economics april 8, 2016 brazil economic activity · 2017-09-22 · economics april 8, 2016...
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IMPORTANT DISCLOSURES/CERTIFICATIONS ARE IN THE “IMPORTANT DISCLOSURES” SECTION OF THIS REPORT. U.S. investors' inquiries should be directed to Santander Investment at (212) 350-0707.
*Employed by a non-US affiliate of Santander Investment Securities Inc. and is not registered/qualified as a research analyst under FINRA rules.
ECONOMICS April 8, 2016
Brazil—Economic Activity
Deterioration in the Labor Market:
The Worst Consequence of the Economic Downturn
Rodolfo Margato*
55113553-1859
All labor market variables have been deteriorating significantly, in-line with the deepening recession. In our view, the negative performance of these indicators will continue until 1H17, as economic activity should stabilize only at the end of this year.
There are significant methodological differences among the available labor market surveys. We present the main limitations of these data sources and offer some estimates in order to improve the accuracy and completeness of the labor market analysis.
We estimated the historical data series of the main labor market variables published by PNAD, considering the period from January 2002 to February 2012: (i) employed population; (ii) labor force; (iii) unemployment rate; (iv) average real wage; and (v) aggregate real wages. The official statistical (observed data series) results of PNAD are only from March 2012 onward.
Despite the methodological discrepancies, all surveys have been showing a widespread worsening in the domestic employment level, which is not likely to be interrupted this year, in our opinion. In turn, we believe the shrinkage of household income will keep the labor force on an upward path.
We forecast that the national unemployment rate published by PNAD will climb from 9.9% in 2015 to 12.8% in 2016 (end of period, seasonally adjusted), peaking only in mid-1H17 at 13.6%, which would mean the highest level of the historical data series.
One of the most severe consequences of the recessionary outlook has been the increase in employment informality. Due to the poor financial conditions of companies and the uncertain macro environment, we believe the informality will continue to increase over the next two years, at least.
According to our estimates for the aggregate real wages with social benefits (Social Security and Social Protection benefits), which functions as a proxy for the household income, we reiterate our expectation that private consumption will not resume growth in 2016, weighing heavily on GDP dynamics.
2
Different Measures for Labor Market Indicators
Labor market indicators have been showing a deep and widespread deterioration. The worst recession in many years has led to a
rapid increase in the unemployment rate, a steep decline in real wages, and increase in employment informality, among other
dismal effects. Looking ahead, we think the negative path of these indicators will not be reversed until 1H17, as economic
activity should stabilize only at the end of this year, in our view. According to our econometric estimates, the main variables of
the labor market react with an average lag of about six months with regard to economic activity indicators, notably GDP.
There has been a lot of evidence of the poor performance of the Brazilian labor market. Nevertheless, some methodological
differences among the available surveys are noteworthy. Thus, we present in this study the main limitations of these surveys and
offer some estimates in order to improve the accuracy and completeness of the labor market analysis.
The Monthly Employment Survey (PME) released by IBGE—Brazilian Institute of Geography and Statistics—had been for a
long time the official source of labor market data in Brazil. However, PME’s historical data series, which began in 2002, covers
only six metropolitan areas in the country (São Paulo, Rio de Janeiro, Salvador, Belo Horizonte, Recife, Porto Alegre), totaling
44,000 households in 145 municipalities. Because of this limitation, in January 2014 IBGE started publishing the Continuous
National Household Sample Survey (Continuous PNAD, or simply PNAD). PNAD data series cover the entire national
territory, around 211,000 households in 3,500 municipalities, and it will provide the official statistics for the Brazilian
labor market from April onward, as PME was discontinued. The last publication of PME was March 22, with data for
February. Due to the sample survey design, PNAD indicators are available on a quarterly moving average basis.
