# **III.** Examples

The previous section has shown that under certain assumptions we can anticipate how measured poverty will change if different definitions of consumption are used. To check these predictions and also to ascertain by _how much_ measured poverty changes, we consider two empirical examples, drawing on household survey data from Ecuador and Pakistan.

The Ecuador household survey _(Encuesta Sobre Las Condiciones de Vida)_ is a nationally representative household survey modelled on the World Bank's Living Standard Measurement Surveys. It was fielded in Ecuador during the period June-September, 1994. Over 4,500 households were surveyed in total and after cleaning and data consistency checks, information for 4,391 households is available for analysis. Hentschel and Lanjouw (1996) describe in detail the construction of the Ecuador consumption aggregates. The Pakistan survey _(Pakistan Integrated Household Survey)_ is also nationally representative and based on the LSMS model. It was fielded over the course of the whole year in 1991. In total, information on 4,673 households is available for analysis. The construction of the consumption aggregates has been described in Howes, Gazdar and Zaidi (1994).

Tables 2 and 3 provide calculations of poverty in Ecuador based on the "traditional" and "austere" poverty lines in turn. In each table three common summary indicators of poverty are applied: the headcount index and two indicators from the FGT class, with parameter values of 1 and 2. From Table 2 it appears that, if the poverty line is set using the "traditional" approach, the headcount ratio is robust to alternative definitions of consumption (the differences are not statistically significant). This accords with the theoretical prediction. On the other hand, there is also no significant change in the FGT indicators. On the basis of the arguments above we might have expected them to increase. Turning to Table 3, where the "austere" poverty line is set, the incidence of poverty falls as predicted: from 50% when only food expenditures are used to as low as 35% when the full consumption aggregate for Ecuador is applied. Even between measures of consumption which both include food and non-food spending the decline in the incidence of poverty is as large as ten percentage points. It is important to note that the consumption aggregate defined in the second row of both tables is one which would probably find acceptance as a comprehensive measure of consumption by most observers. Poverty measured by the two FGT indicators also declines sharply.

Tables 4 and 5, based on data from Pakistan. provide a similar picture of how measured poverty changes with the definition of consumption. Once again poverty measured with respect to the "traditional" poverty line does not vary markedly as the definition of consumption changes, and this is true over all poverty indicators. And once again, poverty measured with reference to the "austere" poverty line declines sharply. The estimated incidence of poverty with the full definition of consumption is 24 percentage points lower than the incidence when only food expenditures are utilized, and still 15 percentage points lower than when a simple consumption aggregate including both food and non-food items is applied.

The patterns observed for both Ecuador and Pakistan accord broadly with those predicted. The single exception, in both cases, is failure of the FGT indicators to increase with aggregation under the "traditional" poverty line. An explanation is suggested in Section V when we consider measurement error.

8