpredictable rules coupled with inconsistent enforcement increase the costs of doing business and stifle entrepreneurship. When these harmful business-climate factors are coupled with a generally bad climate the result is something like Cleveland, OH.

The reality is that the tax and regulatory environments of declining manufacturing cities remain too similar to those of cities in the Sunbelt while their weather and geography differ dramatically, and not in a good way. Since only relative differences cause people and firms to relocate, the similarity across tax and regulatory environments ensures that weather and climate remain the primary drivers of population change.

To overcome the persistent disadvantage of geography and climate officials in cold-weather cities need to be aggressive in implementing reforms. Fiddling around the edges of tax and regulatory policy in a half-hearted attempt to attract educated people, entrepreneurs and large, high-skill employers is a waste of time and residents’ resources – Florida’s cities have nicer weather and they’re in a state with no income tax. Northern cities like Flint, Cleveland, and Milwaukee that simply match the tax and regulatory environment of Houston, San Diego, or Tampa have done nothing to differentiate themselves along those dimensions and still have far worse weather.

Location choices reveal that people are willing to put up with a lot of negatives to live in places with good weather. California has one of the worst tax and regulatory environments of any state in the country and terrible congestion problems yet its large cities continue to grow. A marginally better business environment is not going to overcome the allure of the sun and beaches.

While a better business environment that is attractive to high-skilled workers and encourages entrepreneurship is unlikely to completely close the gap between a place like San Diego and Dayton when it comes to being a nice place to live and work, it’s a start. And more importantly it’s the only option cities like Dayton, Buffalo, Cleveland, St. Louis and Detroit have.

Baltimore’s misguided move to raise its minimum wage will harm its most vulnerable

Baltimore’s city council, like others around the country, is considering raising the city’s minimum wage to $15 per hour. This is an ill-advised move that will make it harder for young people and the least skilled to find employment, which is already a difficult task in Baltimore.

The figure below shows the age 16 – 19 labor force participation (LFP) rate, employment rate, and unemployment rate in Baltimore City from 2009 to 2014 (most recent data available). The data are from the American Community Survey table S2301.

baltimore 16-19 emp stats

As shown in the figure, the LFP rate declined along with the employment rate, which has caused the unemployment rate to hold steady at approximately 40% (red line). So 40% of Baltimore’s unemployed teens were searching for a job but couldn’t find one and only 20% of all teens were actually employed, a decline of 4 percentage points (blue line). How is increasing the minimum wage to $15 per hour going to help the 40% who are looking for a job find one?

The minimum wage increase may help some people who are able to keep their job at the higher wage, but for the 40% who can’t find a job at the current minimum wage of $8.25, an increase to $15 is only going to make the task harder, if not impossible. Who is standing up for these people?

The data are just as gloomy when looking at workers with less than a high school degree, which is another group that is severely impacted by a higher minimum wage. As the figure below shows, the employment rate is falling while the unemployment rate is rising.

baltimore lt hs emp stats

In 2009 over 42% of people in this skill group were employed (blue line). In 2014 only 37% were, a decline of five percentage points. Meanwhile, the unemployment rate increased from about 19% to over 25% (red line). And all of this occurred while the economy was supposedly improving.

Again we should ask; how is a higher minimum wage going to help the 25% of high school dropouts in Baltimore who are unemployed find a job? It won’t. Unemployed workers do not become more attractive as employees simply because the city council mandates a higher wage.

What’s going to happen is that more people in this skill group will become discouraged and leave the labor market entirely. Then they will earn $0 per hour indefinitely and be forced to rely entirely on family, friends, and public assistance to live. A $15 minimum wage destroys their chances of finding meaningful employment and unduly deprives them of opportunities to better their lives.

This is the unseen effect of minimum wage hikes that $15 supporters rarely acknowledge. When faced with the higher cost, firms will hire workers who can justify a $15 wage and those who cannot will be unable to find employment. Additionally, firms will start using more technology and automation instead of workers. This happens because consumers want low prices and high quality, and as the minimum wage increases technology and capital become the best way to give consumers what they want. Over time workers in states with lower minimum wages may be forced out of the labor market as well as new technologies spread from high minimum wage areas to low minimum wage areas.

Another common argument put forth by minimum wage supporters is that taxpayers subsidize firms that pay low wages. But this is not true. Firms like Wal-Mart, McDonalds, and the countless other large and small business that employ low-skill workers are doing their part by giving people an opportunity. Firm owners did not unilaterally decide that all Americans should have a minimum standard of living and they should not be required to provide it on their own. Ultimately, advocates of a higher minimum wage who worry that they are subsidizing firms will likely be forced to contribute even more tax dollars to social programs since the wage for unemployed workers is $0.

Furthermore, why $15 and not $20? The argument is that $15/ hour is the minimum necessary to maintain a basic standard of living for working Americans but that argument is subjective. In fact, it can be extended to other areas. For example, should new hires be paid more than an entry-level salary so they can pay off college debt and maintain the standard of living of their parents?

