HOUSEHOLD BEHAVIOR ON SOLID WASTE MANAGEMENT: A

CASE OF KATHMANDU METROPOLITAN CITY

Abstract

This paper tries to show the household behavior of Kathmandu residents towards solid waste

management. The paper is the outcome of a primary survey of 432 households covering different

parts of the city of Kathmandu. The daily per capita waste generation in Kathmandu is 0.29 kg

and is lower in the core zone than in the outer and middle zones. This indicates that as there is

more open space to throw the waste people usually generate more waste. Household size and

income are the major determining factors for the total quantity of wastes generated in all the zones.

About 80% of the households are willing to pay for better management of waste. This comes to

about Rs. 72 per household per month. The willingness to pay is highest in the outer zone and

lower in the core zone. The main factor determining the “Willingness to Pay” is income.

1. INTRODUCTION

Prior to 1950, there was hardly any problem of solid waste management in Nepal. The solid waste

was locally managed in all the urban areas of Nepal including Kathmandu Valley. Almost all the

wastes was organic in nature and was used as manure (Tuladhar 1996). Traditionally, only a special

caste (i.e. Pode or Chyame) was involved in waste management activities. In the past, these people

collected the waste from settlements using primitive tools such as buffalo ribs to lift the waste and

shoulder baskets (Kharpan) to carry the wastes (Tuladhar 1996). The wastes collected were

dumped on nearby river banks or in open fields. In those days, the flow of water in nearby rivers

was capable in degrading the dumped organic wastes which were small in quantity. But these

traditional practices could not continue due to the increasing population densities in urban areas.

Increase in population density has lead to the increase in the volume of waste. This has created a

massive threat to public health due to the lack of proper solid waste management.

1

Thus after the mid-1960s initiation started in the diagnosis of the problem and some short-term as

well as long term suggestions were given by different studies (Flinthoff1, 1970; Tabasaran, 1976

and 1981; Croll 1978). These studies were basically meant for the smooth functioning of the Solid

Waste Management Project and quick collection and disposal of the waste. Some other studies were

on the possibility of pricing for garbage services (Agrawal et al. 1982; Flinthoff, 1970; GTZ 1996;

SWMB GTZ 1985).

1.2 Rational

Even with all these research and studies, the problem of solid waste management in Kathmandu has

been increasing over the years. Presently, the task of solid waste management comes under the

auspices of concerned municipalities. The service is provided almost free of charge using funds

available at the disposal of the municipalities. Nearly 20-25% of the total budget of the Metropolis

goes for solid waste management (KMC, Department of Solid Waste Management, 1998).

One of the studies conducted by the Central Bureau of Statistics shows that unmanaged waste

disposal was considered the main cause of environmental problems in Kathmandu followed by

unmanaged sewage (CBS 1996, in CBS 1998 a). Thus solid waste management is a growing issue

in the context of urban environmental degradation of Kathmandu. The rate of growth of population

of the Kathmandu Valley is more than 6%, which is the highest among the cities of Nepal. Due to

the rapid increase in population and increase in the consumption of packed goods, the amount as

well as the quantum of non-biodegradable waste is increasing over time. Among the total waste

generated in Nepal, 80% is generated only from Kathmandu and only 30% of the total urban refuse

is being collected in containers and transferred to the landfill site (Thapa et al. 1999).

1.2. Studies on the Economics of Solid Waste Management

Solid waste management is also a non-excludable good as it is difficult to be protected by the

general market forces. One way of managing non-excludable goods or services is either by the

internalization of costs (by levying charges for the use of the services) or by following a command

and control policy or a combination of both. Government intervention is necessary for this. The

rationality of the government’s intervention can be judged when the costs of producing the good or

service decline as more of the good or service is produced and when production or use of the good

or service results in "externalities" such as environmental pollution (Macauley and Walls, 1995;

1 Mr. F. Flinthoff was from WHO Regional Office for South East Asia and stayed as a short-term consultant in Kathmandu about the end of 1970 for a period of two months. He gave a report named Assignment Report in the Solid Waste Management in Kathmandu Who-Project Searo. 0150, 1970.

2

Jenkins, 1993). Thus, the major problem for solid waste management is the internalization of costs

of waste disposal.

In the early days economists discussed about the socio-economic factors influencing waste

generation by the households. Wertz (1976) discussed about the economic aspects of household's

decisions to produce more or less refuse. He mainly analyzed the theoretical concept about

household behavior on waste generation due to the changes in income, price of refuse service,

frequency of service, site of refuse collection and packaging. He also discussed on resource

implications of the local government policy, which refrains from the pricing of public refuse

service to households.

