1 property tax © allen c. goodman, 2009 2 2006 37.6

1

Property Tax

© Allen C. Goodman, 2009

2

Property Tax as Percentage of State and Local Taxes

--

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

1975 1980 1985 1990 1995 2000 2005

Year

Per

cen

tag

e

Great Lakes

Illinois

Indiana

Michigan

Ohio

Wisconsin

http://www.taxpolicycenter.org/taxfacts/displayafact.cfm?Docid=517

1977 1982 1987 1992 1997 2002 2004 2005Great Lakes.................................................................................36.9 36.8 33.6 36.0 32.8 33.8 34.8 34.9 Illinois .................................................................................36.7 35.7 34.2 38.6 38.1 38.1 39.6 38.0 Indiana .................................................................................36.8 35.6 32.0 30.7 34.6 35.2 32.5 35.8 Michigan .................................................................................37.5 42.5 38.2 42.7 29.0 32.0 35.8 36.6 Ohio .................................................................................37.7 33.6 28.2 29.7 28.8 29.4 28.7 28.7 Wisconsin .................................................................................34.5 35.0 34.6 34.9 33.4 34.7 36.3 36.4

2006

37.6


3

Property Taxes as a Percentage of Total State and Local Taxes, Selected Years 1977-2005

Region and State [1] 2005 2004 2002 1997 1992 1987 1982 1977

United States .................................................................................30.6% 31.5% 30.8% 30.1% 32.2% 29.9% 30.8% 35.5%

New England.................................................................................39.2 40.1 40.0 37.6 39.3 35.8 40.9 47.3 Connecticut .................................................................................37.9 39.5 39.6 35.7 40.3 38.7 43.1 46.6 Maine .................................................................................41.2 42.1 42.1 43.0 39.3 33.4 37.8 36.4 Massachusetts .................................................................................36.0 36.3 36.5 32.9 34.3 30.7 37.6 49.0 New Hampshire .................................................................................61.4 61.9 60.3 66.0 60.0 61.2 62.1 62.0 Rhode Island .................................................................................40.4 41.9 40.4 41.9 43.9 38.1 42.0 40.8 Vermont .................................................................................41.0 41.6 41.9 44.6 42.4 41.7 41.4 40.5

Mideast.................................................................................32.0 33.1 32.3 32.9 33.6 29.8 32.0 35.2 Delaware .................................................................................14.8 15.1 14.9 15.9 14.1 13.6 15.2 16.2 District of Columbia.................................................................................26.4 25.9 24.9 26.5 37.5 28.5 27.6 22.4 Maryland .................................................................................23.4 27.0 27.2 25.9 28.0 24.4 26.7 29.4 New Jersey .................................................................................45.1 46.1 46.3 46.6 44.6 40.3 43.9 50.7 New York .................................................................................30.7 31.9 30.2 32.0 33.4 28.8 32.1 35.9 Pennsylvania .................................................................................29.1 29.3 29.0 28.3 27.8 26.5 26.1 26.1

Great Lakes.................................................................................34.9 34.8 33.8 32.8 36.0 33.6 36.8 36.9 Illinois .................................................................................38.0 39.6 38.1 38.1 38.6 34.2 35.7 36.7 Indiana .................................................................................35.8 32.5 35.2 34.6 30.7 32.0 35.6 36.8 Michigan .................................................................................36.6 35.8 32.0 29.0 42.7 38.2 42.5 37.5 Ohio .................................................................................28.7 28.7 29.4 28.8 29.7 28.2 33.6 37.7 Wisconsin .................................................................................36.4 36.3 34.7 33.4 34.9 34.6 35.0 34.5

1. Have declined somewhat over last 30 years

2. Highest in New England, less in Great Lakes, even less in Mideast.http://www.taxpolicycenter.org/taxfacts/displayafact.cfm?Docid=517


4

Schematic (Fisher text)

Rule

Tax Variable

Agent

Actual or True Mkt Value

5


Rule

Tax Variable

Agent


Assessed orTaxable Value

Ratio ruleExempt Property

Assessor

6


Rule

Tax Variable

Agent



PropertyTax Levy


Assessor

Rate andTax Limits

TaxingGov’t

ReferendumRequired or Optional

7


Rule

Tax Variable

Agent



PropertyTax Levy

PropertyTax Revenue


Assessor

Rate andTax Limits

TaxingGov’t

ReferendumRequired or Optional

Tax Collector

8

How Property is Assessed

• Comparative Sales, or “Comps” – What has been the value of other recently sold properties?

• Cost Approach – How much did the property cost to build?– How much have construction costs changed?– How much has it depreciated?

• Income Approach– What is net present value of income to be generated

by property?

Most oftenfor residences.

Cost and income approachesare most often used for

commercial property.

Valuations as golf courses, for example, are often based on

how much they can earn.

9

Comparables

• If you’re buying (appraising) a house, you do this.

