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The Euro Area variables are constructed as weighted averages of the corresponding series of Austria, Belgium, Finland, France, Germany, Greece, Ireland, Italy, Netherlands, Portugal, and Spain. The weights are each country’s mean shares of the Euro Area’s real GDP in PPP over the period 1995-2000. The real GDP in PPP series are obtained from the World Bank’s World Development Indicators 2002.

Following Pesaran et al. (2004a), the variables used in the estimation of each country/region-speci…c VEC model are constructed from the series above as follows:

y= ln[100 (Y CC=P OP)=P OP2000];

sr= 0:25 ln(1 +SR=100) ln(CP I+1=CP I);

q= ln(100 N ER=N ER2000) ln(CP I);

nf a=N F A=(Y N C=N ER);

yi =PN 1 j=0 wijyj; sri =PN 1

j=0 wijsrj;

oil= ln(100 OIL=CP I2000).

References

[1] Agenor, P. R., C. J. McDermott, and E. S. Prasad (2000) “Macroeconomic Fluctuations in Developing Countries: Some Stylized Facts”World Bank Economic Review, 14, 251-285.

[2] Ahmed, S. (2003) “Sources of Economic Fluctuations in Latin America and Implications for Choice of Exchange Rate Regime”,Journal of Development Economics, 72, 181-202.

[3] Aiol…, M., L. Catão, and A. Timmermann (2006) “Common Factors in Latin America’s Business Cycles”, IMF Working Paper, 06/49.

[4] Artis, M. J. (2003) “Re‡ections on the Optimal Currency Area (OCA) Criteria in the Light of EMU”, International Journal of Finance and Economics, 8, 297-307.

[5] Baltagi, B. H. (2004) “Comment”,Journal of Business Economics and Statistics, 2, 163-164.

[6] Banerjee, A., M. Marcellino, and C. Osbat (2004) “Some Cautions on the Use of Panel Methods for Integrated Series of Macro-economic Data”,Econometrics Journal, 7, 322-340.

[7] Berg, A., E. Borensztein, and P. Mauro (2002) “An Evaluation of Monetary Policy Regime Options for Latin America”,North American Journal of Economics and Finance, 13, 213-235.

[8] Boschi, M. (2007) “Foreign Capital in Latin America: A Long-run Structural Global VAR Perspective”, University of Essex, Department of Economics Discussion Paper, n. 647.

[9] Canova, F. (2005) “The Transmission of US Shocks to Latin America”,Journal of Applied Econometrics, 20, 229-251.

[10] Dees, S., F. di Mauro, M. H. Pesaran, and L. V. Smith (2007a) “Exploring the International Linkages of the Euro Area: A Global VAR Analysis”,Journal of Applied Econometrics, 22, 1-38.

[11] Dees, S., S. Holly, M. H. Pesaran, and L. V. Smith (2007b) “Long run Macroeconomic Relations in the Global Economy”,Economics - The Open-Access, Open-Assessment E-Journal, 2007-3.

[12] Edwards, S. (2002) “The Great Exchange Rate Debate after Argentina”, North American Journal of Economics and Finance, 13, 237-252.

[13] Girardi, A. and P. Paesani (2008) “The Transfer Problem in the Euro Area: A Cointegration Analysis”, Open Economies Review, forthcoming.

[14] HM Treasury (2003) “Analysis of European and UK Business Cycles and Shocks”, available at www.hm-trasury.gov.uk.

[15] Ho¤maister, A. W. and J. F. Roldos (1997) “Are Business Cycles Di¤erent in Asia and Latin America?”

IMF Working Paper, n. 97/9.

[16] Johansen, S. (1992) “Determination of the Cointegration Rank in the Presence of a Linear Trend”, Oxford Bullettin of Economics and Statistics, 54, 383-397.

[17] Koop, G., M. H. Pesaran, and S. M. Potter (1996) “Impulse Response Analysis in Nonlinear Multivariate Models”,Journal of Econometrics, 74, 119-147.