Economists also compared the composition and quantity of waste in terms of income level,

household size and age structure of the household. The household size, household income and

population were important factors affecting the quantity and composition of solid waste. The study

shows that grass, yard wastes and newspaper were positively correlated to the level of income

(Richardson et al. 1978). The present paper attempts to apply these models in the context of

developing country like Nepal with some modification.

1.3 Objectives:

The objectives of this paper are to discuss household behavior regarding waste generation and

management of waste; the relationship of the waste component in different zones within the city;

and the “willingness to pay” for changes in the provision of waste management services.

1.4 Methodology:

The study was conducted using primary information. Information from households was collected

using a structured questionnaire. The Kathmandu Metropolis is divided into 35 wards. Wards are

not homogenous but heterogeneous in terms of population density and land use patterns.

1.4.1 Selection of Areas and size of the Sample:

All the wards can be categorized into three main groups i.e. Core, Middle and Outer depending on

population density, settlement and land use pattern. 5 wards (15%) out of the 35 were selected for

field study. To make the sample more representative, wards were selected in such a way that they

covered all the zones i.e. Core, Middle and Outer. Thus, 3 wards from the core, 1 from the outer

3

and 1 from the middle zone were selected. Table 1 shows the detail regarding the selected wards

and size of the sample.

Table 1 Sample HouseholdsWard Total

households (Nos.)

Sample households (Nos.)

Total Households (%)

Area Covered by sample (Sq. km.)

Total Population

Population Density per sq. Km

14 3460 173 05 3.03 18425 6080.9

18 775 41 05 0.19 8081 42531.6

19 1122 57 05 0.16 7588 47425.0

28 385 31 08 0.07 5077 72528.6

35 2486 130 05 3.95 12000 3038.0

Total 8228 432 05.25 7.4 51171 6915

Total population data is as per the census of 1991.

About 5% of the households were selected from among the households of the selected wards. Thus

in total 432 households were selected from the selected 5 wards. The households were selected

randomly with the help of the voters’ list. Attempts were made to cover the entire locality within

the ward.

1.4.2 Justification of the Sample Size:

To depict the reliability of the overall situation of the population, the selected sample should

contain a sufficient number of households. Therefore, to reduce costs, simplify management and

control of the quality of the interviews, the sample size was kept within reasonable limits. In order

to ensure representative views, each household was provided an equal opportunity to be selected in

the sample.

Sampling Error (SE): SE is the error inherent in making inferences for the whole population from

observing only some of its members. It is considered as a guideline as to what the sample size

should be, in order to guarantee a maximum given error when estimating a proportion from the

sample.

For a pure random sample drawn from an infinite population, the following formula has been taken

as the basis for computing the sample size;

n = k2 p (1-p)/e2

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Where, p is the value of the proportion in the population, e is the acceptable error and k is a

coefficient dependent on the confidence level for = 0.95 ( i.e. " 95 % confidence level”) k =

1.96. The term p(1-p) is maximum for p = 0.5. Then the formula becomes:

n = 0.9604/e2

Thus, to achieve a maximum error of 0.05 (5%) in the estimation of proportion, n = 0.9604/05 2 =

384. Therefore, a minimum sample size of 384 households is required.

1.4.3 Data Collection Method:

The name and number of the household head was collected from the final voters’ list of 2000 for

the 5 selected wards. After preparing the list of the household head sample households were

selected randomly using the random Table. The information from the household was collected with

the help of a structured questionnaire. The questionnaire was finalized after a pre-test. The pre-test

was made in ward no. 14 with 5% (25) of the sample households. The result of the pre-test was

presented in a closed door meeting with the team of University Professors. The questionnaire was

finalized incorporating all the suggestions provided by the Professors. The questions were on

demographic characteristics of the households, information on waste generation by types, waste

disposal practices (e.g. throwing in street, river, burning etc.), door-to-door collection systems,

monthly fee, and willingness to pay for the better management of waste and causes for not willing

to pay. Family income, sources of income, education level, and possession of domestic amenities

were also among the questions asked.

The questions were filled by visiting the selected households from August to November 2001. The

households were visited twice to complete the questionnaire. On the first day socio-economic

information were collected and households requested to deposit the wastes in different plastic bags.

On the next day the wastes were weighted. Three research assistants (one from each zone) were

employed for the work.

1.4.4 Analytical Method:

The data were entered in the computer and analyzed using different statistical tools. Data were

grouped for the Core, Middle and Outer zones. Some of the information was analyzed using simple

statistical tools and others analyzed econometrically. The econometric models used for the analysis

of household behavior and Willingness to Pay is given in the relevant sections.

