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Vol. 13(9), pp. 354-364, September 2019
DOI: 10.5897/AJEST2019.2681
Article Number: 41AC78261637
ISSN: 1996-0786
Copyright ©2019
Author(s) retain the copyright of this article
http://www.academicjournals.org/AJEST
African Journal of Environmental Science and
Technology
Full Length Research Paper
Household perception and willingness to pay for
improved waste management service in Mamfe,
Cameroon
Veronica Ebot Manga1*, Oru Thompson Oru1 and Martin Ngwa Ngwabie2
1Department of Environmental Science, Faculty of Science, University of Buea, Cameroon.
2Department of Agricultural and Environmental Engineering, College of Technology, University of Bamenda, Cameroon.
Received 21 March, 2019; Accepted 25 June, 2019
Lack of financial resources and public participation are major factors that constrain solid waste
management in many towns in developing countries. This study sought to determine the willingness to
pay (WTP) and the perception of the inhabitants of Mamfe, Cameroon for an improved solid waste
management system. A total of 371 households were interviewed and data analysis to identify the
determinants of WTP values was performed using multiple regression models (Probit and Tobit) and
Contingent Valuation Method. Approximately 95.1% of the residents were concerned with the problems
of solid waste management. 51.5% were satisfied with the present environmental conditions; with 74.5%
of the opinion that water pollution caused by poor waste disposal presented the most serious
environmental problem. Most of the respondents (85.1%) showed a positive attitude towards WTP for an
improved solid waste management system. The monthly mean WTP was 1000FCFA ($1.73) per
household and the annual WTP was approximately 180 million FCFA for the entire town. Regression
analysis revealed that age, employment type, gender and income of the respondent have a significant
relationship with willingness to pay at p<0.05. The trend of WTP and income variables (income and type
of employment) was negative and significant implying that this payment could be afforded by a cross
section (low, middle and high-income levels) of the population.
Key words: Cameroon, contingent valuation method, household, perception, solid waste management,
willingness to pay.
INTRODUCTION
Pacione (2005) alludes to the fact that the provision of
waste management services in any large city is an
expensive undertaking that makes huge demands on the
finances of local governments. Apart from making
investments in capital equipment, money is also required
for the day to day operational cost of the service in the
procurement of fuel, spare parts and working gear
(Boateng et al., 2016). Cameroon is ranked in the 144th
position out of a total of 177 countries and it is one of a
group of 20 countries for which the Human Development
Index (HDI) worsened between 1990 and 2006 (UN
2006). Cameroon only achieved one of the seven goals
*Corresponding author. E-mail: ebotmangav@gmail.com.
Author(s) agree that this article remain permanently open access under the terms of the Creative Commons Attribution
License 4.0 International License
on target: access to improved safe water (Parrot et al.,
2005). The nation is considered a lower middle-income
country with a gross national income per capita of
US$1,320 in 2015, compared to an average of US$1,628
for all sub-Saharan African countries. The minimum wage
is approximately FCFA 36 000/month or $72 (National
Institute of Statistics, 2018) with 37.5% of the population
living below the national poverty line, and 27% below the
international poverty line of US$1.90 per day (World
Bank, 2017). Most of the population have limited access
to sanitation services, especially the poorest who live in
areas with little infrastructure. Concerning the disposal of
solid waste, the government covers 85% of the financial
costs for the management of solid wastes for the major
cities (most of them serving as regional headquarters)
from the state budget and the Councils cover the
remaining 15% (Ymele, 2012). This policy further
deepens the spatial disparities between urban and rural
areas. It is common for both residents and Council
authorities in towns to dump waste of all sorts into
roadsides, vacant lots, marshlands and water courses.
This practice is associated with unsustainable and
unplanned urban development and can give rise to air
pollution, water pollution, poor sanitation and housing-
related health risks. Uncollected and illegally or
improperly disposal of wastes poses serious risks to
public health and the environment (Wilson et al., 2003;
Olley et al., 2006).
Previous studies on waste management in Cameroon
have focused on technical aspects such as collection,
treatment, disposal practices and their environmental
implications (Vermande and Ngnikam, 1994; Ngnikam,
2000) and the legislative and regulatory aspects (Manga
et al., 2008); with little attention on the financing of solid
waste management. Municipal solid waste management
is financed from three principal sources; taxes and
revenues generated by Council activities, supplementary
budgets from the state and lending facilities from the
Government‟s Council Development Fund (FEICOM)
(Manga et al. 2008). Nationally, there is very little
exploitation of alternative sources of financing.