To the extent that Americans deserve a particular lifestyle, providing it is a collective burden that should be shared by everyone. Politicians, clergy, union heads and other minimum wage supporters who want to push the entire burden onto firms are abandoning the moral obligation they claim we all share.

While minimum wage supporters mean well they appear to be blind to those who are harmed by wage controls. And those who are harmed are some of the most vulnerable members of the workforce – high school drop-outs, recent immigrants and urban youth. The minimum wage is a misguided policy that consigns these vulnerable members of the labor force to the basement of the economy and prevents any escape.

States with lower minimum wages will feel the impact of California’s experiment

California governor Jerry Brown recently signed a law raising California’s minimum wage to $15/hour by 2022. This ill-advised increase in the minimum wage will banish the least productive workers of California – teens, the less educated, the elderly – from the labor market. It will be especially destructive in the poorer areas of California that are already struggling.

And if punishing California’s low-skill workers by preventing them from negotiating their own wage with employers isn’t bad enough, there is reason to believe that a higher minimum wage in a large state like California will eventually affect the employment opportunities of low-skill workers in other areas of the country.

Profit-maximizing firms are always on the lookout for ways to reduce costs holding quality constant (or in the best case scenario to reduce costs and increase quality). Since there are many different ways to produce the same good, if the price of one factor of production, e.g. labor, increases, firms will have an incentive to use less of that factor and more of something else in their production process. For example, if the price of low-skill workers increases relative to the cost of a machine that can do the same job firms will have an incentive to switch to the machine.

To set the stage for this post, let’s think about a real life example; touch screen ordering. Some McDonald’s have touchscreens for ordering food and coffee and San Francisco restaurant eatsa is almost entirely automated (coincidence?). The choice facing a restaurant owner is whether to use a touch screen or cashier. If a restaurant is currently using a cashier and paying them a wage, they will only switch to the touch screen if the cost of switching and the future discounted costs of operating and maintaining the touch screen device are less than the future discounted costs of using workers and paying them a wage plus any benefits. We can write this as

D + K + I + R < W

Where D represents the development costs of creating and perfecting the device, K represents the costs of working out the kinks/the trial run/adjustment costs, I represents the installation costs, and R represents the net present value of the operating and maintenance costs. On the other side of the inequality W represents the net present value of the labor costs. (In math terms R and W are: R = [ ∑ (rk) / (1+i)^n from n=0 to N ] where r is the rental rate of a unit of capital, k is the number of units of capital, and i is the interest rate and W = [ ∑ (wl) /(1+i)^n from n=0 to N ] where w is the wage and l is the amount of labor hours. But if this looks messy and confusing don’t worry about it as it’s not crucial for the example.)

The owner of a restaurant will only switch to a touch screen device rather than a cashier if the left side of the above inequality is less than the right side, since in that case the owner’s costs will be lower and they will earn a larger profit (holding sales constant).

If the cashier is earning the minimum wage or something close to it and the minimum wage is increased, say from $9 to $15, the right side of the above inequality will increase while the left side will stay the same (the w part of W is going up).  If the increase in the wage is large enough to make the right side larger than the left side the firm will switch from a cashier to a touch screen. Suppose that an increase from $9 to $15 does induce a switch to touch screen devices in California McDonald’s restaurants. Can this impact McDonald’s restaurants in areas where the minimum wage doesn’t increase? In theory yes.

Once some McDonald’s restaurants make the switch the costs for other McDonald’s to switch will be lower. The reason for this is that the McDonald’s that switch later will not have to pay the D or K costs; the development or kinks/trial run/adjustment costs. Once the technology is developed and perfected the late-adopting McDonald’s can just copy what has already been done. So after the McDonald’s restaurants in high wage areas install and perfect touch screen devices for ordering, the other McDonald’s face the decision of

I + R < W

This means that it may make sense to adopt the technology once it has been developed and perfected even if the wage in the lower wage areas does not change. In this scenario the left side decreases as D and K go to 0 while the right side stays the same. In fact, one could argue that the R will decline for late-adopting restaurants as well since the maintenance costs will decline over time as more technicians are trained and the reliability and performance of the software and hardware increase.

What this means is that a higher minimum wage in a state like California can lead to a decline in low-skill employment opportunities in places like Greenville, SC and Dayton, OH as the technology employed to offset the higher labor costs in the high minimum wage area spread to lower wage areas.

Also, firm owners and operators live in the real world. They see other state and local governments raising their minimum wage and they start to think that it could happen in their area too. This also gives them an incentive to switch since in expectation labor costs are going up. If additional states make the same bad policy choice as California, firm owners around the country may start to think that resistance is futile and that it’s best to adapt in advance by preemptively switching to more capital.

And if you think that touch screen ordering machines aren’t a good example, here is a link to an article about an automated burger-making machine. The company that created it plans on starting a chain of restaurants that use the machine. Once all of the bugs are worked out how high does the minimum wage need to be before other companies license the technology or create their own by copying what has already been done?

This is one more way that a higher minimum wage negatively impacts low-skill workers; even if workers don’t live in an area that has a relatively high minimum wage, the spread of technology may eliminate their jobs as well.