Note that some factors make PME and PNAD not directly comparable, such as their different concepts of
employment/unemployment and questionnaires. For example, (i) PME includes as the working age population individuals aged
over 10 years, while PNAD considers only individuals aged over 14 years; and (ii) for the PME sample, an unemployed person
is anyone without a job, willing to participate in the labor market, and who had sought employment in the past 30 days, whereas
for the PNAD sample a person without an occupation and willing to enter the labor market can already be considered
unemployed. Indeed, the creation of PNAD corrected the weakness of PME of considering as inactive the worker who had
given up looking for a job, but was still interested in returning to the labor market.
In short, PNAD can be considered more representative of the Brazilian labor market, in our view , especially due to its wider
coverage and the use of more modern concepts aligned to international patterns. Nevertheless, PNAD historical data series
begin only in March 2012 (on a quarterly moving average, as mentioned), hindering the development of long-term
analysis and forecasts. Thus, we decided to estimate the data series of some PNAD variables backward through econometric
methods.
In this report, we present our own estimates for the main labor market variables published by PNAD, considering the
period from January 2002 to February 2012: (i) employed population; (ii) labor force; (iii) unemployment rate; (iv)
average real wage; and (v) aggregate real wages. For the development of our methodological framework, we took into
account the information contained in other Brazilian labor market surveys with longer historical data series.
These surveys are: (1) Labor Ministry General Register for Employed and Unemployed (CAGED) that publishes monthly data
on the net creation of jobs in the formal labor market—entire national territory; (2) SEADE/DIEESE’s Employment and
Unemployment Report (PED) that releases monthly data for six metropolitan regions in Brazil—São Paulo, Salvador, Recife,
Porto Alegre, Fortaleza, Distrito Federal; (3) IBGE’s Monthly Employment Survey (PME), as described above; and (4) Annual
National Household Sample Survey (Annual PNAD) that provides only annual data for the Brazilian labor market, covering
around 1,100 municipalities. For the latter, it should be noted that the reference period of data collection is the last week of
September, and so its information becomes relevant only to the long-term dynamics of our estimates for PNAD indicators.
Annual PNAD data are useful for the comparison with the PNAD estimates’ annual growth rate, whereas the other three data
sources bring important contributions to short-term variations.
3
Continuous PNAD: Expanding the Analysis Period
In order to estimate the historical data series of PNAD’s employed population, we regressed its cyclical component1 against the
cyclical component of the PME, CAGED, and PED employed population time series, considering the period ranging from
March 2012 to December 2015. After normalizing the coefficient estimates of this multiple regression, we calculated the PNAD
employed population for the period from January 2002 to February 2012 (standardized weights of the explanatory variables
multiplied by their respective observed time series at such period). Besides this econometric method, we compared the long-
term behavior of the estimated series with the annual PNAD data series in order to validate the results. Despite the known
methodological differences, the comparison did not disqualify our analysis. The standardized weights (sum equal to 1) and the
dynamics of the estimated PNAD employed population are shown in Appendix 1.
Looking at the employed population data series, we highlight the significant increase of the employment level in CAGED data
series from 2004 to 2013, which reflects the strong expansion in the formalization of the Brazilian labor market in the period.
CAGED report covers only formal jobs, while the other surveys also include the informality. Furthermore, note that the PNAD
data series has shown a less pronounced deterioration in the recent period, compared with the other three data sources, possibly
due to: (i) the higher resilience in regions that are not in major metropolitan areas and to (ii) the increase of the “self-employed”
category (relevant for the comparison with CAGED data). Despite these differences, we emphasize that all surveys have
been showing a widespread worsening in the domestic employment level, which is not likely to be interrupted this year,
in our opinion.
Similarly, we estimated the PNAD labor force with the information contained in PME and PED data series. (See Appendix 1.)
In this case, we note the continued increase of the PNAD labor force in recent years, which contrasts significantly with the other
labor market surveys. For example, PME data registered a fall of 0.7% in 2014 and an increase of only 0.6% in 2015, while
PNAD results posted an expansion of 1.1% and 1.9% in the same periods, respectively. As mentioned, PNAD methodology
considers as active the worker who has given up looking for a job, but is still interested in returning to the labor market (unlike
the PME methodology), largely explaining these discrepancies. In our view, the shrinkage of household income will keep the
labor force on an upward path in the coming years.
