commodity prices and the business cycle in latin america ... · dependence: policy challenges and...

COMMODITY PRICES AND THE BUSINESS CYCLE IN LATIN AMERICA:LIVING AND DYING BY COMMODITIES?

Maximo Camacho and Gabriel Perez-Quiros

Documentos de Trabajo N.º 1304

2013

COMMODITY PRICES AND THE BUSINESS CYCLE IN LATIN AMERICA:

LIVING AND DYING BY COMMODITIES?

Documentos de Trabajo. N.º 1304

2013

(*) Part of the paper was written when the authors worked as consultants for the Latin America and the Caribbean Division of the World Bank. We thank Riccardo Trezzi, O. Calvo-González and R. Shankar for graciously sharing their data on commodity prices, the editor and two anonymous referees for their suggestions, and Andreea Popescu for her research assistance. We also thank seminar participants in the Workshop “Myths and Realities of Commodity Dependence: Policy Challenges and Opportunities for Latin America and the Caribbean”, especially John Nash, Emily Sinnott and Chris Papageorgiou, who provided for an excellent discussion. M. Camacho would like to thank CICYT (ECO2010-19830) for their financial support. The views in this paper are those of the authors and do not represent the views of the Banco de España, the Eurosystem or the World Bank.

Maximo Camacho

UNIVERSIDAD DE MURCIA

Gabriel Perez-Quiros

BANCO DE ESPAÑA AND CEPR

COMMODITY PRICES AND THE BUSINESS CYCLE IN LATIN

AMERICA: LIVING AND DYING BY COMMODITIES? (*)

The Working Paper Series seeks to disseminate original research in economics and fi nance. All papers have been anonymously refereed. By publishing these papers, the Banco de España aims to contribute to economic analysis and, in particular, to knowledge of the Spanish economy and its international environment.

The opinions and analyses in the Working Paper Series are the responsibility of the authors and, therefore, do not necessarily coincide with those of the Banco de España or the Eurosystem.

The Banco de España disseminates its main reports and most of its publications via the INTERNET at the following website: http://www.bde.es.

Reproduction for educational and non-commercial purposes is permitted provided that the source is acknowledged.

© BANCO DE ESPAÑA, Madrid, 2013

ISSN: 1579-8666 (on line)

Abstract

We analyze the dynamic interactions between commodity prices and output growth of the

seven biggest Latin American exporters: Argentina, Brazil, Colombia, Chile, Mexico, Peru

and Venezuela. Using a novel defi nition of Markovswitching impulse response functions,

we fi nd that the response of their respective output growth to commodity price shocks

is time-dependent, size-dependent and sign-dependent. Overall, the major evidence

of asymmetries in output growth responses occurs when commodity price shocks lead

to regime shifts. Accordingly, we consider that the design of optimal counter-cyclical

stabilization policies in this region should take into account that the reactions of economic

activity vary considerably across business cycle regimes.

Keywords: commodities, business cycle, non linearities.

JEL classifi cation: F44 y E32.

Resumen

En el trabajo analizamos las interacciones entre el precio de las materias primas y el

crecimiento del PIB en siete grandes países exportadores de América Latina: Argentina,

Brasil, Colombia, Chile, México, Perú y Venezuela. Usando una nueva defi nición de funciones

de impulso-respuesta no lineales en procesos de cadenas de Markov, encontramos que

las respuestas de las tasas de crecimiento del PIB en cada país a los shocks de precios

dependen del momento en que se produzcan los shocks, del tamaño de los shocks y del

signo del shock. La mayor evidencia de asimetrías se observa cuando el shock de precios

produce un cambio de régimen en la serie. Por ello, concluimos que el diseño de las políticas

contracíclicas óptimas debería tener en cuenta que las reacciones de la actividad económica

dependen de manera fundamental de los posibles cambios de ciclo derivados de los shocks.

Palabras clave: precio materias primas, funciones de impulso-respuesta no lineales,

economías emergentes.

Códigos JEL: F44 y E32.

