The most significant step in the recent past has been bringing the official measurement of poverty in line with international best practice (Vidyaratne and Tilakaratne 2003, DCS 2004a). As the discussion in section 3.1 indicated, and the Announcement of the Official Poverty Line (DCS 2004) states, the Department of Census and Statistics is now committed to calculating the Official Poverty Line using the Cost of Basic Needs
method in line with best practice.95 The value of the food basket for the official poverty
line was constructed based on the most recent Income and Expenditure Survey (HIES 2002), spatial price indices (regional poverty lines) were computed using imputed prices (unit values) for the survey data, and the new official price index covering all districts of the country, the Sri Lanka Consumer Price Index (SLCPI), has been identified to update the official poverty line for future years.
Equivalence scales
Thus, all that remains to bring the methodology for measuring absolute poverty in the monetary approach completely in line with best practice is to derive appropriate equivalence scales which can be used to assign household expenditure to individuals.
Many approaches exist in theory and practice on how to derive equivalence scales.96 The
existing practice in Sri Lanka and several developing countries of using only nutrition based equivalence scales is not a good practice. Little reference is made at all to the concept of economies of scale. Ironically, some of the most rigorous empirical work on equivalence scales used survey data from Sri Lanka (Deaton 1981 and Deaton and Case 1988, using the 1969/70 and 19809/81 Socioeconomic Surveys). While future work on poverty measures should employ equivalence scales, the method and basis for doing so should be made explicit. Ideally, several equivalence scales should be used and the results compared. These can initially be done using existing datasets (eg. HIES 2002).
9 5 See Gunewardena (2004a): 39-52 for a discussion of poverty line methodology.
9 6 Deaton (1997):241-270 provides a good introduction to the issues that need to be dealt with in
A review of the existing nutrition based equivalence scales (used by the MRI) could be undertaken, comparing it with nutrition based equivalence scales used in other countries, for instance, India. Such a review would deal with issues such as the appropriateness of using different scales in different sectors/occupational levels, etc. The “subjective” approach uses qualitative data to construct equivalence scales. One or more of existing small scale surveys that have included the minimum income question (or similar appropriate questions) may be used to triangulate information on equivalence scales (Ravallion and Pradhan 2000). However, to do so requires datasets that combine qualitative and quantitative data. The possibility of including a qualitative/ subjective module in future budget surveys (HIES; CFS) is something to be considered by the Department of Census and Statistics and the Central Bank of Sri Lanka.
Relative poverty and Subjective Poverty
Derivation of an appropriate relative poverty line for Sri Lanka
While the need for focusing on relative poverty has been emphasised in recent discussions on poverty, there appears to be no attempt to derive an official relative poverty line. It is probably inappropriate to follow the example of developed countries— such as the cut off point of 60 percent of median income (European Union) in locating the relative poverty line for Sri Lanka. A process of discussion and consensus building informed by analysis would be useful in order to locate a poverty line for Sri Lanka. The analysis of household data linking absolute poverty measures and conducting simulations to obtain several relative poverty lines under different scenarios could provide a useful starting point. Such a relative poverty line should follow best practice and be based on consumption expenditure, not income (several developed countries are now following the practice of using expenditure based poverty lines as well); use a median concept, not mean, and should be compared with the absolute poverty line and
any subjective poverty lines in order to provide context.97
Derivation of Subjective poverty lines
Deriving a subjective poverty line for Sri Lanka is an important gap that needs to be filled. Existing qualitative surveys can be used in conjunction with quantitative surveys to derive subjective poverty lines. These should be tested for robustness (to the survey, sample size, and type of question asked). Subjective poverty lines could be income or expenditure based (eg. based on the minimum income question, or the kinds of
questions used in Ravallion and Pradhan 2000)98 or based on “items that are lacked”
(Mack and Lansley 1985 and Callan and Nolan 1998). Subjective poverty lines could
9 7 See Gunewardena 2004a: 36-38 and 49-50.
9 8 Pradhan and Ravallion (2000) have devised a set of alternative questions that could be used
instead of the minimum income question. These would be best included in a HIES, in order to make comparisons between subjective measures and monetary measures of poverty. See Section 2.9.3 in Part I of this study, Poverty Measurement: Meanings, Methods and Requirements (Gunewardena 2004a: 120-128).
also incorporate other dimensions of poverty including social exclusion and the lack of resources. A study or review of existing qualitative data should identify the appropriate
indicators to be used for this purpose.99 Alternatively, a survey (qualitative, but in several
parts of the country, and ensuring coverage of different groups) could be initiated for the purpose of identifying the indicators that could go into a subjective description of poverty.
Baseline data for the North and the East
1. The most recent representative survey for the North and the East is the 1985/86
LFSS. Although poverty estimates cannot be constructed below district level, poverty analyses which examine the determinants of poverty, can be. This can be compared with analysis (in 1985/86) on the rest of the country—to determine differences or similarities at the time of the beginning of the conflict.
2. Administrative data—this is available at the GN division level, and an effort can be
made to include these into a poverty database. This will help identify divisions that are “poorer” than others in the case of indicators such as mortality, morbidity and supply of services.
Combining qualitative and quantitative methods
Much can be achieved by combining qualitative and quantitative methods of poverty analysis in Sri Lanka. The rich qualitative literature can be used to design questions to be included in a subjective module in a structured questionnaire.