To market urbanists and many others, it’s clear that there is a positive relationship between high housing costs and land-use restrictions and that liberalizing zoning would lower housing costs relative to what they would be in a more regulated environment. Given this relationship, reducing zoning would improve efficiency in the housing market by allowing consumer demand to drive the amount of resources that are put into housing development. However, land-use reform would also affect other policy areas such as public schools, transportation infrastructure, and sewer and water provision. Predicting how a liberalizing reform in one policy area will affect the complete public policy landscape is as impossible as predicting how one private sector innovation will affect other markets.
Political scientist Steven Teles coined the term “kludgeocracy” to describe the complexity of contemporary American policy. For example, zoning has become a tool to make high-performing public schools exclusive, even though land-use policy and education policy are seemingly unrelated areas governed by different agencies. Because providing zero-price quality education to every child in the country may be impossible, zoning is a kludge that allows policymakers to provide this service to their high-income and influential constituents. Teles describes this policy complexity:
A “kludge” is defined by the Oxford English Dictionary as “an ill-assorted collection of parts assembled to fulfill a particular purpose…a clumsy but temporarily effective solution to a particular fault or problem.” The term comes out of the world of computer programming, where a kludge is an inelegant patch put in place to solve an unexpected problem and designed to be backward-compatible with the rest of an existing system. When you add up enough kludges, you get a very complicated program that has no clear organizing principle, is exceedingly difficult to understand, and is subject to crashes. Any user of Microsoft Windows will immediately grasp the concept.
“Clumsy but temporarily effective” also describes much of American public policy today. To see policy kludges in action, one need look no further than the mind-numbing complexity of the health-care system (which even Obamacare’s champions must admit has only grown more complicated under the new law, even if in their view the system is now also more just), or our byzantine system of funding higher education, or our bewildering federal-state system of governing everything from welfare to education to environmental regulation.
In even the simplest government, it’s impossible to forecast the effects of one policy reform due the inherent difficult of predicting how humans will react to a change in rules. However, under today’s kludgeocracy, policy analysis has grown ever more complex. Not only will a change in the rules of the game change the outcomes of interaction on the market square, but a change in one policy will also change the incentives that other policymakers face on the public square. For example, a governor may attempt to implement policies that will create economic growth, recognizing that growth would benefit from an elastic housing supply that readily allows new people to enter his state. At the same time, school board officials who oversee an exclusive school district in the state may wish to maintain the current demographics of their jurisdiction without allowing any new residents in. If state policymakers implemented a policy to make it easier to build new housing, such as a tax credit for homebuyers in the state, municipal policymakers within the state might feel compelled to pass new rules to restrict housing supply at the local level.
In their paper “Why Is Manhattan So Expensive?” Edward Glaeser, Joseph Gyourko, and Raven Saks estimate what they call the “zoning tax” for 21 cities. This is the portion of housing costs that they attribute to land-use regulation in each city. They find that San Francisco has the highest zoning tax, with regulations accounting for over half of the cost of housing. Following from the conclusion of Glaeser et. al., it’s easy to make the policy recommendation that liberalizing land-use regulation would improve economic efficiency, making the country’s most productive cities more accessible to more people. And it’s likely true that deregulating the housing market would have the expected effect on house prices. However, it’s also true that many other policies at the federal, state, and local levels would be affected by a change in housing regulations. For example, municipally-provided services such as roads and sewers are designed under current zoning rules. A change in land-use regulations would change the effects of other municipal programs.
Federal programs such as the mortgage-interest tax deduction and affordable housing programs also have complex interactions with locally implemented and enforced zoning rules. In many cases, local and federal policymakers are not aware of all of the policies affecting housing supply and demand, so they may not even be able to see the full scope of the kludgeocracy that they are contributing to. Under the circumstances of a tightly wound knot of policies that affect a market, it’s impossible to predict the effects of repealing or liberalizing a given rule. Permitting more housing construction in San Francisco may reduce its zoning tax, but it would also result in many other changes within the market and public squares that are unknown.
While studying economics often leads people to think about the ceteris paribus effect of a policy change, in the real world, a policy will rarely be changed without resulting in domino effect of other changes in other policies and market outcomes because land-use policy is entangled with so many other policies. Teles writes, “While it might seem like an uphill climb, a simpler, less kludgey government is an immensely attractive goal, and should appeal to Americans of all parties and ideologies.” In this world, land-use reform would be much more likely because zoning wouldn’t be serving as a kludge for so many other policy areas.