The effect of change in the property tax: evidence from the Swedish

taxation reform*

Timotheos Mavropoulos1

This version: October 16, 2014

Preliminary draft

Abstract

The paper investigates the effect of the property taxation reform

introduced in Sweden after April 2007 on the market price of the

affected properties (one-family houses). Inference is focused on

discount rates, growth rates and the implied degree of tax

capitalization. Stronger results for the capital compared to the rest of

the country underline the importance of land scarcity for the degree

of tax capitalization.

*I would like to thank Peter Englund for his advice during the completion of this term paper and encouragement

whenever I found obstacles in proceeding. I would also like to thank Valueguard AB and in particular Lars-Erik Ericson

for his support in data extraction process. Gratitude goes to participants of the NFN PhD conference 2014 and Kristian

Miltersen (Copenhagen Business School). 1

Stockholm School of Economics (email: timotheos.mavropoulos@hhs.se)

1

Introduction

The degree of capitalization of property taxes and its effect on the market price of properties is an

important subject to investigate. Property tax reductions shift the tax burden from current homeowners to

the future ones. In the current paper I try to investigate if the tax effects are rationally accounted for by the

market. In particular, it is interesting to know to which degree the Swedish property market for one-family

houses capitalizes the property taxes, hence revealing the information about the expectations on the future

taxation treatment of such properties. I will analyze a tax reform announced in April 20071. Until 2007 the

tax was proportional to house value. From April 2007 a cap on the tax in SEK was introduced. This meant a

sharp reduction of the tax for most properties in Stockholm and other major markets, but no reduction in

other parts of the country. Though the magnitude of the tax effect is not obvious, it is clear that it should

differ across different types of properties depending on their assessed value (e.g. major cities versus

provincial areas).

The research literature on the capitalization of property taxes is rather scarce and mainly

concentrated on the US property tax system (Bradley 2011, Bradbury et al. 2001). Most of the literature is

cross-sectional in nature and asks whether differences across jurisdictions in taxes and local amenities get

capitalized in house prices. Few studies deal with the dynamic issue of price effects due to a tax reform. A

recent example is a study by Bradley 20112, where the effect of tax obligations of new homebuyers is

explored in connection to the sale prices using data on homes sold in Michigan for the 1997-2007 period.

Introducing a cap on the taxable values of the real estate properties results in a substantial variation in tax

obligations for existing homeowners vis-à-vis new entrants to the housing market. The study of taxation cap

can reveal the degree of real estate market efficiency. In particular, if the existing homeowners with lower

tax obligations due to the introduced cap are overcompensated as if such a cap is maintained permanently,

the market is considered highly efficient. This is important information from the policy decision point of

1 A more detailed description of the reform history is given in the later section.

2Bradley Sebastien, Capitalizing on Capped Taxable Values: How Michigan Homebuyers are Paying for Assessment

Limits, University of Michigan, 2011.

2

view. Elinder and Persson (2014), while exploring price responses and capitalization degrees from the

Swedish real estate reform present results largely inconsistent with capitalization theory, emphasizing the

role of behavioral theories of bounded rationality as a key explanation. I will attempt to contribute to the

literature by exploring the effect of the taxation cap introduction in Sweden in 2007 while emphasizing the

rational explanations, taking into account the implied discount rates and degrees of tax capitalization.

I proceed with reform history in the context of property taxation environment in Sweden, refer to

capitalization theory, data, sample selection and methodology, present results and conclusion.

Property taxation in Sweden

To carry out property taxation the Tax Agency in Sweden completes real estate assessment

according to a rolling schedule triennially, with different types of assessment units like one- or two-dwelling

buildings, apartment buildings, units for agriculture and forestry, etc. The assessed value is set at 75% of the

market value. From 2007, as will be described in a later section, a reform was introduced with government

property tax on dwellings having been abolished and replaced by a local real estate fee. Since then the

charge for single-family houses should not exceed 0.75% of the tax assessed value and reachingin total

SEK6.387 billion in 2010. It should be noted that taxes on property are the relatively insignificant as a source

of government tax revenue in Sweden with 2.4% share of total tax revenues as of 20093.

Reform history

The Swedish Homeowners Association (VillaägarnasRiksförbund) - a national organization with

322.000 members (households) throughout Sweden promoting the interests of homeowners has been

lobbying for years to abolish the property taxes on one-family houses.

In 2007 Fiscal Policy Bill of proposed guidelines on the economic and budgetary policy (Regeringens

proposition 2006/07:100), dated 12th of October 2006, it was mentioned that the property tax will be at

3http://www.skatteverket.se/download/18.3684199413c956649b57c0a/1361442608379/10413.pdf

3

some point abolished but no details were provided (2006/07:1, volym 1, s. 147). The projection was that

“the reform will be implemented during fiscal year 2008”.Later on, the Proposition 2006/07:100 dated 10th

of April 2007mentioned that the property tax will be abolished (effectively from the taxation year 2008) and

substituted with a “fee”(“fastighetsavgift”). The proposal was to make it 0.75% of Tax Assessed Value up to

SEK4.500, with the details to be announced and discussed until the fall. It was also mentioned that the

reform would be funded "within the sector" but did not describe exactly how. Finally, Proposition

2007/08:27 dated 25th ofOctober 2007 announced the actual reform with the cap at SEK6.000 (increased

fromSEK4.500 announcedpreviously). The funding of the reform was planned through an increase of the

capital gains tax from 20% to 22% and the introduction of an 0.5% interest charge levied on the tax liability

when the capital-gains tax can be rolled forward, which is the case when it is reinvested in housing. From the

reform history it can be inferred that the reform dating is rather fuzzy, thus a definite pre-reform period can be

determined as the earliest possible period ranging from a newly-conducted assessment in 2006 (i.e. January

2006) till the earliest possible rumors about the reform. The problem is that the mentioned rumors may have

already started from October 2006, leading to a decision of making January 2006 the earliest possible pre-

reform period to examine the effect of the 2007 reform on a set of properties assessed during 2006 and

onwards.

Tax capitalization theory in the context of Swedish taxation reform

The standard model of property tax capitalization is presented in this section4. This model will be

modified to accommodate the effects of the Swedish property tax reform, and in particular the

discontinuous tax treatment after October 2007 of properties sold after the reform. A description of the

model departs from the idea that market value of the property equals to the present value of the stream of

housing services net of property tax obligations and then introduces the necessary features to account for

4To refer to a more thorough presentation of the basic model, see Ross and Yinger (1999) as well as Yinger(2005)

4

the reform. Assuming that constant continuous housing services R5 over the infinite lifetime of the house

embody all associated public services and other amenitiesnet of tax payment, then we can investigate the

effect of the reform in the following way. Before the reform the property tax was equal to 1% of the tax

assessed value, or 0.75% of the market value6. After the reform the property tax equals to 0.75% of tax

assessed value with a cap of SEK6.000 or, in terms of assessed value, SEK800.000. To illustrate the reform

effect on the tax payment, observe the graph below:

Graph 1. Tax reform illustration: tax assessed value in SEK plotted against corresponding tax obligations in SEK

The cap introduced by the reform establishes a decrease in tax obligations proportional to the properties’ tax assessed

value.