A $15 minimum wage will excessively harm California’s poorest counties

Lawmakers in California are thinking about increasing the state minimum wage to $15 per hour by 2022. If it occurs it will be the latest in a series of increases in the minimum wage across the country, both at the city and state level.

Increases in the minimum wage make it difficult for low-skill workers to find employment since the mandated wage is often higher than the value many of these workers can provide to their employers. Companies won’t stay in business long if they are forced to pay a worker $15 per hour who only produces $12 worth of goods and services per hour. Statewide increases may harm the job prospects of low-skill workers more than citywide increases since they aren’t adjusted to local labor market conditions.

California is a huge state, covering nearly 164,000 square miles, and contains 58 counties and 482 municipalities. Each of these counties and cities has their own local labor market that is based on local conditions. A statewide minimum wage ignores these local conditions and imposes the same mandated price floor on employers and workers across the state. In areas with low wages in general, a $15 minimum wage may affect nearly every worker, while in areas with high wages the adverse effects of a $15 minimum wage will be moderated. As explained in the NY Times:

“San Francisco and San Jose, both high-wage cities that have benefited from the tech boom, are likely to weather the increase without so much as a ripple. The negative consequences of the minimum wage increase in Los Angeles and San Diego — large cities where wages are lower — are likely to be more pronounced, though they could remain modest on balance.

But in lower-wage, inland cities like Bakersfield and Fresno, the effects could play out in much less predictable ways. That’s because the rise of the minimum wage to $15 over the next six years would push the wage floor much closer to the expected pay for a worker in the middle of the wage scale, affecting a much higher proportion of employees and employers there than in high-wage cities.”

To put some numbers to this idea, I used BLS weekly wage data from Dec. of 2014 to create a ratio for each of California’s counties that consists of the weekly wage of a $15 per hour job (40 x $15 = $600) divided by the average weekly wage of each county. The three counties with the lowest ratio and the three counties with the highest ratio are in the table below, with the ratio depicted as a percentage in the 4th column.

CA county weekly min wage ratio

The counties with the lowest ratios are San Mateo, Santa Clara, and San Francisco County. These are all high-wage counties located on the coast and contain the cities of San Jose and San Francisco. As an example, a $600 weekly wage is equal to 27.7% of the average weekly wage in San Mateo County.

The three counties with the highest ratios are Trinity, Lake, and Mariposa County. These are more rural counties that are located inland. Trinity and Lake are north of San Francisco while Mariposa County is located to the east of San Francisco. In Mariposa County, a $600 weekly wage would be equal to 92.6% of the avg. weekly wage in that county as Dec. 2014. The data shown in the table reveal the vastly different local labor market conditions that exist in California.

The price of non-tradeable goods like restaurant meals, haircuts, automotive repair, etc. are largely based on local land and labor costs and the willingness to pay of the local population. For example, a nice restaurant in San Francisco can charge $95 for a steak because the residents of San Francisco have a high willingness to pay for such meals as a result of their high incomes.

Selling a luxury product like a high-quality steak also makes it relatively easier to absorb a cost increase that comes from a higher minimum wage; restaurant workers are already making relatively more in wealthier areas and passing along the cost increase in the form of higher prices will have a small effect on sales if consumers of steak aren’t very sensitive to price.

But in Mariposa County, where the avg. weekly wage is only $648, a restaurant would have a hard time attracting customers if they charged similar prices. A diner in Mariposa County that sells hamburgers is probably not paying its workers much more than the minimum wage, so an increase to $15 per hour is going to drastically affect the owner’s costs. Additionally, consumers of hamburgers may be more price-sensitive than consumers of steak, making it more difficult to pass along cost increases.

Yet despite these differences, both the 5-star steakhouse in San Francisco and the mom-and-pop diner in Mariposa County are going to be bound by the same minimum wage if California passes this law.

In the table below I calculate what the minimum wage would have to be in San Mateo, Santa Clara, and San Francisco County to be on par with a $15 minimum in Mariposa County.

CA comparable min wage

If the minimum wage was 92.6% of the average wage in San Mateo it would be equal to $50.14. Using the ratio from a more developed but still lower-wage area – Kern County, where Bakersfield is located – the minimum wage would need to be $37.20 in San Mateo. Does anyone really believe that a $50 or $37 minimum wage in San Mateo wouldn’t cause a drastic decline in employment or a large increase in prices in that county?

If California’s lawmakers insist on implementing a minimum wage increase they should adjust it so that it doesn’t disproportionately affect workers in poorer, rural areas. But of course this is unlikely to happen; I doubt that the voters of San Mateo, Santa Clara, and San Francisco County will be as accepting of a $37 + minimum wage as they are of a $15 minimum wage that won’t directly affect many of them.

A minimum wage of any amount is going to harm some workers by preventing them from getting a job. But a minimum wage that ignores local labor market conditions will cause relatively more damage in poorer areas that are already struggling, and policy makers who ignore this reality are excessively harming the workers in these areas.

Where’s the growth?