Based on our own estimates for the employed population and labor force, we calculated the PNAD national unemployment rate
for the period from March 2002 to February 2012. According to our results, the current level of unemployed people is the
highest since late 2006. The following figure shows the significant increase in the unemployment rate since mid-2014, as
registered by both PME and PNAD data series. Despite the difference in levels, the dynamics presented by these surveys are
quite similar. Looking ahead, we forecast the national unemployment rate will climb from 9.9% in 2015 to 12.8% in 2016
(end of period, seasonally adjusted), peaking only in mid-1H17 at 13.6%, which would mean the highest level of the
PNAD historical data series.
1 We adopted the Hodrick-Prescott filter (HP filter) to remove the cyclical component of the labor market time series from raw data.
70,000
75,000
80,000
85,000
90,000
95,000
Ma
y-0
2S
ep-0
2Jan
-03
Ma
y-0
3S
ep-0
3Jan-0
4M
ay-0
4S
ep-0
4Jan
-05
Ma
y-0
5S
ep-0
5Jan
-06
Ma
y-0
6S
ep-0
6Jan
-07
Ma
y-0
7S
ep-0
7Jan
-08
Ma
y-0
8S
ep-0
8Jan
-09
Ma
y-0
9S
ep-0
9Jan
-10
Ma
y-1
0S
ep-1
0Jan
-11
Ma
y-1
1S
ep-1
1Jan
-12
Ma
y-1
2S
ep-1
2Jan
-13
Ma
y-1
3S
ep-1
3Jan
-14
Ma
y-1
4S
ep-1
4Jan
-15
Ma
y-1
5S
ep-1
5Jan
-16
Continuous PNAD - Employed Population (in thousands of occupations)
Source: IBGE, SEADE/DIEESE, MTE and Santander estimates
observed data seriesestimated data series
4
The deterioration in labor market conditions has been heavily affecting all regions and sectors in the Brazilian economy.
With this, one of the most severe consequences of the recessionary outlook has been the increase in employment informality. Indeed, labor informality has grown considerably since last year. Regarding the occupation breakdown, the
categories of “self-employed” and “domestic worker,” which account for around 30% of total employed population, had strong
growth in 2015, whereas the category of “employee in the private sector with a formal contract,” which accounts for nearly 40%
of total occupations, registered a sharp decline in the period. Due to the poor financial conditions of companies and a macro
environment full of uncertainties, we believe informality will continue to increase over the next two years.
The rising informality has been contributing to a decline in the average real wage in the Brazilian labor market, as the
groups of informal jobs have lower earnings than the groups comprising employees with a formal contract. Moreover, the
wages of hired workers in the formal labor market have been falling substantially, while the average wages of dismissed
workers continue to grow.
4.0
6.0
8.0
10.0
12.0
14.0
Au
g-0
2
Jan
-03
Jun
-03
No
v-0
3
Ap
r-04
Se
p-0
4
Fe
b-0
5
Jul-
05
Dec-0
5
Ma
y-0
6
Oct-
06
Ma
r-0
7
Au
g-0
7
Jan
-08
Jun
-08
Nov-0
8
Ap
r-09
Se
p-0
9
Fe
b-1
0
Jul-
10
Dec-1
0
Ma
y-1
1
Oct-
11
Ma
r-1
2
Au
g-1
2
Jan
-13
Jun
-13
Nov-1
3
Ap
r-14
Se
p-1
4
Fe
b-1
5
Jul-
15
Dec-1
5
PME PNAD
Unemployment Rate (%) - PNAD x PMEseasonally adjusted series
Source: IBGE and Santander estimates
PNAD estimated data series observed data series
-12.0
-8.0
-4.0
0.0
4.0
8.0
Mar-
13
May-1
3
Ju
l-1
3
Se
p-1
3
No
v-1
3
Ja
n-1
4
Mar-
14
May-1
4
Ju
l-1
4
Se
p-1
4
No
v-1
4
Ja
n-1
5
Mar-
15
May-1
5
Ju
l-1
5
Se
p-1
5
No
v-1
5
Ja
n-1
6
Employed Population by Type of Occupation3-Month Moving Average - % YoY
Employee in the private sector with a formal contract (38.7%)Employee in the private sector without a formal contract (10.9%)Domestic Worker (6.6%)Self-Employed (24.2%)Employee in the public sector (12.4%)
Source: National Household Sample Survey - PNAD / IBGENote: Relative weights are given in parenthesis (other smaller categories were not considered)
5
We also estimated the historical data series for the PNAD average real wage from 2002 to early 2012. As in the case of the
employed population and labor force, we developed a multiple regression with the cyclical components of the available labor
market surveys: PME, CAGED, and PED. The first two data sources showed the largest relative contributions to the short-term
dynamics, according to our calculations. (See Appendix 1.)
