## 4. Tax Rate Constraint and Presence of Foreign Firms

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### Introduction
- Research question: assess how taxation matters compared to other investment climate factors in attracting foreign direct investment (FDI) beyond natural resource sectors in sub-Saharan Africa (SSA).
- Data scope: 30 sub-Saharan African countries; 7,615 firms, including 1,425 foreign firms.
- FDI definition: dummy equals 1 if at least 10 percent of firm capital is foreign.

### Main empirical findings
- Taxes (as perceived by firms) are not significant drivers of foreign firms’ decisions to locate in SSA countries.
- Key investment climate factors that reduce the probability of receiving FDI:
  - Infrastructure constraints (roads/transport, electricity, telecommunication).
  - Financing constraints (access to finance and reliance on informal financing).
  - Human capital shortages and weak institutional quality also reduce FDI.
- Financial development importance varies with ownership:
  - A domestically developed financial sector matters for attracting foreign firms in general.
  - It matters less when foreign companies own 50 percent or more of a firm’s capital — suggesting majority-foreign firms rely more on external/parent financing.
- Heterogeneity by FDI type:
  - Horizontal FDI (local-market oriented) is more influenced by financing and human capital constraints and attracted to areas with higher trade regulations.
  - Vertical FDI (export-oriented) is more affected by infrastructure and institutional constraints, particularly telecommunication problems.
- Agglomeration effects (number of foreign firms in same region-sector) have no significant effect on foreign firm location in the baseline models.

### Tax incentives and policy interpretation
- Tax incentives/tax holidays are commonly used to attract FDI, but:
  - They tend to distort the investment playing field.
  - They do not necessarily tackle root causes (e.g., poor infrastructure) that constrain investment.
  - Granting tax exemptions is costly in the long run and can be self-perpetuating.
- Empirical implication: SSA countries should prioritize investment climate reforms (infrastructure, institutions, human capital, and domestic financial development) over costly tax incentives that erode revenue bases with doubtful effectiveness.

### Other investment climate factors (literature and paper’s focus)
- Infrastructure: reliable electricity, transport, and telecommunications increase market access and attract foreign firms.
- Financial development: domestic financial services matter for operational needs, hedging, and growth; informal financing reliance discourages foreign firms.
- Institutions: secure property rights, contract enforcement, political stability, and low corruption increase attractiveness.
- Human capital: availability of skilled workers influences FDI depending on firm activity (skill-intensive MNEs vs. non-skill-intensive firms).

### Data and descriptive statistics (selected exact figures)
- Sample: 30 SSA countries; 7,615 firms; 1,425 foreign firms.
- Sectoral note: in high-value sectors (nonmetallic and plastic materials; chemicals and pharmaceuticals) around one quarter of firms are partly or fully foreign-owned.
- Table A.2 key moments:
  - FDI mean: 0.21; Std. Dev.: 0.41; Maximum: 1
  - Age mean: 14.94; Std. Dev.: 15.26; Maximum: 167
  - Number of permanent workers mean: 88.53; Std. Dev.: 440.84; Maximum: 18,753
  - Agglomeration mean: 40.66; Std. Dev.: 30.70; Maximum: 119
  - Tax problem mean: 1.05; Std. Dev.: 1.44; Maximum: 4
  - Telecom problems 1 mean: 0.48; Std. Dev.: 0.50; Maximum: 1
  - Informal finance problems mean: 0.60; Std. Dev.: 4.98; Maximum: 100
  - Skilled labor problems mean: 0.74; Std. Dev.: 1.21; Maximum: 4
  - Crime and disorder mean: 0.83; Std. Dev.: 1.28; Maximum: 4
  - Custom and trade mean: 0.67; Std. Dev.: 1.20; Maximum: 4

### Empirical strategy (key elements)
- Unit of analysis: firm-level; estimates whether each firm is foreign given local-region investment climate characteristics.
- Baseline estimating equation: FDIijk = function(Xijk, Zijk, Vi, Uj) where:
  - FDIijk: dummy (1 if at least 10% foreign capital).
  - Xijk: tax variable and structural constraints (physical and financial infrastructure, skilled labor, institutions).
  - Zijk: other determinants (agglomeration, trade regulations, firm size, firm age).
  - Vi and Uj: country and sector fixed effects.
- Endogeneity mitigation:
  - Instruments: sector-region averages for potentially endogenous variables; sector-region average of whether financial statements are audited used as additional instrument for financial infrastructure.
  - Agglomeration variable included to reduce endogeneity.
- Estimation methods: instrumental variable fixed-effect logit (IV FE logit) and Two-Stage Least Squares linear probability model (2SLS).
- FDI thresholds: robustness checks use thresholds from 10% to 100% foreign capital to define FDI; exporter thresholds at 10%, 20%, and 30% of sales.

