1. International Monetary Fund Revenue Mobilization in sub-Saharan Africa: Empirical Norms and key Determinants Paulo Drummond, Wendell Daal, Nandini Srivastava, Luiz Oliveira Business & Economics Society International Perth Conference January 2013

2. Introduction Purpose of the study How much and how fast countries can expect to mobilize more revenues? What are key determinants of revenue mobilization? Why mobilizing revenue is important? Create space to raise priority spending Move toward fiscal sustainability Reduce aid dependence 2

3. How Much and How Fast? 3

4. Methodology of Statistical Analysis Sample of 28 SSA-LICs (as of 2010); 15 non-fragile SSA-LICS 13 fragile SSA-LICs Sample period: 1990 - 2010 Fiscal revenues, i.e., tax and non-tax revenues, excluding grants Frequency distribution to determine the pace of mobilizing revenue; Most frequently observed Exceptional pace In-between or middle pace Time horizon for observed changes; Short-to-medium term (1 to 3 years) Longer horizon (5 to 10 years) 4

5. Results of Statistical Analysis I.Pace of mobilizing revenue II.How ambitious can countries be? III.A closer look into strong performers IV.Was is it sustainable? 5

6. I. Pace of mobilizing revenue  Short-to-medium term  Most frequent pace: ½ - 2 percent of GDP  Middle pace: 2 – 5 percent of GDP  Exceptional pace: >5 percent of GDP 6

7. I. Pace of mobilizing revenue  Longer term  Most frequent pace: 2½ - 3½ percent of GDP  Middle pace: 3½ – 7½ percent of GDP  Exceptional pace: >7½ percent of GDP 7

8. II. How ambitious can countries be? Countries can expect increases of about ½ - 2 percentage points in revenue ratios in the short-to-medium terms, and about 2½ -3½ percent of GDP over the longer term. However, countries can be cautiously ambitious; almost all SSA-LICs managed to increase revenue ratios by 2 percentage points of GDP or more in the short-to-medium term at least once in the last 2 decades. 8

9. II. How ambitious can countries be? 9

10. 10 II. How ambitious can countries be?

11. III. A closer look into strong performers 11

12. 12 III. A closer look into strong performers

13. 13 III. A closer look into strong performers

14. 14 III. A closer look into strong performers

15. IV. Was it sustainable? Sustainability can be an issue.  Non-Fragile SSA-LICs were able to at least partially sustain their revenue gains.  Fragile SSA-LICs had more problems sustaining their revenue gains 15

16. 16 IV. Was it sustainable?

17. 17 IV. Was it sustainable?

18. HOW FAST AND HOW MUCH HAVE SSA-LICS BEEN ABLE TO MOBILIZE REVENUES Success stories arise among fragile and non- fragile countries.  Among the non-fragile SSA-LICs, Ghana, Kenya, and Zambia are the countries that were able to mobilize most revenues in a 1, 3, 5 or 10-year period and sustain it.  Among the fragile SSA-LICs, Sierra Leone, Liberia, and Democratic Republic of Congo achieved the largest increase in revenue ratios in at least one of these periods and were able to sustain these gains. 18

19. What Determines Revenue Mobilization? 19

20. Results of Statistical Analysis I.Stylized Facts II.Empirical Methodology III.Main Findings 20

21. Stylized facts Mobilizing revenue remains a challenge for many SSA countries Average revenue for SSA countries has remained low over the past two decades at around 20 per cent of the GDP Low income and fragile countries have had more difficulty mobilizing revenues Low income countries averaged 13 per cent of GDP between 1990-2009 as compared to 20 and 22 per cent for middle and upper middle income countries Fragile countries averaged 14 per cent as a proportion of GDP as compared to non fragile countries which averaged 20 per cent 21

22. Total Revenue (without grants) as a Proportion of GDP, 2010 Source: Revenue Mobilization in Developing Countries (2011), Board Paper, International Monetary Fund (IMF) Low Average for SSA countries

