Property Tax Reform and Land Use:
Evidence from Japan
Tomomi Miyazaki
Motohiro Sato
Abstract
It is often said that farmland conservation in urban areas (i.e., cities and inner suburbs) is not desirable
because it hinders converting farmland into residential areas, thereby deterring urbanization. If thepreferential treatment of property taxes on farmland is rectified, these problems can be solved. In thispaper, we study two property tax preferential treatment reforms that took place in Japan
during the 1990s. We examine the effects of these reforms by theoretical and empirical investigation.
The econometric results are consistent with our theoretic model’s main predictions; the proportion of
farmland in the major cities in the three metropolitan areas (Tokyo, Chubu, and Kansai) decreased
following the reforms. However, since landlords did not replace all the farmland with housing lots,
the problem of obstructed urbanization remains to be solved.
Key words: Property tax, land use in urban area, preferential treatment on farmland, urbanization
JEL Classification: H22, H71, R52, R58

 We conducted this study as a part of the “Economic Analysis of Property Tax and Reform Program” undertaken at

the Research Institute of Economy, Trade and Industry (RIETI). Miyazaki thanks the University of California (UC)
Irvine for giving him the opportunity to be a visiting researcher. We would like to acknowledge the following
individuals for their insightful comments and suggestions: Nobuo Akai, Real Arai, Lars-Erik Borge, Jan Brueckner,
Takero Doi, Amihai Glazer, Shinya Horie, Toshihiro Ihori, Keigo Kameda, Ryuta Ray Kato, Daiji Kawaguchi, Chung
Mo Koo, Shiyu Li, Masayuki Morikawa, Patricia Moser, Katsuji Nakagane, Shi-ichi Nishiyama, Kazuki Onji, Hiroki
Tanaka, Kimiko Terai, Tuan Khai Vu, Robert Wassmer, Junichi Yamasaki, and Hideo Yunoue. We would also like toacknowledge seminar participants at Chuo University, Kansai University, Kobe University, RIETI, and UC Irvine.
The Japan Society for the Promotion of Science (JSPS, Grant-in-Aid for Scientific Research #16H03637 and#17K03764) provided financial support for this work. We extend our gratitude to Kai Lance Yoshioka for
proofreading the text. Wataru Takahashi and Ayu Tomita are excellent research assistants. The usual disclaimer
applies.
 Corresponding author. Graduate School of Economics, Kobe University. E-mail: miyazaki@econ.kobe-u.ac.jp
 Graduate School of Economics, Hitotsubashi University.

1Foreign visitors to Tokyo, Japan, are surprised to see farmers tending crops ofbroccoli and radishes amid high-rise office and apartment buildings … these arepossibly the most expensive fruits and vegetables in the world. … economists see
the farms as an extreme example of economic inefficiency. (Bruce 2000)

1. Introduction
Public finance economists have reiterated that property tax on land is neutral with respect toresource allocation. However, as a matter of practice, property tax is distortive because the tax rate
differs depending on land use. Indeed, as explained later, the taxable value of farmland turns out tobe lower than that of housing lots in the US and other countries.1 Particularly, such preferential
treatments are also given to farmland within cities and inner suburbs (hereafter defined as urban
areas).2 If this is the case, landlords may be reluctant to convert their farmland for other uses.
Consequently, alternative uses that are valued more highly (e.g., housing lots or office buildings)
may be lost as suggested by Bruce (2000). That said, it is likely that rescinding preferential
treatments will urge owners to change their farmland into residential lots. However, to ourknowledge, the effects of preferential property tax law reforms on land use in urban areas remains
underexplored.3
The purpose of this study is to examine the effects of two reforms on the preferential property tax
treatment in the urban area in Japan. To investigate the effect of the tax reforms, we construct atheoretical model and run difference-in-differences (DID) estimation. Japan’s property tax system
has interesting practical characteristics to address the effects of property tax reforms on land use inurban areas. On one hand, the government gave preferential treatment to farmland owners, even inurban areas, which led to the circumstances discussed by Bruce (2000). Indeed, local governments inthe three metropolitan areas (Tokyo, Chubu, and Kansai) are eager to preserve farmland.4 On theother hand, the Japanese government undertook fundamental reforms of preferential property tax
measures so that farmland owners in urban areas are induced to transform their farmland into
residential lots.
Here, let us provide details on the preferential treatment of farmland and the history of the reforms
in Japan. Farmland in Japan is classified as either ordinary farmland or farmland in urban promotion
Bird and Slack (2004) raise four policies as preferential treatments with regard to farmland: (1) lower assessments,(2) exemptions for part or all of the farm property, (3) lower tax rates on farms, and (4) farm tax rebates. Among thefour policies, this paper focuses on the first one.
2 For instance, some local governments in the US give preferential treatment on urban farmland; for example, thestate of California allows municipalities to lower the assessed value of property tax base even in urban area. Pleasesee also the link: http://articles.latimes.com/2013/oct/02/local/la-me-urban-agriculture-law-20131003.
3 Although Bruce (2000) mentioned how ineffective the protection of farmland within cities is, he did not proceed
this argument with any theoretical or empirical investigations.
4 For example, a great portion of farmland is preserved even in the center and inner suburbs of Tokyo. What is more,
the City of Yokohama, one of the largest and most famous urban hubs of Japan, also boasts a large agriculturalindustry. For more details, please visit https://www.japanfs.org/en/news/archives/news_id035384.html.
12

areas (hereafter UPA farmland). Like many other countries, the assessment of both types of farmland
is lower in Japan. Meanwhile, UPA farmland in the designated cities within the three metropolitan
areas (hereafter referred to as the designated cities)5 is taxed as housing lots. As shown in Table 1,
however, the government gave preferential treatment to UPA farmland owners in the designated cites
from Fiscal Year (FY) 1982. This is the long-term agricultural operation system, which let many
landlords keep their farmland as it was for ten years. In a practical manner, many farmland owners in
the designated cities took advantage of this system and escaped a higher tax burden by “disguising”
their property as farmland, which was pointed by Ishi (1991). To solve this problem, the Japanese
government undertook two fundamental reforms of the preferential property tax measure in the
1990s. One is that the long-term agricultural operation system was revoked at the end of FY 1991
(March 1992).6 After the rescindment of this system, whereas the UPA farmland in the designatedcities are taxed as housing lots, this is not applicable to the rest of the cities. Another reform is theamendment of the Production Green Land (PGL) Law in September 1991 (effective after January1992). Under the revised PGL Law, farmland owners in the designated cities receive preferential
treatment as long as they maintain the land as PGLs (a part of farmland) for 30 years.7
Table 2 shows the preferential treatment of UPA farmlands in the designated cities before and after
the reforms in FY 1991. As can be seen from Table 2, following the reforms, farmland owners had
the option to keep their farmland as UPA farmland. However, the owners face the same tax burden as
housing lots. Usually, if landlords build apartments or commercial buildings and lend the buildings
to others, they can reap more benefits. In this regard, farmland owners are expected to change the
UPA farmland into housing lots after the reforms.
Our analysis is based on the theoretical model that contains three periods over which land prices
stochastically evolve. With this model we establish two hypotheses: (1) The property tax reforms
decrease the amount of farmland in urban areas (i.e., the UPA farmland). However, (2) the effect on
the supply of housing lots is ambiguous.
To estimate the model using DID, following the previous arguments, we set the designated cities
that were affected by the property tax reforms as the treatment group whereas all other cities thatremained unaffected are in the control group. We use municipality level data for our empiricalinvestigation. Another approach is to use micro data on individual landlords. However, in Japan,
there are no household level data available that can be used to examine the behavior of landlords
This wording follows Ishi (1991). The designated cities in the three metropolitan areas include: (1) ones designatedby the government ordinance, whose population is over 500,000 (e.g., Osaka, Nagoya, and Yokohama); (2) thoseclassified as existing urbanized areas by the National Capital Region Development Act; and (3) those earmarked for
suburban development by the same act.
6 Following the UK, the Japanese fiscal year is from April to the following March.
7 For more information on the PGL, please visit: https://unu.edu/publications/articles/japan-s-urban-agriculture-whatdoes-the-future-hold.html. In the meantime, landlords can choose to preserve their land as PGL even after thereforms. However, in a practical manner, the reforms had an immediate effect because nearly all landowners whowanted to preserve their farmland designated them as PGLs at the timing of the reforms Therefore, we can assume theresponses of the landlords with respect to two reforms as one-short events and apply DID estimation.
5