[18] Kose, M. A., C. Otrok, and E. Prasad (2008) “Global Business Cycles: Convergence or Decoupling?”, IZA Discussion Papers, n. 3442.

[19] Kose, M. A., C. Otrok, and C. Whiteman (2003) “International Business Cycles: World, Region, and Country Speci…c Factors”,American Economic Review, 93, 1216-1239.

[20] Lane, P. R. and G. M. Milesi-Ferretti (2004) “The transfer problem revisited: Net foreign assets and real exchange rates”,Review of Economics and Statistics, 86, 841-857.

[21] Lanne, M., H. Lütkepohl, and P. Saikkonen (2002) “Comparison of Unit Root Tests for Time Series with Level Shifts”,Journal of Time Series Analysis, 23, 667-685.

[22] Lanne, M., H. Lütkepohl, and P. Saikkonen (2003) “Test Procedures for Unit Roots in Time Series with Level Shifts at Unknown Time”,Oxford Bulletin of Economics and Statistics, 65, 91-155.

[23] Lütkepohl, H. (2006)New Introduction to Multiple Time Series Analysis, Springer Verlag, Berlin.

[24] McKinnon, R. I. (1963) “Optimum Currency Areas”, American Economic Review, 53, 717-725.

[25] Mundell, R. A. (1961) “A Theory of Optimum Currency Areas”, American Economic Review, 51, 657-665.

[26] Ng, S. and P. Perron (2001) “Lag Lenght Selection and the Construction of Unit Root Tests with Good Size and Power”,Econometrica, 69, 1519-1554.

[27] Pesaran, M. H., T. Schuermann, and S. M. Weiner (2004a) “Modelling Regional Interdependencies using a Global Error-Correcting Macroeconometric Model”,Journal of Business Economics and Statistics,2, 126-162.

[28] Pesaran, M. H., T. Schuermann, and S. M. Weiner (2004b) “Rejoinder to Comments on Modelling Re-gional Interdependencies using a Global Error-Correcting Macro-econometric Model”,Journal of Busi-ness Economics and Statistics,2, 175-181.

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[30] Saikkonen, P. and H. Lutkepohl (2002) “Testing for a Unit Root in a Time Series with a Level Shift at Unknown Time”,Econometric Theory, 18, 313-348.

Table 1: Trade weights

Argentina Bolivia Brazil Chile Mexico Peru Euro Area Japan US

Argentina 0 0.158 0.178 0.126 0.003 0.033 0.026 0.004 0.012

Bolivia 0.011 0 0.008 0.010 0.000 0.023 0.001 0.000 0.001

Brazil 0.358 0.149 0 0.094 0.009 0.064 0.067 0.020 0.041

Chile 0.075 0.077 0.029 0 0.006 0.080 0.015 0.012 0.011

Mexico 0.025 0.020 0.028 0.054 0 0.041 0.031 0.020 0.283

Peru 0.010 0.093 0.008 0.026 0.002 0 0.005 0.002 0.006

Euro Area 0.273 0.077 0.334 0.248 0.060 0.219 0 0.272 0.342

Japan 0.042 0.091 0.081 0.149 0.027 0.083 0.224 0 0.305

US 0.207 0.335 0.334 0.293 0.894 0.458 0.631 0.670 0

Notes: Trade weights, computed as shares of exports and imports in 1995-2001, are displayed in column by country/region. Each column, but not row, sums to one. Source: Direction of Trade Statistics Yearbook, IMF, 2002.

