the incidence of differential commercial property … · ied upon commercial and industrial prop-...

THE INCIDENCE OF DIFFERENTIAL COMMERCIAL PROPERTY TAXES: EMPIRICAL EVIDENCE JOYCE Y. MAN*

Abstract - This paper evaluates the effects of property tax differentials within and among municipalities on the sales value of

commercial real estate to provide a direct empirical test of Mieszkowski’s (7972) ar-

gument about the incidence of commercial property taxation. He argued that consum-

ers of the products made with commercial capital must “bear 75 percent or more of the burden in the form of higher prices”. By examining the commercial real estate

market in the Phoenix metropolitan area, I find that over 70 percent of interjurisdictional differences and about 60 percent of

intrajurisdictional differences on commercial property taxes are borne by property owners, either capital or land owners, instead of consumers as Mieszkowski sug-

gested. It implies that the spatial demand for commercial real estate is highly price

elastic in metropolitan Phoenix and differences in commercial property taxes largely caused by errors in the assessment practice

may have significant resource allocation effects.

*School of Pubk and Enwronmental

Indianapolls, IN 46202 Affatrs, Unwerslty,

INTRODUCTION

In the literature of property taxation (Netzer, 1966; Aaron, 1975; Hamilton, 1976; Mieszkowski, 1972), the incidence of the residential property tax has received enormous scholarly attention, but the incidence of the local property tax levied upon commercial and industrial property has not been adequately studied. In reality, however, taxes levied on nonresi- dential property can easily constitute up to 40 percent of the tax base, most of which is composed of commercial and industrial real estate. Moreover, more than 40 percent of the states in the United States have implemented a classified property tax system that usually taxes commercial and industrial property more heavily than the residential property. Any conclusion about the incidence of property tax would not be complete without an analysis of taxes on commercial and industrial property.

The currently prevailing view on commercial property tax and its incidence stems from Mieszkowski. In his seminal paper (1972), Mieszkowski suggested that inter-

479

jurisdictional difference!, in commercial and industrial property taxes result in an “excise tax effect,” and so most of the tax burden on commercial assets must be passed on to consumers because capital and labor are perfectly mobile in the long run and the immobile land is too small a share of costs to absorb much of the tax burden. Therefore, Mieszkowski con- cluded that “commodity prices will rise and I venture to guess that at least 75 percent of the burden of the tax differential falls on consumers, when capital is perfectly shiftable” (p. 95).

Mieszkowskr’s observation has been chal- lenged by Wheaton (1984), who provided strong empirical evidence contrary to Mieszkowski’s conclusions Wheaton ex- amined the Incidence oi interjurisdictional difference in comrnerclal property taxes by exploring the effect of commercial property taxes on rents of commercial office buildings in the Boston metropolitan area. He discovered that the tax variable does not have a significant impact on gross rents in office buildings in metropolitan Boston. This suggests that there is no tax shifting from proiperty owners to renters or users, and the burden of interjurisdictional difference:, in commercial property taxes falls on capital and land owners. It implies that the spatial demand for commercial capital vvould seem to be highly price elastic, and land and real estate capital are inelastically supplied within the Boston Standard Metropolitan Statistical Area (SMSA). Wilson (‘I 984) provided a theoretical argument for why a difference between tax regions’ property tax rates does not cause their local good prices to differ. However, in another study of office rents and intrajurisdictional differences in commercial property taxes, McDonald (1993b) found that 45 percent of property 1:ax differentials in downtown Chicago are shifted forward to the tenants as higher gross rents. His finding suggests that the demand for real

estate capital within a central city is not perfectly price elastic, and therefore there exist pril:e effects from1 intra jurisdictlonal property tax differences.

These contradictory results concerning the incidence of commercial property taxes warrant further cross-sectional and tlme- series studies of other commercral real estate markets. Using the sales data for the cities in the Phoenix SMSA between 1985 and 1988, the present study attempts to provide additional evidence on the incidence of tax on commercial property by examinlllg the effects of both interjurisdictional and intrajurisdirtronal differential commercial property taxes on the market value of commercial real estate.

As Dusansky, Ingber, and Karatjas (1981) have observed, most empirrcal studies of the incidence of property tax fall into two major categories. The first group contains studies that examine the effect of local property taxation on the market values of real estate, focusing on the issue of tax capitalization. The second c:ategory includes studies that expllore the effects of property taxes on gross rental values, with focus on the issue of tax shifting from owners to renters. Both Wheaton’s and McDonald’s estimations of the incidence of commercial property tax differences fall into the second category, as they explore the effects of property tax differentials on gross rental incomes of commercial office buildings. The present study follows the tradition of capitalization analysis to evaluate the effects of property taxes on the market value of commercial property, in anattempt to provide a direct empirical test of Mieszkowski’s conclusion on the incidence of commercial property taxation. The extent of capitalization may provide information regarding the incidence of property taxes. A high degree of capitalization may indicate that a large portion of ithe tax burden is borne by property owners, and the de-

480

I INCIDENCE OF DIFFERENTIAL COMMERCIAL PROPERTY TAXES

mand for commercial real estate or the demand for the products made with the commercial property is unlikely to be price inelastic. Therefore, interjurisdictional property tax differences would result in differences in the after-tax return to capital and consequently lead to capital outflow and locational shifts for capital in the long run until the net rate of return to capital is equalized across jurisdictions. There may exist significant resource allocation effects from interjurisdictional tax differences.

By examining the commercial real estate market in the Phoenix metropolitan area, I find that effective property tax rate differentials within and among municipalities in the metropolitan Phoenix area have a significant negative effect on the sales price of the commercial real estate. The empirical evidence shows that about 70 percent of both interjurisdictional and intrajurisdictional tax differentials on commercial property are borne by capital and land owners of commercial real estate for the study sample. It suggests that differences in commercial property taxes in the Phoenix SMSA cause resource allocation effects as well as price effects.

THE CONCEPTUAL FRAMEWORK

The value of business property can be determined by a bid-rent model. I construct a model of commercial property value determination based on the bid-rent framework that Wheaton (1977) and Brueckner (1979, 1982) developed. First, I assume that firms are identical and they all use labor, structural and nonstructural capital, and benefit of public services in their pro- duction of nonhousing goods. Thus, the firm’s output of nonhousing goods in the city is determined by the following pro- duction function:

Q = Q(L K 5 Z>

481

where L, K, S and Zare the amount of labor, nonstructural capital, structure used for commercial purposes that has a set of physical characteristics and locational attributes, and benefits of local public goods and service provision, respectively. The cost function of the firm can be rep- resented as

c = kvl + rK + (1 + tqr.5

where r is the after-tax rate of return to both structural and nonstructural capital. It is assumed that capital is perfectly mobile across sectors and jurisdictions at no cost, and that its after-tax rate of return f is determined at the national market. Therefore, the net rate of return to capital is uniform across jurisdictions. The wage rate of the local labor market is w and the property tax rate is tp. Based upon the bid-rent model, the rent payment of business property will be bid up until the profits of all firms equal zero. It also requires communities to be identical in all respects, except public expenditures and taxes, so that the only differences among communities that are reflected in property values are variations in public good provision and taxes. Therefore, the zero-profit condition requires

P( 1 + P)X(L, K, s, z) - w/!