23. Dependence on Income 23 Source: Revenue Mobilization in Developing Countries (2011), Board Paper, International Monetary Fund (IMF)

24. Dependence on Conditions in the country 24 Source: Revenue Mobilization in Developing Countries (2011), Board Paper, International Monetary Fund (IMF)

25. Aid and Revenue: Does it help? Aid and Tax Revenue (2010) Source: Revenue Mobilization in Developing Countries (2011), Board Paper, IMF

26. The structure of the Economy matters… Trends in the composition of revenues differ according to the structure of the economy income, relative importance of different sectors like agriculture, manufacturing, trade, natural resources 26

27. Changes in Tax Structures Non tax revenues have fallen in comparison to tax revenues as a proportion of GDP Lower and declining trade taxes associated with trade liberalization As economies develop, indirect taxes become more important contributors to tax revenues. For most low income countries, the composition of tax revenue has tended to be biased towards direct taxes Resource rich countries experienced a decline in average tax revenues and greater volatility 27

28. Income Tax Average Income Tax Revenue as a Proportion of GDP (1999- 2010) Source: Revenue Mobilization in Developing Countries (2011), Board Paper, IMF Average is taken from 1999-2010 due to limitations of data availability

29. Trade Tax Average Trade Tax Revenue as a Proportion of GDP (1999-2010) Source: Revenue Mobilization in Developing Countries (2011), Board Paper, IMF Average is taken from 1999-2010 due to limitations of data availability

30. Tax in Oil Vs. Non-Oil Average Tax Revenue as a Proportion of GDP Oil vs NonOil (1990-2010) Source: Revenue Mobilization in Developing Countries (2011), Board Paper, IMF

31. Tax Revenue Composition Composition of Tax Revenues (2010) Source: Revenue Mobilization in Developing Countries (2011), Board Paper, IMF Missing data for income tax for Nigeria and Gabon, for corporate tax for Madagascar, Ethiopia, Guinea, Cameroon, Eritrea, Niger, Guinea-Bissau, Côte d'Ivoire, Kenya, Tanzania, Mali, Nigeria, Comoros, Mozambique, Liberia, Democratic Republic of Congo, Botswana, Malawi, Angola, Republic of Congo

32. DETERMINANTS OF TAX REVENUE Empirical Methodology Cross country panel regression using fixed effects and robust standard errors dependent variable is tax revenues as a share of GDP X contains a range of controls 32

