nationally representative probability sample of 18,671 households in 2008 and 2009. In 2008, the survey was conducted monthly with 720 and annually with 8,640 sample households between January 1 – December 31. That is, survey data of the first 720 households were collected in January. In February, the survey was carried out on a different set of 720 households. This rotation continued until the end of December. The 2009 HBS followed the same methodology but the size of the survey was expanded to contain monthly 1,050 and annually 12,600 sample households. Because each household appears in the dataset only once, the dataset supports a pure pooled cross-section analysis.

The survey is conducted through in-home interview. Each interviewer recorded the data on consumption expenditures during eight visits to the household throughout the survey month, including one visit prior to the survey month, twice during the 1<sup>st</sup> and 2<sup>nd</sup> weeks, once during 3<sup>rd</sup> and 4<sup>th</sup> weeks and once following the end of the survey month. Interviewers also inventory the households’ appliances, physical characteristics of the residence and collect demographic information. Further details about the HBS data and survey design are available in Turkish Statistical Institute (2007).

The survey data are then combined with the actual monthly rate schedule. The Turkish electricity tariff data have two advantages that are fairly unique to the study. First, in the retail sector, Turkey has applied a price equalization mechanism to maintain a nationwide uniform tariff until 2011. Under such a system, all residential consumers face a uniform flat-rate price schedule. The simplicity of the rate structure avoids specification difficulties in identifying marginal electricity prices – a common challenge for demand studies. Second, the tariff reform in 2008 introduced three price hikes for residential electricity that jointly increased the price by more than 50 percent from the previous year. The price change by virtue of its magnitude and exogeneity to the household provides a unique opportunity to identify the price elasticities of electricity demand.

# _Descriptive Analysis_

Table 1 lists the summary statistics of the variables included in the analysis. I divide the sample into reporting and non-reporting groups based on whether the household has responded to the inquiry on electricity expenditure. Table 2 reports mean value and mean differences in household characteristics between the two groups. Households who did not report electricity expenditure had lower per capita income and are more likely to reside in rural areas. Heads of these households are less educated and are more likely to not have a permanent job or health insurance during the survey month. All these differences are statistically significant at 0.01 level.

A narrower way of assessing the distributional impact of electricity tariff reform is to look at its effect on the affordability of household electricity services. Affordability can be defined as households’ ability to purchase an adequate level of utility services without suffering undue financial hardship (World Bank 2009). Affordability is usually measured by the affordability 10