Earnings and Chronic Renal Disease
M.R. Godoy, G. Balbinotto Neto, and E.P. Ribeiro
ABSTRACT
Background. The number of patients with chronic renal disease (CRD) has grown
worldwide, especially in Brazil. This disease increases the public expenditure, besides
having other economic implications and impacts. Most patients are in the productive age,
range (15– 49 years old).
Purpose. The purpose of this study was to estimate the income losses due to CRD using
data from the Brazilian Household Survey (Pesquisa Nacional por Amostra de Domicílios
[PNAD-1998]).
Methods. Two econometric methods were used: ordinary least squares and quantile
regression.
Results. The data showed that the incidence rate was higher among individuals with
lower income deciles and few years of schooling. The incidence rate among individuals
who studied 1 year was almost 5 times higher than that among those subjects who studied
for 14 years. The estimates showed that CRD had a negative effect on patient income. On
average, CRD individuals suffered an 11% reduction in remuneration.
Conclusions. These estimates pointed out that the poorest people are more affected by
CRD. The highest incidence in the lower income stratus suggests that new actions and
prevention must be adopted to provide health assistance for individuals with CRD.
E
CONOMISTS have been studying many aspects related to the treatment of chronic renal disease
(CRD), proposing mechanisms to reduce the extended
waiting lists for kidney transplantation.1– 4 The most effective solution for CRD is a kidney transplantation, but it
takes a long time to find an organ donor, approximately 3
years in Brazil. During such time, dialysis reduces the
readiness for work and other activities. This work sought to
assess the impact of CRD on the remuneration of patients
who were reported to be suffering from this illness in Brazil,
using data from the Brazilian Household Survey (Pesquisa
Nacional por Amostra de Domicílios [PNAD-1998]). This
study followed the line of recent works, such as that by
Kassouf5 and Rivera and Currais,6 but was concentrated on
CRD cases.
METHODS
Description of the Data
The analysis was based on the PNAD-1998, which surveyed 344,975
individuals, covering most of the Brazilian territory. The exploratory analysis of the data showed that the CRD incidence was
inversely correlated with income (namely, CRD individuals having
a lower income than others), and years of education.7 The inci0041-1345/07/$–see front matter
doi:10.1016/j.transproceed.2007.01.007
378
dence of patients with 1 year of education was almost 5 times
higher than that of subjects with 14 years of education (5.34% and
1.11%, respectively). The wage for CRD women is lower 31.28%
than those who do not have the disease. For men, the average
difference was lower (15.09%). It was also noticed that the amount
of education was lower among CRD individuals, the difference
being approximately 20% for men and 10% for women.
Econometric Model: Quantile Regression
In order to verify the effect of the presence of CRD on earnings, 2
different methodologies were used: ordinary least squares (OLS)
and quantile regression (QR). The QR allowed us to analyze the
impact of the explanatory variables throughout the conditional
From the Universidade Federal do Rio Grande do Sul
(UFRGS), Programa de Pós-Graduação em Economia, Porto
Alegre, RS, Brazil.
The authors acknowledge the financial support of Capes and
Cnpq.
Address reprint requests to Marcia Regina Godoy, Universidade Federal do Rio Grande do Sul, Faculdade de Ciências
Econômicas, Programa de Pós-Graduação em Economia, Av
João Pessoa, 52 Sala 33 B - 3 Andar, CEP 90040-000 - Centro Porto Alegre, RS, Brasil. E-mail: [email protected]
© 2007 by Elsevier Inc. All rights reserved.
360 Park Avenue South, New York, NY 10010-1710
Transplantation Proceedings, 39, 378 –380 (2007)
EARNINGS AND CHRONIC RENAL DISEASE
379
Table 1. Results of the Estimates for OLS and QR*
QR
Gender
Study
Age
Age2
Color
CRD
Constant
R2/pseudo R2
OLS
10th
25th
50th
75th
90th
⫺0.359 (78.23)**
0.141 (258.33)**
0.874 (54.74)**
⫺0.088 (38.52)**
0.104 (23.36)**
⫺0.111 (8.33)**
0.246 (9.30)**
0.44
⫺0.308 (35.28)**
0.122 (111.90)**
0.717 (32.77)**
⫺0.077 (24.66)**
0.101 (12.76)**
⫺0.112 (4.72)**
⫺0.127 (3.51)**
0.1704
⫺0.324 (64.00)**
0.130 (172.00)**
0.793 (36.49)**
⫺0.083 (27.27)**
0.110 (19.25)**
⫺0.132 (7.15)**
0.051 (1.39)
0.2155
⫺0.359 (65.71)**
0.141 (215.07)**
0.878 (40.93)**
⫺0.089 (29.00)**
0.108 (18.28)**
⫺0.119 (7.91)**
0.233 (6.66)**
0.2610
⫺0.383 (54.43)**
0.147 (212.91)**
0.947 (39.98)**
⫺0.093 (26.64)**
0.104 (20.66)**
⫺0.115 (5.77)**
0.485 (12.93)**
0.3033
⫺0.378 (42.75)**
0.150 (162.88)**
1.014 (26.61)**
⫺0.099 (18.08)**
0.101 (12.80)**
⫺0.103 (5.26)**
0.744 (12.00)**
0.3213
*t statistics are presented in parentheses.
