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Table 3.11. Ownership of Non-lighting Electric Appliances by Income Quintile Income Quintile (thousands of Tk) <25 25–50 50–75 75–100 >100 All quintiles
Electric Fans % Connected 15.0 23.2 33.7 38.2 54.2 29.0
% Ownership 40.0 52.4 61.0 71.1 73.0 60.4
Mean Number Owned 0.53 0.75 1.07 1.42 1.87 1.16
Television Sets Mean % Number Ownership Owned 16.0 0.16 23.6 0.24 36.4 0.36 49.4 0.49 59.2 0.62 37.6 0.38
Radios/Tape Recorders % Ownership 17.3 26.0 37.0 43.4 50.0 35.6
Mean Number Owned 0.17 0.26 0.38 0.45 0.55 0.37
Source: BIDS Survey (2004).
farmers’ selection of fuels and irrigation pumps. From a policy perspective, it is critical to determine the relative importance of these factors, given the competing demand for alternative sources of energy and its quality. The question for researchers is this: What are the direction and magnitude of these factors’ effects on demand for various Table 3.12. Summary Statistics of Outcomes types of energy? and Important Explanatory To answer this question, we conVariables of Household Energy ducted an econometric analysis to preDemand Regressions dict how household energy demand is affected by changes in the various factors. Standard Variable Type Mean Deviation A tobit regression was run to account Household energy demand for households having zero values for Fuelwood (kg/month) 98.86 104.57 one or more types of energy demand. Kerosene (liter/month) 2.41 1.94 The variables used as influencing factors Diesel (liter/month) 1.80 11.18 were gender of household head, age, maximum level of education in the Electricity (kWh/month) 25.72 252.29 household, household income (proxied Explanatory by land and non-land assets), comMaximum education of 5.02 4.17 munity prices for major energy sources household adults (years) and consumer goods, and community Household assets infrastructure variables.5 Table 3.12 Land (acres) 1.25 2.22 provides summary statistics of energy Non-land (Tk 10,000) 1.68 5.55 demand and selected influencing variVillage price ables of policy relevance, while Table 3.13 Fuelwood (Tk/kg) 1.65 0.68 presents the effects of selected variables Kerosene (Tk/liter) 22.94 2.73 on energy demand. Diesel (Tk/liter) 23.19 2.61 The study results support the Electricity (Tk/kWh) 2.85 0.40 assumption that an increase in income If village has electricity 0.66 0.47 increases the demand for energy. Indeed, Source: BIDS Survey (2004). with higher incomes, rural Bangladeshis