Short Answer

In its International Guide for Electric Cooperative Development and Rural Development, the National Rural Electric Cooperative Association defines willingness to pay as “the maximum amount that an individual indicates that he or she is willing to pay for a good or service.” Willingness-to-pay surveys are essential, because the financial feasibility of a mini-grid project depends largely on the ability of users to pay a tariff that generates enough revenue to cover the costs of operations, maintenance and repairs for the mini-grid system. If a willingness-to pay-survey indicates that revenues from tariffs are insufficient to cover costs, the project will need to find subsidies or other sources of revenue.

Willingness-to-pay surveys are generally accomplished through at least one of following two approaches:

  • A survey of expressed willingness to pay. This is the maximum amount that a person says he or she is willing to pay for electricity.
  • A survey of revealed willingness to pay (sometimes referred to as “ability to pay”). This is the actual amount people already pay for kerosene lamps, candles, flashlight batteries, diesel for a home generator or other substitutes for mini-grid electricity.

Data from these surveys are compiled into a database to determine an average willingness to pay (generally in monetary units per month for a certain quality of service) and a distribution profile of survey respondents’ willingness to pay, ranked from highest to lowest. The database is designed to store and analyze the collected data.

A mini-grid is more likely to be financially viable if it can provide a superior level of service (i.e., more reliable, more hours of electricity, brighter lights, less indoor pollution, cell-phone charging or television) for a tariff that is similar and ideally lower than a household’s current energy expenditures. Willingness-to-pay surveys can help calibrate system design to sustainably provide tiers of service within the budget defined by revenue collections.

Further Explanation of Key Points

Expressed Willingness to Pay

Expressed willingness to pay for mini-grids is generally determined through a process, called “contingent valuation,” in which researchers describe a hypothetical electricity service and then ask survey respondents to state the maximum amount they would be willing to pay for that level of service. This methodology can consider a variety of tiers of service, soliciting willingness to pay for each level. Contingent valuation can be used either in individual household surveys or in focus groups.

Researchers should be aware that respondents may not understand the service and its limitations and benefits enough to offer a realistic response. Some, for example, may state an excessively high figure in the hopes of encouraging the service to be deployed. On the other hand, they may state unreasonably low figures, because they expect off-grid power to be available at the same low prices that their urban friends and relatives pay for grid-connected electricity.

Revealed Willingness to Pay

In gauging revealed willingness to pay, researchers ask respondents what they currently pay for candles, kerosene and dry-cell batteries, or for electricity from a local diesel generator in the case of households that own their own generator or connect to a neighbor’s generator. When households only have candles or kerosene lights, this represents what they already pay for “Tier 0” service and thus what they could pay for the same or higher level of service if tariff payment schedules are similar to current patterns of expenditure. In households that benefit from diesel generation or a solar home system, information on the expenditures (and thus revealed willingness to pay) of this higher-tier level of service are also recommended.

It is also useful to ask questions that augment data on whether the target population has enough income to pay for electricity services. This process generally includes questions about expenditures on telecommunications such as cell phones, housing, education, health, transportation and food.

Finally, the survey can be an opportunity to ask the community about community organizations or businesses, their feelings about their provision of electricity service and what impact (if any) they anticipate it having on their daily lives.

Putting it Into Practice

Steps for Conducting a Willingness-to-pay Survey
Identify the Information Needed
What levels of service are under consideration? What do people already pay for energy? What are their sources of income? Is the income seasonal?
Define the Variables
Identify variables such as expenditures per month for items like candles or kerosene, household population and number of lamps.
Formulate the Necessary Questions for the Survey
Visual diagrams can help explain levels of service. In formulating questions, try to imagine all possible circumstances.
Design and Test the Instrument
Surveys usually contain some mistakes. It is best to discover these before survey teams are sent to the field. Keep in mind that different regions may use different colloquial terminology.
Design the Database
The database must be compatible with the survey instrument.
Define the Target Population
Generally, this is the population to be served by the electrification project.
Determine the Size of the Survey Sample
Find a balance between statistical significance and practicality.
Establish a Sample Framework and Produce a Map of the Project Area
The sample framework maps out the specific areas within the area to be surveyed, chosen to help ensure broad representation across different socioeconomic conditions.
Select a Random Sample
This should be done rigorously to avoid bias that arises from choosing homes that “look more approachable” or are closest to the main roads. Typically, with villages of 100 households or less, the entire village should be surveyed. For larger areas, use a chart to determine valid sample sizes or an online sample size calculator. It is useful to plan for 15–20 extra surveys to allow for mistakes.

 

Consider gender and disenfranchised segments of the population in your survey methodology. Who will answer the survey questions? Men and women may have different uses for electricity and may have different levels of control over the household budget.

Instruct the Enumerators
This should include field-testing the survey instrument with someone who has never seen the questionnaire to ensure that the enumerator understands and can communicate each question.
Conduct and Supervise the Survey
A field supervisor should accompany each enumerator at least once to review the way in which he/she conducts the interview.
Enter, Revise and Tabulate the Data
Reliability of data entry is essential. Random records from the database can be selected and compared against the survey instrument.
Calculate Consumer Willingness to Pay
Expressed willingness to pay is calculated as a range and mean figure, based on responses to different levels of service. Revealed willingness to pay is calculated by adding up expenditures for each energy source, calculated in dollars per month.

Resources

The following downloadable tools can be used to conduct feasibility and willingness-to-pay studies.

Information Sheet for Participants (DOCX 18K).
This document should be read aloud to community members participating in the study. It explains the purposes of the survey and contains important qualifiers, such as the fact that there is no guarantee of a solar mini-grid being built and that accurate willingness-to-pay responses are critical in allowing the mini-grid developer to set a proper tariff.

Residential Demand and Willingness-to-Pay Survey (DOCX 28K).
This survey can be used to gauge approximate energy use in residential homes, as well as willingness to pay.

Non-Residential Demand and Willingness-to-Pay Survey (DOCX 273K).
Developers can use this survey to gauge the demand and WTP of potential commercial, industrial, small and medium enterprise and public-sector customers.

Extended Residential Demand and Willingness-to-Pay Survey (DOCX 250K).
This survey includes extra questions to refine the accuracy of demand and willingness-to-pay estimates gleaned from survey data.