The aftermath of 2008 turmoil on Brazilian economy: tsunami or “marolinha”?

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The Aftermath of 2008 Turmoil on Brazilian

Economy: Tsunami or “Marolinha”?

Emerson Fernandes Marçal Ronan Cunha Giovanni Merlin

Oscar Simões

CEMAP-EESP-FGV

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Talking points

Motivation and Goals

Methodology

Empirical Strategy

Results

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Motivation

• "September and October of 2008 was the worst financial crisis in global history, including the Great Depression." - Ben Bernanke

• Economists agree that the Financial events in 2008 was an unexpected, severe and global incident.

• It had global impacts on stocks prices, trade flows, economic activity among others.

• Unexpected rare negative shocks may cause great impacts on economic activity and turns on additional propagation

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Motivation

• Economists agree that the Financial events in 2008 was an

unexpected, severe and global incident.

• It had global impacts on stocks prices, trade flows, economic activity among others.

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Motivation

• It had global impacts on stocks prices, trade flows, economic

activity among others.

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Motivation

• It had global impacts on stocks prices, trade flows, economic

activity among others.

• Unexpected rare negative shocks may cause great impacts on

economic activity and turns on additional propagation mechanisms.

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But at the time

• When asked about what would be the effects of 2008 turmoil

on Brazilian Economy, Brazilian president at the time, Luis Inacio Lula da Silva, stated in São Bernardo do Campo the following:

• “Lá (nos EUA), ela é um tsunami. Aqui, se ela chegar, vai chegar uma marolinha que não dá nem para esquiar.” link

• “There (in USA), the crisis has a dimension of a tsunami. Here, if it gets here, it will look like a “marolinha” that you can not even surf.” (October 4th, 2008)

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But at the time

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But at the time

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“Marola” looks like this

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Objectives

• We want to test whether U.S downturn had an impact on

Brazilian economic activity, measured by its Industrial Production.

• Analyze if the magnitude can be seen as unusual, that is, if this unexpected shock turns on additional propagation mechanisms.

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Objectives

• We want to test whether U.S downturn had an impact on

Brazilian economic activity, measured by its Industrial Production.

• Analyze if the magnitude can be seen as unusual, that is, if

this unexpected shock turns on additional propagation mechanisms.

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Counterfactual Analysis

• We have to construct two scenario:

• First scenario with no effect at all on Brazilian economy;

• Second scenario contains the expected effect of a “normal” downturn on Brazilian economy;

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Counterfactual Analysis

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Counterfactual Analysis

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Counterfactual Analysis

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Options in the literature

• Counterfactual:

• Synthetic control method (Abadie and Gardeazabal, 2003), Abadie at al., 2012).

• Tests of Policy Ineffectiveness in the context of a Rational Expectations Model with and without dynamics (Pesaran and Smith, 2014 and Pesaran and Smith, 2016);

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Options in the literature

• Counterfactual:

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Options in the literature

• Counterfactual:

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How to run a counterfactual analysis?

• We apply the Policy Ineffectiveness Test by Pesaran and

Smith (2014).

• Rational Expectation model:

A0   ipbrat ratet psdt  = K1 ∑ k=1 A1kEt     ipbrat+k ratet+k psdt+k    + K2 ∑ k=1 A2k   ipbrat−k ratet−k psdt−k  + K3 ∑ k=0 A3k ipusat−k fedt−k +ut, (1)

• where ipbra is the Brazilian industrial production logarithm growth, rate is the logarithm Brazilian ex-post real interest rate, psd is the first difference of the Brazilian real Public Sector Deficit, piusa and fed are the American industrial production logarithm growth and logarithm of T-bill.

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How to run a counterfactual analysis?

Smith (2014).

• where ipbra is the Brazilian industrial production logarithm growth, rate is the logarithm Brazilian ex-post real interest rate, psd is the first difference of the Brazilian real Public Sector Deficit, piusa and fed are the American industrial production logarithm growth and logarithm of T-bill.

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How to run a counterfactual analysis?

Smith (2014).

• where ipbra is the Brazilian industrial production logarithm

growth, rate is the logarithm Brazilian ex-post real interest rate, psd is the first difference of the Brazilian real Public Sector Deficit, piusa and fed are the American industrial production logarithm growth and logarithm of T-bill.

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Solving RE model

• Under ordinary assumptions, the RE model has the unique

solution given by   pibrat ratet psdt  = K2 ∑ k=1 Φ2k   pit−k ratet−k psdt−k  + K3 ∑ k=0 Ψ3k piusat−k fedt−k + Γut, (2)

• where Φand Ψ are the matrix with the parameters of the endogenous and exogenous variables, respectively and Γis the matrix linking the shocks to endogenous variables;

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Solving RE model

• Under ordinary assumptions, the RE model has the unique

solution given by   pibrat ratet psdt  = K2 ∑ k=1 Φ2k   pit−k ratet−k psdt−k  + K3 ∑ k=0 Ψ3k piusat−k fedt−k + Γut, (2)

• where Φand Ψ are the matrix with the parameters of the

endogenous and exogenous variables, respectively and Γis the matrix linking the shocks to endogenous variables;

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Test of Ineffectiveness of the treatment:

• The Policy Ineffectiveness Test statistic is given by

τd ,H= ¯ ˆ dH( ˆθ) q ˆ ωq2+ ˆωx2 H = 1 H∑ H j=1(ipbrat+j−ipbraˆ t+j) q ˆ ω2q+ ˆω2x H , (3)

• whereipbra is the Brazilian industrial production logarithmˆ growth forecast and ˆω_q2 and ˆω_x2 are uncertainties related to the estimators of the endogenous and exogenous variables,

respectively.