3

before and after the reforms.8
Our main findings from the empirical results substantiate these hypotheses. First, the share of the
UPA farmland declined in the designated cities after the reforms of FY 1991. This is supported by DID
estimation. These results remain the same even if we add other independent variables, confirming therobustness of our results. Second, when housing lots ratio is used as the dependent variable, we do nothave statistically significant results for our treatment. Finally, on the other hand, our results imply thatsome landlords chose to preserve the land as the PGL. One important implication of these findings isthat the abolishment of the long-term agricultural operation system was not as effective as expected
because it shrunk UPA farmlands, which should in principle be converted into residential lots.
Our results contribute to two literatures. First, this study is related to the literature on the effects ofpreferential property tax treatment. A number of studies have addressed this issue: Brueckner (2001),
Brueckner and Kim (2003), Lynch (2003), Song and Zenou (2006, 2009), Anderson et al. (2015),
Wassmer (2016), and Yagi and Garrod (2018). These studies focus on how preferential property tax
treatment of farmland is useful in solving deficiencies of farmland resources and the encroachmentof farmland to the fringe due to urban sprawl. To our best knowledge, this is the first empirical andtheoretical research that addresses the preferential treatment of farmland in urban areas.
Furthermore, our research contributes to the literature on the effects of property tax reforms that use
natural or quasi-experimental approaches such as the reforms’ effects on fiscal competition(Lyytikäinen 2012, Skidmore et al. 2012), the real estate market (Dachis et al. 2012), housing
investments (Löffler & Siegloch 2015, Lutz 2015, Gemmell et al. 2017), and tax collection (Stine
2003, Ross & Yan 2013). However, to our knowledge, nobody has explored the reforms with respect
to the preferential treatment of land use. We differentiate ourselves by utilizing a natural experiment
provided by the two of FY 1991’s reforms in Japan.
The rest of this paper is organized as follows. Section 2 explains the institutional background ofJapan’ s property tax system and preferential treatment on farmland. Here we explain this byintroducing the case of the US and other countries first. Section 3 presents our theoreticalframework. Section 4 explains the data and discusses the assumptions to validate our DID
estimation. Section 5 reports the empirical framework and results. Section 6 concludes.

The Survey of Housing and Land offers information about land use based on questionnaires given to individual
households. However, this survey is conducted every five years, which makes it difficult for us to examine the effects
before and after the reforms in terms of exact timing. Although Japan’s Geospatial Information Authority gives us
detailed data on land use, we cannot identify the difference between the UPA farmland and other types; this is crucial
to our analysis.
84

2. Institutional background2.1. Experience with preferential treatment on farmland in the United States and othercountries
Property taxes have served as major revenue sources to subnational governments around the globe.
For example, property tax revenue is the primary source of tax receipt at the local level in the US.
Indeed, on average, it accounts for 40% of total state and local tax revenues; some state and local
governments count more heavily on property tax revenues than others.9 What is more, although theproperty tax in Norway is a voluntary tax for the local governments, nearly 50% of them gained
revenue from property taxation. In many countries, the property tax is applied to land. This isjustifiable in terms of economic efficiency; since land is in fixed supply, a tax on land falls on
landlords. Therefore, tax burden cannot be shifted onto others.
However, at the same time, many countries give various kinds of preferential treatments withregard to farmland in tax collection as summarized in Bird and Slack (2004). In fact, all 50 states in
the U.S. adopt some form of use-value assessment for farmland. For example, as shown in Wassmer(2009), the California Land Conservation Act of 1965 (the Williamson Act) allows landowners toreceive property tax assessments which are much lower than normal for a ten-year renewable term ifthey agree to keep their land in agricultural production or open space.
There are some rationales for conserving farmland through preferential treatment. For example,
Lynch (2003) raises four points: local and national food security, employment in the agriculturalindustry, the efficient development of urban and rural land, and the protection of rural andenvironmental amenities. Furthermore, as stated in Brueckner (2011), in the circumstance that urban
sprawl generates economic inefficiencies such as traffic congestion and air pollution, preferential
treatment on farmland reins in the excessive urban expansion to the suburbs, which reduces
inefficiency.

2.2. Japan’s property tax system and preferential treatment on farmland
Table 3 outlines Japan’s property tax system. Municipalities have the authority to impose property
taxes, except for the 23 special wards in Tokyo, where the metropolitan government is engaged inproperty tax administration. Property taxes cover land, houses, buildings, and depreciable businessassets (tangible assets except for land and buildings). The statutory tax rate is set as 1.4%; there islittle room for municipalities to change it. The upper limit is 2.1%, and the reality is that not many
local governments set the tax rate above 1.4%. When it comes to the share of the tax revenue ofmunicipalities, as shown in Figure 1, property tax comprises 42% in FY2016, suggesting thatmunicipalities heavily rely on property taxes.
Property tax is levied annually based on the assessment value of the aforementioned three taxable
9

For more details, see the website: http://eyeonhousing.org/2017/10/property-taxes-by-state-2016/.

5assets. Each municipality assesses the value of taxable assets based on a unified formula set by the
Ministry of Internal Affairs and Communications (hereafter referred to as MIAC). The assessedvalue of land is determined by considering the return on each item. Figure 2 depicts the timing ofproperty tax assessment and levies. As shown in the figure, tax liability is determined by ownershipof the assets, based on the value as of January. This record becomes the basis for tax collection overthe next fiscal year (from April to the following March).
Farmland in Japan is taxed much more lightly than housing lots as is done in other countries, but
the UPA farmland is an exception; it is treated as housing lots when local governments makeevaluations in the designated cities. The current City Planning Law (CPL), enacted in 1968, regards
the UPAs as urban zones where existing farmland should, in principle, be converted to housing use
from the viewpoint of urban planning in the designated cities.10 In this regard, the UPA farmland in
the designated cities can be defined as land that should be changed into housing lots.
Meanwhile, in the designated cities, not all UPA farmland has been transformed into residential use,which may give rise to the inefficiency of land use. The long-term agricultural operation system wasenacted from FY 1982 to FY 1991, whereby the tax burden was mitigated if farmers operated large
tracts of land over a period of ten years. As indicated by Ishi (1991), such lenient treatment offarmland in major cities reflected farmers’ special interests. Whereas the CPL aims to promoteurbanization, the long-term agricultural operation system contradicts this objective because thesystem prevented landlords from converting the land for other uses.

2.3. The details with regard to the reforms in FY 1991
To solve the problems mentioned in Section 2.2, as addressed by Terai (2001) and Kabeya and
Itaba (2009), in FY 1991, two reforms were simultaneously executed in the designated cities in order
to not only decrease the proportion of “disguised” farmland, but also to spur the development of
housing lots there. The first reform repealed the long-term agricultural operation system at the end of
FY 1991 (March 1992). At the same time, the PGL Law was rectified in September 1991 andeffective after January 1992. Under the amended PGL Law, UPA landlords whose farmland area is
500 m2 or greater in the designated cities faced two options: (1) Convert farmland into housing lots;or (2) Preserve it as PGL. Provided that landlords maintain their land as PGL for 30 years, their tax
burden is lowered because PGL is preferentially treated based on the same criteria as ordinary
farmland.
In the meantime, an inheritance tax is also levied on land. The string of reforms in FY 1991
included one that changed the inheritance tax, whereby the tax burden is abated if landlords preserve
land as PGL for 30 years. Here, the motivation behind holding farmland can be divided into (1)bequest and (2) option. Needless to say, the inheritance tax is related to the motivation as a bequest,
10

For more details, please see Ishi (1991) and Ito (1994).

