Tag Archives: construction

The unseen costs of Amazon’s HQ2 Site Selection

Earlier this year Amazon narrowed down the list of potential cities to site its second headquarters. Applicants are now waiting out the selection process. It’s unclear when Amazon will make its choice, but that hasn’t stopped many from speculating who the likely contenders are. Varying sources report Atlanta, Boston, and Washington D.C. at the top of the list. The cities that didn’t make the cut are no doubt envious of the finalists, having just missed out on the potential for a $5 billion facility and 50,000 jobs. The second HQ is supposed to be as significant for economic growth as the company’s first site, which according to Amazon’s calculations contributed an additional $38 billion to Seattle’s economy between 2010 and 2016. There is clearly a lot to be gained by the winner.  But there are also many costs. Whichever city ends up winning the bid will be changed forever. What’s left out of the discussion is how the bidding process and corporate incentives affect the country.

Although the details of the proposals are not made public, each finalist is likely offering some combination of tax breaks, subsidies, and other incentives in return for the company’s choice to locate in their city. The very bidding process necessitates a lot of time and effort by many parties. It will certainly seem “worth it” to the winning party, but the losers aren’t getting back the time and effort they spent.

This practice of offering incentives for businesses has been employed by states and localities for decades, with increased usage over time. Targeted economic development incentives can take the form of tax exemptions, abatements, regulatory relief, and taxpayer assistance. They are but one explicit cost paid by states and cities looking to secure business, and there is a growing literature that suggests these policies are more costly than meets the eye.

First, there’s the issue of economic freedom. Recent Mercatus research suggests that there may be a tradeoff to offering economic development incentives like the ones that Amazon is receiving. Economists John Dove and Daniel Sutter find that states that spend more on targeted development incentives as a percentage of gross state product also have less overall economic freedom. The theoretical reasoning behind this is not very clear, but Dove and Sutter propose that it could be because state governments that use more subsidies or tax breaks to attract businesses will also spend more or raise taxes for everyone else in their state, resulting in less equitable treatment of their citizens and reducing overall economic freedom.

The authors define an area as having more economic freedom if it has lower levels of government spending, taxation, and labor market restrictions. They use the Fraser Institute’s Economic Freedom of North America Index (EFNA) to measure this. Of the three areas within the EFNA index, labor market freedom is the most affected by targeted economic development incentives. This means that labor market regulation such as the minimum wage, government employment, and union density are all significantly related to the use of targeted incentives.

Economic freedom can be ambiguous, however, and it’s sometimes hard to really grasp its impact on our lives. It sounds nice in theory, but because of its vagueness, it may not seem as appealing as a tangible economic development incentive package and the corresponding business attached to it. Economic freedom is associated with a series of other, more tangible benefits, including higher levels of income and faster economic growth. There’s also evidence that greater economic freedom is associated with urban development.

Not only is the practice of offering targeted incentives associated with lower economic freedom, but it is also indicative of other issues. Economists Peter Calcagno and Frank Hefner have found that states with budget issues, high tax and regulatory burdens, and poorly trained labor forces are also more likely to offer targeted incentives as a way to offset costly economic conditions. Or, in other words, targeted development incentives can be – and often are – used to compensate for a less than ideal business climate. Rather than reform preexisting fiscal or regulatory issues within a state, the status quo and the use of targeted incentives is the more politically feasible option.

Perhaps the most concerning aspect of Amazon’s bidding process is the effect it has on our culture. Ideally, economic development policy should be determined by healthy economic competition between states. In practice, it has evolved into more of an unhealthy interaction between private interests and political favor. Economists Joshua Jansa and Virginia Gray refer to this as cultural capture. They find increases in business political contributions to be positively correlated with state subsidy spending. Additionally, they express concern over the types of firms that these subsidies attract. There is a selection bias for targeted incentives to systematically favor “flighty firms” or firms that will simply relocate if better subsidies are offered by another state, or potentially threaten to leave in an effort to extract more subsidies.

None of these concerns even address the question of whether targeted incentives actually achieve their intended goals.  The evidence does not look good. In a review of the literature by my colleague Matthew Mitchell, and me, we found that of the studies that evaluate the effect of targeted incentives on the broader economy, only one study found a positive effect, whereas four studies found unanimously negative effects. Thirteen studies (half of the sample) found no statistically significant effect, and the remaining papers found mixed results in which some companies or industries won, but at the expense of others.

In addition to these unseen costs on the economy, some critics are beginning to question whether being chosen by Amazon is even worth it. Amazon’s first headquarters has been considered a catalyst for the city’s tech industry, but local government and business leaders have raised concerns about other possibly related issues such as gentrification, rising housing prices, and persistent construction and traffic congestion. There is less research on this, but it is worth considering.

It is up to each city’s policymakers to decide whether these trade-offs are worth it. I would argue, however, that much of the evidence points to targeted incentives – like the ones that cities are using to attract Amazon’s business – as having more costs than benefits. Targeted economic development incentives may seem to offer a lot of tangible benefits, but their unseen costs should not be overlooked. From the perspective of how they benefit each state’s economy as a whole, targeted incentives are detrimental to economic freedom as well as our culture surrounding corporate handouts. Last but not least, they may often be an attempt to cover up other issues that are unattractive to businesses.

State tax refunds and limiting spending growth

This fall eligible Alaskans will be receiving a check of $1,100 from their state government. Although the amount of the check can vary, Alaskans receive one every fall – no strings attached. Other state residents are probably more familiar with IRS tax refunds that come every spring, but this “tax refund” that Alaskans receive is unique. It’s a feature that residents have benefited from for decades, even in times when the government has experienced fiscal stress. Considering the state’s unique and distressed budget situation that I’ve described in an earlier post, I think it warrants a discussion of the fiscal viability of their refunds.

A narrow tax base reliant on volatile revenue sources, restricted funds, and growing spending are all factors that made closing Alaska’s budget gap this year very difficult. It even contributed to pulling down Alaska from 1st in our 2016 ranking of states by fiscal condition to 17th in our 2017 edition. Given this deterioration, it will be helpful to look into how and why Alaska residents receive dividend payments each year. There is no public finance rule that says giving refunds to residents is fiscally irresponsible, but there definitely are better ways to do it, and Alaska certainly hasn’t proven to display best practices.

