## 1. Bilateral Trade with South Africa, 2010

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### I. Introduction — size and role of South Africa
- South Africa is the largest sub-Saharan Africa economy, accounting for over a third of Sub-Saharan Africa’s GDP and about 40 percent of its exports.
- South African GDP is closely correlated to world GDP; this correlation has increased over the last few decades.
- Intraregional trade expansion has potentially increased spillovers within the region, including from South Africa to BLNS (Botswana, Lesotho, Namibia, Swaziland).

### II. Interlinkages and trade structure
- Major channels of spillovers: exports of goods and services, remittances, foreign direct investment, cross-border banking flows, and the SACU customs revenue formula.
- Intra-SACU trade structure (2011):
  - South African exports into the region account for over 80 percent of intra-SACU trade.
  - Total intra-SACU exports of BLNS countries: 16 percent of intra-SACU trade.
  - Total intra-SACU imports of BLNS countries: about 50 percent of total intraregional trade.
  - South Africa exports to BLNS about five times the amount it imports from them.
- BLNS reliance on South Africa differs by country:
  - Botswana: United Kingdom more important than South Africa for exports.
  - Lesotho: South Africa is the only important market destination.
  - Namibia: South Africa main partner; China fairly important.
  - Swaziland: advanced economies are relatively important markets.

### III. Current account receipts, ODA, and remittances (2010)
- Exports as share of current account receipts (2010):
  - Lesotho: exports amount to about 40 percent of current account receipts.
  - Namibia and Swaziland: exports amount to about 65–70 percent of current account receipts.
- Official Development Assistance from OECD (selected, 2010) (as presented in source formatting):
  - South Africa: 0.3 percent of GDP and U.S. dollars 1,211.4 (table shows "1,211.4 363.7 0.3").
  - Lesotho: 11.3 percent of GDP (table shows "Les otho 261.9 2.3 11.3").
- Remittances:
  - Ratha and Shaw (2007) estimate remittances from South Africa to Lesotho amounted to 20 percent of Lesotho GDP.
  - Remittances to Lesotho have fallen by about 50 percent over the last 10-15 years.

### IV. Foreign direct investment and corporate presence (2010–2011)
- South Africa is the largest source of FDI for BLNS; relatively more important for smaller countries.
- SSA FDI stocks from selected countries (2010) include South Africa contributions (source table entries such as "South Africa 35.5 ... 59.9").
- Strong presence of South African nonfinancial firms across SADC and beyond (examples listed in source): Anglogold Ashanti, Impala Platinum, Anglo American Platinum, Gold Fields, Illovo, Sasol, Nampak, South African Breweries, Massmart, Tiger Brands, Shoprite, Pick n Pay, MTN, Telkom, etc.
- Selected Pan-African financial groups (2011 entries in source): Standard Bank Group/Stanbic, ABSA, Nedbank, First Rand, Barclays group, Old Mutual, Sanlam, Ecobank (percent-share distributions shown in source).

### V. Cross-border banking and financial linkages (2010)
- Deposits in South Africa as percent of GDP (selected entries from source):
  - Lesotho: 20.0
  - Namibia: 3.3
  - Swaziland: 9.7
  - Malawi: 0.4
  - Mauritius: 0.7
  - Mozambique: 1.3
  - Zimbabwe: 1.1
- Because financial systems in BLNS are much less developed than in South Africa, South Africa may act as a conduit in transmission of external financial shocks.

### VI. Monetary, exchange rate arrangements, and SACU fiscal linkages
- South Africa, Lesotho, Namibia, and Swaziland form the Multilateral Monetary Area; LNS currencies are pegged to the rand and the rand circulates freely.
- Botswana’s currency has traded closely to the rand.
- Result: South Africa de facto decides monetary policy in the region; exchange rate flexibility serves as shock absorber but increases tradable price volatility.
- SACU revenue sharing (since 2002) depends on amount of intraregional trade of each country; BLNS receive a fixed expected customs revenue each fiscal year with ex post settlement of deviations.
- Total customs revenues to be distributed depend critically on South Africa’s imports from the world.
- Consequence: volatility in customs revenues can produce sharp volatility in fiscal revenue for BLNS:
  - After the global financial crisis, customs revenue fell by about 20 percent of GDP in Lesotho and about 15 percent of GDP in Swaziland, triggering fiscal stress in Swaziland (figures reported in source).