Public and private partnerships offer interesting
alternatives to MSW services, particularly in terms of
innovation (Ahmed and Ali, 2006). Non-governmental
organizations (NGOs) and Community-based
organizations (CBOs) operate in the informal sector and
considerably alleviate the burden of the urban poor in
African cities. They also operate in areas where the
official operators do not have access because of poor
road conditions. In a report on livelihood, the National
Institute of Statistics remarked that there is an opportunity
for NGOs and CBOs to implement garbage collection and
transfers to garbage bins operated by the official operator
Hygiène et Salubrité du Cameroun (HYSACAM) (INS
2002). Parrot et al. (2009) investigated some public-
private partnerships in urban solid waste management in
the city of Yaounde, Cameroon.
Manga et al. 355
According to Parrot et al. (2009), the main waste
service provider to the Yaounde Urban Council,
(HYSACAM), signed limited official public-partnership
with some small NGOs and CBOs (TAM–TAM mobile,
GIC–JEVOLEC, ERA–Cameroon and Sarkan
Zoumountsi) for the pre-collection of wastes from
selected, mostly upper class neighborhoods. The authors
report that some of these collaborations proved to be
fatal in the long term mainly as a result of lack of funding,
high membership costs and mis-targeted areas. Mckay et
al. (2015) identified inadequate organizational structure;
poor logistical support; lack of capital and technical
expertise; inhibiting government policy and regulations;
as well as low levels of awareness and education at the
household level as the main inhibitors of growth in this
sector. Mbeng et al. (2009) in their study reported that
although information and awareness campaign are
important drivers to behavior change in waste
management, these do not necessarily translate into an
increased participation in recycling or reuse initiatives
because other factors such as economic incentives can
hamper participation rate. These studies have so far,
explored issues related to the participation of the private
sector and public attitudes and awareness in the solid
waste sector; they do not however address residents‟
willingness to pay (WTP) for solid waste management.
The current study seeks to determine households‟
perception of solid waste management and the
willingness to pay (WTP) using the contingent valuation
method (CVM). This study carried out in Mamfe town
(Cameroon) is of significance to towns with limited
budgets that are interested in exploring user fees as
sources of financing for SWM services under current
privatization policy.
CVM uses survey questions to elicit people‟s
preferences for non-market goods by asking them how
much they would be willing to pay for specified
improvements or to avoid decrements in them (Mitchell
and Carson 1989). In its simplest form, the respondent is
offered a binary choice between two alternatives, one
being the status quo policy and the other alternative
policy having a cost greater than maintaining the status
quo. Debate over this method lies with issues linked to
validity and measurements (Carson, 2000). However,
despite these shortcomings, CVM has in recent years
been extensively used in both developed and developing
countries for valuation of a wide range of environmental
goods and services (Whittington, 2002). Examples of
recent application of CVM for solid waste-management
services in developing country contexts include Niringiye
and Omortor (2010), Wang et al. (2011), Amfo-Out et al.
(2012), Ezebilo (2013), Addai and Danso-Abbeam
(2014), Boateng et al. (2016). In these studies, the
socioeconomic and contingent variables found to
influence household WTP for solid waste management
included the payment amount, age, income, household
size, occupation, dwelling type and educational level.
356 Afr. J. Environ. Sci. Technol.
Figure 1. Map of Mamfe, Cameroon.
Addai and Danso-Abbeam (2014) used CVM to predict
the determinants to pay in Dunkwa-on-Offin, Ghana. The
results of the study reveal that willingness to pay for
improved solid waste management is significantly related
to level of education, gender, household size and age of
the household head. Niringiye and Omortor (2010) in
their study of the determinants of willingness to pay for
solid waste management in Uganda, using the CVM,
found that age influences willingness to pay.
MATERIALS AND METHODS
Study area
Geographically, Mamfe is situated at latitude 5.76° N, and longitude
9.28°E (Figure 1). Climatically, it is dominated by the Equatorial
climate with high rainfalls (3500-4000 mm) and high temperature
(30 -32°C). Mamfe is the capital town of Manyu Division in the
South-West Region of Cameroon. It is richly watered by River
Manyu with its tributaries at River Baku and River Badi which
serves as the fishing ground and major travels roads from the town
to Nigeria.
Mamfe is a traditional town characterized by the convergence of
surrounding (indigenous) villages linked to the main urban center by
new settlements with a population of 60,000. Arrey (2005) in a
study carried out within the Mamfe Council (Mamfe Rural Council
Monographic Study) classified the town into three sub-areas on the
basis of commercial versus residential activities, years of existence
and income levels. The three delineated areas are mixed in terms
of income groups. For example, there are some households of
high-income neighborhoods in the „indigenous‟ part of the town, as
well as individuals of low-income neighborhoods in the „government
residential area‟ part of the town.