- rK - (1 + t+S = 0

where P is the output price of the nonhousing good, which is determined at the national market and therefore will be set at unity indicating that the nonhousing good IS numeraire, and tS is the local sales tax rate. Because rent payments on business property, n = (1 + ~$5 = p(1 + F)X(L, K, S, Z) - WL - K, are bid up to eliminate profits, the rent payment for a given structure size can be defined implicitly as

q A n = ?r(S, z, t: w) Equation 4 indicates that the rent payment of a firm for a piece of business property located in a community is a function of the size of structure used for commercial purposes, the level of public goods and services provided by the local government, the local sales tax rate, and the wage rate in the local market.

As the market value of business property equals the present value of the rental flow minus the present value of the property tax flow, then assuming an asset yields an infinite stream of returns of 7c at the discount rate of i, the value of business property is

Solving for B yields

q a 4s z t: 4

B=(i+P) - = B(.S, z, t: t’: w)

Assuming the local government’s tax revenue is raised entirely from property and sales taxes, and a household’s wage income is independent 01 its residential location choices, the balanced budget re- quirement of the local government ensures that the folIowang condition is met:

q 2 tf’B,($ z, tf’, t: w) + PV

,= 1

+ (: + tqx = c(Z, N)

where i = 1, 2, . . . N, N is the number of business property parcels in the community, c is the cost function for the provi-

sion of public goods, alnd V is the aggre- gate residential properly value in the community. Then the i plicit function for the tax rate of the ith r arcel of business property can be determined as

0 : ty q = ty:B, Z, t: w, N, V)

Substituting equation 7 into equation 5, we can write an impliciit function for the value of an individual business property unit as

q 0 B, =I B,( 5, if’, t : ty (4 4 t: w N, W, 4

Equation 9 expresses the relationship between the market value of the ith unit of business property and other structural, Io- cational, and fiscal factors, while property tax rates adjust to maintain budget bal- ance for the local government. Substitut- ing equation 3 into equation 5 and taking the partial derivative, one also can find that dBld.S > 0, dB/dZ’> 0, and dB/dtp < 0, which imply that Ian Increase in public expenditure increases business property value, while an increase in the property tax rate leads to a’ decrease in the value ot business prop e rty. The theoretical framework discussed above can be applied to the examination of the determination of commercial real estate value. Firms bid for commercial property on the basis of different publi/c service tax pack- ages offered by various jurisdictrons In a similar way as househ Ids bid for housrng If firms are requir ,” d to pay higher property taxes in one jIurisdiction than in another one, then the,firms would have high levels of profits bb relocating to juns- dictions with low tax rates, everything else equal. As a result,’ bids for commercial property in the lovv-tax jurisdiction increase, while bids for commercial real estate in the high-tax jurisdiction decrease. In equilrbrium, there WIII be differences in

‘w‘!


market value of commercial property that ensure equalization of profits among firms. Therefore, property tax differentials are fully capitalized into values of commercial property. As long as at least one firm in one jurisdiction prefers to be located in another jurisdiction to maximize profit, the property value will reflect such movement and capitalization will occur.

Examination of the extent of capitalization may provide information regarding the incidence of commercial property taxation. Rewriting equation 5 with the property tax rate effect possessing an ex- ponent (b) for individual property parcels gives

q ” =

q(.$ z t: 4 (i + tf))”

Under the assumption of inelastic supply of commercial property (which is true at least in the short run), if the market is in equilibrium and buyers and sellers are ra- tional and have full information in their bidding, then b equals one, which indicates that differences in property tax payments are fully capitalized into differences in property values, dollar for dollar. Prop- erty owners bear the full burden of the property tax differentials. If those conditions are not met, then the value of b may be greater or less than one, which indicates overcapitalization or undercapi- talization.

In order to provide a direct empirical test of the incidence of commercial property taxation, I use micro sales data of real property for commercial uses in the Phoe- nix metropolitan area from 1985-8 to estimate the effects of property tax differentials within and among municipalities on the sales price of commercial real estate. The model includes two simultaneous equations, ‘l 1 and 12, with two endogenous unknowns, CpRlCE and EBTAX.

+ 6G + BEBTAX, + p,

m EBTAX, = b, + ylnCPR/CE,

+ cp + x cmDm, + E,

IDENTITY: t” = (E - NPV)INAV

where CPRKE = the sales price of each unit of

commercial real property EBTAX, = the effective tax rate on an in-

dividual unit of commercial property

Xk, = a vector of exogenous variables such as structural and locational characteristrcs that influence sales price, where k = 1, 2, . . . Kand Kis the number of attributes

G = the level of public services offered in each jurisdiction

t” = the statutory property tax rate Qn, = a vector of assessment bias in-

struments E = total expenditure of a jurisdic-

tion NPR = nonproperty revenues NAV = total net assessed value in a

given jurisdiction ,LL, and E, = the error terms

Equation 11 indicates that the sales price of commercial real estate is a function of a set of structural characteristics and locational attributes (e.g., number of rooms, noise pollution, etc.) and of fiscal characteristics of the jurisdiction where the commercial unit is located (e.g., the level of public services, effective property tax rate, etc.). As the effective property tax defined as the ratio of the annual tax bill to the property sales value is endogenous by def-

483

initron, there exists reciprocal causality between the effective tax tate and the sales price of commercial property. In this study, I take a simultaneous equation approach to control for the spurious correlation problem by specifying an explicit tax rate prediction equation expressed in equation 12, which provides justification for the appropriate instrument set. As the value of each unit of property for the tax purpose is appraised by local government officials and the assessment processes have never been perfectly administrated, the differences between the actual and fair property tax over a given unit result in assessment errors. In order to distinguish between property tax differences caused by assessment errors and those caused by differences in townwide tax rates, an al- ternative model in the flollowing form will be specified and estimated.

lE

i- pt” + qDEBTAX, + p,’

a A

DEBTAX, = bl, + ~‘InCNNX,

-t x o,!,,Dm, + c;

where DEBTAX, = EBTk\X, - tn

In a world where the property tax is perfectly administered, the nomlnal tax rate (P) and the effective tax rate (EBTAX) would not differ. Therefore, like properties should be taxed at The same rate within the same jurisdiction. However, the administration of the property assessment process has been far from perfect” As some studies have found widespread intrajurisdictlonal assessment bias in favor of high-valued property (Ihlanfeldt and Jackson, 1982), this study attempts to identify systematic errors in the assessment practices to explarn the existence of

a wide range of effective tax rates on commercial property.