### Aggregate FDI model — selected quantitative results and robustness
- Baseline: taxation (tax problems) not statistically significant in explaining FDI in multiple specifications.
- Infrastructure and finance indices: marginal increases in constraints reduce probability of receiving FDI (significant across aggregated indices and objective variables).
- Table-level coefficients (selected reported estimates in source):
  - Telecom problems (example column): -0.345 (logit marginal effect, IV FE, Table 2 column 3).
  - Informal finance (example column): -0.799 (2SLS, Table 2 column 3).
  - Infrastructure index: -0.042 and -0.043 (2SLS, Table 2 column 1).
  - Physical infrastructure problems: -0.06 (2SLS, Table 2 column 2).
  - Financial infrastructure problems: -0.033 (2SLS, Table 2 column 2).
- Model diagnostics reported in source:
  - % of correct predictions: 70, 70, 68 (for different specifications reported).
  - Weak instrument test statistic example: 290.77 (critical value 13.43 reported).
  - Hansen J-statistic p-values vary; overidentification not rejected in most cases.

### Ownership-degree heterogeneity
- Results across FDI thresholds (10% to 100%) show:
  - Tax problem remains not significant at all ownership thresholds.
  - Telecom problems and informal finance show stronger negative associations for lower foreign-ownership thresholds (i.e., joint ventures/more local ownership).
  - Skilled labor problems and crime/disorder reduce FDI at multiple ownership thresholds.
  - Trade regulation positively associated with FDI across thresholds.
- Interpretation: when foreign capital > 50%, domestic financial development matters less, consistent with majority-foreign firms’ access to external/parent financing.

### Horizontal vs. vertical FDI (exporter vs nonexporter)
- Taxation does not significantly affect either horizontal (nonexporter) or vertical (exporter) FDI.
- Distinct effects by FDI type:
  - Physical infrastructure: more important for exporting foreign firms (vertical FDI); telecommunication problems have larger negative effects on exporters.
  - Financing constraints: significantly affect nonexporter (horizontal) foreign firms, not exporters.
  - Trade regulations: positively associated with nonexporter (horizontal) FDI (attraction to protected markets); not significant for exporters.
  - Skilled labor constraints: affect nonexporters more than exporters (exporters may import or train labor).
  - Institutional weaknesses: exporters may be more affected due to international standards and delivery requirements.
- Selected table coefficients (exact values reported in source):
  - Telecom problems (nonexporter vs exporter, Table 4 examples): -0.309 (nonexporter) and -1.159 (exporter) in one specification.
  - Informal finance (nonexporter examples): -0.989 (significant); exporter coefficients less consistently significant.

### Policy recommendations
- Prioritize improvement of investment climate over tax incentives:
  - Invest in transport, electricity, and telecommunication infrastructure.
  - Strengthen domestic financial systems to reduce reliance on informal finance.
  - Improve human capital (skilled labor availability) and institutional quality (property rights, contract enforcement, reduce crime/disorder).
- Avoid broad, costly tax incentives/tax holidays that erode revenue bases given weak evidence of effectiveness in attracting non-resource FDI.
- Target reforms to the type of FDI sought:
  - To attract exporters (vertical FDI): prioritize telecommunication and broader infrastructure, and address institutional weaknesses.
  - To attract local-market firms (horizontal FDI): focus on domestic finance availability, skilled labor development, and trade-policy considerations.

### Appendix — Variables and diagnostics (selected exact items)
- FDI: Dummy equals 1 if at least 10% of firm capital is foreign.
- Agglomeration: Number of foreign firms in same sector and same region.
- Telecom problems 1: Constraint: access to e-mail for business with clients and suppliers (dummy).
- Informal finance problems: Informal sources of financing in a firm’s working capital (%).
- Financial and physical infrastructure PCA constructs reported in Tables A.4–A.6; Physical and Financial Infrastructure index = (0.36/0.59)*Component 1 + ((0.59 -0.36)/0.59)*Component 2 (as defined in source).
- Country list includes: Angola; Benin; Botswana; Burkina Faso; Burundi; Cameroon; Cape Verde; Congo, Dem. Rep.; Eritrea; Ethiopia; Gambia; Guinea; Guinea Bissau; Kenya; Lesotho; Madagascar; Malawi; Mali; Mauritania; Mauritius; Mozambique; Namibia; Niger; Rwanda; Senegal; South Africa; Swaziland; Tanzania; Uganda; Zambia.