Research design
The research adopted a mixed triangulation design. Stratified,
purposive and random sampling techniques were used to select
households for this study. Both primary and secondary data
sources were used. Questionnaire survey, interviews with key
personnel and observations were the main tools for data collection.
Both qualitative and quantitative methods of data analysis were
considered. Qualitative data played supplementary role and content
analysis of the ideas, opinion, and concepts of data were
considered. SPSS Version 21 was used for quantitative analysis of
data. Contingent valuation method was employed to elicit
household‟s willingness to pay for the proposed improvement in
solid waste management service. With an estimated total of 15,000
households, and on the basis of Yamane (1967)‟s sample size
formula, a sample size of 377 households was selected for the
survey. Household selection was a multi-stage process beginning
with stratification of households into three socio-economic strata:
high, middle and low-income groups based on the neighborhood.
This activity was facilitated by exploiting a spatial economic zoning
established by the Council (Arrey, 2005). A purposive sampling
based on the standard of housing infrastructure was used to
delineate income levels of households within the different income
zones.
The data collection was made by hand-delivered questionnaires.
Pre-test surveys were conducted in April in 10 randomly selected
households in a town outside the study area. People who had no
formal education were interviewed based on the questions in the
questionnaire, while people who had formal education were handed
a copy of the questionnaire (which were filled in the presence of
survey assistants). The focus groups, personnel of Waste
Management Board (the Hygiene and Sanitation Department
authorities of Council) and those involved during the pre-test
surveys contributed in the development of questions that were used
during the main survey. Following the pre-test surveys, some
questions in the questionnaire (e.g. presentation format for the
valuation question and independent variables) were adjusted to
reflect the concerns raised by survey assistants and respondents.
The main survey was conducted during the months of May and
June 2017.
Willingness to pay questions
The CVM was used to quantify each household‟s decision on
whether or not to purchase an improved provision of solid waste
management services. CVM is a type of stated-preference
approach that employs a hypothetical market system to extract
WTP or willingness to accept environmental goods (Carson, 2000).
The single-bound Dichotomous CVM was used to acquire the
necessary data for both WTP and the associated specific amount to
pay.
With the understanding of the market scenario, the respondents
were first asked if they will be willing to pay anything for the
improvement scenario presented. The response was either „yes‟ or
„no‟. If the respondent answered “no”, they were asked to give
reasons why they were not willing to pay for the improved service
and to state how they will properly manage their waste such that it
will not lead to environmental damage. A „yes‟ response to the
participating question was followed by the selection from a list of
monthly amounts they were willing to pay; (1) 500-1000 FRS; (2)
1000-1500FRS; (3) 2000-4000 FRS; and ≥5000 FRS. This was
followed by selection of options relating to time and frequency of
collection. The final question for those who answered „yes‟ was to
state the maximum monthly amount they will be willing to pay based
on their selected options in the later. Respondents were then asked
to state the maximum amount service charge (per month) they were
willing to pay to solve the household solid waste problem.
The respondents were asked a series of questions relating to
their perception of problems of solid waste and socio-economic
status (educational level, income, age, gender, house ownership
and other socio-economic determinants). The respondents were
asked about their participation in sanitary campaigns and
environmental concerns. Incorporation of individuals' socio-
economic variables into the CVM helped the researchers to gain
information on validity and reliability of the CVM results and
increase confidence in the practical application of results obtained
from the CVM empirical analysis (Haab and McConnell, 2002).
The empirical strategy
The main purposes of this study were to assess the residents‟
willingness to pay for improved solid waste management, the
amounts and obtain the determinants of WTP. In this regard, the
issue involved „‟yes‟‟ or „‟no‟‟ response, on one hand, and the
elicitation of specific monetary value for the yes responses; on the
other hand the calculation of mean WTP and the estimation of a
parametric model that includes respondents‟ socioeconomic factors
in the WTP function. Two models, that is Probit and Tobit were
used to analyze the WTP of household. Firstly, since we do not
know the random part of preferences and can only make probability
statements about "yes" or "no", we used the Probit model to
estimate the probability of WTP. Secondly, since the nature of the
decision problem for determining the WTP is unknown, the Tobit
model was used to identify the factors that determine how much the
respondents were willing to pay for improved waste management
services study.
Probit model
Despite its shortcomings, this model was found useful in this study,
since it was aimed at providing information to policy makers on the
possible interventions derived from the findings (1-3).