BANCO DE ESPAÑA 7 DOCUMENTO DE TRABAJO N.º 1304


−−−− ++++=

+++= −− ρρ

( )σ

+= β

ε+++= −−

( )σε

+= β

ε+++= −−

( )σε ε ε


β

β


εφ=

− ++=

σε

= =

−χ

( ) ( ) ======= −−−− χ


=

=


π

⊗

( ) ( ) νπθλεμ +⊗++=+=

νσν θ

λ

π

λ

π


ε

δ

( ) ( ) ( )+−=+= δε

•

δ


( )=

++= −


Ω

δ

( ) ( ) ( )−+−+− −== δεδ

δ

ξ ×

( )χ=

ξξ =+

× Γ

( ) ++ Γ=+

ξ ξ

−++ +=


ξ

+ξ

( )η

×

⊗

ξ

( )( )( )ηξ

ηξξ⊗

⊗=−

−

=

+ξ


+ξ

+ξ

+ξ


+++++++++= −−−−−−−−β

=− += β

( )=ψ

αψ =

=

−

−

−

ββ

βββ

ββ

ηαα += −

+=

−

−

−

−

−

−

−

−

−

−

−

−

εε

ε

ρ

( )η ( )σσσ=


Table 1. Indicators used to construct the indexes

Country GDP Employ. Unemploy. IP Sales

Argentina 93.II-09.I 03.I-09.I - 86.01-09.05 97.01-09.05

Brazil 90.II-09.I - 90.01-09.04 92.01-09.05 01.01-09.04

Chile 90.II-09.I - 86.01-09.04 82.03-09.05 06.01-09.05

Colombia 91.II-09.I - 01.01-09.04 81.01-09.04 90.01-09.04

Mexico 90.II-09.I - 87.01-09.03 71.01-09.03 02.01-09.04

Peru 80.II-09.I - 01.05-08.12 87.01-09.04 -

Venezuela 97.II-09.I 94.III-09.I - 98.01-09.04 03.01-09.01

Notes. The source of the data are World Bank and Datastream.

Table 2. Loading factors

Country GDP Employ. Unemploy. IP Sales % variance

Argentina 0.55

(0.08) 0.34

(0.38) -

0.32 (0.01)

0.04 (0.03)

49.18

Brazil 0.57

(0.06) -

-0.02 (0.01)

0.31 (0.03)

0.10 (0.03)

67.12

Chile 0.11

(0.01) -

-0.01 (0.01)

0.05 (0.01)

0.01 (0.01)

79.53

Colombia 1.12

(0.40) -

-0.05 (0.04)

0.01 (0.01)

0.05 (0.01)

95.00

Mexico 1.12

(0.06) -

-0.02 (0.02)

0.42 (0.01)

0.42 (0.04)

92.44

Peru 0.81

(0.05) -

-0.02 (0.12)

0.36 (0.02)

- 77.42

Venezuela 0.05

(0.03) 0.02

(0.03) -

0.04 (0.01)

0.04 (0.01)

23.29

Notes: Loading factors capture the correlation between the unobserved common factor and the variables Standard errors are in parentheses. Last row refers to the percentage of variance of GDP growth explained by the common factor.


Table 3. Cointegration tests

Prices Countries

Economist Moodys Food Nonfood Metal Specific Engle and Granger (1987)

Argentina -1.60 -1.52 -1.69 -1.53 -1.56 -1.49

Brazil -3.08 -3.59 -2.87 -2.97 -3.22 -2.93

Chile -1.48 -1.44 -1.46 -1.74 -1.73 -1.67

Colombia -1.39 -1.43 -1.58 -1.50 -1.39 -0.84

Mexico -2.44 -2.57 -2.23 -2.85 -2.37 -2.06

Peru -2.21 -2.20 -2.22 -2.33 -2.20 -2.21

Venezuela -1.57 -1.56 -1.74 -1.56 -1.57 -1.43

Stock and Watson (1988)

Argentina -3.41 -0.32 -4.35 -8.30 -4.98 -1.73

Brazil -1.95 -0.18 -2.76 -5.93 -2.60 -0.01

Chile -2.54 0.08 -4.83 -6.70 -4.29 -1.61

Colombia -2.65 -0.02 -6.07 -6.35 -4.46 -4.48

Mexico -6.72 -1.85 -8.62 -7.89 -6.19 -6.47

Peru -2.52 -0.06 -5.41 -5.38 -4.29 -1.94

Venezuela -1.50 -0.44 -2.98 -3.96 -2.16 -1.92

Bierens (1997)

