DISCUSSION PAPER SERIES
2009-03
Effective Policy Package on Household Garbage
and Recycling

Akihiro Kawase and Tadakatsu Nakamura

November 20, 2009

Discussion Papers can be downloaded:
http://www1.tcue.ac.jp/home1/c-gakkai/dp/dp09-03

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Effective Policy Package on Household Garbage
and Recycling∗

Akihiro Kawase
Faculty of Economics, Toyo University

andTadakatsu Nakamura
Faculty of Regional Policy, Takasaki City University of Economics

November 2009∗

We are grateful to Kazuyoshi Kurokawa, Kazuhiro Ueta, and participants at the Japanese Economic
Association meeting for helpful comments. We collect data of price per bag of household garbage inmunicipalities in Japan. We are also grateful to persons in charge of administrative divisions who
cooperated in our data collection. Kawase also thanks the Grant-in-Aid for Young Scientists (B) for
financial support.
2

1. Introduction
An increasing number of local governments in Japan have begun charging theirresidents for garbage collection. The share of cities that implement a user-fee programfor garbage collection increased from 20% in 2000 to roughly 40% in 2004 (Yamakawa
and Yano, 2008). In Japan, there are basically two types of user-fee programs: theunit-based pricing program and the flat-fee program. The unit-based pricing program,which is widely used in many municipalities, requires each household to purchase a
special bag or sticker for each unit of garbage it presents for collection. The flat-fee
program, now used in a minority of municipalities, imposes on each household a fixed
fee per family regardless of the quantity of garbage.
Waste management is a responsibility of the local government in Japan.
Municipalities are obliged to collect four types of waste separately: (1) burnablegarbage, such as food scraps; (2) noncombustible garbage, such as glass or fluorescentlights; (3) recyclable material, including cans, bottles, plastic pet bottles, magazines,
newspapers; and (4) bulky waste. However, the classification of burnable andnoncombustible garbage differs by municipality. For instance, some municipalities
classify plastic as burnable garbage, whereas others classify it as noncombustible
garbage. Statistics of the Ministry of the Environment in Japan classify burnablegarbage and noncombustible garbage as general waste.
The quantity of household garbage has not greatly decreased between 2000 and
2004. The quantity of household garbage per capita dumped in 2004 was 1.09 kg a year
(Ministry of the Environment, 2004). That was a decrease of only 3.5% from 1.13 kg in
2000. However, the recycling rate rose from 14.3% in 2000 to 17.6% in 2004. Moreover,Japan has a particular problem—a shortage of dump-sites. Since Japan is small, it isdifficult to secure governmental permission to build a dump-site. In 2004, Japan’s
existing dump-sites had an average remaining life of 13.2 years. Therefore, it isnecessary for the Japanese to reduce the quantity of garbage and to promote recycling3

immediately. It is also the reason why municipalities are considering charging forcollection of household garbage and recyclable material.
There must be other economic approaches that are effective for reducing household
garbage and promoting recycling than charging for municipal garbage collection anddisposal. This paper employs municipality-level data in Japan to suggest a more
effective policy for reducing household garbage and promoting recycling. It is an
important contribution to clarify a more effective policy package to reduce household
garbage and promote collection of recyclable materials for municipalities in Japan.
Our paper makes three main contributions. First, we collect original data from asignificantly large cross-section of Japanese municipalities, and we estimate the priceelasticity of garbage demand in Japan. Evaluated at the mean price, the price elasticity is−0.024 for municipalities with price data calculable in our sample, and −0.215 formunicipalities that implement a unit-pricing program. Second, while other studies
estimate the demand for garbage collection or for recycling collection, we estimate bothwith seemingly unrelated regression (SUR) because households dispose garbage andrecyclable materials simultaneously. Third, we suggest an effective package ofmunicipal policies to reduce household garbage and promote recycling.
This paper is organized as follows. Section 2 describes previous literature
concerning reducing household garbage and recyclable materials. Section 3 discusses
our empirical method and data. Section 4 estimates the effect of municipal policies on
garbage and recycling employing cross-sectional data of Japan using SUR. Section 5
concludes the paper.

