observatory on exchange rate - eesp...

CEMAP: Observatory on Exchange Rate: Misalignment Assessment Empirical Illustration Future Challenges

Observatory on Exchange Rate

Emerson Fernandes Marçal

CEMAP-EESP-FGV

Talking pointsCEMAP:

Forecast Lab:Time Series Reconstruction:

Observatory on Exchange Rate:Recent Releases:

Misalignment AssessmentWhy do we have a preferred methodology?

Traditional Behavioral Exchange Rate ApproachAddressing Important Econometric Issues

Our approach: Joint Modeling (JMA)Why exchange misalignment can differ.

Empirical IllustrationDatabase DescriptionBrazilian Case:Australian Case:

Future ChallengesMapping Real Effective Exchange rate into bilateral realexchange rate

Projects

• Observatory on Exchange Rate:• Foster research on Exchange Rate Equilibrium Models and its

relationship with trade issues;

• Forecast Lab:• Joint project with CEQEF;• Test and develop forecast techniques to Brazilian

Macroeconomic and Financial series;

• Reconstruction and evaluating compatibility of historical datausing Econometric techniques:

• PNAD reconstruction from 1970 up to now.

Projects

CEMAP:Forecast Lab:Time Series Reconstruction:

Forecast Lab

• Site - www.cemap.fgv.br;

• Social Medias;

• Our Publications:• CEMAP Short Notes on economic activity, inflation and

exchange rate (link);

• CEMAP Letters (link);

• CEMAP Working Papers (link);

Forecast Lab

• Social Medias;

Forecast Lab

• Social Medias;

Forecast Lab

• Social Medias;

Forecast Lab

• Social Medias;

Forecast Lab

• Many scholar paper published on peer review journals andconferences:

• Applied Economics; Economic Studies (USP); J. ofForecasting;

• ESEM, IAAE, Oxmetrics User Conference, BCB;

• Mini-courses on the subject;

• Papers on on methodological evaluation of forecast tecniques:• inflation, credit volume and default rates, GDP, industrial

production;

• FAPESP, CNPQ grants;

Forecast Lab

production;

Forecast Lab

production;

Forecast Lab

production;

Estimate of Historical Unemployment Rate

Unemployment Rate - PNAD

1980 1985 1990 1995 2000 2005 2010 2015

14Unemployment Rate - PNAD

Observatory on Exchange Rate: Some Facts

• First Release of Exchange Rate Estimates were 2010 inCEMAP’s Letter number 2;

• In 2013 Observatory on Exchange Rate was officially created;

• Two years grant from IPEA (2013-2014);

• One year grant from BNDES (2014);

• Three years grant from WTO Chair (2015-2017);

• Three years from FGV (2015-2017);

Observatory in Action:

• Releases Estimates of Exchange Rate Misalignment in aMonthly Basis;

• A Series of Working Papers on the subject;

• Peer Review Papers Published on Economic Journals;

• Papers discussed with Staff of Peterson Institute, IMF, WorldBank, BCB and private financial institutions;

• Papers presented and discussed in Conferences such as IAAF,EMG-ECB, LAMES, Oxmetrics Users, Petersen Institute.

Researchers:

• Emerson Fernandes Marçal (CEMAP);• Vera Thorstensen (CCGI)• Beatrice Zimmerman (World Bank);• Diogo de Prince (CEMAP - UNIFESP);• Giovanni Merlin (PhD candidate, EESP);• Rafael Mouallem Rosa (PhD candidate, EESP);• Ronan Cunha (PhD candidate, EESP);• Oscar Simões (PhD candidate, EAESP).

Brazilian Case: Average

Real Effective Exchange Rate Fundamentals

1980 1985 1990 1995 2000 2005 2010 2015

Average Exchange Rate Misalignment

1980 1985 1990 1995 2000 2005 2010 2015

Average Exchange Rate Misalignment

Brazilian Case: Preferred MethodologyFundamentals: ToT, NFA, BS and TB.