Table 2: ADF unit root test statistics Panel [A]. AIC order selection

Argentina Bolivia Brazil Chile Mexico Peru Euro Area Japan US

y -1.92 -1.33 -1.74 -2.57 -2.28 -1.67 -3.25 -1.49 -2.84

nfa -1.86 -2.71 -1.06 -4.41 -3.03 -3.90 -5.14 -1.20 -3.04

∆nfa -7.82 -2.67 -4.88 -2.96 -5.02 -5.24 -3.45 -5.60 -3.18

y* -2.12 -2.80 -2.05 -3.64 -2.92 -3.19 -3.49 -4.32 -2.65

∆y* -9.30 -8.02 -5.44 -4.76 -4.74 -4.91 -3.70 -4.96 -5.42

sr* -2.04 -2.79 -6.02 -7.78 -2.62 -3.84 -3.27 -3.53 -2.53

∆sr* -2.70 -2.96 -4.98 -7.55 -6.32 -7.41 -4.61 -12.42 -6.57

oil - - - - - - - - -1.85

∆oil - - - - - - - - -5.87

Panel [B]. Modified AIC order selection

Argentina Bolivia Brazil Chile Mexico Peru Euro Area Japan US

y -1.92 -1.33 -1.74 -2.57 -2.28 -1.67 -1.96 -1.49 -2.88

∆y -4.54 -2.79 -2.59 -3.24 -4.02 -2.56 -2.76 -3.24 -4.39

sr -1.69 -2.32 -3.39 -1.25 -2.68 -0.90 -1.87 -1.20 -0.85

∆sr -16.65 -11.40 -7.74 -5.30 -5.71 -5.20 -14.66 -18.48 -12.48

q -2.65 -1.19 -1.48 -1.76 -4.07 -1.58 -2.47 -1.58 -2.31

∆q -3.73 -1.98 -6.32 -1.86 -4.59 -3.58 -4.10 -4.19 -2.25

nfa -1.15 -3.10 -1.06 -2.42 -1.61 -2.31 -3.78 -1.20 -3.19

∆nfa -2.34 -1.72 -1.95 -1.61 -4.33 -4.85 -2.37 -4.02 -1.83

y* -2.12 -1.98 -1.51 -2.25 -2.92 -2.78 -2.24 -3.02 -1.84

∆y* -2.80 -5.03 -3.84 -4.90 -4.02 -5.02 -5.93 -3.22 -4.87

sr* -1.16 -2.11 -4.64 -1.49 -0.79 -2.61 -2.26 0.08 -2.06

∆sr* -2.37 -2.57 -19.04 -15.77 -12.60 -13.20 -18.86 -12.42 -4.53

oil - - - - - - - - -1.85

∆oil - - - - - - - - -6.27

Notes: The ADF statistics are based on univariate AR(p) models in the levels with p chosen according to the modified AIC, with a maximum lag order of 11. The sample period is 1980:1-2003:4. The regressions for all variables in the levels include an intercept and a linear trend with the exception of interest rates whose underlying regressions include only an intercept. The 95 percent critical value for regressions with trend is -3.46 and for regressions without trend -2.89.

Table 3: ADF unit root tests with breaks statistics

Panel [A]. Level variables

y sr q nfa y* sr* oil

Argentina

Suggested break date 1994 Q2 1991 Q2 1984 Q2 1984 Q4 1985 Q1 1990 Q3

-Test statistic -2.23 [8] -3.61 [3] -1.52 [2] -1.83 [3] -1.37 [0] -2.58 [7] -Bolivia

Suggested break date 1985 Q2 1991 Q1 1984 Q3 1988 Q4 1994 Q2 1994 Q2

-Test statistic -1.04 [10] -1.07 [7] -1.34 [2] -3.52 [10] -2.56 [1] -5.83 [7] -Brazil

Suggested break date 1995 Q1 1988 Q4 1994 Q4 1989 Q2 1991 Q2 1982 Q2

-Test statistic -1.88 [0] -1.63 [1] -2.03 [5] -2.30 [5] -1.87 [9] -4.85 [4] -Chile

Suggested break date 1995 Q1 1991 Q2 2003 Q1 1987 Q1 1985 Q1 1990 Q3

-Test statistic -1.11 [4] -2.56 [10] -2.29 [4] -2.02 [3] -2.70 [2] -2.99 [0] -Mexico