Expressing this in terms of market value before the reform with the real discount factor 𝑟 − 𝑔,

where constant growth rate of housing services g and the constant discount rate𝜌 are assumed, one gets:

MV0 =R0

ρ − g + 0,0075=

TAV

0,75

while after the reform, for the properties below SEK800.000 in tax assessed value:

5 Note that this assumption has implications for the resulting magnitude of tax capitalization. When land is scarce, the

total supply of land may be assumed to be fixed, with the long-run supply having positive slope. This, together with the long-run output growth in the economy which is likely to raise the total demand for land, is contributing to the increasing relative prices of land used for housing purposes, and hence the market price of houses. The housing services R in this case should adjust downwards due to an increased supply. As a result, the current theoretical calculations may overstate the resulting capitalization. 6Typically the assessment process aims to determine the assessment value at 75% of the market value one year before

the assessment is conducted. Property owners fill in the detailed questionnaire where the characteristics of the house via hedonic indices determine the property tax assessed value.

02000400060008000

100001200014000

Tax

ob

ligat

ion

in S

EK

Tax Assessed Value in SEK

Tax Reform Illustration

Tax before

Tax after

5

MV′ =R0

ρ − g + 0.75 ∗ 0,0075=

TAV(ρ − g + 0,0075)

0,75(ρ − g + 0.75 ∗ 0,0075)

and for the properties above SEK800.000 in tax assessed value and the tax cap of SEK6.000 (assuming the

cap also grows at rate 𝑔):

MV′ =R0

ρ − g−

6.000

ρ − g=

TAV(ρ − g + 0,0075)

0,75(ρ − g)−

6.000

ρ − g

The difference before and after the reform for the above SEK800.000 properties is thus:

MV′ −𝑀𝑉0 =TAV ρ − g + 0,0075

0,75 ρ − g −

6.000

ρ − g−

TAV

0,75=

0,01TAV

ρ − g−

6.000

ρ − g

Expressing the difference before and after in terms of a ratio, we have for the above SEK800.000 tax

assessed value properties:

𝑀𝑉′

𝑀𝑉0=

TAV (ρ−g+0,0075)

0,75(ρ−g)−

6.000

ρ−g

TAV

0,75

= 𝜌 − 𝑔 + 0.0075

𝜌 − 𝑔−

6.000 ∙ 0,75

TAV(𝜌 − 𝑔)

A table presenting the above ratio of capital gain MV ′

MV depending on different values of the real discount

factor ρ − g and the tax assessed value TAV is given below:

Table 1. Ratio of capital gain due to reform for the properties with the tax assessed value above SEK800.000

ρ-g

TAV

800.000 1.000.000 1.500.000 2.000.000 5.000.000 10.000.000 ∞

0,01 1,188 1,300 1,450 1,525 1,660 1,705 1,750

0,02 1,094 1,150 1,225 1,263 1,330 1,353 1,375

0,03 1,063 1,100 1,150 1,175 1,220 1,235 1,250

0,04 1,047 1,075 1,113 1,131 1,165 1,176 1,188

0,05 1,038 1,060 1,090 1,105 1,132 1,141 1,150

0,075 1,025 1,040 1,060 1,070 1,088 1,094 1,100

0,1 1,019 1,030 1,045 1,053 1,066 1,071 1,075

The table shows that with increase in the tax assessed value TAV the ratio of capital gain 𝑀𝑉′

𝑀𝑉becomes very

sensitive to the discount rate ρ-g.Note that after the reform, the difference in market values between the

above SEK800.000 and below SEK800.000 tax assessed value properties is:

MV>800′′ − MV<800′

′ =TAV ρ − g + 0,0075

0,75 ρ − g −

6.000

ρ − g−

TAV ρ − g + 0,0075

0,75 ρ − g + 0.75 ∗ 0,0075 =

=0,0075 ρ − g + 0,0075

ρ − g ρ − g + 0.75 ∗ 0,0075 TAV−

6.000

ρ − g

6

The theoretically derived relation above will be connected to the ones derived from regression

analysis in the next section.

Investigating the tax gain after the reform we should note that there are two sources of this gain to

be capitalized: a 0.25%TAV decrease from a 1%TAV tax and the cap itself. Since after the reform the tax on

properties is 0.75%TAV with the cap of SEK6.000, the cap in SEKto be capitalized is:

Cap = 0.75% ∙ TAV − 6000

For properties with TAV above SEK800.000, thatimplies in terms of capitalization in SEK:

Tax Gain per year = 0.25%TAV+ 0.75%TAV− 6000 = 1%TAV− 6000

or

Tax Gain =0,01TAV

ρ − g−

6.000

ρ − g

as noted previously. Since the tax assessed value can be assumed unchanged by the reform (it is

adjusted triennially), the driving force behind a change in market value for the properties with TAV above

SEK800.000 is the capitalized tax gain 0,01TAV

ρ−g−

6.000

ρ−g.

It should be noted that while the cap introduced by the reform could be assumed to stay constant

and not grow at rate g , so we could rewrite the tax gain as 0,01TAV

ρ−g−

6.000

ρand infer about 𝜌 and 𝑔 separately.

However, the policy in the aftermath of the reform (as of 2014) has indeed made an increase in the initially

proposed cap and in particular made the cap indexed to a disposable income index, with the 2014 cap being

SEK7.074. That implies annual cap growth rate of 2.78245%, revealing information about g that can be

further used in the analysis.

Furthermore, assuming the degree of tax capitalization β, one can express the tax gain as

β 0,01TAV

ρ−g−

6.000

ρ .

Note that since the discount rate ρ and the degree of tax capitalization β both enter the formula for

the capitalized tax gain one needs to hold either of the two fixed to infer about the degree of tax

capitalization or the implied real discount rate correspondingly. That is, one can infer about the degree of tax

7

capitalization by assuming particular real discount rates constant or, holding the assumption of full tax gain

capitalization, infer about the implied real discount rates.

Data and method

The data comes from transactions on all individual homes (one-family houses) between individuals

from 2007 until the latest available year from the real estate agencies (SvenskMäklarstatistikAB) when the

transaction was made.