2. The previous literature
There are several empirical studies about policies to reduce waste and encourage

4

recycling.1 Many researchers have especially discussed the effect of user-fee programsfor garbage collection and disposal service. There are two streams of literature that
estimate the impact of implementing unit-based pricing programs. The first uses
cross-sectional data from municipalities (Wertz, 1976; Jenkins, 1993; Miranda et al.,
1994; Strathman et al., 1995; Callan and Thomas, 1997; Podolsky and Spiegel, 1998;
Van Houtven and Morris, 1999; Kinnaman and Fullerton, 2000; Dijkgraaf and Gradus;
2004). The second uses household survey data (Hong et al. 1993; Reschovsky and Stone,
1994; Fullerton and Kinnaman, 1996; Van Houtven and Morris, 1999; Hong, 1999;
Hong and Adams, 1999; Linderhof et al., 2001; Jenkins et al., 2003).
In Japan, many empirical studies analyze municipal policies, which effectively
reduce the quantity of household garbage (Maruo et al., 1997; Sasao, 2000; Usui, 2003;
Nakamura, 2004; Nakamura et al., 2007).2 However, because price data per garbage
bag are not provided publicly in Japan, Maruo et al. (1997), Sasao (2000) andNakamura (2004) analyze the effect of the pricing program on municipal garbage
collection and disposal service using dummy variables (=1 where a pricing program is
implemented, and =0 otherwise). They show that the unit-pricing type of user-fee
program is effective in reducing household garbage, and that flat-fee program isineffective.3
However, using dummy variables to represent user fees as a factor in reducing thequantity of garbage presents two problems: it becomes impossible to consider variationof price per garbage bag among municipalities, and it merely verifies the average effectof a user-fee program on garbage reduction. Given this situation, we cannot analyze therelation between the setting of the price and the quantity of garbage. In addition,
estimates of the effect of user-fee programs on the quantity of garbage are insufficient.
Recently, several researchers have collected original price data for user-fee
1Kinnaman and Fullerton (1999) and Kinnaman (2006) give an overview of the empirical studies.
Yamakawa and Ueta (1996, 2001) provide an overview of the Japanese literature.
3
The marginal cost that households faced in the flat-fee pricing program is zero. It is a program
design that might not incentivize reducing the quantity of garbage per household.
2

5

programs and estimated price elasticity of garbage demand. Usui (2003) interviewed
611 municipalities and collected the price of garbage bag. Results using cross-sectional
data for municipalities showed that the price elasticity of municipal garbage collection
and disposal is −0.082. Nakamura et al. (2007) collected, via e-mail, original price datafor garbage bags. They estimate the price elasticity equal to −0.026 evaluated at the
average price per garbage bag.4
Estimation of price elasticity in Japan is in the early stage of research, asmentioned above. We focus not only on the user-fee program in municipal solid waste
management policy but also on economic instruments such as the number ofsegregations, frequency of collection service, collection system, etc. The purpose of thispaper is to indicate direction for an effective policy to reduce garbage and promote
recycling. While other studies estimate the demand for garbage collection or forrecycling collection respectively, we estimate both with SUR as households dispose of
garbage and recyclable materials simultaneously. This paper contributes to the empiricalliterature estimating the effects of municipal policies designed to reduce household
garbage and promote recycling.

3. The model
We estimate the following model to show an effective policy package formunicipalities to reduce garbage and collect more recyclable materials (Model 1):

log Gi = α 10 + X iα 11 + α 12 S i + Fiα 13 + C iα 14 + I iα 15 + u1i

4(1)

The difference in price elasticity estimated in these two articles arises from differences in thedependent variable used. Nakamura et al. (2007) use the quantity of household garbage as adependent variable, which excludes bulky waste. Usui (2003) uses the total quantity of household
garbage as a dependent variable, which includes bulky waste. But households’ decision-making for
disposing of general waste and bulky waste must be different.
6log Ri = β10 + X i β11 + β12 S i + Fi β13 + Ci β14 + I i β15 + ε 1i ,[where Fi = FiG

⎡C siGFi , Ci = ⎢ R
⎣C si
R

]

ChiG
ChiR

⎡ I Gfi
CkiG ⎤⎥, I i = ⎢ RCkiR ⎦⎣⎢ I fi(2)

