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*

rodolfo.silva@santander.com.br

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 maciej.reluga@bzwbk.pl 48-22-534-1888 Sergio Galván* Economist – Argentina sgalvan@santanderrio.com.ar 54-11-4341-1728 Maurício Molan* Economist – Brazil mmolan@santander.com.br 5511-3012-5724 Juan Pablo Cabrera* Economist – Chile jcabrera@santander.cl 562-2320-3778 Brendan Hurley Economist - Colombia bhurley@santander.us 212-350-0733 David Franco* Economist – Mexico dafranco@santander.com.mx 5255 5269-1932 Tatiana Pinheiro* Economist – Peru tatiana.pinheiro@santander.com.br 5511-3012-5179 Piotr Bielski* Economist – Poland piotr.bielski@bzwbk.pl 48-22-534-1888 Marcela Bensión* Economist – Uruguay mbension@santander.com.uy 5982-1747-5537

Fixed Income Research David Duong Macro, Rates & FX Strategy – Brazil, Peru dduong@santander.us 212-407-0979 Brendan Hurley Macro, Rates & FX Strategy – Colombia, Mexico bhurley@santander.us 212-350-0733 Juan Pablo Cabrera* Chief Rates & FX Strategist – Chile jcabrera@santander.cl 562-2320-3778 Nicolas Kohn* Macro, Rates & FX Strategy - LatAm nicolas.kohn@santandergbm.com 4420-7756-6633 Aaron Holsberg Head of Credit Research aholsberg@santander.us 212-407-0978

Equity Research Christian Audi Head LatAm Equity Research caudi@santander.us 212-350-3991 Andres Soto Head, Andean asoto@santander.us 212-407-0976 Walter Chiarvesio* Head, Argentina wchiarvesio@santanderrio.com.ar 5411-4341-1564 Valder Nogueira* Head, Brazil jvalder@santander.com.br 5511-3012-5747 Pedro Balcao Reis* Head, Mexico pbalcao@santander.com.mx 5255-5269-2264

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