# 4 DATA

Our analysis is based on a unique panel dataset spanning a 20-year period. The second wave of the survey, conducted in 2004/05 by the authors, revisited the same households of a 1985 study by the International Food Policy Research Institute (IFPRI) and Instituto de Nutrición de Centro América y Panama (INCAP) on a sample of NTX adopters and non-adopters.<sup>17</sup> The 1985 survey was administered to 399 households from six communities in the municipality of Santiago Sacatepéquez, and collected information on household composition, education, health and anthropometric measurements, employment, dwelling conditions, consumption and income, land holdings, cultivation patterns, cooperative membership, and technical assistance. The six communities served by _Cuatro Pinos_ were Pachalí, San José Pacúl, Santa Maria Cauqué, San Mateo Milpas Altas, El Rejón, and Santiago, where the cooperative is located. The region’s proximity to the Pan-American Highway is notable, as access to infrastructure has not been a constraint on the sustainability of NTX production by smallholders.

Prior to the follow-up, extensive fieldwork was carried out in 2004 in the _Cuatro Pinos_ communities of interest in order to locate original sample households and identify the names and locations of each original household member for a follow-up interview.<sup>18</sup> Subsequently, 314 original-households were located, and the sample used for this study includes 293 originalhouseholds.<sup>19</sup> The 2004 listing operation also revealed that the vast majority of the individuals that have left original-households since 1985 and formed separate households were living in the same or surrounding communities. Hence, in addition to original-household interviews, the 2005 survey was administered to one “split-off” household, randomly chosen among former household members still living in the survey communities.

While the same set of 1985 modules were administered in 2005 to ensure comparability, additional recall modules on full histories of cooperative membership, NTX cultivation, land transactions, agricultural and durable assets, and perception of economic wellbeing were also included.<sup>20</sup> Information for a money-metric welfare indicator and several non-monetary welfare 17 See von Braun, Hotchkiss, and Immink (1989) for the original survey design.

18 The full listing exercise was necessary, since with the exception of the household head, the names of each member of the original household were missing from the dataset, and paper questionnaires were no longer available. For these individuals, the information was available only on the age, gender and relation to the household head, which required tracking and collection of the missing names prior to the survey fieldwork.

19 Out of the original sample of households, 15 could not be identified since neither the name of the household head nor address information were recorded in the 1985 survey. In 54 cases, the heads of households had died, and another 16 were known to have moved from the community. Only the original households with original heads are used for this study. Further data cleaning eliminated households with insufficient or suspect information, yielding a final sample size of 293. To test for the existence of endogenous attrition, we follow Galasso et. al. (2004) and regress the attrition indicator, which is a dichotomous variable equal to 1 if an observation was not resurveyed in 2005, on the 1985 value of any outcome of interest and other baseline characteristics of the household, including community fixed-effects with Santiago being the reference category; the age and years of education of household head and his/her spouse; the number of household members in the age category of [0,14]; and the separate counts of male and female household members in the age category of [15,64]. The test for attrition bias is equivalent to testing whether the baseline value of the outcome of interest is statistically significant. Following this approach, we were not able to detect any sign of attrition bias. The results, which are available upon request, were not sensitive to the choice of OLS vs. Probit to fit the model with a binary dependent variable, i.e. the attrition indicator.

20 In addition to the careful design of all recall modules, all enumerators were trained extensively on collecting recall data in order to minimize the impact on our results of inevitable errors of recollection.

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