Another state that we can look at for comparison is Colorado, which has a similar “tax refund” for residents but is structured very differently. Colorado’s Taxpayer Bill of Rights (TABOR) requires that higher than expected tax revenues each year be refunded to taxpayers and acts as a restraint on government spending growth. In contrast, Alaska’s check comes from the state’s Permanent Fund’s earnings that are generated from oil severance taxes each year, and acts more like a dividend from oil investment earnings.

Are distributing these refunds to taxpayers fiscally responsible? I am going to take a deeper look at these mechanisms to find out.

First, Alaska’s refund.

The figure below displays Alaska’s Permanent Fund checks since 2002 overlaid with the state’s revenue and expenditure trends, all adjusted for inflation. The highest check (in 2015 dollars) was $2,279 in 2008 and the lowest was $906 in 2012, with the average over this time period being about $1,497 per person. Although the check amounts do vary, Alaska has kept on top of delivering them, even in times of steep budget gaps like in 2002, 2009, and 2015. The Permanent Fund dividend formula is based on net income from the current plus the previous four fiscal years, so it makes sense that the check sizes are also cyclical in nature, albeit in a slightly delayed fashion behind oil revenue fluctuations.

Alaska’s dividend payments often end up on the chopping block during yearly budget debates, and there is growing pressure to at least have them reduced. Despite this, Alaska’s dividends are very popular with residents (who can blame them?) and probably won’t be going away for a long time; bringing a new meaning to the Permanent Fund’s name.

The Alaska Permanent Fund was established in 1976 by constitutional amendment and was seen as an investment in future generations, who might no longer have access to oil as a resource. Although this may have been decent forward-thinking, which is rare in state budgets, it does illustrate an interesting public finance story.

Alaska is a great example of a somewhat backwards situation. They generate high amounts of cash each year, but because of the way many of their funds are restricted they are forced to hoard much of it, and give the rest to citizens in the form of dividends. If a different state were to consider a similar dividend before dealing with serious structural budget flaws would be akin to putting the cart before the horse.

Luckily for Alaskan dividend recipients, there are many other areas that the state could reform first in order to improve their budget situation while avoiding cutting payments. As my colleague Adam Millsap has recommended, a fruitful area is tax reform. Alaska doesn’t have an income or sales tax; two of the most common sources of revenue for state governments. These are two potentially more stable sources of income than what the state currently has.

How does Colorado’s “tax refund” compare?

Colorado’s Taxpayer Bill of Rights (TABOR) has a feature that requires any tax revenue growth beyond inflation and population growth be refunded to taxpayers. It was adopted by Colorado voters in 1992 and it essentially restricts revenues by prohibiting any tax or spending increases without voter approval.

A recent example of this playing out was in 2014 when the state realized higher than expected tax revenues as a result of marijuana legalization. At the point of legalization, the plan was to direct tax revenues generated from the sale of marijuana towards schools or substance abuse program funding. But because of the higher than expected revenues, TABOR was triggered and it would require voter approval to decide if the excess revenues would be sent back to taxpayers or directed to other state programs.

In November of 2015, Colorado voters approved a statewide ballot measure that gave state lawmakers permission to spend $66.1 million in taxes collected from the sale of marijuana. The first $40 million was sent to school construction, the next $12 million to youth and substance abuse programs, and the remainder $14.2 billion to discretionary spending programs. A great example that although TABOR does generally restrain spending, citizens still have power to decline refunds in the name of program spending they are passionate about.

 

The second figure here displays TABOR refunds compared with state revenues and expenditures over time. Adjusted for inflation, checks have varied from $18 in 2005 to $351 in 1999, much smaller than the Alaska dividend checks. TABOR checks have only tended to be distributed when revenues have exceeded expenses. The main reason why checks weren’t distributed between 2006 and 2009, despite a revenue surplus, was because of Referendum C which removed TABOR’s revenue limit for five years, allowing the state to keep collections exceeding the rule. The revenue limit has since been reinstated, but some question the effectiveness of TABOR given an earlier amendment in 2000 which exempts much of education spending from TABOR restrictions.

The main distinguishing factor between Colorado’s refund and Alaska’s Permanent Fund dividend is that the former also acts as a constraint on spending growth. By requiring the legislature to get voter approval before any tax increase or spending of new money, it implements automatic checks on these activities. Many states attempt to do this through what are called “Tax and Expenditure Limits” or TELs.

The worry is that left unchecked, state spending can grow to unsustainable levels.

Tax and Expenditure Limits

A review of the literature up to 2012 found that although the earliest studies were largely skeptical of the effectiveness of TELs, as time has passed more research points to the contrary. TELs can restrain spending, but only in certain circumstances.

My colleague Matt Mitchell found in 2010 that TELs are more effective when they (1) bind spending rather than revenue, (2) require a super-majority rather than a simple majority vote to be overridden, (3) immediately refund revenue collected in excess of the limit, and (4) prohibit unfunded mandates on local government.

Applying these criteria to Colorado’s TABOR we see that it does well in some areas and could improve in others. TABOR’s biggest strength is that it immediately refunds revenue collected in excess of the limit in its formula, pending voter approval to do otherwise. Automatically refunding surpluses makes it difficult for governments to use excess funds irresponsibly and also gives taxpayers an incentive to support TABOR.

Colorado’s TABOR does well to limit revenue growth according to a formula, rather than to a fixed number or no limitation at all. The formula partially meets Mitchell’s standards. It stands up well with the most stringent TELs by limiting government growth that exceeds inflation and population growth, but could actually be improved if it limited actual spending growth rather than focusing on tax revenue. When a TEL or similar law limits revenues, policymakers can respond by resorting to implementing more fees or borrowing. There’s some evidence of this occurring in Colorado, with fees becoming more popular as a way to raise revenue since TABOR’s passing. A spending-based TEL is more difficult to evade.

Despite its faults, Colorado’s TABOR structure appears to be doing better than attempts to constrain spending growth in other states. The National Conference of State Legislatures still considers it one of the strictest TELs in the nation. Other states, like Arkansas, could learn a lot from Colorado. A recent Mercatus study analyzes Arkansas’ Revenue Stabilization Law and suggests that it is missing a component similar to Colorado’s TABOR formula to refund excess revenues.

How much a state spends is ultimately up to its residents and legislature. Some states may have a preference for more spending than others, but given the tendency for government spending to grow towards an unsustainable direction, having a conversation about how to slow this is key. Implementing TEL-like checks allows for spending to be monitored and that tax dollars be spent more strategically.