As published by PNAD, the average real wage grew only 0.2% in 2015, decelerating from 1.1% in 2014 and 3.1% in 2013, and,
based on our estimates, the average annual growth from 2004 to 2012 was 3.3%. In our view, real wages will continue to
weaken until mid-2017, given the sharp net destruction of formal jobs and increased informality of employment. We
forecast a 2.8% contraction in 2016, marking the first negative result since 2003.
The dismal performance of the employment and wage indicators, combined with tighter credit conditions, high
household debt, and lower levels of consumer confidence led private consumption into the negative territory last year. Focusing on the labor market, note the substantial retreat in aggregate real wages—employed population multiplied by the
average real wage—in the recent period. The average growth of this indicator inched down to 0.5% in 2015 from 2.6% in 2014
and from 5.3% for the 2004-2013 period, according to our estimates.
In addition to aggregate real wages, other sources of income have an important role in explaining the dynamics of household
consumption—namely, (i) Social Security benefits; (ii) unemployment insurance and salary bonuses; and (iii) Social Protection
benefits. Considering all these items—whose data are released by public institutions, such as the National Treasury—and
our own estimates for PNAD indicators, we built a monthly historical time series for aggregate real wages with social
benefits, which functions as a proxy for household income.
400
800
1,200
1,600
2,000
2,400
2,800
3,200
Public Sector Private Sectorwith a Formal
Contract
Self-Employed Private Sectorwithout a Formal
Contract
DomesticWorker
Dec-15
Dec-12
Source: National Household Sample Survey - PNAD / IBGE
Average Real Earning by Type of Occupation (BRL)
-3.0
-1.0
1.0
3.0
5.0
Jan
-12
Ma
r-1
2
Ma
y-1
2
Jul-
12
Se
p-1
2
Nov-1
2
Jan
-13
Ma
r-1
3
Ma
y-1
3
Jul-
13
Se
p-1
3
Nov-1
3
Jan
-14
Ma
r-1
4
Ma
y-1
4
Jul-
14
Se
p-1
4
Nov-1
4
Jan
-15
Ma
r-1
5
Ma
y-1
5
Jul-
15
Se
p-1
5
Nov-1
5
Jan
-16
Wages of Dismissed Workers
Wages of Hired Workers
Source: CAGED - Ministry of Employment and Labor
Wages of Hired Workers x Wages of Dismissed Workers% 12-Month Accumulated
1,300
1,400
1,500
1,600
1,700
1,800
1,900
2,000
Ma
r-0
2A
ug-0
2Ja
n-0
3Ju
n-0
3N
ov-0
3A
pr-
04
Se
p-0
4F
eb
-05
Ju
l-0
5D
ec-0
5M
ay-0
6O
ct-
06
Ma
r-0
7A
ug-0
7Ja
n-0
8Ju
n-0
8N
ov-0
8A
pr-
09
Se
p-0
9F
eb
-10
Ju
l-1
0D
ec-1
0M
ay-1
1O
ct-
11
Ma
r-1
2A
ug-1
2Jan-1
3Ju
n-1
3N
ov-1
3A
pr-
14
Se
p-1
4F
eb
-15
Ju
l-1
5D
ec-1
5
Source: IBGE, SEADE/DIEESE, MTE and Santander estimates
Continuous PNAD - Average Real Wage (BRL)
estimated data series observed data series
6
According to our calculations, all the ARWB components had continued growth from 2003 to 2014, even during the 2008
global financial crisis. Moreover, we highlight that SSB and UNI+SPB weights have become increasingly larger over that
period, especially the latter—the important contribution of the social program called “Bolsa Família”, for example—at the
expense of the ARW weight.
