Willingness to Pay for Improved Electricity Service in Nigeria

Published: 20-06-2020| Version 1 | DOI: 10.17632/32tbhgdppn.1
Contributor:
Emmanuel Onyeuche

Description

The data was gathered with the aid of a well-structured questionnaire administered within the cities of Abuja, Ibadan, Port Harcourt and Lagos in Nigeria. The data comprised of three thematic areas. First is the social economic characteristics of the household. Secondly, the nature of the quality electricity supply and how it affects households’ welfare. In the third section, a hypothetical scenario of an improved electricity system that conforms to all the dimensions of quality electricity supply was created. Respondents were asked to state the maximum amount they were willing to pay for such an improved quality of electricity supply system. The CVM elicitation format that was employed in the study was the discrete choice with a follow-up approach. A first bid was proposed to each respondent. If the respondent agrees to pay that amount, a higher amount was proposed. If he agrees to that, a third amount, higher than the second was further proposed. If he declined to pay the first bid, the follow up bid proposed to the respondent was lower. After going through the follow up process, all respondents were asked to state after careful thoughts what their maximum WTP for the improved electricity service would be. The amounts each respondent states here were compared to the responses from the follow up process to check for consistency. The Ordered-Probit Model was employed as the main estimation technique for the study. The model estimated using the Ordered Probit regression was: WTP = β1 HSZ + β2 HY + β3 EDL + β4 REL + β5 CRR + β6 CAP + β7 MO + ε The model investigates the factors that influence consumers’ willingness to pay (WTP) for the improved electricity service in the study area. In the model, the outcome variable is WTP (coded 1, 2; 1 being N41 – N55 and 2 being Above N55) which is an ordered categorical variable. The variables used as predictors are Household Size (HSZ), Monthly Outages (MO) - which are continuous variables, Household Monthly Income (HY), Highest Educational Level (EDL), Reliability of Current Supply (REL), Cost incurred in damage of appliances (CRR) and Cost of Alternative Power Supply (CAP) - which are categorical variables. However, it should be stated that ‘n-1’ (n being the number of categories) dummies were created for each of the categorical variables in the model. The reference category for Household Monthly Income is Below N51,000, Highest Educational Level is no formal education, Reliability of Current Supply is Excellent, Cost of Damage is Below N2,000.00 and Cost of Alternative Supply is Below N2,000. The models were estimated separately for each of the enumerated cities and full sample for easy comparison. Microsoft Excel and the STATA statistical package was used in analyzing the collected data.

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