5

2. MAJOR FINDINGS OF THE STUDY

2.1 Waste Generation in the Households:

The table 2 shows that average waste generation by the households is 0.29kg per capita per day

(0.26kg in the core zone, 0.32kg in the outer zone and 0.29kg in the middle zone). Waste

generation is higher in the outer zone and lower in the core zone. This may be due to the sufficient

open spaces available in the surroundings of the outer zone. In the core zone people have no space

and so they may be generating less waste.

Table: 2 Per Capita Waste Generation by the households

Zone Waste generation (Kg./ HH /day )

Std. Dev. Min Max Total waste ( Kg.)

Per capita waste generation in a day (Kg.)

All zone 1.91 1.27 0.33 9.15 824.14 0.29

Core Zone 1.98 1.26 0.53 9.15 255.63 0.26

Middle

Zone

1.85 1.28 0.33 6.99 320.43 0.29

Outer

Zone

1.91 1.28 0.51 7.63 248.1 0.32

The percentage of people following the separation practice is also very high in the core zone as

compared to other zones (Table 4). This may also be responsible for the low waste generation in the

core zone.

Table 3 shows about the types and proportion of solid waste. Kitchen waste is the major waste in

terms of volume and quantity of the selected households. It accounts for nearly 85% of the total

waste. Packing waste (7%) is next to kitchen waste. Plastic content is 3% whereas paper waste is 2

% only. The remaining 2% are other wastes, which include battery, dust etc.

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Table: 3 Types of Waste and their Proportion in all ZonesWaste types Average per

HH per day

(Kg.)

Std. Dev Min Max Total waste

(Kg)

Per Capita

Waste per day

(Kg.)

Kitchen waste 1.63 1.01 0.30 8.5 703.8 (85) 0.24

Packing waste 0.14 0.26 0 3.02 59.85 (7) 0.02

Plastic 0.14 0.26 0 2.05 22.71 (3) 0.01

Paper 0.04 0.13 0 2 16.27 (2) 0.01

Other Waste 0.05 0.22 0 3.02 21.57 (3) 0.01

Total Waste 1.91 1.27 0.33 9.15 824.14 (100) 0.29

Figure within brackets indicate percentage

2.2 Existing Waste Management Practices

2.2.1 Separation Practice

Table 4 shows about the separation practices of the sample households. Among the sample

households, only 31% of the households reported having separate bins for storage of different types

of waste and the remaining households do not have any separate bins. Thus the majority of the

households leave their mixed wastes at one place or in plastic bags. Though only 31% households

have separate bins, about 65% separate the reusable and recyclable wastes. Among the zones the

households having separate bins is the highest (49%) in the middle zone, lowest (7%) in the outer

zone and moderate (32%) in core zone. The separation practice is the highest (81%) in the core

zone, lowest (52%) in outer zone and moderate (62%) in middle zone.

Table 4: Separation Practices of the HouseholdsZones Separate bin Separation practice

Yes No Yes No

All zones 135 (31) 297 (69) 280 (65) 152 (35)

Core 41(32) 88 (68) 105 (81) 24 (19)

Middle 85 (49) 88 (51) 107 (62) 66 (38)

7

Outer 9 (7) 121 (93) 68 (52) 62 (48)

Figures within brackets indicate percentage and absolute number indicate the number of households

2.2.2 Door-to-Door Collection:

About 57% of the households are served by the door-to-door collection system. The majority of

them receive the service by paying the fee and few are receiving the service not because of the fee

but because of the location of their house along the road. Municipal collectors provide the service

without receiving any bonus since they are the employees of the municipality.

Table 5: Door-to-Door Collection and Disposal of WasteZones Satisfied with the present collection system Environmentally safe disposal of the collected

waste

Total No. of HH

with Door to Door

Collection

Satisfied Not

Satisfied

Yes No Don't know

All zones 245 (100) 207 (84) 38 (16) 18 (7) 46 (19) 181 (74)

Core 87 (100) 77 (88) 10 (12) 13 (15) 7 (8) 67 (77)

Middle 116 (100) 103 (89) 13 (11) 4 (3.4) 26 (22.4) 86 (74.2)

Outer 42 (100) 27 (64) 15 (36) 1 (2) 13 (31) 28 (67)

Absolute number indicate the number of households and Figure within bracket indicate percentages

The perception of the households towards the present collection system was also captured through

the questionnaire. Table 5 shows that most households (86%) were satisfied with the present door-

to-door collection system. Only 14% were not satisfied. However, very few households (25%)

know where the collected waste is disposed. Only 7% feel that the disposal of such collected waste

is environmentally safe, 19% feel that the disposal of such collected waste is not environmentally

safe and the remaining 74% could not explain whether it is environmentally safe or not (Table 5).

Table 5 also shows the zone-wise details regarding the knowledge on the disposal of the collected

waste. The percentage of unsatisfied households is higher in the outer zone relative to the core and

middle zones.