Suggested break date 1982 Q1 1988 Q4 1982 Q1 1982 Q2 1982 Q2 1986 Q2

-Test statistic -3.43 [2] -3.79 [0] -4.19 [3] -2.84 [2] -2.43 [3] -2.82 [2] -Peru

Suggested break date 1992 Q2 1984 Q4 1991 Q1 1989 Q1 1984 Q1 1990 Q3

-Test statistic -1.92 [1] -0.90 [8] -1.94 [3] -3.45 [2] -1.83 [1] -1.80 [2] -Euro Area

Suggested break date 1984 Q2 1993 Q2 1991 Q2 1999 Q4 1990 Q2 2002 Q1

-Test statistic -2.27 [6] -2.64 [3] -2.11 [1] -2.86 [9] -2.18 [7] -3.34 [3] -Japan

Suggested break date 2001 Q3 1986 Q4 1995 Q3 2000 Q2 1982 Q1 1986 Q4

-Test statistic -1.73 [3] -1.70 [4] -2.88 [3] -1.67 [4] -2.86 [3] -3.93 [0] -US

Suggested break date 1981 Q4 1986 Q4 1988 Q4 2000 Q3 1995 Q2 1991 Q4 2000 Q3 Test statistic -2.34 [2] -3.04 [2] -2.72 [7] -2.28 [9] -2.21 [2] -2.90 [4] -2.33 [4]

Crit. value at 5% (1%) -3.03 (-3.55) -2.88 (-3.48) -3.03 (-3.55) -3.03 (-3.55) -3.03 (-3.55) -2.88 (-3.48) -3.03 (-3.55) Panel [B]. Differenced variables

∆y ∆sr ∆q ∆nfa ∆y* ∆sr* ∆oil

Argentina

Suggested break date 1991 Q3 1992 Q1 1988 Q3 1985 Q3 1991 Q2 1991 Q2

-Test statistic -2.19 [7] -2.96 [5] -3.04 [1] -2.50 [2] -3.37 [0] -1.54 [3] -Bolivia

Suggested break date 1984 Q1 1984 Q2 1983 Q1 2003 Q1 1994 Q2 1993 Q4

-Test statistic -3.42 [4] -2.94 [6] -3.60 [0] -2.59 [4] -2.06 [1] -1.76 [10] -Brazil

Suggested break date 1991 Q2 1989 Q2 1990 Q2 2003 Q1 2002 Q2 1988 Q4

-Test statistic -3.54 [0] -2.30 [1] -1.35 [4] -2.59 [4] -4.06 [7] -3.11 [7] -Chile

Suggested break date 1988 Q3 1991 Q1 1982 Q2 2002 Q4 2002 Q2 1982 Q3

-Test statistic -3.37 [0] -1.03 [10] -3.72 [2] -2.97 [10] -3.66 [7] -6.45 [4] -Mexico

Suggested break date 1987 Q1 1985 Q1 1982 Q1 1982 Q3 1983 Q1 1986 Q2

-Test statistic -4.12 [1] -4.26 [0] -4.30 [3] -5.75 [4] -5.79 [2] -2.68 [5] -Peru

Suggested break date 1989 Q2 1988 Q3 1990 Q2 1986 Q1 1985 Q3 1990 Q1

-Test statistic -2.47 [3] -1.80 [7] -1.80 [2] -2.39 [3] -6.05 [9] -2.72 [4] -Euro Area

Suggested break date 1984 Q3 1992 Q4 1988 Q4 1989 Q4 1990 Q2 1988 Q2

-Test statistic -3.89 [3] -1.70 [7] -3.38 [0] -2.80 [9] -2.75 [6] -3.18 [3] -Japan

