PROPERTY TAXATION, PROPERTY BASE, AND PROPERTY VALUE: AN EMPIRICAL TEST OF THE “NEW VIEW” ROBERT W. WASSMER*

Abstract - The “Traditional,” “New,” and “Benefit” Views of property taxation yield different predictions in regard to the ef- fects of property taxation, An empirical test for evidence on the predicted effects of the New View is given. Results support the New View and indicate that ( ‘7) the greater the positive differential between a city’s rate of property taxation and the nation’s average rate, the smaller the amount of capital in the city and the smaller the per-unit market value of its property tax base; and (2) the higher the average rate of property taxation in the country, the lower the return to all prop- erty. Simulations regarding revenue alter- natives vided.

to the PweQ tax are a/so pro-

INTRODUCTION

Property taxation is controversial in the United States. Reasons for this controversy are numerous. Property taxes are highly visible and usually assessed on a house- hold’s biggest consumption item and a household’s or firm’s biggest investment item. Assessment of the stock of property has inevitably led to horizontal inequities.

*Wayne State Umverslty, Detroit, MI 48202

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The fact that property taxes in the United States are the primary source of local fund- ing for probably the most valued govern- ment service, K-12 public education, also contributes to the debate surrounding them.

In addition to the discord caused by the in- stitutional arrangement of property taxes, policymakers believe that the incidence of the property tax is regressive. Many elected officials also contend that an excessive rate of property taxation discourages local eco- nomtc development by driving out prop- erty, employment, and population. Property taxation is also a controversial political topic because of these two widely ac- cepted beliefs.

Economists have responded to this contro- versy by developing theories on the inci- dence of property taxation. Unfortunately, the three basic theories or “Views” devel- oped in regard to property taxation yield quite different predictions on the effects of the tax. The Traditional View, popularized by Netzer (1966), finds that owners of the capital portion of taxed property bear no burden of the tax since it is passed fully forward to capital renters. The conclusion that the property tax is regressive follows because the poor generally spend a greater

portion of their income to rent capital than the rich. Alternatively, the New View, pre- sented by Mieszkowski (1972) and pop- ularized by Aaron (1975), finds that the owners of all property bear some burden of the tax. The finding that property taxes are progressive follows, since the rich ob- tain a greater portion of their income from capital ownership than the poor. The more recent Benefit View, introduced by Hamil- ton (1975, 1976) and discussed by Fischel (‘I 987, 1992), quite distinctly concludes that property taxes can be a form of effi- cnent user charges for local public services. If such is the case, the incidence of the property tax is of much less concern.

Mieszkowski and Zodrow (1989) have writ- ten a comprehensive survey on the three basic theoretical views of the property tax and the many extensions made to them. They conclude that .the Traditional View is (only a variation of the New View and that the Benefit View is entirely valid only if a binding form of local zoning or perfect capitalization exists. Mieszkowski and Zod- row’s support of the New View of property taxation is based on their belief that per- fect zoning and capitalization do not exist in the United States. As pointed out in their survey, there is a need for a well-de- vised investigation to test this opinion and provide some empirical measure of the va- lidity of the New View.

The purpose of this paper is to present the derivation and result of an empirical test of the type called for by Mieszkowski and Zodrow. The goal of the empirical test is t.o identify elasticity measures that can, in principle, measure the predicted effects of property taxation obtained from the New View of property taxes. If these elasticity measures are not statistically different from zero or differ in the predicted direction of the effect, then the Benefit View may be the more appropriate way to model the ef- fects of property taxation.

To better understand the denvation of this

empirical test, a brief discussion of the Tra- ditional, New, and Benefit Views of the property tax is given first. Following this, the conceptual framework behind the em- pirical test is presented. The next section contains a description of data used in the estimation, econometric issues considered before estimation, and the results of the estimation. Simulations regarding an exog- enous increase in property taxation and al- ternatives to the property tax are then pre- sented.

THE TRADITIONAL, NEW, AND BENEFIT

VIEWS OF THE PROPERTY TAX

The Traditional View of the property tax uses a “differential” rnethod of tax incl- dence analysis. This method ignores the benefits received by those paying taxes, because benefits are (assumed to display lit- tle relationship to the amount of taxes paid. The Traditional ‘View of the property tax examines the effect of replacing a “lump-sum” -or nondistortionary form of tax-with a distortionary property tax.

The Traditional View originates in the par- tial-equilibrium framework of one taxing jurisdiction. The analysis considers property taxes to be separate payments on capital and land. The supply of capital to any ju- risdiction is modeled as perfectly elastic at a nationally determined rental rate paid to owners of capital (rN). Figure 1 contains the effect in a city that enacts an ad valo- rem property tax (t) on capital.’ The de- mand for capital decilines by the percent- age amount of the tax (D to D’) and the gross-of-tax rental rate paid by capital rent- ers rises io absorb the entire tax increase (rN to fN(” -t t)).

If a city enacts a property tax on its per- fectly inelastic supply of land, the result is perfect capitalization-the rental rate paid to owners of land falls by the entire tax in- crease (rfi4 to rN(l - !)). Under these tradi- tional assumptions, the effect of instituting a properly tax in a city (or raising the rate

1 136

I AN EMPIRICAL TEST OF THE “NEW VIEW”

FIGURE 1. The TraditIonal View of a Property Tax on Capital

rN (l+t)

of an existing property tax) is to reduce the amount of assumed perfectly mobile capital in the jurisdiction (K, to K,). The rental rate paid to owners of local capital (or the related market price of local capital) does not change. The rental rate paid to owners of land in the city (or the market price of land) falls.

The New View of the property tax distin- guishes itself through the use of a general equilibrium analysis of all jurisdictions in a country. A country’s supply of taxable capi- tal is considered fixed and perfectly mobile in the long run. Each jurisdiction also con- tains a fixed amount of taxable land. The remaining discussion of the New View is based primarily on Zodrow and Mieszkows- ki’s (1986) reformulation of Mieszkowski’s (1972) original article.

Zodrow and Mieszkowski assume that there are N different types of demanders

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of a locally provrded service that have sep- arated themselves into N different jurisdic- tions. Initially, the locally provided service is funded through a head tax. As first de- scribed by Tiebout (1956), this results in an efficient allocation of individuals to jurisdic- tions. The ownership of land and capital is not restricted to the city of residence.

For simplicity, assume that (1) each jurisdic- tion begins with an equal amount of land and capital, (2) the rental elasticity of capi- tal demand is equivalent in each jurtsdic- tion, and (3) there are only three types of demanders of the locally provided service. Low types of demanders prefer the local service at 50 percent below the level pre- ferred by medium types, while high types prefer the local service level at 50 percent above the medium service level. Figure 2 contains one city for each type of deman- der. The head tax in the jurisdiction with

FIGURE 2. The New View of Property Taxation

'H,3

5J

'H,2 'H,l

I?1 PO Hi.gh-Type

pO Medium-Type

high-type demanders is necessarily 200 jpercent higher than the head tax in the ju- risdiction with low-type demanders. Capital mobility Insures that the rental rate paid to owners of capital (rJ is constant across all three jurisdictions in the long run. A head tax has no effect on each city’s property market.

Now consider the outcome of an exoge- nous requirernent that a certain percentage of revenue, formerly raised by the head tax, be raised by an ad-valorem tax on property. The medium-type city would In- stitute the average rate of property taxa- tion. The rate of property taxation in the high- and lovv-type cities would, respec- tively, be 50 percent higher and lower. Since capital ownership is not restricted to the jurisdictron in which residents live and there are no local ordinances on the amount of capital that a homeowner or firm must have, this is also a form of drf- ferential incidence analysis.

In Figure 2, the supply of taxable property (the amount of property is represented by a “P”) represents both the supplies of cap- ital and land in the city. Property supplies are fixed in the short run. The result of revenue being partially raised by a property tax is a shift in the property demand curve in each city (D to D’). After the decrease in

D D'

po p1 :Low-Type

demand, ihe rental rate paid to owners of property iI7 the medium-type city falls from

h to hl. Zodrow and Mieszkowrki refer to this as the “profits tax” effect that de- presses the market value of property throughout all cities by the averrjge rate of taxation. In the high-type jurisdiction, the rental rate paid to owners of property falls to an r,,, that is lower than the rM,, in the medium-type city. The negative differential between rH,, 1t-1 the high-type city and r,,,,, in mediurn-type city is an “excise tax” ef- fect due to the higher property tax rate in the high.Iype city.2 In the low-type jurisdic- tion the rental rate paid to owners of property lalls to a higher rL,, than rM,, in the medium-type jurisdrction. This higher rate reflects the sum of the nationwide profits tax effect and a positive excise tax effect.

So far, the analysis has been based on the short-run assumption of a fixed supply of property in a community. If owners of tax- able capital receive differential rental rates in three cities, there IS an incentive for mo- bility. In the long run, owners of capital in the high-type city will relocate their capital investments to the low-type city. This shifts the short run property supply curves (S, to S,). Supply-side equilibrium is achieved when the rent paid to owners of property

I AN EMPIRICAL TEST OF THE “NEW VIEW”

is equalized at rH.2 and rL,2 in the high- and low-type cities, which equals rM,, in the medium-type city.

The New View yields empirically testable predictions on the effect of property taxa- tion on a city’s aggregate property base and property value. Holding local capital and land fixed, an increase in the local rate of property taxation-that replaces a non- distortionary form of taxation-depresses a city’s aggregate value of property by the average rate of property taxation. A city’s aggregate value of property will be even lower in the high-type city and higher in the low-type service city. Allowing for capi- tal mobility after an increase in property taxation, the profits tax effect implies that the aggregate value of taxed property will be lower in all cities. Due to excise tax ef- fects, the aggregate property base in the high-type service city will be even lower while the aggregate property base in the low-type service city will be somewhat higher than implied by the profits tax alone.

At this point in the analysis, the rental rate paid by renters of taxable property is high- est in the high-type city (at r,,J , and low- est in the low-type city (near rL,,). If the sorting of individuals to city types does not result in perfectly homogenous communi- ties, residents may now be able to increase their utility by moving between cities.3 Res- idents for which the higher rental rate of T,,~ is not offset by higher service levels would migrate to other cities, causing the rental rates to move closer together but not necessarily converge. The convergence of rental rates paid by demanders would cause another round of the supply shifts just described. Since all high service de- manders do not wish to move to lower service cities, a long-run equilibrium with excise tax rent differentials on local prop- erty demanders is likely to persist.4

The final view of property taxation, or the Benefit View, uses the assumptions of the

139

New View but places additional restrictions on property ownership and pricing. As given by Hamilton (1975, 1976), these re- strictions include “perfect fiscal zoning” or “perfect fiscal capitalization.” Perfect fiscal zoning allows a city to restrict residential capital (housing units) to some minimum value. In a Tiebout world, homes greater than this value would not be built in the city because through property tax financ- ing, they would pay a greater price for city services. Perfect fiscal capitalization occurs in a fully developed heterogeneous hous- ing community when the fiscal surplus- the excess of local service benefits over lo- cal property tax payments for a small house in a typically large house commu- nity-is capitalized into a higher rental rate (or market price) than the same small house would earn in a homogenous small house community. Fiscal deficits for rela- tively large houses are also negatively capi- talized in the heterogeneous community.