6whereas property tax affects whether landlords sell it in the future. The effects of the inheritance tax
do not seem to be substantial, however, for three reasons. First, whereas the inheritance tax applies
to landlords with heirs, the property tax is levied regardless of inheritors as long as landlords possess
assets. Second, when it comes to the Japanese inheritance tax system, the basic deduction is set at 30
million yen (or approximately 300,000 USD) plus 6 million yen (60,000 USD) multiplied by the
number of statutory heirs. Indeed, the share of inheritance cases subject to the inheritance tax (=theannual number of decedents subject to the inheritance tax/annual number of deaths) has been lessthan 10% over the past three decades.11 Finally, provided that life expectancy is uncertain, people do
not necessarily factor in the long term. In this regard, the assumption that landlords keep the land as
PGL for 30 years as a bequest is not plausible.12

3. Theoretical and empirical framework
3.1.

Theoretical foundation

We begin with developing a theoretical illustration of how preferential tax treatment of PGL
influences land use. Land may be utilized for either residential or agricultural purposes. The model
contains three periods over which land prices stochastically evolve13 and addresses different optionsof land holding, one of which is PGL. For example, consider farmland owners in the designated cites
who decide when to sell their property. We assume that their decision is discrete for simplicity’s sake,but the model can easily be extended to continuous choice, whereby landowners choose the size ofland to sell. We also assume that they form rational expectation for future land prices and tax policies.
Before the property tax reforms, there is policy uncertainty during the second period regarding
property taxes on farmland. Given that PGL is in place for 30 years, one period may refer to 10 years.
Thus, it is plausible that landowners are not sure about future taxes. Hence, they may opt to sell landin the first period if they expect a higher property tax to be applied to their holding land afterward.
The reform does not remove the uncertainty, but instead clarifies the tax treatment of UPA farmland.
In the present context, PGL symbolizes government commitment to maintain preferential tax rates on
farmland, and requires landlords to not sell their land during the first two periods. This corresponds tothe institutional arrangement of the PGL, with the mandate of 30 years of cultivation, as mentioned
earlier. In UPAs, landowners have to pay higher taxes according to the land value of residential use.
By doing so, however, they can exert their selling option before the last period. Thus, there is a tradeoff
between favorable tax treatment and the option value of selling land.

For these points, please visit: https://www.mof.go.jp/english/tax_policy/tax_system/asset/index.html#a01
What is more, Horioka (2002) indicates that the selfish lifecycle model is rather applicable to Japan, which
reinforces the argument that landlords do not maintain farmland as PGL for the purpose of inheritance.
13 Similarly, Anderson (1986) develops a dynamic model for the optimal timing of development (land improvement)with continuous time.
11
12

7

Note that we focus on the representative landowner’s selling decision, taken as the given pricedynamics, thus abstracting the general equilibrium effect of property taxes on land prices. 14 Pt
denotes the market price of land corresponding to residential use at period t (=1, 2, 3). Pt may beinterpreted as the net price, subtracting the cost associated with leveling the land. P1 is known,whereas prices in subsequent periods involve uncertainty. Let E[ Pt ] be the expected land price. To
clarify our theoretical hypothesis, we assume that in the last period, landlords always opt to sell theirland.
(Assumption) P3  R for all P3
where R represents the return on farmland use, including non-market gains (such as recreation). Thisimplies that landlords seek the timing to sell their land, rather than intending to cultivate it. Figure 3
provides a timeline of their decisions. We consider that the reform is undertaken during the first period
and becomes effective afterward. Accordingly, no tax is charged at t=1. As noted above, tax policy atperiod t=2 is uncertain before the reform. Let x 2 represent the government policy stance taking unity
if agricultural land becomes subject to tax and zero otherwise. Then an effective tax is applied tofarmland at period t=2, which can be written as x2 where x 2 is stochastic in the pre-reform era.
After the reform, x2 = 1 for UPAs and x2 = 0 for PGL.
Designate j=H, A and G to housing, agriculture, and PGL, respectively. This corresponds to the three
options farmland owners have: (1) Sell and convert the land to housing lots at period 1; (2) hold theirproperty as farmland in UPA; or (3) maintain their land as PGL by committing not to sell the land at
period t=2. There may be another option of lending land for housing use to gain rent revenue. We
include this in j=H, interpreting Pt as the present value of rent. In the case of j=H, the payoff to thelandlord equals VH = P1 which is not affected by the property tax reform. If the owner opts for the
PGL after the reform, the owner commits to cultivating the land during the first two periods. At t=3,
the preferential tax treatment expires, and the owner chooses to sell land at price P3 . Then, his payoff
is given by(1) VG = (1 +  ) R +  E1 P3 
1

2

where  <1 is the discount factor and the superscript 1 refers to the post-reform period. The second
term is the expected price at t=3 from the first period perspective. For simplicity’s sake, we assume
zero property tax on the land for agricultural use. Alternatively, the owner can delay selling, although
this may trigger a high property tax afterward. Before the tax reform, given that x 2 is stochastic, i.e.,either 0 or 1, the payoff from j=A becomes:(2)
The model is close to the optimal timing of a job search model. In this regard, the present model deviates fromprevious literature such as Arnott (2005), Brueckner (2001), and Brueckner and Kim (2003). Wassmer (2016) reviews
theoretical findings as to how property taxes and urban sprawl interact.
148

where the superscript 0 denotes pre-reform and  is the tax rate. The tax reform determines the tax
rate at t=2 with certainty. The above pay-off after the reform is written as:(3)With j=A, the owner can keep the option of selling land at t=2. Such an option is not allowed underj=G, whereas the last term represents the property tax burden, given that the tax base is assessed basedon residential use after the reform. Thus, there is a tradeoff between the option to sell and the tax
burden at t=2. Such a tradeoff does not occur before the reform. Indeed, we have V A0  VG0 whereby
the right side symbolizes the pre-reform pay-off from the commitment to farming at t=2, as requiredby the PGL, and is defined by





 

(4) VG = (1 +  ) R −  E1 x2 P2 +  E1 P3
02

The difference from Eq. (1) is that the tax may be charged at t=2 before the reform. To sum up, thefollowing lemma establishes a relationship among the pay-offs.
[Lemma 1](i)

V A0  V A1(ii)

V A0  VG0(iii)

VG0  VG1

The first statement of the lemma implies that the option of j=A turns out to be less attractive after thereform, as a high property tax is charged on farmland in the UPA. The result is straightforward as thereform sets x 2 =1. Before the reform, j=A dominates commitment to holding farmland, as addressedin (ii); j=A adds the option value of selling land during the earlier period, whereas the government
does not yet commit to preferential tax treatment for j=G. On the other hand, during the post-reform
stage, the PGL (j=G) becomes more beneficial than holding farmland (j=A) due to the preferential tax
treatment as stated in (iii).
We now turn to decision making by landowner over different options among j=H, A and G. In
characterizing it, we adopt the setting of the random utility model that has been widely used inempirical literature on decision makings over options. To be specific, let landowner’s utility from each
option be given by U j = V j +  j where  j is a random variable. It may represent transaction costs
associated with land sale and non-pecuniary costs such as attachment to own land. Difference in risk
aversion over land price change and thus risk premium to be paid may be incorporated in the random
component as well. Then for instance landowner would like to hold land in the form of PGL if andonly if9(5) U G = VG +  G  U j = V j +  j  VG − V j   j −  G for j=A and H.
The joint distribution of the three random variables,  j (j=A, G, H) yields the probability that option
j is chosen against the other alternatives:(6)