Alaska’s Permanent Fund dividend is not structured as well as Colorado’s, but perhaps the state’s saving grace is that it has a relatively well structured TEL. Similarly to Colorado’s TABOR, Alaska’s TEL limits budget growth to the sum of inflation and population growth and is codified in the constitution. Alaska’s TEL doesn’t immediately refund revenue that is collected in excess of the limit to taxpayers as Colorado’s TABOR does, but it does target spending rather than revenues.

Colorado’s and Alaska’s TELs can compete when it comes to restraining spending, but Colorado’s is certainly more strict. Colorado’s expenditures have grown by about 55 percent over the last decade, while Alaska’s has grown approximately 120 percent.

The Lesson

Comparing Colorado and Alaska’s situations reveals two different ways of giving tax refunds to residents. Doing so doesn’t necessarily have to be fiscally irresponsible. Colorado has provided refunds to residents when state revenues have exceeded expenses and as a result this has acted as a restraint on over-spending higher than expected revenues. Although Colorado’s TABOR has been amended over time, its general structure illustrates the effectiveness of institutional restrains on spending. The unintended effects of TABOR, such as the increase in fees, could be well addressed by specifically targeting spending rather revenue, like in the case of Alaska’s TEL. Alaska may have had their future residents’ best intent in mind when they designed their Permanent Fund Dividend, but perhaps this goal of passing forward oil investment earnings should have been paired with preparing for the potential of cyclical budget woes.

Why the lack of labor mobility in the U.S. is a problem and how we can fix it

Many researchers have found evidence that mobility in the U.S. is declining. More specifically, it doesn’t appear that people move from places with weaker economies to places with stronger economies as consistently as they did in the past. Two sets of figures from a paper by Peter Ganong and Daniel Shoag succinctly show this decline over time.

The first, shown below, has log income per capita by state on the x-axis for two different years, 1940 (left) and 1990 (right). On the vertical axis of each graph is the annual population growth rate by state for two periods, 1940 – 1960 (left) and 1990 – 2010 (right).

directed migration ganong, shoag

In the 1940 – 1960 period, the graph depicts a strong positive relationship: States with higher per capita incomes in 1940 experienced more population growth over the next 20 years than states with lower per capita incomes. This relationship disappears and actually reverses in the 1990 – 2010 period: States with higher per capita incomes actually grew slower on average. So in general people became less likely to move to states with higher incomes between the middle and end of the 20th century. Other researchers have also found that people are not moving to areas with better economies.

This had an effect on income convergence, as shown in the next set of figures. In the 1940 – 1960 period (left), states with higher per capita incomes experienced less income growth than states with lower per capita incomes, as shown by the negative relationship. This negative relationship existed in the 1990 – 2010 period as well, but it was much weaker.

income convergence ganong, shoag

We would expect income convergence when workers leave low income states for high income states, since that increases the labor supply in high-income states and pushes down wages. Meanwhile, the labor supply decreases in low-income states which increases wages. Overall, this leads to per capita incomes converging across states.

Why labor mobility matters

As law professor David Schleicher points out in a recent paper, the current lack of labor mobility can reduce the ability of the federal government to manage the U.S. economy. In the U.S. we have a common currency—every state uses the U.S. dollar. This means that if a state is hit by an economic shock, e.g. low energy prices harm Texas, Alaska and North Dakota but help other states, that state’s currency cannot adjust to cushion the blow.

For example, if the UK goes into a recession, the Bank of England can print more money so that the pound will depreciate relative to other currencies, making goods produced in the UK relatively cheap. This will decrease the UK’s imports and increase economic activity and exports, which will help it emerge from the recession. If the U.S. as a whole suffered a negative economic shock, a similar process would take place.

However, within a country this adjustment mechanism is unavailable: Texas can’t devalue its dollar relative to Ohio’s dollar. There is no within-country monetary policy that can help particular states or regions. Instead, the movement of capital and labor from weak areas to strong areas is the primary mechanism available for restoring full employment within the U.S. If capital and labor mobility are low it will take longer for the U.S. to recover from area-specific negative economic shocks.

State or area-specific economic shocks are more likely in large countries like the U.S. that have very diverse local economies. This makes labor and capital mobility more important in the U.S. than in smaller, less economically diverse countries such as Denmark or Switzerland, since those countries are less susceptible to area-specific economic shocks.

Why labor mobility is low

There is some consensus about policies that can increase labor mobility. Many people, including former President Barack Obama, my colleagues at the Mercatus Center and others, have pointed out that state occupational licensing makes it harder for workers in licensed professions to move across state borders. There is similar agreement that land-use regulations increase housing prices which makes it harder for people to move to areas with the strongest economies.

Reducing occupational licensing and land-use regulations would increase labor mobility, but actually doing these things is not easy. Occupational licensing and land-use regulations are controlled at the state and local level, so currently there is little that the federal government can do.

Moreover, as Mr. Schleicher points out in his paper, state and local governments created these regulations for a reason and it’s not clear that they have any incentive to change them. Like all politicians, state and local ones care about being re-elected and that means, at least to some extent, listening to their constituents. These residents usually value stability, so politicians who advocate too strongly for growth may find themselves out of office. Mr. Schleicher also notes that incumbent politicians often prefer a stable, immobile electorate because it means that the voters who elected them in the first place will be there next election cycle.

Occupational licensing and land-use regulations make it harder for people to enter thriving local economies, but other policies make it harder to leave areas with poor economies. Nearly 13% of Americans work for state and local governments and 92% of them have a defined-benefit pension plan. Defined-benefit plans have long vesting periods and benefits can be significantly smaller if employees split their career between multiple employers rather than remain at one employer. Thus over 10% of the workforce has a strong retirement-based incentive to stay where they are.

Eligibility standards for public benefits and their amounts also vary by state, and this discourages people who receive benefits such as Temporary Assistance for Needy Families (TANF) from moving to states that may have a stronger economy but less benefits. Even when eligibility standards and benefits are similar, the paperwork and time burden of enrolling in a new state can discourage mobility.

The federal government subsidizes home ownership as well, and homeownership is correlated with less labor mobility over time. Place-based subsidies to declining cities also artificially support areas that should have less people. As long as state and federal governments subsidize government services in cities like Atlantic City and Detroit people will be less inclined to leave them. People-based subsidies that incentivize people to move to thriving areas are an alternative that is likely better for the taxpayer, the recipient and the country in the long run.