• Look at house you’re buying (appraising)– Find other comparable houses.– See how they differ.– Adjust values based on differences.

• (Sometimes) float baseline values up according to neighborhood specific inflation factors.

10

Adjustments to make “comparable”

similar to appraised house

Better than subject house, so you adjust this downward.

Larger than subject house, so you adjust this downward.

11

On-Line Tools

• There are also on-line appraisal tools

• Here’s one.– http://www.zillow.com

http://www.zillow.com/

12

Proposal A in MichiganProposal A Spreadsheet

Tax RateRate 1.5%

Value % CPI Taxable Effective Taxes on MobilityYear Value Increase Inflation Value Taxes Rate Value Tax

1994 200,000 200,000 3,000 1.50% 3,000 01995 220,000 10.0% 2.5% 205,017 3,075 1.40% 3,300 2251996 240,000 9.1% 2.8% 210,808 3,162 1.32% 3,600 4381997 255,000 6.3% 2.9% 216,992 3,255 1.28% 3,825 5701998 265,000 3.9% 2.2% 221,766 3,326 1.26% 3,975 6491999 275,000 3.8% 1.3% 224,704 3,371 1.23% 4,125 7542000 290,000 5.5% 2.2% 229,723 3,446 1.19% 4,350 9042001 300,000 3.4% 3.5% 237,686 3,565 1.19% 4,500 9352002 320,000 6.7% 2.7% 244,183 3,663 1.14% 4,800 1,1372003 360,000 12.5% 1.4% 247,581 3,714 1.03% 5,400 1,6862004 400,000 11.1% 2.2% 253,131 3,797 0.95% 6,000 2,2032005 420,000 5.0% 2.6% 259,713 3,896 0.93% 6,300 2,4042006 420,000 0.0% 3.5% 268,868 4,033 0.96% 6,300 2,2672007 400,000 -4.8% 3.2% 277,516 4,163 1.04% 6,000 1,8372008 375,000 -6.3% 2.9% 285,472 4,282 1.14% 5,625 1,343

13

Housing -- Why is it Different?

• Why?– Housing is heterogeneous– Housing is immobile– Housing is durable– Housing is expensive– Moving costs are high– Neighborhood comes with housing … and it

matters!

14

Heterogeneous?

• Dwellings differ in:– house size (sq. feet)– lot size (sq. feet)– configuration– quality

• People seem to value these qualities differently.

15

Immobile?

• It is where it is. Where you buy it, you get:– Accessibility (to good and bad things)– Package of local public services– Environmental quality

• Further– You can’t (really) “move” houses– You can’t rebundle them (use half of two

different houses at the same time).

16

Price: The Hedonic Approach

• Hedonic approach looks at house as a bundle of components.

• Analogy: Suppose that when you went to the grocery store, all you could buy were “filled” shopping carts (food, soaps, etc.), and each one had a price.

• You know what’s in them, but you can’t take things out or put things in.

17

Price: The Hedonic Approach

• How do you figure out what the individual components are worth?

• A> If you had a large sample of carts, and each had different amounts of goods in them, then you could come up with the value of the individual components.

18

Hedonic Prices

P (ln P) = P (House, Neighborhood, Location, Services)

P (ln P) = P (h1, …, hi, n1, …, nk, l1, … lj, s1, …, sm)

Usually estimated as:

P = i aihi + k bknk + j cjlj, + m dmsm

These give you the coefficients:

The “hedonic price” of housing component i, for example, is:

P/ hi = ai

If P is in log form, then:

P/ hi = aiP

We’ll spend a lecture on this stuffafter the exam.

19

Example for Hedonic Prices

• Suppose that sq. feet of living space was ALL that mattered in the price of house.

• You collect data on lots of houses.

Sq. feet

Pri

ce

20


• What does this suggest?– A> Bigger

houses have more value.

• Let’s draw a line.

Sq. feet

Pri

ce

?

?

21


• Line has a form:

Price = a + b*size

Sq. feet

Pri

ce

• What does a mean?

• What does b mean?

a

slope = b

22


• Says that for each additional sq. ft., house price is $b more.

Sq. feet

Pri

ce

• Although it is hard to think of, we could draw this diagram in n dimensions!

a

slope = b

b is the hedonic price of house size.

23

n dimensions?

Let’s look at a house with 2000 sq.ft., 5 rooms for $75,000 Pr

ice

Sq. feet20005

75

Let’s look at a house with 3000 sq.ft., 6 rooms for $100,000

3000

6

100

Rooms

Line has a form: Price = a + b*size + c*rooms

24

How do you do this?