The question is whether the market during the period of 2007-2008 fully capitalizes the property tax

is by no means simple to answer, given the fact that the discount rate cannot be determined not having

previously assumed the degree of tax capitalization and, analogously, to determine the degree of tax

capitalization one should assume a particular discount rate. One could in principle derive the implied

discount rate while assuming full degree of tax capitalization or, having assumed particular discount rates,

investigate the degree of tax capitalization implied from the property market values. In addition, a crucial

step is to compare the tax capitalization in provincial areas versus the capital city, since the testable

prediction is that in Stockholm the tax capitalization will be more profound due to land scarcity and higher

market values.

Sample selection

The whole sample consists of 86.830 properties sold in the years 2006-2008 and assessed in 2006.

Note that the number of properties sold that are above and below SEK800.000 are increasing during 2006

due to the fact that their relative share in the market- compared to the properties assessed in 2003 - is

increasing. However, in the sense that the differences between the above SEK800.000 group and below

SEK800.000 group are not affected by the assessment year per se, the sample of properties assessed in 2006

is not systematically different from the sample assessed in 2003 (consult Appendix for the details).

8

Graph 2. Illustrating the dynamics of the number of properties sold quarterly during 2006-2008 and assessed in 2006.

From graph 2 above it can be inferred that the relative share of the properties below and above SEK800.000

remains relatively stable in the reform period 2007-2008, and for the above SEK800.000 group is 52%.

Graph 3. Illustrating the relationship between the number of properties sold and the median market value

0

2000

4000

6000

8000

10000

12000

14000

Number of properties above and below SEK800.000

<800.000

>800.000

0

500000

1000000

1500000

2000000

0

2000

4000

6000

8000

10000

12000

14000

Number of properties and median Market value by quarter

Number of properties

Median MV

9

Graph 4. Illustrating the relationship between the number of properties sold and the median tax assessed value

The graphs 3 and 4 show a slight decreasing trend in the market value and the tax assessed value

during 2006. Comparing in to the data available from SCB, one notes that despite a slight decrease the

median TAV value is in line with the one mentioned by SCB7. One can observe a slight increase in the median

market value of properties in the treatment group after the reform. This slight increase actually occurs one

quarter prior to the reform and persists for the period until third quarter of 2008:

Graph 5. Illustrating the relationship between the market value of the properties with the tax assessed value of below and above SEK800.000

7http://www.scb.se/en_/Finding-statistics/Statistical-

Database/TabellPresentation/?layout=tableViewLayout1&rxid=c576218a-468f-4b11-85ba-d5704813a83d

0

200000

400000

600000

800000

1000000

1200000

0

2000

4000

6000

8000

10000

12000

14000

Number of properties and median Tax assessed value by quarter

Number of properties

Median TA value

0

500000

1000000

1500000

2000000

2500000

3000000

20

06

01

20

06

02

20

06

03

20

06

04

20

07

01

20

07

02

20

07

03

20

07

04

20

08

01

20

08

02

20

08

03

20

08

04

Mar

ket

Val

ue

Time (Quarters)

Median Market Value development over time for properties below and above SEK 800.000

MV (TAV<800000)

MV (TAV>=800000)

10

Empirical analysis

Note that the degree of tax capitalization depends on supply elasticity. Poterba (1984) underlines

that specification of the relationship between inputs of land and structures and outputs of housing services R

is almost impossible to obtain. However, land scarcity in the capital and other major city areas vis-à-vis

provincial areas is indicative for the corresponding difference in the degree of tax capitalization. In

Stockholm, for example, the degree of capitalization is expected to be much higher compared to provincial

areas or the whole country. The results for Stockholm presented later are supporting this prediction for the

degree of tax capitalization.

In the methodology applied in the study the event (taxation reform) is a change in government

policy and considered to be exogenous hence the data arise from a natural experiment. Note however the

fuzzy timing of the reform which prevents a clear distinction between the pre-reform and post-reform

periods.

Taking a sample of properties assessed in a particular year before the reform (2006) one can

investigate if the market value of the properties with TAV above SEK800.000(“treatment group”) was

affected disproportionally by the reform.

Presenting the results for Stockholm observe that all of the observations belong to the above

SEK800.000 group. The following basic model in levels is first investigated:

MVi = β0 + β1T + εi (1)

Where T denotes monthly time dummies for the whole period (2006-2008). Since this is a simple

regression on a monthly dummy variable, the intercept is the average market price for single family houses

in the base month of January 2006 (SEK 2.859.167 from the Table 2 in the Appendix) and the coefficient β1

on T is the difference in the average market price between houses sold in the base month of January 2006

and those sold in the month of the reform period, with the estimate indicating that on average, properties

sold in for example, April 2007 are sold for SEK 1.425.000 more than those in the base moth of January 2006.

11

Adding the tax assessed values variable and the corresponding interaction term to the above basic

model in levels, the following model is then estimated:

MVi = β0 + β1T + β2TAVi+β3T ∙ TAVi + εi (2)

It makes possible a direct comparison to the theoretically derived difference in the previous section.

Recall that:

MV′ −𝑀𝑉0 ==0,01TAV

ρ − g−

6.000

ρ − g

Thus β1 coefficient is related to 6.000

ρ−g while β3 coefficient is related to

0,01

ρ−g , making possible an

inference about the implied discount rates and the degree of tax capitalization for Stockholm. In addition,

with the help of coefficient β1 we can infer about the discount rate ρ, assuming the cap grows at rate

g=2.78245%, while the coefficient β3also provides inference about discount rate ρ assuming full degree of

tax capitalization.Predicted negative sign for the coefficient β1is observed. Jump is noticed from January

2007 onwards, and acquires maximum magnitude around the time of Proposition 2006/07:100 dated 10th of

April 2007 that mentioned that the property tax will be abolished. It should be noted that in terms of tax

assessed values, the 1SEK of the tax assessed value of the properties sold in the reform period has translated

in an at least 0.5SEK increase of market value of those properties compared to the base month.

For the implied discount rates and the degree of tax capitalization for Stockholm,observe the table

below for ρ,ρ being consistent at around 4% inferring from both coefficients β1and β3for the period of the

Proposition 2006/07:100 dated 10th of April 2007 which mentioned that the property tax will be abolished

(effectively from the taxation year 2008) and substituted with a “fee” (“fastighetsavgift”):

Month (2007) ρ= g +6000/β1 ρ = g +0.01/β3

Feb 3,62% 4,38%

Mar 5,68% 5,13%

Apr 4,77% 4,57%

May 3,54% 4,02%

Jun 3,66% 4,11%

12

While for the period around Propostion 2007/08:27 dated 25 October 2007 which announced the

actual reform with the cap at SEK6.000:

Month (2007) ρ= g +6000/β1 ρ = g +0.01/β3

Aug 3,77% 4,30%

Sep 6,19% 4,81%

Oct 3,54% 4,07%

Nov 3,64% 4,49%

Dec 3,57% 4,52%

Observe positive growth implied by the assumed full degree of tax capitalization and a relatively

stablereal discount rate of 4% implied from the market.