In essence, binding fiscal zoning and/or perfect capitalization turns the property tax into the head tax or nondistortionary user charge that Tiebout (1956) imagined for the provision of local residential services. If either occurs, all jurisdictions in a Tiebout world would be equal in regard to the per- unit, after-tax cost of residential capital. Ju- risdictions would also be homogenous in regard to residents’ demand for the locally provided service. White (1975) and Fischel (1975) have extended Hamilton’s line of reasoning to the taxation of firm property .

Assuming perfect fiscal zoning in regard to all types of property, a pure Benefit View of property taxation performs a “balanced- budget” incidence analysis of the property tax by considering that property taxes paid by demanders of residential and firm prop- erty are equivalent to the benefits they re- ceive through the city’s expenditures. If this is the case, the exogenous adoption of a partial property tax by the three communi- ties shown in Figure 2 should have no ef-

feet on the demand for property in each community.

Under perfect fiscal capitalization in fully developed heterogeneous cities, the Benefit View of property taxation implies that local property tax dbfferentials will be capitalized tnto individual local property values. Rela- tively large (small) homes in a heteroge- neous city would sell at a discount (pre- mium). As given by Hamllton (19’76), in the aggregate, these individual capitalization effects cancel so that the net effect on to- tal city property tax base from shifting to a property tax should be zero, despite a mul- titude Iof negative and positive capitaliza- tion effects on individual properties. There- fore, the Benefit View also yields empirically testable predictions on the ef- fect of property taxation on a city’s aggre- gate property value and amount. A shift to property taxation (or alternatively a reve- nue neutral increase in the rate of property taxation that lowers an alternative local tax) should have no effect on a city’s ag- gregate unit value of property and no ef- fect on a city’s aggregate property amount. Note that this absence of aggre- gate effects IS in stark contrast to the prof- its and excise tax effects predicted by the New View of property taxation. Local ser- vice levels are reflected in higher aggregate local property values in both the New and Eenefit Views But, only under the New Vew should tlhe method or rate of prop- erty taxation affect aggregate property val- Uf!S.

In the past, economists have evaluated the merits of the 13enefit View based on evi- dence of perfect fiscal zoning or capitaliza- tion. Mieszkovvski and Zodrow (1989) have argued that there is little evidence to sup- port perfect fiscal zoning and capttaliza- ton.’ Flschel (1987, 1992) has responded with a long and impressive list of institu- tional evidence demonstrating the perva- siveness of fiscal zoning in the United States. Beginning with Oates (1969), capi- talization studies have shown that, ceteris

pdribus, Increased local expenditures in- crease individual and aggregate local prop- erty values, while increased local property taxation decreases individual and aggregate local property values.” The capitalization of local property tax rates into indiv~~dual local property values can conceivably occur un- der both I he New View and the Benefit View of the property tax that relies on per- fect fiscal capitalization within heteroge- neous jurisdictions. The validity of the New View of property taxation remains to be shown through an empirical test for evi- dence on the aggregate excise and profits tax effects predicted specifically by the New View and not expected to occur un- der the Benefit View.

THE CONCEPTUAL FRAMEWORK OF

THE EMPiRICAL TEST

It would be difficult to prove that only the New View of property taxation is valid and to consequently disprove the Benefit View entirely. E!ven if evidence in support of the New View is found, the magnitude of this evidence rnay have been mitigated by off- setting effects predicted by the Benefit View. Therefore, a reasonable null hypoth- esis to test is that the New View is entirely Invalid. Rejecting this null hypothesis re- quires proof of the existence of the aggre- gate effects predicted specifically by the New View A rejection of this null hypothe- sis does not dismiss the possibility of ef- fects predicted by the Benefit View. As Wildasin (‘1986) has suggested, under irn- perfect zoning and imperfect capitalization, the choice between the New and Benefit Views may not be absolute and the prop- erty tax may best be c:onsidered a combi- nation capital tax and user charge. The ob- jective here is to look for empirical proof to support the claim that the property tax is, in part, a capital tax.

As shown earlier, under the New View, a national system of property taxation at dif- ferent local rates exerts two effects. Hold- Ing the amount of property in the country

140

I AN EMPIRICAL TEST OF THE “NEW VIEW”

constant, the profits tax effect depresses any owner’s per-unit rental rate (or per- unit market price) of property by the aver- age effective rate of property taxation in the country. Holding the amount of prop- erty constant in each jurisdiction, the pre- dicted excise tax effects are that local property tax rates above the national aver- age depress the per-unit market price of property further while local rates below the national average raise the per-unit market price above that indicated by the profits tax effect. Under the Benefit View of prop- erty taxation, the national average rate of property taxation and local deviations from this rate should have no effect on the per- unit market price of aggregate local tax- able property. Proof of an excise or profits tax effect is sufficient evidence to reject the null hypothesis that the New View of property taxation is invalid.

The prescribed empirical test is to seek evi- dence of a profits and/or excise tax effect on the per-unit market price of property and the amount of property in a city. The test presented here is motivated by Brueck- ner’s suggestion included in Mieszkowski and Zodrow (1989, p. 1131). Brueckner suggests that the tax effects predicted in the New View, and not the Benefit View, can be sorted out by focusing on interme- tropolitan rent differences. At an interme- tropolitan level, the Benefit View predicts that local property rents depend on con- struction costs, local expenditures per household, and other demand characteris- tics.’ As discussed earlier, with a local bud- get identity and assuming efficient produc- tion, how local revenue is raised, or the rate of local property taxation, should exert no influence on aggregate property value.* On the other hand, the New View indi- cates that the rate of property taxation ex- erts distinct profits and excise tax effects.

A problem arises in finding an appropriate measure of the per-unit aggregate price of property. The solution is that the market value of a community’s property, holding

141

the amount of property constant, is directly related to the per-unit aggregate market price of property. As given in equation 1, the aggregate market value of city i’s property tax base (PTB) is expected to be a positive function of the quantity (supply) of property-capital (K) and land (L)-in the city and a positive function of a J-length vector of variables (0,; where i = 1, 2, 3,

J) that determines the demand for property in the city:

PTB, = PTB(K,, L,, O,,,,

As shown using Figure 2, holding property constant, the New View predicts that the national average rate of property taxation (APT) and city i’s rate of property taxation less APT (DAPT) have a negative effect on the demand for property and hence on the market value of the property tax base.’ Under both the New View and Benefit View of property taxation, the level of local expenditure levels per unit of property (EXP) should increase property demand and PTB.” Assuming that property is a normal good, the level of individual income (Y) in the city would also increase property de- mand and PTB. If there is any shifting of tax incidence to producers, the existence of other forms of local taxation-a local sales tax (STAX) and/or a local income tax (ITAX)-could reduce property demand and PTB. Ladd and Bradbury (1988) point out that city property owners receive ser- vices in return for paying taxes to overlap- ping special districts, school districts, county governments, and state govern- ments. Ceteris paribus, this rate of overlap- ping government (OVTAX) should exert an additional influence on PTB.” A high rate of crime (CM) would reduce property de- mand and PTB. The city’s population (POP) represents the number of aggregate resi- dential property demanders. Replacing 0, in equation 1 with the just described vector of demand variables results in the follow- ing:

tent. A silnultaneous equation estimation is therefore necessary.“’

PTB, = PTB(K,, L,, DAPT,, EXP,, Y,, STAX,,

ITAX,, OVTAX,, CM,, POP,).

E.quatilon 2 does not include APT, because, in a cross section of cities, it is constant.lZ The prescribed test of the null hypothesis is to estimate equation 2 using a national sample of cities and to check the derived relationship between PTB and DAPT. If PTB is negatively Irelated to DAPT, the null hy- pothesis that the New View is entirely in- appropriate can be rejected.13

An additional problem to estimating equa- tion 2 is the ,ssmultanerty that exists among some of the explanatory variables. Capital (K) is endogenous because capital mrgra- tion into a city may be negatively related to the endogenously determined excise tax effect (DAPT). Controlling for local taxes, residential and business capital may also be attracted to a high service city (EXP). Hold- ng all else constant, residential capital is

(also expected to be larger in a high in- come (Y) city The difference between a city’s effective property tax rate and the average rate Iof national property taxation I(II) is expected to be greater the lower the city’s property tax base (PTB) and the Ihigher the city’s expenditure per unit of property (EXP)

A city’s expenditure per unit of property (EXP) is positively determined, in part, by its level of indrvidual income (Y). EXP may also be positively or negatively related to DAPT.14 Accounting for capital and labor complementanty in production, local per- sonal ilqcome (Y) is related to the amount and type of business capital (K) in the city. The marginal product of labor, and hence person,al income, should be larger the greater the arnount of capital in the city. If equation 2 is estimated without taking 1 hese endogenous relationships into con- sideration, the regression coefficients on the endogenous variables will be inconsis-

The first r>tep to estimate the system of si- multaneous equations is to specrfy, in gen- eral functional form, the four rernaining equations that represent the determination of the endogenous in equations 3-6:

variables. This is done

R K, = K(DAPT,, EXP,, Y,,, STAX,, ITAX,,

OVTAX,, AREA,, CM,, POP,)

R DAPT, = DAPT(PTB,, EXP,, STAX,, I-TAX,,

IGOV,, OVTAX,, SENR,,

OWN,, MAN&)

R EXP, = EXP(DAPT,, Y,, STAX,, ITAX,,

OVTAX,, IGOV,, CM,, SENR,,

CHILD,, EDUC,, MIANUF,)

R 0 Y, = Y(K,, SENR,, CHILD,, EDUC,, MANUF,)

As given In equation 3, besides the endog- enous relationships just described, local and state taxes could also drive out capital and cause it to be negatively related to a local sales tax (STAX), local income tax (IlAX), and the rate of overlappirlg taxes (OVTAX). The amount of residential and business capital in a city is likely to be pos- itively related to its square miles (AREA) and negatively rela ted to its crime rate (CM). The amount of residential capital is also positively related to the city’s popula- tion (POP)

As given I~I equation 4, the difference be- tween a city’s local property tax rate and the natiorl’s average rate of property taxa- tion is expected to be negatively related the availability of alternative tax ii-rstru-

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to

I AN EMPIRICAL TEST OF THE “NEW VIEW”

ments (STAX and ITAX), the percentage of a city’s revenue garnered from intergovern- mental revenue sharing (IGOV), and the degree of services (proxied by the degree of taxation) offered by overlapping jurisdic- tions (OVTAX). A city’s degree of property tax reliance should also be related to the percentage of residents over 65 (SENR) and the percentage of owner-occupied homes (OWN). Due to relatively larger property holdings, fixed incomes, and the lack of school-age children, senior citizens are more likely to direct city officials to limit property taxation. Homeowners, as op- posed to renters, may also be more likely to demand limited property taxation due to their perception of a direct tax burden. As Ladd (1975) and others have shown, the composition of the local property tax base should also have an impact on the rate of property taxation. Controlling for the size of the property tax base, a higher percent- age of people employed in manufacturing (MANUF) would indicate a larger manufac- turing property tax base and perhaps a tendency to rely less on property taxes due to the fear of driving more mobile manu- facturing firms-as opposed to less mobile commercial firms-out of the community.

