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kaushik, K. (2009). Methodology for estimation of the benefits of a  surface water supply project in the view point of the consumer. PHILICA.COM Article number 154.

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Methodology for estimation of the benefits of a surface water supply project in the view point of the consumer

Kaushik dutta roy kaushikunconfirmed user (Delhi University)

Published in enviro.philica.com

Abstract
To assess the effectiveness of a water supply project the cost benefit analysis should be incorporated. For quantifying the benefit from the project, it is obligatory to measure the value which a community would take into account for this project. But in developing countries municipal water is treated as non marketed goods and services which is not available in the market. In that situation, this value is ascertained by contingent valuation (CV) survey upon creation of a hypothetical market. A contingent valuation survey for estimation of willingness to pay ( WTP ) for improved surface water supply is carried out in Kolkata, a metropolitan city of eastern part of India. The mean WTP is found to be INR. 87.13 with standard deviation of INR .79.03. It was found that WTP is highly dependent on household monthly income and type of profession.

Article body

 

    Introduction

A lot of public fund is being spent in the developing countries for new water supply projects. The criterion to evaluate the water supply projects in developing countries initiated since 1980. International donors and other multinational institutions started to discuss the efficiency of water supply projects finance from that time (Brookshire and Whittingtone 1993; Whittingtone and Swarna 1994). According to Whittingtone and Swarna water supply projects in developing countries frequently failed, because the projects were not evaluated with rationality. This rationality should consider the application of Cost Benefit Analysis (CBA) to assess   whether the estimated benefits and costs of the proposed change in the water supplies would justify in economic terms. To implement this revised paradigm for evaluation of water supply we have to measure the value which a community would take into account for this improved service in water supply.

 Problems for evaluation of the benefit from a water supply project

        The concept of ‘water as an Economic good' is simple. Like any other good water has a value to its user who will agreeable to pay for it. Like any other good consumer will use water so long as the benefits from use of an additional unit exceeds the costs so incurred. The value of water to a user is the maximum amount the user willing to pay for his use of water. For normal economic goods which are exchanged between consumers and producers, this value can be estimated by analysing the market demand curve of that particular commodity. But the markets for municipal water are either typically do not exist or are highly imperfect. In the many developing countries, the municipal water is treated as non marketed goods and services are not available in the market and also they are non excludable. As a result consumers do not have incentive to reveal their willingness to pay for municipal water, a non marketed good. People generally tend to act as a free rider by concealing their preference for the municipal water in order to enjoy the benefit without paying them. Due to these facts, it is not simple to determine what the value of municipal water for users is.

Application of contingent valuation method to evaluate the benefit.

            In that circumstances to determine value of the benefit actually a consumer takes into account for that proposed changed in water supply service Contingent Valuation (CV) method is applied. This method is based on survey technique in which a member of the house hold is asked a series of questions designed to determine the maximum amount of money that he is willing to pay for that proposed changed in the service provision (Whittingtone and Swarna 1994). The CV method has been broadly applied for assessment of water services in developing countries (Brookshire and Whittingtone 1993)

Methodology and survey design

For CV method a survey was arranged in Kolkata, a metropolitan city of eastern India. The questionnaire was drafted in Bengali to make it more understandable to the respondent.  Trained surveyors collected data by the direct method during the month of May to August 2008. Information was obtained from head of the family as far as possible. About 326 households are covered in the survey. A stratified sampling method has been employed for the selection of households. Care has been taken to ensure that the sample is representative.

 The questionnaire has two broad divisions. One part have included the different socio economic status of the respondent ,such as the monthly family income, educational qualification of all the members of the family ,occupation, number of family members, ownership status of the residence, availability of municipal water within his premises etc. In the second part, the respondent has been asked the maximum monthly amount he is willing to pay for the supply of surface water within his residence.

Table1. Description of the explanatory variables

 

Name of

Variable

Description

AV.WH

 

= 1, if the household  has the availability of municipal water within

Its' premises

= 0, Otherwise

OWN.HS

 

=1, if the respondent is the owner of the resident.

= 0, Otherwise

NO.FM.M

 

 Total number of the family member

MONTH.IN.

 

Total monthly income of the family in

Indian National Rupee (INR)

Busn Mn

 

= 1, if the main source of income of the family is from business

= 0 ,Otherwise

Wht CL Jb

 

= 1, if the main income holder is doing a white colour job.

= 0, Otherwise

Avg yr Edct

 

Average year of education of the whole family except the member below the age of 7 year i.e. Avg yr Edct. =      where  are the year of education of the family members n = no of family member above 7 years.

       Analysis of the distribution of the explanatory variables.