Real Effective Exchange Rate

1980 1985 1990 1995 2000 2005 2010 2015

Exchange Rate Misalignment-RER TB NFA BS TOT

1980 1985 1990 1995 2000 2005 2010 2015

Brazilian Case: Preferred MethodologyFundamentals: ToT, NFA, BS and TB.

1980 1985 1990 1995 2000 2005 2010 2015

Misalignment Decomposition:Fundamentals and Solvency Issues.

Exchange Rate Misalignment-RER NFA TB-NFA Disequilibrium Contribution

Fundamentals Contribution

1980 1985 1990 1995 2000 2005 2010 2015

Exchange Rate Misalignment-RER NFA TB-NFA Disequilibrium Contribution

Fundamentals Contribution

North American Case:Fundamentals: NFA, and TB.

1975 1980 1985 1990 1995 2000 2005 2010 2015

Exchange Rate Misalignment

1975 1980 1985 1990 1995 2000 2005 2010 2015

40Exchange Rate Misalignment

Australian Case:Fundamentals: ToT, NFA, BS-PIB and TB.

1975 1980 1985 1990 1995 2000 2005 2010 2015

Exchange Rate Misalignment

1975 1980 1985 1990 1995 2000 2005 2010 2015

20 Exchange Rate Misalignment

Summary:

• Real (R$) compared to its basket has reached its equilibrium;

• Dolar (US$) compared to its basket is strongly overvalued;

• Australian Dolar (AUD$) is weakly overvalued.

Summary:

Basic Equilibrium Equation for RER.• From many intertemporal macroeconomic models it’s possible to obtain

the following steady state equations

RER = −φ tb+λX (1)

• equation (1) shows that if a country can run a trade deficit in equilibriumthe RER has to appreciate ;

• The term X accounts for any other factor affecting equilibrium RealEffective Exchange Rate (RER) such as Balassa-Samuelson effect, termsof trade, government consumption, trade and financial openness amongothers;

tb = −r ∗NFA (2)

• equation (2) shows that a country can run a trade deficits if revenuesfrom NFA are large enough;

Basic Equilibrium Equation for RER.• From many intertemporal macroeconomic models it’s possible to obtain

the following steady state equations

RER = −φ tb+λX (1)

• equation (1) shows that if a country can run a trade deficit in equilibriumthe RER has to appreciate ;

• The term X accounts for any other factor affecting equilibrium RealEffective Exchange Rate (RER) such as Balassa-Samuelson effect, termsof trade, government consumption, trade and financial openness amongothers;

tb = −r ∗NFA (2)

• equation (2) shows that a country can run a trade deficits if revenuesfrom NFA are large enough;

A brief description of traditional BEER approach

• Fundamental Real exchange rate is calculated using an econometricmodel (based on (2)):Applications: Faruquee (1994, IMF), Clark (1999), Ubide (1999) andKubota (2009)

• Cointegration techniques based on selected series associated withfundamentals ;

• Econometric Questions:

• Detect long run relationship - cointegration analysis;• Different set of fundamentals can be tested;

• Perform permanent and transitory decomposition to better understandthe adjustment towards equilibrium;

• Gonzalo and Granger decomposition is the most common choice;

Our starting point

• We assume for simplicity that DGP for the variables trade balance,real effective exchange rate and net foreign asset position andfundamentals is given by the following vector autoregressive model:

∆Yt = Γ1∆Yt−1 + ...+Γk−1∆Yt−k+1 +αβ′Y t−1 +µ + εt (3)

• Instead of arbitrarily ignoring trade balance information andestimate (2), we jointly estimate (2) and (1).

• We use long run restrictions suggested by the theory to validate theexchange rate misalignment estimate;

Our starting point

Transitory and Permanent components

• Using the parameters from (3), it is possible to calculate the transitory (Tit)and permanent (Pit) components from the following equations:

Pt = β⊥(α′⊥β⊥)

−1α′⊥Yt (4)

Tt = α(β ′α)−1

β′Yt (5)

• Assuming that the real exchange rate is in the first position of the vector, andusing the value of the error correction mechanism centered on their own means,we can calculate the misalignment using the following equation, then:

mist ≡ F 1(β′1Yt −E([β ′

1Yt ])+F 2(β′2Y t −E([β ′

2Yt ]) (6)

where [ V1 V2 ] = (β ′α)−1 and Vi has dimension 2x1

F ≡ [F1F2] = [ [ 1 0 ... 0 ][ α1 α2 ]V1 [ 1 0 ... 0 ][ α1 α2 ]V2 ].