As given in equation 5, a city’s expenditure per unit of property is also expected to be related to other local revenue alternatives (STAX and ITAX). Due to the general form of the EXP function, these relationships could be either positive or negative. Local expenditure per unit of capital should also be negatively related to the degree of sub- stitute expenditure offered by overlapping jurisdictions (OVTAX). EXP is expected to be positively related to the percentage of total revenue coming from outside grants (IGOV). The greater the value of IGOV, the greater the percentage of revenue raised through tax exportation to nonresidents. Though the direction of the influence is unpredictable, expenditure should also be influenced by exogenous forces that can be measured by the rate of crime (CM).

143

Using the standard model of a decisive voter, city expenditure would also be re- lated to the characteristics of this voter. These are proxied for by the percentage of the population greater than age 65 (SENR), the percentage of the population less than age 18 (CHILD), and the percentage of population with greater than a high school education (EDUC). The influences that these variables exert could take many ave- nues and are considered unpredictable. Though also unpredictable in direction, MANUF should also influence a city’s ex- penditure.

Equation 6 is a production function for lo- cal family income (Y). A predominantly older (SENR) or younger (CHILD) population should produce lower Y, while a more ed- ucated (EDUC) population should produce greater Y. Considering the greater value added in manufacturing, a larger MANUF could produce a higher Y. Alternatrvely, considering the economic decline in pri- marily manufacturing cities, a larger MANUF could predict a lower Y.

DATA, ECONOMETRIC ISSUES, AND

REGRESSION RESULTS

In the system of simultaneous equations, there are five endogenous variables (PTB, K, DAPT, EXP, and Y) and 13 exogenous variables (STAX, ITAX, OVTAX, IGOV, AREA, CM, SENR, OWN, CHILD, EDUC, HPLUM, HROOM, and MANUF).16 Each of the endogenous variable equations (2-6) is overidentified for both the rank and order conditions. The system can be estimated using the method of two-stage least squares (TSLS) and U.S. cities as the unit of observation.

Due to jurisdictronal differences in the rate of property assessment and variance in the accuracy of cities achieving their specific assessment ratios, it is difficult to get a property base measure that is comparable across U.S. cities.17 The quinquennral Cen- sus of Governments contains the solution

to the problem of property tax base com- parability. In the volume titled Taxable Property Valwes and Assessment--Sales Price Ratios, the U.S. Census Bureau re- ports the results of a survey that measures the average assessment to sales price ratio for real business and residential property in a select groulp of cities.18 The survey’s pur- pose was to Icorrect the comparability problem discussed earlier. Unfortunately, the survey was terminated after 1981 and real business property was excluded before 1966. The desired statistics are only avail- able for limited cities for periods 5 years apart between 1966 and 1981. I9 A pooled data set is necessary to obtain the neces- sary degrees of freedom.

T’he initial objective was to gather data from the 200 most populated U.S. cities in 1986.*’ It was only possible to gather the appropriate sales-assessment ratios for some of these cities To calculate PTB, it was then necessary to multiply each city’s sales-assessment ratio by its gross value of all locally assessed real property 21 Nonre- Iporting of this variable further reduced the original sample of 2100 cities. Table 1 con- tains the final sample of 62 cities included in one of the four cross sections:”

The effective rate of real property taxation in each city is equal to the property tax payments made to the city divided by the calculated PTB and rnultiplied by 1OO.23 The average rate of property taxation is measured as the mean effective property tax rate across all cilies in a cross section. Table 1 contains the calculated effective property tax rates for each city in each cross section.“4 Table 1 also includes the mean and standard deviation of effective property taxation in a given year. Notice the general decline in both of these statis- tics. DAPT equals the city’s effective prop- erty tax rate rninus the mean for that cross section .25

A further issue to consider is the appropri- ate proxy measure for the amount of city

capital. Two possibilities come to mind. The number of homes could roughly mea- sure the city’s residential capital, while em- ployment could approximate the city’s businesi capital. In the sample of cities, homes and employment exhibit a simple correlation coefficient of 0.982. Since both essentially measure the same vanation, the number of homes was chosen as the ap- propriate proxy for K. HOMES is a more di- rect measure and avoids the substitutability issue that arises if employment is used to proxy for business capital. If this measure is to be used effectively, local capital differ- ences that are not picked up by HOMES need to be controlled for. This is done by including the percentage of a city’s hous- ing that is owner occupied (OWN), the percentage of a city’s housing that lacks complete plumbing (HPLUM), the median number of rooms in a year-round housing unit in the city (HROOM), and a proxy for the percentage of a c:ity’s nonresidential capital that is used in manufacturing (MANUF). HROOM and MANUF should be related to a more valuable local capital stock. HPLUM should be related to a less valuable capital stock The effect of OWN on PTB is uncertain.

HPLUM is also included in the HOMES regressions as an approximation of the age and quality of the residential housing stock. An inferior housing stock (high HPLUM) may require, everything else con- stant, a greater number of housing units to serve a gtven population. The greater existence Iof inferior housing and the num- ber of rooms in the typical houslng unit may also provide information on residential taste for local expenditure. HPLUM and HROOM are therefore included in the EXP regression

An additional issue is the inclusion of pop- ulation (POP) as an explanatory variable in equations 2 and 3. POP and HOMES ex- hibit a sirnple correlation coefficient of 0.997. A city’s population and the chosen proxy for its capital base essentially mea-

I AN EMPIRICAL TEST OF THE “NEW VIEW”

TABLE 1 CITIES IN EACH CROSS SECTION (GIVEN BY EFFECTIVE PROPERTY TAX RATE)

City 1966 1971 1976 1981

1. Little Rock, AR 2. Birmingham, AL 3. Mobile, AL 4. Montgomery, AL 5. Phoenix, AZ 6. Tucson, AZ 7. Berkeley, CA 8. Fresno, CA 9. Glendale, CA

10. Long Beach, CA 11. Los Angeles, CA 12. Oakland, CA 13. Pasadena, CA 14. Sacramento, CA 15. San Diego, CA 16. San Jose, CA 17. San Francisco, CA 18. Torrance, CA 19. Denver, co 20. Bridgeport, CT 21. Washington, DC 22. Jacksonville, FL 23. Miami, FL 24. St. Petersburg, FL 25. Tampa, FL 26. Honolulu, HI 27. Des Moines, IA 28. Chicago, IL 29. Wichita, KS 30. Louisville, KY 31. New Orleans, LA 32. Shreveport, LA 33. Baltimore, MD 34. Detroit, Ml 35. Minneapolis, MN 36. St. Paul, MN 37. Kansas City, MO 38. St. Louis, MO 39. Omaha, NE 40. Charlotte, NC 41. Jersey City, NJ 42. Newark, NJ 43. Albuquerque, NM 44. Buffalo, NY 45. New York, NY 46. Rochester, NY 47. Cleveland, OH 48. Columbus, OH 49. Dayton, OH 50. Toledo, OH 51. Oklahoma City, OK 52. Tulsa, OK 53. Portland, OR 54. Philadelphia, PA 55. Pittsburgh, PA 56. Memphis, TN 57. Nashville, TN 58. Salt Lake City, UT 59. Norfolk, VA 60. Richmond, VA 61. Seattle, WA 62. Milwaukee WI

0.205 0.287 0.125

- 0.364 0.334 0.329 0.461 0.195 0.265 0.352 0.434 0.339 0.373 0.328 0.305 0.747 0.187 0.714 1.406 1.064 0.491 0.650 0.727

- 1.064 0.812 0.695 0.538 0.489

0.463 3.033 1.022 0.787 0.830 0.394 0.735 0.555 0.670 3.785 4.237 0.434 3.236 2.066 2.058 0.676 0.128 0.369 0.214 0.367 0.277 0.680 1.319 1.092 0.647 1.439 0.369 1.155 1.625 0.318 1.159

0.213 0.254 0.134 0.189 0.205 0.247" 0.601 0.466 0.218 0.306 0.449 0.540 0.393 0.554 0.332 0.336 1.541 0.211 0.527 1.705 1.431 0.638 0.704 0.449 0.606 0.831 0.886 0.680 0.770 0.407 0.345

- 3.058 1.163 0.784 0.717 0.352 0.638 0.601 0.641 3.881 5.069 0.548 1.710 1.677 1.720 0.607 0.099 0.318 0.120 0.371 0.324 0.617 1.086 1.300 0.755 1.014 0.130 1.230 1.794 0.273 1.107

0.270 0.124 - - - - - -

0.147a 0.089 0.161' 0.071 0.562 0.258 0.419 0.150 0.187 0.083 0.305 0.127 0.416 0.216 0.505 0.190 0.372 0.127 0.454 0.247 0.263 0.127 0.261 0.129 0.846 0.412 0.163 0.070 0.447 0.236 2.442 2.310 1.162 1.196 0.482 0.467

- - - - -

0.690 0.813a 0.563a 0.383 0.405 0.301

0.483 0.740 0.447 0.324 0.338 0.245

- 2.013 1.570 0.881 0.870

1.779 1.777 0.386 0.321

- 0.758 0.275

- 0.532a 4.291 2.397 0.407" 1.721 1.809 1.974 0.543" 0.086a

0.424 3.018 2.011 0.266 2.123 1.439 1.901 0.480 0.072

- 0.115" 0.351 0.148 0.555' 0.701 1.068 0.683" 0.853 0.154" 1.036 1.630

0.109 0.158 0.058 0.492 0.903 0.912 0.611 0.682 0.178 1.140 1.494

- - 1.111 0.662

Mean 0.855 0.848 Standard deviation 0.860 0.870

?mputed value: cross-sectional data not available for regression.