Q j = F j (V A , VG , VH ) = Pr( j −  i  V j − Vi , i  j )The probability is increasing in V j and declining with Vi ( i  j ). In empirical studies on discrete
choice over different alternatives, Eq. (6) is often specified as the multiple logit function.15(7) Q A = FA (V A , VG , VH ) − FA (V A , VG , VH )
1

1

0

0

(8) QH = FH (V A , VG , VH ) − FH (V A , VG , VH )
1

1

0

0

Eq. (7) becomes negative given that V A0  V A1 and

VG0  VG1 . This may be obvious since the tax

reform raises the tax burden on holding farmland. Thus, option j=A becomes less likely to be exercised.
On the other hand, Eq. (8) cannot be signed. Given V A0  V A1 , the choice of selling land at t=1 becomes
more advantageous relative to holding it as farmland, whereas the gain from the commitment to PLG
is enhanced due to preferential tax treatment leading to VG0  VG1 . Therefore, we can establish thefollowing Proposition, which should be empirically confirmed:<Proposition 1:>(1) Property tax reform decreases farmland in UPA at the time that the reform is conducted.
(2)

The property tax reform effect on the supply of housing lots at the time of the reform is

ambiguous.

Empirical framework

3.2.

This section establishes the empirical methodology and results. In doing so, we give basic
specifications of the DID regression, as follows.
(9)
where Lit is the ratio of UPA farmland, Ti is the dummy variable that takes 1 if it is a designatedcity within the three metropolitan areas and the others are 0, 𝑅𝐸𝐹𝑂𝑅𝑀𝑡 is the dummy variable that15

The probability function is specified as Q =jexp[V j ]exp[V A ] + exp[VG ] + exp[VH ] .

10takes 1 the period when the reforms are implemented and 0 for the others,,

𝐶𝑖𝑡 is the vector of other control variables, and  it is the disturbance term.
When it comes to the UPA farmland ratio, if the coefficients ofare estimated to be negativeand statistically significant, we conclude that the first hypothesis is substantiated. We also estimate Eq.
(9) using housing lot ratio and farmland ratio as the dependent variable. We do so to check whether
reduced UPA farmland was converted into housing lots. On top of that, the farmland ratio can also be
used as the dependent variable to capture the change in PGL because the data on farmland also
encompass PGL after the reforms.
For other control variables, as stated in Section 4.1., we add the effective tax rate of UPA farmland,
local government tax revenue per total local government revenue, agricultural income, population
density, and shipments.16

4. Data and discussion on the validity of DID estimation
4.1.

Sample period, data, and city characteristics

To be consistent with our theoretical model, we focus on the duration before and after the reforms.
Therefore, the sample period is from FY 1991 to FY 1992.17
Table 4 gives the description and source of the data used in estimation. All data on square (area)
measure, property value, and tax base come from the Brief Report on the Value of Properties
provided by MIAC. We use these data in order to calculate the ratios of UPA farmland, ordinary
farmland, and housing lots. These are obtained by dividing each item by total land (the sum of UPA
farmland, ordinary farmland, and housing lots). Note that after the reforms, a proportion of the UPA
farmland may have become preserved as the PGL and has been added into ordinal farmland in theofficial statistics. Recall that the collection of property taxes between April and the following March(the fiscal year in Japan) is based on information from January of the previous fiscal year. In thisregard, as shown in Table 4, our data on land use in FY 1991 (April 1991–March 1992) come fromthe Brief Report on the Value of Properties in FY 1992, reflecting the land use in January 1992 when

Regarding possible additional variables, the age structure and share of primary and secondary industries can beconsidered. Although the National Census can provide such data, the census is a quinquennial survey in Japan.
Therefore, it would not be adequate to use data collected every five years in a framework that compares outcomes
before and after the treatment.
17 It would also be possible to extend the sample periods to include before FY 1990 and after FY 1993. However,even if some methods have been proposed in several previous studies (e.g., Bertrand et al. (2004)), we cannot
confidently rule out the possibility of serial correlation in the DID estimation by including the periods outside thereforms. Furthermore, the influence of asset price bubbles over the periods from the late 1980s to FY 1990 makes thisproblem more serious.
16

11

the long-term agricultural operation system was still in effect. Likewise, the data in FY 1992 arefrom the Brief Report in FY 1993, which is based on the evaluation in January 1993. Meanwhile,
since the data for other independent variables reflect the change from April to the following March,
we can use these data for each fiscal year.
Data on local government tax revenue and total local government revenue come from the Statisticsof the Final Accounts of Municipal Governments, and population data are from the Basic Resident
Register. MIAC provides these data. Regarding the area of municipality, we use the data of the Area
Statistics of Prefectures and Municipalities by the Geospatial Information Authority of Japan. The
data on agricultural income come from the Production Agricultural Income Statistics, provided by
the Ministry of Agriculture, Forestry, and Fisheries. The data on shipments come from the Industry
Statistics provided by the Ministry of Economy, Trade, and Industry.
When it comes to additional control variables, the coefficient on the effective tax rate, with respect
to the UPA farmland, is expected to be negative when we estimate the model with UPA farmland
ratio as the dependent variable.18 We also use this as an independent variable when the housing lot
ratio is used as a dependent variable, where the coefficient would be estimated to be positive. By
doing this, we hope to capture the path through which the reduction in UPA farmland leads to anincrease in housing lots.
Local tax revenue share in total local government revenue and population density are added asindicators of urbanization. Hence, the coefficients are expected to be positive when we use UPA
farmland ratio or housing lots ratio as the dependent variable; on the other hand, we expect thesecoefficients to be negative when using farmland ratio as the outcome. Shipment addresses the size of
manufacturing industries, and agricultural income is a proxy for rural areas. The coefficient ofshipment is estimated to be positive when we use UPA farmland or housing lot ratio as the left-handside variable, and negative if farmland ratio is employed as the dependent variable. The coefficienton agricultural income is expected to be negative when UPA farmland or housing lots ratio is used as
the outcome, and positive in the case that farmland ratio is used as the left-hand side variable. We
take the logarithm of agricultural income, population density, and shipment in the estimation.
We focus on 501 cities throughout the period from FY 1985 to FY 1994.19 As stated in Section 4.2,
we conduct a placebo test between FY 1985 and FY 1986. Therefore, we choose FY 1985 as the18

To calculate the effective tax rate, we use two procedures. First, the tax revenue is determined by multiplying tax

base by the statutory tax rate (=0.014) as follows.

After that, we calculate the effective tax rate by dividing the tax revenue by the property value.
Although the Brief Report on the Value of Properties includes data on Tokyo’s 23 wards, such data is aggregated;
information is not provided for individual wards. Therefore, our sample exclude the 23 wards.
19

12

initial period. We chose these cities as follows. First, we omit cities without ordinary or UPA
farmland. Second, during our sample period, the central government did not designate certain cities
as ordinance cities before FY 1991. When we examine the placebo effect, the city’s characteristics
should be the same.20 Therefore, we do not include such cities. Finally, there was an amalgamationof municipalities even in the 1980s and 1990s, which makes it difficult for us to obtain coherent data
throughout that period for such cities. Therefore, we omit cities that merged or disappeared from1985 to 1994.
The process above yields a sample of 501 cities. Here, the treatment group comprises 183
designated cities, and the control group has 318. There are three cases for our treatment groups. We
set this as the basic case and call it “Case 1.”
As our second case, we limit our sample to cities with populations over 50,000 on average. This is
why though there are some exceptions, under Japan’s local public finance system, the population
should be over 50,000 for municipalities to be classified as a city. Whereas most designated cities(treatment group, 183) meet this requirement, this is not the case for the rest. In order to make thetwo groups comparable, we restrict the sample to 206 cities with population over 50,000 on averagethroughout our sample period. This is “Case 2,” and total number of cities is 389.
Furthermore, for the third case, we chose 104 cities with populations over 100,000 as our control
group. This is defined as “Case 3,” and the total number of cities is 287.