In a famous Wendy’s commercial from 1984, three elderly women are examining a hamburger with a rather large bun when one of them asks “Where’s the beef?” in order to express her disappointment that the burger is all bun and no meat. When it comes to the economy growth is like the beef of a burger – without it all you’re left with is fluff and filler.

For the last 8 years the US economy has been mostly fluff and filler. Sure unemployment is down, but that is largely due to a lower labor force participation rate. Wage growth has been anemic and total GDP growth remains below the pre-recession long-run average of 3%.  GDP per capita growth is weak too.

Within a country as large as the US different regions are going to have different levels of GDP per capita and different growth rates for a variety of reasons including labor force characteristics, industry composition, weather, and geography. In order to examine the differences across the US, the graph below depicts the natural log of real GDP per capita in 2009 dollars for the 9 census divisions from 2001 to 2014. Because the natural log is on the y-axis the slope of the line corresponds to the growth rate between years. The black line is the US Metropolitan Area average and does not include rural areas.

ln real per cap gdp by cen div 2001-14

I created the census division average by generating a population weighted average of the real per capita GDP of the Metropolitan Statistical Areas located in each division. The weights are adjusted for each year in the data. Also, since the averages discussed in this post do not include rural areas one can think of them as the urban average in each census division. The population data for the weights and the real GDP per capita data are from the BEA.

As shown in the graph, the highest average real GDP per capita is in the New England division (orange) while the lowest is in the East South Central (purple), although as of 2014 the Mountain is not far ahead.

The slopes of the lines are steeper on average prior to the recession, indicating that the regions were growing faster during the pre-recession period. This is particularly noticeable in the Mountain and South Atlantic division, where real GDP per capita growth has essentially been zero (flat line) since 2009. Growth has also slowed considerably in the Pacific division (dark blue). Only in the East North Central (yellow) and West South Central (brown) does it appear that growth has reached or eclipsed its pre-recession rate.

The next graph below shows the average real per capita GDP by census division in three separate years – 2001, 2007, and 2014. This makes it easier to see the changes in levels over time.

real per cap gdp by cen div 2001,07,14

Real GDP per capita was higher in 2014 than in 2007 (year prior to the recession) in only three divisions – the Mid Atlantic, West North Central, and West South Central. The rest of the country has experienced either no gain or a decrease in the case of the South Atlantic and Mountain divisions. Together these graphs are hardly evidence of a strong economy.

High per capita GDP is not a perfect measure of economic prosperity but it is strongly correlated with many of the other things people care about. Countries with a higher level of per capita GDP are healthier, freer, and happier. The data presented here show that the US economy is struggling when it comes to growth, especially in the South Atlantic and Mountain divisions where people have become worse off on average. Whoever the next president is, he or she needs to come up with an answer to the question – Where’s the growth?


City population dynamics since 1850

The reason why some cities grow and some cities shrink is a heavily debated topic in economics, sociology, urban planning, and public administration. In truth, there is no single reason why a city declines. Often exogenous factors – new modes of transportation, increased globalization, institutional changes, and federal policies – initiate the decline while subsequent poor political management can exacerbate it. This post focuses on the population trends of America’s largest cities since 1850 and how changes in these factors affected the distribution of people within the US.

When water transportation, water power, and proximity to natural resources such as coal were the most important factors driving industrial productivity, businesses and people congregated in locations near major waterways for power and shipping purposes. The graph below shows the top 10 cities* by population in 1850 and follows them until 1900. The rank of the city is on the left axis.

top cities 1850-1900


* The 9th, 11th, and 12th ranked cities in 1850 were all incorporated into Philadelphia by 1860. Pittsburgh was the next highest ranked city (13th) that was not incorporated so I used it in the graph instead.

All of the largest cities were located on heavily traveled rivers (New Orleans, Cincinnati, Pittsburgh, and St. Louis) or on the coast and had busy ports (New York, Boston, Philadelphia, Brooklyn, and Baltimore). Albany, NY may seem like an outlier but it was the starting point of the Erie Canal.

As economist Ed Glaeser (2005) notes “…almost every large northern city in the US as of 1860 became an industrial powerhouse over the next 60 years as factories started in central locations where they could save transport costs and make use of large urban labor forces.”

Along with waterways, railroads were an important mode of transportation from 1850 – 1900 and many of these cities had important railroads running through them, such as the B&O through Balitmore and the Erie Railroad in New York. The increasing importance of railroads impacted the list of top 10 cities in 1900 as shown below.

top cities 1900-1950

A similar but not identical set of cities dominated the urban landscape over the next 50 years. By 1900, New Orleans, Brooklyn (merged with New York) Albany, and Pittsburgh were replaced by Chicago, Cleveland, Buffalo, and San Francisco. Chicago, Cleveland, and Buffalo are all located on the Great Lakes and thus had water access, but it was the increasing importance of railroad shipping and travel that helped their populations grow. Buffalo was on the B&O railroad and was also the terminal point of the Erie Canal. San Francisco became much more accessible after the completion of the Pacific Railroad in 1869, but the California Gold Rush in the late 1840s got its population growth started.