0.808 0.644 0.774 0.698

145

sure the same thing In equation 2, POP was dropped as an explanatory variable be- cause of the collinearity problem its inclu- sion would create with HOMES. In equa- tion 3, POP IS not included as an explanatory variable of HOMES because of collinearity with lagged (HOMES) whose in- clusion will be discussed.“6 Land (L) is mea- sured in square miles (AREA). A city’s cnme rate (CM) is calculated as the number of crimes per home. A city’s level of income (Y) is measured by the city’s median family income.

Substituting the variables just discussed into the original system of equations (2-6) and dropping POP yields the following re- vised system :

P-I-B, = PTB(HOMES,, DAPT,, EXP,, Y,,

ST,4X,, ITAX,, OVTAX,, AREA,, CM,,

OWN,, HPLUM,, HROOM,, MANUF,)

HOMES, == HOMES(DAPT,, EXP,, Y,,

ST,4X,, ITAX,, OVTAX,, AREA,,

CM,, HPLIJM,)

DAPT, == DAPT(PTB,, EIXP,, STAX,, ITAX,,

OVTAX,, lGOV,, SENR,, OWN,, MANUF,)

m EXP, = EXP(DAPT,, Y,, STAX,,

ITAX,, OVTAX,, IGOV,, CM,, SENR,,

CHILD,, EDUC,, HPLUM,,

HROOM,, MANUF,)

Y, = Y(HOMES,, SENR,, CHILD,,

EDUC,, MANUF,).

Table 2 contains a description of all vari- ables and a list of sources. Table 3 con- talns descriptive statistics for all variables.

There are a few econometric issues to con- sider before equations (7-l 1) can be esti- mated. Along with the right-side variables specified previously, city or regional specific influences that do noit change over time (flxed effects) are also irnportant City property values, property bases, reliance on the property tax, and expenditure levels can all be influenced by time-invariant poli- tics, laws, institutions, historical factors, cli- mate, location in country, etc. City income could also be influenced by compensating differentials, labor market peculiarities, and some of the same timle-consistent factors just mentioned. In a pooled regression with many cross-sectional units and a few time series performed on stock-dependent vari- ables, sue h city-specific effects could be crudely p:oxred for by regional dLlmmies and climate variables Ibut never fully con- trolled for.27 As suggested by Holtz-Eakin (1986), a solution is to estimate the regres- sions using the first differences of each variable’s observatlons.2E’ This was accom- plished by restricting the 62 city clata set to cities in which observations were avail- able for contiguous cross sections. Sub- tracting 1966 values from 1971 values, 1971 from 1976 values, and 1976 from 1981 values yielded a new poolecl data se- ries of three cross sections consisting of 134 observations. A “difference” variable is delineated from the previous stock vari- ables by a “I)” after the stock variable’s name. The interpretation of the differenced regression coefficients is no different than if they were stock regression coefficients.

A second econometric issue is that equa- tion 8 represents a housing stock equation. A partial-adjustment model of housing was used to account for the inertia in a city’s housing stock.*’ A third econometric issue relates to Ihe two-stage estimation process. To derive consistent estimators for the coefficient!, on the endogenous variables in

I AN EMPIRICAL TEST OF THE “NEW VIEW”

TABLE 2 VARIABLE DESCRIPTION AND SOURCE

Name Description Sourcea

Endogenous:

PTB HOMES DAPT EXP Y

market value of all real property number of year-round housing units (effective real property tax rate-“APT”) in percent total city general expenditure/“HOMES” median family income

CENGOV CCDB* CENGOV CGF CCDB* and DCEN*

Exogenous:

APT STAX ITAX OVTAX IGOV

AREA CM OWN SENR CHILD EDUC HPLUM HROOM MANUF D8176, etc.

city’s average effective property tax rate in percent CENGOV dummy if city general or selective sales tax CGF dummy if city income tax CGF overlapping state, county, school taxes/“HOMES” CENGOV, SGF (city’s intergovernmental revenue/general revenue) in per- CGF

cent square miles (serious crimes known to police/“HOMES”) in percent housing units owner occupied in percent population greater than age 65 in percent population less than age 18 in percent population high school graduates in percent housing lacking adequate plumbing in percent median number of rooms in year-round housing manufacturing employment in percent dummy for 1981-1976 cross section, etc.

CCDB* UCR, CCDB* CCDB* CCDB* CCDB* CCDB* CCDB* DCEN* CCDB*

Weighting:

POP population

%ENGOV = Census of Governments, 1966, 1971, 1976, and 1981; CCD8 = City and County Databook, 1968, 1978, and 1988; CGF = City Government Finances, 1966, 1971, 1976, and 1981; SGF = State Government Finances. 1966, 1971, 1976, and 1981; DCEN = U.S. Decennial Census (various volumes), 1960, 1970, and 1980; and UCR = F.B./.‘s Uniform Crime Report, 1966, 1971, 1976, and 1981.

DCEN*

All variables measured in dollars have been deflated by the appropriate U.S. GNP deflator. A local CPI deflator was not used, because part of the variation in local consumer price; is.due to the housing component of the CPI. Deflating by CPI would rem&e much of the variation that the empirical work is attempting to-explain. An asterisk (*) indicates- that the variable was riot available for the desired years of 1966, 1971, 1976, and 1981 and was calculated from 1960, 1970, and 1980 census values by interpolation and extrapolation.

A “D” follows variable names to indicate the 5 year difference in value. An “L” follows to indicate the lagged value of the nondifferenced variable for the particular cross section.

the second stage, the first-stage instru- ments must each be uncorrelated with the second-stage error term. Candidates for the required instruments are all 13 exoge- nous difference variables and the initial val- ues of all endogenous and exogenous vari- ables. To test the requirement that the candidates for instruments are uncorrelated with the second-stage error term, a form of the Hausman (1978) test was used.30

(D8176, D7671, and D7166). If a set of dummies was jointly significant, they re- mained in the regression. These dummies are intended to control for time-specific conditions, such as the average rate of property taxation in the country (APT) and macroeconomic effects, that would be common to all jurisdictions but not con- trolled for by dlfferencing.3’

To estimate the system, the three differ- enced cross sections were pooled together. The regressions were initially run without a constant and with a set of three dummies

147

The final econometric issue is heteroske- dasticity. In studies of this sort, residual variance is often related to some measure of relative size. If this is not corrected, cal- culated standard errors are biased and t-

TABLE 3 VARIABLE DESCRIPTIVE STATISTICS

----- .----__ .--- --.- Coefficient

of Value where Variablle Mean Variation Maximum Minimum DAPT is Maxa _-~---- .--- Endogenous:

PTB 1.579E+ 10 2.15 HOME!; 246005.00 I .74 DAPT 0.02 36.75 absolute (DAPT) 0.57 I .06 EXP 1869.00 0.70 Y 23942.09 0.15

Exogenous:

2.575E-t ‘I 1 1.822E+9 4.04E+9 .2943 I 5 I .oo 19723.00 126776.00

4.22 -0.75 4.22 4.22 0.02 4.22

8799.43 611.88 3641.77 36882.50 14417.38 19730.44

APT 0.79 0.10 STAX 0.98 0.29 ITAX 0.20 2.00 OVTAX 3202.49 0.41 IGOV 30.14 0.49 AREA ‘I 25.50 1.15 CM 17.35 I .02 OWN 50.Q3 0.22 SENR 1 I .S6 0.27 CHILD 29.02 0.16 E.DUC 57.46 0.23 HPLUM 4.28 0.92 HROOM 4.78 0.09 MANUIF 26.013 0.55

Weighting:

0.86 0.65 0.85 1 .oo 0.00 1 .oo I .oo 0.00 0.00

6187.23 0.00 3464.10 76.88 0.61 33.31

765.13 IO.36 23.56 247.89 4.47 27.42

71.22 20.56 20.56 30.21 4.38 8.08 38.36 15.02 37.07 87.46 21.10 34.34 17.82 0.50 5.14

5.68 3.48 4.20 91.44 5.07 35.19

POP 649105.32 1.71 ‘7850132.00 101901 .oo 313547.00 ---- --- .------.-- “DAPT was a maximum 01 4.22 in the city of Newark, NJ in 1976. The descriptive statistics are based on 209 observations from 1966, 1971, 1976, and 1981.

tests of statistical significance are invalid. Using different forms of the Glesjer test, heteroskedasticity in relation to HOMES or POP was detected in all regressions and they were re-estimated using the appropri- .ate weight.32

The final results of tihe estimation of equa- tions (7-1 1) are reczrded in Table 4.33 The <jet of dummies representing each differ- Ienced cross section was jointly statistically ‘significant in each regression except EXP. ‘These dummies capture all cross-sectional (effects not represented by other right-side lvariablles and hence include the effect of the difference in the average rate of na- tional Iproperty taxation (APTD). It is note- vdorthy that, In the IPTBD regression, the coefficients on the cross-sectional dummies continually inlzreased frorn the D7166, to zhe D7671, to the D8176 cross section.