33. Dep VarTax Revenue/GDP 1980–2009Including Corruption Including Shadow Economy 1990–20093-yr non- overlapping average (1980–09) Including Corruption GDP per capita 0.00112** (1.74) 0.0011406** (1.45) 0.0010521** (1.52) 0.0027115*** (2.73) 0.00186*** (2.50) 0.00180*** (2.39) 0.000554 (0.65) 0.0017706*** (1.86) Share of agriculture in GDP -0.103*** (-2.34) -0.0845695*** (-1.69) -0.1823801*** (-2.59) -0.0051849*** (-1.89) -0.0933*** (-2.75) -0.125*** (-2.81) -0.0413 (-1.08) -0.1122353*** (-3.07) Inflation-0.000392* (-1.48) -0.0008125*** (-16.86) -0.0007533*** (-15.16) -0.0007504*** (-7.48) -0.000385* (-1.26) -0.000367* (-1.19) 0.0000581*** (-6.60) -0.000766*** (-18.53) Degree of openness 0.0215** (1.55) 0.0314454*** (1.67) 0.0501996*** (3.39) 0.1026031*** (1.90) 0.0271*** (3.24) 0.0374*** (4.73) 0.0420*** (2.02) 0.0414096*** (5.22) Oil rents-0.196*** (-4.50) -0.0943209* (-1.83) -0.150* (-1.20) -0.171*** (-3.50) Natural resource rents -0.1831798*** (-2.40) -0.2206015*** (-1.81) -0.0917** (-1.53) -0.0984322*** (-1.84) Aid0.000742 (0.04) -0.0023504 (-0.24) -0.0026459 (-0.19) 0.0225858 (0.20) 0.0428 (1.03) 0.0465* (1.22) -0.0122 (-0.70) 0.0276829*** (1.70) Short-term debt 0.0356754 (0.47) 0.0291976 (0.42) 0.0172686 (0.19) -0.0818*** (-1.71) -0.0681* (-1.29) -0.00745 (-0.08) 0.0047133 (0.07) FDI0.0986 (0.68) 0.1234117 (0.34) 0.3719272 (0.89) 0.3934651 (0.91) 0.149 (0.98) 0.190 (1.18) -0/0793 (-0.24) 0.2572334 (0.64) Current- account balance -0.0106 (-0.46) -0.0109151 (-0.31) -0.0178363 (-0.48) -0.0176219 (-0.55) -0.0311 (-0.88) -0.0445* (-1.27) -0.0310* (-1.46) -0.0178995 (-0.37) Corruption-0.7264521*** (-2.24) -0.8135721*** (-2.40) -0.581732*** (-1.72) -1.254407** (-1.54) Shadow economy -0.0488828** (-1.41) Constant19.63*** (10.68) 18.94*** (8.16) 21.62*** (8.02) 15.89*** (6.09) 19.85*** (8.10) 19.31*** (9.10) 14.71*** (6.03) 19.50*** (7.45) N593479 162382 233321 Note : t stats in parenthèses ( * p<0.20, ** p<0.15, ***p<0.10).

34. Determinants Per Capita GDP: capacity to collect and pay taxes increases with the level of development Share of Agriculture: Large subsistence agricultural sector difficult to tax, might reduce spending on goods and services which derive more from urbanization Inflation: Stable macroeconomic regime is more conducive to greater collection of revenues and tax revenues; inflation tax is another source of revenue Openness: Trade-related taxes are easier to impose Oil or natural resources rents: Might indicate that countries that are dependent on natural resources tend to have weaker tax systems as they excessively rely on rents from these resources

35. Most important determinants Results of regression : Impact (coefficient estimates) of key determinants of tax revenues from the best specification A percentage point increase in: Share of agriculture decreases tax revenue (as a proportion of GDP) by 0.1 percentage point Degree of openness increases tax revenue by 0.02 percentage point Oil rents decreases tax revenue by 0.19 percentage point GDP per capita increases tax revenue by 0.001 percentage point Inflation decreases tax revenue by 0.0004 percentage point 35

36. The role of corruption and shadow economy Degree of corruption has a strong negative impact on tax revenues (reduces tax revenues by 0.5 percentage points) Size of the informal economy also has a negative effect on tax revenues (reduces tax revenues by 0.04 percentage points) Aid is not a significant determinant Other factors like FDI, short term debt and current account balance are not robust