 

The descriptive statistics for the explanatory variables is summarised. The results are obtained from 326 samples taken from Kolkata metropolitan area.

 

Table 2. Descriptive statistics of the explanatory variables

 

Explanatory variables

AV.WH

OWN.HS

NO.FM.M

MONTH.IN.

Busn Mn

Wht CL Jb

Avg yr Edct

N     Valid  

 

326

326

326

326

326

326

326

       Missing      

 

1

1

1

1

1

1

1

Mean

.83

.80

3.83

8583.13

.35

.48

10.49977359

Std. Error of Mean

.021

.022

.079

379.207

.026

.028

.236814343

Median

1.00

1.00

4.00

6000.00

.00

.00

11.18333333

Std. Deviation

.378

.402

1.434

6846.762

.477

.500

4.275794288

Skewness

-1.748

-1.488

.601

1.214

.648

.074

-.501

Std. Error of Skewness

.135

.135

.135

.135

.135

.135

.135

Kurtosis

1.063

.215

.604

1.134

-1.590

-2.007

.035

Std. Error of Kurtosis

.269

.269

.269

.269

.269

.269

.269

Range

1

1

9

33000

1

1

26.250000

Minimum

0

0

0

1000

0

0

.000000

Maximum

1

1

9

34000

1

1

26.250000

 

 

 

             1) Availability of Water within premises ( AV.WH)

 

Table 3 Frequency table of  AV.WH

 

 

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

0

56

17.1

17.2

17.2

1

270

82.6

82.8

100.0

Total

326

99.7

100.0

 

Missing

System

1

.3

 

 

Total

327

100.0

 

 

 

As per census 2001, 62% of total household get water within its premises and 91% of the total house holds have not to go far from his for water. In the survey its value is 82.8%.

 

 

 

2) Ownership of residence (  OWN.HS)

 

Table 4 Frequency table for OWN.HS

 

 

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

0

66

20.2

20.2

20.2

1

260

79.5

79.8

100.0

Total

326

99.7

100.0

 

Missing

System

1

.3

 

 

Total

327

100.0

 

 

 

 Overall, there are more owners, than tenants. This is truer in the higher income group. In the slum population tenants are more. As per KMDA report in KMA area (Socio-Economic profile of household in Calcutta Metropolitan Area: 1996-97 ) 37.7% of total population reside in rented house. In the survey ownership of the residence is 79.8%.

 

 

3) Profession of the main income holder of the resident as Businessman

 ( Busn Mn )

                                                                                                           

Table 5.Frequency table for Busn Mn

 

 

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

0

213

65.1

65.3

65.3

1

113

34.6

34.7

100.0

Total

326

99.7

100.0

 

Missing

System

1

.3

 

 

Total

327

100.0

 

 

 

Any short of private entrepreneur, small or large in size are taken as businessman. In the survey 34.6% of the total sample is businessman.

 

 

4) Main income holder of the household is doing White colour service                ( Wht CL Jb)

 

Table 6 Frequency table for Wht CL Jb

 

 

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

0

169

51.7

51.8

51.8

1

157

48.0

48.2

100.0

Total

326

99.7

100.0

 

Missing

System

1

.3

 

 

Total

327

100.0

 

 

 

            The population of the persons who are doing white colour job in the metropolitan city is more or less half of the whole population. In the survey, it is 48%. Hence it is closely representative to the whole population

 

 

5) Average Family Size ( NO.FM.M )

 

 

Table 7 Frequency table for NO.FM.M

 

 

 

 

 

 

 

 

 

 

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

0

1

.3

.3

.3

1

8

2.4

2.5

2.8

2

42

12.8

12.9

15.6

3

89

27.2

27.3

42.9

4

104

31.8

31.9

74.8

5

45

13.8

13.8

88.7

6

15

4.6

4.6

93.3

7

19

5.8

5.8

99.1

8

2

.6

.6

99.7

9

1

.3

.3

100.0

Total

326

99.7

100.0

 

Missing

System

1

.3

 

 

Total

327

100.0

 

 

 

 

  Average family size in urban area of west Bengal is 4. The higher and lower value is distributed along the average. The sample survey is done according to that.

 

 

 

6) Monthly Income of the House holds (Month. In.)

 

 

 

                                      

             Table 8 Descriptive statistcs of  Month. In

 

 

 

 

 

N

Valid

326

Missing

1

Mean

8583.13

Median

6000.00

Mode

5000

 

           Figure 1  Hisotgram of Month In

 

 

In the sample survey the median value of the monthly income per household is of 6000.00 INR. Average household income is 8583.13 INR. As per KMDA Report (Socio-Economic profile of household in Calcutta Metropolitan Area: 1996-97) in 1997 the mean monthly income was Rs. 3363.00 in Kolkata metropolitan area. After 10 years with inflation this value is very close to the sample mean. Hence the sample is representative with the population.