The coeffjcients in the HOMESD regression increased from the D7671 to the D8176 cross section. Though1 there are other con- founding effects, these are the patterns ex- pected from the New View’s profits tax ef- fect since the average 11.5. rate of property taxation continually declined over this pe- riod.34

In all regressions, except the PTBD and HO- MESD regressions, all statistically significant coefficients displayed the signs predicted earlier.35 An unexpected finding in the PTBD regression was the sign on the HROOMD coefficient. The negative influ- ence of a greater median number of rooms in housing may be due to the room number acting as a negative proxy for the age of a city’s housing stock. As evidence, for all cities in the sample, the average value of HROOM declined from 5.4 in

148

I AN EMPIRICAL TEST OF THE “NEW VIEW”

TABLE 4 FIRST-DIFFERENCED-WEIGHTED TSLS REGRESSION RESULTS

Right-Side Variable

PTBD (HOMESLO.‘)

Dependent Variable (Weight)

HOMESD DAPTD EXPD (POPD) [(I /POPL)O 51 [H~MESL] [(I ,Pyd)pL)O 5]

PTBD

HOMESD

DAPTD

EXPD

YD

STAXD

ITAXD

OVTAXD

IGOVD

AREAD

CMD

SENRD

CHILDD

EDUCD

OWND

HPLUMD

HROOMD

MANUFD

90953.397” (33545.118)

-3.243E+gb (1.625E+9)

-682346.520 (955030.940) 534928.1 70b

(284616.230) 2.034E+9

(l,BOBE+9) 2.723E+9

(2.754E+9) 301958.600

(420192.750)

-1144884.100 16.251 (4332527.600) (27.245)

-26048367.000 125.713’ (51379698.000) (79.411)

93740888.000 (173554328.000)

-1.46lE+8 (1.40lE+8)

-5.180E+ga (2.051 E+9) 3.462E+8

(5.485E+8) (LAG) HOMESD

D7166 -3.600E+gb (1.6lOE+9)

07671 1 .008E+gC (0.715E+9)

08176 1.904E+9 (0.492E +9)

-5561 .073a (2121.780)

1.1 lZC (0.789) 0.239

(0.245) 9378.803b

(5767.007) 6525.946

(8949.168) -4.02Ba (0.922)

B90.43ga (194.968)

0.422a (0.023)

14121.220a (3246.926) 1317.48Sb (738.968)

4002.554” (744.596)

-5.235E-12a (2.128E-12)

1.798-4” (0.49BE-4)

-0.131 (0.165)

-0.267b (0.118) 6.396E-05

(5.259E-05) -0.007b (0.003)

-0.181a (0.066)

-0.008 (0.025)

0.006 (0.009)

-0.067 (0.116) 0.126b

(0.056) 0.215”

(0.082)

O.OOsb (0.003)

209.726 (260.378)

0.074b (0.040)

-402.208 (402.004) 732.128

(867.897) -0.12Sb (0.063) 14.907a (4.258)

7.658 (8.423)

-72.308 (74.242)

-33.273 (40.596)

-29.28Sb (17.314)

-29.298b (17.312)

-646.676b (296.566) -22.910’

(7.450)

- 693.828” (I 77.639)

-736.065 (91.933y 105.832a (54.427)

- 28.980' (22.749)

1341 .653a (325.595)

-4141 .590a (426.414)

-2867.06Sa (434.875)

Adjusted f?* 0.248 0.935 0.726 0.337 0.857 F-Statistic 2.64ga 1 58.053a 33.58ga 7.124a 114.797”

Two-tailed statistical significance: a99% or greater, b90-98%, and ‘80-89%; all regressions use 134 observations.

149

1960 to 4.7 In 198(1.36 An additional unex- pected finding in the HOMESD regression is the significant positive influence of the effect of putting a local sales tax in place. This result may be due to the positive capi- talization of the inital expectation that this action signals lower property tax increases 111 the future.37 Also, in the HOMESD regression, the coefficient on the number Iof crimes per household was surprisingly 3ositive. A feasible explanatron is that the (crime measure may proxy for other positive characteristics’ that attract new housing to a city.

Other Interesting and statistrcally significant findings are that the greater the percent- age of housrnig units with inferior plumb- rng (HPLUMD) and the greater the median number of rooms in these housing units (HROOMD), the less local expenditure per housing unit. HPLUMD and HROOMD were Intended to measure restdential tastes, and it appears that the greater the propensity for residents to live rn inferior and greater roomed housing (which, as shown in the fW3D rlegression, is ltkely older and less valuable), the less local expenditure per house Iprovided them. Also, as the percent- age of local workers employed in manufac- turing increases (MANUFD) and the per- centage with high school diplomas increases (EDUCD), the city’s total expendi- ture per unit of capital decreases. Per unit of property tax base, commercial or retail outlets likely require greater infrastructure and police expenditure than manufactur- ing. A greater percentage of high school grads likely reduce a city’s social service spending. Finajlly, MANUFD had an overall negative influence on the change in local median family rncome (YD). Cities whose ernployment was more concentrated in manufacturing lost family income during this period, ceteris paribus.

Calculated at the mean for each variable and at the maximum observed value for DAPT, Table 5 lists, in the appropriate row and column element, the elasticities for all

significant coefficrents.38 The elasticities from the DAPTD regression should be of particular interest to policymakers, because they indicate local characteristics that have caused a large U.S. city to rely cm a higher than average rate of property taxation. Evaluated at the mean, a 1 percent in- crease in the value of the local property tax base causes only a 0.15 percent de- crease in the difference between the city’s effective rate of property taxation and the nation’s average rate. A similar increase in local expenditure per house causes a larger 0.59 percent Increase in the average city’s reliance on property taxes. The response, evaluated at the mean, of a 1 percent in- crease in the percentage of senior citizens in a city IS a very elastic 3.67 percent de- crease in DAPT. If the average city adopted a local income tax or experienced a 1 per- cent increase in the percentage of local revenue coming from intergovernmental sources, its reliance on the property tax would respectively decline by 0.4’7 and 0.39 percent. In the city with the greatest reliance on the property tax, the response in the change in property tax reliance is much smaller in absolute terms than the responses evaluated at the mean.

Concerning the proposed null hypothesis, the evidence required to reject the state- ment that the New View is entirely without merit exists. The regression using PTBD as the dependent variable Indicates that a 1 percent increase in the difference in the rate of property taxation above the na- tional mean, ceteris paribus, would cause a 0.13 percent decrease in the average city’s per-unit market value of real property. The direction of this finding is the result pre- dicted by the excise tax effect of the New View of property taxation. Under a pure Benefit View of property taxation, the rate of property taxation should not influence PTB.

As the New View has been described in Figure 2, a 1 percent inc:rease in a city’s DAPT, holding property constant, should

150

I AN EMPIRICAL TEST OF THE “NEW VIEW”

TABLE S ELASTICITIES OF STATISTICALLY SIGNIFICANT VARIABLE9

Right-Side Variables PTB

Dependent Variables HOMES

(short run)b DAPT EXP Y

PTB HOMES DAPT EXP Y STAX ITAX OVTAX IGOV AREA CM SENR CHILD EDUC OWN HPLUM HROOM MANUF

1.42 (2.85) -0.13 (-3.39) -0.01 (-0.18)

0.812.61) 0.01 (0.03)

- 0.04(0.07) - - -0.05(-0.11)

- - 0.010.02)

-

-1.5775.39) 0.02 (0.04)

-

-0.15 (-0.01) 0.05 (0.04)

- 0.59 (0.16)

0.94 (0.40)

-0.47(-0.06) -

-0.39(-0.06) -0.21-0.11)

0.24 (0.13)

- -3.67 (0.34) - -0.33 (-0.28)

-0.90-0.28) -0.89 0.25 (-1.38) (0.18) -

-0.07 (-0.04) - 1.65 (-0.75)

- -0.32 (-0.22) -0.03 (-0.05) ‘Initial values in the cells of the table represent the elasticity calculated at the mean (for DAPT, these elasticities are calculated at the mean of the absolute value). Values in parenthesis represent the elasticity calculated at the maximum observed value of DAPT. For ITAX and STAX, the elasticity is represented as the percentage change in dependent vari- able given the implementation of the local tax. % calculate the corresponding long-run elasticities, divide the given value by 0.58.

be fully capitalized into a 1 percent de- crease in PTB. A positive excise tax effect shifts the city’s property demand curve down a perfectly inelastic supply curve and drives the city’s property value down by the full amount of the effect. There are likely two related reasons for the elasticity calculated here being less than one. The first is the use of a proxy to control for the short-run perfectly inelastic supply of capi- tal. HOMES, even including the various control measures, is an imperfect measure of firm and even residential capital. This creates an elasticity to the supply curve that can cause the calculated DAPT elastic- ity of PTB to be less than one. A second reason is the use of proxy variables to con- trol for local property demand. If property demand is not held constant after an in- crease in DAPT, the regression result will pick up the effect of mobile consumers that could leave the city after the increase in property taxes. If this occurs, there is a mixture of backward shifting of the prop- erty tax increase to land and fixed capital (captured in lower property values) and

151

forward shifting to imperfectly mobile con- sumers (not captured in lower property val- ues). Allowing for full adjustment of prop- erty supply and demand, Mieszkowskr’s (1972) original conjecture was that approx- imately 25 percent of the excise tax effect would be borne by immobile factors. The partial capitalization result of 13 percent is consistent with the imperfect measure of property supply and property demand and Mieszkowski’s conjecture.

The excise tax effect of the New View also predicts that a local property tax rate above the national average should, in the long run, reduce the amount of mobile capital in the city. As given by the signifi- cant negative effect of DAPT on HOMES, there is evidence of this occurring in the chosen sample of cities. After 5 years, the percentage decline in HOMES, after a 1 percent increase in DAPT, was only a very inelastic -0.01. Allowing for full adjust- ment, the long-run elasticity was still only -0.02 (-0.01/0.58). The very small DAPT elasticities of HOMES connotes that, If cap-

ltal mobility is the mechanism that equal- izes differences in property rental rates across cities, then these differences will persist3’ Although the excise effect of property taxation does drive capital (as measured by number of residential homes) out of a city, there is no empirical evidence here to indicate that movements in hous- ing capital are very responsive to differ- ences in local property tax reliance. This re- sult calls into doubt the primary assumption of the Traditional View of property taxation that, at a nationally de- termined rental rate (I;v), there is a per- fectly elastic supply of capital to all cities. This could only occur if capital were per- fectly mobile between all cities in the short run. The implication of capital immobility in regard to the incidence of the property tax is discussed in the conclusion.

The pertinent finding to consider is the sta- tistically significant negative effect of DAPT on PTB and HOMES. These negative effects vvere robust across all cross sections and support the rejection of the proposed null hlypothesis thatt the New View is entirely invalid.“’ The excise tax effect’s negative capitalization result is similar to previous Oates’ type results where property tax rates, holding all else constant, lower ag- gregate local property values. The impor- tant difference here 1’5 that the New View’s predicted excise and Iprofits tax effects exist for both the per-unit value of property and the number of units of property In large cities drawn from a national sample.

SIMULATIONS REGARDING AN IN-

CREASE IN THE PROPERTY TAX AND

REVENUE ALTERNATIVES TO IT

Using the regrlession results, rt IS possible to examine the effect that a purely exoge- nlzus 1 percent increase in the difference between the average city’s property tax rate and the national average rate would have on other endogenous variables in the simultaneous system. An increase in this

property tax dlfferentual can possibly have direct and indirect effects. The direct effect occurs if DAPT directly influences an en- dogenous variable. The indirect effect oc- curs if DAPT effects one of the four re- maining endogenous variables that, in turn, influences the endogenous variable under question. To conduct the proposed simulations, only the statistically significant variables vvere considered to exert any in- fluence.

