## 1. Partnership Between Nigerian Banks and Foreign Asset Managers

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### I. Introduction
- Context: Debate on "decoupling" — whether emerging markets could continue to grow despite a US slowdown.
- Background claims cited by proponents:
  - Emerging markets constitute 30 percent of the world economy and contribute 60 percent of global growth.
  - Working age population in emerging market countries will rise by one billion people by 2050, while the same group will shrink by 120 million in developed countries (Garner (2008) cited).
- Crisis context:
  - US recession began in December 2007 (NBER).
  - Global spillovers from the US subprime crisis affected equity and commodity prices, remittances, trade financing, foreign direct investment, and commodity prices.
  - Projected increase in financing requirements of low-income countries by as much as US$25 billion (IMF, 2009).
- Nigeria-specific effects:
  - Over 90 percent of Nigeria’s foreign exchange earnings and public sector revenue come from exports of crude oil.
  - Fall in crude oil price led to rapid depreciation of the exchange rate and reversal of the trade balance from surplus to deficit.
  - Plummeting of share prices and market capitalization; remittances projected to fall by as much as 20 percent.
- Paper objective:
  - Examine magnitude and transmission channels of spillovers to Nigeria from key trading partners and from shocks captured by the PPP-implied exchange rate.
  - Measure relative importance and contribution of trade linkages, financial channels, and commodity prices.
- Structure: Sections on stylized facts; data; VAR models; contributions of trade, commodity prices and finance; policy implications.

### II. Trade and Financial Linkages (stylized facts)
- Trade openness:
  - Trade openness (exports + imports to GDP) rose from just above 3 percent in 1991 to over 11 percent by 2008.
  - 2008 moderation partly reflects unrest in Nigeria’s oil-producing Niger Delta region.
- Direction of trade (shares of exports):
  - US: nearly 45 percent of Nigeria’s exports.
  - EU: over 25 percent of Nigeria’s exports.
  - Brazil: about 6 percent of total exports.
  - Within the EU, Spain accounts for over 30 percent of exports to the EU; France, Germany and The Netherlands also prominent.
- Banking linkages:
  - Major recapitalization in 2004 resulted in 24 commercial banks.
  - Top 14 banks have strong ties to foreign asset managers; central bank decision (February 2006) awarded management of Nigeria’s external reserves to foreign asset managers with local partnership agreements.
  - Table 1 (Central Bank of Nigeria Press Release, October 2006) lists pairings between Nigerian banks and foreign asset managers.
- FDI and remittances:
  - Net FDI increased steadily from 2000 with a peak of about $8.7 billion in 2006; sharp decline in 2008.
  - Nigeria is the single largest recipient of remittances in Sub-Saharan Africa and accounts for about 65 percent of total remittances in West Africa (Orozco, 2003a, 2003b).
  - Remittances represent about 7 percent of the country’s GDP (World Bank, 2007).
- Business cycle correlations:
  - Fairly similar turning points between Nigeria and key trading partners (plots for US, EU, Brazil vs Nigeria shown for 1996Q1–2008Q3).

### III. Description of Data
- Sample and variables:
  - Quarterly data spanning 1996Q1 to 2008Q4.
  - Real GDP growth rate for the US, the EU, Brazil, and Nigeria.
  - Nigerian PPP-implied exchange rate, net exports, and inflation.
  - Non-energy component of the Goldman Sachs Commodity Index and average petroleum spot price (APSP) of crude oil.
- Data sources and transformations:
  - EU Real GDP: Eurostat; seasonally adjusted harmonized ESA95 quarterly GDP in millions of chained 2000 euros.
  - US GDP: Bureau of Economic Analysis; seasonally adjusted in billions of chained US 2000 dollars.
  - Brazil GDP: Annual GDP in billions of Reais at 1995 prices from IMF WEO converted to quarterly using Eviews "Quadratic Match Sum".
  - All Nigerian Data: Annual data from IMF WEO converted to quarterly using Eviews "Quadratic Match Sum".
- Stationarity:
  - All variables found to be stationary using the Ng-Perron unit root test.
  - Table 2 presents Ng-Perron test statistics with critical values; *, **, and *** denote rejection of the unit root hypothesis at the 1 percent, 5 percent, and 10 percent levels, respectively.
- Covariance/correlation notes:
  - EU–US correlation about 0.6.
  - Nigeria’s GDP has weak correlations with major trading partners, but covariances appear stronger.