2.2.3 Waste Collection and Collectors

About 56 % households are served by the door-to-door collection system. Among them 35 % use

the municipal collection system and the remaining uses the private collectors including community-

8

based organizations. Table 6 shows the detail regarding the waste collection and collectors in the

sample households. Among the zones, municipal collectors are collecting wastes in the core area

whereas NGOs plays dominant roles in the middle zone and a private firm is working in the outer

zone. The majority of the private collectors collect the waste 3 times a week and municipal

collectors collect the waste every day.

Table 6: Waste Collectors and Collection Frequency Zones Collectors Collection Frequency in a week

Municipal

collectors

Wage

Workers

NGO CDC Pvt 0 2 3 4 6 7

All

zone

87 (35) 4 (2) 91

(37)

17 (7) 46

(19)

187

(43)

4 (2) 142 (58) 4

(2)

10

(4)

85

(34)

Core 79 (91) 4 (4.5) 0 0 4

(4.5)

42

(33)

3 (3) 2 (2) 0 9

(11)

73

(84)

Middle 8 (7) 0 91

(78)

17

(15)

0 57

(33)

0 99 (85) 2

(2)

1(1) 14

(12)

Outer 0 0 0 0 42

(100)

88

(68)

0 42 (100) 0 0 0

Where, CDC=Community Development Committee and Pvt.= Private, NGO= Non-Government Organization

Absolute number indicate the number of households and Figure within brackets indicate percentages

2.2.4 Management of Waste where no door to door collection

Among the households surveyed about 43 % do not have door-to-door collection system. Table 7

shows the detail regarding management practices of sample households. Households that are not

practicing door-to-door collection are managing their waste in different ways (e.g. burying in their

own land, composting and burning).

Table 7: Waste Management in households, which have no Door-to-Door Collection System

Management Practices Total Number of

HH

Core Middle Outer

Total No of HH with No door

collection system

187 42 57 88

9

Throwing in the Container 18 (4) 4 (8) 7 (5) 7 (3)

Throwing in the road 69 (16) 25 (50) 22 (14) 22 (10)

Throwing in open field 55 (13) 8 (16) 23 (15) 24 (11)

Burying in own land 92 (22) 4 (8) 36 (24) 52 (24)

Prepare the compost from waste 45 (11) 3 (6) 22 (14) 20 (9)

Cattle feeding 8 (2) 0 5 (3) 3 (1)

Burn 109 (25) 4 (8) 35 (23) 70 (32)

Throw in the river 28 (7) 2 (4) 3 (2) 23 (10)

Total no of HH with different

practices

424 (100) 50 (100) 153 (100) 221 (100)

Absolute number indicate the number of households and Figure within brackets indicate percentage

2.3. Waste Generation and its Relationship with Socio-Economic Variables

This section, mainly discusses the empirical analysis of the relationships of quantity and

composition of household solid waste to selected social and economic variables. The analysis is

based on data for components of household wastes, by type of material judged having recycling

potential.

2.3.1 Model, Hypothesis and Data

Normally waste is a function of consumption. The relationship between waste and consumption

activities may be expressed as (Richardson et al. 1978):

W=C

Where,

W = vector of components of solid waste

= Vector of technical waste transformation coefficients relating the types and quantities of solid

waste to each consumption activity

C = is a vector of consumption activities selected by the household.

Any particular waste may be generated by the consumption of more than one commodity. Here no

attempt is made to identify the technical waste transformation coefficients associated with the

10

individual products. It mainly tries to compare the relationship between different types of waste

generation and socio-economic variables affecting the quantity of waste.

The major determinants of household consumption activities are assumed to be household monthly

income (TOTI), size of the household (TOTPOP), educational status of the household (GRAD) and

extra land area in the house compound (EXTLA). The model for the waste component is:

TOTW = 0 + 1TOTI + 2TOTPOP + 3 GRAD + 4 EXTLA+5 CS+e

Where:

TOTW = quantity of waste per household per day (Kg)

TOTI= Monthly income of the household (Rs.)

TOTPOP= Household size (numbers of persons)

GRAD= Educational status, (number of college graduates)

EXTLA = Extra land area within the compound of the selected household (ha.)

Here household is assumed as a production unit producing solid wastes.

The hypothesis is as follows:

1. Increase in income is expected to increase the demand for convenience factors and services

embodied in commodities. The sign of the coefficient is expected to be positive for all

types of waste.

2. A larger household size is expected to generate higher quantity of waste since more

households are included in the unit; thus, the sign is also expected to be positive.

3. Educated household members work in the office and stay outside of the house for a long

time. So the waste generation will be low. However, the generation of packing waste may

be higher in case of a fully employed family as they have less time to prepare food. As

such, they consume more packed food.