Reading across the DAPT row in Table 5, evaluated at the mean, a 1 percent in- crease in DAPT causes a 0.13 percent de- crease in the typical city’s property value and a 0.0’1 percent decrease in the short- run (5 year) change in the number of homes. This exogenous change would dt- rectly reduce PTB by 0.13 percent. Through an induced decrease in the numbler of homes, it would also indirectly decrease PTB by a 0.014 (1.42 multiplied by 0.01) percentagcl in the short run and 0.028 (1.42 multlplied by 0.02) percentage in the long run. The total effect would be a 0.144 percent decrease in the value of the city’s property tax base in the short run and a 0.158 percent decrease in the long run. The effect on the city with the great- est reliance on property taxes would be a more elastic short-run decline of 3.90 per- cent in unit property value and 0.18 per- cent in HOMES. These short-run effects, along with others, are recorded in Table 6.

As the Benefit View of property taxation requires, even after accounting for the in- duced local expenditure increase that could follow an increase in local property taxes (but does not in this data set), the per-unit value of local property and its amount de- clines in both the short and long runs fol- lowing the property tax Increase. This again indicates that, in part, the property tax does act as a capital tax. The depres- SIVE? effect of the New View’s excuse tax ef- fect on capital is not much larger in the long run than in the short run.

1 ii2

I AN EMPIRICAL TEST OF THE “NEW VIEW”

TABLE 6 RESULTS OF POLICY-RELEVANT SIMULATIONS

DAPT STAX ITAX OVTAX IGOV

PTB HOMES

-0.14 (-3.90) -0.01 (-0.18) 0.06 (0.20) 0.04 (0.07) 0.06 (0.20) 0.005 (0.01)

-0.07 (-0.31) -0.05 (-0.11) 0.05 (0.20) 0.01 (0.02)

DAPT

1.02 (1.03) 0.00 (0.00)

-0.47 (-0.06) -0.12 (-0.02) -0.24 (-0.04)

EXP

0.00 (0.00) 0.00 (0.00) 0.00 (0.00)

-0.21 (-0.12) 0.24 (0.13)

The ceils in the table represent the percentage change in each column’s variable after a 5 year period if, during that same period, there was an exogenous 1 percent increase in the given row variable (DAPT, OVTAX, or IGOV; or the implementation of a STAX or ITAX). Initial values are calculated at the mean. Values in parentheses are calculated at the maximum value of DAPT.

Perhaps because of an implicit understand- ing of the destructive effects of a relative over-reliance on property taxation, local policymakers have increasingly looked for revenue alternatives. As recorded in Table 1, both the mean and standard deviation of effective property taxation in this sample of large U.S. cities declined almost contin- ually between 1966 and 1981. A largely untapped alternative to local property taxes is the use of local income taxes. In the chosen set of cities, 10 out of 62 (16 per- cent) used a local income tax in 1966. This figure only grew to 16 out of 62 (26 per- cent) cities in 1981. Of interest to policy- makers looking for local revenue alterna- tives would be a full simulation of the total effect on the average large U.S. city that decided to adopt a local income tax. As re- corded in Table 6, adopting a local income tax would, (1) increase real property values by 0.06 percent, (2) increase the number of homes by only 0.005 percent, (3) de- crease the differential between the city’s rate of property taxation and the national average rate by 0.47 percent, and (4) have no measurable effect on a city’s expendi- ture per house.

Another local revenue alternative is sales taxation. Large cities in the United States have already used this alternative to a much larger degree. In 1966, 55 out of the 62 (89 percent) large U.S. cities in the sample had either a personal or selective sales tax. This figure grew to 59 out of 62 (95 percent) of the cities in the 1981 sam-

153

ple. A simulated adoption of local sales taxation would increase the value of a city’s property tax base by 0.06 percent, which is the same as the city adopting a local income tax. The same adoption of a local sales tax would increase the number of homes by 0.04 percent in the short run, which is about eight times the magnitude of an adoption of local income tax. In this sample of large U.S. cities, the adoption of a local sales tax had no effect on decreas- ing local reliance on the property tax.

Another option available to higher govern- ments wishing to reduce local property tax reliance would be to increase intergovern- mental revenue shared with cities. Over the period of observation, this was occurring. In 1966, the median value of the percent- age of local revenue that came from higher governments was 10 percent. By 1981, this figure had risen to 16 percent. The effects of Increased revenue sharing to the average city can be approximated by simulating the result of an exogenous 1 percent increase in the percentage of the average city’s budget coming from inter- governmental grants (IGOV). The simula- tion process is similar to that discussed ear- lier, and the results are again in Table 6. As expected, an infusion of outside money would have a positive effect on the per- unit value of property, homes, and expen- diture per home in the sample of U.S. cities. Evaluated at the mean, a 1 percent increase in IGOV would also have the de- sired effect of reducing DAPT by 0.24 per- cent.

A 1 percent increase in overlapping taxes (OVTAX), holding other exogenous vari- ables constant, decreases local reliance on the property tax and reduces local expendi- ture per house, because services once pro- vlded by the community are now being provided by outside governments. Local policymakers ‘jnould note that the overall effect of this change to the average large IJ.S. city is a 0.07 percent decline in unit property value and a 0.05 decline in homes. City officials not only need to be concerned about their own rate of local taxation, but also the rates imposed by overlapping governments The negative ef- fects of greater fiscal activity outside the city are even greater in the most property tax reliant city.

Local plolicymakers woulcl generally look upon the simulated rlesultr of reducing the reliance on property taxes favorably and hence these results should be of interest to them. As demonstrated, 1r-1 order to benefit property, this reduction needs to come from an exogenous source (statewtde property tax limitation holding other vari- ables constant), through an increase In rev- enue sharing, or through the implementa- tion of a less burdensome? sales or income tax. In the current political climate and due to the fact that most large U.S cities have local sales taxes of one form or another, the option of adopting a local Income tax is probably the most realistic alternative. As demonstrated by the responses in Table 6, it 1s also one of the most effective.

Cmclusions

Clonsidering thle evidence just given, a con- clulsion to reject the null hypothesis that the New View of prol:)erty taxation is en- tirely invalid is appropriate. The reported regression resulis and simulations provide evidence that local property taxes affect lo- cal property values in the manner predicted by the New View and are not possible un- der a pure Benefit View of property taxa- tion. Due to the increasing magnitude of

coefficiems on the cross-sectional dummy variables In the property tax base and homes’ regressions, there is the necessary, but probably not entirely sufficient, evi- dence of !he New View’s profits tax effect. There is much stronger evidence in support of the New View’s excise tax effect. Ceteris paribus, a greater than average reliance on property taxes reduces property value and drives out property. The effect on property value is much larger than both the short- and long-run effects on property mobility. As shown using a full simulation, these ex- cise tax effects occur even after allowing for the benefits from the increased expen- diture that could follow a property tax in- crease.

Note the effects of a greater than average reliance on the property tax. As shown here, such an overreliance drives down lo- cal per-unrt property values and slightly de- creases the amount of property in the city. Since there is evidence in support of the New View’s tax effects, at least a portion of the property tax falls on all owners of property throughout the United States. The property tax is, in part, a capital tax, or a progressive form of taxation.

Note also the finding that, based only on local property tax differentials, housing capital displays little mobility between large U.S. cities. The excise tax effect on local property rental rates (or local property val- ues) is likely to persist, because without deterioration, mobile capital is the instru- ment necersary to equalize property rental rates across cities. Owners of property in higher that-1 average property tax cities will earn lower property rental rates than own- ers of the same property in lower than av- erage property tax cities. If, as Mieszkowski and Zodrow assume, property ownership is not restricted to city of residence, this find- ing has no Importance to the progressivity or regressivty of property taxation. But, if like homeowners, all property owners re- side in the city in which they own prop- erty, a high rate of local property taxation

I AN EMPIRICAL TEST OF THE “NEW VIEW”

reduces their property value. The income incidence of the property tax can then be examined by finding the relationship be- tween local property reliance and local in- come. For the entire sample of cities, the correlation between DAPT and local me- dian family income is -0.34. Given this correlation and the little mobility displayed by capital, the excise tax effect of an in- crease in property taxation on the owner of a home residing in one of these large cities is regressive.4’

This paper’s empirical results call into ques- tion the Traditional View that property taxes are regressive and the Benefit View that the incidence of property tax is of lit- tle concern. Though there is evidence that the property tax distorts capital decisions, further empirical research of the type pre- sented here is necessary before a definitive conclusion on the portion of the property tax best considered a capital tax and the portion best considered a user fee is drawn. Further empirical research is also necessary to distinguish between different forms of capital and the residence of capi- tal owners before a definitive statement on the incidence of the property tax is also made. The hope is that the ideas and methods presented here offer some guid- ance to this necessary future research.

ENDNOTES

A version of thus paper was presented at the 56th annual meetrng of the Mrdwest Economrc Assocratron Wassmer

rece’ved funding from, and IS also a faculty associate of,

Wayne State Unrversity’s College of Urban, Labor, and

Metropolitan Affairs (CULMA) Phil Grossman, three anon

ymous referees, and participants at a Wayne State semr-

nar provided valuable comments Pnya Rajagopalan as-

sisted In data gathering All remarnrng errors are my own

’ The Appendix contarns all figures and tables

* This excise tax effect could also cause lower wages and

higher consumer prices In the high-type city

3 The reasons for this farlure of the Tiebout model have

been widely discussed In the literature and Include admrn

rstratrve and sprllover costs that prevent less than the cre-

at’on of N d’fferent crtres for each of the N d’fferent

types of demanders of the local tax and expendrture

package and rnttial taxable property differences that

would cause cities to raise property taxes more or less

155

than the demand differentral exhrbrted by the crty’s rest-

dents Capital demanders In even a homogenous commu-

nrty could Increase utilrty rf moving costs are relatrvely

small

4 If capital demanders are rmmobrle (homeowners and firms

who refuse to move based on differences In property

rental rates), the caprtal rental rates paid by demanders In

the hrgh-type city would be greater than those paid by

demanders In both the medium-type crty, and the low-

type city Given thus scenario, rmmobrle consumers of cap-

ital would share the burden of the tax along with per-

fectly rmmobrle land Thus likely occurrence was predicted

by Mreszkowski (1972) and IS reflected In the regression

results drscussed later In the paper

5 As an example, Goodman (1983) has shown In empmcal

work using the New Haven SMSA that intrajunsd’ctronal

tax and expendtture drfferentrals among communrtres are

caprtalrzed Into local aggregate property values at a rate

that vanes between 53 and 97 percent

e See Yinger (1988) for an excellent summary of thus emprn-

cal work

7 If perfect mobility among Junsdrctrons occurs, then utrlrty

levels of property consumers must be equal ‘n all lunsdrc-

tions, property demand IS the sole determtnant of prop-

erty values, and none of the New View’s excuse tax effects

can occur This IS Brueckner’s reason for focusing on an

‘ntermetropolrtan set of crtres where mobrl’ty IS ltkely to

be less than perfect

a Offsetting caprtal’zatron effects do occur to rndrvidual

properties (see Brueckner (1979) for further drscuss’on)