Suggested break date 2002 Q2 1987 Q2 1995 Q3 2000 Q3 1990 Q2 1986 Q2

-Test statistic -2.50 [2] -2.41 [3] -1.57 [3] -1.93 [5] -3.49 [9] -3.11 [10] -US

Suggested break date 1981 Q3 1998 Q1 1988 Q3 1991 Q1 1995 Q1 1982 Q3 1986 Q3 Test statistic -3.18 [2] -2.29 [10] -2.36 [3] -3.23 [7] -1.64 [2] -4.88 [3] -2.34 [3]

Crit. value at 5% (1%) -2.88 (-3.48) -2.88 (-3.48) -2.88 (-3.48) -2.88 (-3.48) -2.88 (-3.48) -2.88 (-3.48) -2.88 (-3.48) Notes: the regressions for all variables in the levels include an intercept and a linear trend with the exception of interest rates whose underlying regression include only an intercept. For differenced variables the regressions do not include an intercept and a linear trend. The lag order, selected according to the AIC with a maximum lag order of 10, is reported in square brackets.

Table 4: Test statistics for selecting the lag order of the endogenous (domestic) variables in the VARX*(pi,qi) model

Order (pi) AIC SBC Adjusted LR test

4 750.1 629.1

3 760.7 659.8 χ2(16) = 8.0098[.949]

2 761.8 681.1 χ2(32) = 30.0748[.564]

1 757.3 696.7 χ2(48) = 60.3741[.108]

0 354.6 314.2 χ2(64) = 679.3204[.000]

Order (pi) AIC SBC Adjusted LR test

4 1108.0 987.0

3 1111.5 1010.7 χ2(16) = 18.4464[.298]

2 1118.8 1038.1 χ2(32) = 31.3951[.497]

1 1072.1 1011.5 χ2(48) = 124.1005[.000]

0 529.1 488.8 χ2(64) = 950.3084[.000]

Order (pi) AIC SBC Adjusted LR test

4 676.7 560.7

3 682.5 586.6 χ2(16) = 15.3189[.501]

2 690.2 614.6 χ2(32) = 27.6889[.685]

1 694.9 639.4 χ2(48) = 44.6904[.609]

0 241.1 205.8 χ2(64) = 749.4294[.000]

Order (pi) AIC SBC Adjusted LR test

4 970.4 854.4

3 970.2 874.3 χ2(16) = 24.3738[.082]

2 961.1 885.5 χ2(32) = 61.8960[.001]

1 942.6 887.1 χ2(48) = 113.7365[.000]

0 450.9 415.6 χ2(64) = 875.3154[.000]

Order (pi) AIC SBC Adjusted LR test

4 979.0 868.1

3 974.1 883.3 χ2(16) = 31.8997[.010]

2 973.4 902.8 χ2(32) = 57.2928[.004]

1 950.4 900.0 χ2(48) = 116.5151[.000]

0 552.1 521.9 χ2(64) = 747.0024[.000]

Order (pi) AIC SBC Adjusted LR test

4 814.2 693.1

3 820.8 720.0 χ2(25) = 13.8210[.612]

2 797.7 717.0 χ2(50) = 71.6619[.000]

1 800.5 740.0 χ2(75) = 91.1393[.000]

0 291.1 250.7 χ2(100) = 867.8986[.000]

Order (pi) AIC SBC Adjusted LR test

4 1423.5 1307.5

3 1423.4 1327.6 χ2(25) = 24.1098[.087]

2 1423.1 1347.5 χ2(50) = 48.5555[.031]

1 1408.5 1353.1 χ2(75) = 94.4301[.000]

0 846.9 811.6 χ2(100) = 960.8257[.000]

Order (pi) AIC SBC Adjusted LR test

4 1156.6 1040.6

3 1155.6 1059.8 χ2(25) = 25.5334[.061]

2 1164.0 1088.3 χ2(50) = 37.0023[.249]

1 1155.6 1100.1 χ2(75) = 73.5455[.010]

0 801.8 766.5 χ2(100) = 628.2555[.000]

Order (pi) AIC SBC Adjusted LR test

4 1359.1 1253.2

3 1361.7 1275.9 χ2(25) = 20.8059[.186]

2 1367.4 1301.9 χ2(50) = 36.5831[.264]

1 1305.6 1260.3 χ2(75) = 156.6580[.000]

0 797.0 771.8 χ2(100) = 966.4766[.000]

Japan

US

Notes: statistics in bold indicate the order selected by the relevant criterion/test. Unrestricted VARs are estimated with foreign variables treated as exogenous.