4. It is assumed that higher the extra land area within the compound (EXTLA) less the waste

generated by the household. It is also assumed that the household with extra land area may

dispose some of the waste in their land, which may not be counted in the total volume of

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waste generated. Thus extra land area and the total quantity of waste are inversely related

and the sign of the coefficient of extra land area will be negative.

Data for the analysis were collected from the 432 households in 2001. Attempt has been made to

cover all the area within the city i.e. the data will represent the core, middle and outer settlements.

To calculate the quantity of waste sample households were given plastic bags and requested for the

collection of waste in these bags and the waste was weighed the next day.

2.3.2 Equation Results:

The estimated coefficients, coefficients of determination (R2), adjusted for degrees of freedom

(R¯2) and t and F values are shown in Table 8.

Table 8: Relationship of Waste and Socio-Economic Variables by Zones

Waste

Component

Intercept Household

Income

(TOTI)

HH size

(TOTPOP)

Extra

land

(EXTLA)

Education

(GRAD)

DW R¯2 F

TOTW (all

zones)

-2.70

(7.6)

0.26 (6.24) 0.49 (8.5) 0.08

(1.58)

-0.14(2.7) 1.8 0.25 38

TOTW

(Core)

-2.19

(-3.8)

0.19 (2.79) 0.52 (5.8) -0.84

(-1.9)

-0.03

(-0.37)

2.0 0.38 18

TOTW

(Middle)

-2.7

(-3.6)

0.26 (3.04) 0.50 (5.5) 0.04

(0.47)

-0.32

(-3.72)

1.7 0.27 16

TOTW

(Outer)

-3.87

(-6.2)

0.41 (6.08) 0.38 (2.79) 0.09

(1.04)

0.05

(0.58)

2.0 0.27 13

Figure within bracket indicate 't' value

Table 8 shows that generation of waste is related to the total income and total population of the

household. The elasticity of the household size is higher relative to the elasticity of the total income

in all the zones except outer zone. However, the elasticity of income is higher than the elasticity of

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the household size in the outer zone. Extra land area has positive but insignificant effect in all the

zones except the core zone. In the core zone as there are very few households with extra land area,

the result will not be useful in the analysis.

2.4 Economics of Solid Waste Management

2.4.1 Willingness to Pay

One of the features of the questionnaire was to find out the "willingness to pay (WTP)" of the

residents for the management of waste. The majority of them do not care on the final disposal of the

waste. Table 9 shows about the participation in fee collection system and their willingness to pay.

About 49 % households participate in the fee based collection system and are paying an average of

Rs. 60 per month for collection of their wastes. However, the participation rate is different for

different zones. About 67 % are participating in middle and core zone, while in the outer zone the

participation is only 32 %. Forty seven percent households are ready to pay for the better

management of waste and the average amount of WTP is Rs. 57 per month.

Table 9: Participation in Fee collection system and willingness to pay

Zone People actually participating the fee collection system

People ready to pay and amount of willingness to pay

Total WTP which includes Willingness to additional pay and the monthly fee

Number of HH

Average fee in Rs.

Tot. Ave

Number of HH

Average wtp in Rs.

Tot Ave

Number Average Amountin Rs.

Tot. Ave

All

Zone

213 (49) 60 30 202 (47) 57 27 336 (78) 72 57

Core 87 (67) 23 16 89 (69) 60 41 111(86) 66 57

Middle 116 (67) 67 45 47 (27) 51 14 136 (79) 74 58

Outer 42 (32) 74 24 66 (51) 57 29 89 (68) 77 53

Figure within brackets indicate percentage

Here too the zone wise situation is different. The majority of the households who were paying fees

for the collection of waste were ready to pay only the amount, which they were paying, as they did

not find any problem regarding collection of their waste. Those who were not participating in the

fee collection system were also ready to pay only near about the fee amount, which their neighbors

were paying. The total willingness to pay is the amount of the actual fee and the amount of

willingness to pay since the question was about the willingness to pay over and above the existing

13

fee for the better management of the waste. About 78 % of the sample households are willing to

pay for the management of the waste and the average amount is Rs. 72 while the amount is Rs. 66

in the core, Rs. 74 in the middle and Rs. 77 in the outer zones.

The average value of the Total willingness to pay is not equal to the sum of the average values of

the fee and willingness to pay. The households who are willing to pay are mainly those who are not

participating in the fee-based door-to-door collection system. However, they were questioned on

the additional willingness to pay for the better management of the waste and some have expressed

the willingness to pay. Some expressed that they could not pay more than the present fee. Thus, the

average figure is calculated by dividing the applicable number of households and not all the

households. Table 10 shows the total average. The average total willingness to pay is only Rs. 57.

