Alcances esperados si se implementa la propuesta de la metodología

The first matching estimator was derived by matching each individual in a pilot area to the individual in a control area whose demographic characteristics were closest to theirs according to their ‘propensity’ to be in a pilot area. This involved examining the

characteristics of young persons in the pilot areas and seeing whether they were similar to the characteristics of young persons in the control areas. The ‘propensity’ is a weighted index of all the observable characteristics that are believed to be an important influence on education decisions. Information was used on family income; family structure; education; age; labour market status and occupation of parent(s); ethnicity; early childhood experience; gender; housing tenure; and whether the young person lived in an urban or rural area. It was not possible to match individuals on the type of school attended in year 11 because this question was only asked of those who continued in post-16 full-time education.2 This exercise was undertaken only for young people in pilot and control areas who were, or would have been, eligible for EMA. The quality of the data meant that only very close matches were accepted.3 Table A5.1 in Appendix A5 assesses the impact of the matching process by comparing

sample sizes and the mean characteristics of individuals in pilot and control areas, both before and after matching took place. The population considered contains EMA eligible individuals only, or those in control areas who would have been eligible. Males and females in urban and rural areas are presented separately in accordance with the methodology used.

The first rows of Table A5.1 show the sample sizes in each of these groups. Consider first the pilot area population used in the matched and unmatched samples, as shown in the first

row of the table. Individuals who could not be well matched have been dropped during the matching process, so that the pilot area population used for the analysis for urban males declined from 1795 in the unmatched sample of urban males to 1752 in the matched sample, or by 2.4 per cent. For urban females, the drop in sample size was from 1832 to 1773 or by 3.2 per cent. The losses to the sample in rural areas were somewhat higher, at 6.5 per cent for males and 12.2 per cent for females. The reduction in sample size was necessary to ensure that valid comparisons were made. Since the one-way matching retains the majority of the sample and Table A5.1 in Appendix 5.1 shows that the reduction in sample size does not change the composition of the pilot group in any important way, these reductions should not be of concern.

Consider next the control area populations used. As a result of the experimental design, the unmatched data contains more pilot area individuals than control area individuals. As can be seen in Table A.5.1, almost twice as many interviews were conducted in urban pilot areas than in urban controls. However after matching, each individual in a pilot area was directly linked to his or her closest match in a control, and the numbers compared in pilots and controls were therefore identical. Note that this means that many of the control area individuals were used as matches for more than one pilot area individual. The maximum number of times any one control area individual was used as a match is 14, although the average number of times a control area individual was used in urban areas is approximately 4.1 times, falling to 2.5 times in a rural area (not shown on the Table). This is because in the rural sample, the numbers in the pilot and control areas were almost identical (by design).

Some of the characteristics used in the matching process differed between pilots and controls in the unmatched and matched samples; Table A.5.1 shows this be indicating the mean characteristics in pilots and controls. The rows marked ‘difference’ show the difference between the pilot and control means. Unless otherwise marked, these will be differences in proportions, but for family income the difference given is a percentage difference.

Differences marked by a star are significant at the five per cent level.

On many characteristics, the samples were well balanced between pilot and control areas prior to matching and, for this reason, matching did not alter the mean sample characteristics significantly. As would be expected, some of the mean characteristics converged between

decisions of young persons in the pilot areas are being compared to that of genuinely similar young persons in the control areas. Most notably, differences in family income were less pronounced in all of the matched samples compared to the unmatched samples. Note, however, that since matching allows differences in characteristics to be traded off against each other, some characteristics also became slightly more divergent between pilots and controls after matching. Examples of this include the proportion of rural females who live in council or housing association accommodation.