Lecture on Household Sorting and municipal differentiation Based

Lecture on Household Sorting and municipal differentiation Based on Chapters 13 and 20 in Urban Economics by Arthur O’Sullivan, 5 th edition and Chapter 14 of The Economics of Zoning Laws by William Fischel Adapted and summarized by Austin Troy, University of Vermont

Urban differentiation and mobility • We looked at two ways of allocating resources voter rule and benefits taxation; first results in inefficient allocation and second is unrealistic • An alternate way of allocating is to let households form new municipalities based on their preferences • In this model, preferences are homogeneous within jurisdiction so MSB=MPB, so privately determined allocation decisions are efficient

How big should park be? Cost/ acre Marginal social benefit= MB 1+MB 2+MB 3 MC $60 MB curves for three citizens MB 1 MB 2 Marginal private cost MB 3 Q 1 Q 2 Q* acres Q 3

Urban differentiation and mobility If all people in jurisdiction have same preferences…. MCsocial MBsocial MCPrivate MBPrivate Q* Note: mistake in book

Voting with feet: Interjurisdictional mobility • Charles Tiebout model (1956) explains how differences in pricing and provision of services define jurisdictions, and residents “shop” for those bundles. • Tiebout model suggests that interjurisdictional mobility might prevent median voter inefficiencies • Increases efficiency in allocation of public services, but not equity of distribution

Voting with feet: Interjurisdictional mobility • In the model, households sort themselves according to housing consumption and public goods consumption into homogeneous communities • Hence residents go to where their preferences are, rather than imposing their preferences on those who don’t want them • Essentially provides market for public services

Simplified Tiebout model assumptions • Households choose municipality providing ideal level of public goods, meaning there are enough jurisdictions from which to choose • There is perfect information and costless mobility • There are no interjurisdictional spillovers • City pays for public goods with head tax

Tiebout and the park example • Households move so as to maximize utility given income, preferences, taxes, and prices of private goods (land, housing) • Mobility plus more jurisdictions will increase intra-city homogeneity • Park lovers all go to one city with big parks, and those who value other uses for their money over parks sort themselves in a different city • Park size will be efficient within each city • In this case, the median voter is irrelevant

Tiebout model and sorting • Each household moves to the jurisdiction with the service quantities for which they are willing to pay • Because public goods are “normal goods” high income households have higher marginal benefit • The tradeoff for more services is higher tax burden • At a low quantity of public good, benefits> tax burden for all households, but as increase amount, tax burden>benefits for lower income households • Hence low income households outbid high income people in low public good areas and vice versa.

Tiebout model and sorting • Because public goods are income elastic, high income households will have larger MB from consuming public goods than low income, therefore steeper BR functions and will outbid where level of PG is high • Hence when HH’s sort themselves based on public goods will sort based on income— this is because income determines MB

Tiebout model and sorting Bid rent: high income HH Bid rent: low income HH Low inc zone high inc zone Q of local public good Where tax outweigh benefits of public goods for rich Where tax outweigh benefits of public goods for poor

Tiebout mode—empirical evidence • Metro areas with one municipality have wide variety of demanders for public services (Gramlich and Rubinfeld 1982) • The greater the number of municipalities, the more homogeneous each is with respect to demand for public services, and hence clustering of residents with similar preferences occurs (G and R 1982, Heikkila 1996). • There are more and smaller municipalities on average in metro areas with heterogeneous demand for public services (Fisher and Wassmer 1998).

Jurisdictions in NYC area

Jurisdictions in Boston Area

Jurisdictions in LA Area

Jurisdictions in SF Bay. Area

Tiebout model with qualifications from Fischel • Because most of these goods are actually partial rather than pure, they are impacted by crowding; Av cost curve goes down, then up with size • At N 0 , newcomers start imposing a congestion cost on others(becomes semi-rivalrous), however, until cost minimizing point (N 1), impact of crowding is made up for by contribution of new users to average cost, hence they are welcomed until then. • Towns use zoning to get towards N 1

Fischel Amendment to the Tiebout model While AC $ per capita MC Additional users are welcome until congestion costs (MC)>AC, at N 1 AC Congestion point: here additional people start imposing cost on others declines (<N 1), it is pure public good According to Tiebout, this is the optimal size, because it minimizes average cost of services (AC) N 0 N 1 Community size

Fischel Amendment to the Tiebout model • Hence, communities that are smaller will encourage development and communities that are bigger, or nearing that size will use exclusionary zoning to limit supply. • This is why rural communities will have highly permissive zoning and established suburbs will not.

Fischel Amendment to the Tiebout model • In some cases, N 1(min point for AC), is not most efficient point • Assume town does not have monopoly zoning power (does not affect prices in metro area) and that residents do not share cost equally (don’t all pay AC; assumes non-uniform assessment of property ). Then efficient level is now N 2, where MC intersects MR/AR, which is horizontal because their decisions have no effect on regional supply and they are price takers. • Means last household to move in is WTP exactly amount that costs community in additional provision services

Fischel Amendment to the Tiebout model If N 1’, town is too small because costs BD imposed on community, but perceived benefit by prospective residents in AD. As long as new residents pay at least BD, town is no worse off MC $ per capita AC A A MR=AR B C D N 0 N 1 ’ N 2 Community size N 3 N 2= Optimal size without monopoly zoning power

Optimal community size without MZ • A population less than N 2 is inefficient because more net benefits could be gained by addition of more residents since marginal benefit (AD) is still greater than the marginal cost (BD). Only when they are equal (exhausted) have all potential gains been used up. Hence Pareto improvements to moving from N 1’ to N 2.