Table 5: Univariate speci…cation tests statistics

∆y ∆sr ∆q ∆nfa

Argentina

Serial Correlation F(4,83) 1.87 [0.123] 2.39 [0.057] 2.27 [0.069] 1.58 [0.187]

Normality χ2(2) 67.18 [0.000]** 1.36 [0.506] 2.00 [0.369] 17.08 [0.000]**

Heteroscedasticity F(1,93) 0.14 [0.709] 5.44 [0.022]* 4.47 [0.037]* 1.55 [0.217]

Bolivia

Serial Correlation F(4,82) 1.63 [0.174] 1.59 [0.184] 1.96 [0.108] 33.30 [0.000]**

Normality χ2(2) 0.00 [0.998] 0.64 [0.725] 0.88 [0.645] 2.02 [0.365]

Heteroscedasticity F(1,93) 5.36 [0.023]* 3.78 [0.055] 4.54 [0.036]* 2.63 [0.108]

Brazil

Serial Correlation F(4,84) 0.41 [0.803] 1.38 [0.247] 0.61 [0.654] 1.84 [0.129]

Normality χ2(2) 1.48 [0.476] 2.36 [0.308] 0.64 [0.725] 0.19 [0.911]

Heteroscedasticity F(1,93) 0.65 [0.423] 4.16 [0.044]* 4.51 [0.036]* 0.58 [0.450]

Chile

Serial Correlation F(4,83) 1.11 [0.357] 6.09 [0.000]** 3.60 [0.009]** 1.76 [0.145]

Normality χ2(2) 1.52 [0.468] 0.86 [0.652] 2.87 [0.238] 1.69 [0.430]

Heteroscedasticity F(1,93) 3.09 [0.082] 0.34 [0.559] 0.34 [0.559] 0.39 [0.535]

Mexico

Serial Correlation F(4,85) 4.45 [0.003]** 0.79 [0.537] 0.73 [0.575] 0.90 [0.469]

Normality χ2(2) 0.98 [0.612] 1.01 [0.605] 35.25 [0.000]** 0.19 [0.909]

Heteroscedasticity F(1,93) 2.06 [0.155] 0.19 [0.668] 0.20 [0.658] 3.68 [0.058]

Peru

Serial Correlation F(4,83) 0.75 [0.559] 1.16 [0.336] 0.42 [0.795] 1.67 [0.164]

Normality χ2(2) 0.75 [0.686] 1.25 [0.535] 2.22 [0.330] 1.14 [0.564]

Heteroscedasticity F(1,93) 1.16 [0.285] 1.95 [0.166] 0.25 [0.617] 0.79 [0.376]

Euro Area

Serial Correlation F(4,83) 1.02 [0.401] 2.08 [0.091] 3.14 [0.019]* 1.57 [0.190]

Normality χ2(2) 3.22 [0.199] 2.77 [0.250] 2.01 [0.367] 3.73 [0.155]

Heteroscedasticity F(1,93) 2.09 [0.152] 0.17 [0.681] 2.37 [0.127] 0.10 [0.753]

Japan

Serial Correlation F(4,84) 0.39 [0.812] 0.82 [0.514] 3.00 [0.023]* 1.28 [0.284]

Normality χ2(2) 0.49 [0.782] 0.39 [0.824] 0.46 [0.794] 0.03 [0.984]

Heteroscedasticity F(1,93) 7.12 [0.009]** 0.90 [0.345] 2.05 [0.155] 2.68 [0.105]

US

Serial Correlation F(4,83) 3.55 [0.010]* 1.77 [0.142] 2.56 [0.045]* 16.18 [0.000]**

Normality χ2(2) 5.96 [0.051] 1.37 [0.503] 1.96 [0.375] 0.65 [0.721]

Heteroscedasticity F(1,93) 1.26 [0.265] 0.29 [0.592] 10.30 [0.002]** 0.03 [0.867]

Notes: the figures in square brackets are probability values associated with test statistics.

