As discussed in Chapter 14, the widespread introduction of new technology has brought
new employment opportunities and rising relative wages to those with the highest levels
of human capital. However, this new technology has also helped to bring about higher
than normal job losses, particularly among unskilled workers, and put a premium on
being able to adapt to new workplace challenges. The result has been that
unemployment, or the fear of unemployment, has touched the lives of more and more
people. While the national unemployment rate is often viewed as being determined solely
by macroeconomic forces, it clearly has a number of important microeconomic
determinants. The purpose of Chapter 15 is to present an analysis of the phenomenon of
unemployment from a microeconomic perspective.
The national unemployment rate is one of the most visible and closely-watched indicators
of aggregate economic well-being. To understand its microeconomic determinants, it is
first necessary to understand how it is measured. As noted in Chapter 2, the population
(POP) aged 16 or over can be divided into those in the labor force (L) and those not in the
labor force (N). The labor force consists of all those who are employed for pay (E),
actively seeking work, or waiting to be recalled from layoff. Those actively seeking work
or waiting to be recalled from layoff are classified as unemployed (U). Therefore, if the
population can be defined as the sum of L and N, the labor force can be defined as the
sum of E and U. The unemployment rate (u) is defined as the ratio of U to L. The data
on U and L come from the Current Population Survey, a national survey of over 60,000
households conducted monthly.
As a measure of economic hardship, the unemployment rate has a number of drawbacks,
some of which have been discussed in previous chapters. For example, the
unemployment rate actually decreases when those who search unsuccessfully for work
give up the search. The rate also does not distinguish between part-time and full-time
work, nor does it distinguish whether the unemployed person is the primary source of
their family’s income. The unemployment rate may also give very little indication as to
the employment rate (e)—the fraction of the total population that is employed. The
reason is that the employment rate is related to the unemployment rate via the equation
where lfp denotes the labor force participation rate, the ratio of the labor force to the
population. If the labor force participation rate is growing rapidly, the employment rate
can increase at the same time the unemployment rate is rising. If one keeps in mind these
limitations, the unemployment rate can still be a useful indicator of labor market
conditions.
The microeconomic determinants of the unemployment rate are best understood within
the context of the stock-flow model of the labor market. In this model, the
unemployment rate can be expressed as a function of the flows of people over any given
period between different labor market categories. Letting Pij represent the proportion of
individuals in labor market state i that flow to labor market state j during the period,
where the labor market states are employment (e), unemployment (u), and not in the labor
force (n), under certain conditions the unemployment rate can be expressed as a function
(F) of these flows where
The sign over each proportion indicates the effect of an increase in that particular
proportion on the unemployment rate, holding all else constant. An intuitive
understanding for each of the effects can be obtained by using the definition of the
unemployment rate. For example, an increase in the flow from e to n raises the
unemployment rate because it leaves the numerator of the unemployment rate unchanged
but reduces the denominator. The stock flow model shows that even when the
unemployment rate is not changing, significant changes are still taking place in the labor
market.
The values of Pij, if computed using monthly data, are also referred to as average monthly
transition probabilities. Data on the proportions for particular demographic groups can be
useful in understanding why unemployment rates vary across groups. For example, the
relatively high unemployment rate for teenagers is due to relatively high flows from e to n
and from e to u. This suggests that the unemployment problem is not so much a lack of
jobs but an inability or unwillingness to keep a job. By using the stock flow model to
pinpoint the cause of a group’s unemployment rate, it may be possible to design a more
appropriate policy for lowering the group’s unemployment rate. For example, since
teenagers have trouble holding jobs, not finding them, a program of job search assistance
would have little impact on that group. Such a program would be more appropriate for a
group that has a relatively low probability of moving from unemployment to employment.
Teenagers would be better served by attempts to promote on-the-job training (perhaps by
lowering the minimum wage for teens).
The stock flow model can also be helpful in understanding the various types or categories
of unemployment. Frictional unemployment occurs because labor market information is
imperfect. Even when labor markets are in equilibrium, it may take time for job seekers
to fill the available job vacancies. These market imperfections reduce the proportion of
people flowing from u to e and so raise the unemployment rate.
Additional insights into the determinants of unemployment can be obtained using a model
of the job search process.
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