Willingness to pay for improved solid waste management services and associated factors among urban households: One and one half bounded contingent valuation study in Bahir Dar city, Ethiopia

Figures & data

Figure 1. Conceptual framework.

Figure 2. Map of the study area.

Table 1. CV Formats and Econometric models used for analysis

Contingent Valuation Formats	Econometric models
Open ended	Multiple linear regression; Tobit
Bidding game	Multiple linear; Tobit; Bivariate probit/Logit; Binary logit
Payment card	Multiple linear regression; Tobit
Single bounded	Binary logit; Binary probit
Double bounded	Multiple linear; Tobit; Bivariate probit; Binary logit; Multivariate probit

Table 2. Definition, descriptive statistics and expected sign of variables

Variable	Definition	Measurement	Expected sign
SEHH	Sex of household head	1 for female, 0 otherwise	-
AGEHH	Age household head	Year	-
MARITSTATUS	Marital status	1 married, 0 otherwise	+
EDUCLEVEL	Educational level	Year	+
JOBOFRES	Job of respondents	1employed, 0 otherwise	+
MONAGGRINC	Monthly aggregate income	Ethiopian Birr/ETB	+
DURRESIDENCE	Duration of residence	year	+
ACCESSWAMGTS	Access to SWM service	1 user, 0 otherwise	+
QUANWGEN	Quantity of waste generated	Plastic bag	+
DISEOB	Disease outbreak	1 yes, 0 otherwise	+
NUMCHILD	Number of children	Number	-
RESPWMGT	Responsibility of WM	1 responsible, 0 otherwise	+
HEADST	Headship status	1 head, 0 otherwise	+

Table 3. WTP for improved SWM services in Bahir Dar city

WTP responses	High income		Middle income		Low income		Total sample HHs
	N^o	%	N^o	%	N^o	%	N^o	%
Yes	116	93.55	110	88	76	75.25	302	86.3
No	8	6.45	15	12	25	24.75	48	13.7
Total	124	100	125	100	101	100	350	100

Source: Survey results, 2018

Figure 3. Reasons for not WTP for better SWM services.

Table 4. Estimating total WTP for the different household income groups

Class mark	Sample distribution		Total HHs	WTP for different income groups						Total WTP
				Low income		Middle income		High income
1 ETB	2 (No.)	3 (%)	4 (No.)	5 HHs	6 WTP	7 HHs	8 WTP	9 HHs	10 WTP	11 ETB
3.5	125	41.4	23,470	5906	20,671	8549	29,921.5	9015	31,552.5	82,145
9.5	112	37.1	21,032	5293	50,283.5	7661	72,779.5	8078	76,741	199,804
15.5	37	12.2	6916	1740	26,970	2519	39,044.5	2657	41,183.5	107,198
20	28	9.3	5272	1327	26,540	1920	38,400	2025	40,500	105,440
Total	302	100	56,690	14,266	124,464.5	20,649	180,145.5	21,775	189,977	494,587

Source: own survey, 2018

Figure 4. Estimated Demand curve for improved SWM services Source: survey results, 2018.

Table 5. Expected Aggregate Revenue

Income groups	% of HHs from sample households	Total No. of HHs in population	No. of HHs from population (WTP)	Mean WTP per month	Expected total revenue(in ETB)
High	92.74	23,273	21,775	16.75	364,731.25
Middle	87.14	26,276	20,649	13.25	252,950.25
Low	75.58	16,141	14,266	6.00	85,596
Total	350	65,690	56,690	-	703,277.5

Source: own calculation, 2018

Table 6. Determinants of Households’ for better SWM services

Variables	Description of explanatory variables	Coefficients	Odds Ratio	Z	P>/Z/
SEXHH	Household headship; 1 = male, 0 = female	−6.898364	.0010094	−1.99	0.047**
AGEHH	Age of household in terms years	.1472266	1.158617	1.77	0.077
MARITSTATUS	Marital status; 1 = married, 2 = otherwise	3.819977	4.560316	1.83	0.067
EDUCLEVEL	Education level of households; 1 = illiterate, 2 = basic, 3 = secondary, 4 = tertiary & above	3.329949	27.93692	1.91	0.001***
JOBOFRES	Main occupation of Households	2.876608	17.75395	1.63	0.104
MONAGGRINC	Aggregate income of the household;	.0015612	1.001562	2.13	0.003***
DURRESIDENCE	Household length of stay in the area	−.1244059	.8830213	−1.58	0.113
ACCESSWAMGTS	Service availability or not for HHs; 1 = yes, 0 = no	6.970835	10.65111	2.19	0.029**
QUANWGEN	Quantity of waste generated per week (KURTU plastic)	1.365848	8.546803	1.93	0.001***
DISEOB	Cases of disease in the HH members in the past 1 year; 1 = yes, 0 = No	−3.994983	.0184078	−1.56	0.120
NUMCHILD	Number of children in the household	−4.356335	.0128253	−2.03	0.043**
RESPWMGT	Responsibility of solid waste Mgt.; 1 = HHs believe that we are responsible, 0 = otherwise	8.740313	6.24985	2.13	0.003***
HEADST	Status of the respondent in the household	−2.255874	.1047819	−1.09	0.274
Log likelihood −11.758381 LR chi2(13) 87.38*** Pseudo R^2 0 .7879 No. of observations 350

*; ** and *** significant at p < 0.01; 0.05 and 0.1. Source: own survey, 2018