4.2.

The validity of DID estimation

Table 5 reports the summary statistics of all variables used in estimation. Here, the UPA farmland
ratio, our main outcome variable, plunged between FY 1991 and FY 1992 for the treatment group,
while it did not change between the two fiscal years for the control group. On the other hand, while
the difference between the two periods with regard to housing lots ratio is not large, farmland ratio
increased after the reforms for the treatment group. These simple comparison before and after thereforms for our treatment and control groups suggest the following. First, the decrease in the UPA
farmland at the timing of the reforms is consistent with our first hypothesis. Second, however, as
indicated by our second hypothesis, landlords might not convert all UPA farmlands into housing lots,
instead keeping them as PGLs.
Figures 4a to 6b show the average of the ratio for each item with regard to land use (each item per
total land, respectively) between the designated cities (the treatment group or treated cities) and theremaining cities (the control group or untreated cities) from FY 1989 to FY 1994. According to
Figures 4a, 5a, and 6a, in FY 1992, when the long-term agricultural operation was repealed and the
For example, Chiba became a city designated by government ordinance in FY 1992. Although Chiba may beclassified as an existing urbanized area or a suburban development even before that time, we omit this city following
the argument above. Likewise, we do not include Sendai as part of the control group, because Sendai was notdesignated as an ordinance city until FY 1989.
20

13

amended PGL Law came into force, the share of UPA farmland fell dramatically in the designatedcities from the previous year; on the other hand, the ratio did not change after the reforms in theremaining cities. Therefore, the two concurrently implemented reforms are useful in reducing UPA
farmland in the designated cities.
On the other hand, the right charts of Figures 4b, 5b, and 6b suggest that landlords did not convert
all PGL farmland into housing lots after the reforms, although the housing lot ratio has been increasing
throughout the periods. If the owners had converted most PGL farmland into housing lots following
the amendment of the PGL Law, the proportion would have increased dramatically in FY 1992 incomparison to FY 1991. However, these figures suggest this was not the case.
In the meantime, as noted earlier, PGL is included in farmland data of the Brief Report on the Valueof Properties after the reforms. Although it is impossible for us to extract PGL from MIAC data,
Figures 4b, 5b, and 6b also suggest that the farmland ratio temporarily rose between FY 1991 and FY
1992 for the designated cities. This implies that some landlords might decide to keep farmland as PGL
after the reforms.
These figures imply that our hypotheses may be true. To substantiate them, we should perform an
econometric investigation using Equation (9). We discuss the validity of this method by focusing on
the UPA farmland ratio, the main outcome that we would like to address to examine the effects of thereforms.
First, we discuss the common shocks assumption. The Japanese government implemented several
measures for land-related taxes in the early to mid-1990s. For example, the land-value tax wasenacted in FY 1992. Moreover, the government set the assessed value of land at 70–80% of themarket value in FY 1994, which some landlords might respond to in advance. However, thesepackages were carried out not for a certain group, but for all municipalities. Therefore, the common
shocks assumption is not violated within our framework.
Second, we check the common trend assumption using Figures 4a, 5a, and 6a. The identifying
assumption of our DID specification is that both the treated and untreated cities would have tofollow the same time trend in the absence of the reforms in FY 1991. If this common trend
assumption holds, our empirical strategy allows us to control for all unobserved differences between
the two groups. The average of the share of UPA farmland moved almost in parallel in the designatedand remaining cities between FY 1989 and FY 1990, with the proportion of UPA farmland declining
slightly in the two groups. Therefore, these graphs provide visual evidence of treatment and control
cities, with a common underlying trend for pretreatment periods.21
Furthermore, we present the results of the placebo test for our simple DID estimation (without any
control variables) for the case where the UPA farmland ratio is used as the dependent variable. This is

Meanwhile, we also implement Autor (2003)’s type Granger Causality test to check whether or not landlords
change the behavior before the reforms. For both cases, null hypothesis is not rejected.
21

14

done in order to further verify the common trend assumption. Notice that, since the duration of theasset price bubble was from December 1986 to February 1991, the period between FY 1989 and FY1990 contains the peak and collapse of the asset bubble in Japan. Even if the common shocks
assumption is not violated because the business cycle fluctuation in these periods affects both groups,
it would be favorable not to include the asset price bubble period in the estimation. Therefore, we
conduct our placebo test for FY 1985 and FY 1986. The placebo treatment variable is equal to 1 forFY 1986. No results in Table 6 are statistically significant, and there are no differences between thetreated and untreated cities before the reforms.

5. Empirical results
Table 7 reports the estimation results of simple DID estimation without control variables. For thecase where the UPA farmland ratio is used as the dependent variable, the coefficients of(DID

estimate within the table) are estimated to be negative and significant for all cases. However, once we
use the housing lot ratio as the dependent variable, the coefficients are not statistically significant
under any cases. The rest of the columns of Table 7 show that the coefficients ofare estimatedto be positive and significant in Cases 1 and 2, implying that after the treatment the PGL in thedesignated cities increased. However, we cannot confirm statistically significant results in Case 3.
We also estimate Eq. (9). Tables 8 to 10 present the results. Table 8 confirms that after the reforms,
the UPA farmland ratio decreased as was suggested by our simple DID estimation for all cases. Also,
the estimated coefficients are close to the simple DID estimation. Therefore, we also establish that theresults regarding the UPA farmland ratio are robust. Meanwhile, Table 9 reports that the coefficientsofare not estimated to be statistically significant when we use housing lot ratio as a dependent

variable. However, as you can see from Table 10, the coefficients are estimated to be positive andsignificant in Cases 1 and 2 with farmland ratio as the outcome.
Tables 8 to 10 confirm our first hypothesis. The tables also imply that after the reforms somelandlords preserved UPA farmland as PGLs rather than convert them into housing lots, which isconsistent with the second hypothesis.
It is likely that most landlords, who often engaged in other jobs, would like to escape a higher tax
burden. Indeed, most Japanese farmers work part-time and have second jobs.22 They earn enoughincome from other sources, which may induce them to preserve farmland as PGL so that they can

The Economist (2013) shows that full-time farmers make up 28% of all farmers in Japan. For more details, please
visit https://www.economist.com/asia/2013/04/13/field-work.
22

15

escape a higher tax payment. Yagi and Garrod (2018) demonstrated that farmers in areas with a higher
population density who depend on revenue from real estate income tend to continue farming. What ismore, Onishi et al. (1992) surveyed farmers in Osaka at the timing of the reforms; approximately 50%of the respondents said they chose to conserve their land as PGLs in order to lower their tax burden,
supporting our interpretation above.
Among the control variables, the coefficients on the effective tax rate are estimated to be negativeand significant in the case where the UPA farmland ratio is used as the dependent variable. On theother hand, these coefficients are estimated to be positive and significant when we use the housing lot
ratio as the dependent variable. This suggests that while a hefty effective tax rate reduces UPA
farmland, the reduced land would be converted into housing lots. For all cases, the coefficients of thelogarithm of population density are estimated to be positive and significant in Tables 8 and 9, andnegative in Table 10 as we expected. The coefficients of shipment is estimated to be positive for allcases and statistically significant in Tables 9 and 10. However, the coefficient of the logarithm ofagricultural income is estimated to be negative and significant regardless of the dependent variables.
In Japan, cropping vegetables and fruits, which require little land, have shared a substantial part ofagricultural income. Therefore, there would be a negative relationship between the size of farmland
and agricultural income. This may be the reason why the coefficient is estimated to be negative when
we use farmland ratio as the dependent variable.