### VII. Macroeconomic comovements (1990–2011)
- Contemporaneous correlations with world macroeconomic developments (selected entries preserved exactly):
  - South Africa: GDP 0.8, Real DD 0.8, Real GNI 0.6, Dollar GDP 0.6, Dollar GNI 0.5, Nominal exports 0.9, Nominal imports 0.9, Inflation 0.7.
  - Botswana: GDP 0.4, Real DD 0.1, Real GNI 0.1, Dollar GDP 0.7, Dollar GNI 0.7, Nominal exports 0.6, Nominal imports 0.5, Inflation 0.8.
  - Lesotho: GDP 0.1, Real DD 0.0, Real GNI 0.0, Dollar GDP 0.6, Dollar GNI 0.7, Nominal exports 0.3, Nominal imports 0.6, Inflation 0.7.
  - Namibia: mixed low real correlations but stronger nominal/dollar correlations.
  - Swaziland: mixed low real correlations but stronger nominal/dollar correlations.
- Correlations with South African macroeconomic developments (selected entries preserved exactly):
  - South Africa with itself: all correlations 1.0.
  - Botswana: GDP 0.2, Real DD 0.0, Real GNI -0.3, Dollar GDP 0.7, Dollar GNI 0.6, Nominal exports 0.7, Nominal imports 0.6, Real exports 0.6, Real imports 0.2, Inflation 0.7.
  - Lesotho: GDP -0.2, Real DD 0.1, Real GNI 0.2, Dollar GDP 1.0, Dollar GNI 0.9, Nominal exports 0.4, Nominal imports 0.6, Real exports 0.2, Real imports 0.3, Inflation 0.9.
  - Namibia: GDP 0.2, Real DD 0.0, Real GNI 0.0, Dollar GDP 0.9, Dollar GNI 0.7, Nominal exports 0.8, Nominal imports 0.6, Real exports 0.2, Real imports -0.1, Inflation 0.8.
  - Swaziland: GDP -0.2, Real DD -0.1, Real GNI 0.1, Dollar GDP 1.0, Dollar GNI 0.9, Nominal exports 0.2, Nominal imports 0.4, Real exports -0.3, Real imports -0.3, Inflation 0.7.
- Interpretation from source:
  - Real GDP growth correlations between SACU countries and world economy are relatively small except for South Africa.
  - Correlations between BLNS growth and South Africa are even smaller; some are negative for more exposed countries.
  - Nominal (dollar) comovements are significantly stronger.

### VIII. Panel data evidence (GMM, Arellano-Bond, 1986–2010, 5 countries)
- Model and variables:
  - Dependent variable: real GDP growth.
  - Main independent variables: lagged real GDP growth; World growth; South African growth; Terms of trade; Openness; Fiscal balance; Financial condition proxied by TED spread (3-month LIBOR vs. U.S. Treasury bills).
  - Sample: 5 countries (BLNS), annual data 1986–2010.
- Main numeric estimates and diagnostics (preserved exactly from source):
  - World Growth coefficient: 0.63 (t-statistics (3.78)*** in Equation 1; (2.73)*** in Equation 2).
    - Text interpretation: a 1 percentage point slowdown in world growth has on average cut growth in BLNS countries by 0.6 percentage points.
  - Fiscal deficit coefficient: 0.26 (t-statistics (6.19)*** in Equation 1; (2.23)** in Equation 2).
    - Text interpretation: a 1 percentage point decrease in fiscal balance (expenditure induced) increases growth by 0.25 percent.
  - Level terms of trade coefficient: 0.03 (t-statistics (6.58)*** in Equation 1; (1.1)* in Equation 2).
  - Financial condition coefficient (TED spread): -1.37 (t-statistics (-3.56)*** in Equation 1; (-2.21)** in Equation 2).
    - Interpretation: an increase in the TED spread lowers growth rates in BLNS countries.
  - Real GDP growth (t-1) coefficient: -0.16 (t-statistics (-1.24) in Equation 1; (-1.30) in Equation 2).
  - Number of observations: 88.
  - Diagnostic tests (GMM specification):
    - AR(1) test: p-value 0.07
    - AR(2) test: p-value 0.14
    - Sargan test: p-value 0.49
- Robustness notes from source:
  - South African growth is statistically not significant in the panel once global variables and domestic fiscal policies are included.
  - Real domestic demand growth and real exchange rate developments were not significant in alternative specifications.
  - Openness was not significant in the panel.