Transitory and Permanent components

• Using the parameters from (3), it is possible to calculate the transitory (Tit)and permanent (Pit) components from the following equations:

Pt = β⊥(α′⊥β⊥)

−1α′⊥Yt (4)

Tt = α(β ′α)−1

β′Yt (5)

• Assuming that the real exchange rate is in the first position of the vector, andusing the value of the error correction mechanism centered on their own means,we can calculate the misalignment using the following equation, then:

mist ≡ F 1(β′1Yt −E([β ′

1Yt ])+F 2(β′2Y t −E([β ′

2Yt ]) (6)

where [ V1 V2 ] = (β ′α)−1 and Vi has dimension 2x1

F ≡ [F1F2] = [ [ 1 0 ... 0 ][ α1 α2 ]V1 [ 1 0 ... 0 ][ α1 α2 ]V2 ].

Adapting Blinder-Oaxaca decomposition:

• Blinder-Oaxaca decomposition.

misJMAi ,t −misBEER

i ,t = (hJMA

1hBEER

1−1)(hBEER

1 f BEER1,t )︸︷︷︸

Less weight on what we knew

+hJMA1 (f JMA

1,t − f BEER1,t )+hJMA

2 f JMA2,t︸︷︷︸

What we learn from new model

Adapting Blinder-Oaxaca decomposition:

• If cointegrated relationships are properly identified:

f JMA1,t − f BEER

1,tp→ 0 (8)

• Both models are nested and it is interesting to investigatewhether

• hJMA1

hBEER1

= 1• hJMA

2 = 0.

Conditions to guarantee hJMA2 = 0

• Weight of GG decomposition are given by:

1 hJMA2

]= α(β ′

α)−1 =

[α11 α21α12 α22

](β ′

1α1 β ′1α2

β ′2α1 β ′

)−1(9)

• If β ′1α2 = 0 and α21 = 0 then hJMA

2 = 0.• Note that α21 = 0 is not sufficient to guarantee hJMA

2 = 0.

Example when hJMA2 = 0

• Assume that:

α′=

[α11 ab32 −a α41 α510 α21 α31 α41 α51

β′ =

[1 0 b31 b41 b510 1 b32 0 0

• Then β ′1α2 = 0 and α21 = 0 and so hJMA

2 = 0.

Example when (hJMA

1hBEER

1−1) = 0 and hJMA

• Assume that:

α′=

[α11 0 0 0 00 0 α31 α41 α51

β′ =

[1 0 b31 b41 b510 1 b32 0 0

• Then (hJMA

1hBEER

1−1) = 0 and hJMA

2 = 0. Note also thathJMA

1 = hBEER1 = 1

Database descriptionVariable Source Definition

Real EffectiveExchange Rate

IMF andBIS

Weighted Average of Real exchange ratebased on Consumer price index (RERi ,t).

IMF andBIS

Trade balance asShare of GDP

IMF andWB

Ratio of trade balance and GDP (TBi ,t)

IMF andBIS

IMF andWB

Relative per capitaincome

WB BSPIBi ,t =Percapita Indexii ,t

∑Ni=1 wi Percapita Indexj,t

IMF andBIS

IMF andWB

Relative terms oftrade

IMF Toti ,t =ToTi ,t

∑Ni=1 wi ToT j,t

IMF andBIS

IMF andWB

∑Ni=1 wi ToT j,t

Net Foreign AssetPosition

Milesi eFerreti andIMF

Ratio of Net Foreign Asset Position andGDP (NFAi ,t)

IMF andBIS

IMF andWB

∑Ni=1 wi ToT j,t

Net Foreign AssetPosition

Milesi eFerreti andIMF

Ratio of Net Foreign Asset Position andGDP (NFAi ,t)