The average total fee is Rs. 30 and the average amount of willingness to pay is only Rs. 27.

While asking the question, the WTP amount was started from Rs.50 but some of the households

gave very low figures as their WTP for the waste management. In the core city area the municipal

collection system is regular but still the households are willing to pay only a small amount for the

collection of their waste. Normally, the municipal employee themselves collect the waste and get

nominal amount as tips from the house owners.

In the fee structure, households who are paying fees below Rs. 25 are mainly the residences of the

core city area. They pay a very small amount of fee for the collection of the waste to the municipal

employee. The municipal employees are also happy as they get an extra bonus.

The number of the households having door-to-door collection system is slightly higher than the

number of households participating in the fee-based door-to-door collection system. It is because

the core city households have reported that they have door-to-door collection system but are not

paying any fee as they live very close to the collection point.

2.4.2 Willingness to Pay and its Relationship with Other Variables:

A regression analysis was made with the help of the SPSS window program. "Willingness to Pay"

was regressed with the Total Income of the household (TOTI), time required to reach the municipal

collection center (TTR), extra land area around the house (EXTLA), and the collage graduate

people (GRAD). Consciousness Training (COTR) was taken as a dummy variable. Certain

hypothesis was made regarding the coefficient of the independent variable.

The hypothesises are:

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1 TOTI will positively affect the Willingness to Pay (TWTP) i.e. higher the income higher

will be WTP for better management of the waste

2. TTR will also positively affect to WTP i.e. more the time needed for the disposal of waste

at the free collection center, higher the WTP for the collection and safe disposal of the

waste

3. COTR will also positively affect to WTP i.e. as people are more conscious regarding the

bad effects of haphazard disposal they are ready to pay more for waste management.

4. EXTLA will be negatively related to WTP, i.e. higher the land area around the house,

lower will be the Willingness to Pay for waste disposal since people may use their waste as

a soil conditioner in the kitchen garden.

5. GRAD will also positively affect to the Willingness to Pay, i.e. educated people will be

cautious about the negative effects of haphazard waste disposal and are ready to pay for

better management of the waste.

6. The total quantity of the waste (TOTW) also has a positive relationship with WTP i.e.

higher the quantity of waste; higher will be the Willingness to pay for the collection and

management of the waste.

2.4.3 Willingness to Pay and its Relationship with Socio-Economic Variables

The regression results are presented in Table 10. The result of Equation 1 shows that Willingness

to Pay is positively related to the total income. The coefficient of income is positive (0.28), which

means that for a 100 % increase in income the WTP will increase by 28 % or to put it in another

way, the elasticity of WTP with respect to income is 0.28. The time needed to throw the waste in

the public collection point has also a positive and significant relationship with the Willingness to

Pay. Greater the time required for throwing the waste, greater the amount that people are willing to

pay for better management of the waste. The coefficient of time is .09, which shows that a 100 %

increase in time will cause 9 % increase in the Willingness to pay for better management of the

waste. Graduate (GRAD) shows a positive relationship with WTP though it is very insignificant.

Households having extra land areas have positive but insignificant effects. During the survey, it

was found that the majority of the rich households have extra land area and they mainly want to

throw the waste even if the organic content is high (see Eq. No 1 in Table 10). Similarly, COTR is

negative, which is also contradictory to the assumption (hypothesis). It may be because of the low

quality of the training. In the survey it was considered that those who have attended any program,

15

which simply discussed about the waste management or environmental issues, was considered as

consciousness training. The training was mainly by NGO or clubs, which were mainly motivated to

make the households participate in the fee-based collection system. Thus the quality of the training

may not be as desired and as such, it may not be able to have a positive effect. The total explained

portion of the adjusted R2 is 0.31 and F value is above 8 and is highly significant. The Durbin-

Watson Test is 1.69.

Table 10 Willingness to Pay and its Relationship with other VariablesEq.No Dep.

VariableIndependent Variables R 2 F dw

Const Toti Grad Ttr Extla Cotr Totw1 TWTP 1.86 0.28 0.03 0.09 0.01 -0.17 - 0.31 8 1.

62't' value 4.95* 0.4 2.46* 0.38 -2.35**

2 TWTP 1.59 0.28 0.02 0.07 -0.001 - - 0.27 8 1.45

't' value 4.75* 0.256 1.96** -.036 - -3 TWTP 1.62 0.35 - 0.06 0.05 - -0.11 0.14 7 1.

54't' value 5.31* - 1.31 1.33 - -1.91**

4 TWTP 1.45 0.25 0.39 0.11 -0.04 - - 0.32 4 1.55

't' value 2.44* 1.32 2.16** -0.96 - -* Significant at 99 % level of significance** Significance at 95% level of significance

If one variable is dropped i.e. variable COTR, the regression result is shown in Equation 2, Table

10. The total income and time needed to reach the municipal collection center are significant and

land area other than house and education has an insignificant effect on the Willingness to Pay.