### IX. Spillovers evidence from Vector Autoregressions (VARs, annual data 1986–2010)
- Model specification (country i VAR includes):
  1. World real GDP growth
  2. South Africa’s domestic demand growth or real GDP growth
  3. South Africa’s real exchange rate
  4. Real growth rate for BLNS country i
- Identification: Cholesky ordering with world growth first as most exogenous.
- Impulse response and variance decomposition summaries (exact statements preserved):
  - World growth shocks spill over into GDP growth of most BLNS countries, with the exception of Lesotho.
  - South Africa’s real GDP growth does not contribute much to BLNS GDP growth after controlling for world growth, except for Lesotho.
  - Lesotho: growth in Lesotho falls when South African growth increases (possible interpretation: migration of Lesotho workers to South Africa during booms reduces Lesotho domestic production).
  - Replacing South Africa real GDP growth with real private domestic demand growth:
    - World growth remains robustly significant in all countries but Lesotho.
    - South Africa’s real domestic demand becomes positively significant for Namibia and Swaziland, and remains negatively significant for Lesotho.
  - South African real exchange rate:
    - A real appreciation in South Africa tends to reduce growth in Botswana (competitiveness channel) and increase growth in Swaziland.
    - Appears insignificant for Lesotho and Namibia.
  - Variance decompositions:
    - World growth is the most important variable for Botswana, Namibia, and Swaziland; its importance increases over time for Namibia and Swaziland.
    - For Lesotho, South African developments (GDP or domestic demand growth) are the most important short-run determinants; over time world growth and the South African real exchange rate gain importance.
    - For Botswana and Swaziland, the importance of South Africa’s real exchange rate increases over time.

### X. Impulse response directions and significance (Model 2 summary)
- Notes: "* implies significancy of the impulse response functions." "Signs in brackets show the direction of the impulse response" "All impulses are significant in the 1st period only."
- Directional summary from source:
  - Botswana: (+)*(-)*
  - Lesotho: (-)*
  - Namibia: (+)*(+)*
  - Swaziland: (+)*(+)*(+)*

### XI. Variance decompositions (Models 1 and 2 — percentages of total, preserved exactly)
- Model 1 — Variables: World economic growth; South Africa economic growth; South Africa real exchange rate
  - Year 1:
    - Botswana: 41.6 0.2 8.9
    - Lesotho: 1.0 41.4 3.3
    - Namibia: 21.0 0.0 6.3 3.5
    - Swaziland: 37.6 1.8 15.4
  - Year 5:
    - Botswana: 30.5 5.6 30.5
    - Lesotho: 20.4 30.9 10.4
    - Namibia: 43.9 2.1 5.2
    - Swaziland: 38.7 2.4 29.9
- Model 2 — Variables: World economic growth; South Africa domestic demand growth; South Africa real exchange rate
  - Year 1:
    - Botswana: 29.6 9.0 12.6
    - Lesotho: 10.1 18.2 1.4
    - Namibia: 17.6 16.0 2.8
    - Swaziland: 31.0 12.2 17.7
  - Year 5:
    - Botswana: 19.7 11.1 39.4
    - Lesotho: 17.7 14.7 17.0
    - Namibia: 37.4 11.9 8.6
    - Swaziland: 36.6 6.8 29.9