37. 37

38. 38

39. Dep VarTax Revenue/GDP 1980–2009Including Corruption Including Shadow Economy 1990–20093-yr non- overlapping average (1980–09) Including Corruption GDP per capita 0.00112** (1.74) 0.0011406** (1.45) 0.0010521** (1.52) 0.0027115*** (2.73) 0.00186*** (2.50) 0.00180*** (2.39) 0.000554 (0.65) 0.0017706*** (1.86) Share of agriculture in GDP -0.103*** (-2.34) -0.0845695*** (-1.69) -0.1823801*** (-2.59) -0.0051849*** (-1.89) -0.0933*** (-2.75) -0.125*** (-2.81) -0.0413 (-1.08) -0.1122353*** (-3.07) Inflation-0.000392* (-1.48) -0.0008125*** (-16.86) -0.0007533*** (-15.16) -0.0007504*** (-7.48) -0.000385* (-1.26) -0.000367* (-1.19) 0.0000581*** (-6.60) -0.000766*** (-18.53) Degree of openness 0.0215** (1.55) 0.0314454*** (1.67) 0.0501996*** (3.39) 0.1026031*** (1.90) 0.0271*** (3.24) 0.0374*** (4.73) 0.0420*** (2.02) 0.0414096*** (5.22) Oil rents-0.196*** (-4.50) -0.0943209* (-1.83) -0.150* (-1.20) -0.171*** (-3.50) Natural resource rents -0.1831798*** (-2.40) -0.2206015*** (-1.81) -0.0917** (-1.53) -0.0984322*** (-1.84) Aid0.000742 (0.04) -0.0023504 (-0.24) -0.0026459 (-0.19) 0.0225858 (0.20) 0.0428 (1.03) 0.0465* (1.22) -0.0122 (-0.70) 0.0276829*** (1.70) Short-term debt 0.0356754 (0.47) 0.0291976 (0.42) 0.0172686 (0.19) -0.0818*** (-1.71) -0.0681* (-1.29) -0.00745 (-0.08) 0.0047133 (0.07) FDI0.0986 (0.68) 0.1234117 (0.34) 0.3719272 (0.89) 0.3934651 (0.91) 0.149 (0.98) 0.190 (1.18) -0/0793 (-0.24) 0.2572334 (0.64) Current- account balance -0.0106 (-0.46) -0.0109151 (-0.31) -0.0178363 (-0.48) -0.0176219 (-0.55) -0.0311 (-0.88) -0.0445* (-1.27) -0.0310* (-1.46) -0.0178995 (-0.37) Corruption-0.7264521*** (-2.24) -0.8135721*** (-2.40) -0.581732*** (-1.72) -1.254407** (-1.54) Shadow economy -0.0488828** (-1.41) Constant19.63*** (10.68) 18.94*** (8.16) 21.62*** (8.02) 15.89*** (6.09) 19.85*** (8.10) 19.31*** (9.10) 14.71*** (6.03) 19.50*** (7.45) N593479 162382 233321 Note : t stats in parenthèses ( * p<0.20, ** p<0.15, ***p<0.10).

40. Robustness and Sensitivity Sample data Business cycle effects Dynamic panel Lagged controls

41. Dependent variableTax Revenue/GDP 1980–2009 Excluding OilExcluding OutliersArellano Bond Control variables: GDP per capita0.000402 (1.07) 0.00118** (1.66) 0.000602*** (1.72) Share of agriculture in GDP-0.145** (-1.58) -0.148*** (-2.06) -0.0102 (-0.31) Inflation-0.000810*** (-10.02) -0.000754*** (-13.70) -0.000449*** (-3.60) Degree of openness0.109*** (2.48) 0.0521*** (3.37) 0.0299*** (3.19) Oil rents0.112*** (2.12) Natural resource rent-0.153*** (-2.20) -0.114** (-1.65) Aid-0.00564 (-0.33) 0.0471 (1.11) 0.0183 (1.06) Short-term debt-0.0231 (-0.28) 0.000862 (0.01) FDI0.270* (1.34) 0.299 (0.75) 0.182 (0.59) Current account balance-0.00791 (-0.16) -0.0371 (-1.07) -0.0120 (-0.43) Corruption-1.052*** (-2.30) -0.820*** (-2.47) -0.521*** (-2.66) Lag0.639*** (16.39) Constant17.79*** (4.25) 19.85*** (8.79) N326425432

42. Conclusions Alongside economic development and economic structure, macroeconomic stability and governance are critical for revenue mobilization Policies that strengthen institutions and reduce economic fragility can be conducive to better revenue mobilization; fragile economies tend to lag behind in collecting more revenue. Resource rich countries are subject to greater volatility; resource richness does not translate into greater ability to mobilize revenue. Over reliance on aid, trade taxes can hamper mobilization Revenue administration reforms should concentrate on reducing corruption and addressing the problem of non-compliance. The study can be extended to empirically determine the role of tax policy and administrative reforms to increase revenue.