### IV. Methodology
- Econometric approach:
  - Base and extended vector autoregression (VAR) models to assess spillovers, using impulse responses and variance decomposition.
- Ordering and variables:
  - Base VAR Cholesky ordering: US real GDP growth, EU real GDP growth, Brazil real GDP growth, Nigeria real GDP growth, PPP-implied (real) exchange rate.
  - Extended VAR includes Oil price Growth and orders: Oil price Growth, US GDP, EU GDP, Brazil GDP, Nigeria GDP, PPP-implied exchange rate.
- Lags and estimation:
  - VAR models estimated with two lags based on lag selection results (Table 3).
  - Sensitivity check planned with four lags.
  - All models estimated using Eviews 6.0.
- Channel decomposition method:
  - Augment original VAR by introducing proxies for channels as exogenous variables in separate VARs; difference between base and augmented impulse responses yields channel contribution (ji K,i = IR_i - IR_{ji}).
  - Proxies:
    - Trade linkages: Nigeria’s net exports (exogenous).
    - Financial linkages: London Interbank Offer Rate (LIBOR) (exogenous).
    - Commodity prices: non-energy component of the Goldman Sachs Commodity Index and average petroleum spot price (APSP) (exogenous).

### V. Results

- Estimation sample and technical:
  - Sample: 1996Q1–2008Q4; included observations: 50 (Appendix: VAR Granger Causality/Block Exogeneity Wald Tests).

A. Base VAR Model Results
- Lag choice: two lags.
- Variance decomposition for Nigeria’s Real GDP Growth (Base VAR Model):
  - Over a 12-quarter horizon, variations in US GDP explain about a third of variations in Nigeria’s GDP.
  - US effect rises over time with a peak of over 50 percent by the end of the second year.
  - Brazil’s GDP growth contributes substantially (about 26 percent on average) with an early peak at about 44 percent in the second quarter.
  - EU contributes the least among the three trading partners.
  - Exchange rate changes (PPP-implied) explain an insignificant share of variations in Nigeria’s GDP.
- Impulse responses (normalized to percentage change in Nigeria’s GDP for one percent shocks):
  - One percentage point shock in US GDP growth: peak of about 1¼ percent increase in Nigeria’s GDP in the 5th quarter following the shock.
  - EU shock: peak about 1¾ percent in the third quarter.
  - Brazil shock: peak about 1½ percent in the second quarter.
  - Appreciation of exchange rate contemporaneously depresses Nigeria’s GDP growth; responses hover around zero from the sixth quarter of the 12-quarter horizon.

B. Extended VAR Model Results (includes Oil price Growth)
- Variance decomposition (extended model):
  - Trading partner GDP variations continue to explain a substantial part of variations in Nigeria’s GDP.
  - US GDP growth accounts for about a third of variations in Nigeria’s GDP growth over the 12-quarter horizon.
  - On average, about 7 ¼ percent of variations in Nigeria’s GDP are attributable to variations in Brazil’s GDP growth.
  - Over the 12-quarter horizon, EU GDP growth accounts for about 14 percent of variations in Nigeria’s GDP growth.
  - Oil price growth accounts for a quarter of variations in Nigeria’s GDP in the extended model.
  - Effect of changes in US GDP on Nigeria’s GDP rises over time and peaks at about 50 percent by the end of the second year.
- Impulse responses (extended VAR):
  - One percent shock from oil price growth: contemporaneous increase in Nigeria’s GDP growth over 12 quarters with a peak of about 1 ¾ percent in the 5th quarter.
  - Shocks from US, EU, Brazil increase Nigeria’s GDP growth with peaks of about 3.1 percent (US), 1.6 percent (EU), and 1.7 percent (Brazil), respectively.
  - Appreciation of the exchange rate contemporaneously depresses GDP growth, but GDP growth returns to positive territory around the 5th quarter after the shock.

