Presentation on theme: "Lecture on Household Sorting and municipal differentiation Based on Chapters 13 and 20 in Urban Economics by Arthur OSullivan, 5 th edition and Chapter."— Presentation transcript:
Lecture on Household Sorting and municipal differentiation Based on Chapters 13 and 20 in Urban Economics by Arthur OSullivan, 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? Marginal social benefit= MB 1+ MB 2+ MB 3 MB 1 MB 2 MB 3 MC Q* acres $60 Cost/ acre MB curves for three citizens Marginal private cost Q1Q1 Q2Q2 Q3Q3
Urban differentiation and mobility MB Private MB social Note: mistake in book MC social MC Private Q* If all people in jurisdiction have same preferences….
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 dont 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 HHs 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 Where tax outweigh benefits of public goods for rich Where tax outweigh benefits of public goods for poor Q of local public good
Tiebout modeempirical 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 BayArea
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 Community size $ per capita N1N1 N0N0 MC AC Additional users are welcome until congestion costs (MC)>AC, at N 1 Congestion point: here additional people start imposing cost on others According to Tiebout, this is the optimal size, because it minimizes average cost of services (AC) While AC declines (
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 (dont 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 Community size $ per capita N1N1 N2N2 N0N0 MC MR=AR AC N2= Optimal size without monopoly zoning power A C B A D N 1 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 N3N3
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 Community size $ per capita N1N1 N2N2 N0N0 MC MR=AR AC New residents will arrive until size= N 3 A N3N3 Thats 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
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 cant 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 (300k) and 50% small ($100k) City must raise average of $3k/ HH To do this they have 1.5% rate, resulting in $4.5k in tax for big HH and $1.5k 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 $100k homes; half are low income and have $50k homes Half of households in each income group want large park budget ($2k) 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 and 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 House valPark BudgTax rate W-LB100k2k2% W-SB100k500.2% LI-LB50k2k4% LI-SB50k500.4%
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 Thats why poor municipality with big PB pays higher tax rate than wealthy municipality with big PBbecause 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 wont 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