*Source — IMF working paper content unit "4. Tax Rate Constraint and Presence of Foreign Firms" (excerpt).*

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

### _wp1415 - References

### Tables
- 1. Share of Foreign Firms by Sector, Size, and Export Status ...................................................6
- 2. Basic Model with Tax and Infrastructure Variables ............................................................12
- 3. Model with Different Joint Venture Structures and Full foreign Ownership ......................13
- 4. Vertical and Horizontal FDI ................................................................................................16

### Figures
- 1. Ranking of Investment Climate Constraints ..........................................................................7
- 2. Telecom Problems and Presence of Foreign Firms ...............................................................8
- 3. Informal Finance and Presence of Foreign Firms ..................................................................8

*Source: _wp1415 - References.*

### 4. Tax Rate Constraint and Presence of Foreign Firms .............................................................8

### 4. Tax Rate Constraint and Presence of Foreign Firms

### Introduction
- Research question: assess how taxation matters compared to other investment climate factors in attracting foreign direct investment (FDI) beyond natural resource sectors in sub-Saharan Africa (SSA).
- Data scope: 30 sub-Saharan African countries; 7,615 firms, including 1,425 foreign firms.
- FDI definition: dummy equals 1 if at least 10 percent of firm capital is foreign.

### Main empirical findings
- Taxes (as perceived by firms) are not significant drivers of foreign firms’ decisions to locate in SSA countries.
- Key investment climate factors that reduce the probability of receiving FDI:
  - Infrastructure constraints (roads/transport, electricity, telecommunication).
  - Financing constraints (access to finance and reliance on informal financing).
  - Human capital shortages and weak institutional quality also reduce FDI.
- Financial development importance varies with ownership:
  - A domestically developed financial sector matters for attracting foreign firms in general.
  - It matters less when foreign companies own 50 percent or more of a firm’s capital — suggesting majority-foreign firms rely more on external/parent financing.
- Heterogeneity by FDI type:
  - Horizontal FDI (local-market oriented) is more influenced by financing and human capital constraints and attracted to areas with higher trade regulations.
  - Vertical FDI (export-oriented) is more affected by infrastructure and institutional constraints, particularly telecommunication problems.
- Agglomeration effects (number of foreign firms in same region-sector) have no significant effect on foreign firm location in the baseline models.

### Tax incentives and policy interpretation
- Tax incentives/tax holidays are commonly used to attract FDI, but:
  - They tend to distort the investment playing field.
  - They do not necessarily tackle root causes (e.g., poor infrastructure) that constrain investment.
  - Granting tax exemptions is costly in the long run and can be self-perpetuating.
- Empirical implication: SSA countries should prioritize investment climate reforms (infrastructure, institutions, human capital, and domestic financial development) over costly tax incentives that erode revenue bases with doubtful effectiveness.

### Other investment climate factors (literature and paper’s focus)
- Infrastructure: reliable electricity, transport, and telecommunications increase market access and attract foreign firms.
- Financial development: domestic financial services matter for operational needs, hedging, and growth; informal financing reliance discourages foreign firms.
- Institutions: secure property rights, contract enforcement, political stability, and low corruption increase attractiveness.
- Human capital: availability of skilled workers influences FDI depending on firm activity (skill-intensive MNEs vs. non-skill-intensive firms).

### Data and descriptive statistics (selected exact figures)
- Sample: 30 SSA countries; 7,615 firms; 1,425 foreign firms.
- Sectoral note: in high-value sectors (nonmetallic and plastic materials; chemicals and pharmaceuticals) around one quarter of firms are partly or fully foreign-owned.
- Table A.2 key moments (exact values from source):
  - FDI mean: 0.21; Std. Dev.: 0.41; Maximum: 1
  - Age mean: 14.94; Std. Dev.: 15.26; Maximum: 167
  - Number of permanent workers mean: 88.53; Std. Dev.: 440.84; Maximum: 18,753
  - Agglomeration mean: 40.66; Std. Dev.: 30.70; Maximum: 119
  - Tax problem mean: 1.05; Std. Dev.: 1.44; Maximum: 4
  - Telecom problems 1 mean: 0.48; Std. Dev.: 0.50; Maximum: 1
  - Informal finance problems mean: 0.60; Std. Dev.: 4.98; Maximum: 100
  - Skilled labor problems mean: 0.74; Std. Dev.: 1.21; Maximum: 4
  - Crime and disorder mean: 0.83; Std. Dev.: 1.28; Maximum: 4
  - Custom and trade mean: 0.67; Std. Dev.: 1.20; Maximum: 4