Now note the implied degree of tax capitalization βimplied from two different sources, in particular:

β =β1(ρ−g)

6000 and β =

β3(ρ−g)

0,01 :

For implied degree of tax capitalization from an assumed discount rate and coefficient β1, that is

β =β1(ρ−g)

6000 with g= 0,027825we have:

Month (2007)

ρ

3,50% 4,00% 4,50%

Aug 72,13% 122,39% 172,65%

Sep 21,02% 35,66% 50,31%

Oct 94,53% 160,41% 226,28%

Nov 83,79% 142,18% 200,57%

Dec 91,02% 154,44% 217,86%

While the implied degree of tax capitalization from an assumed discount rate and coefficient β3, that is

β =β3(ρ−g)

0,01 with g= 0,027825 we have:

Month (2007)

ρ

3,50% 4,00% 4,50%

Aug 47,36% 80,36% 113,36%

Sep 35,38% 60,03% 84,68%

Oct 55,68% 94,48% 133,28%

Nov 41,90% 71,10% 100,30%

Dec 41,33% 70,13% 98,93%

13

Observe that the degree of tax capitalization is proportional to the increase in the difference of real

discount rate and the growth rate as well as undercapitalization for comparatively smaller discount rates.

For the entire country a following regression is run:

MVi = β0 + β1TAVi + β2Tr + β3T+β4Tr ∙ TAVi + β5T ∙ TAVi + β6Tr ∙ T + β7Tr ∙ T ∙ TAVi + εi(3)

where T denotes monthly time dummies for the whole period (2006-2008) and Tr dummy variable for the

Treatment group (properties above SEK800.000), one infers to what degree the tax gain is capitalized into

the market value.

Observe that the coefficient β6 is the double interaction term of the monthly dummy with the

affected properties (treatment group) dummy while the coefficient β7 is the triple interaction term of the

monthly dummy with the affected properties (treatment group) dummy and their tax assessed value TAV.

The coefficientβ7showsthe average monthly increase in market value per 1SEK in tax assessed value

of the houses due to the reform, provided that properties with tax assessed values below and above SEK

800.000 did not appreciate for other reasons.

Coefficients β6 and β7also yield the degree to which tax gain is capitalized, i.e. the degree to which

tax gain is translated into the increase of the market value of the properties in the treatment group given

particular discount and growth rates.The estimates of these coefficients are to be compared to the

theoretical difference: 0,0075 ρ−g+0,0075

ρ−g ρ−g+0.75∗0,0075 TAV−

6.000

ρ−gfrom page 5. In particular, 0,0075 ρ−g+0,0075

ρ−g ρ−g+0.75∗0,0075 is to be related

to β7 while β6to 6.000

ρ−g. In addition, with the help of coefficient β6 we can infer about the discount rate ρ,

assuming the cap grows at rate g=0,0278245, while the coefficient β7also provides inference about

discount rate ρ, assuming full degree of tax capitalization.

After the initial reform, that is from 12 October 2006 as mentioned in Government proposition

2006/07:1 where the property tax was decided to be abolished, we would expect a kink in the relation

between MV and TAV, proportionality up to SEK 600.000 (due to initially discussed cap of SEK 4.500) and a

steeper slope above. Two sets of coefficients for the interaction TAV and time will be estimated, one for TAV

14

below and one for TAV above SEK600.000 (“treatment group”). Finally, since the proposition 2007/08:27

dated 25 October 2007 announces the actual reform where the cap is at SEK6.000 (not 4.500 as previously

announced), that is the treatment group consists now of properties above SEK800.000. The results for the

coefficient of interest (β7)are presented in the tables4-5 in the appendix (base month: Jan 2006). Observe a

significant jump in market value in the case of SEK6.000 cap - that is a much more significant price impact of

tax capitalization from January 2007 onwards.

For the implied discount rates and the degree of tax capitalization in the whole country,observe the

table below for ρ for the period around the Proposition 2006/07:100 dated 10th of April 2007 mentioned

that the property tax will be abolished (effectively from the taxation year 2008) and substituted with a “fee”

(“fastighetsavgift”):

Month (2007)

ρ=g+6000/β6

Feb 3,91%

Mar 3,71% Apr 4,06%

May 3,99%

Jun 5,92%

While for the period around Propostion 2007/08:27 dated 25 October 2007 which announced the

actual reform with the cap at SEK6.000:

Month (2007)

ρ=g+6000/β6

Aug 3,96%

Sep 3,74%

Oct 3,68%

Nov 4,45%

Dec 3,97%

Observe positive growth rates implied by the assumed full degree of tax capitalization and the

approximately 4% real discount rate implied from the market.

Now note the implied degree of tax capitalizationβ implied from different discount rates and

coefficients β6 and β7, with g=0,0278245:

15

β =β6(ρ − g)

6000

and

β =β7

0,0075 ρ−g+0,0075

ρ−g ρ−g+0.75∗0,0075

For implied degree of tax capitalization from an assumed discount rate and coefficient β6 , that is

β =β6(ρ−g)

6000 we have:

Month (2007)

ρ

3,50% 4% 4,50%

Aug 61% 104% 146%

Sep 75% 127% 179%

Oct 80% 135% 191%

Nov 43% 73% 103%

Dec 60% 102% 144%

While the implied degree of tax capitalization from an assumed discount rate and coefficient β7, that

is β =β7

0,0075 ρ−g+0,0075

ρ−g ρ−g+0.75∗0,0075

we have:

Month (2007)

ρ

3,50% 4% 4,50%

Aug 42% 74% 107%

Sep 44% 77% 110%

Oct 44% 77% 111%

Nov 20% 35% 51%

Dec 38% 67% 97%

Observe that the degree of tax capitalization is proportional to the increase in the difference of real

discount rate and the growth rate as well as the fact that the tax is capitalized less compared to Stockholm.

Several conclusions can be drawn from tables 3-5 and graphs 6-8 in the appendix. The cap of SEK6.000

resulted in a much more significant price impact regarding a tax capitalization, the point estimates become

more precise in the period around the Proposition 2006/07:100 dated 10th of April 2007and improve further

as one goes from a country level to the capital city level.