### XII. Key findings and policy implications (as presented in source)
- Global real and financial developments are significant drivers of BLNS growth:
  - A 1 percentage point slowdown in world growth reduces BLNS growth by approximately 0.6 percentage points (panel interpretation).
  - Financial conditions (TED spread) have a strong negative effect on growth (coefficient -1.37).
  - Terms of trade improvements boost growth (coefficient 0.03).
- Fiscal policy matters:
  - Evidence consistent with countercyclical fiscal policy — a 1 percentage point decrease in fiscal balance increases growth by about 0.25 percent (fiscal coefficient 0.26).
- Role of South Africa:
  - South African growth per se does not systematically transmit growth shocks to BLNS as a block once global variables and fiscal policies are controlled for; however, country-specific VARs reveal important heterogeneity with Lesotho notably more linked to South African developments.
  - Because BLNS financial systems are less developed, South Africa may act as a conduit for external financial shocks rather than amplifying or cushioning them.
- Fiscal vulnerability via SACU customs revenue sharing:
  - Volatility in South Africa’s import performance can produce large swings in BLNS customs revenue (example drops post-crisis: Lesotho about 20 percent of GDP, Swaziland about 15 percent of GDP), with significant fiscal stress implications.
- Policy relevance highlighted in source:
  - Global developments matter for BLNS growth.
  - Domestic fiscal policies influence cross-country differences; evidence consistent with effective countercyclical fiscal policy raising growth when fiscal balance decreases (expenditure-led).
  - Country-specific policies should acknowledge heterogeneity in transmission (e.g., Lesotho’s stronger link to South African labor and demand dynamics).

*Source: _wp1331 - 1. Bilateral Trade with South Africa, 2010 — https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2013/_wp1331.pdf*

### 1. Bilateral Trade with South Africa, 2010 .............................................................................

### _wp1331 - 1. Bilateral Trade with South Africa, 2010

### Section inventory (headings and page references)
- 1. Bilateral Trade with South Africa, 2010 ................................................................................5
- 2. Sub-Saharan Africa: Composition of Current Account Receipts, 2010 ..............................10
- 3. Sub-Saharan Africa: Official Development Assistance from OECD Countries .................10
- 4. Sub-Saharan Africa: Remittances, 2010 ..............................................................................11
- 5. Sub-Saharan Africa: Foreign Direct Investment Stocks from Selected Countries, 2010 ....12
- 6. Sub-Saharan Africa: Key Nonfinancial South African Firms Operating in the Region ......12
- 7. Sub-Saharan Africa: Selected Pan-African Financial Groups, 2011 ...................................13
- 8. Sub-Saharan Africa: Cross-border Banking Operations with South Africa, 2010 ..............14
- 9. Sub-Saharan Africa: Contemporaneous Correlation with World Macroeconomic 
  Developments, 1990–2011 ...................................................................................................16
- 10. Sub-Saharan Africa: Contemporaneous Correlation with South African  
  Macroeconomic Developments, 1990–2011 .......................................................................16
- 11. Explaining Growth in BLNS Countries. ............................................................................19
- 12. Model 1 and 2—Impulse Response Functions ..................................................................21
- 13. Model 1 Variance Decompositions ....................................................................................22

### Figures listed
- Figure 1. Sub-Saharan Africa: Intra Sub-Saharan Africa Trade Distribution: 1980–2010 ...................4
- Figure 2. Intra Sub-Saharan Africa Trading Network, 2010 .................................................................6
- Figure 3. South Africa Trading Network with Key Global Partners, 20101.........................................7
- Figure 4. SACU Countries: Trading Network with Key Global Partners, 2010 ...................................8
- Figure 5. Key Global Partners: Trading Network with SACU Partners, 2010 .....................................9
- Figure 6. SACU: Country Share of Customs Receipts .......................................................................15
- Figure 7. Swaziland: Fiscal Policy ......................................................................................................15

### Major thematic foci (as indicated by section headings)
- Bilateral trade patterns between South Africa and individual partners in 2010.
- Composition of current account receipts for Sub-Saharan Africa in 2010.
- Official development assistance flows to Sub-Saharan Africa from OECD countries.
- Remittance inflows to Sub-Saharan Africa in 2010.
- Foreign direct investment stock positions in Sub-Saharan Africa from selected countries (2010).
- Presence and operations of key nonfinancial South African firms in the Sub-Saharan region.
- Selected pan-African financial groups operating as of 2011.
- Cross-border banking operations linking Sub-Saharan Africa and South Africa in 2010.
- Statistical correlations of Sub-Saharan Africa with world and South African macroeconomic developments over 1990–2011.
- Empirical analysis explaining growth in BLNS countries.
- Model results: Impulse response functions for Models 1 and 2, and variance decompositions for Model 1.