Manga et al. 357
i* = Xiβ + i (1)
Where i* is the unobserved dependent variable. is a parameter
of the model (the intercept and coefficients), Xi is an exogenous set
(independent) explanatory variables and i is the error term,
whereby:
i {0,²}
If an individual household i is willing to pay, i = 1 and otherwise i
= 0 (zero).
Mathematically, this is given by:
(2)
Wheni * = 1 then i = 1 implying the specific household is willing
to pay a positive price for the service. This probability that a
household would be willing to pay can be estimated by the Probit
model below:
(3)
Where; Yi is the dependent Variable (willingness to pay) taking a
value of 0 or 1.
Two categories of respondents were identified in terms of MWTP
values. The first category included respondents that: - (i) were not
satisfied with the current SWM services, (ii) considered SWM to be
the responsibility of the government authority and (iii) had low
income; and were expected or assumed to offer zero value for
improved SWM. The second category included those that were (i)
satisfied with the current SWM services, (ii) aware of the SWM
system in place and, (iii) in the high-income bracket; and were
expected to offer positive roughly distributed values. Since, the
dependent variable (MWTP value), was not totally observed (it is
censored at zero) and an OLS (ordinary least squares) estimator
cannot be applied, a Tobit model for the observed MWTP was
employed (Hagos et al., 2012).
Tobit model
The Tobit model identifies the factors that determine how much the
respondents are willing to pay for improved waste management
services. Tobit model for the observed maximum willingness to pay
(MWTP) is given in terms of an index function (4-6):
i = + X‟β + i (4)
That is,
MWTPi* = + X‟β + i (5)
MWTPi = MWTPi* if MWTPi* > 0
= 0 if MWTPi* ≤ 0 (6)
Where: i (MWTP*) is the dependent variable. In this case, it
captures the respondents‟ unobserved maximum willingness to pay
for improved solid waste management; MWTPi is a household‟s
actual maximum willingness to pay for improved solid waste
management; X' is vector of independent variables; β is vector of
coefficients; α is the intercept; and εi is disturbance term, which is
assumed to be normally and independently distributed.
Assuming that there is a perceived utility (i) for paying for
improved waste management services, and, a utility (0) for not
paying for improved waste management services, β is vector of
coefficients; α is the intercept.
MWTPi = + β1age + β2 gender + β3income + β4education +
358 Afr. J. Environ. Sci. Technol.
Table 1. Correlation matrix between independent variables.
Variable
Age
Educational
level
Type of
employment
Income
Gender
Age
Correlation
1
-0.54
-0.272**
0.319**
-0.161**
Sig
0.125
0.00
0.00
0.003
Educational
level
Correlation
-0.54
1
-0.089
0.132*
-0.40
Sig
0.125
0.104
0.015
0.466
Type of
employment
Correlation
-0.272**
-0.089
1
-0.540**
0.079
Sig
0.00
0.104
0.00
0.147
Income
Correlation
0.319**
0.132*
-0.540**
1
-0.129*
Sig
0.00
0.015
0.00
0.011
Gender
Correlation
-0.161**
-0.161**
0.079
-0.129*
1
Sig
0.003
0.003
0.147
0.011**
*Correlation is significant at the 0.01 level (2-tailed); ** Correlation is significant at the 0.05 level (2-tailed).
β5household-size+ β6type of house + β7house-ownership+
β8location+ β9sanitary inspector+ β10trust + i
(if MWTPi* > 0 = Otherwise (if MWTPi*≤ 0). (7)
Before the Probit model was applied to analyze the effect of
explanatory variables on WTP, a correlation matrix of the
independent variables was analyzed to test for the occurrence of
multi-collinearity among the exogenous variables. Multicollinearity is
a serious problem when correlation coefficient is 0.8 (Gujarati and
Porter, 1999). Begum et al. (2007) argue that a multiple regression
model with a correlation coefficient greater than 0.70 among any
two variables shows best in multi-collinearity. The correlation
between the variables did not exceed 0.8 (Table 1). This shows that
multicollinearity and collinearity are not serious problem in the
estimated model. Adjusted R² values and F-tests have been tested
for examining the theoretical validity of the CVM bids (Sumukwo et
al. 2012).
Choice of variables
The variables (Table 2) used in the Probit and the Tobit models
were based more on related studies by researchers as follows:
(i) Income. This variable refers to the monthly money income of the
household in terms of franc CFA. It includes the income of the head
of household from all sources. There is a general agreement in
environmental economics literature on the positive relationship
between income and demand for improvement in environmental
quality (Afroz et al., 2009). There are many studies which have
found that income is positively significantly related to the WTP for
improved SWM services (Padi et al., 2015; Maskey and Singh,
2017). Therefore, we expected the income to affect the willingness
to pay and its amount positively.