16

Robustness check

As a robustness check, the regional analysis is performed as follows: the provinces (kommuns) are

divided into two groups: one group is consistent of the kommuns where more than 90% of the properties

have a tax assessed value above SEK800.000, and the other – where more than 90% of the properties have a

tax assessed value below SEK800.000. The regression for the kommuns is:

MVi = β0 + β1TAVi + β2Gr1 + β3Gr3 + β4T+ βidouble interaction terms10i=5 + β10TAV ∙ T ∙ Gr1 + β11TAV ∙ T ∙ Gr3 + εi(4)

where T denotes quarterly time dummies for the whole period (2006-2008) and Gr dummy variable for the

group that the property sold belongs to (Gr1 denotes kommuns with the majority of properties below

SEK800.000, while Gr3 those above). From the regression results one infers that the tax gain is capitalized to

a larger degree in geographical areas where the majority of properties are theoretically affected by the

taxation reform. Consult the table below for further details (1Q 2006 is a base quarter) and observe that the

timing of the jump is around the Proposition 2006/07:100 dated 10th of April 2007,mentioning that the

property tax will be abolished (see table 6 in the Appendix):

It is noted that for the post-reform period the kommuns with the majority of properties above

SEK800.000 show significant jump regarding their market value. Descriptive graphs for the kommuns where

the majority of the properties (more than 90%) have their TAV above SEK800.000, and those where the

majority of the properties (more than 90%) have their TAV below SEK800.000 are provided below. There are

24.325 properties in the kommuns where the majority of the properties have TAV above SEK 800.000, and

54.871 properties in the ones where the majority of the properties have TAV below SEK 800.000:

17

Graph 9. Geographical areas (kommuns) where properties sold over a 2006-2008 period have in majority tax assessed value above SEK800.000

Graph 10. Geographical areas (kommuns) where properties sold over a 2006-2008 period have in majority tax assessed value below SEK800.000

Results and Conclusion The paper investigated the effect of the property taxation reform introduced in Sweden after April

2007 on the market price of the affected properties (one-family houses). Observe that the degree of tax

capitalization is proportional to the increase in the difference of real discount rate and the growth rate as

well as a much more profound degree of capitalization in the capital of Stockholm compared to the

provincial areas. The degree of tax capitalization is also very sensitive to the real discount rate, which under

148000015000001520000154000015600001580000160000016200001640000

0500

1000150020002500300035004000

Kommuns with the majority of the properties (more than 90%) having TAV above SEK 800.000

Number of properties

Median GroupHigh TAV

0100000200000300000400000500000600000700000800000

010002000300040005000600070008000

Kommuns with the majority of the properties (more than 90%) having TAV below SEK 800.000

Number of properties

Median GroupLow TAV

18

full degree of tax capitalization reaches 4%. An increase in real discount rate from 3,5% to 4,5% nearly

doubles the degree of tax capitalization.

As a concluding remark, note that the study was performed for the entire country as well as for the

capital city. Since the market price of a house includes the price of land, the tax capitalization channel may

be lying through the increase of the land prices. However, in the period 2005-2008 the land prices for

housing - as approximated by the price of agricultural land - were increasing at an almost constant rate8,

something which implies that that in the reform period of 2007-2008 the driving force behind the market

price increase in the housing market was a capitalized tax gain capitalized to a higher degree in the capital

city of Stockholm in comparison to the rest of the country.

8See Sorensen, 2013, ”The Swedish housing market: trends and risks”, agricultural land prices analysis, page 14.

Appendix

Table 2.Simple regression (1), Stockholm

Months 2006 2007 2008

Jan 618599 495564

(585236) (579485)

Feb 183864 1.340e+06** 1.137e+06**

(609963) (551382) (563641)

Mar 280833 1.357e+06** 1.236e+06**

(609963) (548694) (582802)

Apr 294992 1.425e+06*** 1.484e+06***

(589280) (551115) (557201)

May 846449 1.455e+06*** 1.159e+06**

(568516) (541575) (556442)

Jun 380064 1.247e+06** 532917

(597320) (543816) (572196)

Jul 124833 310833 697976

(774757) (682227) (860562)

Aug 347227 1.219e+06** 1.037e+06*

(571414) (558406) (601107)

Sep 809485 1.367e+06** 999452*

(556442) (542568) (569921)

Oct 642599 1.365e+06** 561262

(553398) (538754) (605298)

Nov 669495 931310* 705098

(564760) (540674) (607566)

Dec 831083 1.068e+06* 459333

(660715) (561570) (660715)

Constant 2.859e+06***

(522341)

N 3157

R-squared 0,043

Table 3.Estimation results for regression (2), Stockholm

Coefficient: β1 (T) Coefficient: β3 (TAV_x_dT) Coefficient: β2 (TAV)

Constant

Months 2006 2007 2008 2006 2007 2008

Jan -664,728* -247,322 0.558*** 0.376 1.731*** -190,470

(378,351) (488,459) (0.213) (0.285) (0.0658) (162,150)

Feb -9,587 -718,142** -1.099e+06*** 0.0285 0.627*** 0.889***

(303,410) (317,121) (421,802) (0.165) (0.162) (0.227)

Mar 734,618** -206,700 -1.062e+06** -0.384** 0.426*** 0.931***

(294,370) (310,497) (458,567) (0.151) (0.152) (0.256)

Apr -160,501 -301,685 -388,217 0.0788 0.560*** 0.606***

(302,717) (326,199) (310,723) (0.163) (0.172) (0.158)

May -189,174 -790,819** -391,204 0.162 0.805*** 0.596***

(244,567) (330,546) (289,647) (0.112) (0.168) (0.150)

Jun -13,078 -683,902** -657,360** 0.0177 0.751*** 0.737***

(328,701) (339,332) (319,163) (0.164) (0.178) (0.175)

Jul -562,141 214,066 1.351e+06*** 0.376 0.219 -0.529**

(633,834) (425,923) (368,207) (0.364) (0.244) (0.209)

Aug 49,102 -603,122** 505,692 0.0122 0.660*** 0.0290

(208,283) (281,990) (372,597) (0.102) (0.137) (0.207)

Sep -134,829 -175,738 -458,150 0.157 0.493*** 0.531***

(255,987) (272,839) (341,028) (0.123) (0.138) (0.170)

Oct -169,233 -790,467** -280,652 0.259* 0.776*** 0.325***

(273,376) (325,155) (212,289) (0.143) (0.167) (0.0989)

Nov -155,360 -700,672** -361,526 0.241 0.584*** 0.352***

(346,951) (272,589) (222,142) (0.185) (0.140) (0.107)