The two specifications of the simultaneous model described above satisfy the rank and order conditions for overidentifi- cation because more than one exogenous variable is omitted from each equation. They will be estimated to examine the incidence of both interjurisdic:tional differences in commercial property taxes across 20 cities within the Phoenix SMSA and of the intrajunsdictional tdx differences withln the city of Phoenix usrng micro data on sales of commercial real estate from 1985--8. The sem’ilog function form is chose11 because such a functional form reduces the sum of squarecl residuals, and at tile same time allows the independent variables to have a broad range of values such as zero and negative. Such a functional form also seirves well In the control for nonlinearity of property value and tax rate and the r duction of the po-

4 tential of heteroskedas, ic disturbances. The three-stage least square (3Sl.S) estimation method is used~ to get the best fit for the simultaneous equations.

THE DA,TA

In order to determine whether the users or owners of commerc/al property bear the differential tax burden, I use micro data of (commercial property sales from 1985-8 in the Phoenix’ rnetropolitan area in Arizona to estimate the market value equation specified in equation 1 1. Equa- tion 11 IS estimated for the effect of interjurisdictional tax differences on commercial property across 20 cities in the Phoenix SMSA and of the intrajurisdictional tax differences within the central city of Phoenix.

The data used in the study are drawn frorn several sources. l$licro data on sales prices, sales assessment ratios, and struc-

8 tural and locational ch racteristics of commercial real estate are obtainecl from


the sales tape compiled by the Arizona Department of Revenue. Arizona implemented a classified property tax system that assesses commercial and industrial property at a higher percentage of market value than residential property. For example, Arizona state law stipulates that owner-occupied residential property is assessed at 10 percent of full cash value appraised for tax purposes, while commercial and industrial property is assessed at 25 percent. There also exist wide variations in statutory property tax rates that range from 0.184 in Buckeye to 0.006 in Youngtown. In addition, 7 out of the 21 cities in the Phoenix SMSA do not levy property tax.’ The assessment sales ratios on individual property parcels also vary enormously within and among jurisdictions from 0.05 to 12.65 with the mean ratio of 0.91 and standard deviation of 0.81. As a result, commercial real estate faces a wide range of different effective property tax rates, from 0.08 percent to 3.58 percent across municipalities in the metropolitan Phoenix area (Table 1). This wide variation in effective tax rates provides a natural experiment for testing the hypothesis that differential commercial property taxes affect the market value of commercial real estate.

Commercial real estate is concentrated not only in the central city of Phoenix, but in other suburban cities and towns as well. To generate a data set for the time- series and cross-sectional analysis of tax incidence, I first pulled out all detached commercial property sales for the period under examination. Because Phoenix has more commercial real estate sales than other cities, I randomly selected a smaller sample of observations for Phoenix for the inter-jurisdictional tax incidence analysis, whereas I included all sales in the city of Phoenix for intrajurisdictional tax incidence analysis.

The commercial real estate in the sample refers to space used for wholesaling, re-

tailing, and service activities such as of- fices, stores, shopping centers, banks, restaurants, and theaters. The market values of these commercial real estates vary enormously, with mean value of $256,134 and standard deviation of $455,442 across the sample size and period.

The data for the fiscal variables are de- rived from the file compiled by the Ari- zona Joint Select Committee on State Revenue and Expenditures, from which the data on sales tax revenue, state and federal aid, and local government expenditures are extracted for 20 cities in the Phoenix SMSA. Demographic and social- economic data such as vacant rate, size and composition of population, and per capita income of each city come from the mid-decade population surveys by the U.S. Census Bureau.

EMPIRICAL ESTIMATION

The simultaneous-equation economic model contains two equations, the commercial real estate sales price equation and effective property tax rate equation. The sales price equation captures the effects of the local property tax rate upon the market value of commercial property and addresses the issue of who bears the differential tax burden, property owners or property users. The determinants of the market value of commercial property, aside from local taxes, are physical characteristics of each property unit, locational attributes that influence its desirability to prospective buyers, access to a transportation facility, and local public goods provision, etc. The property tax equation presents both assessment error impact and expenditure side effect on the determination of the effective tax rate. The variables are listed and defined in Ta- ble A-l.

Commercial Real Estate Sales Price Equation

In modeling the incidence of the commercial property tax, I specify the sales value

485

TABLE 1 THE COMMERCIAL REAL ESTATE MARKET IN THE PHOENIX SMSA

Townwide Average Sample Average Effective Rate Municipality Statutory Tax Rate= Effective Tax Rateb Standard Deviation

_--~ -- _-.--.- Buckeve Chandler Gilbert Glendale Mesa Tempe Tolleson Wickenburg Avondale Goodyear Phoenix Carefree El Mirage Scottsdale Peoria Surprise Youngtown Guadalupe Gila Bend

0.184 0.0228 0.116 0.0295 0.151 0.0249 0.123 0.0294 0 0 0.127 0.0283 0.077 0.0185 0.135 0.0 174 0.058 0.0090 0.072 0.0180 0.177 0.0358 0 0 0 0 0.091 0.0186 0.135 0.0.341 0 0 0.006 0.0008 0 0 0.139 0.009

0.0148 0.0156 0.0136 0.0174 0 0 0192 -- 0.0099 0.0036 0.0029 0.0218 0 0 0.0152 0.0213 0 0.0009 0 -._

Cave Creek 0 0 0 ---- --.~ -

‘Townwide average statutory tax rate for all types of property from 1985-8. %alculated samole average effective tax rate (annual tax bill/sales price) for commercial property from 1985.-8.

.-

Source: Arizona’iax Research Foundation

of commercial units as the dependent variable, controlling for four sets of exogenous variables in addrtron to the effective commercial property tax rate, and year and property type dummies. The first set of those exogenous variables de- scribes structural characteristics such as size of the unit (SQFT), age of structure (AGE), quality of physical conditions (GRADEG, GRADEP), types of heating and cooling systems (HEATAIR, HEATFUR, COOL/?, COOL!!), quality of wall or structural framing materials :WALLB, WALLS, WALLFC), the evaluation of improvement needs of each unit (IMPROVG, IMPROVP), size of attached st:ructure (ADD), and the structural style of each Icommercial unit (MODERN, OBSOLETE). It is expected that the size of usable area, newer structure, better quality of wall material, and overall physical condition, moaern style of the building, more attached structure, and better heating and cooling systems are positively related to the sales value of the commercial unit.

The selling price of a commercial building is also affected by locational attributes.