Like any other environmental and public good, whether
households are willing to pay or not for an improved solid waste
disposal, they are expected to be affected by various factors. Some
of these factors with their prior expectations are defined as follows:
(ii) Age of the respondent. This variable refers to the age of the
respondent in years. It is expected that the age of the respondent
will affect the willingness to pay negatively. This is because older
citizens because of their age make more mature decisions related
to evaluating health and environmental issues (Afroz et al., 2009).
(iii) Educational level of respondent: It is hypothesized that
education increases the individual‟s awareness and knowledge of
the consequences of improper solid waste management. Thus, it is
expected that the longer time in formal schooling (years), the more
individuals will be willing to pay for improved waste collection and
disposal. As such, educated will positively affect WTP (Sumukwo et
al. 2012).
(iv) Households‟ size. This variable refers to the number of
individuals in the household. In larger household members are
more aware of the risk involved with unhygienic practices and thus
crave for a better service by being more willing to pay for improved
service (Hago et al., 2012). It is also expected that with more
people in the household, there is likelihood for shared
responsibilities in executing domestic tasks and solid waste
management, rather than paying the Council to clean the
environment.
(v) Household ownership. Individuals living in their homes would
like to ensure that their surroundings are clean; this will improve the
value of their property. This is in contrast with those renting who do
not have any such interests. As a result, it is expected that those
living in their own houses will be more willing to pay for the
improvement as compared to their tenants (Hagos et al., 2012).
(vi) Type of house: This refers to the housing type in terms of
housing units and physical space. It is a variable that is sometimes
used to assess the physical space available to households. WTP is
expected to be higher for those who live in confined area like
flats/bungalows with limited compounds compared to those living in
detached houses with compound.
(vii) Type of employment: This variable is based on the employment
status (employer) and connotes aspects on the reliability of income.
It is expected that households with more secure employment will
show higher WTP for services; therefore, WTP decreases with
employment status (lower security). This variable is intricately linked
to household income.
(viii) Sanitary inspector: WTP for improved waste is expected to be
positive for those in areas with no environmental inspector and
negative for those in areas with the presence of environmental
inspector.
Manga et al. 359
Table 2. Description of explanatory variables used in this study.
Variable
Description
Unit of Measure
Gender (Nominal)
Gender of household head
(i) Male
(ii) Female
Age (Ordinal)
Age of household head
(i) <25years
(ii) 26-35
(iii) 36-45
(iv) 46-55
(v) ≥56years
Education (Ordinal)
Educational level attained by
household heads
(i) Primary school
(ii) Secondary school
(iii) High school
(iv) Post high school
Income (FRS/CFA)
(Interval)
Total average monthly income of
household
(i) <20,000
(ii) 21,000-50,000
(iii) 51,000-100,000
(iv) 100,001-250,000
(v) ≥250,000
Type of employment
(Nominal)
Employment type of household heads
(ii) Government official
(ii) Private official
(iii) Farmer
(iv) Businessmen
(v) Retired
(vi) Students
Household size (interval)
Total number of members currently
residing in the house
(i) 1-2
(ii) 3-5
(iii) 6-8
(iv) >9
House ownership (Nominal)
Ownership of currently resided house
(i) Owned
(ii) Rented
Type of house (Nominal)
Type of housing unit
(iii) Flats/bungalows (no compound)
(iv) Detached with compound
(ix) Trust: This refers to trust developed between individuals and
institutions, in this case „Mamfe Council‟ which is the service
provider. It is a variable that capture the community perception of
the level of confidence they have for the service provider. It is
expected that, the WTP will be positive for those household who
trust in the reliability of the service provider and negative for those
who do not.
RESULTS AND DISCUSSION
Socio-economic characteristics of the respondents
After eliminating missing or inconsistent answers to
valuation questions, 371 (98.9%) responses are
considered valid representative sample for Mamfe
residents‟ population. The sex distribution of the sample
is 56.9% females and 43.1% males. The age group with
the highest frequency is 36-45 years, that is, 28.5% of the
respondents, while those above 56 years account for
9.4%. The mean age of the respondents is 39.5 years.
This implies that respondents are economically active
and are able to earn more income. This can influence
their decision to pay for an improved waste management
service. Most of the respondents have attained the
secondary school level of education. This implies that
majority of the respondents have acquired basic
360 Afr. J. Environ. Sci. Technol.
educational knowledge, a factor that can influence their
WTP. Income generated by most Mamfe residents is
either through employment in the formal or business
sector, with a mean income class of 50000-100000 FRS.