’ A pure Benefit Vrew of property taxation would Indicate

that APT and DAPT exert no effect on PTB

lo The true determinant of local property demand IS the rel-

ative qualrty of locally provided servrces. EXP IS only a

crude proxy of th’s The drffrculty, even ‘mpossrbrl’ty, of

gathering a measure of local service quality that IS fully

comparable across all crtres and all years regretfully pre-

vented a better proxy As an alternative, the crime rate IS Included to partrally measure the qualrty of service delrv-

ery Ladd and Bradbury (1988) used a srmrlar approach First drfferencrng should also make this compromrse more

acceptable

” OVTAX IS Intended to be a proxy for the amount of over-

lapping taxes that a untt of K would pay ‘n the city It will

be measured as state plus county plus school drstnct own-

source revenue in the city’s state divided by the units of K

in the state Due to the drffrculty ‘n drscernrng their pres-

ence and the relatively small amount of revenue Involved

during the period under consrderatron, overlapprng special

drstncts were not Included As directed by Ladd and Brad-

bury (1988). if a city IS respons’ble for school drstnct and/

or county functions, the appropriate revenue measure

was removed Since overlapprng tax rate and service delrv-

ery measures are excluded, OVTAX may have either a positive or negative Influence on PTB

‘* Even In a pooled analysis of many crtres and few cross

sectrons, the effect of APT WIII be confounded by other

effects constant across a cross section To assess the true

effect of APT, it would be necessary to perform a time-se-

ries analysrs on one city Data avarlabrl’ty prohrbrts the

gathenng of a t’me series of suffrcrent length Cross-sec-

ttonal dummres wll later be used to control for the effect

of APT

l3 The coeffrcrent cn DAPT III any regresson would be the

same as the coefficient or’ a var’able that ‘measured the

effective rate of local property taxation, though the calcu-

lated elastrcrtres ,would be different It IS Incorrect to as-

sume that the use of DAPT is the only thing that sepa-

rates thus study from previous studies The differences tn

order of lrnportance are separate regress’ons for PTB and

K, Improved ecoinometnc techn’ques, and thle use of a

nattonal sample

“’ The value of EXP IS lo’ntly related to supply and demand

forces A high EXP may require a high DAPT (supply side)

or a high DAPT rnay reduce EXP (demand side)

“’ Wassmer (1990) hias d’scussed the bras that results If SI-

multane’ty IS Ignored He demonstrated, as others have

before h’m, that the reversal In the earlier belief that local

ftscal vanables do not rnfluence f’rm locatron was largely

due to not accountrng for srmult,~nerty In regression tests

on this Issue Wales and Wrens (1974) also point out that

a local budget ‘dentrty makes local expendrtures, property

tax rates, and property tax bases endogenous Estimated

correlai’ons may be spur’ous If endogenerty IS not con-

trolled for

‘I’ POP, contalned III equat’o% 2, 3, and 5, hd5 been ‘g-

nored In the tally of endol3enous and exogenous van-

ables Reasons for this and the lr’clus’on of the percent-

age of city hous’ng lacking adequate plumbrng (HPLUM)

and the medran number ci’ rooms In year round housing

(HROOM) are d’sc.rssed later

’ ’ For a d’scussron or this, see F’shier (1988, ch 7)

“r For assessment purposes, local property IS divided Into

“real” <and “personal” components Real property ‘ncludes

land and burld’ngs Def’nrt’ons of taxable personal prop-

erty vary by city bJt can Include equipment, Inventories,

motor vehicles, and household property

“’ The 1966 survey 1s based :)n “ordinary real estate,” later

surveys are based on “total real property ” In readrng the

definrt’ons of these two var’ables. It I!, drff’cult to drscern

a majo’ difference and they are assurned to be the same

*(’ As observed by Frschel (1992). the Benefit View’s fiscal

zoning IS, In reality, best applred m suburbs but, ‘n theory,

It could occur anywhere As drscussed rn Hamilton (1976).

the Benefit View’s fiscal caprtalrzatron occurs whenever

demanders of property arc fully rnobrle between junsdrc-

trons As discussed earl’er, rmmobilrty IS more l’kely to ex-

1st at the rntermet,opolltarl level Evidence In favor of the

New V~ew’s tax effects should be found in a national data

set An Ideal emprncal test would include crt’es of all

types Large c’t’es were chosen tf#Je to data avarlab’lrty

*’ Gross value ‘ncludles assessed property value before partial

exemptIons that ‘can differ across clues These can Include

homestead, veterans, and senior cmzen exerrptrons

21 The c’tres In the 1981 sample contain approx’mately 18

percent of the entire U S population and 43 percent of

the U 5 property base Thirty-four percent of the crt’es

are drawn irom the West Census Region, 20 percent

from the North Central, 28 percent from the South, and

18 percent from the East Smce the data arc’ only taken

from large cities, they are not truly represen tatrve of the

un’verse of crt’es using property taxes. Thus caveat should

be considered when drawrng conclusrons from the data

23 City property tax payments are recorded In annual Issues

of the Census City Governrnent Finances These are pay-

‘nents mad12 on both personal and real properties Since

*he chosen measure of PTB includes only real property, It

was necess,lry to calculate property tax payments made

on only real property Thus was done by assuming that

lproperty tax revenue from real property IS collected rn the

c,ame proport’on as assessecl real to assessed total prop-

erty m the l:rty lnformatron on this percentage IS reported

In the Census of Government’s Taxable Property Values

and Assesment -Sales Pm? R&/OS volume

24 An “a” ‘ndcates that ‘nformat’on was not available to dr-

rectly calculate the effectrve property tax rate The rate

was calculated by knearly rmputrng Its value from a pre-

uous and follow’ng cross sect’on’s value These Imputed

values are only used to estrmate the mean and standard

deviation 01 property taxation In a year Cities in a given

year with <a11 “a” were not included In the est’mation

” As evidence of reasonable measures, the means are astm’-

lar to anallsgous values calculated by Ladd dnd Bradbury

(1988) fro’rl a different sample of 68 large LI S crties for

I972 (0 86) , 1977 (0 80), and 1982 (0.64)

26 Dropp’ng POP also eliminated the need to create another

endogenou, var’able equatron

27 1 he regressions were ong’nally esttmated In i he form

s~pecrfred In equations 7- 11 using a pooled data set of

stock variables In all of these regressrons. a set of re-

gional dummy variables and a r:l’mate vanable were found

to be stat’strcally srgnrfrcant This indrcates the presence of

crty or regional specrf’c Influences that do net change

over time I‘ these influences are not controlled for, the

resultrng estrmators are biased

‘~3 If each stock regressron IS represented as

N

“-’

where

I = 1, 2. 3, I (total number Iof cities),

t= 1,2,3,or4,and

f = crty-spec rf’c effects that do not change over t

F’rst-drfferenc’ng results ‘n

b’t,f - zf-1 11 = (B0.r - B0.r 1)

+ c wn f - /-w”,t- 1.J + :cLc.i - I*t- 1,J "= 1

City-spec’f’c effects fall out of the first-difference equa-

tion If the r onstant term does not vary over time, It also

156

I AN EMPIRICAL TEST OF THE “NEW VIEW”

falls out A ttme-consrstent test of the constant WIII be

performed. An addmonal assumptron IS that coeffrcrents

on right-side vanables do not vary over time The lack of

degrees of freedom prevents the testing or use of a

pooled model where coefficients could vary As a substr-

tute, the consrstency of estimated coeffrcrents usrng drffer-

ent cross sections IS discussed later

2g This technique calls for the addition of the 5 year lagged

value of HOMES as a right-side variable in the regression The coefficient on this variable IS equtvalent to 1 - 6,

where S equals the percentage of adjustment to the long-

run value of homes that occurs over a 5 year period

Coefficrents on other explanatory variables represent the

short-run influence of the respectrve variable. The long-

run Influence IS equal to the coefficient divided by 6

3o The TAXLIM variable (described later) and an addrtronal

measure of the number of families In the city (FAM) were

also considered as potential instruments The Hausman test tnvolves Including the candrdate for an Instrument,

derived from theory, In an OLS regressron of the basic

equation under consrderatron. If In this test regression the

candidate for an instrument IS statrstrcally rnsrgntfrcant, It

can be used as an instrument tn TSLS StatistIcal slgnrfi-

cance in this test IS defined as a 90 percent or greater

confidence level In a two-tailed test In addition to the ex-

ogenous variables Included In each regression, acceptable

instruments for the PTBD regression are IGOVD, SENRD,

CHILDD, EDUCD, STAXL, ITAXL, AREAL, CML. SENRL,

CHILDL, EDUCL, OWNL, HPLUML, MANUFL, OVTAXL,

EXPL, FAMD, FAML, and TAXLIM, for the HOMESD

regression, they are SENRD, CHILDD, EDUCD, OWND,

MANUFD, HROOMD, YL, AREAL, CML, SENRL, CHILDL,

EDUCL, OWNL, MANUFL, FAML, and TAXLIM; for the

DAPTD regression, they are AREAD, CMD, CHILDD, ED-

UCD, HROOMD, (LAG)HOMESD, PTBL, HOMESL, YL,

STAXL, ITAXL, AREAL, CML, SENRL, CHILDL, EDUCL,

OWNL, MANUFL, HROOML, OVTAXL, FAMD, FAML, and

TAXLIM; for the EXPD regression, they are AREAD,

OWND, (LAG)HOMESD, PTBL, HOMESL, YL. STAXL, ITAXL, IGOVL, AREAL, CML, SENRL, CHILDL, EDUCL. OWNL,

HPLUML, MANUFL, HROOML, EXPL, FAML, and TAXLIM,

and for the YD regression, they are ITAXD, IGOVD,

AREAD, CMD. HROOMD, OVTAXD, DAPTL, YL, STAXL,

IGOVL, AREAL, SENRL, CHILDL, OWNL, HPLUML,

HROOML, FAML, and TAXLIM.