Argentina 0.0008 0.0008 0.0001 0.0005 0.0035 0.030

Brazil 0.001 0.0001 0.0001 0.0001 0.0001 0.000

Chile 0.0016 0.0023 0.0011 0.0006 0.0024 0.003

Colombia 0.0002 0.0004 0.0001 0.0003 0.0007 0.001

Mexico 0.001 0.0011 0.0005 0.0011 0.0001 0.001

Peru 0.0001 0.0001 0.0001 0.0001 0.0001 0.001

Venezuela 0.0001 0.0001 0.0003 0.0002 0.0001 0.000

Gabriel, Psaradakis and Sola (2002)

Argentina -2.98 -2.57 -2.31 -2.91 -3.02 -1.54

Brazil -2.13 -5.03 -2.84 -2.96 -3.17 -3.21

Chile -1.96 -2.42 -3.70 -2.70 -2.65 -2.87

Colombia -2.26 -2.63 -2.88 -2.72 -2.74 -2.02

Mexico -2.29 -2.56 -3.71 -3.69 -3.52 -0.82

Peru -2.52 -2.51 -4.53 -2.70 -2.46 -2.56

Venezuela -1.38 -2.73 -1.33 -2.44 -3.27 -3.49

Notes: Critical values (5%) for Engle-Granger and Gabriel-Psaradakis-Sola tests are -3.42. For Stock-Watson and Bieren tests, they are -8.0, and 0.0169. The country-specific commodity price indexes (last column) have been obtained from Cunha, Prada and Sinnott (2010).


c0 c12wσ p00 p11 Pseudo R2

Argentina

Specific

1.30 (0.09)

9.05 (0.64)

-2.17 (0.04)

-1.83 (0.06)

1.43 (0.04)

29.25 (0.01)

0.97 (1.29)

0.85 (0.32)

0.83 (0.49)

0.95 (0.58)

0.58

0.53

Brazil

Specific

1.44 (0.11)

11.35 (0.96)

-1.08 (0.09)

-1.09 (0.14)

1.37 (0.05)

27.86 (0.01)

0.92 (0.57)

0.79 (0.28)

0.82 (0.39)

0.95 (6.04)

0.59

0.53

Chile

Specific

0.44 (0.11)

23.16 (1.58)

-0.26 (0.19)

-1.51 (0.13)

0.46 (0.03)

88.24 (0.01)

0.97 (2.60)

0.74 (0.25)

0.82 (0.84)

0.96 (0.64)

0.74

0.51

Colombia

Specific

1.19 (0.06)

20.00 (1.91)

-0.21 (0.05)

-1.76 (0.12)

0.47 (0.03)

81.15 (0.01)

0.94 (0.81)

0.81 (0.33)

0.84 (0.40)

0.96 (0.84)

0.54

0.52

Mexico

Specific

1.15 (0.11)

14.09 (1.35)

-4.75 (0.01)

-2.10 (0.08)

3.31 (0.01)

86.86 (0.01)

0.98 (2.07)

0.84 (0.35)

0.85 (0.62)

0.95 (0.65)

0.55

0.42

Peru

Specific

1.27 (0.11)

15.74 (1.54)

-0.21 (0.05)

-0.90 (0.23)

0.47 (0.03)

47.20 (0.01)

0.94 (0.81)

0.78 (0.29)

0.84 (0.40)

0.95 (0.91)

0.54

0.40

Venezuela

Specific

0.70 (0.14)

56.65 (8.86)

-12.18 (0.05)

0.98 (0.39)

3.37 (0.01)

208.73 (0.01)

0.99 (6.63)

0.71 (0.52)

0.85 (1.26)

0.90 (3.72)

0.63

0.32

Economist 6.39 (0.43) -2.27 (0.03) 21.44 (0.01) 0.93 (0.61) 0.95 (0.72) 0.56

Moodys 5.71 (0.49) -1.86 (0.08) 16.60 (0.01) 0.91 (0.44) 0.92 (0.57) 0.53

Food 8.11 (0.55) -2.79 (0.03) 27.22 (0.01) 0.91 (0.47) 0.94 (0.57) 0.60

Nonfood 6.91 (0.67) -2.29 (0.06) 40.73 (0.01) 0.93 (0.68) 0.95 (0.82) 0.41

Metal 12.01 (1.36) -2.83 (0.04) 59.30 (0.01) 0.87 (0.42) 0.95 (0.86) 0.52

Notes: The figure reports the parameter estimates from the model wtst tcw ε+= , where

),0(~ 2wwt iidN σε , and ( ) ijtt pisjsp === −1 . Entries labelled as specific refer to the

country-specific index of prices obtained from Cunha, Prada and Sinnott (2010).