### VI. Channels of Spillovers to Nigeria
- Method: Augment base VAR with exogenous proxies for channels and compute contribution as difference in impulse responses (following Bayoumi and Swiston, 2007; Obiora, 2009).
- Proxies used:
  - Trade: Nigeria’s net exports (exogenous).
  - Finance: LIBOR (exogenous).
  - Commodity prices: non-energy Goldman Sachs Commodity Index and APSP of crude oil (exogenous).
- Contribution to overall spillovers in Nigeria (tabulated summary as presented in source):
  - US: Finance 15.6, Trade 38.7, Comm-prices 45.7
  - EU: Finance 19.8, Trade 41.3, Comm-prices 38.9
  - Brazil: Finance 12.0, Trade 39.0, Comm-prices 49.0
- Key interpretations:
  - Trade and commodity prices account for over 80 percent of spillovers to Nigeria from each main trading partner.
  - Commodity price linkages alone account for over 70 percent of spillovers from the EU.
  - Financial linkages account for about 16 percent of spillovers on average.
  - Dominance of trade and commodity price channels is consistent with Nigeria’s export structure concentrated in crude oil.
  - Nigerian banks have limited direct linkages to banking systems in advanced countries, limiting direct financial spillovers.

### VII. Conclusion and Lessons for Policy
- Main conclusion:
  - Results from both base and extended VAR models debunk the "decoupling theory" for Nigeria: significant cross-country spillovers from the US and other major trading partners exist.
- Dynamics:
  - Effect of a shock from the US rises over time in Nigeria with peaks around the end of the second year following the shock.
- Dominant channels:
  - Trade and commodity price linkages are the most dominant channels of spillovers from the US to Nigeria.
- Policy implications:
  - Policymakers in Nigeria need to monitor economic developments in key trading partners, especially the US and EU.
  - Recognize that shocks from the US and the EU may have larger effects over time (variance decomposition results).
- Suggestions for further research:
  - Evaluate extent of spillovers from the US to regional trading blocs in developing and emerging market countries and to major emerging market countries individually to gain fuller understanding of cross-country linkages and the decoupling debate.

*Source: _wp09218*

### 1. Partnership Between Nigerian Banks and Foreign Asset Managers ..........................9

### 1. Partnership Between Nigerian Banks and Foreign Asset Managers

### Table of contents (sections listed)
- 1. Partnership Between Nigerian Banks and Foreign Asset Managers ..........................9
- 2. Results of Unit Root Tests Using the Ng-Perron Procedure.....................................14
- 3.      Lag      Length      Selection ................................................................................................16
- 4. Variance Decomposition for Nigeria’s Real GDP (Base VAR Model) ...................17
- 5. Variance Decomposition for Nigeria’s Real GDP (Extended VAR Model) ............20

### Figures (titles and numbering)
- 1. Nigeria’s Trade Openness (in percent of GDP, 1991–2008) ......................................7
- 2. Nigeria: Direction of Trade in Goods and Services  
  (in percent of total, 1990–2007)..................................................................................8
- 3 Nigeria: Main Exports Markets in the EU (1990–2007). ...........................................8
- 4. Net Foreign Direct Investment in Nigeria 
  (in billions of US Dollars, 1980–2008)....................................................................10
- 5. Remittances to Nigeria (in millions of US Dollars, 1995–2007)..............................10
- 6. Business Cycle Correlations Between Nigeria and its Key Trading Partners...... ..11
- 7. Quarterly Real GDP Growth Rates...........................................................................13
- 8. Nigeria: GDP Growth Responses to 1 Percent Shocks from Major Trading Partners 
  and PPP-implied Exchange Rate (Base VAR Model)................................... 18
- 9. Nigeria: GDP Growth Responses to 1 Percent Shocks from Major  Trading Partners,  
  Oil Price Growth, and PPP-implied Exchange Rate (Extended VAR Model)....... 21
- 10.    Decomposition of Spillovers from Nigeria’s Key Trading Partners ........................24

### Appendix and References
- References..........................................................................................................................27
- Appendix

*Source: _wp09218 - 1. Partnership Between Nigerian Banks and Foreign Asset Managers ..........................9*