An attempt was made to see the relationship of total waste and total willingness to pay. If we look

at the regression result after adding total waste (TOTW) as an independent variable, it shows a

negative relation with Willingness to Pay. This shows that the volume and quantity of waste have a

very low effect on the Willingness to Pay. It seems to be true in this context since the ability to pay

is very important for the Willingness to Pay. The rich people may be generating low volume of

waste and the poor may be generating high volume of waste since waste volume/quantity is highly

related with the size of the population (Equation 3, Table 10).

An attempt was made to see the relationship between wealth and the Total Willingness To Pay

(TWTP). The possession of different assets was taken as the proxy for wealth. The possession of

only a TV is considered as a poor household and the possession of a car, computer, motorcycle,

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refrigerator etc. by households were considered rich and households between these are considered

as middle-income groups.

Thus, regression was made with the households who possess only a TV. The Equation No. 4 (table

10) shows the relationship of TWTP and the independent variables in case of those households,

who possess only a TV.

The regression result shows that Total Income (TOTI) and Time required to dispose the waste at

the public collection center (TTR) have positive relations with TWTP as hypothesized and are

highly significant. Here extra land area has a negative coefficient, which indicates that poor people

use their waste in the kitchen garden as a soil conditioner and are not willing to pay for waste

management. The total explained portion of the regression (i.e. adjusted R2) is 0.32. The value of F

is around 4 and highly significant (Equation 4, Table 10).

2.4.3 Relationship of WTP with Other Variables in Different Zones

The zone wise relationship of WTP with the variables is presented in table 11. The regression

results show that in the outer zone the extra land area has a negative effect on TWTP. It shows that

greater the extra land area, more the waste is used as compost and low willingness to pay for waste

management. Total income, time to dispose the waste and the number of graduate members in the

house have significant positive relations with the willingness to pay which are as hypothesized.

However, extra land area has a positive relation with the willingness to pay in the core and middle

areas. In the core area the households with extra land area are very low in number (about 12 %). In

the core area, extra land area does not mean the availability of a kitchen garden. The land is for the

car parking or for the chouk2.

Table 11 Willingness to Pay and its Relation with other Variables by Zones

Zone Dep. Var Adj.R2 DW F Const Coefficient of Independent VariableLEXTRA LTTR LTOTI LGRAD

Total LTWTP 0.27 1.45 8.6 1.59 -001 0.07** 0.28* 0.02

Outer LTWTP 0.57 0.99 25 -0.12 -0.05 0.10 0.47* 0.03

Core LTWTP 0.62 5 2.94 1.29* 0.34** 0.52* -0.73*

Middle LTWTP 0.25 1.95 2.85 2.77 0.01 0.03 0.16** 0.19**

* Significant at 99 % level of significance

2 Chouk is an open space between few houses in the core city area.

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** significance at 95 % level of significance

Thus, the waste will not be used in the extra land area and may not be true for our assumption. In

the middle area also, the coefficient of the variable extra land area possesses the positive sign

against the hypothesis. It may be because the area is very small and used for other than kitchen

garden purposes. As such the waste may not be used in the extra land as compost, but rather prefer

to through the waste out. The coefficient of the graduate people has a positive sign in all cases

except for one case of the core area. Though the value is insignificant, it indicates that though

people are college graduate they do not take the case of waste management seriously. It also may

be because the respondent may not be a college graduate even if the house members are graduates.

Thus, though many household members are college graduates, they do not care about waste

management. One of the reasons of unwillingness to pay may be because they feel the waste

management problem is not their problem. They may feel that it is the duty of the municipality,

since the municipality has managing it for a long time without any fee charged to the generator.

2.4.4 Causes of Not Willing to Pay

Questions were asked regarding the unwillingness of the households to pay. Households have given

more than one reason for not willing to pay for the management of the waste. Table 12 shows that

the majority of the households (53%) were not willing to pay as their waste was collected and they

do not have any problems from the waste. Some (21%) of them do not feel the problem from the

waste since they have sufficient space to throw the waste either within their compound or outside.

Few households were not ready to pay, as their income was very low. They account for only 12 %

among the unwilling households (8 % of the total surveyed households). They feel that their

priority is hand to mouth survival and not the waste. Very few households feel that it is the duty of

the municipality and the government and so they are not willing to pay.