6. Conclusion
This paper examines how the property tax reforms affect land use through theoretical and empiricalinvestigation by focusing on land use tax reforms that took place in the 1990’s in Japan. On one hand,as stated in Brueckner (2011), preferential property tax treatment can solve economic inefficiencies
such as traffic congestion and air pollution caused by urban sprawl. On the other hands, preferential
property tax treatment on farmland in urban areas may cause another type of inefficiency indicated byBruce (2000). Both the theoretical and empirical findings illustrate that the reforms reduced the
proportion of UPA farmland in the designated cities within the three metropolitan areas. However, wecannot confirm whether all reduced UPA farmland was converted into housing lots. The results alsosuggest that the PGL Law should not have been amended because not all the farmland was converted
into housing lots, the problem of obstructed urbanization remains to be solved. Hence, obstructing theurbanization remains to be resolved.
Our findings imply that policy makers should be wary of unintended consequences when they
make changes to laws concerning preferential property tax treatments. The preferential treatment toprotect urban agriculture, which has been also employed in some other countries, may become16controversial; it may make housing shortage more severe in major cities.23 Japan’s experience may
not be unique. If there is a loophole such as the amended PGL law, it may work against the aim ofpromoting urbanization. Meanwhile, there are caveats to generalizing our results. For example, theresults apply only to countries where farmland owners earn larger income from another source. Ourinterpretation is based upon the fact that part-time farmers, whose fraction is larger in Japan than inother countries, have an incentive to keep farmland to avoid a heavier tax burden. Nevertheless, ourresearch demonstrates that if the exception becomes a rule, the reforms with regard to preferential
treatment will lead to unintended consequences, as in the case of many tax reforms.

References
Anderson, J.E (1986) “Property taxes and the timing of urban land development.” Regional Scienceand Urban Economics 16 (1986) 483-492.
Anderson, J.E., S.H. Giertz, S.N. Shimul. (2015) “Property Taxes for Agriculture: Use-Value
Assessment and Urbanization across the United States.” Mercatus Center Working Paper.
Arnott, R. (2005) “Neutral Property Taxation.” Journal of Public Economic Theory 7 (1): 27-50.
Autor, D. (2003) “Outsourcing at Will: The Contribution of Unjust Dismissal Doctrine to the Growthof Employment Outsourcing.” Journal of Labor Economics 21: 1-42.
Bertrand, M., E. Duflo., S. Mullainathan. (2004) “How Much Should We Trust Differences-inDifferences Estimates?” Quarterly Journal of Economics 119: 249-275.
Bird, R. M., E. Slack. Eds. (2004) International Handbook of Land and Property Taxation. Edward
Elgar Publishing.
Bruce, N. (2000) Public Finance and the American Economy. 2nd Edition. Addison Wesley.
Brueckner, J.K. (2001) “Urban Sprawl: Lessons from Urban Economics.” In: Gale, W.G., Pack, J.R.
(Eds.), Brookings-Wharton Papers on Urban Affairs. Brookings Institution, Washington, D.C., 6589.
Brueckner, J.K. (2011) Lectures on Urban Economics. The MIT Press.
Brueckner, J.K., H. Kim. (2003) “Urban Sprawl and the Property Tax.” International Tax and Public
Finance 10: 5–23.
Dachis, B., G. Duranton., M. T. Turner. (2012) “The Effects of Land Transfer Taxes on Real Estate
Markets: Evidence from a Natural Experiment in Toronto.” Journal of Economic Geography 12:327-354.

23

For example, as mentioned in Nagourney and Dougherty (2017), shortages of homes and apartments has led to the
exorbitant housing costs in major cities in California. For more details, please see the website:
https://www.nytimes.com/2017/07/17/us/california-housing-crisis.html.

17Gemmell, N. A. Grimes., M. Skidome. (2017) “Do Local Property Taxes Affect New
Building Development? Results from a Quasi-Natural Experiment in New Zealand.”The Journal of Real Estate Finance and Economics, forthcoming.
Horioka, C. Y. (2002). “Are the Japanese Selfish, Altruistic, or Dynastic?” The Japanese Economic
Review 53 (1): 26-54.
Ishi, H. (1991) “Land Tax Reform in Japan.” Hitotsubashi Journal of Economics 32: 1-20.
Ito, T. (1994) “Public Policy and Housing in Japan.” In: Noguchi, Y., J. Poterba (Eds.), Housing
Market in the United States and Japan, pp. 215-238, University of Chicago Press.
Kabeya, N., Y, Itaba. (2009) “Land Taxation and a Local Public Finance Income: Revolve the Tax
Break over Farmland.” Government Auditing Review 40: 79-96 (in Japanese).
Löffler. M., S. Siegloch. (2015) “Property Taxation, Local Labor Markets, and Rental Housing.”
https://www.econstor.eu/handle/10419/112967
Lutz, B. (2015) “Quasi-Experimental Evidence on the Connection between Property Taxes andResidential Capital Investment.” American Economic Journal: Economic Policy 7 (1): 300-330.
Lynch, L. (2003) “Do Agricultural Preservation Programs and Preferential Property Tax Programs
Affect Farmland Conversion?” Paper presented at the 2003 Annual Meeting of the American
Agricultural Economics Association.
Lyytikäinen, T. (2012) “Tax Competition among Local Governments: Evidence from a Property Tax
Reform in Finland.” Journal of Public Economics 96: 584-595.
Nagourney, A., C. Dougherty. (2017) “The Cost of a Hot Economy in California: A Severe Housing
Crisis.” The New York Times July 17, 2017.
Onishi, T., H. Kobayashi., T. Hashimoto. (1992) “Revised Production Green Land andFarming in Urban Areas.”
https://www.jstage.jst.go.jp/article/arfe1965/28/Supplement1/28_Supplement1_1/_pdf(in Japanese)
Ross J. M., W. Yan. (2013) “Fiscal Illusion From Property Reassessment？An Empirical Test of the
Residual View.” National Tax Journal 66 (1): 7-32.
Skidmore, M., R. Reese., S. H. Kang. (2012) “Regional Analysis of Property Taxation, Education
Finance Reform, and Property Value Growth.” Regional Science and Urban Economics, 42: 351363.
Song, Y., Y. Zenou. (2006) “Property Tax and Urban Sprawl: Theory and Implications for US Cities.”
Journal of Urban Economics 60: 519-534.
Song, Y., Y. Zenou. (2009) “How Do Differences in Property Taxes within Cities Affect Urban Sprawl?”
Journal of Regional Science 49 (5): 801-831.
Stine, W. F. (2003) “The Effect of Personal Property Tax Repeal on Pennsylvania’s Real
Estate Tax Growth and Stability.” National Tax Journal 56 (1): 45-60.
18

Terai, K. (2001) “The Effects of Non-Preferential Treatment on Urbanization Promotion Area’s
Farmland.” Urban Problem, 92 (11): 69-81 (in Japanese).
The Economist (2013) “Field Work.” April 13th, 2013.
Wassmer, R.W. (2009) “California’s Farmland Preservation Programs, Taxes, and Furthering theAppropriate Safeguarding of Agriculture at the Urban Fringe to Reduce Greenhouse Gas Warming.”
In: Denman, A. C., O. M. Penrod (Eds.), Land Use Policy, pp. 1-30, Nova Science Publishers.
Wassmer, R.W. (2016) “Further Empirical Evidence on Residential Property Taxation and the
Occurrence of Urban Sprawl.” Regional Science and Urban Economics, 61: 73-85.
Yagi, H., G. Garrod. (2018) “The Future of Agriculture in the Shrinking Suburbs: The Impact of Real
Estate Income and Housing Costs.” Land Use Policy 76: 821-822.

19

Figure 1. Share of tax revenue of municipalities in Japan (FY 2016)

Urban planning tax
6%

Other
8%

Local corporatetax
9%

Property tax
42%

Local income tax
35%

Source: The White Paper on Local Public Finance (issued by MIAC)

Figure 2. The timing of the assessment and levy of property taxes in Japan

Notes: The Japanese fiscal year runs from April to the following March. Under the Japanese property tax administration
system, tax liability is determined by ownership of assets, based on the value as of January. Municipalities collectproperty taxes over the next fiscal year in reference to this record.