How to increase labor mobility

Since state and local governments are unlikely to directly address the impediments to labor mobility that they have created, Mr. Schleicher argues for more federal involvement. Some of his suggestions don’t interfere with local control, such as a federal clearinghouse for coordinated occupational-licensing rules across states. This is not a bad idea but I am not sure how effective it would be.

Other suggestions are more intrusive and range from complete federal preemption of state and local rules to federal grants that encourage more housing construction or suspension of the mortgage-interest deduction in places that restrict housing construction.

Local control is important due to the presence of local knowledge and the beneficial effects that arise from interjurisdictional competition, so I don’t support complete federal preemption of local rules. Economist William Fischel also thinks the mortgage interest deduction is largely responsible for excessive local land-use regulation, so eliminating it altogether or suspending it in places that don’t allow enough new housing seems like a good idea.

I also support more people-based subsidies that incentivize moving to areas with better economies and less place-based subsidies. These subsidies could target people living in specific places and the amounts could be based on the economic characteristics of the destination, with larger amounts given to people who are willing to move to areas with the most employment opportunities and/or highest wages.

Making it easier for people to retain any state-based government benefits across state lines would also help improve labor mobility. I support reforms that reduce the paperwork and time requirements for transferring benefits or for simply understanding what steps need to be taken to do so.

Several policy changes will need to occur before we can expect to see significant changes in labor mobility. There is broad agreement around some of them, such as occupational licensing and land-use regulation reform, but bringing them to fruition will take time. As for the less popular ideas, it will be interesting to see which, if any, are tried.

New York’s Buffalo Billion initiative has been underwhelming

New York’s Buffalo Billion plan has come under fire amidst an ongoing corruption probe looking into whether some contracts were inappropriately awarded to political donors. The investigation has led to funding delays and there are reports of some contractors and companies rethinking their investments. But even without these legal problems, it is unlikely that the Buffalo Billion initiative will remake Buffalo’s economy.

Buffalo, NY has been one of America’s struggling cities since the 1950s, but before then it had a long history of growth. After it became the terminal point of the Erie Canal in 1825 it grew rapidly; over the next 100 years the city’s population went from just under 9,000 to over 570,000. Growth slowed down from 1930 to 1950, and between 1950 and 1960 the city lost nearly 50,000 people. It has been losing population ever since. The Metropolitan Area (MSA), which is the economic city, continued to grow until the 1970s as people left the central city for the surrounding suburbs, but it has also been losing population since then. (click to enlarge figure)

buffalo-population

Buffalo’s population decline has not escaped the notice of local, state and federal officials, and billions of dollars in government aid have been given to the area in an effort to halt or reverse its population and economic slide. The newest attempt is Governor Andrew Cuomo’s Buffalo Billion, which promises to give $1 billion of state funds to the region. The investment began in 2013 and as of January 2016, $870.5 million worth of projects have been announced. The table below lists some of the projects, the amount of the investment, and the number of jobs each investment is supposed to create, retain, or induce (includes indirect jobs due to construction and jobs created by subsequent private investment). This information is from the Buffalo Billion Process and Implementation plan (henceforth Buffalo Billion Plan).

buffalo-billion-projects

The projects listed have been awarded $727 million in direct investment, $150 million in tax breaks and $250 million in other state funds. The total number of jobs related to these investments is 9,900 according to the documentation, for an average cost of $113,859 per job (last column).

However, these jobs numbers are projections, not actual counts. This is one of the main criticisms of investment efforts like Buffalo Billion—a lot of money is spent and a lot of jobs are promised, but rarely does anyone follow up to see if the jobs were actually created. In this case it remains to be seen whether reality will match the promises, but the early signs are not encouraging.

Executives of the first project, SolarCity, which received $750 million of benefits and promised 5,000 jobs in western New York, appear to have already scaled back their promise. One company official recently said that 1,460 jobs will be created in Buffalo, including 500 manufacturing jobs. This is down from 2,000 in the Buffalo Billion Plan, a 27% decrease.

The SolarCity factory is not scheduled to open until June 2017 so there is still time for hiring plans to change. But even if the company eventually creates 5,000 jobs in the area, it is hard to see how that will drastically improve the economy of an MSA of over 1.1 million people. Moreover, page eight of the Buffalo Billion Plan reports that the entire $1 billion is only projected to create 14,000 jobs over the course of 5 years, which is again a relatively small amount for such a large area.

Contrary to the local anecdotes that say otherwise, so far there is little evidence that Buffalo Billion has significantly impacted the local economy. Since the recession, employment in Buffalo and its MSA has barely improved, as shown below (data are from the BLS). There has also been little improvement since 2013 when the Buffalo Billion development plan was released. (City data plotted on the right axis, MSA on the left axis.)

buffalo-employment

Real wages in both Erie and Niagara County, the two counties that make up the Buffalo MSA, have also been fairly stagnant since the recession, though there is evidence of some improvement since 2013, particularly in Erie County (data are from the BLS). Still, it is hard to separate these small increases in employment and wages from the general recovery that typically occurs after a deep recession.

buffalo-county-wages

The goal of the Buffalo Billion is to create a “Big Push” that leads to new industry clusters, such as a green energy cluster anchored by SolarCity and an advanced manufacturing cluster. Unfortunately, grandiose plans to artificially create clusters in older manufacturing cities rarely succeed.

As economist Enrico Moretti notes in his book, The New Geography of Jobs, in order for Big Push policies to succeed they need to attract both workers and firms at the same time. This is hard to do since either workers or firms need to be convinced that the other group will eventually arrive if they make the first move.

If firms relocate but high-skill workers stay away, then the firm has spent scarce resources locating in an area that doesn’t have the workforce it needs. If workers move but firms stay away, then the high-skill workers are left with few employment opportunities. Neither situation is sustainable in the long-run.

The use of targeted incentives to attract firms, as in the aforementioned SolarCity project, has been shown to be an ineffective way to grow a regional economy. While such incentives often help some firms at the expense of others, they do not provide broader benefits to the economy as a whole. The mobile firms attracted by such incentives, called footloose firms, are also likely to leave once the incentives expire, meaning that even if there is a short term boost it will be expensive to maintain since the incentives will have to be renewed.

Also, in order for any business to succeed state and local policies need to support, rather than inhibit, economic growth. New York has one of the worst economic environments according to several different measures: It’s 50th in overall state freedom, 50th in economic freedom, and 49th in state business tax climate. New York does well on some other measures, such as Kauffman’s entrepreneurship rankings, but such results are usually driven by the New York City area, which is an economically vibrant area largely due to historical path dependencies and agglomeration economies. Buffalo, and western New York in general, lacks the same innate and historical advantages and thus has a harder time overcoming the burdensome tax and regulatory policies of state government, which are particularly harmful to the local economies located near state borders.