### 1. VAR Granger Causality/Block Exogeneity Wald Test ............................................29

### 1. VAR Granger Causality/Block Exogeneity Wald Test ............................................29

### I. INTRODUCTION
- Context: Debate on "decoupling" — whether emerging markets could continue to grow despite a US slowdown.
- Key background claims by decoupling proponents:
  - Emerging markets constitute 30 percent of the world economy and contribute 60 percent of global growth.
  - Working age population in emerging market countries will rise by one billion people by 2050, while the same group will shrink by 120 million in developed countries (Garner (2008) cited).
- Crisis context:
  - US recession began in December 2007 (NBER).
  - Global spillovers from the US subprime crisis affected equity and commodity prices, remittances, trade financing, foreign direct investment, and commodity prices.
  - Projected increase in financing requirements of low-income countries by as much as US$25 billion (IMF, 2009).
- Nigeria-specific effects from the global crisis:
  - Over 90 percent of Nigeria’s foreign exchange earnings and public sector revenue come from exports of crude oil.
  - Fall in crude oil price led to rapid depreciation of the exchange rate and reversal of the trade balance from surplus to deficit.
  - Plummeting of share prices and market capitalization; remittances projected to fall by as much as 20 percent.
- Paper objective:
  - Examine magnitude and transmission channels of spillovers to Nigeria from key trading partners and from shocks captured by the PPP-implied exchange rate.
  - Measure relative importance and contribution of trade linkages, financial channels, and commodity prices.
- Structure: Section II — stylized facts on trade and financial linkages; III — data description; IV — VAR models; V — contribution estimation of trade, commodity prices and finance; VI — policy implications.

### II. TRADE AND FINANCIAL LINKAGES
- Trade openness:
  - Trade openness (exports + imports to GDP) rose from just above 3 percent in 1991 to over 11 percent by 2008.
  - 2008 moderation partly reflects unrest in Nigeria’s oil-producing Niger Delta region.
- Direction of trade:
  - US accounts for nearly 45 percent of Nigeria’s exports.
  - EU accounts for over 25 percent of Nigeria’s exports.
  - Brazil accounts for about 6 percent of total exports.
  - Within the EU, Spain accounts for over 30 percent of exports to the EU; France, Germany and The Netherlands also prominent.
- Banking linkages:
  - Major recapitalization in 2004 resulted in 24 commercial banks.
  - Top 14 banks have strong ties to foreign asset managers; central bank decision (February 2006) awarded management of Nigeria’s external reserves to foreign asset managers with local partnership agreements.
  - Table 1 lists pairings between Nigerian banks and foreign asset managers (source: Central Bank of Nigeria Press Release, October 2006).
- FDI and remittances:
  - Net FDI increased steadily from 2000 with a peak of about $8.7 billion in 2006; sharp decline in 2008.
  - Nigeria is the single largest recipient of remittances in Sub-Saharan Africa and accounts for about 65 percent of total remittances in West Africa (Orozco, 2003a, 2003b).
  - Remittances represent about 7 percent of the country’s GDP (World Bank, 2007).
- Business cycle correlations:
  - Fairly similar turning points between Nigeria and key trading partners (plots for US, EU, Brazil vs Nigeria shown for 1996Q1–2008Q3).

### III. DESCRIPTION OF DATA
- Sample and variables:
  - Quarterly data spanning 1996Q1 to 2008Q4.
  - Real GDP growth rate for the US, the EU, Brazil, and Nigeria.
  - Nigerian PPP-implied exchange rate, net exports, and inflation.
  - Non-energy component of the Goldman Sachs Commodity Index and average petroleum spot price (APSP) of crude oil.
- Data sources and transformations:
  - EU Real GDP: Eurostat; seasonally adjusted harmonized ESA95 quarterly GDP in millions of chained 2000 euros.
  - US GDP: Bureau of Economic Analysis; seasonally adjusted in billions of chained US 2000 dollars.
  - Brazil GDP: Annual GDP in billions of Reais at 1995 prices from IMF WEO converted to quarterly using Eviews "Quadratic Match Sum".
  - All Nigerian Data: Annual data from IMF WEO converted to quarterly using Eviews "Quadratic Match Sum".
- Stationarity:
  - All variables found to be stationary using the Ng-Perron unit root test.
  - Table 2 presents Ng-Perron test statistics with critical values; *, **, and *** denote rejection of the unit root hypothesis at the 1 percent, 5 percent, and 10 percent levels, respectively.
- Covariance/correlation notes:
  - EU–US correlation about 0.6.
  - Nigeria’s GDP has weak correlations with major trading partners, but covariances appear stronger (table of covariance and correlation statistics provided).