Table 4. Markov-switching parameter estimates


Table 5. Markov-switching tests

Hansen (1992) Carrasco et al. (2004) Time series

p=0 p=1 p=1 Argentina Specific

0.000 0.000

0.024 0.000

0.060 0.000

Brazil Specific

0.000 0.000

0.000 0.000

0.000 0.000

Chile Specific

0.000 0.000

0.000 0.000

0.000 0.000

Colombia Specific

0.000 0.000

0.000 0.000

0.000 0.000

Mexico Specific

0.000 0.000

0.016 0.000

0.040 0.000

Peru Specific

0.000 0.000

0.018 0.000

0.170 0.000

Venezuela Specific

0.000 0.000

0.000 0.000

0.010 0.000

Economist 0.000 0.000 0.590

Moodys 0.000 0.000 0.000

Food 0.000 0.000 0.000

Nonfood 0.000 0.000 0.822

Metal 0.000 0.000 0.000

Notes: Entries are p-values of the null of linearity against Markov-switching. Entries labelled as specific refer to the country-specific index of prices obtained from Cunha, Prada and Sinnott (2010).

Table 6. Test of nonlinear responses

Prices Countries

Economist Moodys Food Nonfood Metal Specific

Argentina 0.072 0.005 0.103 0.065 0.279 0.264

Brazil 0.082 0.015 0.001 0.017 0.001 0.217

Chile 0.001 0.001 0.028 0.095 0.009 0.036

Colombia 0.021 0.069 0.349 0.104 0.528 0.000

Mexico 0.010 0.001 0.185 0.001 0.001 0.057

Peru 0.018 0.071 0.061 0.160 0.191 0.028

Venezuela 0.057 0.014 0.001 0.069 0.034 0.001

Notes: Following Hamilton (2001), entries are p-values of the null that the reaction of outputs to prices is linear. The alternative assumes that this relation is nonlinear with a flexible functional form. The country-specific commodity price indexes (last column) have been obtained from Cunha, Prada and Sinnott (2010).


Figure 1. Recent economic developments in LAC

Notes. The figure plots quarterly GDP growth rates. Shaded area refers to the 2008 NBER recession (the through has not been dated yet).

-6

-4

-2

0

2

4

07.2 07.3 07.4 08.1 08.2 08.3 08.4 09.1 09.2

NBER

US

zero-line

Mexico

Argentina

Brazil

Chile

Colombia

Peru

Venezuela


Figure 2: Quarterly GDP growth rates: Data and interpolation.

Argentina Brazil

ChileColombia

-8

-4

0

4

86.07 89.01 91.07 94.01 96.07 99.01 01.07 04.01 06.07 09.01 -8

-4

0

4

90.07 93.03 95.11 98.07 01.03 03.11 06.07 09.03

-8

-4

0

4

82.07 85.03 87.11 90.07 93.03 95.11 98.07 01.03 03.11 06.07 09.03-8

-4

0

4

81.07 84.01 86.07 89.01 91.07 94.01 96.07 99.01 01.07 04.01 06.07 09.01

Mexico

-8

-4

0

4

71.07 74.12 78.05 81.10 85.03 88.08 92.01 95.06 98.11 02.04 05.09 09.02-15

-10

-5

0

5

10

80.12 84.01 87.02 90.03 93.04 96.05 99.06 02.07 05.08 08.09

Peru

-20

-15

-10

-5

0

5

10

94.07 96.02 97.09 99.04 00.11 02.06 04.01 05.08 07.03 08.10

Venezuela

Notes. The charts plot (straight lines) quarterly growth rates of GDP which have been interpolated by using monthly indicators with dynamic factor models and their 68% confident bands (dotted lines). Plot marks refer to actual quarterly growth rates.