Nevertheless, ARWB dynamics worsened significantly last year. Regarding its breakdown, all the components showed a
decline in the recent period, in real terms; we used the National Consumer Price Index to deflate the nominal series. In our
view, the deep and prolonged recession combined with the sharp deterioration in public finances will keep real Social
Security and Social Protection benefits on a downward trend in upcoming quarters.
The negative outlook for aggregate real wages with social benefits supports our expectation that retail sales and
household consumption will not resume growth in 2016. We see some stabilization of these variables only by the end of
the year, mainly due to falling inflation and a slight improvement in consumer confidence. Therefore, we forecast that
broad real retail sales will contract around 6% this year (-8.6% in the previous year), whereas we expect Household
-03
00
03
06
09
12
Au
g-0
4
De
c-0
4
Ap
r-05
Au
g-0
5
De
c-0
5
Ap
r-06
Au
g-0
6
De
c-0
6
Ap
r-07
Au
g-0
7
De
c-0
7
Ap
r-08
Au
g-0
8
De
c-0
8
Apr-
09
Au
g-0
9
De
c-0
9
Ap
r-10
Au
g-1
0
De
c-1
0
Ap
r-11
Au
g-1
1
De
c-1
1
Ap
r-12
Au
g-1
2
De
c-1
2
Ap
r-13
Au
g-1
3
De
c-1
3
Ap
r-14
Au
g-1
4
De
c-1
4
Ap
r-15
Au
g-1
5
De
c-1
5
Aggregate Real Wages with Social Benefits3-Month Moving Average - % YoY
Source: Brazil Central Bank, IBGE, National Treasury, Ministry of Social Development and Santander estimates
Average Growth = 5.2%
Period ARW SSB UNI+SPB
2003 - 2006 81.9 15.3 2.8
2007 - 2009 80.6 15.7 3.7
2010 - 2013 79.8 15.9 4.3
2014 - 2015 79.1 16.3 4.7
Aggregate Real Wages with Social Benefits - Component Weights (%)
-6.0
-2.0
2.0
6.0
10.0
14.0
18.0
22.0
Jun-0
5S
ep-0
5D
ec-0
5M
ar-
06
Jun-0
6S
ep-0
6D
ec-0
6M
ar-
07
Jun-0
7S
ep-0
7D
ec-0
7M
ar-
08
Jun-0
8S
ep-0
8D
ec-0
8M
ar-
09
Jun-0
9S
ep-0
9D
ec-0
9M
ar-
10
Jun-1
0S
ep-1
0D
ec-1
0M
ar-
11
Jun-1
1S
ep-1
1D
ec-1
1M
ar-
12
Jun-1
2S
ep-1
2D
ec-1
2M
ar-
13
Jun-1
3S
ep-1
3D
ec-1
3M
ar-
14
Jun-1
4S
ep-1
4D
ec-1
4M
ar-
15
Jun-1
5S
ep-1
5D
ec-1
5
ARW SSB UNI+SPB
Aggregate Real Wages with Social Benefits by Component6-Month Moving Average - % YoY
Source: Brazil Central Bank, IBGE, National Treasury , Ministry of Social Dev elopment and Santander estimates
7
Consumption GDP to decline nearly 3.5%, following a contraction of 4.0% in 2015. (Household Consumption GDP
accounts for a little over 60% of total GDP.)