### Empirical strategy (key elements)
- Unit of analysis: firm-level; estimates whether each firm is foreign given local-region investment climate characteristics.
- Baseline estimating equation: FDIijk = function(Xijk, Zijk, Vi, Uj) where:
  - FDIijk: dummy (1 if at least 10% foreign capital).
  - Xijk: tax variable and structural constraints (physical and financial infrastructure, skilled labor, institutions).
  - Zijk: other determinants (agglomeration, trade regulations, firm size, firm age).
  - Vi and Uj: country and sector fixed effects.
- Endogeneity mitigation:
  - Instruments: sector-region averages for potentially endogenous variables; sector-region average of whether financial statements are audited used as additional instrument for financial infrastructure.
  - Agglomeration variable included to reduce endogeneity.
- Estimation methods: instrumental variable fixed-effect logit (IV FE logit) and Two-Stage Least Squares linear probability model (2SLS).
- FDI thresholds: robustness checks use thresholds from 10% to 100% foreign capital to define FDI; exporter thresholds at 10%, 20%, and 30% of sales.

### Aggregate FDI model — selected quantitative results and robustness
- Baseline: taxation (tax problems) not statistically significant in explaining FDI in multiple specifications.
- Infrastructure and finance indices: marginal increases in constraints reduce probability of receiving FDI (significant across aggregated indices and objective variables).
- Table-level coefficients (selected reported estimates in source):
  - Telecom problems (example column): -0.345 (logit marginal effect, IV FE, Table 2 column 3).
  - Informal finance (example column): -0.799 (2SLS, Table 2 column 3).
  - Infrastructure index: -0.042 and -0.043 (2SLS, Table 2 column 1).
  - Physical infrastructure problems: -0.06 (2SLS, Table 2 column 2).
  - Financial infrastructure problems: -0.033 (2SLS, Table 2 column 2).
- Model diagnostics reported in source:
  - % of correct predictions: 70, 70, 68 (for different specifications reported).
  - Weak instrument test statistic example: 290.77 (critical value 13.43 reported).
  - Hansen J-statistic p-values vary; overidentification not rejected in most cases.

### Ownership-degree heterogeneity
- Results across FDI thresholds (10% to 100%) show:
  - Tax problem remains not significant at all ownership thresholds.
  - Telecom problems and informal finance show stronger negative associations for lower foreign-ownership thresholds (i.e., joint ventures/more local ownership).
  - Skilled labor problems and crime/disorder reduce FDI at multiple ownership thresholds.
  - Trade regulation positively associated with FDI across thresholds.
- Interpretation: when foreign capital > 50%, domestic financial development matters less, consistent with majority-foreign firms’ access to external/parent financing.

### Horizontal vs. vertical FDI (exporter vs nonexporter)
- Taxation does not significantly affect either horizontal (nonexporter) or vertical (exporter) FDI.
- Distinct effects by FDI type:
  - Physical infrastructure: more important for exporting foreign firms (vertical FDI); telecommunication problems have larger negative effects on exporters.
  - Financing constraints: significantly affect nonexporter (horizontal) foreign firms, not exporters.
  - Trade regulations: positively associated with nonexporter (horizontal) FDI (attraction to protected markets); not significant for exporters.
  - Skilled labor constraints: affect nonexporters more than exporters (exporters may import or train labor).
  - Institutional weaknesses: exporters may be more affected due to international standards and delivery requirements.
- Selected table coefficients (exact values reported in source):
  - Telecom problems (nonexporter vs exporter, Table 4 examples): -0.309 (nonexporter) and -1.159 (exporter) in one specification; other specifications show similar patterns with larger negative magnitudes for exporters.
  - Informal finance (nonexporter examples): -0.989 (significant); exporter coefficients less consistently significant.

