TUNISIA Economic convergence slowed after 2010 and the gap in GDP per capita with respect to OECD countries is still large. Productivity is relatively high compared to other emerging economies but labour participation is low, especially for women and young graduates. Poverty has declined, as well as income inequality, which is lower than in comparable countries. However, significant disparities in employment and well-being still exist between regions. Water supply is a critical issue and the rising risk of water stress may impact growth and wellbeing. Business investment should be promoted by improving the business environment. The 2017 investment law and the adoption of the list of sectors needing authorisation will help in this respect. Remaining administrative and regulatory burden should be removed. Trade facilitation should be enhanced and taxation made more predictable. Credit to the private sector should be enhanced to help start-ups and growing companies. Reducing inequalities in the labour market and across regions is also crucial and requires a new regional development policy, emphasising the specific assets of each region around the development of urban centres. The quality of education should be improved and education systems should better respond to the need of businesses, while women employment should be encouraged by childcare policies and awareness campaigns. Growth performance, inequality and environment indicators Average annual growth rates (%) GDP per capita
A. Growth
Labour utilisation1 Labour productivity
2002-08 4.3 1.1 3.2
2012-18 0.8 -0.1 0.9
Level 2015 32.8 (31.7)*
3
GHG emissions per capita (tonnes of CO2 equivalent)
GHG emissions per unit of GDP3 (kg of CO2 equivalent per USD) 3
Share in global GHG emissions (%) * OECD simple average (weighted average for emissions data)
Gap to the upper half of OECD countries4
Per cent 0 -10
B. Inequality and environment
Gini coefficient2
C. Gaps in GDP per capita and productivity are large and persistent
Annual variation (percentage points)
2015 3.7 (12.3)*
2010-15 -0.6 (0)* Average of levels 2010-2012-2015 3.7 (12.8)*
0.4 (0.3)*
0.4 (0.4)*
0.1
0.1
-20 -30 -40 -50 -60 -70 -80 -90
GDP per capita
GDP per employee
Note: For the explanation of the indicators above and their sources, please go to the metadata annex at the end of this note. Source: OECD, Economic Outlook Database, International Labour Organisation (ILO), Key Indicators of the Labour Market (KILM) Database and World Bank, World Development Indicators (WDI) Database.
Policy indicators A. Barriers to entrepreneurship and trade and investment are high
B. The total tax wedge on labour is high Percentage of total labour costs, 2018²
Index scale of 0-6 from least to most restrictive, 2016¹
6
Employees' social security contributions Employers' social security contributions Income tax
Barriers to entrepreneurship Explicit barriers to trade and investment
5 4
50 40 30
3 20
2
10
1 0
TUNISIA
Advanced economies
TUNISIA
Emerging economies
Advanced economies
Emerging economies
0
Note: For the explanation of the indicators above and their sources, please go to the metadata annex at the end of this note. Source: Panel A: Product Market Regulation Database; Panel B: OECD, Taxing Wages Database and OECD (2018), OECD Economic Surveys: Tunisia 2018.
Beyond GDP per capita A. Inequality has decreased but remains higher than in advanced economies Gini coefficient, 2016 or last available year¹
SVK, 24.1
ZAF, 63.0
TUNISIA, 32.8
Advanced economies median, 29.7
Emerging economies median, 46.2
B. Exposure to fine particulate matter is very high Percentage of population exposed to PM2.5, 20172
% TUNISIA Advanced economies
< 10 μg/m³ 10-35 μg/m³
Emerging economies
> 35 μg/m³
World 0
10
20
30
40
50
60
70
80
90
100
Note: For the explanation of the indicators above and their sources, please go to the metadata annex at the end of this note.
Source: Panel A: OECD, Income Distribution Database, World Bank, World Development Indicators Database and China National Bureau of Statistics; Panel B: OECD, Environment Database.
Tunisia : Going for Growth 2019 priorities Improve the business climate to boost investment. Private investment is low. The adoption of the list of sectors needing authorisation is an important step to simplify the business environment. •
Recommendations: Further reduce restrictions on the presence of foreign executives. Reconsider price controls and other restraints on competition. Evaluate systematically the fiscal cost and the impact of financial and tax incentives contained in the new law on investment, job creation and regional inequalities.
Improve performance in logistics and trade facilitation. Cross-border trade suffers from unnecessary administrative burdens and poor infrastructure and the performance in this respect has deteriorated. •
Recommendations: Simplify administrative and customs procedures for goods entering and exiting the country. Improve the management of port infrastructures, potentially through publicprivate partnerships.
Facilitate firms’ access to funding. Access to financing is a major issue for many enterprises and the performance of the banking system could be enhanced. •
Recommendations: Ensure prompt application of the bankruptcy law. Speed up the adoption of the law governing credit bureaus. Allow banks to set risk premiums by reconsidering the ceiling on lending rates.
Boost job creation to reduce inequalities. Job creation is weak and informal employment is widespread. Unemployment is high, especially among young graduates and the gender gap in the labour market is significant. •
Recommendations: Diversify the funding sources for social security. Ensure that systems for education, learning and training respond to the requirements of businesses. Improve the quality of education by developing lifelong training for teachers. Encourage the recruitment of women through awareness campaigns.
Promote a new regional development policy. There are significant regional disparities in well-being and employment. •
Recommendations: Consider a new approach to the development of regions in the interior based on their specific assets and on economies of agglomeration in major cities. Modernise the governance of the regions and local authorities. Give the regions the autonomy and resources they need to determine their own development strategies.
Metadata Annex
Growth performance, inequality and environment indicators 1. Labour utilisation is defined as the ratio of total employment over population. 2. The Gini coefficient measures the extent to which the distribution of disposable income among households deviates from perfect equal distribution. A value of zero represents perfect equality and a value of 100 extreme inequality. 3. Total GHG emissions in CO2 equivalents from the International Energy Agency (IEA) database. This data conform to UNFCCC GHG emission calculations but are not directly comparable to data for Annex I countries due to definitional issues. The OECD average is calculated according to the same definition. GDP is expressed in USD, at constant 2010 prices and PPPs. For the share in global GHG emissions, the last available year is 2015.
4. Percentage gap with respect to the weighted average using population weights of the highest 18 OECD countries in terms of GDP per capita (in constant 2010 PPPs). The 2018 value of total employment has been estimated for Australia, Canada, Japan and the United States.
Policy indicators 1. Data refer to 2013 for advanced and emerging economies. 2. Situation of a single person at 100% of average earnings without children. Data refer to 2015 for Tunisia.
Beyond GDP per capita 1. Inequality is measured by the Gini coefficient at disposable income. Emerging economies median excludes India and Indonesia. Data refer to 2015 for Tunisia. 2. Data refer to 2015 for Tunisia. According to the World Health Organisation (WHO), exposure to fine particulate matter (PM2.5) has significant adverse effects on health compared to other pollutants. Inhaled PM2.5 cause serious health problems (respiratory and cardiovascular diseases), having most serious effects on children and elderly persons. The estimates of chronic outdoor exposure to PM2.5 (from both anthropogenic and natural sources, in Âľg/m3) are derived from satellite observations, chemical transport models and ground monitoring stations. Population exposure to air pollution is calculated by weighting concentrations with populations in each cell of the underlying gridded data.