Relative price ratio IMF BSi ,t =WSPi ,tIPCi ,t

∑Ni=1 wi

WSPi ,tCPIi ,t

Are TB and NFA cointegrated?Countries Rank Eigenvalues Trace p-value

Australia r=0 0.345 18.596 0.3% ***

r=1 0.000 0.012 95.1%

Austria r=0 0.111 8.011 23.7%

r=1 0.062 2.812 10.9%

Brazil r=0 0.264 13.729 2.8% **

r=1 0.006 0.258 68.4%

China r=0 0.139 9.137 16.2%

r=1 0.056 2.539 13.0%

Colombia r=0 0.150 7.795 25.5%

r=1 0.015 0.649 48.4%

Denmark r=0 0.207 12.114 5.3% *

r=1 0.042 1.906 19.6%

Finland r=0 0.288 17.649 0.5% ***

r=1 0.060 2.715 11.6%

Germany r=0 0.153 8.286 21.7%

r=1 0.022 0.991 37.2%

Greece r=0 0.174 10.263 10.8%

r=1 0.041 1.862 20.2%

Ireland r=0 0.129 6.453 38.4%

r=1 0.008 0.365 61.7%

Italy r=0 0.214 10.686 9.2% *

r=1 0.002 0.080 84.0%

Japan r=0 0.273 17.607 0.5% ***

r=1 0.078 3.578 6.8% *

Korea r=0 0.303 17.730 0.5% ***

r=1 0.050 2.202 16.2%

Mexico r=0 0.195 9.527 14.1%

r=1 0.000 0.000 99.3%

Netherland r=0 0.057 2.682 87.2%

r=1 0.003 0.111 80.6%

New Zeland r=0 0.244 12.036 5.5% *

r=1 0.000 0.014 94.4%

New Zeland r=0 0.244 12.036 5.5% *

r=1 0.000 0.014 94.4%

Norway r=0 0.268 13.828 2.7% **

r=1 0.003 0.128 78.9%

Portugal r=0 0.125 6.313 40.0%

r=1 0.017 0.729 45.4%

Singapore r=0 0.255 13.048 3.7% **

r=1 0.003 0.114 80.3%

Spain r=0 0.373 20.764 0.1% ***

r=1 0.006 0.246 69.2%

Sweden r=0 0.218 12.338 4.9% **

r=1 0.034 1.510 25.7%

Sweden r=0 0.218 12.338 4.9% **

r=1 0.034 1.510 25.7%

Switzerland r=0 0.063 2.973 83.9%

r=1 0.002 0.109 80.8%

Turkey r=0 0.205 10.776 8.9% *

r=1 0.015 0.661 47.9%

United Kingdom r=0 0.212 11.743 6.2% *

r=1 0.029 1.276 30.3%

United States r=0 0.074 6.501 37.9%

r=1 0.068 3.105 9.1% *

Uruguay r=0 0.194 10.280 10.7%

r=1 0.018 0.798 43.0%

Summary of evidence for TB and NFA:

• Evidence of cointegration between TB and NFA for good number of variables.

• The number of rejection taking into account the size of the sample is quitegood;

Summary of evidence for TB and NFA:

• Evidence of cointegration between TB and NFA for good number of variables.

• The number of rejection taking into account the size of the sample is quitegood;

What we have learned from the model with TB:

From REER to bilateral real exchange rate:

• After some algebra it is possible to convert RER misalignmentestimates into bilateral estimates;

Bilateral estimates:

AU IT SW

AS JP SZ

BE KR UK

BR ME US

2005 2010 2015

50 AU IT SW

AS JP SZ

BE KR UK

BR ME US

But nominal variable may matter:

• After some algebra it is possible to convert REERmisalignment estimates into bilateral real estimates;

• Under certain statistical conditions it may be possible tomodel nominal variables as marginal models;

• It would be possible to address how nominal shocks in interestrate and-or inflation affect real exchange rate andmisalignment;

• No preliminary results to show but probably next seminar!

Dealing with mixed frequency:

• Variables are available in different frequency (daily, monthly,quarterly, etc);

• How to adapt the methodology to deal with fact in anefficient way;

That’s all.

observatory on exchange rate - eesp...

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