Two commercial units with the same physical characteristics will have different prices if locational attriibutes differ. In determining the effect of amenities on the value of commercial unit, I include variables measuring percentage of neighborhood desirability evaluated by the county assessors (NEIGHBOR), ,vacant rate of the Jurisdiction in which thie commercial unit is located (VACANTR), and population density lof the city (DE/V.WY). In addition, dummy variables indicating market areas In which each commercial property unit is located [MARKET(i)] are also included in the model.

Starting from Muth (1 69), distance from the central business di ! trict has been em- ployed in spatial analy$is and has been tested statistically signilficant in almost all previous studies. In thij; study, the linear distance between suburban towns and the central city of Phoenix (D/STAN, D/.VSQ) is measured ahd included in the regiression of the commercial unit sales price equation. In addition, I include two variables assessing the accessrbility of


each city to highways and railways (HIGH- DUM, RALDIST). It is believed that better access to transportation facilities en- hances the attractiveness of commercial real estate to prospective buyers because of its locational convenience to clients and customers as well as to their employ- ees. Following Wheaton (1984), I also include a variable measuring the percentage of the city residents with a college education (COLLED) to assess the avail- ability and accessibility to a skilled work force that is believed to be an important determinant of industrial and commercial locations.

Public service is an important component of any study of the effects of state and local taxes. As it is believed that both tax liability and the level of public services are taken into account in a firm’s location de- cision, failure to control for services could lead to incorrect estimates of the tax coefficients. Therefore, I use local governments’ noneducational per capita expenditure on fire and police protection, roads and bridges, sanitation, and sewage and garbage collection services (LOCEXP) as a proxy for the benefits of public services received by prospective firms. This variable is expected to have a positive sign, which implies that the more and better public services are provided by the local government, the higher prices those prospective buyers are willing to pay to locate their business in that community.

The sales price of a commercial unit may also be influenced by other local taxes or fiscal policy in addition to local property taxes. Arizona is one of the 30 states al- lowing local governments to impose sales taxes. No local income taxes are levied. Nearly 40 percent of the cities in Arizona do not levy property tax either. Thus, local sales taxes are heavily relied upon for own-source revenues. Man and Bell (forthcoming) argued that a relatively higher local sales tax discourages pro-

spective buyers to locate their business in the higher-tax locality because it reduces the net profit of firms unless the demand for the taxed goods and services IS perfectly price Inelastic. If the demand for commercial property is not perfectly price inelastic, the tax differences in the local sales tax are also capitalized into the sales value of the commercial real estate. In the present study, the city’s sales tax rate (STAXR), used as a measure of the sales tax effect, is included in the commercial unit sales price equation. I also include dummy variables that indicate different types of property, because the sales price of commercial real estate may also differ by type of uses (OFFICE, STORE, SHOP, DEPTS, BANK, RESTR). The year dummy variables (YY85, YY86, YY87) are needed in the pooled regression to control for cy- clrcal trends of sales price change.

Property Tax Rate Equation

The estimation of the commercial real estate sales price equation would be much simpler if the property tax variable is exogenous. Due to the reciprocal causality between the sales price and the effective property tax rate, we need to identify instrument variables to control for a possible simultaneity bias. The explicit specifications of property tax rate equations 12 and 14 identify and provide justification of potential instruments. Because the effective property tax rate is the product of the citywide tax rate and the assessment sales ratio, the statutory property tax rate can be a good Instrument if it is truly exogenous. Variables measuring demographic composition of residents of the jurisdrctions (POPI8PC, POP65PC), the poverty level (POVERTY), and the demand pressure induced by population growth (POPCHAN) are also included in the estimation of the property tax equation.

Because the effective property tax rates also vary due to the assessment errors that occurred during the property assess-

487

ment process, the search for the determinants of differential property tax rates Ideally should be based on a behavioral model that seeks to explain the causes of assessment errors. The error committed in assessing a particular property may de- pend upon the training, experience, and personal beliefs of indivrdual tax assessors; the appeals procecure; court practices; and reassessment lags. Because of data limitation, my search focuses on the systematic errors in the <assessment of var- IOUS uses of property and different ages of structure in order to explain the large deviations of effective tax rates. For example, it is possible that prejudiced assessors may assess commercial office buildings at a higher rate than restaurants and bars, even though these properties are all classified into the same class by law, which requires a uniformity of assessment within a class. As property value is assessed by local officials, assessment errors (NEW, OLD, STORE, DEPTS, SHOP, OF- FICE, BANK) may systematically affect the effective property tax rates of commercial units.

These possible determinants of the effective tax rate on commercial property must satisfy two conditions in order to be truly a good set of Instruments: (1) they must be uncorrelated with the error term in the sales price equation; and (2) they must be strongly correlated with the effective tax rate. The first condition guarantees con- sistent estimates of the capitalrzatron coefficient, while the second condition yields estimates small III variance. Follovv- ing Ladd and Bradbury (1988) and others, I apply Hausman’s exogeneity test to all of those potential Instrument variablesz

RESULTS AND FINDINGS

Incidence of Interjurisdictional Tax Differences

The asymptotic estimation method of 3SLS is used because we cannot justifia-

bly assume zero correlation among the disturbance term and the tax variables in the commercial property value equation. If the structural equations were estimated by ordinary least squares (OLS), the srmul- tanelty problem would result in inconsis- tent and inefficient estiimators of the pa- rameters. The 3SLS esti~mation method is more efficient than the two-stage least square (ZSLS) estimation method because It makes use of the cross-equation corre- lations of the disturbances, so the 3SLS coefficient estimates are preferred results.

Table 2 Ipresents the coefficient estimates of equal ions 12 and 14 of property tax rates for commercial property by using 3SLS estimation metho~ds with micro sales data for 20 cities and tpwns in the Phoe- nix t5MS4. The results show that variables describing the systematic assessment errors sublstantially affect the tax rates on commercial real estate. The significant and positive coefficient of the variable NEW implies that the value of the newly built commercial units is systematically ov- erassessed by local officials so that Isuch property units consistently suffer a hlgher effective tax rate. Values of commercial office buildings and delpartment stores are usually assessed at a higher ratio relative to its sales value than other types of uses and, therefore, are taxed at higher rates. The demand pressure from the population growth in a given community also leads to higher property tax rates in order to provide adequate public: services to 11s rer,idents.