I viG ⎤⎥,
I viR ⎦⎥

where Gi and Ri are the per capita weight of garbage and recycling for municipality

i those were exhausted by household for the municipality’s collection service,respectively. Both are converted into logarithms. X i is a vector of independent
variables. The econometric model controlled for per capita income, household size,
gender ratio, floor space per capita, population density, and rate of daytime population
to nighttime population. S i is the number of segregations of garbage. Fi is the vectorof frequency of collection of garbage and recyclable materials. Ci is the vector ofdummy variables, which indicate the collection system of garbage and recyclable
materials, respectively. The superscript s denotes that garbage and recyclable
materials are collected at the limited number of places selected by municipalities.5 The
superscript h denotes that garbage and recyclable materials are collected individuallyin front of a resident’s house. The superscript k denotes that both types of thesecollection systems are adopted in one municipality. I i also includes vectors of dummy
variables that indicate the presence of user-fee pricing programs for garbage andrecyclable materials, respectively. The subscript f denotes that the user fee is fixed
regardless of the quantity of garbage (flat fee); and the subscript v denotes that theuser fee is variable according to the number of garbage bags (unit-pricing).
In addition to Model 1, we estimate the following model, which includes the priceper garbage bag, to calculate the price elasticity of demand (Model 2):

log Gi = α 20 + X iα 21 + α 22 S i + Fiα 23 + C iα 24 + I iα 15 + α 26 pricei + u 2i

5This type of collection system is called “station” in Japan.
7(3)log Ri = β 20 + X i β 21 + β 22 S i + Fi β 23 + C i β 24 + I i β 25 + ε 1i ,[where Fi = FiG

⎡C siGFi , Ci = ⎢ R
⎣C si
R

]

ChiG
ChiR

⎡ I Gfi
CkiG ⎤⎥, I i = ⎢ RCkiR ⎦⎣⎢ I fi(4)

I viG ⎤⎥,
I viR ⎦⎥

where pricei denotes the price per garbage bag, which we originally collected fromeach prefecture.6 We calculate price per 10-liter garbage bag from our collected data inmunicipalities that implement a unit-pricing program, and set zero in the municipalitythat implements a flat fee or no fee. The marginal price, which is imposed on theresident, is positive in municipalities that implement a unit-pricing program. The
marginal price is zero in municipalities that implement a flat fee or no fee. Data used in
the analysis are cross-sectional data for 2004, and the number of observations is 2,070.
The number of observations in Model 2 is 1,633, which is fewer than Model 1 because
the price data are missing.
It is possible that a part not explained by the explanatory variables is included in
the error term and that the correlation is caused in the error term of each function,
because the households’ decisions to dispose of garbage and recyclable materials occur
simultaneously. We then estimate both Eq.(1) and Eq.(2), and Eq.(3) and Eq.(4), with
SUR, a procedure advocated by Zellner (1962) to deal with this problem.
Definitions of variables and data sources are shown in Table 1, and descriptive
statistics of these variables are shown in Table 2.
Table 2 shows considerable variation among municipalities. Garbage averages
236.3 kg per person per year. Recycling averages only 39.8 kg per person per year.
Number of segregations ranges from 2 to 26, and it averages 11. Frequency of collection
service for household garbage averages two or three times per week, and frequency ofcollection service for recyclable materials averages only once every two weeks. About
90% of municipalities have adopted the station collection system. Less than half of6

We e-mailed questionnaires to all (47) prefectures in Japan and received 19 replies.
8

municipalities charge for garbage collection. About 29.8% of municipalities adopt theunit-pricing user-fee system, and 14.4% adopts the unit-charging system. On the other
hand, collection of recyclable materials is free in most municipalities. Although we havea sample size of 2,070 from publicly available data, we gathered data from 1,633
municipalities by our request. We eliminate the remaining 437 municipalities from theregressions of Model 2, which reduces our sample size to 1,633. The price ranges fromzero to ¥25.7 per 10-liter garbage bag, and it averages ¥1.127 per 10-liter bag.

4. Estimation results
The estimation results using SUR are shown in Table 3. The null hypothesis thatthe correlation of the error term is zero is rejected from the result of the Breusch–Pagan
test at the 1% significance level. Let us first examine the results of Model 1.