Labor Market Prognosis and Conclusions: It May Get Even Worse
As we present in this report, there are different sources of labor market data. In our view, the PNAD methodology
brings significant improvement to the analysis of the topic, especially due to the national coverage and the wider
definition of unemployment. Nevertheless, its short historical data series hinders the development of long-term analysis
and forecasts, so we used econometric methods to estimate the main PNAD indicators for a longer period, ranging from
2002 to early 2012. (The observed results of PNAD are for the period 2012-15.)
We think that all labor market indicators will continue to deteriorate until next year. The widespread contraction of
economic activity across sectors should lead to an additional net destruction of formal jobs in the period, in our opinion,
with the retail and services sectors showing the most negative contributions. Combined with this, the labor force should
remain on an upward trend, in our view, owing to the decline in household income. In other words, the Brazilian labor
market scenario may get even worse, with the unemployment rate peaking only in mid-1H17, in our opinion.
Considering more disaggregated data, note that the shares of informal occupations have grown rapidly, as have job
losses among heads of household, leading to negative effects on socioeconomic conditions, such as poorer qualification
levels, falling productivity, and lower potential growth.
The table below summarizes our forecasts for the main labor market variables:
-12
-08
-04
00
04
08
12
16
200
6Q
4
200
7Q
2
200
7Q
4
200
8Q
2
200
8Q
4
200
9Q
2
200
9Q
4
201
0Q
2
201
0Q
4
201
1Q
2
201
1Q
4
201
2Q
2
201
2Q
4
201
3Q
2
201
3Q
4
201
4Q
2
201
4Q
4
201
5Q
2
201
5Q
4
Aggregate Real Wages with Social Benefits (estimated)
Household Consumption GDP
Broad Retail Sales
Aggregate Real Wages with Social Benefits,Household Consumption GDP and Broad Retail Sales - % YoY
Source: Brazil Central Bank, IBGE, National Treasury, Ministry of Social Development and Santander estimates
Indicator 2015 2016F 2017F
Net Creation of Formal Jobs - million jobs (CAGED) -1.63 -1.44 0.23
Employed Population - million people 92.1 90.6 91.1
Employed Population - annual change (%) 0.0 -1.7 0.5
Labor Force - million people 100.7 102.8 104.1
Labor Force - annual change (%) 1.9 2.1 1.3
Unemployment Rate - annual average (%) 8.5 11.9 12.5
Unemployment Rate - end of period (%)* 9.9 12.8 13.3
Average Real Wage - BRL 1,963 1,908 1,889
Average Real Wage - annual change (%) -0.2 -2.8 -1.0
Aggregate Real Wages - BRL million 175,2 167,3 166,7
Aggregate Real Wages - annual change (%) 0.0 -4.5 -0.5
Source: National Household Sample Survey (PNAD), CAGED and Santander forecasts
* seasonally adjusted series
Forecasts for the Main Labor Market Indicators
8
Appendix 1
Notes:
(a) The normalized weights were calculated from the coefficient estimates of our econometric models.
(b) From March 2012 backward, the charts present our own estimates for the PNAD data series.
(c) Annual PNAD data were used to validate the long-term dynamics of the estimated data series.