### IV. METHODOLOGY
- Econometric approach:
  - Combination of a base and an extended vector autoregression (VAR) model to assess spillovers, using impulse responses and variance decomposition.
  - Cholesky decomposition ordering in base VAR: US real GDP growth, EU real GDP growth, Brazil real GDP growth, Nigeria real GDP growth, PPP-implied (real) exchange rate — ordering based on relative exogeneity.
  - Extended VAR includes Oil price Growth and orders: Oil price Growth, US GDP, EU GDP, Brazil GDP, Nigeria GDP, PPP-implied exchange rate.
- Lags and estimation:
  - VAR models estimated with two lags based on lag selection results (Table 3).
  - Sensitivity: plan to use four lags as robustness check.
  - All models estimated using Eviews 6.0.
- Channel decomposition methodology (section VI expands):
  - Augment original VAR by introducing proxies for channels as exogenous variables in separate VARs; difference between base and augmented impulse responses yields channel contribution:
    - ji K,i = IR_i - IR_{ji}  (equation (3) in text)
  - Proxies:
    - Trade linkages: Nigeria’s net exports (exogenous).
    - Financial linkages: London Interbank Offer Rate (LIBOR) (exogenous).
    - Commodity prices: non-energy component of the Goldman Sachs Commodity Index and average petroleum spot price (APSP) (exogenous).

### V. RESULTS
A. Base VAR Model Results
- Lag choice: two lags (Table 3).
- Variance decomposition for Nigeria’s Real GDP Growth (Base VAR Model, Table 4):
  - Over a 12-quarter horizon, variations in US GDP explain about a third of variations in Nigeria’s GDP.
  - US effect rises over time with a peak of over 50 percent by the end of the second year (interpreted as Nigeria suffering US shocks until about 2010).
  - Brazil’s GDP growth contributes substantially (about 26 percent on average) with an early peak at about 44 percent in the second quarter.
  - EU contributes the least among the three trading partners.
  - Exchange rate changes (PPP-implied) explain an insignificant share of variations in Nigeria’s GDP.
- Impulse responses (normalized to percentage change in Nigeria’s GDP for one percent shocks):
  - One percentage point shock in US GDP growth: peak of about 1¼ percent increase in Nigeria’s GDP in the 5th quarter following the shock.
  - EU shock: peak about 1¾ percent in the third quarter.
  - Brazil shock: peak about 1½ percent in the second quarter.
  - Appreciation of exchange rate contemporaneously depresses Nigeria’s GDP growth; responses hover around zero from the sixth quarter of the 12-quarter horizon.

B. Extended VAR Model Results (includes Oil price Growth)
- Key variance decomposition results (Table 5):
  - Variations in trading partner GDP continue to explain a substantial part of variations in Nigeria’s GDP.
  - US GDP growth accounts for about a third of variations in Nigeria’s GDP growth over the 12-quarter horizon.
  - On average, about 7 ¼ percent of variations in Nigeria’s GDP are attributable to variations in Brazil’s GDP growth.
  - Over the 12-quarter horizon, EU GDP growth accounts for about 14 percent of variations in Nigeria’s GDP growth.
  - Oil price growth accounts for a quarter of variations in Nigeria’s GDP in the extended model.
  - Effect of changes in US GDP on Nigeria’s GDP rises over time and peaks at about 50 percent by the end of the second year.
- Impulse responses (extended VAR, Figure 9):
  - One percent shock from oil price growth: contemporaneous increase in Nigeria’s GDP growth over 12 quarters with a peak of about 1 ¾ percent in the 5th quarter.
  - Shocks from US, EU, Brazil increase Nigeria’s GDP growth with peaks of about 3.1 percent (US), 1.6 percent (EU), and 1.7 percent (Brazil), respectively.
  - Appreciation of the exchange rate contemporaneously depresses GDP growth, but GDP growth returns to positive territory around the 5th quarter after the shock.