4.1 Other control variables
The coefficient on the logarithm of per capita income is positive for the quantity ofhousehold garbage and recyclable materials and significant at the 1% level. Householdswith high incomes not only have more waste material, but they also face a highopportunity cost for time spent dumping. Therefore, high-income households dispose of
more garbage and recyclable materials. A 1% increase in per capita income increases thequantity of the household garbage by 0.38% and recyclable material by 0.46%.7 The
income elasticity of recyclable materials is higher than that of garbage because many
heavy-weight items are included in recyclable waste: newspaper, magazines, waste cans,
empty bottles, etc.
Household size has a negative relationship to the quantity of household garbage
7

Others have estimated income elasticity to be 0.279 and 0.272 (Wertz, 1976), 0.41 (Jenkins, 1993),
0.57 (Podolsky and Spiegel, 1998), and 0.262 (Kinnaman and Fullerton, 2000).
9and recyclable materials and is significant at the 1% level: a one-person increase inhousehold size decreases the quantity of garbage by 9.2% and recyclable material by
34.6%.8 The reason for this result is that families share the use and consumption ofmany goods. Therefore, the impact on quantity of recyclable materials is larger than for
garbage because food packaging, newspapers, and so on that are taken to the municipal
collection service for recycling are items consumed by many family members.
The coefficient on the gender ratio (male/female) is negative and significant at 1%
level only in the Eq.(1) and is not significant in Eq.(2). If the ratio of male to female
increases by 1%, the quantity of household garbage decreases by 0.5%. This result
arises from the difference in lifestyle between men and women in Japan. Japanese men
dine out more often than women and generate less waste at home. In addition, thegeneral cycle time from purchase to abandonment of clothes is slower among men
relative to women.
The floor space per capita has different effects on the quantity of household
garbage and recyclable material. The coefficient on floor space per capita of Eq.(1) is
negative and that of Eq.(2) is positive and significant at the 5% level. A one square
meter increase in floor space per capita decreases the quantity of household garbage by
0.4% and increases the quantity of recyclable material by 0.8%. The reason for thisresult is that it is easier for households living in roomy homes to store unnecessary
wastes, such as clothing that is purchased but never worn, and it is easier to separate andstore recyclable materials because households can maintain spaces for trash boxes.
The coefficients on population density and the density-squared are significant.
Population density has a positive effect on the quantity of household garbage and anegative effect on the quantity of recyclable materials. In Eq.(1), the coefficient on
density is positive. Although households in rural areas can burn or compost their waste
in their backyard, urban households must use the municipality’s garbage collection and8

Jenkins (1993), Podolsky and Spiegel (1998), Dijkgraaf and Gradus (2004) find that an increase in
the size of households decreases the per capita quantity of garbage disposed.
10disposal service. The square term is negative; we find the marginal quantity of garbage
decreasing with population density.
On the other hand, in Eq.(2) the coefficient on population density is negative andthe square term is positive. Many supermarkets set out collection boxes for people todeposit paper, food packaging trays, glass bottles, metal cans, dry cell batteries, and soforth in areas where population density is very high. In addition, homeless people
sometimes collect recyclable waste and sell it to collection traders before it is collectedby the municipality. In both instances, recyclable waste is collected without dependingon the service provided by the municipality in these areas.
The coefficient on the ratio of daytime population to nighttime population ispositive and significant only in regard to the quantity of household garbage. The
business and commercial garbage is charged in Japan. More than half of Japan’smunicipalities provide garbage collection service without charge, as shown in Table 2.
There is a possibility that business and commercial garbage is mingled with household
garbage in areas where daytime population is high.

4.2 Policy variables
We now discuss the results of our study for municipal waste management policy.
The coefficient on the number of segregation shows a negative impact on thequantity of household garbage and a positive impact on the quantity of recyclable
materials. 9 The 1.4% decrease in the weight of garbage and the 6.1% effect oncollection of recyclable waste can be expected by increasing one kind of number ofsegregation. This estimated result implies that increasing the number of segregation ofwaste is one of the effective policies for reducing household garbage and collecting
recyclable materials.
The coefficient on frequency of garbage collection service per week is positive for
9