Figure 3. Quarterly growth rates of country-specific commodity price indexes.

Argentina Brazil

ChileColombia

Mexico Peru

Venezuela

Notes. The country-specific price indexes have been obtained from Cunha, Prada and Sinnott (2010).

-30

-15

0

15

30

71.07 74.12 78.05 81.10 85.03 88.08 92.01 95.06 98.11 02.04 05.09 09.02-30

-15

0

15

30

71.07 74.12 78.05 81.10 85.03 88.08 92.01 95.06 98.11 02.04 05.09 09.02

-30

-15

0

15

30

71.07 74.12 78.05 81.10 85.03 88.08 92.01 95.06 98.11 02.04 05.09 09.02-30

-15

0

15

30

71.07 74.12 78.05 81.10 85.03 88.08 92.01 95.06 98.11 02.04 05.09 09.02

-30

-15

0

15

30

71.07 74.12 78.05 81.10 85.03 88.08 92.01 95.06 98.11 02.04 05.09 09.02 -30

-15

0

15

30

71.07 74.12 78.05 81.10 85.03 88.08 92.01 95.06 98.11 02.04 05.09 09.02

-30

-15

0

15

30

71.07 74.12 78.05 81.10 85.03 88.08 92.01 95.06 98.11 02.04 05.09 09.02


-24

-12

0

12

24

71.07 74.12 78.05 81.10 85.03 88.08 92.01 95.06 98.11 02.04 05.09 09.02

Figure 4. Quarterly growth rates of composite commodity price indexes.

The Economist

-24

-12

0

12

24

71.07 74.12 78.05 81.10 85.03 88.08 92.01 95.06 98.11 02.04 05.09 09.02

Moodys

-24

-12

0

12

24

71.07 74.12 78.05 81.10 85.03 88.08 92.01 95.06 98.11 02.04 05.09 09.02

Food Non-food

-30

-15

0

15

30

71.07 74.12 78.05 81.10 85.03 88.08 92.01 95.06 98.11 02.04 05.09 09.02

-30

-15

0

15

30

71.07 74.12 78.05 81.10 85.03 88.08 92.01 95.06 98.11 02.04 05.09 09.02

Metal

Notes. The composite price indexes have been obtained from Moodys, and The Economists (including its disaggregation in Food, Non-food and Metals).


Figure 5. Evolution of linear responses and output growth in Argentina

Notes. The left-hand-side chart plots the 24-month (X axis) linear responses of Argentinean GDP growth to one standard deviation shock in its country-specific commodity price shock . They are calculated from 2006.04 to 2009.03 (Y axis) using a rolling window of four years. The right-hand-side graph plots the quarterly growth rate of GDP at monthly frequency.

Output growth

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

2006.04 2006.09 2007.01 2007.05 2007.09 2008.01 2008.05 2008.09 2009.01

2006.04

2007.0

3

2008.02

2009.0

1 0

8

16

240

0.5

1

Output responses


Figure 6. IRF Argentina

GDP response at highest filtered prob of recession

0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6

GDP response at lowest filtered prob of recession

0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6

Recession probs. responses to +6 std shock in pricesat highest probability of recession

0

0.2

0.4

0.6

0.8

1

0 4 8 12

horizon h

with shock without shock

Recession probs. responses to -6 std shock in pricesat lowest probability of recession

0

0.2

0.4

0.6

0.8

1

0 4 8 12

horizon h


GDP response with linear models

0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6

es. Reactions to positive (negative) d-standard-deviation shocks in commodity prices are on the left (right) hand graphs. The first graphs are linear responses of output growth. The next graphs show the Markov-switching responses of output (second and

d row graphs) and recession probabilities (last row of graphs) to price shocks that occur at the highest and lowest probabilities of ssion.


Figure 7. IRF Brazil


0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


0

0.2

0.4

0.6

0.8

1

0 4 8

horizon h



0

0.2

0.4

0.6

0.8

1

0 4 8 12

horizon h



0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6

Notes. See notes of Figure 6.