 

7. Education status of the family (  Avg yr Edct )

 

Table 9 Descriptive statistics Avg yr Ed

                                  

N

Valid

326

 

Missing

1

Mean

10.49977359

Median

11.18333333

Mode

15.000000

      Figure 2 Histogram of Avg yr Edct

 

 

 In this survey educational qualifications of all the members are taken. 99% of the respondent is literate. As the mean and median value is above 10 hence half of the total sample population have completed schooling. In 1997 as per KMDA report (Socio-Economic profile of household in Calcutta Metropolitan Area: 1996-97) 35.1% of the population completed school education. After one decade this value may be assumed to be high. Hence the sample is representative of the population.

 

 

Econometric analysis of willingness to pay (Wtp) for surface water supply in Kolkata

 

 Multiple regression analysis has been applied for willingness to pay (Wtp) function. The dependent variable is Wtp. The Regression is done by the software  SPSS 15.

 

The result of the regression is given below

 

 

Table 9 Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.564(a)

.318

.303

65.98832

 

a Predictors: (Constant), Avg yr Edct, NO.FM.M, Busn Mn, OWN.HS, MONTH.IN, AV.WH, Wht CL Jb

 

                                                                                        

Table 10 ANOVA (b)

 

 

Model

 

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

645425.588

7

92203.655

21.175

.000(a)

Residual

1384717.740

318

4354.458

 

 

Total

2030143.328

325

 

 

 

a  Predictors: (Constant), Avg yr Edct, NO.FM.M, Busn Mn, OWN.HS, MONTH.IN, AV.WH, Wht CL Jb

b  Dependent Variable: Wtp

 

                                                                                                                      

Table 11 Coefficients

Model

 

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

95% Confidence Interval for B

 

 

B

Std. Error

Beta

 

 

Lower Bound

Upper Bound

1

(Constant)

-12.881

14.861

 

-.867

.387

-42.120

16.358

*

AV.WH

30.362

13.402

.145

2.265

.024

3.994

56.731

 

OWN.HS

-17.919

10.587

-.091

-1.692

.092

-38.749

2.911

 

NO.FM.M

3.664

2.607

.066

1.405

.161

-1.466

8.794

**

  MONTH.IN.

.004

.001

.323

5.607

.000

.002

.005

*

Busn Mn

28.446

13.555

.172

2.099

.037

1.777

55.116

**

Wht CL Jb

43.767

14.661

.277

2.985

.003

14.922

72.611

 

Avg yr Edct

1.156

1.365

.063

.847

.398

-1.529

3.842

  Dependent Variable: Wtp

 

*Significant at 5% Level

** Significant at 1% Level

 

 

 

 

 

 The analysis shows that the explanatory power of the model (indicated by R2 ) is 31.8%. This compares favourably with the value, reported 23% by Vaidya (Vaidya, 1995) in earlier econometric study on WTP in Baroda, India. The analysis shows that the two explanatory variables MONTH.IN and Wht CL Jb are significant at 1% level. That means family income is found an important determinant of WTP for supply of surface water .White colour job (dummy variable) is also very significant determinant. The analysis of the model shows that availability of water (i.e existing municipal connection of water supply) has an affinity   for higher WTP. A positive relationship is observed between occupations as businessman with WTP. The result shows that house owners are less interested to pay higher WTP than those who live in rented house. House owners are paying municipal taxes. They may be in the opinion that it should include water tax. This may the cause of negative connection of WTP with ownership of the residence. All the condition remaining the same average education level of the family is positively associated to the WTP. A positive relationship of WTP with family size also shows the correct sign.

 

Estimation of WTP

 

                                                              

                                              

Table 12 Descriptive statistics of WTP

 

N

Valid

326

Missing

1

Mean

87.1319

Std. Error of Mean

4.37737

Median

75.0000

Mode

.00

Std. Deviation

79.03540

Variance

6246.595

Skewness

.907

Std. Error of Skewness

.135

Kurtosis

.644

Std. Error of Kurtosis

.269

Range

400.00

Minimum

.00

Maximum

400.00

Sum

28405.00

 

 

 

 

 

                                                   

Table 13 Frequency distribution of WTP

Wtp in  INR

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

0

82

25.1

25.2

25.2

10

4

1.2

1.2

26.4

20

3

.9

.9

27.3

30

10

3.1

3.1

30.4

50

56

17.1

17.2

47.5

75

9

2.8

2.8

50.3

80

1

.3

.3

50.6

100

67

20.5

20.6

71.2

150

50

15.3

15.3

86.5

200

30

9.2

9.2

95.7

250

1

.3

.3

96.0

300

12

3.7

3.7

99.7

400

1

.3

.3

100.0

Total

326

99.7

100.0

 

