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 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.

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.

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.

Exit, voice, and loyalty in cities

March 18, 2016

Economist Albert Hirschman’s 1970 book Exit, Voice, and Loyalty: Responses to Decline in Firms, Organizations, and States presents a theory of how consumers express their dissatisfaction to firms and other organizations after a decline in product or service quality. In terms of interjurisdictional competition exit is demonstrated by migration: dissatisfied residents migrate to a community […]

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Where’s the growth?

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Economic freedom matters at the local level too

February 18, 2016

Since 1996 the Fraser Institute has published an annual economic freedom of the world index that ranks countries according to their level of economic freedom. They also publish an economic freedom of North America Index that ranks the US states, Canadian provinces, and Mexican provinces using similar data. Both of these studies have been used […]

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Ignoring the adverse effects of the minimum wage may cost taxpayers billions

February 4, 2016

Today the Obama administration issued a statement calling for a ‘First Job’ funding initiative to connect young Americans with jobs. The statement laments how difficult it is for young people to find employment and emphasizes how important a first jobs is for future career success: “After the worst economic crisis of our lifetimes, the United […]

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Saving for retirement is something most workers do – either on their own or through an employer – and most are aware that the rate of return on their retirement investment matters. For example, if I save $100 today and it earns 10% per year in interest for the next 20 years I will have […]

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City population dynamics since 1850

January 26, 2016

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 […]

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