**Significance level at 1%. Amount of observations: 111,988.
distribution of the dependent variable (lnw ⫽ hourly wage).8 The
estimates were obtained by bootstrapping with 100 replications.
The earnings equation depends on individual characteristics (gender, color, age) and the human capital (education), and also the
presence of CRD. This relationship is expressed in equation 1:
logW␪ ⫽ ␣0␪ ⫹ ␣1␪E ⫹ ␣2␪S ⫹ ␣3I ⫹ ␣4␪I2 ⫹ ␣5␪D ⫹ ␣6␪C ⫹ ␧␪
(1)
where the dependent variable (W) is the logarithm of the hourly
wage, which is the total income divided by the amount of worked
hours; E is the years of education; I is the age; S is the gender; D
is the dummy variable that assumes a value of 1 whenever the
individual reported was suffering CRD, or 0 otherwise; C is a
dummy variable that assumes a value of 1 when the individual was
white, or 0 otherwise.
RESULTS
The sample for the estimates contained 111,988 observations of men and women between 18 and 55 years of age
and greater than R$1.00 income. The estimates were made
using all data from the sample (both genders), as well as by
differentiation by gender, applying the QR on the 10th,
25th, 50th, 75th, and 90th quantiles.
Table 1 shows the results of the estimates for the total
sampling. The results showed the expected signs for all
coefficients that were significant at conventional test levels.
The variable color indicated that white individuals had a
higher income (positive sign). The coefficient of the gender
variable showed that women had a lower income than men
(negative sign), indicating a discrimination in the job market
for women in Brazil. The variable years of study revealed that
the rate of return of the additional years of education was
higher for individuals with high quantiles. The returns to
school varied from 12.2% to 15.0%. CRD had a negative
impact throughout all quantiles of the conditional earnings
distribution, being more important in the 25th quantile. That
impact varied between 10.3% and 13.2%.
Whenever the quantile regressions were applied for both
genders, the estimates showed that they were similar to
those attained from the total sampling. All coefficients
showed the expected signs and statistical significance, but
they are not discussed herein. As to CRD, both genders
showed negative coefficients, which were significant from a
statistical point of view. For men, the CRD coefficient was
higher in the 25th quantile, and decreased along the
conditional earnings distribution, having varied between
11.3% and 14.8%. For women, the CRD coefficients were
lower (6.9%–10.4%), and the 10th quantile showed the
highest coefficient (in absolute values).
Upon comparison of renal variable coefficients for both
genders, it was noticed that CRD had a lesser impact on
women’s incomes. Therefore, the results suggested that
CRD has a negative impact on conditional earnings distribution, in which lower quantiles showed a more negative
impact.
DISCUSSION
This paper investigated whether the presence of CRD had
an impact on individuals’ income. The econometric results
suggested that there was a negative impact on earnings. It
seems that this paper is the first to measure the impact of
CRD on earnings in a developing country.
The results from the OLS and QR analyses showed that
CRD had more impact on lower income patients. The use
of such an econometric technique allowed us to show that
throughout the conditional earnings distribution, the presence of CRD had negative effects on income. The magnitude of that earnings reduction was approximately 11%
according to the PNAD-1998. Health policies seeking to
prevent or retard the CRD could contribute to a reduction
in income inequality, making possible a healthier population with higher participation in the job market, including
more working hours and greater productivity.
ACKNOWLEDGMENTS
We thank Claudio Rotta, Everton Nunes da Silva, Pedro Pita
Barros, Tanara Rosangela Sousa, Valter Duro Garcia for helpful
comments and conversations. The authors acknowledge the financial support of Capes and Cnpq.
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