### VI. CHANNELS OF SPILLOVERS TO NIGERIA
- Method: Augment base VAR with exogenous proxies for channels and compute contribution as difference in impulse responses (following Bayoumi and Swiston, 2007; Obiora, 2009).
- Proxies used:
  - Trade: Nigeria’s net exports (exogenous).
  - Finance: LIBOR (exogenous).
  - Commodity prices: non-energy Goldman Sachs Commodity Index and APSP of crude oil (exogenous).
- Contribution results (Figure 10 and summary table):
  - Contribution to overall spillovers in Nigeria (in percent) [tabulated in text as]:
    - US: Finance 15.6, Trade 38.7, Comm-prices 45.7 (presented as "U S15 . 638 .745 . 7" in source formatting)
    - EU: Finance 19.8, Trade 41.3, Comm-prices 38.9 (presented as "E U19 . 841 .338 . 9")
    - Brazil: Finance 12.0, Trade 39.0, Comm-prices 49.0 (presented as "BRAZIL12.039.049.0")
  - Trade and commodity prices account for over 80 percent of spillovers to Nigeria from each main trading partner.
  - Commodity price linkages alone account for over 70 percent of spillovers from the EU.
  - Financial linkages account for about 16 percent of spillovers on average.
- Interpretation:
  - Dominance of trade and commodity price channels expected given Nigeria’s export structure (crude oil).
  - Nigerian banks have limited direct linkages to banking systems in advanced countries, limiting direct financial spillovers.

### VII. CONCLUSION AND LESSONS FOR POLICY
- Main conclusion:
  - Results from both base and extended VAR models debunk the "decoupling theory" for Nigeria: significant cross-country spillovers from the US and other major trading partners exist.
- Dynamics:
  - Effect of a shock from the US rises over time in Nigeria with peaks around the end of the second year following the shock.
- Dominant channels:
  - Trade and commodity price linkages are the most dominant channels of spillovers from the US to Nigeria.
- Policy implications:
  - Policymakers in Nigeria need to monitor economic developments in key trading partners, especially the US and EU.
  - Recognize that shocks from the US and the EU may have larger effects over time (variance decomposition results).
- Suggestions for further research:
  - Evaluate extent of spillovers from the US to regional trading blocs in developing and emerging market countries and to major emerging market countries individually to gain fuller understanding of cross-country linkages and the decoupling debate.

*Source: _wp09218 - 1. VAR Granger Causality/Block Exogeneity Wald Test ............................................29*