• Let’s look at the examples from the Brasington Database.• Parameter Estimates

Parameter StandardVariable Estimate Error t Value Pr > |t|

Intercept 11962 927.66440 12.89 <.0001bedrooms -3581.51 302.64817 -11.83 <.0001agehouse -496.30 6.47546 -76.64 <.0001buildingsqft 93.62 0.34959 267.79 <.0001

• R2 = 0.5294• SER = 65629

25

Parameter StandardVariable Estimate Error t Value Pr > |t|

Intercept -2983.78 960.58704 -3.11 <.0001bedrooms -6066.13 302.92296 -20.03 <.0001

brick 4990.21 432.77493 11.53 <.0001

fullbath 22079 440.67336 50.10 <.0001agehouse -372.20 6.83443 -54.46 <.0001buildingsqft 83.86 0.39310 213.32 <.0001

• R2 = 0.5404• SER = 64854

Or

26

Prediction is Important!• The prediction accuracy threshold employed by the

automated valuation model (AVM) industry is that at least 50% of the predicted house prices must be within 10% of observed transaction prices.

• Goodman and Thibodeau (2007) find:

Standard Spatial SM PSF SM Hybrid

Percent within 10% 35.53% 66.04% 62.90% 65.06%

Percent within 15% 50.86% 78.73% 76.69% 78.32%

Percent within 20% 63.32% 86.11% 85.49% 86.74%

• Why is this important?– If you predict too low, you lose money– If you predict too high, you incite costly appeals.

SM = submarket

2727

Analyzing the property tax

• If we look at land, labor, and capital, the property tax is a tax on plant, land, and equipment, but not on labor.

• As a result property tax will be borne by– Owners of the property and/or– Consumers of the goods that are made by the taxed.

• Much of the analysis comes from an (almost entirely unreadable) article by Peter Mieszkowski, “The Property Tax: An Excise Tax or a Profits Tax,” Journal of Public Economics, 1972

• Also McLure, Charles E., Jr., "The 'New View' of the Property Tax: A Caveat,". National Tax Journal, Vol. 30 (March 1977), pp. 69-75

2828

How Mobile is Capital?

• From town to town, ultimately pretty mobile.

• For the country as a whole, possibly not very mobile.

• What does this mean?

Suppose the supply elasticity of capital is 0!

Suppose the supply elasticity of capital is 0!

S$

Amount of Capital

D = MPcapital

Income from Capital

r0

2929

If we impose a national property tax?

• Effective demand shifts down.

S$

Amount of Capital

D = MPcapital

Income from Capital

r0

(1-t)r0

• Who pays the tax?

TAX

Why?Why?

3030

We don’t have a national property tax … but

• Suppose we have 1000 municipalities and none of them impose a property tax.

• Now, suppose that one of them (Southfield) imposes a 2% property tax.

• We want to look at Southfield … and at the rest of the world.

• What happens to capital in Southfield … and what happens elsewhere?

3131

Southfield … and elsewhereSouthfield

LR Supply, why?

Demand

$

Amount of Capital

Elsewhere

LR Supply, why?Demand

$

Amount of Capitalb0 B0

After-Tax Demand

3232

Where does the capital go?Southfield

LR Supply

Demand

$

Amount of Capital

Elsewhere

LR Supply

Demand

$


After-Tax Demand

Everywhere Else!Everywhere Else!

B1

b1

3333

What has happened?Southfield

LR Supply

Demand

$

Amount of Capital

Elsewhere

Demand

$


After-Tax Demand

B1

b1

Price of capitalwent up a LOTin Southfield

This is an excise tax

effect!

Return to capital went

down by0.02/1000

Elsewhere.

LR Supply

Prices of items made

with capital in Southfield

a lot.

Prices of items madewith capitalelsewhere

a little.

3434

Remember

• This was only 1 city in 1,000.• Suppose a second city passes a 2%

property tax. Big excise tax there; little capital tax

elsewhere.• Suppose eventually that every one of them

passes a 2% property tax.• What do you have? A national property

tax!

3535

What has happened?Southfield

LR Supply

Demand

$

Amount of Capital

Elsewhere

Demand

$


After-Tax Demand

B1

b1

r0 (1 – 0.02)

Allocation of capital isthe same as at the beginning.

Return is 2% lower!

LR Supply

r0 (1 – 0.02)

3636

So … what do we have?

• The tax differentials between jurisdictions function as excise taxes (if there is a “national” property tax of 2%, then a jurisdiction w/ taxes of 3% will incur excise tax effects).

• The overall weighted property tax functions as a national tax on capital and land.

3737

Incidence

• Incidence depends on:– Excise tax effects (probably somewhat

regressive)– Capital ownership effects (probably somewhat

progressive).

3838

Who pays?

• Carroll and Yinger (1994) look at $1.00 increase in city property taxes used to produce $1.00 of services for renters.

• They find that landlords bear between 70 and 91% of the increase because tenants are relatively more mobile than landlords.

1 property tax © allen c. goodman, 2009 2 2006 37.6

Documents

optional slide

michigan slide

true mkt value slide

optional tax collector

property tax allen

property cost

commercial property

house size