Duggal et al. (1991) also find that increases in the number of items increases the quantity ofrecycled glass.
11the quantity of household garbage and negative that the quantity of recyclable materials
and significant at the 1% level. On the other hand, the coefficient on frequency ofrecycling collection service per week is negative for the quantity of household garbage
and positive to that of recyclable materials. 10 These estimated results imply that
decreasing the frequency of garbage collection and increasing the frequency ofrecycling collection also are effective policies for reducing garbage and collecting
recyclable materials. If the costs of collecting garbage and collecting recyclable
materials are the same, our estimates show that the municipality should shift from thecollection of garbage to collection of recyclable wastes.
Variations among collection systems have little impact on the quantity ofhousehold garbage and recyclable materials. The base group of collection systemdummy variables is “station” system. We believe the coefficient on individual
household collection is significantly positive because it is easy for households todispose of garbage and recyclable materials. However, the coefficient on the
combination of station collection and household collection is positive for the quantity ofhousehold garbage, and the coefficient on “others” is negative for the quantity ofrecyclable material. We can neither explain these results nor draw conclusions
concerning the type of collection system because there is narrow variation amongcollection systems, as shown in Table 2.
The implementation of user-fee pricing systems for household garbage of flat fee
and unit-pricing type has a negative effect on the quantity of household garbage and issignificant at the 1% level. If the municipality employs a flat-fee program, the quantityof household garbage declines by −14.8% ( = exp(−0.160) −1) relative to municipalities
that do not implemented user-fee programs. If the municipality employs a unit-pricing
program, the quantity of household garbage declines −10.3% ( = exp(−0.108) −1)
relative to municipalities that do not implement a user-fee system. Ordinarily, because
10

Duggal et al. (1991) estimate that the quantity of recycled glass increases with the frequency ofcollection.
12

unit-pricing programs provide better marginal incentives, we would predict that thequantity of household garbage collected by unit-pricing programs is less than that byflat-fee programs. Unfortunately, however, it is not known exactly why, and discovering
why is a task for the future. We cannot obtain statistically significant results in theimplementation of user-fee program for recyclable materials.

4.3 The price elasticity of demand for garbage
Next, we discuss the estimated results of Model 2. Our estimates of Model 2 aresimilar to Model 1. We find that the estimated coefficients on these variables are robust.
Therefore, we describe only findings that pertain to the price per bag.
The coefficient on the price per bag is negative for the quantity of household
garbage and significant at the 1% level. By these estimates, the change in price per bagof ¥1 would reduce weight of garbage by 2.1%. The price elasticity is −0.024 (= −0.021
× 1.127), evaluated at the point of the mean price (¥1.127/10 liter), because thecoefficient on the price per bag implies semi-elasticity. The price elasticity at this pointis very low because the average price is very low.11 Most municipalities in our sample
had not implemented a user-fee program and thus charged a price of zero. Among
municipalities with unit-pricing user-fee programs, the average price charged was¥10.235. Evaluated at this point, the price elasticity is −0.215 (= −0.021 × 10.235). This
calculation is perhaps the one that is most appropriate to compare with price elasticity
estimates provided in the previous literature.12

5. Conclusion

11

Kinnaman and Fullerton (2000) estimates the price elasticity at the mean price is −0.034.
Others have estimated price elasticity to be −0.15 (Wertz, 1976), −0.12 (Jenkins, 1993), −0.39(Podolsky and Spiegel, 1998), −0.15 (VanHoutven and Morris, 1999), −0.28 (Kinnaman and
Fullerton, 2000), −0.08 (Usui, 2003), −0.43 (Dijkgraaf and Gradus, 2004).
12

13

This paper estimates the implications of municipal policy on reducing household
garbage and promoting recycling in Japan. We collected original data from asignificantly large cross-section of Japanese municipalities, and we estimated the priceelasticity of garbage, which is −0.024 evaluated at the average price per bag (¥1.13/10
liter) for municipalities with price data calculable in our sample, and −0.215 at the
average price (¥10.24/10 liter) for municipalities that implement a unit-pricing program.
We employ SUR because households dispose of garbage and recyclable materials
simultaneously.
Our results show that a municipality can expect to reduce the quantity of household
garbage and to promote recycling by implementing the following policies. (1) Increase
the number of segregations. (2) Decrease the frequency of collection service forhousehold garbage and increase frequency of collection for recyclable material. (3)Implement a unit-pricing program for collecting household garbage and collectrecyclable material free of charge.
However, we cannot determine the optimal municipal policy for reducing
household garbage and promoting recycling. We only indicate a direction for effective
policy. Japanese municipalities are increasingly implementing user-fee programs to help
reduce household garbage. The advisability of these policies depends on thecircumstances specific to municipalities, such as number and condition of garbage
disposal facilities, the extent of illegal dumping, their fiscal condition, etc.