As rail and eventually automobile/truck transportation became more important during the early 1900s, cities that relied on strategic river locations began to decline. New Orleans was already out of the top 10 by 1900 (falling from 5th to 12th) and Cincinnati went from 10th in 1900 to 18th by 1950. Buffalo also fell out of the top 10 during this time period, declining from 8th to 15th. But despite some changes in the rankings, there was only one warm-weather city in the top 10 as late as 1950 (Los Angeles). However, as the next graphs shows there was a surge in the populations of warm-weather cities during the period from 1950 to 2010 that caused many of the older Midwestern cities to fall out of the rankings.

top cities 1950-2010

The largest shakeup in the population rankings occurred during this period. Out of the top 10 cities in 1950, only 4 (Philadelphia, Los Angeles, Chicago, and New York) were still in the top 10 in 2010 (All were in the top 5, with Houston – 4th in 2010 – being the only city not already ranked in the top 10 in 1950, when it was 14th). The cities ranked 6 – 10 fell out of the top 20 while Detroit declined from 5th to 18th. The large change in the rankings during this time period is striking when compared to the relative stability of the earlier time periods.

Economic changes due to globalization and the prevalence of right-to-work laws in the southern states, combined with preferences for warm weather and other factors have resulted in both population and economic decline in many major Midwestern and Northeastern cities. All of the new cities in the top ten in 2010 have relatively warm weather: Phoenix, San Antonio, San Diego, Dallas, and San Jose. Some large cities missing from the 2010 list – particularly San Francisco and perhaps Washington D.C. and Boston as well – would probably be ranked higher if not for restrictive land-use regulations that artificially increase housing prices and limit population growth. In those cities and other smaller cities – primarily located in Southern California – low population growth is a goal rather than a result of outside forces.

The only cold-weather cities that were in the top 15 in 2014 that were not in the top 5 in 1950 were Indianapolis, IN (14th) and Columbus, OH (15th). These two cities not only avoided the fate of nearby Detroit and Cleveland, they thrived. From 1950 to 2014 Columbus’ population grew by 122% and Indianapolis’ grew by 99%. This is striking compared to the 57% decline in Cleveland and the 63% decline in Detroit during the same time period.

So why have Columbus and Indianapolis grown since 1950 while every other large city in the Midwest has declined? There isn’t an obvious answer. One thing among many that both Columbus and Indianapolis have in common is that they are both state capitals. State spending as a percentage of Gross State Product (GSP) has been increasing since 1970 across the country as shown in the graph below.

OH, IN state spending as per GSP

In Ohio state spending growth as a percentage of GSP has outpaced the nation since 1970. It is possible that increased state spending in Ohio and Indiana is crowding out private investment in other parts of those states. And since much of the money collected by the state ends up being spent in the capital via government wages, both Columbus and Indianapolis grow relative to other cities in their respective states.

There has also been an increase in state level regulation over time. As state governments become larger players in the economy business leaders will find it more and more beneficial to be near state legislators and governors in order to lobby for regulations that help their company or for exemptions from rules that harm it. Company executives who fail to get a seat at the table when regulations are being drafted may find that their competitors have helped draft rules that put them at a competitive disadvantage. The decline of manufacturing in the Midwest may have created an urban reset that presented firms and workers with an opportunity to migrate to areas that have a relative abundance of an increasingly important factor of production – government.

Berkeley, CA and the $15 – oops – $19 living wage

Berkeley, CA’s labor commission – in what should be an unsurprising move at this point in Berkeley’s history – has proposed raising the city’s minimum wage to an astounding $19 per hour by 2020! The labor commission’s argument in a nutshell is that Berkeley is an expensive place to live so worker’s need more money. And while Berkeley may be an expensive place to live, mandating that employers pay a certain wage doesn’t necessarily mean that the workers will get that money. As one Berkeley restaurant owner noted:

“We can raise our prices. But you can’t charge $25 for a sandwich,” said Dorothee Mitrani, who owns La Note. “A lot of mom-and-pop delis and cafes may disappear.”

The article states that Ms. Mitrani’s

…. full-service restaurant now subsidizes her take-out shop, which she said is running in the red as a result of the increases already in place. If the minimum rose to $19, she expects she would have to shut it down.

Of course, there are some politicians – and unfortunately some economists – who insist that raising the minimum wage doesn’t have adverse effects on employment, despite sound theoretical reasoning and empirical evidence to the contrary. My Mercatus center colleague Don Boudreaux has compiled an extensive collection of blog posts at Café Hayek debunking and refuting every pro-minimum wage argument out there, and I encourage interested readers to check them out.

The minimum wage most adversely effects low-skill, inexperienced workers, such as those without a high school degree, below the poverty level, between the ages of 16 – 19, and with some type of disability. So how do the people who fit into those categories currently fare in Berkeley’s labor market?

The table below shows the labor force rate and percentage employed for people 16 and over in each of those categories in the city of Berkeley in 2013 and 2014. The data is from the ACS 1-year survey. (American FactFinder table S2301)

berkely min wage employment 2013-14

As the table shows the labor force rate and the employment rate for each of those categories is already low compared to the overall labor force rate in Berkeley of 67% and employment rate of 62%. From 2013 to 2014 both the labor force rate and the employment rate declined for people without a high school degree, while the employment rate increased in the other categories. Nothing in this table leads me to believe that it would be a good idea to make the workers in these categories more expensive to hire, as it seems it is already difficult for them to find employment and it’s getting more difficult for some.