Optimal community size without MZ • The key point here is the order in which people came. If all residents shared costs equally (uniform assessments), then N 1 would be optimal for them, since at N 1’ new residents pay the AC but they impose a larger MC (BD, rather than CD). This forms a subsidy to the new development at expense of previous homeowners • Without controls, new residents would make decisions based on AC, and hence they would continue arriving until N 3

Fischel: size without controls MC $ per capita AC A MR=AR That’s bad for the community, because MC> MR after N 2; from there until N 3 it benefits newcomers, but at the expense of previous residents N 0 New residents will arrive until size= N 3 N 1 N 2 Community size N 3

Hamilton addition: Tiebout model and property tax • The Tiebout model assumes a simple head tax as the entry price. • Under this scenario, residents sort only on the basis of public good preference, not on the basis of home value because the amount paid is independent of home value • With property tax, sorting now occurs on two dimensions: goods preference and home value • This will result in more jurisdictions

Hamilton addition: Tiebout model and property tax • If lower income family moves to town and sets up house worth less than average, they pay less tax, but still get same amount of service (e. g. schooling) • This constitutes a transfer, so incentive for existing residents to zone them out. • Illegal to zone by home value, but lot size can proxy that often.

Hamilton addition: Tiebout model and property tax • What about lower income residents who are willing to pay that amount in taxes for that level of service, but can’t afford the house • In theory, there will be enough jurisdictions such that one out there will have high tax rates on small, low value houses, coupled with high expenditure on the service. • Are there this many? In reality, D for housing and services is highly correlated.

Tiebout model and property tax • Example: • Head tax: all pay equal amount; property tax: those with expensive houses pay more • Assume 50% houses big (300 k) and 50% small ($100 k) • City must raise average of $3 k/ HH • To do this they have 1. 5% rate, resulting in $4. 5 k in tax for big HH and $1. 5 k for small

How does Property Tax Affect Location Choice? • Big households now pay $4, 500 but only get $3, 000 in services • They could set up own municipality with only expensive houses so that they can lower the tax rate and all households pay for the level of services they get • They will do this if gains to doing so are large relative to transaction costs • They will enforce this in new town through use of large lot zoning, keeps property values high • This leaves small house town with high tax rate

Effects of Property Tax • Increases the number of jurisdictions because leads to more sorting • Now sorting based not just on desired level of public goods, but on housing consumption • Under head tax only sort based on local public good preferences • I. E. There would be high public good/small lot town, high public good/large lot town, etc. • When households sort based on housing consumption, they also sort based on income because housing is a “normal good”

Tiebout model with property tax and variable local public goods • Assume single public good-parks • Half of households are wealthy and have $100 k homes; half are low income and have $50 k homes • Half of households in each income group want large park budget ($2 k) and half small budget ($500). • Households can establish new municipalities using large lot zoning to set house values. • Use of the property tax and zoning can actually help municipalities obtain their optimal size.

Tiebout model with property tax and variable local public goods • Households sort based on park demand property value to form four municipalities (wealthy+big PB, wealthy+small PB, LI+big PB, LI+small PB). • High PB communities will have higher tax rate, as will poorer communities, hence W-LB W-SB LI-LB LI-SB House val 100 k 50 k Park Budg 2 k 500 Tax rate 2%. 2% 4%. 4%

Tiebout model with property tax and variable local public goods • If communities are totally homogeneous, property tax is like a user fee; you pay $X in fee and get $X worth of park • That’s why poor municipality with big PB pays higher tax rate than wealthy municipality with big PB —because the amount is the same, just like with any fee; hence you get what you pay for

Problems with the Tiebout model • Perfect homogeneity of communities is impossible; there will never be enough municipalities to allow citizens to sort themselves into perfectly homogeneous communities, especially when considering all the factors that people could sort on (think of some) • This is especially true in larger, denser central cities where there is simply to much heterogeneity within a small area. • Hence, usually suburban municipalities are much more likely to display Tiebout properties than urban ones • However, research in LA (Heikkila 1996) found that communities do form demographic clusters with relative homogeneity

Problems with the Tiebout model • Assumes no transaction costs to moving around or to forming new jurisdictions, which is clearly inaccurate; moving is expensive • Assumes no cost to forming a new jurisdiction, hence there won’t be unlimited combinations of service and tax levels. – Nevertheless, Fisher and Wassmer(1998) find that in highly diverse MSAs there will be more municipalities than in more homogeneous ones • Also assumes no spillovers, which is clearly unrealistic – But many similar towns with similar LU patterns tend to aggregate • Clearly information about cities in imperfect. Moreover, they are changing over time.

Racial Sorting • Facts: 2/3 blacks live in central cities and 1/3 in suburbs; reversed for whites. • Dissimilarity index: to achieve same racial composition within a neighborhood as within metro area, what percentage of the people would have to move? • The average for the US is 69% • The larger the metro area, the more segregation there is

Causes of Racial Sorting • Empirical studies find blacks prefer to live in more integrated neighborhoods than whites on average • Income sorting generally leads to racial sorting because of correlation – Nevertheless, a black HH with same income/characteristics as white suburban HH is still less likely to live in suburbs, disparity must be explained by something else (Rosenthal 1989, Kain 1985). What? ?

Real Estate Practices and Racial Sorting • Racial Steering: Real estate agents “steers” minority homebuyers towards certain neighborhoods(Ondrich 1998) • Often minority housing is of lower quality relative to price compared to housing in white neighborhoods (Milgram 1988, Krivo 1995) • Minorities often given poorer levels of service in information and financing (Yinger 1998) • “Fair housing audits” now increasingly common