### Key datasets and time coverage (explicit from headings)
- Year-specific datasets: 1980–2010 (Figure 1); 2010 (multiple sections); 2011 (selected financial groups).
- Panel/correlation analyses covering 1990–2011.

*Source: _wp1331 - 1. Bilateral Trade with South Africa, 2010 — https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2013/_wp1331.pdf*

### References .............................................................................................................

### References

### I. Introduction
- South Africa is the largest sub-Saharan Africa economy, accounting for over a third of Sub-Saharan Africa’s GDP and about 40 percent of its exports.
- South African GDP is closely correlated to world GDP; this correlation has increased over the last few decades.
- Intraregional trade expansion has potentially increased spillovers within the region, including from South Africa to BLNS (Botswana, Lesotho, Namibia, Swaziland).

### II. Interlinkages
- Major channels of spillovers: exports of goods and services, remittances, foreign direct investment, cross-border banking flows, and the SACU customs revenue formula.

Trade
- Intra-SACU trade structure (2011): South African exports into the region account for over 80 percent of intra-SACU trade.
- Total intra-SACU exports of BLNS countries: 16 percent of intra-SACU trade.
- Total intra-SACU imports of BLNS countries: about 50 percent of total intraregional trade.
- South Africa exports to BLNS about five times the amount it imports from them.
- BLNS reliance on South Africa differs by country:
  - Botswana: United Kingdom more important than South Africa for exports.
  - Lesotho: South Africa is the only important market destination.
  - Namibia: South Africa main partner; China fairly important.
  - Swaziland: advanced economies are relatively important markets.

Current Account Receipts
- Exports as share of current account receipts (2010):
  - Lesotho: exports amount to about 40 percent of current account receipts.
  - Namibia and Swaziland: exports amount to about 65–70 percent of current account receipts.
- Official Development Assistance from OECD (selected, 2010):
  - South Africa: 0.3 percent of GDP and U.S. dollars 1,211.4 (table shows "1,211.4 363.7 0.3" formatting in source).
  - Lesotho: 11.3 percent of GDP (table shows "Les otho 261.9 2.3 11.3" formatting in source).
- Remittances:
  - Ratha and Shaw (2007) estimate remittances from South Africa to Lesotho amounted to 20 percent of Lesotho GDP.
  - Remittances to Lesotho have fallen by about 50 percent over the last 10-15 years.

Foreign Direct Investment
- South Africa is the largest source of FDI for BLNS; relatively more important for smaller countries.
- SSA FDI stocks from selected countries (2010) include South Africa contributions; South Africa entry for "South Africa 35.5 ... 59.9" in table.

Financial
- Strong presence of South African banking and nonfinancial firms across SADC and beyond (list includes Anglogold Ashanti, Impala Platinum, Anglo American Platinum, Gold Fields, Illovo, Sasol, Nampak, South African Breweries, Massmart, Tiger Brands, Shoprite, Pick n Pay, MTN, Telkom, etc.).
- Selected Pan-African financial groups (share of deposits, 2010): Standard Bank Group/Stanbic, ABSA, Nedbank, First Rand, Barclays group, Old Mutual, Sanlam, Ecobank (table shows percent-share distribution across countries).
- Cross-border banking operations with South Africa (2010), deposits in South Africa as percent of GDP:
  - Lesotho: 20.0
  - Namibia: 3.3
  - Swaziland: 9.7
  - Other examples: Malawi 0.4, Mauritius 0.7, Mozambique 1.3, Zimbabwe 1.1

Monetary and Exchange Policies
- South Africa, Lesotho, Namibia, and Swaziland form the Multilateral Monetary Area; LNS currencies are pegged to the rand and the rand circulates freely.
- Botswana’s currency has traded closely to the rand.
- Result: South Africa de facto decides monetary policy in the region; exchange rate flexibility serves as shock absorber but increases tradable price volatility.