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Eastern Economic Journal 17(3), 351-358.
Dijkgraaf, E., Gradus, R., 2004. Cost savings in unit-based pricing of household waste:
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17

Table 1
Variables
Household garbage per capita
Recyclable material per capita
Income per capita

Unit

Definitions of variables

Definitions of Variables

kg

Data source

Weight of household garbage / Number of populationkg
million yen

Ministry of the Environment, Survey on Disposal of General Waste

Weight of recyclable materials / Number of population

Ministry of the Environment, Survey on Disposal of General Waste

Income / Number of population

Income: Ministry of International Affairs and Communications, Survey of Taxation of Cities, Towns and Villages Tax
Population: Ministry of International Affairs and Communications, Population Census

Family size

personNumber of population / Number of households

Gender ratio%(Population of man / Population of woman) * 100

Ministry of International Affairs and Communications, Population Census

Floor space per capitam

Floor spaces / Population

Ministry of International Affairs and Communications, Population Census

Population / Area

Ministry of International Affairs and Communications, Population Census

Population density
Rate of daytime population to nighttime population
Number of segregation
Frequency of collection service
Collection system221,000 people / km%items
times per week
dummy

Ministry of International Affairs and Communications, Population Census(Daytime population / Population) * 100%

Ministry of International Affairs and Communications, Population Census

burnable, unburnable, recycable such as paper, petbottle and magazine so on

Ministry of the Environment, Survey on Disposal of General Waste

Frequency of the collcetion service a month / 4 weeks

Ministry of the Environment, Survey on Disposal of General Waste

Dummy variables as follows:

Ministry of the Environment, Survey on Disposal of General Waste

StationStation which municipality decided=1, others=0.

Individual

In front of house individually=1, others=0.

Combination

Conbination of station and individual=1, others=0.

Others
Implementation of user fee system

dummy

Unit-pricing

Ministry of the Environment, Survey on Disposal of General Waste

User fee is variable per garbage bag=1, others=0.

Flat fee
Price per garbage bag

Dummy variables as follows:
User fee is fixed=1, others=0.

yen / 10 liter

The price per garbage bag.

Originally collected18

Table 2

Descriptive statistics
All sample

Variables

Unit

Sample including variable of price per bag(Obs.=2070)
Mean

Std.Dev.

(Obs.=1633)

Min.

Max.

Mean

Std.Dev.

Min.

Max.

Dependent variables
Household garbage per capita

kg

236.338

87.32915.4561129.432

242.064

85.95915.4561129.432

Recyclable material per capita

kg

39.75927.2850.223

325.473

39.80526.804

0.223

325.473

Controll variables
Income per capita
Family size

1 million yen

1.079

0.279

0.409

2.599

1.095

0.295

0.409

2.599

person

3.071

0.456

1.701

4.567

3.079

0.457

1.701

4.567
180.025

Gender ratio (Male to female rate)%

93.9946.561

65.796180.025

94.2956.829

65.796

Floor space per capita

m2

39.096

5.722

23.21263.78438.943

5.882

23.21263.7842

1,000 people / km
%

0.641

1.381

0.002

13.371

0.732

1.506

0.002

13.37193.57811.15960.915289.92393.57711.65861.051289.923

items

10.930

4.559

2.000

26.00011.070

4.607

2.000

26.000For household garbage

2.816

0.893

0.000

11.500

2.825

0.847

0.000

8.000

For recyclable material

0.521

0.296

0.000

1.750

0.518

0.292

0.000

1.750

[Household garbage] Station

0.876

0.330

0.000

1.000

0.888

0.316

0.000

1.000

[Household garbage] Individual

0.052

0.221

0.000

1.000

0.045

0.207

0.000

1.000

[Household garbage] Combination

0.069

0.254

0.000

1.000

0.063

0.243

0.000

1.000

[Household garbage] Others

0.003

0.058

0.000

1.000

0.004

0.065

0.000

1.000

[Recyclable material] Station

0.897

0.305

0.000

1.000

0.903

0.296

0.000

1.000

[Recyclable material] Individual

0.043

0.203

0.000

1.000

0.037

0.188

0.000

1.000

[Recyclable material] Combination

0.050

0.218

0.000

1.000

0.048

0.215

0.000

1.000

0.010

0.100

0.000

1.000

0.012

0.107

0.000

1.000

Population density
Rate of daytime population to nighttime population
Policy variables
Number of segregation
Frequency of collection service