20

Figure 3. The timeline of the decision

Notes: UPA farmland refers to the farmland in the urban promotion areas.

21

Figure 4a. Trends in UPA farmland ratio (Case 1, unit=%)

2

4

6

8

10

The ratio of UPA farmland

1989

1990

1991

1992

Other cities

1993

1994

Designated cities

Notes: UPA farmland stands for the farmland in the urban promotion areas. Each series plots the average of theshare of UPA farmland per total land (=UPA farmland + housing lots + ordinary farmland) from FY 1989 to FY
1994. The definition of “designated cities” in this paper is the designated cities within the three metropolitan areas(Tokyo, Chubu, and Kansai). The dotted vertical line indicates the year (FY 1991) that the two reforms wereconducted, which were presented in Tables 1 and 2.
.

22

Figure 4b. Trends in ordinary farmland and housing lots ratio (Case 1, unit=%)

40
30
20
10

20

25

30

35

50

The ratio of housing lots

40

The ratio of farmland

1989

1990

1991

Other cities

1992

1993

1994

1989

Designated Cities

1990

1991

Other cities

1992

1993

1994

Designated cities

Notes: “Farmland” within the figure stands for ordinary farmland. Each series plots the average of the share ofordinary farmland or housing lots per total land (=UPA farmland + housing lots + ordinary farmland) from FY 1989
to FY 1994. The definition of “designated cities” in this paper is the designated cities within the three metropolitan
areas (Tokyo, Chubu, and Kansai). A dotted vertical line within the graph indicates the year (FY 1991) that the two
reforms were conducted, which were presented in Tables 1 and 2.

23

Figure 5a. Trends in UPA farmland ratio (Case 2, unit=%)

4

6

8

10

The ratio of UPA farmland

1989

1990

1991

1992

Other cities

1993

1994

Designated cities

Notes: UPA farmland stands for the farmland in the urban promotion areas. Each series plots the average of the shareof UPA farmland per total land (=UPA farmland + housing lots + ordinary farmland) from FY 1989 to FY 1994. The
definition of “designated cities” in this paper is the designated cities within the three metropolitan areas (Tokyo, Chubu,
and Kansai). A dotted vertical line within the graph indicates the year (FY 1991) that the two reforms were conducted,
which were presented in Tables 1 and 2.

24

Figure 5b. Trends in ordinary farmland and housing lots ratio (Case2, unit=%)

The ratio of housing lots

20

20

25

30

30

40

35

50

The ratio of farmland

1989

1990

1991

Other cities

1992

1993

1994

1989

Designated cities

1990

1991

Other cities

1992

1993

1994

Designated cities

Notes: “Farmland” within the figure stands for ordinary farmland. Each series plots the average of the share of ordinary
farmland or housing lots per total land (=UPA farmland + housing lots + ordinary farmland) from FY 1989 to FY 1994.
The definition of “designated cities” in this paper is the designated cities within the three metropolitan areas (Tokyo,
Chubu, and Kansai). A dotted vertical line within the graph indicates the year (FY 1991) that the two reforms wereconducted, which were presented in Tables 1 and 2.

25

Figure 6a. Trends in UPA farmland ratio (Case 3, unit=%)

4

6

8

10

The ratio of UPA farmland

1989

1990

1991

1992

Other cities

1993

1994

Designated cities

Notes: UPA farmland stands for the farmland in the urban promotion areas. Each series plots the average of the shareof UPA farmland per total land (=UPA farmland + housing lots + ordinary farmland) from FY 1989 to FY 1994. The
definition of “designated cities” in this paper is the designated cities within the three metropolitan areas (Tokyo, Chubu,
and Kansai). A dotted vertical line within the graph indicates the fiscal year (FY 1991) that the two reforms wereconducted, which were presented in Tables 1 and 2.

26

Figure 6b. Trends in ordinary farmland and housing lots ratio (Case 3, unit=%)

The ratio of housing lots

20

24

26

30

28

40

30

32

50

The ratio of farmland

1989

1990

1991

Other cities

1992

1993

1994

1989

1990

1991

Other cities

Designated cities

1992

1993

1994

Designated cities

Notes: “Farmland” within the figure stands for ordinary farmland. Each series plots the average of the share of ordinary
farmland or housing lots per total land (=UPA farmland + housing lots + ordinary farmland) from FY 1989 to FY 1994.
The definition of “designated cities” in this paper is the designated cities within the three metropolitan areas (Tokyo,
Chubu, and Kansai). A dotted vertical line within the graph indicates the year (FY 1991) that the two reforms wereconducted, which were presented in Tables 1 and 2.

27

Table 1. History of the preferential treatment for the UPA farmland in the designated cites within thethree metropolitan areas.
Year

Month

1982

April

The enactment of the long-term
agricultural operation system

1991

September

The amendment of the Production
Green Land (PGL) Law

1992

January

The Production Green Land (PGL)
Law has comes into effect (until
March 2023)

March

The repeal of the long-term
agricultural operation system

Notes: UPA farmland refers to the farmland in the urban promotion areas.

28

Table 2. The classification of the UPA farmland in the designated cities within the three metropolitan
areas (Tokyo, Chubu, and Kansai) before and after the reforms in FY 1991
Type of farmland

Preferential treatment

UPA farmland

Yes

Before the reforms(FY 1982-FY1992)

After the reforms
Production Green(FY 1992 - FY 2022

Yes (for 30 years)
Land (PGL)(expected))
UPA farmland

No (taxed as(except PGL)

residential lots)

Notes: UPA farmland refers to the farmland in the urban promotion areas. The Japanese fiscal year runs from April tothe following March. UPA farmland is classified as either production green land (PGL) or non-PGL UPA farmland
following the reforms.

Table 3. An outline of Japan’s property tax system

Municipalities (cities, towns, andTax authority
villages) assess, levy, and collect taxes*

Taxable assets

Taxpayer

1.

Land

2.

Houses and buildings

3.

Depreciable business assets

Owners of each taxable asset

The evaluation of theValue (fair market value) as of January 1
tax baseTax rate

Statutory tax rate: 1.4 %*** For Tokyo’s special wards, the Tokyo metropolitan government is in charge of tax administration.
** The upper limit is 2.1%

29

Table 4. The description and source of the data
Description

SourceThe square measure of UPA

The Brief Report on the Value of

farmland, housing lots, and farmland

Properties(unit: ㎡)(FY 1992 and FY1993) *Tax base and property value of UPA

The Brief Report on the Value of

farmland (unit: million JPY)

Properties(FY 1992 and FY 1993) *Population

The Basic Resident Register(FY 1991 and FY 1992)

The area of municipality

The Area Statistics of Prefectures(unit: ㎡)

and Municipalities(FY 1991 and FY 1992)

Agricultural production income

The Production Agricultural(unit: million JPY)

Income Statistics(FY 1991 and FY 1992)

Shipment value of manufactured

The Industry Statistics

goods (unit: million JPY)

(FY 1991 and FY 1992)

Local government tax revenue and

The Statistics of the Final

total local government revenue

Accounts of Municipal(unit: million JPY)

Governments(FY 1991 and FY 1992)* The collection of property taxes between April and the following March (the fiscal year in Japan) is based on
information from January of the previous fiscal year, as indicated in Figure 2. In this regard, our data with regard toland use in FY 1991 (April 1991–March 1992) come from the Brief Report on the Value of Properties in FY 1992,
reflecting the land use in January 1992 (still within FY 1991) when the long-term agricultural operation system wasstill in effect. Likewise, the data in FY 1992 are from the Brief Report in FY 1993, which indicates the evaluation in
January 1993 (within FY 1992).