### Policy recommendations (derived from empirical results)
- Prioritize improvement of investment climate over tax incentives:
  - Invest in transport, electricity, and telecommunication infrastructure.
  - Strengthen domestic financial systems to reduce reliance on informal finance.
  - Improve human capital (skilled labor availability) and institutional quality (property rights, contract enforcement, reduce crime/disorder).
- Avoid broad, costly tax incentives/tax holidays that erode revenue bases given weak evidence of effectiveness in attracting non-resource FDI.
- Target reforms to the type of FDI sought:
  - To attract exporters (vertical FDI): prioritize telecommunication and broader infrastructure, and address institutional weaknesses.
  - To attract local-market firms (horizontal FDI): focus on domestic finance availability, skilled labor development, and trade-policy considerations.

### Appendix — Variables and diagnostics (selected exact items)
- FDI: Dummy equals 1 if at least 10% of firm capital is foreign.
- Agglomeration: Number of foreign firms in same sector and same region.
- Telecom problems 1: Constraint: access to e-mail for business with clients and suppliers (dummy).
- Informal finance problems: Informal sources of financing in a firm’s working capital (%).
- Financial and physical infrastructure PCA constructs reported in Tables A.4–A.6; Physical and Financial Infrastructure index = (0.36/0.59)*Component 1 + ((0.59 -0.36)/0.59)*Component 2 (as defined in source).
- Country list includes: Angola; Benin; Botswana; Burkina Faso; Burundi; Cameroon; Cape Verde; Congo, Dem. Rep.; Eritrea; Ethiopia; Gambia; Guinea; Guinea Bissau; Kenya; Lesotho; Madagascar; Malawi; Mali; Mauritania; Mauritius; Mozambique; Namibia; Niger; Rwanda; Senegal; South Africa; Swaziland; Tanzania; Uganda; Zambia.

_Italic: Source — IMF working paper content unit "4. Tax Rate Constraint and Presence of Foreign Firms" (excerpt)._

### REFERENCES

### _wp1415 - REFERENCES

### Investment climate, firm performance, and productivity
- Aterido, R., M. Hallward-Driemeier, and C. Pagés, 2007, “Investment Climate and Employment Growth: The Impact of Access to Finance, Corruption and Regulations across Firms,” IDB Working Paper No. 626 (Washington: Inter-American Development Bank).
- Chaffai, M., T. Kinda, and P. Plane, 2012, “Textile Manufacturing in Eight Developing Countries: Does Business Environment Matter for Firm Technical Efficiency?” Journal of Development Studies, Vol. 48 (October), pp. 1470–1488.
- Dollar, D., M. Hallward-Driemeier, and T. Mengistae, 2005, “Investment Climate and Firm Performance in Developing Economies,” Economic Development and Cultural Change, Vol. 54 (January), pp. 1–31.
- Dollar, D., M. Hallward-Driemeier, and T. Mengistae, 2006, “Investment Climate and International Integration,” World Development, Vol. 34 (September), pp. 1498–1516.
- Gelb, A., V. Ramachandran, M. Shah, and G. Turner, 2007, “What Matters to African firms? The Relevance of Perceptions Data,” World Bank Policy Research Working Paper No. 4446 (Washington: World Bank).
- Honorati, M., and T. Mengistae, 2007, “Corruption, Business Environment, and Small Business Fixed Investment in India,” World Bank Policy Research Working Paper No. 4356 (Washington: World Bank).
- Javorcik, B. S., 2004, “Does Foreign Direct Investment Increase the Productivity of Domestic Firms? In Search of Spillovers Through Backward Linkages,” American Economic Review, Vol. 93 (June), pp. 605–27.
- Kinda, T., P. Plane, and M-A. Veganzones-Varoudakis, 2011, “Firm Productivity and Investment Climate in Developing Countries: How Does Middle East and North Africa Manufacturing Perform?” The Developing Economies, Vol. 49 (April), pp. 429–62.
- Lall, S., and T. Mengistae, 2005, “Impacts of Business Environment and Economic Geography on Plant Level Productivity: An Analysis of Indian Industry,” World Bank Working Paper No. 3664 (Washington: World Bank).
- Kinda, Tidiane, 2012, “Foreign Ownership, Sales to Multinationals and Firm Efficiency: The Case of Brazil, Morocco, Pakistan, South Africa, and Vietnam,” Applied Economics Letters, Vol. 19 (June), pp. 551–555.