Dec 562,262 -761,052* -110,483 -0.134 0.576** 0.155

(436,447) (439,715) (348,052) (0.249) (0.232) (0.171)

N 3157

R-squared 0.831

Graph 6.Coefficient β3 point estimates and confidence intervals over a 2006-2008 period, Stockholm

Graph 7.Coefficient β7 point estimates and confidence intervals over a 2006-2008 period, cap SEK4.500

Graph 8.Coefficient β7 point estimates and confidence intervals over a 2006-2008 period, cap SEK6.000

-1.5

-1

-0.5

0

0.5

1

1.5

-1.5

-1

-0.5

0

0.5

1

1.5

-1.5

-1

-0.5

0

0.5

1

1.5

Table 4. Coefficient β7, the cap of SEK4.500

Table 5. Coefficient β7, the cap of SEK6.000

Coefficient: β7 (TAV_x_dTr_x_dT)

Coefficient: β7 (TAV_x_dTr_x_dT)

Months 2006 2007 2008

Months 2006 2007 2008

Jan

0.121 0.292

Jan

0.358 0.535**

(0.286) (0.292)

(0.225) (0.271)

Feb 0.296 0.0606 0.229

Feb 0.127 0.475*** 0.390**

(0.269) (0.234) (0.246)

(0.221) (0.183) (0.185)

Mar -0.134 0.335 -0.198

Mar -0.0400 0.564*** 0.0171

(0.313) (0.241) (0.320)

(0.196) (0.188) (0.329)

Apr -0.251 0.181 0.168

Apr 0.252 0.407** 0.485***

(0.268) (0.240) (0.229)

(0.194) (0.185) (0.174)

Maj -0.0623 0.188 0.104

Maj 0.205 0.467*** 0.277

(0.264) (0.227) (0.262)

(0.195) (0.173) (0.247)

Jun -0.216 -0.0479 -0.173

Jun 0.329* 0.195 0.0911

(0.250) (0.264) (0.286)

(0.197) (0.251) (0.281)

Jul 0.0564 -0.268 -0.604**

Jul 0.230 -0.154 -0.513*

(0.254) (0.310) (0.281)

(0.203) (0.329) (0.270)

Aug -0.0819 0.315 -0.0994

Aug 0.135 0.504*** 0.197

(0.253) (0.223) (0.229)

(0.186) (0.177) (0.180)

Sep -0.0398 0.179 0.0471

Sep 0.176 0.522*** 0.406**

(0.246) (0.232) (0.228)

(0.178) (0.186) (0.182)

Okt -0.170 0.172 -0.127

Okt 0.201 0.526*** 0.191

(0.230) (0.223) (0.232)

(0.175) (0.177) (0.185)

Nov 0.0890 0.0654 -0.00662

Nov 0.191 0.241 0.311*

(0.256) (0.227) (0.225)

(0.188) (0.174) (0.177)

Dec -0.238 0.0749 0.154

Dec 0.138 0.457** 0.408**

(0.258) (0.239) (0.245)

(0.191) (0.178) (0.199)

N

86830

N

86830

R-squared 0.833

R-squared 0.834

Table 6.Coefficients β10 and β11 for the period 2006-2008

Year-Quarter Coefficient:

β10(TAV_T_Gr1) Coefficient: β11

(TAV_T_Gr3)

2006-Q2 0.0636 0.134

(0.151) (0.140)

2006-Q3 -0.0682 -0.0114

(0.143) (0.133)

2006-Q4 -0.181 -0.115

(0.134) (0.124)

2007-Q1 -0.123 0.139

(0.130) (0.121)

2007-Q2 -0.0608 0.360***

(0.127) (0.118)

2007-Q3 -0.0896 0.313**

(0.131) (0.122)

2007-Q4 0.000346 0.254**

(0.127) (0.118)

2008-Q1 -0.642*** -0.184

(0.129) (0.120)

2008-Q2 0.186 0.691***

(0.126) (0.116)

2008-Q3 -0.409*** 0.00123

(0.130) (0.122)

2008-Q4 -0.0561 0.174

(0.129) (0.121)

N 86830

R-squared 0.835

Tables show the median Tax Assessed Values and number of properties sold by sales year and assessment years. Last rows and columns are, correspondingly:

median TAV of the properties sold during the whole period, by assessment year (2003-2012), median TAV of the properties sold for all assessment years, by

year (2005-2012):

Sales year Median TAV by : Assessment year

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Median

2005 663000 662000 913000 1055000 669000

2006 607000 591000 619000 1040000 1975000 689500 717000

2007 498000 475000 511000 853000 1031000 828000

2008 605000 483000 445000 855000 805000 1046000 1175000 832000

2009 657000 707000 424000 924000 870500 900000 1029000 636500 936000

2010 711000 358000 646500 874000 790000 820000 1176000 838000 401500 1132500

2011 707000 2130000 394000 727000 597000 847000 1177000 1186000 865500 1493500 1173000

2012 514000 454000 779000 530000 889000 1232000 1190500 1250000 1128000 1222000

Median 637000 652000 613000 893000 818000 891000 1167000 1173000 1232000 1133000

Sales year Number of transactions by : Assessment year

Total 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

2005 15510 17407 383 444

33744

2006 10126 2644 14487 11501 8 2

38768

2007 716 127 1579 39274 89

41785

2008 79 22 113 18644 17240 72 111

36281

2009 15 2 13 12250 3622 12977 8956 28

37863

2010 7 3 6 951 173 2014 35542 650 28

39374

2011 3 1 5 121 46 175 20018 15007 482 90 35948

2012 4

1 35 15 60 13682 4192 14314 3498 35801

Total 26460 20206 16587 83220 21193 15300 78309 19877 14824 3588 299564

The observations in bold, totaling 86.830, are the ones used in the regression analysis. Note from the first table that Median TAV of the properties sold

during the whole period and assessed in 2006 is 46% higher compared to the Median TAV of the ones assessed in 2005.