Table 3 contains the 3$LS estimates of the sales price equations of commercial property specified in equations 11 and 13, respectwvely. Overall, the equations perform very well. The estimated coefficients are not very sensitive to the choice of estimation method except for the property tax variable.3 The results show that the sales value of commercial real es-


TABLE 2 REGRESSION ANALYSIS OF THE COMMERCIAL PROPERTY TAX RATE EQUATION FOR

INTERJURISDICTIONAL TAX DIFFERENCES (DEPENDENT VARIABLE: EBTAX OR DEBTAX)

Independent Variables

3SLS Estimation

(EBTAX) t-Statistics

3SLS Estimation (DEBTAX) t-Statistics

Constant - 0.041 LCPRICE 0.003 OFFICE 0.004 STORE 0.003 SHOP - 0.001 DEPTS 0.012 BANK - 0.001 NEW 0.006 OLD 0.005 POPCHAN O.SE-04 POP65PC - O.ZE-03 POPl8PC - 0.7E-04 POVERTY - 0.1 E-04 t” 0.823 YY85 0.002 YY86 0.001 YY87 - 0.001

System weighted mean square error System weighted R* Sample size 750

(2.7)” - 0.045 (3.2)a 0.003 (2.5)a 0.004 (1.6) - 0.003 (0.1) - 0.002 (1.7)b 0.013 (0.1) - 0.001 (3.7)” 0.007 (1.6) 0.004 (1.9)b 0.8E-04 (0.9) 0.1 E-03 (0.4) 0.1 E-05 (1.3) -O.lE-04

(17.2)” -

(1 .a 0.004 (0.4) 0.002 (0.3) 0.002

0.97 0.50

750

(2.9)a (2.5)a (2.5)” (1.6) (0.6) (1.7)b (0.1) (4.3)” (1.7)b (2.7)” (0.7)

(2.4)a (1.1) (1 .a

1.007 0.40

Notes: Pooled time series and cross-section sales data for 1985, 1986, 1987, and 1988. “Coefficients sionificantlv different from zero at the 5% level or less, two tail test. EGgnificant at the 10% (eveI.

tate is negatively related to the property tax. The differences in the sales price of commercial property in metropolitan Phoenix are largely attributed to the differential commercial property taxes caused by assessment errors rather than to the differential townwide statutory tax rates. The public service variable (LOCEXP) comes out with the predicted positive sign, implying that a high local public expenditure on noneducational services results in an increase in the sales price of commercial real estate located in that jurisdiction, everything else being equal. Meanwhile, the strong negative estimates of coefficients of sales tax rate (STAXR) shed new light upon the effects of alter- native revenue sources on the market value of commercial property. It indicates that a high local sales tax rate in a given municipality reduces the market values of commercial units located in the city after holding other factors constant.

In contrast to the tax and expenditure variables, the performance of the varia-

bles describing accessibility to transportation facilities and white collar work force is somewhat disappointing. Only the estimate of the dummy variable for highway access (HIGHDUM) has the predicted positive sign and is significantly different from zero at the 10 percent level. Effects of those variables may have been cap- tured by other proxies for locational attributes such as market area indicators and distance to the Central Business Dis- trict (CBD). None of those variables defin- ing various uses of commercial property are statistically significant and therefore are dropped from the estimation equation.

The coefficient of primary interest, that of EBTAX, is - 16.8 from the 3SLS. It is significantly different from zero at a 99 percent confidence level. The magnitude of estimated property tax rate coefficient in 3SLS of - 16.8 implies that a one-unit difference in the effective property tax rate leads to a difference in the sales prices between properties among munici-

TABLE 3 REGRESSION ANALYSIS OF THE COMMERCIAL PROPERTY VALUE EQUATION FOR INTERJURISDICTIONAL

TAX DIFFERENCES (DEPENDENT VARIABLE: LCfWCE)

Independent Variable

Specification (1) -------~- 3SLS t-Statistics

Specification (2) .------__

3SLS t-Statistics

Constant EBTAX DEBTAX t” STAXR LOCEXP AGE SQFT MODERN OBSOLETE ADD GRADEG GRADEP WALL6 WALLC HEATAIR HEATFUR COOLE DISTAN DISTSQ VACANTR DENSITY NEIGHBOR HlGHDlJM RAlLDlST COLLED MARKET2 MARKET4 MARKET6 MARKET8 YY85 YY86 YY87

Sample size

12.73 (13.6)” - 16.80 (2.8)a

_- --

- 1.26 0.6E-03

-0.015 0.036 1.24

- 0.34 0.001 0.39

-0.19 0.41 0.52 0.18 0.30

- 0.28 - 0.039

0.4E-03 - 0.035 - O.lE-03

0.11 0.30

- 0.023 - 0.004

0.15 1.05

- 0.21 - 0.18

0.005 - 0.03 - 0.08

(2.9)‘1 (2.4)“ (6.2)~~ (9.5)“ (4.Ob (1.7)” (2.9P (1.6) (1 .9S’ (2.1 p (2.9) (2.1)’ (2.2),3 (2.4)j (3.0)s (1.4) (1.7)b (1.6)

(2.2),3 (1.4) (0.7) (0.5) (1.6) (2.1)a (0.9) (1.7)b (0.3) (0.5) (0.9)

750

11.33 -

- 19.78 - 0.49 - 0.82

0.4E-03 -0.016

0.037 1.28

- 0.28 0.001 0.39

- 0.23 0.43 0.50 0.17 0.25

- 0.27 -0.014

0.1 E-04 -0.015 - 0.1 E-03

0.12 0.07

- 0.024 - 0.003

0.13 0.98

- 0.09 -0.15

0.09 0.05 0.04

750

(11.9)a

(2.3)” (0.1) (1.9)b (1.7)b (5.9)a (9.7)” (4.0)” (1,4) (2.8)” (1.5) (2.3)” (2.l)a (2.8)” (1.9)b (1 .8)b (2.3)” (1.1) (0.1) (0.7) (0.8) (2.4)d (0.3) (0.8) (0.4) (1.3) (2.0)* (0.4) (1.4) (1.1) (0.6) (0.4)

Note: Footnotes are the same as In Table 2. --- _____----__--_-

palities by the multiplicative factor 16.8. Multiplying the coefficrent of the property tax variable (EBTAX), which IS not In logarithm form, by tts mean value (0.023), we can get the elastictty of market price of commercial real estate with respect to the effective tax rate. The calculatron produces a tax price elasticity of commercial property value of - 0.386, which means that a 1 percent increase in the effective property tax rate reduces the sales value of a commercial unit by 0.386 percent, about $965 on average.4 The statistical results show that differences in effective property tax rates across

junsdictrons in the Phoenix SMSA significantly reduce the sales values of commercial real estate after holding other factors constant. It suggests that there may exist Interjurisdictional property tax capitaltza- tion for thrs data sample and time period.

We can Icalculate the degree of c.apitalrza- tion by comparrng the change in property value with the present value of the flow of tax payments due to Increased liability. The above coefficient for the property tax rate rn the semilog equ,ation is p = d InBl dt~ = 116.8, but the capitalization factor IS dB/dF, where Tp is tax liability. A


change in the tax rate, for a given property value 8, immediately alters Tp, as equation 10 indicates. However, in the presence of capitalization, this induced al- ternation in tax liability itself affects changes in the property value. By some simple substitution, we can find that dBl dTp = /?/(I + Ptp), where tp is the mean sample effective property tax rate.5 By calculation, the capitalization factor dB/dTp is - 12.1, indicating that a $1 difference on

the tax bill across properties and towns would, on average, lead to a $12.1 difference in the sales price of commercral real estate in the Phoenix SMSA, if public output and other variables are kept constant. If we assume a 5% discount rate and 40 years of expected life of structures for commercial uses, then one can find that over 70 percent of interjurisdictional tax differences on commercial property in the Phoenix metropolitan area is capitalized into lower property value.