• Assuming that the error uT0+h are normally distributed, then

as T → ∞, τd ,H→dN(0, 1).

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Test of Ineffectiveness of the treatment:

• whereipbra is the Brazilian industrial production logarithmˆ

growth forecast and ˆω_q2 and ˆω_x2 are uncertainties related to the estimators of the endogenous and exogenous variables,

respectively.

as T → ∞, τd ,H→dN(0, 1).

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Test of Ineffectiveness of the treatment:

respectively.

as T → ∞, τd ,H→dN(0, 1).

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Test of Ineffectiveness of the treatment:

respectively.

as T → ∞, τd ,H→dN(0, 1).

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Data

• Monthly variables from January 1996 till June 2009.

• Brazilian variables: Industrial production growth (pibra), the base interest rate Selic (rate) and the Public Sector Deficit (psd).

• The exogenous policy variable is the American adjusted industrial production (piusa) and T-bill rate (fed).

• We follow NBER dates for US Business Cycles that estimates the decline of the US economy due to Subprime financial crisis from December 2007 till June 2009.

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Data

• Brazilian variables: Industrial production growth (pibra), the

base interest rate Selic (rate) and the Public Sector Deficit (psd).

• The exogenous policy variable is the American adjusted industrial production (piusa) and T-bill rate (fed).

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Data

• The exogenous policy variable is the American adjusted

industrial production (piusa) and T-bill rate (fed).

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Data

• The exogenous policy variable is the American adjusted

industrial production (piusa) and T-bill rate (fed).

• We follow NBER dates for US Business Cycles that estimates

the decline of the US economy due to Subprime financial crisis from December 2007 till June 2009.

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Defining treatment period

• We follow NBER that dates for US Business Cycles;

• They define the period from December 2007 till June 2009 as a recession.

• In the middle, in 2008, this period US economy was hit by subprime financial events;

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Defining treatment period

• They define the period from December 2007 till June 2009 as

a recession.

• In the middle, in 2008, this period US economy was hit by subprime financial events;

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Defining treatment period

• They define the period from December 2007 till June 2009 as

a recession.

• In the middle, in 2008, this period US economy was hit by

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Empirical Strategy: First Step

• First we evaluate if there Brazilian economy was linked to US

macroeconomic variables before the treatment; • For this task we ran (Hendry and Doornik, 2014):

• General Unrestricted Model has 12 lags of each variable

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Empirical Strategy: First Step

macroeconomic variables before the treatment;

• For this task we ran (Hendry and Doornik, 2014):

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Empirical Strategy: First Step

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Empirical Strategy: First Step

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Empirical Strategy: Second Step

• In the second step we test the hypothesis that Brazil was not

affected at all by US downturn;

• We ran the policy effectiveness test to evalutate for the period from from December 2007 till June 2009;

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Empirical Strategy: Second Step

• In the second step we test the hypothesis that Brazil was not

affected at all by US downturn;

• We ran the policy effectiveness test to evalutate for the period

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Empirical Strategy: Third Step

• Finally we run as instability test to evaluate whether

pre-intervention structure remained stable after the intervention;

• For this task we ran: • Chow [1960] test

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Empirical Strategy: Third Step

• For this task we ran:

• Chow [1960] test

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Empirical Strategy: Third Step

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Empirical Strategy: Third Step

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Let’s look at the intervention

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Our final model:

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Testing for effectiveness of the “treatment”:

Table:τ statistic Date d¯ˆ_H( ˆθ_Tt0) τ P-value 2008(10) -0.080% -0.065 0.474 2008(11) -0.633% -0.645 0.259 2008(12) -1.668% -2.096 0.018 2009(1) -1.341% -2.144 0.016 2009(2) -1.083% -2.179 0.015 2009(3) -1.306% -3.550 0.000 2009(4) -0.754% -2.764 0.003 2009(5) -0.891% -5.023 0.000 2009(6) -0.778% -7.260 0.000

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Testing for structural instability

Test Statistic P-value

Forecast Chi2(19) 79.091 0.000

Chow F(19,116) 3.452 0.000

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Testing the effect of the crisis

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The aftermath of Brazilian downturn:

• We estimate that Brazilian Industrial Production drop by

nearly -9.34% on year rate basis from 2007M12 till 2009M6 using Pesaran and Smith (2014) methodology.

• Rejecting the null hypothesis means that there was a structural break in Brazilian DGP;

• Our counterfactual of no contagion suggests that the loss of -6,34% on an annual rate..

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The aftermath of Brazilian downturn:

• Rejecting the null hypothesis means that there was a

structural break in Brazilian DGP;

• Our counterfactual of no contagion suggests that the loss of -6,34% on an annual rate..

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The aftermath of Brazilian downturn:

• Rejecting the null hypothesis means that there was a

structural break in Brazilian DGP;

• Our counterfactual of no contagion suggests that the loss of

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Conclusions

• Brazilian production index is linked to US macroeconomic

variable in the period previous to 2007;

• There is evidence that Brazil was affected by US downturn in the period from 2007M12 till 2009M6;

• We collect evidence that financial turmoil of 2008 turned on additional propagation mechanism on Brazilian economy activity.

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Conclusions

• There is evidence that Brazil was affected by US downturn in

the period from 2007M12 till 2009M6;

• We collect evidence that financial turmoil of 2008 turned on additional propagation mechanism on Brazilian economy activity.

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Conclusions

• There is evidence that Brazil was affected by US downturn in

the period from 2007M12 till 2009M6;

• We collect evidence that financial turmoil of 2008 turned on

additional propagation mechanism on Brazilian economy activity.