I. PNAD Employed Population
II. PNAD Labor Force
PME
CAGED
PED
19.8
Normalized Weights (%)
55.7
24.5
-6.0
-4.0
-2.0
0.0
2.0
4.0
6.0
8.0
10.0
12.0
Ap
r-04
Au
g-0
4
Dec-0
4
Ap
r-05
Au
g-0
5
Dec-0
5
Ap
r-06
Au
g-0
6
Dec-0
6
Ap
r-07
Au
g-0
7
Dec-0
7
Ap
r-08
Au
g-0
8
Dec-0
8
Ap
r-09
Au
g-0
9
Dec-0
9
Ap
r-10
Au
g-1
0
Dec-1
0
Ap
r-11
Au
g-1
1
Dec-1
1
Ap
r-12
Au
g-1
2
Dec-1
2
Ap
r-13
Au
g-1
3
Dec-1
3
Ap
r-14
Au
g-1
4
Dec-1
4
Ap
r-15
Au
g-1
5
Dec-1
5
PNAD PME
PED CAGED
Employed Population - Different Labor Market SurveysYoY (%)
PNAD estimated data series Observed data series
Source: IBGE, SEADE/DIEESE, MTE and Santander estimates
PME
PME PED
CAGED
PED
19.81
Source: IBGE, SEADE/DIEESE and MTE
Normalized Weights (%)
Normalized Weights (%)
41.8
58.255.71
24.48
-3.0
-1.0
1.0
3.0
5.0
Ap
r-04
Au
g-0
4
Dec-0
4
Ap
r-05
Au
g-0
5
Dec-0
5
Ap
r-06
Au
g-0
6
Dec-0
6
Ap
r-07
Au
g-0
7
Dec-0
7
Ap
r-08
Au
g-0
8
Dec-0
8
Ap
r-09
Au
g-0
9
Dec-0
9
Ap
r-10
Au
g-1
0
Dec-1
0
Ap
r-11
Au
g-1
1
Dec-1
1
Ap
r-12
Au
g-1
2
Dec-1
2
Ap
r-13
Au
g-1
3
Dec-1
3
Ap
r-14
Au
g-1
4
Dec-1
4
Ap
r-15
Au
g-1
5
Dec-1
5
PNAD PME PED
Labor Force - Different Labor Market SurveysYoY (%)
Source: IBGE, SEADE/DIEESE, MTE and Santader estimates
PNAD estimated data series Observed data series
9
III. PNAD Unemployment Rate
80,000
85,000
90,000
95,000
100,000
105,000
Ma
r-0
2
Au
g-0
2
Jan
-03
Jun
-03
Nov-0
3
Ap
r-04
Se
p-0
4
Fe
b-0
5
Jul-
05
Dec-0
5
Ma
y-0
6
Oct-
06
Ma
r-0
7
Au
g-0
7
Jan
-08
Jun
-08
Nov-0
8
Ap
r-09
Se
p-0
9
Fe
b-1
0
Jul-
10
Dec-1
0
Ma
y-1
1
Oct-
11
Ma
r-1
2
Au
g-1
2
Jan
-13
Jun
-13
Nov-1
3
Ap
r-14
Se
p-1
4
Fe
b-1
5
Jul-
15
Dec-1
5
Continuous PNAD - Labor Force (in thousands of people)
Source: IBGE, SEADE/DIEESE and Santander estimates
observed data seriesestimated data series
Year Unemployment Rate (%) - annual average Unemployment Rate (%) - end of period*
2002 10.8 10.9
2003 11.0 11.3
2004 11.0 10.7
2005 10.3 10.0
2006 9.9 9.7
2007 9.1 9.2
2008 8.9 8.9
2009 8.7 8.6
2010 8.0 7.7
2011 7.7 7.4
2012 7.3 7.1
2013 7.2 6.8
2014 6.8 7.2
2015 8.3 9.9
2016F 11.9 12.8
2017F 12.5 13.3
Source: IBGE and Santander estimates and forecasts
* seasonally adjusted series
PNAD Unemployment Rate (%) - Entire National Territory - Estimates and Forecasts
10
IV. PNAD Average Real Wage
PME
CAGED
PED
Source: IBGE, SEADE/DIEESE and MTE
Normalized Weights (%)
46.2
35.7
18.1
-14.0
-10.0
-6.0
-2.0
2.0
6.0
10.0
14.0
Nov-0
4
Ma
r-05
Ju
l-0
5
Nov-0
5
Ma
r-06
Ju
l-0
6
Nov-0
6
Ma
r-07
Ju
l-0
7
Nov-0
7
Ma
r-08
Ju
l-0
8
Nov-0
8
Ma
r-09
Ju
l-0
9
Nov-0
9
Ma
r-10
Ju
l-1
0
Nov-1
0
Ma
r-11
Ju
l-1
1
Nov-1
1
Ma
r-12
Ju
l-1
2
Nov-1
2
Ma
r-13
Ju
l-1
3
Nov-1
3
Ma
r-14