Collection systemtimes per week

dummy

[Recyclable material] Others
Implementation of user fee program

dummy[Household garbage] Unit-pricing

0.298

0.457

0.000

1.000

0.110

0.313

0.000

1.000

[Household garbage] Flat fee

0.144

0.351

0.000

1.000

0.179

0.384

0.000

1.000

[Recyclable material] Unit-pricing

0.100

0.299

0.000

1.000

0.040

0.196

0.000

1.000

[Recyclable material] Flat fee

0.060

0.238

0.000

1.000

0.074

0.262

0.000

1.000

1.128

3.566

0.000

25.741Price per garbage bag

yen / 10 liter

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Table 3

Estimation results of SUR
Model 1Model 2

Household garbage

Recyclable material

Household garbage

Recyclable material

per capita (logarithm)

per capita (logarithm)

per capita (logarithm)

per capita (logarithm)

Eq.(1)

Eq.(2)

Eq.(3)

Eq.(4)

Controll variables
Income per capita

logarithm

0.383(0.037)

***

0.458

(0.080) ***0.398(0.041) ***0.438(0.088) ***Family size

person-0.092(0.018)***-0.346(0.038) ***-0.086(0.019) ***-0.309(0.042) ***Gender ratio (Male/Female)percent-0.005(0.001)

***

0.001

(0.003)-0.005(0.001) ***-0.001(0.003)2-0.004(0.002)**0.008(0.004) **-0.004(0.002) **0.004(0.004)

Floor space per capita

m

2

0.087

(0.017)***-0.081(0.036) **0.064(0.018) ***-0.064(0.039) *-0.010(0.002)

***

0.008

(0.004) **-0.008(0.002) ***0.007(0.004) *

%

0.006

(0.001)***-0.002(0.002)0.005(0.001) ***-0.003(0.002) *items-0.014(0.002)

***

0.061

(0.003) ***-0.016(0.002) ***0.057(0.004) ***For household garbage

0.068(0.009)***-0.093(0.019) ***0.070(0.010) ***-0.118(0.022) ***For recyclable material-0.063(0.027)**0.419(0.059) ***-0.021(0.031)

0.353(0.067) ***[Household garbage] Individual

0.106(0.074)-0.031(0.159)0.061(0.085)0.024(0.184)[Household garbage] Combination

0.158(0.050)0.034(0.106)0.141(0.059) ***0.010(0.129)[Household garbage] Others-0.130(0.126)

0.187(0.271)-0.112(0.124)0.192(0.270)[Recyclable material] Individual

0.056(0.081)

0.158(0.174)0.107(0.093)0.038(0.202)[Recyclable material] Combination-0.077(0.057)0.188(0.123)-0.035(0.067)0.168(0.147)[Recyclable material] Others

0.093(0.073)-0.969(0.156) ***0.086(0.075)-0.992(0.163) ***Population density

1,000 person per km

Square of population density
Rate of daytime population to nighttime population
Policy variables
Number of segregation
Frequency of collection service

Collection system

Implementation of user fee program

times per week

dummy
***

dummy

[Household garbage] Unit-pricing-0.108(0.019)***-0.032(0.040)0.130(0.063) **0.018(0.067)[Household garbage] Flat fee-0.160(0.026)

***

0.017

(0.056)-0.167(0.026) ***0.020(0.057)[Recyclable material] Unit-pricing-0.098(0.028)***-0.060(0.060)-0.062(0.049)-0.224(0.106) **[Recyclable material] Flat fee

0.028(0.038)-0.017(0.081)0.030(0.038)-0.012(0.083)-0.021(0.005) ***5.780(0.188) ***4.141(0.410) ***Price per garbage bag
Constant

5.787(0.174)

***

3.759
0.224

(0.374) ***R-squared

0.292

Breusch-Pagan test

53.679 ***36.539 ***Number of observations

2,070

1,633

Note: Standard errors are in parentheses. ***, **, and * indicate significance at 1%, 5%, and 10% level, respectively.

20

0.301

0.213

高崎経済大学地域政策学会
370-0801 群馬県高崎市上並榎町１３００
027-344-6244
c-gakkai@tcue.ac.jp
http://www1.tcue.ac.jp/home1/c-gakkai/dp/dp09-03

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