This illustrates the huge gap in income with only 10.5% of
the population in the high-income bracket. In terms of
employment, the business sector is the highest (30%)
followed by the government and the private sector (17.5
and 19.1% respectively) with the least being students and
retirees (4.3 and 4.9% respectively). Over 70% of the
respondents live in detached building (with compound)
with close to 50% ownership. The household size with
the most frequency (45.8%) is 3-5 persons.
Public perception of the local environment
The environmental quality of an urban landscape can
portray the level of public environmental awareness of a
community. Public awareness reflects many aspects of
environmental status, such as people‟s knowledge,
personal consideration and behavior, public capacity, and
the local citizens‟ attitude towards sustainable society as
a whole, etc. (Song et al., 2016). Over ninety percent
(95.1%) of the respondents are very much concerned
about the problems of environmental degradation; the
illegal dumping of waste in streams, roadsides and
gutters, and some of the health diseases that may come
from poor waste management such as malaria, typhoid
and cholera. However, only 51.5% of the respondents
are satisfied with the current environmental situation of
the town. Considering that only the HIRA currently
receives some level of service (about once in two
months); this level of satisfaction is quite high. Similar
surveys in Ningbo, Quingdao, Zhuhai, Macau and Dalian
city of mainland China showed satisfaction rates of 49.9,
72, 83.8, 92.4 and 95.5% respectively (Song et al., 2016).
Concerning participation in environmental activities,
88.6% indicate that they have participated in one or two
environmental activities organized by the Ministry of
Environment on national environmental day and the usual
“Keep Mamfe Clean” which holds every first Thursday of
the month. Approximately, 74.5% of the respondents are
of the opinion that water pollution poses the most serious
environmental problem. With regards to their participation
in waste separation, 73.1% indicated they are willing to
sort waste at home if the government required them to do
so.
Willingness to pay
Most of the respondents (85.1%) indicate that they are
willing to pay some amount of money in the contingent
market. For the 14.9% respondents who state that are
unwilling to pay anything, 41% (23) indicate that they
could not afford to pay, 36.4% are of the opinion that
waste management is the responsibility of the government
while 21% (12) do not consider the service important
enough to pay for it. This supports the findings of Wang
et al. (2014) and contradicts the findings of Seth et al.
(2014) in which 62% of the respondents were unwilling to
pay.
With regard to the valuation question, the response for
the willingness to pay at each bid level ranges from 500
FRS to ≥5000 FRS per month (Table 3) with the majority
(45.2%) of the respondents choosing the bid 500-1000
FRS while 7.7% selected the ≥5000 FRS bid. These
chosen bids represent the minimum expected WTP of the
respondents. The mean bid amount is 1000 FRS (with a
95% confident interval of 750 FRS and 1500 FRS
representing the lower and upper limits respectively;
approximately US$1.73: current exchange rate). This
amount is comparable to those reported in previous
studies, $1.98 in Ilorin (Ezebilo, 2013). The mean bid
represents 1-2% of the respondents‟ mean income
(50,000-100,000FRS bracket); higher than that obtained
for Ilorin, 0.83% (Ezebilo, 2013). This percentage is still
higher (2.8%) relative to the minimum wage of 36,000
FRS/month.
A validation question was asked to investigate the
validity of households‟ WTP bids and their respective
maximum WTP value; the results show that 6.3% of the
households are not ready to contribute above what they
bided. Nearly all the respondents (93.7%) expressed
WTP response uncertainty (that is, they were WTP more
than their maximum bids when prodded further and
hence expressing uncertainty on their initial maximum
WTP amounts). When expanding the samples to all
households in Mamfe, using the total population of
60,000 inhabitants with a mean number of 4 people per
household, the estimated number of households stands
at 15,000. It can be deduced that the annual WTP value
is approximately 180 million FRS /year. This projected
value can be used as reference values to design a
conservative payment scheme and determine the total
available finance for a solid waste management system.
Factors determining willingness to pay
The Probit regression results of factors influencing
households‟ WTP for improved SWM are presented in
Table 4. The estimation result shows the likelihood ratio
chi-square of 143.2(df=11) with a p-value of 0.008
meaning that the joint significance test of all variables in
the model is significant at 5% level. This implies that the
variables correctly predict the model. The Probit
regression gave a Pseudo R-squared of about 0.6572,
suggesting that approximately 65.72% of the variation in
WTP is explained by the explanatory variables. This is an
indication that the estimated Probit model has integrity; it
is appropriate and is generally good. The validity of the
Probit model in estimating households‟ WTP is in line
Manga et al. 361
Table 3. Distribution of responses by bid amount.