The policy significance of the relative sizes of elasticities for various taxes and public expenditure can be compared. The coefficient of LOCEXP indicates that each additional dollar of the per capita local public expenditure increases the sales value of commercial units by 0.06 percent. By cal- culating and making simple substitution, dB/dG = $150. It suggests that a $1 increase in the per capita local public expenditure will increase the sales price of commercial units by $150, on average, for the Phoenix SMSA. Multiplying the coefficient of LOCEXP by its mean value ($986), one can find that a long-run elasticity of the average sales price of commercial units with respect to a city’s per capita noneducational public expenditure is 0.59, indicating that a 1 percent increase in a city’s per capita noneducational public expenditure increases the sales value of the commercial property located in the city by 0.59 percent.

The elasticity of the average market price of commercial property with respect to

the local sales tax rate can also be obtained by multrplying the coefficient of the sales tax vanable by its mean value (1.085%), which is - 1.36, rmplyrng that 1 percent Increase in the local sales tax rate, on average, reduces the sales price of commercial property by 1.36 percent, about $3,400 on average. To make the coefficient of the sales tax variable com- parable with that of the per capita public expendrture, one can find that a $1 increase in per capita local sales tax revenue will decrease the market value of the commercial property by about $28 (Table 4).

By comparing these magnrtudes, one can find that the percentage change (increase) in the sales price of commercial property induced by each additional percentage point change (increase) in the public service expenditure outweighs the percentage change (decrease) in the sales price induced by each additional percentage point change (increase) in the commercial property tax rate. Also, the elasticity of the sales price of commercial property with respect to the local sales tax is larger than that with respect to the property tax rate. It indicates that changes in the sales price of commercial real estate are more sensitive to the changes in local sales tax rate than to those in commercial property tax rate.

The results from the above tax capitalization study suggest that interjurisdictional tax differences on commercial real estate are largely caprtalized into the sales value of the commercial assets in the Phoenix metropolitan area. Over 70 percent of the tax on commercial real estate is borne by its owners instead of users or consumers. It implies that the demand for commercial assets and the products made with commercial property IS relatively price elastic. Differences in local sales taxes among municipalities are also capitalized into the sales value of commercial property in the

TABLE 4 IMPACT ON THE MARKET VALUE OF COMMERCIAL PROPERTY BY TYPE OF TAX AND

PUBLIC EXPENDITURE

$1 Increase in Tax Bill or Per Capita Tax Revenue or Public Spending

Property tax -812 - .386% Local sales tax - $2B ! - .36% Public expenditure ~~-----Blso--- +~0.59% --- _---~ Note: Entries are percentaqe chanqes in the sales price of commercial property calculated from esjimated coefficients shown in Table 3.

Phoenix SMSA. A heavier burden of local sales taxes may reduce the attractiveness of the city to commercial firms and dis- courage their investment in the high-tax city, causing the commercial property in the community to be sold at a lower price, everything else equal. The statistic:al results also support the view that local public service provision benefits not only households, but also benefits commercial firms so that the differences in the level of public services are capitalized into a higher sales price of commercial real estate.

Incidence of Intrajurisdictional Tax Differences

Although the study of irterjurisdictional tax differences may shecl light on the allocative and efficiency effects of fiscal policy and distribution of tax burden, there are still considerable cortroversies over the measurement of public services. For instance, what services should be included and how to meal;ure them (e.g., by expenditure, quality indexes, benefits received as measured by willingness to pay). These difficulties ctln be avoided, at least in principle, by the microdata study of intrajurrsdictional tax differences. Un- der the assumption that public services do not vary within jurisdictions, one may make G in equation 11 constant In intrajunsdictional tax analysis.

Table 5 reports the stati:,tical results of regression analysis o-f the !,ales price of

-tY‘!

commercial units on th? predicted effective ‘tax rate and a set df variables on structural and locational characteristics. The estimates of EBTAY frorn OLS and 3SLS regressions are - ‘I 6.9 and - 16.26, respectively. The results from OLS are re- ported only for compar son.They are all significantly different fr

b

m zero at the 5 percent level or less, implying a strong negative effect of intrajiurisdictional tax differences on the sellidg price of commercial units.

As discussed in the previous section, the 3SLS estimate of property tax rate is preferred. The calculation of the degree of capitalization is based qn the staristical results with 3SLS estimatiion of equation 11. By using the rule thlat dB/dTp = /Y/(1 + /?tp) for a semilog equation regression

and sub:.tituting the m an value of property tax late of 0.0364 “i or the city of Phoenix, one can find t at dB/dP is - 10.21. Still applying he 5 percent dis-

count rate and 40 year I’ assumed life of structure, I find that ne rly 60 percent of intrajurisdictional tax di ferentlals are borne by property own rs. These results suggest that the comm i rcial property tax differentials in the cent al

5 city of Phoenix

are largely capitalized i to the sales price of commercial real estate. They also indicate that the demand f r commercial property and the products made with the 0 taxed assets are price elastic. There may exist some degree of tak shifting from property owners to conisumers for this sample data set and time, but a larger part of tax differences dmong properties


TABLE 5 PARAMETER ESTIMATES FOR INTRAJURISDICTIONAL COMMERCIAL PROPERTY TAX DIFFERENCES

(DEPENDENT VARIABLE: LCPRICE)

Independent Variables OLS Estimation t-Statistics 3SLS Estimation t-Statistics

Constant EBTAX AGE AGESQ SQFT MODERN OBSOLETE ADD GRADEG GRADEP IMPROVEG IMPROVEP WALLB WALLFC WALLC HEATAIR HEATFUR COOLR COOLE NEIGHBOR MARKET2 MARKET3 MARKETS MARKET8 OFFICE STORE SHOP DEPTS BANK YYB5 YYB6 YYB7