30

Table 5. Summary statistics
Group
Variable

Treatment
Description

Control

FY1991(1) Growth rate
(FY1992-1991, %)FY1992Nmean Std. Dev.

N

mean Std. Dev.

The ratio of
UPA farmland
per total land

183

0.0912 0.0612

183

0.05260.0282

The ratio of
Housing lots
housing lots per
ratio
total land183

0.4499 0.2118

183

0.4562

The ratio of
Farmlandfarmland per
ratio
total land183

0.2327 0.1854

183

Effective tax
rate of UPA
farmland183

0.0057 0.00112

Population per
Population
the area of
densitymunicipality

1834233.6

Agricultural
Agricultural
production
incomeincomeFY1991(2) Growth rate
(FY1992-1991, %)Dif (1)-(2),%mean Std. Dev.

N

mean Std. Dev.

-42.323

318 0.0276 0.0326

318

0.0268 0.0316-2.829-39.4940.2136

1.388

318 0.1704 0.1094

318

0.1730 0.1105

1.557-0.1680.26320.170613.117318 0.3659 0.1676

318

0.3638 0.1671-0.576

13.693183

0.00630.001111.300318

0.00580.0055318

0.0067 0.0057

15.340-4.0403013.31834261.4 3017.91

0.656

318

783.2 725.919

318

786.28 731.88

0.394

0.263

183

1684.9 1775.33

183

1540.9 1654.74-8.546318

3638.9 3259.74

318

3636.7 3108.7-0.061-8.485

Shipment valueof
Shipment
manufactured
goods

183

713710 1272310

183

683154 1216806-4.281

318

342281 447711

318

332138 432097-2.963-1.318Local
government tax
Local tax
revenue perrevenue
total local
ratio
government
revenue183

0.5318 0.09712

183

0.5284 0.09912-0.638318

0.3693 0.11793

318

0.362 0.1159-1.981

1.344

UPA
farmlandratio

Effective
tax rateN

FY1992

Notes: See Table 4 for the definitions and data sources of all the variables.

31

Table 6. Results from a series of placebo tests for the simple DID estimation (without control
variables, FY 1985-1986). Dependent variable: UPA farmland ratio

DID estimate

𝑅2

Case1

Case2

Case3

-0.001-0.001-0.0001(0.007)(0.008)(0.011)

0.34

0.25

0.16

183

183

183

318

206

104

N. of treatedmunicipalities
N. of control
municipalities
Note: The placebo treatment variable (𝑅𝐸𝐹𝑂𝑅𝑀𝑡 ) is equal to 1 for FY 1986. Heteroskedasticity-robust standard errors
are in parentheses. DID estimate indicatesof Equation (9).

32

Table 7. Simple DID estimates (without control variables). Sample periods=FY1991-FY1992
Dependent
variable

Ufarm
Case1

DID esimate

N. of treatedmunicipalities
N. of control
municipalities

Housing
Case2

Case3

Case1

Farm
Case2

Case3

Case1

Case2

Case3

-0.038 ***-0.037 ***-0.037 ***

0.004

0.003

0.003

0.033 *

0.032 *

0.033

(0.005)(0.006)(0.007)(0.02)(0.024)(0.031)(0.022)(0.025)(0.03)

0.29

0.22

0.18

0.43

0.35

0.26

0.1

0.09

0.05

183

183

183

183

183

183

183

183

183

318

206

104

318

206

104

318

206

104

Notes: “Ufarm” means the share of urbanization promotion area farmland in total land (=UPA farmland + housing lots + ordinary farmland), “Housing” is the share of housing lots intotal land, and “Farm” indicates ordinary farmland ratio per total land. Heteroskedasticity-robust standard errors are in parentheses. “DID estimate” indicatesof Equation (9). Asterisks indicate significance levels: * = 10%, and *** = 1%.

33

Table 8. DID estimates with control variables. Dependent variable= the share of urbanization
promotion area farmland per total land. Sample periods=FY1991-FY1992
Case1

Case2

Case3

-0.038 ***-0.038 ***-0.037 ***(0.005)(0.005)(0.005)0.018 ***

0.011 ***

0.007 *

(0.002)(0.004)(0.005)

0.001

0.001

0.001

(0.002)(0.002)(0.003)-1.643 ***-2.117 ***-2.743 ***(0.17)(0.228)(0.495)

Local tax revenue

0.014

0.025 **

0.022

ratio

(0.012)(0.014)(0.018)Agricultural income-0.008 ***-0.012 ***-0.014 ***(0.002)(0.002)(0.003)0.028 ***

0.033 ***

0.036 ***

(0.002)(0.002)(0.002)

0.001

0.002

0.002

(0.002)(0.002)(0.002)-0.063 ***-0.067 ***-0.057 ***(0.015)(0.018)(0.022)

0.593

0.546

0.478

183

183

183

318

206

104

DID estimate

Effective tax rate

Population density

Shipment

const

𝑅2

N. of treatedmunicipalities
N. of control
municipalities

Notes: We take the logarithm regarding agricultural income, population density, and shipment in our estimation.
“DID estimate” indicatesof Equation (9). Asterisks indicate significance levels: * = 10%,**=5%, and *** = 1%.

34

Table 9. DID estimates with control variables. Dependent variable= the share of housing lots per
total land. Sample periods=FY1991-FY1992
Case1

Case2

Case3

0.003

0.002

0.0005(0.013)(0.012)(0.013)0.006-0.022 **-0.037 ***(0.01)(0.01)(0.012)0.0004

0.002

0.003

(0.005)(0.012)(0.008)3.834 ***

4.317 ***

4.994 ***

(0.597)(0.769)(1.254)

Local tax revenue-0.095 ***

0.004

0.003

ratio

(0.033)(0.043)(0.048)Agricultural income-0.017 ***-0.022 ***-0.024 ***(0.005)(0.006)(0.007)0.166 ***

0.189 ***

0.208 ***

(0.005)(0.005)(0.006)0.007 *

0.013 **

0.016 ***

(0.004)(0.005)(0.006)-0.771 ***-0.97 ***

-1.117 ***(0.054)(0.059)(0.069)

0.834

0.836

0.829

183

183

183

318

206

104

DID estimate

Effective tax rate

Population density

Shipment

const

𝑅2

N. of treatedmunicipalities
N. of control
municipalities

Notes: We take the logarithm of agricultural income, population density, and shipment in our estimation. “DIDestimate” indicatesof Equation (9). Asterisks indicate significance levels: * = 10%, **=5%,and *** = 1%.

35

Table 10. DID estimates with control variables. Dependent variable= the share of ordinary farmland
per total land. Sample periods=FY1991-FY1992
Case1

Case2

Case3

0.032 *

0.032 *

0.031

(0.021)(0.022)(0.027)-0.043 **-0.014-0.023(0.019)(0.02)(0.023)

0.006

0.006

0.004

(0.013)(0.017)(0.022)-2.591 ***-2.0472.182(1.323)(1.732)(2.746)

Local tax revenue-0.058-0.0060.125 **

ratio

(0.059)(0.063)(0.068)Agricultural income-0.061 ***-0.063 ***-0.058 ***(0.009)(0.009)(0.01)-0.025 ***-0.057 ***-0.08 **

(0.008)(0.008)(0.01)

0.026 ***

0.025 ***

0.016 **

(0.006)(0.007)(0.007)0.933 ***

1.174 ***

1.335 ***

(0.073)(0.081)(0.09)

0.19

0.25

0.278

183

183

183

318

206

104

DID estimate

Effective tax rate

Population density

Shipment

const

𝑅2

N. of treatedmunicipalities
N. of control
municipalities

Notes: We take the logarithm of agricultural income, population density, and shipment in our estimation. “DIDestimate” indicatesof Equation (9). Asterisks indicate significance levels: * = 10%, **=5%,and *** = 1%.

36