Figure 8. IRF Chile


0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


0

0.2

0.4

0.6

0.8

1

0 4 8 12

horizon h



0

0.2

0.4

0.6

0.8

1

0 4 8 12

horizon h



0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6



39

Figure 9. IRF Colombia


0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6

Recession probs. responses to +6 std shock in pricesat higest probability of recession

0

0.2

0.4

0.6

0.8

1

0 4 8 12

horizon h



0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


0

0.2

0.4

0.6

0.8

1

0 4 8 12

horizon h




Figure 10. IRF Mexico


0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


0

0.2

0.4

0.6

0.8

1

0 4 8 12

horizon h



0

0.2

0.4

0.6

0.8

1

0 4 8 12

horizon h



0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6



Figure 11. IRF Peru


0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


0

0.2

0.4

0.6

0.8

1

0 4 8 12

horizon h



0

0.2

0.4

0.6

0.8

1

0 4 8 12

horizon h



0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6



Figure 12. IRF Venezuela


0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


0

0.2

0.4

0.6

0.8

1

0 4 8 12

horizon h



0

0.2

0.4

0.6

0.8

1

0 4 8 12

horizon h



0

1

2

3

4

5

6

7

8

0 4 8 12 16 20 24 28 32 36

horizon h

d=1 d=3 d=6


-8

-7

-6

-5

-4

-3

-2

-1

0

0 4 8 12 16 20 24 28 32 36

horizon h

d=-1 d=-3 d=-6


BANCO DE ESPAÑA PUBLICATIONS

WORKING PAPERS

1201 CARLOS PÉREZ MONTES: Regulatory bias in the price structure of local telephone services.

1202 MAXIMO CAMACHO, GABRIEL PEREZ-QUIROS and PILAR PONCELA: Extracting non-linear signals from several

economic indicators.

1203 MARCOS DAL BIANCO, MAXIMO CAMACHO and GABRIEL PEREZ-QUIROS: Short-run forecasting of the euro-dollar

exchange rate with economic fundamentals.

1204 ROCIO ALVAREZ, MAXIMO CAMACHO and GABRIEL PEREZ-QUIROS: Finite sample performance of small versus

large scale dynamic factor models.

1205 MAXIMO CAMACHO, GABRIEL PEREZ-QUIROS and PILAR PONCELA: Markov-switching dynamic factor models in

real time.

1206 IGNACIO HERNANDO and ERNESTO VILLANUEVA: The recent slowdown of bank lending in Spain: are supply-side

factors relevant?

1207 JAMES COSTAIN and BEATRIZ DE BLAS: Smoothing shocks and balancing budgets in a currency union.

1208 AITOR LACUESTA, SERGIO PUENTE and ERNESTO VILLANUEVA: The schooling response to a sustained Increase in

low-skill wages: evidence from Spain 1989-2009.

1209 GABOR PULA and DANIEL SANTABÁRBARA: Is China climbing up the quality ladder?

1210 ROBERTO BLANCO and RICARDO GIMENO: Determinants of default ratios in the segment of loans to households in

Spain.

1211 ENRIQUE ALBEROLA, AITOR ERCE and JOSÉ MARÍA SERENA: International reserves and gross capital fl ows.

Dynamics during fi nancial stress.

1212 GIANCARLO CORSETTI, LUCA DEDOLA and FRANCESCA VIANI: The international risk-sharing puzzle is at business-

cycle and lower frequency.

1213 FRANCISCO ALVAREZ-CUADRADO, JOSE MARIA CASADO, JOSE MARIA LABEAGA and DHANOOS

SUTTHIPHISAL: Envy and habits: panel data estimates of interdependent preferences.

1214 JOSE MARIA CASADO: Consumption partial insurance of Spanish households.

1215 J. ANDRÉS, J. E. BOSCÁ and J. FERRI: Household leverage and fi scal multipliers.

1216 JAMES COSTAIN and BEATRIZ DE BLAS: The role of fi scal delegation in a monetary union: a survey of the political

economy issues.

1217 ARTURO MACÍAS and MARIANO MATILLA-GARCÍA: Net energy analysis in a Ramsey-Hotelling growth model.

1218 ALFREDO MARTÍN-OLIVER, SONIA RUANO and VICENTE SALAS-FUMÁS: Effects of equity capital on the interest rate

and the demand for credit. Empirical evidence from Spanish banks.

1219 PALOMA LÓPEZ-GARCÍA, JOSÉ MANUEL MONTERO and ENRIQUE MORAL-BENITO: Business cycles and

investment in intangibles: evidence from Spanish fi rms.

