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Public pensions, economic development, and the labor force participation of older adults in Latin America in 1990–2010

effects. The former creates incentives to retirement since more educated workers are
more able to afford retirement, whereas the latter implies a higher opportunity cost
to leave work (Gordo and Skirbekk, 2013). Education is also related to the age that
workers enter the labor market. Workers with lower levels of education might invest
less in human capital and enter the labor force at younger ages in more physically
demanding jobs (Gordo and Skirbekk, 2013). Those elements might affect the decision
of staying in or leaving out the labor force.
Occupation might also affect the labor supply of the older adults. Occupation is
related not only to the educational level but also to access to social security benefits.
Workers in the formal market have more direct access to social security than workers
in the informal sector and the self-employed. Employers recruit workers in the formal
market in the system, while those in the informal sector should decide on their own
whether to join the pension system.
The existence and the size of pension systems are related to labor force participation
rates. For social security, the model considers four different variables: the length of
time the system has existed, regular retirement age, coverage of the system in relation
to the labor force (ratio of contributors to wage earners), and whether the system is
only a PAYGO or has some sort of private account mechanism.

2.2.2 Statistical Methods
In the second part of the analysis, the paper investigates the determinants of elderly
labor force participation in the dataset by two approaches. To assess the magnitudes
of these effects, this paper estimates a model where changes and variations in elderly
labor force participation are driven by demographic characteristics, education, income
level, and other covariates. All the data used in the estimation come from a time series
for 23 Latin American countries for the period 1990–2010, as described above. Based
on the theoretical review, the following model (Equation 1) was specified:
(1)
LFPR i = α + βX i + γZ i + ε i
The analysis concentrates on country characteristics such as mean years of
schooling, participation in the labor market (formal and informal), percentage urban,
GDP per capita (in 2005 constant US$), social security characteristics, and a set of
control variables. In the model, LFPR represents the labor force participation rates
for population aged 55–59, 60–64 and 65–69, while X is the matrix of explanatory
variables, Z i is the matrix of controls, and ε i is an error term. The analysis was
performed using Stata 12 and R.

3 Results

3.1 Descriptive Analysis

3.1.1 Age Profiles of Labor Force Participation

Figure 1 depicts the labor force participation rate (LFPR) by age and sex for study
countries. Male labor force participation rate is higher than that of females for all
countries. The main result is the rapid rate of withdrawal from the labor force after
age 50 and is always lower for those with pension coverage. For example, by age 65
the labor force participation rate ranges from 15% in Uruguay to over 60% in Bolivia
and Nicaragua. In Uruguay, the participation rates are as low as observed in developed
countries studied by Gruber and Wise (1999; 2004). In the case of Brazil, for instance,
at age 60 around 50% of males are already out of the labor force and the rates fall to
30% at age 65. Using a synthetic cohort approach, this result implies that almost half
of the males working at age 60 in Brazil would leave the labor force before reaching
age 65.

126 International Journal of Population Studies 2017, Volume 3, Issue 1