Fiscal Policies and Customs Revenue Sharing
- SACU revenue sharing (since 2002) depends on amount of intraregional trade of each country; BLNS receive a fixed expected customs revenue each fiscal year with ex post settlement of deviations.
- Total customs revenues to be distributed depend critically on South Africa’s imports from the world.
- Consequence: volatility in customs revenues can produce sharp volatility in fiscal revenue for BLNS.
  - Example: After the global financial crisis, customs revenue fell by about 20 percent of GDP in Lesotho and about 15 percent of GDP in Swaziland, triggering fiscal stress in Swaziland (figures reported in source).

### III. Macroeconomic Comovements
- Contemporaneous correlations (1990–2011) with world macroeconomic developments (selected entries from tables):
  - South Africa: GDP 0.8, Real DD 0.8, Real GNI 0.6, Dollar GDP 0.6, Dollar GNI 0.5, Nominal exports 0.9, Nominal imports 0.9, Inflation 0.7.
  - Botswana: GDP 0.4, Real DD 0.1, Real GNI 0.1, Dollar GDP 0.7, Dollar GNI 0.7, Nominal exports 0.6, Nominal imports 0.5, Inflation 0.8.
  - Lesotho: GDP 0.1, Real DD 0.0, Real GNI 0.0, Dollar GDP 0.6, Dollar GNI 0.7, Nominal exports 0.3, Nominal imports 0.6, Inflation 0.7.
  - Namibia and Swaziland: mixed low real correlations but stronger nominal/dollar correlations.
- Correlations with South African macroeconomic developments (1990–2011):
  - South Africa with itself: all correlations 1.0.
  - Botswana: GDP 0.2, Real DD 0.0, Real GNI -0.3, Dollar GDP 0.7, Dollar GNI 0.6, Nominal exports 0.7, Nominal imports 0.6, Real exports 0.6, Real imports 0.2, Inflation 0.7.
  - Lesotho: GDP -0.2, Real DD 0.1, Real GNI 0.2, Dollar GDP 1.0, Dollar GNI 0.9, Nominal exports 0.4, Nominal imports 0.6, Real exports 0.2, Real imports 0.3, Inflation 0.9.
  - Namibia: GDP 0.2, Real DD 0.0, Real GNI 0.0, Dollar GDP 0.9, Dollar GNI 0.7, Nominal exports 0.8, Nominal imports 0.6, Real exports 0.2, Real imports -0.1, Inflation 0.8.
  - Swaziland: GDP -0.2, Real DD -0.1, Real GNI 0.1, Dollar GDP 1.0, Dollar GNI 0.9, Nominal exports 0.2, Nominal imports 0.4, Real exports -0.3, Real imports -0.3, Inflation 0.7.

Key interpretation from source:
- Real GDP growth correlations between SACU countries and world economy are relatively small except for South Africa.
- Correlations between BLNS growth and South Africa are even smaller; some are negative for more exposed countries.
- Nominal (dollar) comovements are significantly stronger.

### IV. Review of Literature
- Global slowdown and commodity price effects depend on trade and financial linkages.
- IMF World Economic Outlook (April 2007, Chapter 4): on average a 1 percentage point decline in GDP growth in the Euro area is associated with a slowing in GDP growth of about 0.25 percentage point in sub-Saharan Africa.
- Deaton (1996): a decline in non-fuel commodity prices of 10 percent could reduce growth in sub-Saharan Africa by about 1.5 percent.
- Collier and Goderis (2007): positive terms of trade shocks may have positive short-term effects but adverse longer-term effects in countries with weak institutions.

### V. Panel Data Evidence (GMM, Arellano-Bond, 1986–2010, 5 countries)
Model and variables
- Dependent variable: real GDP growth.
- Main independent variables: lagged real GDP growth; World growth; South African growth; Terms of trade; Openness; Fiscal balance; Financial condition proxied by TED spread (3-month LIBOR vs. U.S. Treasury bills).
- Sample: 5 countries (BLNS) using annual data 1986–2010.