1220 ENRIQUE ALBEROLA, LUIS MOLINA and PEDRO DEL RÍO: Boom-bust cycles, imbalances and discipline in Europe.

1221 CARLOS GONZÁLEZ-AGUADO and ENRIQUE MORAL-BENITO: Determinants of corporate default: a BMA approach.

1222 GALO NUÑO and CARLOS THOMAS: Bank leverage cycles.

1223 YUNUS AKSOY and HENRIQUE S. BASSO: Liquidity, term spreads and monetary policy.

1224 FRANCISCO DE CASTRO and DANIEL GARROTE: The effects of fi scal shocks on the exchange rate in the EMU and

differences with the US.

1225 STÉPHANE BONHOMME and LAURA HOSPIDO: The cycle of earnings inequality: evidence from Spanish social

security data.

1226 CARMEN BROTO: The effectiveness of forex interventions in four Latin American countries.

1227 LORENZO RICCI and DAVID VEREDAS: TailCoR.

1228 YVES DOMINICY, SIEGFRIED HÖRMANN, HIROAKI OGATA and DAVID VEREDAS: Marginal quantiles for stationary

processes.

1229 MATTEO BARIGOZZI, ROXANA HALBLEIB and DAVID VEREDAS: Which model to match?

1230 MATTEO LUCIANI and DAVID VEREDAS: A model for vast panels of volatilities.

1231 AITOR ERCE: Does the IMF’s offi cial support affect sovereign bond maturities?

1232 JAVIER MENCÍA and ENRIQUE SENTANA: Valuation of VIX derivatives.

1233 ROSSANA MEROLA and JAVIER J. PÉREZ: Fiscal forecast errors: governments vs independent agencies?

1234 MIGUEL GARCÍA-POSADA and JUAN S. MORA-SANGUINETTI: Why do Spanish fi rms rarely use the bankruptcy

system? The role of the mortgage institution.

1235 MAXIMO CAMACHO, YULIYA LOVCHA and GABRIEL PEREZ-QUIROS: Can we use seasonally adjusted indicators

in dynamic factor models?

1236 JENS HAGENDORFF, MARÍA J. NIETO and LARRY D. WALL: The safety and soundness effects of bank M&As in the EU:

Does prudential regulation have any impact?

1237 SOFÍA GALÁN and SERGIO PUENTE: Minimum wages: do they really hurt young people?

1238 CRISTIANO CANTORE, FILIPPO FERRONI and MIGUEL A. LEÓN-LEDESMA: The dynamics of hours worked and

technology.

1239 ALFREDO MARTÍN-OLIVER, SONIA RUANO and VICENTE SALAS-FUMÁS: Why did high productivity growth of banks

precede the fi nancial crisis?

1240 MARIA DOLORES GADEA RIVAS and GABRIEL PEREZ-QUIROS: The failure to predict the Great Recession. The failure

of academic economics? A view focusing on the role of credit.

1241 MATTEO CICCARELLI, EVA ORTEGA and MARIA TERESA VALDERRAMA: Heterogeneity and cross-country spillovers in

macroeconomic-fi nancial linkages.

1242 GIANCARLO CORSETTI, LUCA DEDOLA and FRANCESCA VIANI: Traded and nontraded goods prices, and

international risk sharing: an empirical investigation.

1243 ENRIQUE MORAL-BENITO: Growth empirics in panel data under model uncertainty and weak exogeneity.

1301 JAMES COSTAIN and ANTON NAKOV: Logit price dynamics.

1302 MIGUEL GARCÍA-POSADA: Insolvency institutions and effi ciency: the Spanish case.

1303 MIGUEL GARCÍA-POSADA and JUAN S. MORA-SANGUINETTI: Firm size and judicial effi cacy: evidence for the new

civil procedures in Spain.

1304 MAXIMO CAMACHO and GABRIEL PEREZ-QUIROS: Commodity prices and the business cycle in Latin America: living

and dying by commodities?

Unidad de Servicios AuxiliaresAlcalá, 48 - 28014 Madrid

Telephone +34 91 338 6368 E-mail: [email protected]

www.bde.es

commodity prices and the business cycle in latin america ... · dependence: policy challenges and...

Documents