Buffalo officials can control some things at the local level that will improve their economic environment, such as zoning, business licensing, and local taxes, but in order to achieve robust economic growth the city will likely need better cooperation from state officials.

State and local policy makers often refuse to acknowledge the harm that relatively high-tax, high-regulation environments have on economic growth, and this prevents them from making policy changes that would foster more economic activity. Instead, politicians invest billions of dollars of taxpayer money, often in the form of ineffective targeted incentives to favored firms or industries, with the hope that this time will be different.

Discovering an areas comparative advantage and creating a sustainable industry cluster or clusters requires experimentation, which will likely result in some failures. Local and state governments should create an environment that encourages entrepreneurs to experiment with new products and services in their region, but they shouldn’t be risking taxpayer money picking winners and losers. Creating a low-tax, low-regulation environment that treats all businesses—established and start-up, large and small—the same is a better way to grow an economy than government subsidies to favored firms. Unfortunately the Buffalo Billion project looks like another example of the latter futile strategy.

Does the New Markets Tax Credit Program work?

Location-based programs that provide tax credits to firms and investors that locate in particular areas are popular among politicians of both parties. Democrats tend to support them because they are meant to revitalize poorer or rural areas. In a recent speech about the economy, presumed Democratic nominee Hillary Clinton spoke favorably about two of them: the New Markets Tax Credit Program and Empowerment Zones.

Some Republicans also support such programs, which they view as being a pro-business way to help low-income communities. However, House Speaker Paul Ryan’s recent tax reform blueprint generally disapproves of tax credit programs.

Due to the volume of location-based programs and their relatively narrow objectives, many taxpayers are unfamiliar with their differences or unaware that they even exist. This is to be expected since most people are never directly affected by one. In this post I explain one that Hillary Clinton recently spoke about, the New Markets Tax Credit (NMTC) program.

The NMTC program was created in 2000 as part of the Community Renewal Tax Relief Act. It is managed by the Community Development Financial Institutions Fund, which is a division of the U.S. Treasury Department.

The NMTC program provides both new and established businesses with a tax credit that can be used to offset the costs of new capital investment or hiring new workers. The goal is to increase investment in low income communities (LIC) in order to improve the economic outcomes of residents.

Even though the program was started in 2000, no funds were issued to investors until 2003 (although some funds were allocated to the program in 2001 and 2002). Since 2001 over $43 billion has been allocated to the program. The figure below shows the allocations by year, amount issued to investors, and the total amount allocated from 2001 – 2014 (orange bar, uses right axis).

NMTC allocations

Figure 1

Practically all of the allocated funds from 2001 to 2012 have been issued to investors. A little over $250 million remains from 2013 and $1.3 billion from 2014. As the figure makes clear, this program controls a non-trivial amount of money.

The types of projects funded by the NMTC program can be seen in the figure below. The data for this figure comes from a 2013 Urban Institute report.

NMTC projects funded

Figure 2

So what have taxpayers gotten for their money? The program’s ‘fact sheet’ asserts that since 2003 the program has

“…created or retained an estimated 197,585 jobs. It has also supported the construction of 32.4 million square feet of manufacturing space, 74.8 million square feet of office space, and 57.5 million square feet of retail space.”

Like many government program administrators, those running the NMTC program seem to confuse outputs with outcomes. Presumably the goal of the NMTC program is not to build office space, which is a trivial achievement, but to improve the lives of the people living in low income communities. In fact, the program’s fact sheet also states that

“Investments made through the NMTC Program are used to finance businesses, breathing new life into neglected, underserved low-income communities.”

What really matters is whether the program has succeeded at “breathing new life” into LICs. To answer this more complicated question one needs to examine the actual economic outcomes in areas receiving the credits in order to determine whether they have improved relative to areas that haven’t received the credits. Such an exercise is not the same thing as simply reporting the amount of new office space.

That being said, even the simpler task of measuring new office space or counting new jobs is harder than it first appears. It’s important for program evaluators and the taxpayers who fund the program to be aware of the reasons that either result could be speciously assigned to the tax credit.

First, the office space or jobs might have been added regardless of the tax credit. Firms choose locations for a variety of reasons and it’s possible that a particular firm would locate in a particular low income community regardless of the availability of a tax credit. This could happen for economic reasons—the firm is attracted by the low price of space or the location is near an important supplier—or the location has sentimental value e.g. the firm owner is from the neighborhood.

A second reason is that the firms that locate or expand in the community might do so at the expense of other firms that would have located there absent the tax credit. For example, suppose the tax credit attracts a hotel owner who due to the credit finds it worthwhile to build a hotel in the neighborhood, and that this prevents a retail store owner from locating on the same plot of land, even though she would have done so without a credit.

The tax credit may also mistakenly appear to be beneficial if all it does is reallocate investment from one community to another. Not all communities are eligible for these tax credits. If a firm was going to locate in a neighboring community that wasn’t eligible but then switched to the eligible community upon finding out about the tax credit then no new investment was created in the city, it was simply shifted around. In this scenario one community benefits at the expense of another due to the availability of the tax credit.

A new study examines the NMTC program in order to determine whether it has resulted in new employment or new businesses in eligible communities. It uses census tract data from 2002 – 2006. In order to qualify for NMTCs, a census tract’s median family income must be 80% or less of its state’s median family income or the poverty rate of the tract must be over 20%. (There are two other population criteria that were added in 2004, but according to the study 98% qualify due to the income or poverty criterion.)

The authors use the median income ratio of 0.8 to separate census tracts into a qualifying and non-qualifying group, and then compare tracts that are close to and on either side of the 0.8 cutoff. The economic outcomes they examine are employment at new firms, number of new firms, and new employment at existing firms.

They find that there was less new employment at new firms in NMTC eligible tracts in the transportation and wholesale industries but more new employment in the retail industry. Figure 2 shows that retail received a relatively large portion of the tax credits. This result shows that the tax credits helped new retail firms add workers relative to firms in transportation and manufacturing in eligible census tracts.

The authors note that the magnitude of the effects are small—a 0.2% increase in new retail employment and a 0.12% and 0.41% decrease in new transportation and wholesale employment respectively. Thus the program had a limited impact during the 2002 – 2006 period according to this measure, despite the fact that nearly $8 billion was granted to investors from 2002 – 2005.

