# **Appendix B on data sources and methodology**

> _Tables 3 and 4._ The Chile estimates are based on CASEN 94, a nationally representative survey that provides information on current labor force participation, working status, affiliation to social security and contributory status. The estimates used are based on the urban sampleapproximately 100,000 individuals age 16 or older. The work patterns reported are those of affiliates (workers who have contributed at some point) in urban areas. The self-employed are not required to contribute. Our data indicate that 73% of all male workers and 55% of female workers

> affiliate (most of the others are self-employed) and 90% of male affiliates (91% of women

> affiliates) who are employed contribute to social security. Thus, in Chile our estimates are close

> to the behavior of the average affiliate but do not apply to women who never worked in the

> formal labor market. Work experience is estimated based on current employment of affiliates.

> Wages reflect pay for full time work (most work is full time, or 35 hours per week, in Chile). For

> some analyses data on the distribution of wages within each cell were used to estimate dispersion of pension accumulations for that cell.

The Argentine data are based on the micro data set of the Encuesta Nacional de Gastos de los Hogares (ENGH) for 1996-97, a nationally representative household survey. The sample contains 103,858 individuals, of whom 69,895 were 16 years or older. All regions covered are considered urban. Our data do not allow us to distinguish between affiliates and non-affiliates or between full timers and part timers. In Argentina all workers, including the self-employed, are supposed to affiliate and contribute. From other sources, we know that 90% of private sector workers and 50% of public sector workers were affiliated in the mid 1990's but the over-all contribution rate is only 50% of employment in urban areas (compared with 68% in Chile). Thus some work years may be non-contributing years. Work experience is estimated based on current employment status of urban population, including both full time and part time workers. Wages reflect pay for full time and part time work, hence understate the true full time wage rate. Because we cannot distinguish between non-affiliates and affiliates, who have a higher labor force participation rate, we probably understate the labor force attachment of affiliates. However, we probably overstate contributions of affiliate when working, because of the 50% evasion rate.

The Mexican data come from the 1997 Mexican National Employment Survey (ENE-97) completed by _INEGI (Instituto Nacional de Estadistica, Geografla e Informnitica),_ the Mexican Statistical Bureau. The sample contains information on 119,405 individuals aged 12 or older. We use the sub-sample corresponding to more-urban areas (communities of 100,000 people or more), which is about 78% of the sample. This survey contained the standard employment survey questions, plus a module with employment history and job training questions. The ENE97 does not allow for the identification of social security affiliates (about 42% of the economically active population) and/or the contributions made to retirement plans. Work experience is estimated based on current employment (both part time and full time) of more-urban population in relevant age-education cells. Wages reflect pay for full time and part time work in each cell. For some analyses we used the observed coefficient of variation on earnings for each cell as an estimate of the distribution of years worked and resulting annuity within that cell.

Using these cross-sectional statistical data, we divided men and women into gender-ageeducation-mantal status cells. A typical cell, for example, might consist of all married women with high school degree age 30-35. For each cell we obtained the average employment rates and wage rates for the current population. Data on marital state enabled us to identify the age, M, at which the probability of being married > 50%. In constructing our synthetic men and women, we used the employment probability and wage rate of the single individual up to age M, and the married individual after age M. The labor force participation rate of women typically declined sharply when they got married. In some (high education older age) cells the number of single women is very small so we could not profile women who remained single throughout life.

_Table 5._ We assumed that for each educational level, an average man or woman who enters the labor force today proceeds through life with the age-specific employment probabilities and 60