3’ A dummy variable In the DAPT regression was also In-

cluded to account for the exrstence of a statewrde prop-

erty tax limitatron (TAXLIM). The estimated coeffrcrent was

statrstically insignrficant and subsequently dropped

32 The Glesjer test IS to regress the absolute value of the

regression’s residuals against POPD, POPL, 1 /POPD, 1/

POPL, POPDZ, POPL’, POPLO ‘, 1 /POPLo 5, and srmilar varr-

ables using HOMES Instead of POP The square root of

the variable displayrng the highest t-statrstrc In the test

regression IS then used as a weight In the final regresston

At the top of Table 4 are the chosen weights

33 The specrficatron of equations 7-l 1 was done In a gen-

eral form that draws upon local fiscal and economrc de-

157

velopment relatronshlps that have been theoretrcally and

emprncally shown to exrst The possible mrsspecrflcatron of

these equations IS a serious concern that whenever posst-

ble has been addressed Equations were first-dlfferenced

to remove fixed effects that could bras estimation Heter-

oskedastrcrty was detected and corrected by weighting

The Inappropriate choice of Instruments and the resulting

mrsspecrfrcatron of a two-stage estrmatron were avoided

through Hausman tests Mrsspecrfrcatron could have also

occurred because of the assumed linear form Difference

equatrons that result In negative dependent and right-side

variables rule out even testing nonlinear log forms As IS

common In difference equatton estlmatlon (Holtz-Eakin,

1986). the linear form IS taken here as the appropriate

functronal form As a further test of whether unknown

variables have been omitted from a regression specrflca-

tron and a test for a mrsspeclfred functronal form, Ramsey

“reset” tests were performed on all regressions These in-

volve rncludrng the square, cubed, and fourth power of

the fitted dependent vanable as endogenous right-side

variables In the two-stage regression and testng for their

joint srgnrflcance jornt statrstrcal lnslgmfrcance Indicates a

lack of omitted variables and the correct functional form

In all regressions, these vanables were jorntly Insrgnrfl-

cantly different from zero See MacKrnnon (1992) for a

descnptron of how these tests are applied In TSLS

34 The primary other confoundrng effect to mterpretlng the

cross-sectional coeffrclents tn the PTBD and HOMESD

regressions IS the macroeconomy Evidence on the rnflu-

ence of the economy IS found In the YD regressron,

where the cross-sectlonal coeffrcrents rndrcate that the

D7166 cross section was the best for local median-family

income across all crtres and the D7671 cross section the

worst On the basrs of macroeconomrc effects alone, this

would lndrcate that the 07166 cross section should have

the highest posmve change In local property value and

homes Since the dummies In the PTBD regression show

just the opposite, this IS further evidence of the negatrve

effect of the average national rate of property taxation In

addition, the drastrc decline In D7671 dummy from the

D7166 dummy In the HOMESD regression may be due to

the large negative macrorncome effect In the D7671 cross

section In further support of the profrts tax effect, Ladd

and Bradbury’s (1988) dummy for 1982 was also greater

than for 1977

35 StatIstIcal srgnrfrcance IS defined as an 80 percent or

greater confidence level In a two-tarled test This smaller

than normal level mrnrmrzed the chance of committing a

“type-II” error which, In later slmulatrons, IS more worrr-

some than the alternatrve The signs and magnitudes of

corresponding elastrcmes reported In Ladd and Bradbury

(1988) are srmrlar to what IS reported here Thus research,

though different In srgnlfrcant ways, IS closest to Ladd and

Bradbury’s

36 The addltron of new rental units and not as large single-

family homes, wrth a smaller number of rooms on aver-

age than exrstrng housing unrts, IS likely the reason for

the decline In HROOM

37 In all cases, STAXD and ITAXD exhrbrted unpredicted posl-

tlve coeffrctents 111 both trle PTBD and HOMESD regres-

SlOFlS

“’ Elastrcltles can be calculated for any observation As IS

comml3n. the mean of each vaIlable 15 used For add!-

tlonal Information on a city hea\illy relant on the property

tax, the second measure 1s also reported The elastlclt\es

reported for the fight-stde vanables STAXD and ITAXD

represent the percentage change In the dependent van-

able If a city thalt dtd not have the tax adopted one For

example, the ITAXD elasticity of DAPTD (-0 47) IS the

coefflclent on ITAXD (-0 267) tllvlded by the mean of the

absolute value of DAPT (Cl 568) The mean of the absolute

value of DAPTD II, used r elasticity calculattons to make

them con5lstent with other elast cltles

” It should also be noted that a property tax tan cause de

tenoratIon of the aggregate value of per-unit local hous-

ing capital or lower rental rates ‘wIthout capital moblllty

through neglect As demonstrated here, the effect of ne

glect 15 likely to occur much quicker tblan thl? effect of

property moblltty

43 The robustness of the DAPTD coefflclen: In the PTBD and

HOMEliD regressions was examined by rerunning the

regresslons using only the 1971. 1966 dlfferenced cross

section (56 observations), the 1976-1971 dlfferenced

cross section (38 observat ens), and the 198 l-1976 dlf-

ferenced cross sectlon (39 observations) In the 71-66

regression, the DAPTD coefficient in PTBD was -3 887E+9 with a 93 percent Iwo-tailed statistIcal signift-

cance In the 76 -71 regresslon, ?he DAPTD coefficient In

PTBD was -1 45OE+9 with a 98 percept significance In

the 81 -76 regression, the DAPTD coefficient in PTBD was

-7 496E+9 with a 89 percent slgniflccrrlce In the 71- 66

regressson, the DAPTD coefflclenl In HOMES was

-3309 08 with 100 percent slgnlfrcance In the 76. 71 regression, the DAPTD coc~fficreni in HOMES was

-3320 83 with a 46 percent slgniftcance In the 81 -76

regression, the DAPT coeflicient in HOMES was -2530 89

with 83 percent slgniftcance In some of these regres-

slons, the variable STAXD and/or ITAXD was dropped be

cause it was zero for all observations

4’ Aaron (1975) repcrted a negatlvc relatlonshlp between

property tax rate and Income In tommunltles within New

Jersey counties tie concluoed that property tax rate dlf-

ferentlals within INew Jersey counties 3re reyresslve but that his fIndIng may vary by state or even different areas

wlthln a state. The evldente gtven hele Indicates that, at

least for homes, .4aron’s flndrng IS consistent wrth this

sample of large clttes In the United Stales

REFERENCES

Aaron, Henry 1. WIIO Pays the Property 7~~7 Washington,

D C Brooklngs Institut!on, 1975

Brueckner, Jan K. “Property Values, Local Public Expend1

ture, and Economic lfificlency ” Journal of Pub//c Economics

I /) (1979)' 223-45

Firchel, William A. “Fiscal arid Env Ionmental Consideration5

In the Location of Firms In Suburban Comrntinltles ” In f/sea/

Zcnmg and Land Use Controls the t conomlc Issues, edlted

by Edwin 5 h11lls and Wallace E

lngton Book:,, 1975, 119-73 Lexrngton, MA Lex-

--. The Lconomrcs of Zoning Laws. a Property Right5

Approach to Amencan land Use Controls

Johns HopkIn: Unlverslty Press, 1987.

Baltimore, MD

-. “Property Taaatlon and tne Tlebout Model. Evidence

for the Benefit View from Zomng and Voting ” Journal of

Econom/c L/tel a ture 30 (1992) 1 7 l-77

Fisher, Ronald C. State and Local Pub//c

IL Scott, Fore,man, and Co , 1988 Glenview,

Goodman, Allen C. “Capitaltzatlon of Property Tax Dlfferen-

teal, within alJ among Munlclpalltles ” Land &onomw 59

(1983) 211- 19

Hamilton, Bruce W. “Zoning and Property Taxation In a

System of Loc<~l C,overnments ” Urban Stud/es 1.2 (1975)

205 11

--. “Capitallzatlon of Intrqunsdlctlonal Differences In

Local Tax Pnccs ” Amencan Economic Rev/ew 66 (1976).

743-53

Hausman, JA. “Specification

me:nca 46 (1978) 1251-71

Econometrics ”

Holtz-Eakin, Douglas. “Unobserved Tastes and the Determi-

nation of Mun cipal Services ” ,Nationa/ Tax Journal 39

(1936) 527-32

Ladd, Helen F. and Katherine L. Bradbury. ’ City Taxes

and Property Tax Bases ” NatIonal Tax Journal 4 I (1988)

503 -24

Ladd, Helen F. “Local Education Expenditures, FIstal Capac-

ity, and the Ccmposltion of the Property Tax Base ” National

Tax Journal 28 (1975). 145-58

MacKinnon, James G. “Model Specification Tests and Artif\-

cial Regressionc, ” Journal of Economic Literature 30 (1992)’

102-46

Mieszkowski, Peter. “The Property Tax An Excise

Tax ” Journal rlf Pub//c Economrcs I (1972): 73--96

Miesrkowski, Peter and George R. Zodrow. “Taxation

,qntl the TIebout Model ” Journal of Economic i.Iter&ure 27

11989) 1098 1146

Netzer, Dick. il?onom/cs of the Property

D C Brooking, Institution, 1966 Tax Washington

Oates, Wallace E. “The Effects of Property Taxes and Local

IPublIc SpendIn< on Property Values An Empirical Study of

Iax Capltallzatl In and the Ttebout Hypothesis ” Journal of

i3ohtfca/ Economy 77 (1969) 9517-7 1.

Tiebout, Charles M. “A Pure Theory of Local Expenditures ”

Journal of Po/,t,ca/ Economy 64 (1956) 416-24

Wales, T.J. and E.G. Wiens. “Capitallzatlon of Resldenllal

Property Taxes an EmpIrical StLldy ” Review of t-conom/cs

dnd Statrstrcs 515 (1974) 329 -33

Wassmer, Robert W. “Local Fiscal Variables anlj Intrametro-

polltan Firm Location Regressjon Evidence from U.S. and Re- sear<-h Suggestions ” Env/ronment (and Planmng C 6 (1990).

283 -96

Wildasin, David E. “Theoretlcal Analyses of Local Public

Economics ” In Handbook of Urban Economics, Vol 2, edlted

158

I AN EMPIRICAL TEST OF THE “NEW VIEW”

by Edwm S Mills Amsterdam Elsevler/North Holland, 1986, Yinger, John et al. Property Taxes and House Values The

1131-78 Theory and Mmation of /ntequnsd/ct/ona/ Property Tax Cap,

White, Michelle J. “Firm Locatlon In a Zoned Metropolitan ta//zatron San Dlego, CA Academic Press, 1988

Area.” In Frscal Zomng and Land Use Controls. the Economrc Zodrow, George R. and Peter Mieszkowski. “The New Issues, edlted by Edwm S Mills and Wallace E Oates Lexlng- View of Property Taxation a Reformulation ” Regional Sa-

ton, MA Lexington Books, 1975, 175-201 ence and Urban Econom/cs 16 (1986). 309-27

159