The symbols "*" and "**" denote statistical significance at the 5 percent and the 1 percent respectively.

Table 6: Cointegration rank statistics

H0 H1 Argentina Bolivia Brazil 95% 90%

r = 0 r = 1 277.51 111.90 85.90 40.98 38.04

H0 H1 Argentina Bolivia Brazil 95% 90%

r = 0 r = 1 338.70 180.60 122.84 90.02 85.59

Notes: the last two columns report the critical values at the 95 percent and 90 percent significance level. Statistics in bold indicate acceptance of the null hypothesis at the 5 percent significance level.

Table 7: Average cross-section correlations of residuals

Argentina Bolivia Brazil Chile Mexico Peru Euro Area Japan US

0.02 0.02 0.00 -0.03 -0.02 0.00 -0.04 -0.02 0.01

[0.17] [0.22] [0.01] [-0.28] [-0.19] [-0.01] [-0.38] [-0.24] [0.07]

0.04 -0.02 0.01 0.00 0.03 0.00 0.01 0.03 0.00

[0.37] [-0.19] [0.13] [-0.02] [0.30] [-0.01] [0.12] [0.30] [0.04]

0.01 0.01 0.02 0.01 0.02 0.02 -0.01 -0.06 -0.03

[0.09] [0.13] [0.16] [0.14] [0.21] [0.19] [-0.10] [-0.53] [-0.34]

0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01

[0.13] [0.44] [0.31] [0.25] [-0.05] [-0.00] [-0.15] [0.13] [-0.05]

Notes: each entry is the average correlation of the residual of the equation on the corresponding row for the country/region on the corresponding column with all other countries/regions endogenous variables residuals.

Two-tailed t-test statistics with 93 d.f.are in square brackets. The null hypothesis is no correlation. The 5 percent critical value is 1.98.

q nfa

y sr

Table 8: F statistics for testing the weak exogeneity of the country-speci…c foreign variables and oil prices Country

y* sr* oil

Argentina F(1,85) 0.58 [0.450] 1.11 [0.296] 0.08 [0.772]

Bolivia F(2,84) 0.49 [0.613] 0.04 [0.965] 2.79 [0.067]

Brazil F(1,85) 0.16 [0.693] 1.92 [0.170] 0.25 [0.618]

Chile F(2,84) 1.47 [0.237] 2.20 [0.117] 0.09 [0.911]

Mexico F(1,85) 6.47 [0.013]* 0.14 [0.706] 0.39 [0.534]

Peru F(1,85) 0.07 [0.799] 16.44 [0.000]** 0.43 [0.512]

Euro Area F(2,84) 1.07 [0.349] 0.40 [0.669] 5.36 [0.006]**

Japan F(1,85) 0.05 [0.822] 3.78 [0.055] 0.66 [0.420]

US F(4,82) 3.13 [0.019]* 0.91 [0.464] 2.39 [0.058]

Foreign variables and oil prices

Notes: the figures in square brackets are probability values associated with test statistics. The symbols "*" and "**" denote statistical significance at the 5 percent and the 1 percent respectively.