Tables show the median Tax Assessed Values and number of properties sold by sales month and assessment years. Last rows and columns are, correspondingly: -Median TAV of the properties sold in a particular year (2006, 2007, 2008), by assessment year (2003-2009) -Median TAV of the properties sold for all assessment years, by month (Jan-Dec 2006, Jan-Dec 2007, Jan-Dec 2008)

Sales 2006

Median TAV by: Assessment year

Sales 2007

Median TAV by: Assessment year

Sales 2008

Median TAV by: Assessment year

2003 2004 2005 2006 2007 2008

2003 2004 2005 2006 2007

2003 2004 2005 2006 2007 2008 2009

Jan 588000 614000 925000 1097000

678000

Jan 472000 640000 530000 933000 718667 758500

Jan 455000

420000 821000 760000

807500

Feb 630000 599000 698000 1124500

714000

Feb 481000 705000 502500 962000 818000 866000

Feb 618000 448000 387500 913000 795000 1122000

878000

Mar 627500 586000 673000 1057000

722000

Mar 455500 428500 452000 920000 865000 860000

Mar 476500 294000 1178000 871000 789000 1070000

839000

Apr 672000 518000 725000 1131000

754500

Apr 479000 443000 477000 923500 1409500 894000

Apr 952000 293000 524500 896500 908000 1242000

899000

May 661000 596000 668000 1130000

740000

May 564000 341500 521000 859500 578000 838000

May 682000 796500 472000 906000 894000 1457500

900000

Jun 597000 600500 661000 1077000

687000

Jun 622000 642000 506500 850000 1004000 841000

Jun 564000 732500 387500 840000 821500 623000 1827000 827500

Jul 519000 529500 498000 836500 1950000

567000

Jul 519500 258000 489000 672000 1298000 662000

Jul 465500 207000 410500 673000 662000 1189000

664000

Aug 513500 395000 526000 948000

638000

Aug 406500 505500 455000 745000 1330000 742000

Aug 303000 1711000 687500 765000 713000 1041500

734000

Sep 643000 453000 586000 1099000 3751000 786000 774000

Sep 509000 1194000 642000 848000 929000 842000

Sep 1053000 1024000 343000 891500 835000 1389000

854000

Oct 603000 645000 633000 1086500 1351000 593000 806000

Oct 573500 715000 636500 909500 1267500 907000

Oct 386000 1447000 319000 872000 790500 904000 1679000 822000

Nov 622000 575500 595500 1026000 2200000

788000

Nov 760500 284000 637000 871000 1135500 869000

Nov 393500

1231000 933000 839500 900000 1012000 887000

Dec 586000 653000 556500 926500 1282000

718000

Dec 584000 933500 480000 829000 1178000 828500

Dec 445000 470000 558000 886000 829000 1161000 1168000 853000

607000 591000 619000 1040000 1975000 689500

498000 475000 511000 853000 1031000

605000 483000 445000 855000 805000 1046000 1175000

Sales 2006

Number of transactions by : Assessment year

Sales 2007

Number of transactions by : Assessment year

Sales 2008

Number of transactions by : Assessment year

2003 2004 2005 2006 2007 2008 Total

2003 2004 2005 2006 2007 Total

2003 2004 2005 2006 2007 2008 2009 Total

Jan 654 686 211 218

1769

Jan 185 15 451 1277 2 1930

Jan 5

9 1473 137

1624

Feb 879 579 717 454

2629

Feb 143 24 346 2401 3 2917

Feb 10 3 16 1942 721 1

2693

Mar 990 383 1168 573

3114

Mar 104 14 202 3036 3 3359

Mar 2 1 5 1647 1154 4

2813

Apr 834 219 1203 538

2794

Apr 56 8 119 2922 6 3111

Apr 9 3 14 1890 1675 2

3593

May 1261 219 1895 781

4156

May 59 12 116 4302 5 4494

May 15 4 15 2226 2147 2

4409

Jun 1299 180 2023 775

4277

Jun 42 11 100 4545 3 4701

Jun 9 2 16 1959 1984 2 2 3974

Jul 846 100 1233 590 1

2770

Jul 24 13 58 2887 5 2987

Jul 8 1 8 1219 1455 3

2694

Aug 764 84 1171 1063

3082

Aug 18 6 52 3158 11 3245

Aug 3 1 8 1248 1561 6

2827

Sep 856 78 1521 1871 1 1 4328

Sep 28 9 62 4335 16 4450

Sep 10 4 7 1620 2093 7

3741

Oct 775 61 1427 1882 2 1 4148

Oct 26 9 36 4528 12 4611

Oct 5 2 7 1398 1766 13 9 3200

Nov 664 38 1172 1810 2

3686

Nov 20 4 28 3492 12 3556

Nov 2

3 1153 1396 17 41 2612

Dec 304 17 746 946 2

2015

Dec 11 2 9 2391 11 2424

Dec 1 1 5 869 1151 15 59 2101

Total 10126 2644 14487 11501 8 2 38768

Total 716 127 1579 39274 89 80563

Total 79 22 113 18644 17240 72 111 36281

The downward trend in TAV values during the sales period Jan2006-Jan2007 can be observed both for Assessment Year 2005 (from SEK 925.000 to SEK

530.000) and Assessment Year 2006 (from SEK 1.097.000 to SEK 933.000). Note from the first table that Median TAV of the properties sold in year 2006 and

assessed in 2006 is 68% higher compared to the Median TAV of the ones assessed in 2005.

Tables show the median Tax Assessed Values and number of properties sold by sales year and assessment years for Stockholm sample. Last rows and

columns are, correspondingly: median TAV of the properties sold during the whole period, by assessment year (2003-2012) and median TAV of the properties

sold for all assessment years, by year (2005-2012)

Sales year Median TAV by : Assessment year

Median 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

2005 1550000 1467000 1735000 2044000

1508000

2006 1619000 1447000 1512500 1776000

1661000

2007 1570000 1114500 1293000 1857000 2806000

1835500

2008 2321000 1097000 1444500 1783000 1821000 2034000 3461000

1806000

2009 1755000 1697000 1779000 2958000 5600500

2037000

2010 2022500 2447000 1653000 2718000 2736000

2657000

2011 1343000 1759000 2802500 2658000 4016000 4374000 2709000

2012 1395000

1574000 2837000 2809000 2721000 3948500 2839000

Median 1572000 1467000 1469000 1820000 1815000 1761000 2773000 2688000 2726000 3950000

Sales year Number of transactions by : Assessment year

Total 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

2005 444 663 13 39 1159

2006 243 53 458 575

1329

2007 11 2 41 1363 5 1422

2008 3 3 6 606 610 1 4 1233

2009

347 83 472 341 2

1245

2010

4 2 53 1209 13

1281

2011

1 6 498 567 2 1 1075

2012

1 1 423 107 549 102 1183

Total 701 721 518 2935 701 533 2475 689 551 103 9927

The observations in bold, totaling 3.160, are the ones used in the regression analysis. Note from the first table that Median TAV of the properties sold

during the whole period and assessed in 2006 is 23,9% higher compared to the Median TAV of the ones assessed in 2005.

