At this point, the first four steps encompass the calculations to calculate the panel weights in the absence of attrition. The round 2 household weight would be:

# _6) Attrition correction factor_

Household panel survey weights need to address the problem of attrition, i.e. where survey observations (household or individual members) are selected for re-interview but cannot be located or refuse to be interviewed. The methodology used to adjust weights for attrition in the LSMS-ISA surveys follows Rosenbaum & Rubin (1984), which has also been adopted in the PSID; see for example, Gouskova et al (2008). Predicted response probabilities from a logistic regression model based on the covariates are used to form the weighting classes or cells.

Due to the somewhat unusual design of the panel, the attrition correction in the case of the LSMS-ISA surveys needs to take into account two distinct sources of attrition: entire households that are not found, and split-off individuals that are selected for tracking but not found. The two potential options for the calculations given these two conditions are (1) to treat the split-off households as household heads and perform the calculations at the level of the household, or (2) to treat the households that are not found as individuals and perform the calculations at the individual level. The first option is problematic if the characteristics of household heads are dissimilar to the characteristics of split-offs. The LSMS-ISA surveys have generally found that the groups most likely to attrite from the sample are young people, generally but not always male, often residing in urban areas. Therefore for the LSMS-ISA surveys, the second methodology is employed.

To obtain the attrition adjustment factor, the probability that a sample household was successfully reinterviewed in round 2 is modeled with the linear logistic model at the level of the individual. A binary response variable is created by coding the response disposition for eligible household members that are not interviewed in round 2 as zero, and household members that are interviewed as one. The eligibility requirements vary between surveys (for example, excluding children under the age of 15 in the Tanzania LSMS-ISA calculations). In all surveys, the dead are excluded from the calculations because they cannot be tracked. Members who moved abroad are generally excluded from tracking but remain eligible, as they may return in later rounds.

These calculations use a logistic response propensity model, including the household and individual characteristics measured in the previous round as covariates. The details of this model will vary, perhaps dramatically in other types of surveys or those implemented in different contexts. General model building techniques should be applied to determine the most appropriate set of covariates for a given dataset. For the purposes of illustration, the following round 1 covariates were among those included in the LSMSISA survey attrition calculations:

- being a split-off member targeted for tracking

- demographic characteristics (age, gender, marital status, etc.)

- residence of one or both parents in household

- years of education

- current school attendance

- labor force participation

- household consumption

- household assets

- household size

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