The table below compares Berkeley to the surrounding San Francisco MSA using only 2014 data.

berkeley min wage emp vs SF MSA

This table reveals that compared to the surrounding area, workers in these categories fare worse in Berkeley. The percentage of people with less than a high school degree who are employed was 11 percentage points lower in Berkeley, while the percentage with a disability was 0.8 points lower and the percentage below the poverty level was 1.5 points lower. Out of the four categories only 16 – 19 year olds had a better chance of being employed in Berkeley than in the surrounding MSA.

Hopefully Berkeley’s city council reviews the labor market reality in their city and thinks about actual consequences vs. intentions before deciding to increase the price that low-skill workers are allowed to charge for their labor. It’s already difficult for low-skill, inexperienced workers to find a job in Berkeley and making it harder won’t help them.

Puerto Rico’s labor market woes

Puerto Rico – a U.S. territory – has $72 billion dollars in outstanding debt, which is dangerously high in a country with a Gross Domestic Product (GDP) of only $103.1 billion. The Puerto Rican government failed to pay creditors in August and this was viewed as a default by the credit rating agency Moody’s, which had already downgraded Puerto Rico’s bonds to junk status earlier this year. The Obama administration has proposed allowing Puerto Rico to declare bankruptcy, which would allow it to negotiate with creditors and eliminate some of its debt. Currently only municipalities – not states or territories – are allowed to declare bankruptcy under U.S. law. Several former Obama administration officials have come out in favor of the plan, including former Budget Director Peter Orszag and former Director of the National Economic Council Larry Summers. Others are warning that bankruptcy is not a cure-all and that more structural reforms need to take place. Many of these pundits have pointed out that Puerto Rico’s labor market is a mess and that people are leaving the country in droves. Since 2010 over 200,000 people have migrated from Puerto Rico, decreasing its population to just over 3.5 million. This steady loss of the tax base has increased the debt burden on those remaining and has made it harder for Puerto Rico to get out of debt.

To get a sense of Puerto Rico’s situation, the figure below shows the poverty rate of Puerto Rico along with that of three US states that will be used throughout this post as a means of comparison: California (wealthy state), Ohio (medium-wealth state), and Mississippi (low-wealth state). All the data are 1-year ACS data from American FactFinder.

puerto rico poverty

The poverty rate in Puerto Rico is very high compared to these states. Mississippi’s poverty rate is high by US standards and was approximately 22% in 2014, but Puerto Rico’s dwarfed it at over 45%. Assisting Puerto Rico with their immediate debt problem will do little to fix this issue.

A government requires taxes in order to provide services, and taxes are primarily collected from people who work in the regular economy via income taxes. A small labor force with relatively few employed workers makes it difficult for a county to raises taxes to provide services and pay off debt. Puerto Rico has a very low labor force participation (LFP) rate relative to mainland US states and a very low employment rate. The graphs below plot Puerto Rico’s LFP rate and employment rate along with the rates of California, Mississippi, and Ohio.

puerto rico labor force

puerto rico employ rate

As shown in the figures, Puerto Rico’s employment rate and LFP rate are far below the rates of the US states including one of the poorest states, Mississippi. In 2014 less than 45% of Puerto Rico’s 16 and over population was in the labor force and only about 35% of the 16 and over population was employed. In Mississippi the LFP rate was 58% while the employment rate was 52%. Additionally, the employment rate fell in Puerto Rico from 2010-14 while it rose in each of the other three states. So at a time when the labor market was improving on the mainland things were getting worse in Puerto Rico.

An educated labor force is an important input in the production process and it is especially important for generating innovation and entrepreneurship. The figure below shows the percent of people 25 and over in each area that have a bachelor’s degree or higher.

puerto rico gt 24 education attain

Puerto Rico has a relatively educated labor force compared to Mississippi, though it trails Ohio and California. The percentage also increased over this time period, though it appears to have stabilized after 2012 while continuing to grow in the other states.

Puerto Rico has nice beaches and weather, so a high percentage of educated people over the age of 25 may simply be due to a high percentage of educated retirees residing in Puerto Rico to take advantage of its geographic amenities. The next figure shows the percentage of 25 to 44 year olds with a bachelor’s degree or higher. I examined this age group to see if the somewhat surprising percentage of people with a bachelor’s degree or higher in Puerto Rico is being driven by educated older workers and retirees who are less likely to help reinvigorate the Puerto Rican economy going forward.

puerto rico 25to44 educ attain

As shown in the graph, Puerto Rico actually fares better when looking at the 25 – 44 age group, especially from 2010-12. In 2012 Puerto Rico had a higher percentage of educated people in this age group than Ohio.