Adjusted R2 0.74 Sample size 516

10.21 (25.2)a 10.18 - 16.91 (14.3)” -- 16.26 - 0.029 (5.8)a - 0.029

0.0003 (3.O)a 0.0003 0.068 (12.8)” 0.068 1.61 (5.O)a 1.60

-0.21 (1.1) -0.21 - 0.7E-03 (1.4) - 0.7E-03

0.59 (2.6)” 0.59 -0.18 (2.2)a -0.18

0.56 (1.3) 0.56 - 0.40 (2.O)a -- 0.40

0.38 (2.4)a 0.38 0.73 (1 .a 0.90

-0.12 (0.6) --0.12 0.37 (2.4)a 0.37 0.15 (1 .a 0.15

-0.18 (1.1) -0.18 - 0.24 (2.O)a -- 0.24

0.13 (2.6)a 0.13 0.115 (1.7)b --0.117 0.504 (2.9)” 0.506 0.164 (0.4) 0.16

-0.14 (1 .8)b -0.14 0.101 (1.3) 0.098 0.151 (2.l)a 0.151 0.706 (3.O)a 0.706

- 0.077 (0.2) - 0.095 0.68 (1.1) 0.69

- 0.047 W-3 -- 0.047 0.076 (0.9) 0.08

-0.134 (1.5) --0.13

- 516

(17.8)” (2.0)” (3.O)a (1.8)d

(1 2.3)a (5.O)a (1 .a (1.3) (2.5)a (2.0)” (1.3) (2.0)” (2.4)a (1.5) (0.6) (2.4)a (1 .a (1.1) (1 .8)b (2.6)” (1.5) (2.8)a (0.3) (1.7)b (1 .a (2.l)a (3.0)” (0.2) (1.0) (0.6) (0.8) (1 .a

Note: Footnotes are the same as Table 2.

in the central city of Phoenix falls on both capital and land owners.

Conclusions

This paper aims to provide empirical evidence concerning the incidence of both interjurisdictional and intrajurisdictional commercial property tax differences, using data for the Phoenix SMSA and the central city of Phoenix. The estimation equation in this study has accounted for the simultaneity between the market value of commercial real estate and property tax rates by explicitly specifying and testing an econometric model of the property tax rate. The left-out-variable

bias is also avoided by using the effective property tax rates as the tax variable and by making use of an extensive set of control variables for structural and locational attributes. The study finds that over 70 percent of tax differences among municipalities within the Phoenix metropolitan area fall on property owners, while about 60 percent of tax differences across properties within the central city of Phoenix fall on property owners. It suggests that the burden of both Interjurisdictional and intrajurisdictional differences in taxes on commercial properties is largely borne by property owners, either capital owners or land owners, or both. Consumers could

also bear some of the tart burden by pay- ing higher output prices, but much smaller in magnitude cornpared with that borne by property owner’s. These findings run contrary to Mieszkowski’s argument that more than 75 percent of commercial tax differences are borne by consumers of products made with the taxed capital in the form of higher price!;. Instead, as my analysis indicates, over 60 percent of the tax burden IS borne by the owners of land and capltal for either interlurlsdlc- tional or intrajurisdictional tax differentials on commercial property.

The evidence uncovered in the present study also implies that the spatial demand for commercial real estate and products made with commercial capital IS highly price elastic within the Phoenix SMSA. With a highly elastsc demand for the goods and services prod_rced with the taxed commercYal property, property owners will bear most ol: the differential tax burden. As long as the supply of land and real estate capital fcir commercial uses is not perfectly price inelastic, the differences in after-tax return to capital and land induced by tax differentials would result In the flighi of resources out of the high-tax jurisdiction to the low-tax jurisdiction or out of the commercial real estate market to other uses in the long run. Thus, there may exist significant resource allocation effects and wealth effects from both the interjurisdictional and intrajurisdictional commercial property tax differences.

The empirical analysis also reveals that interjurisdictional differences in local sales taxes and public expenditure are also capitalized into the sales values of commercial property. As the property and sales tax differences as well as differences in public services significantly affect the values of commercial real estate, one can in- fer that the local government fiscal policy has significant impact upon business location and investment dec sions, and conse-

quently, ion the level of local economic activity.

ENDNOTES

This paper IS based on part of my unpub- I&led F h.D dnssertation, at the Johns Hop- kins University, Baltimorp, MD I am grateful to Brucl? Hamrlton, my ;idviser, for guidance and helpful suggestionsi I thank DII:k Netzer and John Mlkesell for cdmmentlng on an earlier version of this palper. I am also in- debted to Michael Bell fpr allowlng me to use some of his data. Hpwever, any remain- ing errors of omission or commission are my rer,ponr,lblllty alone.

l Another c11y in the Phoenix SMSA, Paradise Valley, IS not Included in the sample because it has no sale of commercial real estate for the sample period. It doles not levy local properly tax.

’ A jet of simple t-tests is performed to determine n hether each of these Ivariables ex- cluded from the sales p{ice equation is truly exogenous, in the sense that it does not belong to the equation as an explanatory vanable and it is uncorrelat

7 d with the error term. The rest works asifollovvs. First, the re- slcluals are calculated frqm an auxiliary re- gressiol of a lpotential ibstrument variable (e.g., r ) on the set of ekogenous variables in the tales price equatipn, plus other variables hypothesized to be exogenous. Sec- ond, I test the null hypdthesis that the coefficient of the residuals ii zero when they are included a<, an explanatpry variable in the sales pt Ice equation. Thps, the joint null hy- pothesls required for ex genetty is tested. A slgniflcjnt estimate of t R e coefficient of the residual Indicates either~the tested variable belong; in the sales priqe equation or it is correla-ed with the error term and therefore IS inot 21 proper instrumqntal variable. The statutory property tax r&e vanable (t”) IS not used ar an instrument because It fails the exogenelty test to satisfl the two character- istlcs fclr Instrument variables.

’ Ordinary least squares ($LS) estimation provides similar results as the 3SLS procedure does, except for the prqperty tax variable (providlzd upon request)(. For example, the coefficient estimate of i!/BTAX is 18.49 with a I’-statistic of 10.3 fror-0 the OLS estimation. The hislh t-value is not @edible when compared \vith those of coefflclents of other variablcls that could be t’nuch more important and visible in determining commercial unit’s price. It indicates that there exists simultaneity bias introduded by the presence


of Vin the measurement of the tax rate. By using 3SLS technique to control for such a problem, we get a more credible t-value of the coefficient of EBTAX. The differences of t-statistics and the values of the estimated coefficients between the OLS estimate and estimates from 3SLS support the critrques of King (1973) and Martinez-Vazquez and Ihl- anfeldt (1987). They argue that the failure of controlling for the simultaneity problem leads to downward bias that produces spuri- ously negative and significant estimate of the property tax rate coefficient, even if it has no effect at all, and at the same time causes underestimation of the degree of caprtalization.

The mean value of the commercial property in the sample is $250,078.

From the definition of the tax liability, Tp = tpB. Taking into account not only the change in Tp due to the change in P, but also the fact that B will change when P changes, then we have dTp = B dP + P dB and dfP = (dTp - P dB)/B. Because we know that /I = d InBldP in the equation with semilog

functional form, it can be written as dB = pB dfp. Substituting the former dfP equation into the above one, we get dB/dTp = /I/(1 + /IF), where tp is the mean sample prop-

erty tax rate, which is 0.023 for cities or towns in the Phoenix metropolitan area. The implied dB/dTp coefficient is - 12.1.

