unit, these analyses are tantamount to analyzing the effect of the interviewers on inequality measures. The main findings of this analysis are summarized below.<sup>2</sup> The main inference from the findings of the ANOVA and cluster analysis is that the observed low inequality indices are not likely due to interviewers’ work practice, nor do they reflect poor supervision of the data collection process. The results of the ANOVA and cluster analysis of the three years data were compared across years and interviewers to see if any pattern emerges by cluster of interviewers. The interviewers were very consistent for all three years 2002, 2003 and 2004 examined. Gini coefficients were uniformly low for all interviewers and for all years. The interviewers appear to be a reasonably homogeneous group in terms of enumeration level inequality. Furthermore, interviewers in the extreme cases (i.e., reporting relatively small or large Ginis) did not remain extreme in all years. For example, only two interviewers, each in 2003 and 2004, had a Gini of above 30 percent and these were not the same. And three interviewers had a Gini that was below 10 percent, two interviewers in 2003 and a different interviewer in 2004. The overall implication that interviewers not no meaningful contribution towards the observed low inequality holds true unless one is to argue that all interviewers through out the country are colluding, a very improbable proposition. Colluding is not practical and physically impossible for interviewers who are geographically isolated and dispersed through out the country.

# **3. Potential Sources of Low Inequality —Hypotheses**

The observed low inequality in the HIES data could be indicative of various underlying conditions. Some of these possible conditions and associated hypotheses are presented below. In the following sections, we test the hypotheses that are testable with the available information in the HIES data. It is anticipated that these will likely help us judge the quality of the HIES data for using to analyze poverty in Azerbaijan as well as identify the potential sources of low inequality in the data.

First, the reason for low inequality in Azerbaijan could be that inequality is in fact low and the low Gini is just reflecting the underlying reality in the country. For anyone with the understanding of the economic structure of Azerbaijan and regional distribution of welfare, such explanation is implausible. The observed Gini coefficients are too low to be credible for Azerbaijan. It is implausible to think that Azerbaijan is the most equal country in the world, and Baku the most equal city. However, certain government and donor programs for the poor and vulnerable households could provide, albeit not sufficient, explanation for the apparently low inequality in the Azeri data. This led us to our first hypothesis.

- **Hypothesis 1:** The government’s social protection programs, the involvement of donors in support of these programs, and family support networks have played an important role in reducing welfare disparity among the population. Well targeted social transfers to the poor and the vulnerable groups, such as the displaced population, lifted the consumption levels of these groups without affecting the welfare of the people in the upper

> 2 For more details, see Ersado (2006).

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