Main findings (preserve numeric estimates exactly)
- World Growth coefficient: 0.63 (t-statistics reported: (3.78)*** in Equation 1; (2.73)*** in Equation 2).
  - Interpretation: a 1 percentage point slowdown in world growth has on average cut growth in BLNS countries by 0.6 percentage points (text states 0.6 percentage points).
- Fiscal deficit coefficient: 0.26 (t-statistics (6.19)*** in Equation 1; (2.23)** in Equation 2).
  - Interpretation: a 1 percentage point decrease in fiscal balance (expenditure induced) increases growth by 0.25 percent (text states 0.25 percent).
- Level terms of trade coefficient: 0.03 (t-statistics (6.58)*** in Equation 1; (1.1)* in Equation 2).
- Financial condition coefficient: -1.37 (t-statistics (-3.56)*** in Equation 1; (-2.21)** in Equation 2).
  - Interpretation: an increase in the TED spread lowers growth rates in BLNS countries.
- Real GDP growth (t-1) coefficient: -0.16 (t-statistics (-1.24) in Equation 1; (-1.30) in Equation 2) — indicates persistence assessment.
- Number of observations: 88.
- Diagnostic tests (reported for GMM specification):
  - AR(1) test: p-value 0.07
  - AR(2) test: p-value 0.14
  - Sargan test: p-value 0.49
- Robustness: South African growth is statistically not significant in the panel once global variables and domestic fiscal policies are included; real domestic demand growth and real exchange rate developments were also not significant in alternative specifications.
- Openness was not significant in the panel.

Policy-relevant inference from panel results (as stated in source)
- Global developments matter for BLNS growth.
- Domestic fiscal policies influence cross-country differences; evidence consistent with effective countercyclical fiscal policy raising growth when fiscal balance decreases (expenditure-led).

### VI. Spillovers Evidence from Vector Autoregressions (VARs, annual data 1986–2010)
Model specification
- For each BLNS country i, VAR includes:
  1. World real GDP growth
  2. South Africa’s domestic demand growth or real GDP growth
  3. South Africa’s real exchange rate
  4. Real growth rate for BLNS country i
- Identification: Cholesky ordering with world growth first as most exogenous.
- Lags: country-specific, selected by lag information criteria.

Impulse response and variance decomposition findings (textual summaries and selected exact statements)
- World growth shocks spill over into GDP growth of most BLNS countries, with the exception of Lesotho.
- South Africa’s real GDP growth does not contribute much to BLNS GDP growth after controlling for world growth, except for Lesotho.
- Lesotho: growth in Lesotho falls when South African growth increases (possible interpretation: migration of Lesotho workers to South Africa during booms reduces Lesotho domestic production).
- Replacing South Africa real GDP growth with real private domestic demand growth:
  - World growth remains robustly significant in all countries but Lesotho.
  - South Africa’s real domestic demand becomes positively significant for Namibia and Swaziland, and remains negatively significant for Lesotho.
- South African real exchange rate:
  - A real appreciation in South Africa tends to reduce growth in Botswana (competitiveness channel) and increase growth in Swaziland.
  - Appears insignificant for Lesotho and Namibia.
- Variance decompositions:
  - World growth is the most important variable for Botswana, Namibia, and Swaziland; its importance increases over time for Namibia and Swaziland.
  - For Lesotho, South African developments (GDP or domestic demand growth) are the most important short-run determinants; over time world growth and the South African real exchange rate gain importance.
  - For Botswana and Swaziland, the importance of South Africa’s real exchange rate increases over time.

Selected summary from Model 1 Impulse Response Functions (as reported)
- Botswana: World economic growth (+); South Africa economic growth (*) and real exchange rate (-) with parentheses indicating sign and * implying significance per source notation.
- Lesotho: South Africa economic growth (-)*
- Namibia: South Africa real domestic demand (+)*
- Swaziland: World economic growth (+)*; South Africa domestic demand (+)*