Dusansky, Ingber, and Karatjas (1981) did not allow for the change in the mean value of B due to the change in tp in their calculation of the degree of capitalization. By par- tially differentiating Tp = PB with respect to tp, they obtained dB/dP = B. Using their measure of capitalization, we can get dB/dTp = /?. As it is widely accepted by economists

that any change in tp will lead to a change in B, I will use the formula discussed above for calculation of degree of capitalization. See Martinez-Vazquez and lhlanfeldt (1987) for various specifications.

REFERENCES

Aaron, Henry J. Who Pays the Property Tax? Washington, D.C.: The Brookings Institution, 1975. Brueckner, Jan K. “Property Values, Local Public Expenditure and Economic Efficiency.” Journal of Public Economics 11 (April, 1979): 223-45.

Brueckner, Jan. K. “A Test for Allocative Effi- ciency in the Local Public Sector.” Journal of

Pub//c Economics 19 (December, 1982): 31 l- 31. Dusansky, Richard, Melvin Ingber, and Nicholas Karatjas. “The Impact of Property Taxation on Housing Values and Rents.” Jour- nal of Urban Economics 70 (September, 1981): 240-55. Hamilton, Bruce W. “Capitalization of Intra- jurisdictional Differences in Local Tax Prices.” American Economic Review 66 (December, 1976): 743-53.

Ihlanfeldt, Keith R. and John D. Jackson. “Systematic Assessment Error and Intrajurisdic- tional Property Tax Capitalization.” Southern Economic louma/ No. 2 (October, 1982): 417-27. King, A. Thomas. Property Taxes, Amenities, and Residential Land Values. Cambridge, MA: Ballinger, 1973. Ladd, Helen F. and Katharine L. Bradbury. “City Taxes and Property Tax Bases.” National Tax Journal 4 1 No. 4 (December, 1988): 503- 23. Man, Joyce Y. and Michael Bell. “The Im- pact of the Local Sales Tax on the Value of Owner-Occupied Housing.” Journal of Urban Economics (forthcoming). Martinez-Vazquez, Jorge and Keith R. Ihl- anfeldt. “Why Property Tax Capitalization Rates Differ: A Critrcal Analysis.” In Perspec- twes on Local Public Finance and Public Policy, edited by John M. Quigley, 127-56. Green- wich, CT: JAI Press, 1987.

McDonald, John F. “Incidence of the Property Tax on Commercial Real Estate: The Case of Downtown Chicago.” National Tax Journal 46 No. 2 (June, 1993b): 109-20. Mieszkowski, Peter M. “The Property Tax: An Excise Tax or a Profit Tax?” Journal of Pub- lic Economics 7 (April, 1972): 73-96. Muth, Richard F. Cities and Housing. Chicago: The University of Chicago Press, 1969.

Netzer, Dick. Economics of the Property Tax. Washington, D.C.: The Brookings Institution, 1966

Wheaton, William. “A Bid Rent Approach to Housrng Demand.” Journal of Urban Econom- ics 4 (April, 1977): 200-l 7. Wheaton, William. “The Incidence of Inter-junsdictional Differences In Commercial Property Taxes.” National Tax Journal 37 No. 4 (Decem- ber, 1984): 515-27. Wilson, John D. “The Excise Tax Effects of the Property Tax.” Journal of Public Economics 24 (August, 1984): 309-29.

495

APPENDIX

TAHLE A- I VARIABLE DEFINITIONS” __~________~_

Variable IName Description

--_--_---- Commercial Real Estate Sales Price Equation

ILCPRKE Sales value of commercial property in 1985, 1986, 1987, and 1988 in 1977 dollars in logarithm (jointly depended)

,EBTAX Effective property tax rate for individual units of commercial property (jointly depended)

(DEBTAX) Differences between the effective commercial property tax rate and the city’s statutory tax rate (jointly depended)

Square feet of usable area (1,000 square ft.)

(1) Structural Characteristics SQFT

AGE AGESQ .ADD

MODERN

Effective age of Qructure (years) Age of structure squared Dollar value of additions to the main building ($1,000) Degree of modernization of the buildings .for commercial uses (in percent)

OBSOLETE

GRADEG

GRADEP

PCONDITG

IMPROVG

IMPROVP

HEATAIR

HEATFUR

WALLB

WALLC

WALLFC

COOLR

COOLE

Degree of obsolescence of the structural style (in percent) Dummy variable that takes the value 1 if the unit judged good and 0 otherwise Dummy vijriable that takes the value 1 if unit judged minimum and 0 otherwise Dummy variable if physical condition is rated above average Dummy variable if improvement class is rated good or excellent Dummy variable if improvement class is rated loti minimal or poor Dummy v<ariable that takes the value of 1 for having forced warrn air or steam heating Dummy v,jriable that takes the value of 1 for having vvall furnace/unit heaters Dummy variable that takes the value of 1 if exterior wall is built with brick or brick veneer Dummy variable that takes the value of 1 for exterior wall with concrete tilt-up Dummy variable that takes the value of 1 for exterior wall with concrete or steel structural framing Dummy variable that takes the value of 1 for refrigeration cooling system Dummy variable that takes the value of 1 for evaporative cooling system

(2) Locarional Attributes NElGHBOR Neighborhood desirability

deterrnined by assessors (in percent) VACANTR Vacant rate of the total units in the

jurisdiction

DENSITY Population density (100s per square mile)

MARKET(i) Dummy variables for market area indicator where each parcel of commercial property is located (total 10 market areas)

(3) Accessibility to Transportation faci/i%y and Work Force DISTA N Linear distance of each city to

central business district of Phoenix DISTSQ Distance squared HIGHDUM Dummy variable that is unity if an

interstate or state highway runs through the city and 0 otherwise

RAlLDlST Distance in miles from city hall to the nearest railway

COLLED Percentage of the city’s residents with a college education

(4) Public Serwces and Nonproperty Tax Variables LOCEXP Per capita noneducational

expenditure in the city on public services such as ,police and fire protection, road, parks, sewage and garbage collect/on, etc. in 11986 (in 1977 dollars)

5 TAX/i The city’s sales tax rates from 198543 (S) Year Dummies YYBS Dummy variable that takes the value

1 if the building is sold m 1985 and 0 otherwise

YY86 Dummy variablq that takes the value 1 for sales in 19186 and 0 otherwise

YY87 Dummy variable that takes the value 1 for sales in Id87 and 0 otherwise

Property Tax Rate Eauation t”

NEW

OLD

OFFICE

STORE

DEPT.5

SHOP

BANh

RESTR

POPCHAN POP7 8PC

POP6SPC

POVE RN

a L denotes rhe riaturdl logarithm.

the incidence of differential commercial property … · ied upon commercial and industrial prop-...

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