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This survey established a baseline for monitoring progress toward Sustainable Development Goal (SDG) 7, specifically target 7.1: \u201cEnsure access to affordable, reliable, and sustainable modern energy for all\u201d by 2030. The results aim to guide the government in setting access targets, developing policies, and designing investment strategies for energy access.\n\nThe MTF approach evaluates energy access across multiple attributes that influence user experience, such as reliability, quality, and affordability, regardless of the technology or fuel used. These attributes define six tiers of access, ranging from Tier 0 (no access) to Tier 5 (full access). A household\u2019s overall tier is determined by the lowest tier it achieves among the attributes, reflecting a comprehensive view of energy access (Bhatia and Angelou, 2015).\n\nThe MTF survey in PNG was integrated into the World Bank\u2019s Poverty Global Practice (GP) survey, which measured the socioeconomic impacts of COVID-19. During the survey\u2019s third round, energy access data were collected by incorporating MTF-related questions into the questionnaire. Due to time constraints, selected questions focusing on key MTF attributes were included in a phone survey conducted from May 7\u201317, 2021, by Digicel\u2019s Port Moresby call center, in collaboration with the Poverty GP.\n\nIt is important to note that mobile phone surveys are often biased toward wealthier households with access to charged mobile phones and network coverage. As a result, lower-income households may be underrepresented. To address this, a wealth index was calculated to minimize potential bias.\n\nThe survey covered a total of 2,500 households across 87 districts. Data collection and management were facilitated using the Survey Solutions (SUSO) software package. These findings offer critical insights into the energy access landscape in PNG and provide a foundation for informed policy and investment decisions.","coll_dates":[{"start":"2021-05-07","end":"2021-05-17","cycle":""}],"nation":[{"name":"Papua New Guinea","abbreviation":"PNG"}],"geog_coverage":"National","analysis_unit":"Household","data_kind":"Sample survey data [ssd]","notes":"The scopes of the survey are:\n1. Household:  Sex of the household head, education level, employment type,\n2. Electricity: Status of the electricity in households \n3. Cooking: Status of the cooking stove and fuel types in the households\n3. WTP: Willingness too to for Grid connection fee and for Off-grid solutions\n4. Energy Expenditure: Expenditure of lightings \n5. 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The weights were based on information from the 2016\u201318 PNG DHS and included adjustments for household location, size, and wealth and the respondent\u2019s sex and education level. 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To avoid this bias, a wealth index was calculated to mitigate the potential bias as much as possible. \n\nThe MTF survey in 2021 re-created the wealth index which allows comparison between the MTF survey and the Demographic and Health Survey (DHS) from 2016 to 2018. The 2016\u201318 DHS dataset in PNG (DHS 2019) used a wealth index based on household assets and housing characteristics. If households have steadily acquired more assets, they will appear higher in the wealth distribution in this MTF survey than they would in the DHS. According to the Papua New Guinea High Frequency Survey on COVID-19: Results from Round 1 (World Bank 2020), the DHS wealth index (DHS n.d.) is calculated using principal components analysis. Not all variables of the full DHS wealth index were considered in the mobile phone survey due to the limited survey length. In the recalculation of the wealth index of the phone survey there is more than 98 percent correlation between the recalculated and original measurements. To get the identical measurement, the pooled data was used with a single set of codes. To infer at the population level instead of mobile phone holders, it was essential to re-weight the survey data. To address the potential upward bias, several methodologies were use, such as correlation, logit model, and raking, among others."},"analysis_info":{"response_rate":"The response rate was 63%."}},"data_access":{"dataset_use":{"cit_req":"World Bank - Energy Services; Electricity Services and Cooking Services 2021. Ref PNG_2021_WBE_v01_M. 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