Since then, however, Puerto Rico’s percentage declined slightly while Ohio’s rose, along with Mississippi’s and California’s. The decline in Puerto Rico was driven by a decline in the percentage of people 35 to 44 with a bachelor’s or higher as shown in the next figure below.

puerto rico 35to44 educ attain

The percentage of 35 to 44 year olds with a bachelor’s or advanced degree fell from 32% in 2012 to 29.4% in 2014 while it rose in the other three states. This is evidence that educated people in their prime earning years left the territory during this period, most likely to work in the US where there are more opportunities and wages are higher. This “bright flight” is a bad sign for Puerto Rico’s economy.

One of the reforms that many believe will help Puerto Rico is an exemption from compliance with federal minimum wage laws. Workers in Puerto Rico are far less productive than in the US, and thus a $7.25 minimum wage has a large effect on employment. Businesses cannot afford to pay low-skill workers in Puerto Rico such a high wage because the workers simply do not produce enough value to justify it. The graph below shows the median individual yearly income in each area divided by the full time federal minimum wage income of $15,080.

puerto rico min wage ratio

As shown in the graph, Puerto Rico’s ratio was the highest by a substantial amount. The yearly income from earning the minimum wage was about 80% of the yearly median income in Puerto Rico over this period, while it was only about 40% in Mississippi and less in Ohio and California. By this measure, California’s minimum wage would need to be $23.82 – which is equal to $49,546 per year – to equal the ratio in Puerto Rico. California’s actual minimum wage is $9 and it’s scheduled to increase to $10 in 2016. I don’t think there’s a single economist who would argue that more than doubling the minimum wage in California would have no effect on employment.

The preceding figures do not paint a rosy picture of Puerto Rico: Its poverty rate is high and trending up, less than half of the people over 16 are in the labor force and only about a third are actually employed, educated people appear to be leaving the country, and the minimum wage is a severe hindrance on hiring. Any effort by the federal government to help Puerto Rico needs to take these problems into account. Ultimately the Puerto Rican government needs to be enabled and encouraged to institute reforms that will help grow Puerto Rico’s economy. Without fundamental reforms that increase economic opportunity in Puerto Rico people will continue to leave, further weakening the commonwealth’s economy and making additional defaults more likely.



Teenage unemployment in cities

New research that examines New York’s Summer Youth Employment Program (SYEP) finds that participation in the program positively impacts student academic outcomes. As the authors state in the introduction, youth employment has many benefits:

“Prior research suggests that adolescent employment improves net worth and financial well-being as an adult. An emerging body of research indicates that summer employment programs also lead to decreases in violence and crime. Work experience may also benefit youth, and high school students specifically, by fostering various non-cognitive skills, such as positive work habits, time management, perseverance, and self-confidence.” (My bold)

This is hardly surprising news to anyone who had a summer job when they were young. An additional benefit from youth employment not mentioned by the authors is that the low-skill, low-paying jobs held by young people also provide them with information about what they don’t want to do when they grow up. Working in a fast food restaurant or at the counter of a store in the local mall helps a young person appreciate how hard it is to earn a dollar and provides a tangible reason to gain more skills in order to increase one’s productivity and earn a higher wage.

Unfortunately, many young people today are not obtaining these benefits. The chart below depicts the national teenage unemployment rate and labor force participation rate (LFP) from 2005 to 2015 using year-over-year August data from the BLS.

national teen unemp, LFP

During the Great Recession teenage employment fell drastically, as indicated by the simultaneous increase in the unemployment rate and decline in the LFP rate from 2007 to 2009. From its peak in 2010, the unemployment rate for 16 to 19 year olds declined slowly until 2012. This decline in the unemployment rate coincided with a decline in the LFP rate and thus the latter was partly responsible for the former’s decline. More recently, the labor force participation rate has flattened out while the unemployment rate has continued to decline, which means that more teenagers are finding jobs. But the teenagers who are employed are part of a much smaller labor pool than 10 years ago – nationally, only 33.7% of 16 to 19 year olds were in the labor force in August 2015, a sharp decline from 44% in 2005.

Full-time teenage employment is unique in that it has a relatively high opportunity cost – attending school full time. Out of the teenagers who work at least some portion of the year, most only work during the summer when school is not in session. Some teenagers also work during the school year, but this subset of teenage workers is smaller than the set who are employed during the summer months. Thus a decline in the LFP rate for teenagers may be a good thing if the teenagers who are exiting the labor force are doing so to concentrate on developing their human capital.

Unfortunately this does not seem to be the case. From 2005 to 2013 the enrollment rate of 16 and 17 year olds actually declined slightly from 95.1% to 93.7%.  The enrollment rate for 18 and 19 year olds stayed relatively constant – 67.6% in 2005 and 67.1% in 2013, with some mild fluctuations in between. These enrollment numbers coupled with the large decline in the teenage LFP rate do not support the story that a large number of working teenagers are exiting the labor force in order to attend school full time. Of course, they do not undermine the story that an increasing amount of teenagers who are both in the labor force and attending school at the same time are choosing to exit the labor force in order to focus on school. But if that is the primary reason, why is it happening now?