The authors find a similar result when examining new firms: Retail firms located in the NMTC eligible tracts while services and wholesale firms did not. Together these two results are evidence that the NMTC does not benefit firms in all industries equally since it causes firms in different industries to locate in different tracts. The latter result also supports the idea that firms that benefit most from the tax credit crowd out other types of firms, similar to the earlier hotel and retail store example.

Finally, the authors examined new employment at existing firms. This result is more favorable to the program—an 8.8% increase in new employment at existing manufacturing firms and a 10.4% increase at retail firms. Thus NMTCs appear to have been primarily used to expand existing operations.

But while there is evidence that the tax credit slightly increased employment, the authors note that due to the limitations of their data they are unable to conclude whether the gains in new employment or firms was due to a re-allocation of economic activity from non-eligible to eligible census tracts or to actual new economic activity that only occurred because of the program. Thus even the small effects identified by the authors cannot be conclusively considered net new economic activity generated by the NMTC program. Instead, the NMTC program may have just moved economic activity from one community to another.

The mixed results of this recent study combined with the inability to conclusively assign them to the NMTC program cast doubt on the programs overall effectiveness. Additionally, the size of the effects are quite small. Thus even if the effects are positive once crowding out and reallocation are taken into account, the benefits still may fall short of the $43.5 billion cost of the program (which doesn’t include the program’s administrative costs).

An alternative to location-based tax credit programs is to lower tax rates on businesses and investment across the board. This would remove the distortions that are inherent in location-based programs that favor some areas and businesses over others. It would also reduce the uncertainty that surrounds the renewal and management of the programs. Attempts to help specific places are often unsuccessful and give residents of such places false hope that community revitalization is right around the corner.

Tax credits, despite their good intentions, often fail to deliver the promised benefits. The alternative—low, stable tax rates that apply to all firms—helps create a business climate that is conducive to long-term planning and investment, which leads to better economic outcomes.

Can historic districts dampen urban renewal?

Struggling cities in the Northeast and Midwest have been trying to revitalize their downtown neighborhoods for years. City officials have used taxpayer money to build stadiums, construct river walks, and lure employers with the hope that such actions will attract affluent, tax -paying residents back to the urban core. Often these strategies fail to deliver but that hasn’t deterred other cities from duplicating or even doubling down on the efforts. But if these policies don’t work, what can cities do?

Part of the answer is to allow more building, especially newer housing. One factor that may be hampering the gentrification efforts of many cities is the age of their housing stock. The theory is straightforward and is explained and tested in this 2009 study. From the abstract:

“This paper identifies a new factor, the age of the housing stock, that affects where high- and low-income neighborhoods are located in U.S. cities. High-income households, driven by a high demand for housing services, will tend to locate in areas of the city where the housing stock is relatively young. Because cities develop and redevelop from the center outward over time, the location of these neighborhoods varies over the city’s history. The model predicts a suburban location for the rich in an initial period, when young dwellings are found only in the suburbs, while predicting eventual gentrification once central redevelopment creates a young downtown housing stock.”

In the empirical section of the paper the authors find that:

… a tract’s economic status tends to fall rather than rise as distance increases holding age fixed, suggesting that high-income households would tend to live near city centers were it not for old central housing stocks.” (My bold)

This makes sense. High income people like relatively nicer, newer housing and will purchase housing in neighborhoods where the housing is relatively nicer and newer. In the latter half of the 20th century this meant buying new suburban homes, but as that housing ages and new housing is built to replace the even older housing in the central city high income people will be drawn back to central city neighborhoods. This has the power to reduce the income disparity between the central city and suburbs seen in many metropolitan areas. As the authors note:

Our results show that, if the influence of spatial variation in dwelling ages were eliminated, central city/suburban disparities in neighborhood economic status would be reduced by up to 50 percent within American cities. In other words, if the housing age distribution were made uniform across space, reducing average dwelling ages in the central city and raising them in the suburbs, then neighborhood economic status would shift in response, rising in the center and falling in the suburbs. (My bold)

To get a sense of the age of the housing stock in northern cities, the figure below depicts the proportion of housing in eight different age categories in Ohio’s six major cities as of 2013 (most recent data available, see table B25034 here).

age of ohio's housing stock

The age categories are: built after 2000, from 1990 and 1999, from 1980-89, from 1970-79, from 1960-69, from 1950-59, from 1940-49, and built prior to 1939. As the figure shows most of the housing stock in Ohio’s major cities is quite old. In every city except for Columbus over 30% of the housing stock was built prior to 1939. In Cleveland, over 50% of the housing stock is over 75 years old! In Columbus, which is the largest and fastest growing city in Ohio, the housing stock is fairly evenly distributed across the age categories. Columbus really stands out in the three youngest categories.

In a free market for housing old housing would be torn down and replaced by new housing once the net benefits of demolition and rebuilding exceed the net benefits of renovation. But anyone who studies the housing market knows that it is hardly free, as city ordinances regulate everything from lot sizes to height requirements. While these regulations restrict new housing, they are a larger problem in cities where demand for housing is already high since they artificially restrict supply and drive up prices.

A potentially bigger problem for declining cities that has to do with the age of the housing stock is historic districts. In historic districts the housing is protected by local rules that limit the types of renovations that can be undertaken. Property owners are required to maintain their home’s historical look and it can be difficult to demolish old houses.

For example, in Dayton, OH there are 20 historic districts in a city of only 142,000 people. Dayton’s Landmark Commission is charged with reviewing and approving major modifications to the buildings in historic districts including their demolition.  Many of the districts are located near the center of the city and contain homes built in the late 1800s and early 1900s. Some are also quite large; St. Anne’s Hill contains 315 structures and the South Park historic district covers 24 blocks and contains more than 700 structures. The table below provides a list of Dayton’s historic districts as well as the year they were classified, number of structures, acreage, and whether the district is a locally protected district. Seventy percent of the districts are protected by a local historic designation while 30 percent are only protected by the national designation.

dayton historic districts table

I personally like old houses, but I also recognize that holding on to the past can interfere with revitalization and growth. Older homes, especially those built prior to 1940, are expensive to restore and maintain. They often have old or outdated plumbing systems, electrical systems, and inefficient windows that need to be replaced. They may also contain lead paint or other hazardous materials that were commonly used at the time they were built which may have to be removed. Many people can’t afford these upfront costs and those that can often don’t want to deal with the hassle of a restoration project.