### REFERENCES

### _wp09218 - REFERENCES

### References
- Bayoumi, T., and A. Swiston, 2007, “Foreign Entanglements: Estimating the Source and Size of Spillovers across Industrial Countries,” IMF Working Paper WP/07/182. (Washington: International Monetary Fund).
- DeJong, D. N., J. C. Nankervis, N. E. Savin and C. H. Whiteman, 1992, “Integration Versus Trend Stationary in Time Series,” Econometrica, Vol. 60, No. 2, pp. 423-433
- Dutse, A.Y. (2008) “Nigeria’s Economic Growth: Emphasizing the Role of Foreign Direct Investment in Transfer of Technology” Communications of IBIMA, Vol3, 2008
- Eviews 6.0, 2007, Quantitative Micro Software (by Lilien, D, et al)
- Harris, R., and R. Sollis, 2003, “Applied Time Series Modeling and Forecasting,” New York: John Wiley and Sons.
- Herrero, A., and J. M. Ruiz, 2008, “Do Trade and Financial Linkages Foster Business Cycle Synchronization in a Small Economy?” Banco De Espana Working Paper No. 0810
- Imbs, J., 2003, “Trade Finance, Specialization, and Synchronization,” IMF Working Paper 03/81 (Washington: International Monetary Fund).
- Inklaar, R., R. Jong-A-Pin, and J. De Haan, 2005, “Trade and Business Cycle Synchronization in OECD Countries: A Re-Examination,” CESifo Working Paper Series No. 1546
- International Monetary Fund, 2007, “Decoupling the Train? Spillovers and Cycles in the Global Economy” World Economic Outlook, (April), pp. 121-159
- International Monetary Fund, 2009, “Implications of the Global Crisis for Low-Income Countries” Special Report, (March, 2009),
- Kanda, D, 2007, “Spillovers to Ireland,” IMF Working Paper WP/08/2 (Washington: International Monetary Fund).
- Koopman, S. J. and J. V. Azevedo, 2008, “Measuring Synchronization and Convergence of Business Cycles for the Euro area, UK and US,” Oxford Bulletin of Economics and Statistics, Vol. 70, No. 1 pp. 23-51
- Kose, M.A., C. Otrok, and C. H. Whiteman, 2003, “International Business Cycles: World, Region, and Country-Specific Factors,” American Economic Review, Vol. 93, No 4, pp. 1216–39.
- ———, E. Prasad, and M.E. Terrones, 2003a, “How Does Globalization Affect the Synchronization of Business Cycles,” IMF Working Paper 03/27 (Washington: International Monetary Fund).
- Ng, S., and P. Perron, 2001, “Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power,” Econometrica, Vol. 69, pp. 1519–54.
- Obiora, K. I., 2009, “Decoupling from the East Toward the West? Analyses of Spillovers to the Baltic Countries,” IMF Working Paper WP/09/125 (Washington: International Monetary Fund).
- Orozco, Manuel. 2003a. “Remittances, Markets and Development.”, Inter-American Dialogue, Washington, D.C.
- ———. 2003b. “Worker Remittances: An International Comparison.” Working Paper Commissioned by the Multilateral Investment Fund, Inter-American Development Bank.
- Schiff, P. D. and J. Downes, 2007, “Crash Proof: How to Profit from the Coming Economic Collapse”, New Jersey: John Wiley& Sons Inc.
- Swiston, A. and T. Bayoumi, 2008, “Spillovers Across NAFTA,” IMF Working Paper WP/08/3 (Washington: International Monetary Fund).
- World Bank, 2007, “Migration and Remittances Factbook”, (Washington, DC).

### Appendix: VAR Granger Causality/Block Exogeneity Wald Tests
- Sample: 1996Q1 2008Q4
- Included observations: 50

Dependent variable: BRAZIL GDP Growth
- Excluded: Y_EU; Chi-sq: 1.9794932; df: 2; Prob.: 0.0127
- Excluded: Y_NGR; Chi-sq: 5.4819372; df: 2; Prob.: 0.5973
- Excluded: Y_US; Chi-sq: 6.2337672; df: 2; Prob.: 0.6370
- Excluded: All; Chi-sq: 14.047346; df: ?; Prob.: 0.0312

Dependent va ri able : EU  G DP  G row th
- Excluded: Y_BRA; Chi-sq: 5.1523942; df: 2; Prob.: 0.0761
- Excluded: Y_NGR; Chi-sq: 0.0389032; df: 2; Prob.: 0.9807
- Excluded: Y_US; Chi-sq: 3.9629532; df: 2; Prob.: 0.1379
- Excluded: All; Chi-sq: 10.306466; df: ?; Prob.: 0.0764

Dependent variable: NIGERIA GDP Growth
- Excluded: Y_BRA; Chi-sq: 2.2425832; df: 2; Prob.: 0.3259
- Excluded: Y_EU; Chi-sq: 3.6116972; df: 2; Prob.: 0.1643
- Excluded: Y_US; Chi-sq: 13.821992; df: 2; Prob.: 0.0010
- Excluded: All; Chi-sq: 16.473966; df: ?; Prob.: 0.0114

Dependent variable: US GDP Growth
- Excluded: Y_BRA; Chi-sq: 8.7392522; df: 2; Prob.: 0.3717
- Excluded: Y_EU; Chi-sq: 1.030812; df: ?; Prob.: 0.0645
- Excluded: Y_NGR; Chi-sq: 0.9020992; df: 2; Prob.: 0.0443
- Excluded: All; Chi-sq: 8.862876; df: ?; Prob.: 0.1227

*Content derived from _wp09218 - REFERENCES*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2009/_wp09218.pdf_