7 The analysis in sections 11 and III suggests that there are some important differences in unemployment rates among demographic groups. In this section, we extend our analysis of unemployment differentials, with particular attention to the dynamics of unemployment and how they differ by sex, age and education.

Recent research in labor economics suggests that unemployment should be viewed not as a static phenomenon affecting a stagnant pool of job seekers, but rather as the result of individuals flowing in and out of unemployment, each experiencing jobless spells of varying length. At any point in time, observed unemployment may comprise a number of individuals experiencing very short spells of unemployment as they move from one job to another (the "churning" or "normal turnover" component of unemployment), as well as a smaller number of people who are out of a job for a long time. The relative importance of these two components in explaining observed unemployment has important welfare implications. If most of unemployment is associated with normal turnover, the burden will be widely spread and few individuals suffer greatly. If, however, most unemployment is associated with a few individuals remaining unemployed for extended periods of time, the hardship associated witn unemployment will fall primarily on a few.

This perspective on unemployment emphasizes the difference between frequency and duration of unemployment, and suggests that the measured unemployment rate, in itself, contains relatively little information: a similar rate of unemployment could reflect a large proportion of the labor force being unemployed for a short period of time, or a small group experiencing long spells of unemployment. Better insights into the nature of unemploynent in Mcxico may be gained by explicitly exploring the dynamics of unemployment and labor market behavior.

# A. Analysis of the Distribution of Spells of Unemplovment.

We begin our analysis by examining the distribution of the duration of completed unemployment spells. We calculate this distribution using individual data for the 1990-91 quarterly urban laDor force survey (ENEU). The questions we seek to answer are: (i) what is the mean duration of a completed spell?; and (ii) what is the relative importance of long-term unemployment?

The procedure we used to calculate the distribution of unemployment spells is the following. We first constructed a dataset comprising two ENEU cohorts. The first cohort included individuals wh.o were unemployed in the third quarter of 1990. These individuals were then observed at discrete three-month intervals over the follcw.ng twelve months. The second cohort included individuals wno became unemployed in the fourth quater of 1990 and were not in the first cohort. For this latter cohort, individuals were followed for only nine months.

As discussed above, most individuals in our dataset report the duration of their (incomplete) unemployment spell up to the time of the survey. We calculate complete unemployment spells by tracking individuals over time, identifying their transitions to employment, and adding time elapsed until the job was found to the incomplete unemployment spell reported in the initial quarter. Unfortunately, the ENEU does not include a question on starting date for the current job. As a result, if an individual moves from unemployment one quarter to employment the next, it is impossible to know exactly when in the intervening three months the transition took place --in other words, knowing which quarter an individual finds a job does not allow us to compute the exact length of the unemployment spell. To obtain a fairly smooth distribution of spells over the quarter, we assume that rifty percent of those who found jobs exited unemployment within one month, thirty