Table: 12 Causes of not willing to payCauses Total Number of

HHCore Middle Outer

It is the duty of the Municipality 14 (5) 1 (2) 6 (4) 7 (8)

It is the duty of the government 2 (1) 0 2 (1) 0

Income is very low and could not afford 35 (12) 6 (12) 7 (4) 22 (25)

My house's waste had not made any

problem to me

62 (21) 8 (17) 28 (17) 26 (30)

Waste collection is continue in one or

other way and no other problem

158 (53) 31 (65) 103 (64) 24 (28)

Volume and quantity is very low 7 (2) 2 (4) 1 (1) 4 (4.5)

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Majority of waste is reusable and

applicable to own self

19 (6) 0 15 (9) 4 (4.5)

Absolute number indicate number of households and Figure within bracket indicate percentage

3. SUMMARY AND CONCLUSION

The per capita waste generation is 0.29 kg./person/day in all the zones of the city. It seems to be

slightly lower than that of the earlier studies (0.46-0.5 kg./person/day) (Rai, 1990; RESTUC, 2000)

and higher than the recent study of the Municipality. Recent study by Kathmandu Metropolitan

City also shows the low rate of waste generation (0.225 kg./person/day) (KMC/KVMP 2001). The

low per capita waste generation may be due to the increase in household sorting of paper and

bottles at the point of generation since they are easily sellable. The per capita waste generation is

found to be the lowest in the core zone and highest in the outer zone. It was also found that

segregation practices are the highest in the core zone relative to other zones. Thus, the low per

capita waste generation in the core zone may be due to the household sorting of waste more

intensively in the core zone than in other zones. This may also be true because the core zone people

have been facing the waste problem since a long time whereas the outer and middle zone people

have open space and have no problem of waste disposal. Thus, as there is more open space people

usually generate more and vice versa.

About 57 % households are participating in the door-to-door collection by paying certain fee.

However, people are not much aware of the environmental problems and safe disposal of the waste.

It still shows that the households of Kathamndu have the feeling of NIMBAY (i.e. not in my

backyard). About 75 % of the city people do not know where the collected waste is disposed. In

terms of zones, people living in the core zone seem to be less aware than in other zones. This shows

that people are conscious regarding the waste problem within their compound but they do not care

where and how the waste is disposed. Few people know about the disposal place of the collected

waste. However, those who know the disposal site do not know whether the disposal practice is

environmentally safe or not.

More than 90 % of waste collectors are municipal workers in the core zone where as their

proportion in other zone is negligible. In the middle zone it is a NGO (SILT Environment), which

covers 78 % of the households practicing door -to-door collection, and a private firm is collecting

waste from the outer zone.

19

In the core zone households, which are not participating in the door-to-door collection system, are

managing their wastes mostly by throwing it on the streets. Whereas in the middle and outer zones

the majority households are managing their wastes either by burying or burning on their land. They

also prepare compost within the compound.

The waste component relationship shows that size of the household and income are the major factor

determining the total quantity of the waste in all the zones. It was also found that education has a

negative effect on waste generation.

About 80 % of the households are willing to pay for the better management of waste. The average

amount of only households who are Willingness to Pay is Rs. 72 per month. However, it we take

the average of all the households WTP is Rs. 57 per household. The willingness to pay is highest in

the outer zone and lowest in the core zone. It may be due to the free3 collection by the municipality

that the core people are not willing to pay. However, in the middle and outer zones the municipality

rarely collects the waste. Thus the willingness to pay is higher in outer and middle zones and lower

in the core zone. Again the environmental awareness of the households seems to be very low and

due to this they are willing to pay for environmentally safe land filling. However, they simply want

the waste to be out from their house. They are ready to pay only for this. Thus, the average

willingness to pay seems to be lower than that of the cost required for the management of the waste.

The Willingness to pay is also positively related to the household income and household size.

Most households feel that the lack of stiff penalty and non-execution of law is the basic problem for

the effective management of waste. Thus, provision of strong penalties and effective execution of

the law will be the major tool to reduce the problem of solid waste management in Kathmandu. It is

found that environmental awareness is very low among the residents of Kathmandu. Thus, stringent

regulations with environmental awareness programs for household sorting and composting can

reduce the volume and quantity of waste for land filling. It could be suggested that a fee be charged

as per the electricity or water bill to the households to cover the costs, since the willingness to pay

is positively related to the level of income. At the initial stage only regular direct cost should be

covered by the charge and fixed cost as well as environmental costs should be subsidized. Other

wise there will be the possibility of illegal dumping. After the successful implementation of this

scheme then only full cost pricing of the solid waste generation should be initiated and this will be

the only sustainable way for the better management of waste of Kathmandu Metropolis.

3 In the core zone the area coverage by the ward is very small and the municipality with some subsidy collects the waste by its tractors along the road and majority of the households are covered. Where as in middle and outer zone the area coverage by the ward is high and municipality rarely collects the waste from the door of the households.

20

21

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