Examining national data is useful for identifying broad trends in teenage unemployment, but it conceals substantial intra-national differences. For this reason I examined teenage employment in 10 large U.S. cities (political cities, not MSAs) using employment status data from the 5-year American Community Survey (ACS Table S2301. 2012 was the latest data available for all ten cities).

The first figure below depicts the age 16 – 19 LFP rate for the period 2010 – 2012. As shown in the diagram there are substantial differences across cities.

City teenage LFP

For example, in New York (dark blue) only 23% of the 16 – 19 population was in the labor force in 2012 – down from 25% in 2010 – while in Denver 43.5% of the 16 – 19 population was in the labor force. Nearly every city experienced a decline over this time period, with only Atlanta (red line) experiencing a slight increase. Five cities were below the August 2012 national rate of 34% – Chicago, Philadelphia, Atlanta, San Francisco, and New York.

Also, in contrast to the improving unemployment rate at the national level from 2010 – 12 shown in figure 1, the unemployment rate in each of these cities increased during that period. Figure 3 below depicts the unemployment rate for each of the 10 cities.

City teenage unemp rate

In August 2012 the national unemployment rate for 16 – 19 year olds was 24.3%, a rate that was exceeded by all 10 cities analyzed here. Atlanta had the highest unemployment rate in 2012 at 48%. Atlanta’s high unemployment rate and relatively low LFP rate reveals how few Atlanta teens were employed during this period and how difficult it was for those who wanted a job to find one.

The unemployment rate may increase because employment declines or more unemployed people enter the labor force, which would increase the labor force participation rate. Figures 2 and 3 together indicate that the unemployment rate increased in each of these cities due to a decline in employment, not increased labor force participation.

The preceding figures are evidence that the teenage employment situation in these major cities is getting worse both over time and relative to other areas in the country. To the extent that teenage employment benefits young people, fewer and fewer of them are receiving these benefits. From the linked article:

“The substantial drop in teen employment prospects has had a devastating effect on the nation’s youngest teens (16-17), males, blacks, low income youth, and inner city, minority males,” wrote Andrew Sum in a report on teen summer employment for the Center for Labor Market Studies at Northeastern University. “Those youth who need work experience the most get it the least, another example of the upside down world of labor markets in the past decade.”

Unfortunately, in many cities the response to this situation will only exacerbate the problem. Seattle and Los Angeles have already approved local $15 minimum wages, and a similar law in the state of New York that applies only to fast food franchises was recently approved by the state’s wage board. While many people still question the effect of a minimum wage on overall employment, there is substantial empirical evidence that a relatively high minimum wage has a negative effect on employment for the least skilled workers, which includes inner-city teenagers who often attend mediocre schools. Thus it is hard to believe that any of the seemingly well-intentioned increases in the minimum wage that are occurring around the country will have a positive effect on the urban teenage employment situation presented here. A better response would be to eliminate the minimum wage so that in the short run low-skilled workers are able to offer their labor at a price that is commensurate to its value. In the long run worker productivity must be increased which involves K-12 school reform.

Post-Katrina HUD funding has underwhelmed in Gulfport

Hurricane Katrina made landfall 10 years ago and devastated much of the gulf coast. In the immediate aftermath of the storm, both public and private aid flooded into the effected areas. Not all of this aid was effective, and my colleagues at the Mercatus Center have meticulously analyzed what worked, what didn’t, and how the region was largely able to get back on its feet.

One project that is still being scrutinized is the Port of Gulfport Restoration Program. In 2007 the Mississippi Development Authority (MDA) requested that $567 million of federal Housing and Urban Development (HUD) funds be diverted to the newly created Port of Gulfport Restoration Program. Prior to Katrina there were 2,058 direct maritime jobs at the port, and the 2007 plan submitted to HUD projected that there would be 5,400 direct, indirect, and induced jobs once the restoration project was complete in 2015. In return for the money the administrators promised HUD that at least 1,300 jobs would be created, and HUD Secretary Julian Castro was recently in Gulfport to check on the progress that has been made. As is typical with HUD projects, the actual progress on the ground has not lived up to the hype.

In September of 2014, nine years after Katrina, the port employed only 814 people. This was well short of even the 2,348 jobs predicted by 2010 in the original 2007 plan. Ignoring the fact that jobs are a poor metric for judging economic development – labor is a cost, not a benefit – the project has failed to live up to the promise made to federal taxpayers who are footing the bill.

HUD funding has a long history of failure. Billions of HUD money has poured into cities such as Detroit and Cleveland since the 1970s with little to show for it. Moreover, any successful HUD story is really just the result of transferring economic activity from one place to another. The $570 million being spent in Gulfport came from taxpayers all over the country who could have spent that money on other things. Moving all of that money to Gulfport caused small declines in economic activity all over the country, such as less investment in local businesses and/or lower demand for local goods and services. These small declines are hard to see relative to the big splash that $570 million in spending creates, but they are real and they do affect people.

Large, federal spending projects rarely live up to their hype and usually waste resources. Local citizens using local assets are often much more effective at revitalizing devastated communities. There are lessons to be learned from Hurricane Katrina, and at the top of the list is don’t expect too much from federally funded programs – they are usually not up to the challenge.