Bid (amount in francs)/month
‘‘Yes’’ votes
Percentage
500-1000frs
140
45.2
1000-1500frs
79
25.5
2000-4000frs
67
21.6
≥5000frs
24
7.7
Table 4. Probit results for willingness to pay determinants.
Parameter
Coefficients
S.E
Z
Sig.
95% Confidence interval
Lower bound
Upper bound
Probit
Age
0.038
0.059
0.646
0.004*
-0.077
0.153
Gender
-0.010
0.121
-0.080
0.014*
-0.247
0.227
Trust
-0.011
0.091
-0.123
0.902
-0.190
0.168
Location (Residential area)
0.181
0.080
2.265
0.024*
0.024
0.338
Number of persons living per household
-0.087
0.073
-1.194
0.233
-0.229
0.056
Type of employment
-0.034
0.037
-0.918
0.059*
-0.106
0.038
Educational level
0.028
0.054
0.515
0.607
-0.078
0.133
House ownership
-0.032
0.131
-0.244
0.807
-0.288
0.224
Income level
-0.092
0.057
-1.625
0.004*
-0.203
0.019
Type of house
0.055
0.133
0.409
0.062*
-0.207
0.316
Sanitary inspector
-0.156
0.096
-1.633
0.102
-0.344
0.031
Prob>chi² (0.008)
LR chi² (11) 143.2
Pseudo R-squared (0.6572)
PROBIT model: PROBIT (p) = Intercept + BX; *represents significance at 5%.
with related studies by Hagos et al. (2012) and Seth et al.
(2014). The following independent variables: household
type, educational level and house ownership are
insignificant in determining WTP; whereas, gender, age,
income level, location (residential area), type of
employment and type of house are significant.
Gender shows a negative coefficient and is significant
(p<0.05) on WTP. This indicates that female respondents
are more willing to pay for improved solid waste
management than males, a situation that can be
explained by the fact that in Cameroon (more so in this
locality that is more rural) women are traditionally
responsible for maintaining hygiene and sanitation in the
home; cleaning and waste disposal. This result lends
credence to findings of Afroz et al. (2009) and Aggrey
and Douglason (2010).
The positive coefficient for age (p<0.05) indicates that
holding all other variables constant, older people are
willing to pay more than younger people. This may
suggest that older citizens make more mature decisions
related to evaluating health and environmental issues,
possibly due to their age. This result is in line with
findings of Afroz et al. (2009) but contradicts the findings
of Aggrey and Douglason (2010). The later held that
older citizens view waste collection, as government
responsibility and could be less willing to pay for it.
The variable type of housing is positive and significant.
This indicates that WTP is higher for those who live in
confined area like flats/bungalows with limited compounds
compared to those living in detached houses with
compound. In such units, the limitation of space (to
permit on site disposal and reduce the immediate impact
of poor waste disposal) can increase their demand for
waste management services. This contrasts with findings
by Ezebilo et al. (2013).
Households‟ income shows a negative and significant
(p<0.05) relationship with WTP, indicating that holding all
other variables constant, the income of the head of
household even though significant did not have the
expected sign on WTP. Thus, an increase in household‟s
income does not necessarily increase the WTP for a
better waste management service. This is contrary to
economics theory which postulates that higher income
households have a greater demand for waste
management and are more willing to pay for it (Hagos et
al., 2012; Maskey and Singh, 2017). The coefficient of
the variable type of employment is negative and
significant with WTP. This indicates that employment
362 Afr. J. Environ. Sci. Technol.
Table 5. Tobit Regression results of factors influencing the amount of money respondents are WTP.
Variable
Coefficient
S.E.
t-statistic
p-values
95% Confidence Interval
Lower bound
Upper bound
Constant
1.764
0.241
7.333
0.000*
1.291
2.238
Gender
-0.035
0.039
-0.903
0.367
-0.112
0.042
Education level
-0.024
0.018
-1.363
0.174
-0.059
0.011
Age
0.042
0.019
2.167
0.031*
0.004
0.080
Household size
-0.032
0.024
-1.298
0.195
-0.080
0.016
Type of employment
-0.039
0.012
-3.201
0.002*
-0.062
-0.015
Type of house
-0.105
0.042
-2.529
0.012*
-0.187
-0.023
Household Income
-0.052
0.019
-2.721
0.007*
-0.089
-0.014
Household ownership
0.051
0.044
1.164
0.245
-0.035
0.136
Trust
0.031
0.030
1.033
0.302
-0.028
0.091
Location (Residential area)
0.034
0.021
1.154
0.057
-0.025
0.187
Inspector
0.057
0.038
1.842
0.081
-0.052
0.241
*Significant at p<0.05.
status (income reliability and job security) has an inverse
relationship with WTP. This is contrary to the a priori
expectation that households with more secure
employment will show higher WTP for services. It,
however, exhibits the same trend with household income;
to which it is intricately linked.