Missing

System

1

.3

 

 

Total

327

100.0

 

 

 

 

In the survey it was found that 82 nos out of 326 of respondents willing to pay Re.Zero for improved surface water supply in house. Respondent who are not willing to pay for that are asked the reason for making such choice. A large section of these ‘Zero' response mainly objects to any payment for basic service like water. They consider that it is the duty of the government to provide these essential services. A small part of the Zero response express their financial in capability for this payment. Including   these ‘Zero' respondents the mean WTP in INR is 87.13 with standard deviation of 79.03. The median is 75 which is close to the mean but slightly less. The table shows that 45% respondents choice their WTPs within INR 100 to 150.

Estimation of WTP for one Kiloliter of treated surface water

The average family size as revealed for the survey is 3.83. The KMDA on socio economic survey (Socio-Economic profile of household in Calcutta Metropolitan Area: 1996-97) stated that the mean size if a house holds in Kolkata metropolitan area is 4. The recommendation of per capita water supply by CPHEEO manual (Manual on water supply and treatment 1991) is 150 litre per for a city of population of above 100000. According to that for one month total water demand is 18 Kilolitre (30 X4X0.150).

         From the survey it is revealed that the mean and the standard deviation of the willingness to pay of a household for one month of treated surface water supply are Rs.87.13 and Rs.79.03 respectively. Therefore the mean willingness to pay for one Kilolitre of treated surface water in city of Kolkata is Rs. 4.83 with a standard deviation of Rs.4.3.

 

Conclusion

 

During the last one and half decades the government strategy is to improve the surface water supply for the city of Kolkata. But like many other developing countries the evaluating of water supply projects have relied only on the cost side of the projects and the benefit from the side of the beneficiaries have not been integrated. The estimation of the WTP for surface water supply may be a device for calculation of the benefit of the project in the viewpoint of the beneficiaries. The Study also revealed the importance of diversity within a community in the willingness to pay for improved surface water supply. In this manner the efficiency of a water supply project from the viewpoint of both engineers and the beneficiaries can be evaluated.

 

 

 

 

 

 

 

REFERENCES

 

1.  Brookshire, David S and Whittingtone Dale (1993) 'water Resource Issues in Developing countries'; Water Resource Research

2.  Manual on Water supply and Treatment by CPHEEO in 1991

 

3.  Socio - Economic Profile of Household in Calcutta Metropolitan Area: 1996-97 by       Chatterjee N, Bhattachary N, Halder A Published by KMDA in 1999

4.  Vaidya Chetan, Study on Willingness to Pay for water and sanitation services-case study of Baroda, Report submitted to HSMI (HUCO), New Delhi, 1995

5.  Whittingtone, Dale and Swarna, Venkataeswarlu (1994), Economic Benefits of potable water supply project to household in developing countries, Manila Asian Development Bank

 





Information about this Article
Peer-review ratings (from 2 reviews, where a score of 100 represents the ‘average’ level):
Originality = 125.00, importance = 150.00, overall quality = 125.00
This Article was published on 8th February, 2009 at 12:37:24 and has been viewed 5346 times.

Creative Commons License
This work is licensed under a Creative Commons Attribution 2.5 License.
The full citation for this Article is:
kaushik, K. (2009). Methodology for estimation of the benefits of a surface water supply project in the view point of the consumer. PHILICA.COM Article number 154.


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1 Peer review [reviewer #54666unconfirmed user] added 12th July, 2009 at 18:50:40

The study is mainly based on Kolkata Survey. But effort is admirable. If the survey could be made in all metropolitan cities of India to ascetain the public mentality for paying water taxes , a good picture of people paticipation for Govt projects like WTP will be revealed. The community based study for willingness of paying water taxes for improved water supply is an excellent one. The project aim in the beneficiaries point of view is very important, so the efficiency of a water treatment project both by the engineers and the beneficiaries can be evaluated from this type of study which is very important.

Originality: 7, Importance: 7, Overall quality: 7


2 Peer review [reviewer #47336unconfirmed user] added 30th September, 2011 at 15:40:01

The statistics presented may be useful, however, the analysis has left out many aspects that are important. Among such very important aspects that were not considered related to the quality of the water supply, is the presence of carcinogenic levels of residual arsenic in ‘drinking’ water in certain parts of India and its neighbor countries.

Originality: 3, Importance: 5, Overall quality: 3




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