Also, people have different tastes and historic districts make it difficult for some people to live in the house they want in the area they want. As this map shows, many of the Dayton’s historic districts are located near the center of the city in the most walkable, urban neighborhoods. The Oregon district and St. Anne’s Hill are both quite walkable and contain several restaurants, bars, and shops. If a person wants to live in one of these neighborhoods they have to be content with living in an older house. The design restrictions that come standard with historic districts prevent people with certain tastes from locating in these areas.

A 2013 study that examined the Cleveland housing market determined that it is economical to demolish many of the older, vacant homes in declining cities rather than renovate them. This is just as true of older homes that happen to be in historic districts.

Ultimately homeowners should be free to do what they want with their home and the land that it sits on. If a person wants to buy a historic house and renovate it they should be free to do so, but they should also be allowed to build a new structure on the property if they wish. When a city protects large swathes of houses via historic districts they slow down the cycle of housing construction that could draw people back to urban neighborhoods. This is especially true if the historic districts encompass the best areas of the city, such as those closest to downtown amenities and employment opportunities. Living in the city is appealing to many people, but being forced to purchase and live in outdated housing dampens the appeal for some and may be contributing to the inability of cities like Dayton to turn the corner.

Rent control, housing supply, and home values in Seattle and Houston

In my recent op-ed about rent control I point out that Houston, TX  permitted more home and apartment building than Seattle, WA from 2005 to 2014. The graph below shows the magnitude of this difference. The bars are the number of permits each year (the left axis) and the line is the ratio of Zillow’s home value index (numerator) and the average single family home construction cost for each city (denominator). The right axis reports the ratio. (Seattle’s data are here, Houston’s are here, and permit data are here).

houston, seattle permits graph

As seen in the graph, the orange bars (Houston) are much taller than the blue bars (Seattle). Also, Houston’s home value to average cost ratio was relatively flat during the period shown despite the fact that Houston grew by 163,000 people during this time period. This is because Houston’s high level of building kept pace with demand. During this 10 year period Houston’s home values were roughly 1.6 times average construction cost.

In Seattle, where less building occurred, home values reached nearly 2.5 times average construction costs in 2007 before falling to approximately 1.8 in 2009 due to the housing bust. Home values decreased even further from there, reaching their low point in 2012. Since 2012, however, they have been increasing while in Houston it appears the ratio has leveled off. The difference between the two ratios is not driven by relative cost changes either. The graph below shows the cost per unit in each city over this time period. They are fairly similar in dollar amounts and the ratio between them was relatively constant during this time period.

houston, seattle cost per unit

Seattle’s building restrictions are contributing to the high price of housing in that city. And because prices in Seattle are primarily driven by demand, home values are much more volatile: When demand increases they rise and when demand falls, like from 2007 – 09, they decline quickly.

For more information about the negative consequences of rent control, see here and here.

Local land-use restrictions harm everyone

In a recent NBER working paper, authors Enrico Moretti and Chang-Tai Hsieh analyze how the growth of cities determines the growth of nations. They use data on 220 MSAs from 1964 – 2009 to estimate the contribution of each city to US national GDP growth. They compare what they call the accounting estimate to the model-driven estimate. The accounting estimate is the simple way of attributing city nominal GDP growth to national GDP growth in that it doesn’t account for whether the increase in city GDP is due to higher nominal wages or increased output caused by an increase in local employment. The model-driven estimate that they compare it to distinguishes between these two factors.

Before I go any further it is important to explain the theory behind the author’s empirical findings. Suppose there is a productivity shock to City A such that workers in City A are more productive than they were previously. This productivity shock could be the result of a new method of production or a newly invented piece of equipment (capital) that helps workers make more stuff with a given amount of labor. This productivity shock will increase the local demand for labor which will increase the wage.

Now one of two things can happen and the diagram below depicts the two scenarios. The supply and demand lines are those for workers, with the wage on the Y-axis and the amount of workers on the X-axis. Since more workers lead to more output I also labeled labor as L = αY, where α is some fraction less than 1 to signify that each additional unit of labor doesn’t lead to a one unit increase in output, but rather some fraction of 1 unit (capital is needed too).

moretti, land use pic

City A can have a highly elastic supply of housing, meaning that it is easy to expand the number of housing units in that city and thus it is relatively easy for people to move there. This would mean that the supply of labor is like S-elastic in the diagram. Thus the number of workers that are able to migrate to City A after labor demand increases (D1 to D2) is large, local employment increases (Le > L*), and total output (GDP) increases. Wages only increase a little bit (We > W*). In this situation the productivity shock would have a relatively large effect on national GDP since it resulted in a large increase in local output as workers moved from relatively low-productivity cities to the relatively high-productivity City A.

Alternatively, the supply of housing in City A could be very inelastic; this would be like S-inelastic. If that is the case, then the productivity shock would still increase the wage in City A (Wi > W*), but it will be more difficult for new workers to move in since new housing cannot be built to shelter them. In this case wages increase but since total local employment stays fairly constant due to the restriction on available housing the increase in output is not as large (Li > L* but < Le). If City A output stays relatively constant and instead the productivity shock is expressed in higher nominal wages, then the resulting growth in City A nominal GDP will not have as large of an effect on national output growth.

As an example, Moretti and Hsieh calculate that the growth of New York City’s GDP was 12% of national GDP growth from 1964-2009. But when accounting for the change in wages, New York’s contribution to national output growth was only 5%: Most of New York’s GDP growth was manifested in higher nominal wages. This is not surprising as it is well known that New York has strict housing regulations that make it difficult to build new housing units (the recent extension of NYC rent-control laws won’t help). This makes it difficult for people to relocate from relatively low-productivity places to a high-productivity New York.

In three of the most intensely land-regulated cities: New York, San Francisco, and San Jose, the accounting contribution to national GDP growth was 19.3%. But these cities actual contribution to national output as estimated by the authors was only 6.1%. Contrast that with the Rust Belt cities (e.g. Detroit, Pittsburgh, Cleveland, etc.) which contributed -28.5% according to the accounting method but +6.1% according to the author’s model.