Catalano et al. (2016) suggest that household income
and other related variables (such as location of a
household and type of employment) may show
significantly negative relationship with WTP for a public
good, which is more a problem of data rather than the
consequence of an unexpected behavior. These authors
intimated that if annual payments are small and can be
afforded by a cross section (low, middle and high-income
levels) of the population, and if fewer households of the
studied population belong to the high-income group; this
little variation cannot make the coefficient positive. This
explanation is highly plausible in our study, where only
10.5% of the households are ranked as high income
(≥250,000) level. This result can also be linked to the fact
that low-income households have stronger demands for
public SWM services, whereas the high-income may
have the ability to employ private solutions as has been
reported in previous studies (Wang et al., 2011, 2014).
Also, low- and middle-income residential areas (LIRA and
MIRA) inhabitants are more WTP for an improved waste
management service than the high-income residents
(HIRA); possibly because this area (HIRA) is receiving
some level of service.
Determinants of the amount of money households
The Tobit regression results of factors influencing the
amount of money respondents are willing to pay for
improved waste management services are presented
in Table 5. The theoretical validity of CVM bids (Tobit
regression) was performed to check the behavior of WTP
determinants (Mitchell and Carson, 1989; Sumukwo et
al., 2012). The Tobit regression gives a Pseudo R-
squared of 0.6572. Four of the exogenous independent
variables in the demand for improved SWM are
statistically significant (p<0.05) predictors for the
maximum amount of money households are WTP for
improved solid waste management service, that is,
household income, type of house, type of employment
and age of respondents. These four variables are also
significant variables in the Probit model used in this
study. Gender, which is significant in determining WTP, is
not a significant predictor in the amount respondents are
WTP. Similar observations were reported by Awunyo-
Vitor et al. (2013).
The coefficients of age variable show positive and
significant relationship with the amount of money the
respondents are willing to pay for improved solid waste
management. This may be explained by the fact that as
people gets older, they tend to understand the need of a
clean environment (Afroz et al., 2009). In addition, they
may also know that access to funds by waste
management organization can improve their services
(Awunyo-Vitor et al., 2013). The coefficient of household
income is negative and significant; implying that increase
in household‟s income does not necessarily increase the
amount residents are WTP for a better waste
management service. This is contrary to economics
theory which postulates that higher income households
have a greater demand for waste management and are
more willing to pay for it (Hagos et al., 2012; Maskey and
Singh, 2017).
The coefficient for the variable type of employment is
negative and significant. This implies that less reliable
income source is a predictor of the amount households
are WTP for the improvement of SWM services. This is
contrary to the expectation that households with more
secure employment will show higher WTP for services.
Education is not statistically significant in either equation,
in contrast to most CVM studies which show that, on
average educated households are willing to pay for
improvements in solid waste management services
(Banga et al., 2011; Sumukwo et al., 2012). Seth et al.
(2014) and Niringiye and Omortor, (2010) made the same
observation, that is the insignificance of education in
WTP.
Conclusion
A high level of concern over the problems of
environmental degradation is displayed by the population
(95.1%) with 74.5% of the opinion that water pollution
posed the most serious environmental problem. Over fifty
percent (51.5%) of the population indicated that they
were satisfied with the current level of environmental
sanitation. Participation in environmental activities,
particularly the monthly „keep clean‟ exercise is very high
88.6 and 73.1% indicated they were willing to sort waste
at home; if the government required them to do so.
With regard to WTP for improvement in SWM services,
over 85.1% indicated their willingness to pay some
amount of money in the contingent market, with a mean
bid amount of 1000 FRS (approximately US$1.73: current
exchange rate). This represents 1-2% of the mean
monthly income (50,000-100,000FRS) bracket. The trend
of WTP and income variables (income and type of
employment) is negative and significant. According to
Catalano et al. (2016) this could result from the fact that
annual payments are small and can be afforded by a
cross section (low, middle and high-income levels) of the
population. It is therefore possible that this could be a
suitable take off fee for any such scheme.
CONFLICT OF INTERESTS
The authors have not declared any conflict of interests.
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