Housing Constraints and Spatial Misallocation

1 Housing Constraints andSpatial MisallocationChang-Tai HsiehUniversity of Chicago and NBERE nrico Moretti University of California, Berkeley and NBERA pril 25, 2018 AbstractWe quantify the amount of Spatial Misallocation of labor across US citiesand its aggregate costs. Misallocation arises because high productivity citieslike New York and the San Francisco Bay Area have adopted stringent re-strictions to new Housing supply, effectively limiting the number of workerswho have access to such high productivity. Using a Spatial equilibriummodel and data from 220 metropolitan areas we find that these constraintslowered aggregate US growth by 36% from 1964 to 2009. An earlier version of this paper circulated under the title Why Do Cities Matter?

2 LocalGrowth and Aggregate Growth. We are grateful to Klaus Desmet, Rebecca Diamond, DanielFetter, Cecile Gaubert, Ed Glaeser, Erik Hurst, Pat Kline, Steve Redding, Jose Vasquez and severalseminar participants for useful suggestions. We thank Jihoon Sung for research MISALLOCATION11 IntroductionStarting with Hsieh and Klenow (2009), a large number of studies have docu-mented the existence and the costs of factor Misallocation across firms. In thispaper, we focus on the Spatial Misallocation of labor across US cities. This anal-ysis is motivated by the observation of a large and growing Spatial dispersion ofnominal wages across US cities. After conditioning on worker characteristics,the standard deviation of nominal wages (in logs) across US cities in 2009 istwice as large compared to 1964, indicating that labor productivity is increas-ingly different across American cities.

3 If productivity of labor is vastly differentacross cities, output can in principle be increased by expanding employmentin high productivity cities at the expense of low productivity cities. We arguethat the growing dispersion of the nominal wage across cities reflects growingspatial Misallocation which ultimately lowers aggregate growth in the increase in Spatial wage dispersion is driven at least in part by cities likeNew York, San Francisco and San Jose, which experienced some of the strongestgrowth in labor productivity over the last five decades (Moretti (2012)). Thesecities also adopted land use restrictions that significantly constrained the amountof new Housing that can be built. As described by Glaeser (2014), since the 1960scoastal cities have gone through a property rights revolution which hassignificantly reduced the elasticity of Housing supply: In the 1960s, develop-ers found it easy to do business in much of the country.

4 In the past 25 years,construction has come to face enormous challenges from any local some areas it feels as if every neighbor has veto rights over every project. Misallocation arises because the Constraints on Housing supply in the mostproductive US cities effectively limit the number of workers who have accessto such high productivity. Instead of increasing local employment, productivitygrowth in Housing -constrained cities primarily pushes up Housing prices andnominal wages. The resulting Misallocation of workers lowers aggregate outputand welfare of workers in all US paper measures the aggregate productivity costs of local Housing con-straints through the prism of a Rosen-Roback model. In a Spatial equilibrium,2 HSIEH AND MORETTI aggregate output and welfare growth are not simply the sum of local shocks ineach city.

5 If workers can move across cities, a localized productivity shock in acity affects wages and employment not only in that city but also in other derive a formula that shows how local shocks aggregate to affect nationaloutput and welfare. Aggregate output and welfare growth depend on a weightedaverage of productivity shocks in each city and the efficiency of the allocationof workers across cities, where the latter depends on the elasticity of housingsupply in high productivity cities. If a city with accommodating Housing supplyexperiences productivity growth, local employment rises and workers in othercities benefit from the reallocation of jobs. If instead the city has restrictivehousing supply, the reallocation of jobs is limited and productivity growth inthe city is dissipated by the higher price of use data from 220 metropolitan areas in the US from 1964 to 2009 toperform two calculations.

6 First, we quantify the effect of Spatial find that most of the increased Spatial dispersion in the marginal productof labor is due to the growing Spatial dispersion in Housing prices. In turn, thegrowing Spatial dispersion of Housing prices is largely driven by strict zoninglaws in cities such as New York and the San Francisco Bay Area with strongproductivity growth. We find that the increased Spatial Misallocation of labordue to Housing supply Constraints in cities with high productivity growth ratesloweredaggregate growth between 1964 and 2009 by a significant particular, we calculate that increasing Housing supply in New York, SanJose, and San Francisco by relaxing land use restrictions to the level of the me-dian US City would increase the growth rate of aggregate output by Inthis scenario, US GDP in 2009 would be higher, which translates into anadditional $3,685 in average annual , we calculate the contribution of each US city to aggregate US growthand compare it to an accounting measure based solely on the growth of thecity s GDP.

7 The difference reflects the effect of a city s growth on the efficiencyof labor allocation across cities. While the accounting measure suggests that1 The earning increase would be smaller if more workers decide to enter the labor market inresponse to the higher salary or if there is immigration from MISALLOCATION3 New York, San Francisco and San Jose s contribution to aggregate GDP growthbetween 1964 and 2009 is 12%, viewed through the lenses of our model, thesecities were only responsible for 5% of growth. The difference is because theaggregate benefit of TFP growth in New York and Bay Area was in part offset byincreased Misallocation of labor across cities. In contrast, for Southern cities theaccounting and model-based measures are the same.

8 Due to an elastic supply ofhousing, much of the growth in the South took the form of employment growth,with no effect on conclude that local land use regulations that restrict Housing supply indynamic labor markets have important externalities on the rest of the homeowners in high productivity cities have a private incentive torestrict Housing supply. By doing so, these voters de facto limit the numberof US workers who have access to the most productive of American cities. Ingeneral equilibrium, this lowers income and welfare of all US paper builds on four bodies of work. First, we build on the literature onresource Misallocation by showing that frictions stemming from the housingmarket can impede the efficient allocation of resources across ,our paper builds on the work that uses cities or regions within a country aslaboratories to understand differences in income across differfrom this work by highlighting how the distribution of economic activity acrosscities itself affects aggregate outcomes in all cities in the country.

9 Third, we buildon the research that measures the effect of local Housing supply Constraints onhousing supply and Housing focus is on theaggregateimpact ofsuch , we use a general equilibrium Rosen-Roback model2 The existing literature on resource Misallocation includes papers on labor market frictions(Hopenhayn and Rogerson (1993); Guner et al. (2008); Gourio and Roys (2014); Garicano etal. (2016); Hsieh and Klenow (2009)); financial frictions (Buera et al. (2011); Greenwood etal. (2013); Midrigan and Xu (2014); Moll (2014)); restrictions in land markets (Restuccia andSantaeulalia-Llopis (2015)) and distortions in output markets (Peters (2016)). Restuccia andRogerson (2013) and Restuccia and Rogerson (2016) provide recent overviews of the literatureon , for example, Barro and Sala-i Martin (1992) and Gennaioli et al.

10 (2014).4 Some examples are Mayer and Somerville (2000); Glaeser and Gyourko (2003); Quigleyand Raphael (2004); Glaeser et al. (2006); Saks (2008); Saiz (2010)); Ganong and Shoag (2013);Diamond (2017).5 Hornbeck and Moretti (2017) use a different approach to estimate the local and aggregate4 HSIEH AND MORETTIto measure the effect of local land use regulations on aggregate have used similar models to measure the effect of state taxes, internaltrade frictions, infrastructure, and land paper is organized as follows. In Section 2 we present the model. Sec-tions 3 describes the data. Section 4 discusses how we infer the driving forcesin the model from the data. In Section 5 we present the main empirical 6 discusses extensions of the model.