The authors conclude that less onerous land-use restrictions in high-productivity cities New York, Washington D.C., Boston, San Francisco, San Jose, and the rest of Silicon Valley could increase the nation’s output growth rate by making it easier for workers to migrate from low to high-productivity areas. In an extreme migration scenario where 52% of American workers in 2009 lived in a different city than they actually did, the author’s calculate that GDP per worker would have been $8,775 higher in 2009, or $6,345 per person. In a more realistic scenario (only 20% of workers lived in a different city) it would have been $3,055 more per person: That is a substantial increase.

While I agree with the author’s conclusion that less land-use restrictions would result in a more productive allocation of labor and thus more stuff for all of us, the author’s policy prescriptions at the end of the paper leave much to be desired.  They propose that the federal government constrain the ability of municipalities to set land-use restrictions since these restrictions impose negative externalities on the rest of the country if the form of lowering national output growth. They also support the use of government funded high-speed rail to link  low-productivity labor markets to high-productivity labor markets e.g. the current high-speed rail construction project taking place in California could help workers get form low productivity areas like Stockton, Fresno, and Modesto, to high productivity areas in Silicon Valley.

Land-use restrictions are a problem in many areas, but not a problem that warrants arbitrary federal involvement. If federal involvement simply meant the Supreme Court ruling that land-use regulations (or at least most of them) are unconstitutional then I think that would be beneficial; a broad removal of land-use restrictions would go a long way towards reinstituting the institution of private property. Unfortunately, I don’t think that is what Moretti and Hsieh had in mind.

Arbitrary federal involvement in striking down local land-use regulations would further infringe on federalism and create opportunities for political cronyism. Whatever federal bureaucracy was put in charge of monitoring land-use restrictions would have little local knowledge of the situation. The Environmental Protection Agency (EPA) already monitors some local land use and faulty information along with an expensive appeals process creates problems for residents simply trying to use their own property. Creating a whole federal bureaucracy tasked with picking and choosing which land-use restrictions are acceptable and which aren’t would no doubt lead to more of these types of situations as well as increase the opportunities for regulatory activism. Also, federal land-use regulators may target certain areas that have governors or mayors who don’t agree with them on other issues.

As for more public transportation spending, I think the record speaks for itself – see here, here, and here.

Some private sector pensions also face funding trouble

A new report by the Pension Benefit Guaranty Corp (PBGC) warns that while the market recovery has helped many multiemployer pension plans improve their funding there remain some plans that,”will not be able to raise contributions or reduce benefits sufficiently to avoid insolvency,” affecting between 1 and 1.5 million of ten million enrollees.

Multiemployer plans are defined as those which unions collectively bargained for, with multiple employers participating within an industry (e.g. building, construction, retail, trucking, mining and entertainment). They are also known as Taft-Hartley plans. Multiemployer plans grew out of the idea of offering pension benefits for unionized employees in transient kinds of work such as construction. These plans have been in trouble for awhile due to a variety of factors. Many plans have taken measures by increasing contributions and in a few cases cutting benefits according to GAO. But those steps have not been nearly enough to fix the growing shortfalls.

When a PBGC-insured pension plan goes insolvent beneficiaries are only guaranteed a fraction of their benefits. Those funds come from the premiums paid by remaining plans. The projected deficit for the ailing multiemployer plans range from $49.6 billion to $79.6 billion in 2022. By contrast the PBGC reports that single employer plans fare better with the current funding deficit of $27.4 billion narrowing to $7.6 billion by 2023.

Source: FY 2013 PBGC Projections Report

 

“Regulatory Certainty” as a Justification for Regulating

A key principle of good policy making is that regulatory agencies should define the problem they are seeking to solve before finalizing a regulation. Thus, it is odd that in the economic analysis for a recent proposed rule related to greenhouse gas emissions from new power plants, the Environmental Protection Agency (EPA) cites “regulatory certainty” as a justification for regulating. It seems almost any regulation could be justified on these grounds.

The obvious justification for regulating carbon dioxide emissions would be to limit harmful effects of climate change. However, as the EPA’s own analysis states:

the EPA anticipates that the proposed Electric Generating Unit New Source Greenhouse Gas Standards will result in negligible CO2 emission changes, energy impacts, quantified benefits, costs, and economic impacts by 2022.

The reason the rule will result in no benefits or costs, according to the EPA, is because the agency anticipates:

even in the absence of this rule, existing and anticipated economic conditions will lead electricity generators to choose new generation technologies that meet the proposed standard without the need for additional controls.

So why issue a new regulation? If the EPA’s baseline assessment is correct (i.e. it is making an accurate prediction about what the world would look like in absence of the regulation), then the regulation provides no benefits since it causes no deviations from that baseline. If the EPA’s baseline turns out to be wrong, a “wait and see” approach likely makes more sense. This approach may be more sensible, especially given all the inherent uncertainties surrounding predicting future energy prices and all of the unintended consequences that often result from regulating.

Instead, the EPA cites “regulatory certainty” as a justification for regulating, presumably because businesses will now be able to anticipate what emission standards will be going forward, and they can now invest with confidence. But announcing there will be no new regulation for a period of time also provides certainty. Of course, any policy can always change, whether the agency decides to issue a regulation or not. That’s why having clearly-stated goals and clearly-understood factors that guide regulatory decisions is so important.

Additionally, there are still costs to regulating, even if the EPA has decided not to count these costs in its analysis. Just doing an economic analysis is a cost. So is using agency employees’ time to enforce a new regulation. News outlets suggest “industry-backed lawsuits are inevitable” in response to this regulation. This too is a cost. If costs exceed benefits, the rule is difficult to justify.

One might argue that because of the 2007 Supreme Court ruling finding that CO2 is covered under the Clean Air Act, and the EPA’s subsequent endangerment finding related to greenhouse gases, there is some basis for the argument that uncertainty is holding back investment in new power plants. However, if this is true then this policy uncertainty should be accounted for in the agency’s baseline. If the proposed regulation alleviates some of this uncertainty, and leads to additional power plant construction and energy creation, that change is a benefit of the regulation and should be identified in the agency’s analysis.

The EPA also states it “intends this rule to send a clear signal about the current and future status of carbon capture and storage technology” because the agency wants to create the “incentive for supporting research, development, and investment into technology to capture and store CO2.”

However, by identifying the EPA’s preferred method of reducing CO2 emissions from new power plants, the agency may discourage businesses from investing in other promising new technologies. Additionally, by setting different standards for new and existing power plants, the EPA is clearly favoring one set of companies at the expense of another. This is a form of cronyism.

The EPA needs to get back to policymaking 101. That means identifying a problem before regulating, and tailoring regulations to address the specific problem at hand.