### Foreign direct investment, multinational firm behavior, and spillovers
- Carr, D., J. Markusen, and K. Maskus, 2001, “Estimating the Knowledge Capital Model of the Multinational Firm,” American Economic Review, Vol. 91 (March), pp. 693–708.
- Du, J., Y. Lu, and Z. Tao, 2008, “Economic Institutions and FDI Location Choice: Evidence from U.S. Multinationals in China,” Journal of Comparative Economics, Vol. 36 (September), pp 412-429.
- Hanson, G., R. Mataloni, and M. Slaughter, 2001, “Expansion Strategies of U.S. Multinationals Firms,” in Brookings Trade Forum 2001, ed. by Rodrik and Collins. (Washington: Brookings Institution Press).
- Javorcik, B. S., 2004, “Does Foreign Direct Investment Increase the Productivity of Domestic Firms? In Search of Spillovers Through Backward Linkages,” American Economic Review, Vol. 93 (June), pp. 605–27.
- Liu, Z., 2008, “Foreign Direct Investment and Technology Spillovers: Theory and Evidence,” Journal of Development Economics, Vol. 85, Nos. 1–2, pp. 176–193.
- Smarzynska, B. K., and S.J. Wei, 2000, “Corruption and Composition of Foreign Direct Investment: Firm-Level Evidence,” NBER Working Paper No. 7969 (Cambridge, Massachusetts: National Bureau of Economic Research).
- Urata, S., and H. Kawai, 2000, “The Determinants of the Location of Foreign Direct Investment by Japanese Small- and Medium-Sized Enterprises,” Small Business Economics, Vol. 15 (February) pp. 79–103.
- Yeaple, S., 2003, “The Role of Skill Endowments in the Structure of U.S. Outward Foreign Investments,” Review of Economics and Statistics, Vol. 85 (March), pp. 726–734.
- Kinda, Tidiane, 2010, “Investment Climate and FDI in Developing Countries: Firm-Level Evidence,” World Development, Vol. 38 (April), pp. 498–513.

### Tax incentives, tax policy, and FDI attraction
- Chai, J., and R. Goyal, 2008, “Tax Concessions and Foreign Direct Investment in the Eastern Caribbean Currency Union,” IMF Working Paper 08/257 (Washington: International Monetary Fund).
- De Mooij, Ruud A., and Sjef Ederveen, 2008, “Corporate Tax Elasticities: A Reader’s Guide to Empirical Findings,” Oxford Review of Economic Policy, Vol. 24 (Issue 4), pp. 680–697.
- Klemm A., and S. van Parys, 2012, “Empirical Evidence on the Effects of Tax Incentives,” International Tax and Public Finance, Vol. 9, No. 5, pp. 393–423.
- Mansour, M., and M. Keen, 2009, “Revenue Mobilization in Sub-Saharan Africa: Challenges from Globalization,” IMF Working Paper 09/157 (Washington: International Monetary Fund).
- Van Parys S. and S. James, 2010, “The Effectiveness of Tax Incentives in Attracting FDI: Evidence from the Tourism Sector in the Caribbean,” Working Paper No. 675 (Gent, England: Universiteit Gent).
- Zee, H., J. Stotsky, and E. Ley, 2002, “Tax Incentives for Business Investment: A Primer for Policy Makers in Developing Countries,” World Development, Vol. 30 (September), pp. 1497–516.

### Sectoral and regional studies
- Chaffai, M., T. Kinda, and P. Plane, 2012, “Textile Manufacturing in Eight Developing Countries: Does Business Environment Matter for Firm Technical Efficiency?” Journal of Development Studies, Vol. 48 (October), pp. 1470–1488.
- Gelb, A., V. Ramachandran, M. Shah, and G. Turner, 2007, “What Matters to African firms? The Relevance of Perceptions Data,” World Bank Policy Research Working Paper No. 4446 (Washington: World Bank).
- Van Parys S. and S. James, 2010, “The Effectiveness of Tax Incentives in Attracting FDI: Evidence from the Tourism Sector in the Caribbean,” Working Paper No. 675 (Gent, England: Universiteit Gent).
- World Bank, 2005, Towards a New Agenda for Growth: Organization of Eastern Caribbean States (Washington: World Bank).

### Methodology, econometrics, and technical tools
- Stock, J. H., and M. Yogo, 2004, “Testing for Weak Instruments in Linear IV Regressions,” NBER Technical Working Paper No. 0284 (Cambridge, Massachusetts: National Bureau of Economic Research).

* _wp1415 - REFERENCES_*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2014/_wp1415.pdf_