Tables show the median Tax Assessed Values and number of properties sold by sales month and assessment years for Stockholm sample. Last rows and

columns are, correspondingly: median TAV of the properties sold in a particular year (2006, 2007, 2008), by assessment year (2003-2009) and median TAV of

the properties sold for all assessment years, by month (Jan-Dec 2006, Jan-Dec 2007, Jan-Dec 2008)

Sales 2006

Median TAV by: Assessment year

Sales 2007

Median TAV by: Assessment year

Sales 2008

Median TAV by: Assessment year

2003 2004 2005 2006

2003 2004 2005 2006 2007

2003 2004 2005 2006 2007 2008 2009

Jan 1334000 1241500 1499000 1600000 1469000

Jan 1869000

1258000 1771000 1669000

Jan

1560000 1669000 1774000

1683000

Feb 1953000 1628000 1522500 1558000 1636500

Feb 2052000

1293000 1914000 1833000

Feb

1273500 1710000 1739000

1710000

Mar 1501000 1409000 1491000 2020000 1539500

Mar 1645000

1413000 1933000 1865500

Mar

2612500 1848000 1796500

1812000

Apr 1434000 1380000 1332000 1697000 1582000

Apr

1127000 1856500 1832000

Apr 2083000

1996000 2009500 2034000

2004000

May 1665500 1655000 1626500 1919000 1753000

May

1199500 1941000 1928500

May 2378000 1097000 1271000 1830000 1998000

1894500

Jun 1619000 2033000 1692000 1733000 1702500

Jun 1570000

1358000 1802000 1800000

Jun

1629500 1805500

1704500

Jul 1750500

1447500 1594000 1581500

Jul

1445000 1445000

Jul

1905000 1599500

1736000

Aug 1370500

1365000 1768000 1578000

Aug

1210000 1911000 1898500

Aug

1890000 1613000

1765500

Sep 1742000 1616000 1561000 1977000 1795000

Sep 1377000 1082000 1069000 1899500 2354000 1893000

Sep

1047000

1767000 1904000

1817000

Oct 1768000 2107000 1587500 1742500 1742500

Oct 1273000 1147000 1286000 1850000 2806000 1850000

Oct

2786000

1582000 1823500

3583000 1726500

Nov 1835000 1805000 1360500 1807000 1744500

Nov 1265500

1879500 1797000 3135000 1792000

Nov

1791500 1816000

3123500 1833000

Dec 1492500

1749000 2079000 1847000

Dec 1866000 1866000

Dec

1797500 1849000

1832000

1619000 1447000 1512500 1776000

1570000 1114500 1293000 1857000 2806000

2321000 1097000 1444500 1783000 1821000 2034000 3461000

Sales 2006

Number of transactions by : Assessment year

Sales 2007

Number of transactions by : Assessment year

Sales 2008

Number of transactions by : Assessment year

2003 2004 2005 2006 Total

2003 2004 2005 2006 2007 Total

2003 2004 2005 2006 2007 2008 2009 Total

Jan 8 12 11 12 43

Jan 3

9 47

59

Jan

1 52 4

57

Feb 35 16 26 33 110

Feb 1

9 105

115

Feb

2 73 32

107

Mar 35 13 43 33 124

Mar 2

6 116

124

Mar

2 49 34

85

Apr 23 3 55 44 125

Apr

1 106

107

Apr 2

87 76 1

166

May 32 4 82 65 183

May

4 160

164

May 1 1 1 89 104

196

Jun 29 1 75 39 144

Jun 1

5 143

149

Jun

60 56

116

Jul 6

8 10 24

Jul

17

17

Jul

7 16

23

Aug 18

23 61 102

Aug

2 84

86

Aug

37 43

80

Sep 19 1 52 89 161

Sep 1 1 2 152 1 157

Sep

1

63 81

145

Oct 19 1 42 98 160

Oct 1 1 1 188 3 194

Oct

1

35 68

2 106

Nov 15 2 30 71 118

Nov 2

2 168 1 173

Nov

34 49

2 85

Dec 4

11 20 35

Dec

77

77

Dec

20 47

67

Total 243 53 458 575 0

Total 11 2 41 1363 5 0

Total 3 3 6 606 610 1 4 1233

Note from the first table that Median TAV of the properties sold in year 2006 and assessed in 2006 is 17.4% higher compared to the Median TAV of the ones

assessed in 2005, while for the properties sold in year 2007 the corresponding increase is 43%.

References

Bradbury L., Mayer J. and Case E., 2001, “Property tax limits, local fiscal behavior, and property

values: evidence from Massachusetts under Proposition 21

2”, Journal of Public Economics, Vol

80 (2), 287-311.

Bradley J., 2011, “Capitalizing on Capped Taxable Values: How Michigan Homebuyers are

Paying for Assessment Limits”, University of Michigan.

Elinder M. and Persson L., 2014,“Property taxation, bounded rationality and housing

prices”.Department of Economics Working Paper, Uppsala University.

Feldman E., 2010, “A Reevaluation of Property Tax Capitalization: The Case of Michigans

Proposal A”, Working Paper.

Oates E., (1969), “The Effects of Property Taxes and Local Public Spending on Property Values:

An Empirical Study of Tax Capitalization and the Tiebout Hypothesis”, Journal of Political

Economy, Vol 77 (6), 957-971.

Palmon O. and Smith A., 1998, “New Evidence on Property Tax Capitalization”, Journal of

Political Economy, Vol 106 (5), 1099-1111.

PoterbaJ.M.,1984, “Tax Subsidies to Owner-Occupied Housing: An Asset-Market Approach”,

The Quarterly Journal of Economics, Vol. 99, No. 4, 729-752.

Richardson H. and Thalheimer R., 1981, “Measuring the Extent of Property Tax Capitalization

for the Single Family Residences”, Southern Economic Journal, Vol 47 (3), 674-689.

Rosen T., 1982, “The Impact of Proposition 13 on House Prices in Northern California: A test of

the Interjurisdictional Capitalization Hypothesis”, Journal of Political Economy, Vol 90 (1), 191-

200.

Sorensen P.B., 2013, The Swedish housing market: Trends and risks, Rapport till

Finanspolitiskarådet.

Yinger J., Ross, 1999, Sorting and Voting: A Review of the Literature on Urban Public Finance,

Handbook of Regional and Urban Economics.

Yinger J., 2005, Housing and Commuting: The Theory of Urban Residential Structure, Chapter

5.4: Property Tax Capitalization, e-book.

Yinger J., Bloom S., Borsch-Supan A. and Ladd F., 1988, “Property Taxes and House Value:

The Theory and Estimation of Intrajurisdictional Property Tax Capitaization”, San Diego:

Academic Press.