Ju
l-1
4
Nov-1
4
Ma
r-15
Ju
l-1
5
Nov-1
5
PNAD PME
SEADE CAGED
Source: IBGE and Santander estimates
Average Real Wage - Different Labor Market SurveysYoY (%)
PNAD estimated data series Observed data series
Year
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016F
2017F
Average Real Wage (BRL) Average Real Wage - Annual Growth (%)
Source: IBGE and Santander estimates and forecasts
1,593
1,635
1,665
1,739
1,794
1,442
1,405
1,423
1,473
1,548
0.2
-2.8
1,881
1,940
1,961
1,964
1,909
-1.0
PNAD Average Real Wage - Estimates and Forecasts
1,890
-
-2.6
1.3
3.5
5.1
2.9
2.6
1.9
4.4
3.2
4.8
3.2
1.1
11
V. PNAD Aggregate Real Wages
90
100
110
120
130
140
150
160
170
180
190
Ma
r-0
2A
ug-0
2Ja
n-0
3Ju
n-0
3N
ov-0
3A
pr-
04
Se
p-0
4F
eb
-05
Ju
l-0
5D
ec-0
5M
ay-0
6O
ct-
06
Ma
r-0
7A
ug-0
7Ja
n-0
8Ju
n-0
8N
ov-0
8A
pr-
09
Se
p-0
9F
eb
-10
Ju
l-1
0D
ec-1
0M
ay-1
1O
ct-
11
Ma
r-1
2A
ug-1
2Ja
n-1
3Ju
n-1
3N
ov-1
3A
pr-
14
Se
p-1
4F
eb
-15
Ju
l-1
5D
ec-1
5
Source: IBGE, SEADE/DIEESE, MTE and Santander estimates
Continuous PNAD - Aggregate Real Wages (BRL billion)
estimated data series observed data series
12
CONTACTS / IMPORTANT DISCLOSURES
Macro Research Maciej Reluga* Head Macro, Rates & FX Strategy – CEE [email protected] 48-22-534-1888 Sergio Galván* Economist – Argentina [email protected] 54-11-4341-1728 Maurício Molan* Economist – Brazil [email protected] 5511-3012-5724 Juan Pablo Cabrera* Economist – Chile [email protected] 562-2320-3778 Brendan Hurley Economist - Colombia [email protected] 212-350-0733 David Franco* Economist – Mexico [email protected] 5255 5269-1932 Tatiana Pinheiro* Economist – Peru [email protected] 5511-3012-5179 Piotr Bielski* Economist – Poland [email protected] 48-22-534-1888 Marcela Bensión* Economist – Uruguay [email protected] 5982-1747-5537
Fixed Income Research David Duong Macro, Rates & FX Strategy – Brazil, Peru [email protected] 212-407-0979 Brendan Hurley Macro, Rates & FX Strategy – Colombia, Mexico [email protected] 212-350-0733 Juan Pablo Cabrera* Chief Rates & FX Strategist – Chile [email protected] 562-2320-3778 Nicolas Kohn* Macro, Rates & FX Strategy - LatAm [email protected] 4420-7756-6633 Aaron Holsberg Head of Credit Research [email protected] 212-407-0978
Equity Research Christian Audi Head LatAm Equity Research [email protected] 212-350-3991 Andres Soto Head, Andean [email protected] 212-407-0976 Walter Chiarvesio* Head, Argentina [email protected] 5411-4341-1564 Valder Nogueira* Head, Brazil [email protected] 5511-3012-5747 Pedro Balcao Reis* Head, Mexico [email protected] 5255-5269-2264
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