Table 9: Generalized variance decomposition of the forecast error of output

y sr rer nfa US EA JAP

0 62.76 2.10 0.01 0.60 20.48 6.38 3.90 3.76 65.47 34.53

4 60.97 5.13 0.03 0.43 20.93 5.53 3.14 3.84 66.56 33.44

8 61.29 5.32 0.03 0.39 20.93 5.30 3.03 3.70 67.04 32.96

12 61.55 5.40 0.03 0.37 20.94 5.13 2.99 3.60 67.34 32.66

20 61.83 5.46 0.03 0.33 20.97 4.92 2.96 3.49 67.66 32.34

40 61.98 5.52 0.03 0.29 21.06 4.75 2.93 3.42 67.83 32.17

0 69.16 6.44 0.68 0.33 19.73 0.80 0.98 1.89 76.61 23.39

4 53.71 22.71 1.81 0.06 15.48 1.69 2.19 2.35 78.30 21.70

8 41.11 30.35 5.76 0.02 15.56 1.83 3.21 2.17 77.23 22.77

12 33.42 32.58 10.33 0.01 16.18 1.74 3.85 1.90 76.34 23.66

20 24.34 29.79 20.55 0.09 17.51 1.80 4.30 1.61 74.77 25.23

40 12.00 14.31 42.63 1.22 19.79 4.32 2.92 2.83 70.15 29.86

0 75.54 0.26 0.65 5.24 9.05 3.55 0.74 4.96 81.69 18.31

4 76.18 0.25 1.35 4.46 9.58 3.54 0.67 3.98 82.23 17.77

8 75.99 0.15 2.18 3.78 10.19 3.56 0.77 3.38 82.10 17.90

12 75.48 0.12 2.97 3.26 10.71 3.59 0.91 2.96 81.83 18.17

20 74.28 0.15 4.28 2.56 11.49 3.66 1.16 2.42 81.27 18.73

40 72.19 0.28 6.13 1.75 12.52 3.74 1.57 1.81 80.35 19.65

0 56.83 4.51 0.34 0.20 24.54 8.53 1.70 3.36 61.87 38.13

4 55.98 5.36 1.34 0.32 24.07 8.02 1.07 3.83 63.00 37.00

8 49.69 3.52 7.78 2.34 24.94 7.01 0.93 3.79 63.33 36.67

12 39.10 2.43 17.25 5.78 24.79 5.90 1.37 3.38 64.56 35.44

20 20.17 3.50 32.08 11.71 22.74 4.52 2.91 2.36 67.47 32.53

40 4.80 7.47 41.46 16.12 19.78 4.17 4.93 1.28 69.85 30.15

0 69.31 0.06 1.00 1.09 15.83 8.50 2.14 2.07 71.46 28.54

4 54.31 6.79 6.26 3.41 14.00 9.70 3.40 2.12 70.77 29.23

8 40.27 15.99 11.48 5.57 12.35 8.04 3.79 2.51 73.31 26.69

12 30.34 23.18 15.01 6.95 11.28 6.48 3.85 2.91 75.48 24.52

20 19.47 31.74 18.63 8.28 10.22 4.58 3.66 3.42 78.13 21.87

40 11.00 39.49 21.21 9.17 9.36 2.98 3.13 3.67 80.87 19.13

0 58.42 4.21 0.03 18.06 13.29 2.40 1.67 1.91 80.72 19.28

4 55.27 1.87 0.36 20.83 14.45 4.30 1.01 1.91 78.33 21.67

8 45.75 3.84 1.39 20.33 20.21 5.45 1.14 1.88 71.31 28.69

12 35.71 7.66 2.54 18.33 26.73 5.54 1.60 1.89 64.24 35.76

20 22.36 14.12 4.25 14.69 35.52 4.61 2.57 1.88 55.41 44.59

40 10.92 20.55 6.26 11.29 41.88 3.84 3.55 1.71 49.01 50.99

Notes: share of the k-step ahead forecast error variance of domestic output explained by the shocks on the corresponding column.

Entries have been normalized so that they sum to 100. Each entry in columns "All domestic factors" and "All foreign factors" are the sum of the corresponding percentages in columns 2, 3, 4, 5 and in columns 6, 7, 8, 9, respectively.

Bolivia

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