### VII. Key Findings and Policy Implications (as presented in source)
- Global real and financial developments are significant drivers of BLNS growth; a 1 percentage point slowdown in world growth reduces BLNS growth by approximately 0.6 percentage points (text statement).
- Financial conditions (TED spread) have a strong negative effect on growth (coefficient -1.37).
- Terms of trade improvements boost growth (coefficient 0.03).
- Fiscal policy matters: evidence consistent with countercyclical fiscal policy — a 1 percentage point decrease in fiscal balance increases growth by about 0.25 percent.
- South African growth per se does not appear to systematically transmit growth shocks to BLNS as a block once global variables and fiscal policies are controlled for; however, country-specific VARs reveal important heterogeneity (Lesotho notably more linked to South African developments).
- Revenue-sharing mechanism via SACU customs formula exposes BLNS fiscal revenues to volatility driven by South Africa’s import performance; example drops in customs revenue post-global financial crisis: Lesotho about 20 percent of GDP, Swaziland about 15 percent of GDP — with Swaziland experiencing severe fiscal stress.

*Source: _wp1331 - References (IMF PDF content provided)*

### 2. Signs in brackets show the direction of the impulse response

### _wp1331 - 2. Signs in brackets show the direction of the impulse response

### Impulse Response Functions — notes and significance
- "* implies significancy of the impulse response functions."
- "Signs in brackets show the direction of the impulse response"
- "All impulses are significant in the 1st period only."
- Summary indicators from Model 2 (directional signs as presented):
  - Botswana: (+)*(-)*
  - Lesotho: (-)*
  - Namibia: (+)*(+)*
  - Swaziland: (+)*(+)*(+)*

### Model 1 — Variance decompositions (Variance Decomposition of BLNS growth rates, percentages of total)
- Variables: World economic growth; South Africa economic growth; South Africa real exchange rate
- Year 1
  - Botswana: 41.6 0.2 8.9
  - Lesotho: 1.0 41.4 3.3
  - Namibia: 21.0 0.0 6.3 3.5
  - Swaziland: 37.6 1.8 15.4
- Year 5
  - Botswana: 30.5 5.6 30.5
  - Lesotho: 20.4 30.9 10.4
  - Namibia: 43.9 2.1 5.2
  - Swaziland: 38.7 2.4 29.9

### Model 2 — Variance decompositions (Variance Decomposition of BLNS growth rates, percentages of total)
- Variables: World economic growth; South Africa domestic demand growth; South Africa real exchange rate
- Year 1
  - Botswana: 29.6 9.0 12.6
  - Lesotho: 10.1 18.2 1.4
  - Namibia: 17.6 16.0 2.8
  - Swaziland: 31.0 12.2 17.7
- Year 5
  - Botswana: 19.7 11.1 39.4
  - Lesotho: 17.7 14.7 17.0
  - Namibia: 37.4 11.9 8.6
  - Swaziland: 36.6 6.8 29.9

### Findings and interpretation (from Conclusions)
- Significant spillovers arise from real and financial interlinkages.
- Shocks to real GDP growth in South Africa do not seem to systematically affect growth developments in BLNS countries as a group.
- Panel regressions suggest:
  - The global real and financial environment affects all SACU members.
  - Countercyclical fiscal policies can play a role to cushion the effect of global shocks on the economy.
- Because financial systems in the other SACU countries (the BLNS) are much less developed than in South Africa:
  - Results could suggest that South Africa acts as a conduit in the transmission of the external environment (otherwise financial effects may be hard to explain).
  - South Africa does not amplify or cushion these effects.
- Vector autoregressions, which allow country-specific parameters, suggest some strong growth spillovers to the smaller economies.

### Key statistics and technical points (exact figures preserved)
- Model 1 Year 1: Botswana 41.6; Lesotho 1.0 41.4; Namibia 21.0; Swaziland 37.6 (with other component figures as listed above).
- Model 1 Year 5: Botswana 30.5 5.6 30.5; Lesotho 20.4 30.9 10.4; Namibia 43.9 2.1 5.2; Swaziland 38.7 2.4 29.9.
- Model 2 Year 1: Botswana 29.6 9.0 12.6; Lesotho 10.1 18.2 1.4; Namibia 17.6 16.0 2.8; Swaziland 31.0 12.2 17.7.
- Model 2 Year 5: Botswana 19.7 11.1 39.4; Lesotho 17.7 14.7 17.0; Namibia 37.4 11.9 8.6; Swaziland 36.6 6.8 29.9.

*Source: Authors' calculations.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2013/_wp1331.pdf_