DjiboutiDjibouti

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Contact at AFI team is Kouassi Yeboua
This entry was last updated on 25 August 2022 using IFs v7.63.

In this entry, we first describe the Current Path forecast for Djibouti as it is expected to unfold to 2043, the end of the third ten-year implementation plan of the African Union's Agenda 2063 long-term vision for Africa. 

The Current Path forecast is divided into summaries on demographics, economics, poverty, health/WaSH and climate change/energy. A second section then presents a single positive scenario for potential improvements in stability, demographics, health/WaSH, agriculture, education, manufacturing/transfers, leapfrogging, free trade, financial flows, infrastructure, governance and the impact of various scenarios on carbon emissions. With the individual impact of these sectors and dimensions having been considered, a final section presents the impact of the Combined Agenda 2063 scenario. 

We generally review the impact of each scenario and the Combined Agenda 2063 scenario on gross domestic product per person and extreme poverty except for Health/WaSH that uses life expectancy and infant mortality. 

The information is presented graphically and supported by brief interpretive text. 

All US$ numbers are in 2017 values.

Summary

  • Current Path forecast
    • Djibouti had a population of approximately one million (0.97 million) in 2019, and on the Current Path, it is forecast to be 1.27 million by 2043, an increase of about 31% over the next 24 years. Jump to Demographics: Current Path 
    • In 2019, the GDP per capita (PPP and 2017 constant US$) for Djibouti was US$ 4 005. By 2043, it is projected to grow to US$7 087, about 29% lower than the projected average for lower middle-income countries in Africa. Jump to Economics: Current Path
    • Using the US$3.20 poverty threshold line for lower middle-income countries, Djibouti had almost half (49.8%) of its population living in extreme poverty in 2019, equivalent to 0.5 million people. The extreme poverty level at US$3.20 is forecast to decline to 27.4% (0.35 million people) by 2043, below the average for lower middle-income countries in Africa, which will then be at 38.3%. Jump to Poverty: Current Path
    • Carbon emissions in Djibouti increased from 0.1 million tons in 1990 to 0.2 million tons in 2019 and are forecast to reach 0.6 million tons by 2043, rising 200% from a very low base between 2019 and 2043. Jump to Carbon emissions/Energy: Current Path
  • Sectoral scenarios 
    • The Stability scenario further improves security and stability in Djibouti. By 2043, the governance security index score in the Stability scenario is 0.87, 10.1% higher than the Current Path forecast and 14.5 % higher than the projected average of 0.76 for African lower middle-income countries in the Current Path forecast. Jump to Stability scenario
    • In 2019, the ratio of the working-age population to dependants stood at 1.9, meaning that there are 1.9 people in the working-age population for each dependant. On the Current Path, it is forecast to be 2.1 by 2043. In the Demographic scenario, the working-age population to dependants ratio is 2.3 by 2043.  Jump to Demographic scenario
    • The Health/WaSH scenario improves life expectancy at birth to 73.9 years compared to 73.8 years in the Current Path forecast by 2043. In this scenario, life expectancy in Djibouti is about 0.3 years above the average for lower middle-income countries in Africa, at 73.3 years in 2043. Jump to Health/WaSH scenario
    • In the Agriculture scenario, crop yields improve from 28.6 tons per hectare in 2019 to 41.3 tons per hectare in 2043, compared to 26.7 tons in the Current Path forecast in the same year. Jump to Agriculture scenario
    • In the Education scenario, the mean years of education improves by about half a year above the Current Path forecast in 2043. In terms of gender, by 2043, in the Education scenario, the mean years of education for males is forecast to be 7.3 years, compared to 6.6 for females. Jump to Education scenario
    • In the Manufacturing/Transfers scenario, the number of poor people stands at 280 000 or 22.6% of the population by 2043, compared to 350 000 million or 27.4% in the Current Path forecast for that year, a difference of 70 000 fewer people in extreme poverty. Jump to Manufacturing/Transfers scenario
    • Fixed broadband subscription is very low in Djibouti; it was 4.4 subscriptions per 100 people in 2019 compared to the average of 3.7 for lower middle-income countries in Africa. In the Leapfrogging scenario, fixed broadband subscriptions increase to 50 subscriptions per 100 people by 2043, 22.2% higher than the Current Path forecast of 41 in the same year. Jump to Leapfrogging scenario
    • Djibouti’s trade deficit represented 13.5% of GDP in 2019, and it is forecast to be 9.7% of GDP in the Free Trade scenario compared to 8.4% of GDP in the Current Path forecast in 2043. Jump to Free Trade scenario
    • In the Financial Flows scenario, foreign direct investment (FDI) flows to Djibouti in 2043 represent 7.3% of GDP compared to 6.2% on the Current Path. Jump to Financial Flows scenario 
    • In 2019, 64.8% of the rural population in Djibouti resided within 2 km from all-weather roads, above the average of 61.4% for lower middle-income African countries. In the Infrastructure scenario, it is projected to increase to 75.6% by 2043, above the 72.6% of the Current Path forecast. Jump to Infrastructure scenario
    • The projected score for government effectiveness in the Governance scenario by 2043 is 2.4 (out of a maximum of 5). This is 4.8% higher than the projected score in the Current Path forecast in the same year. By 2043, Djibouti's government effectiveness score will be on par with the projected average for African lower middle-income countries in 2043. Jump to Governance scenario
    • The Free Trade and Manufacturing/Transfers scenarios will be the leading causes of increased carbon emissions in Djibouti throughout the forecast horizon. Jump to Impact of scenarios on carbon emissions
  • Combined Agenda 2063 scenario 

All charts for Djibouti

Chart 1: Political map of Djibouti
Chart
Djibouti: Current Path forecast

Djibouti: Current Path forecast

This page provides an overview of the key characteristics of Djibouti along its likely (or Current Path) development trajectory. The Current Path forecast from the International Futures forecasting (IFs) platform is a dynamic scenario that imitates the continuation of current policies and environmental conditions. The Current Path is therefore in congruence with historical patterns and produces a series of dynamic forecasts endogenised in relationships across crucial global systems. We use 2019 as a standard reference year. The forecasts generally extend to 2043 to coincide with the end of the third ten-year implementation plan of the African Union’s Agenda 2063 long-term development vision.

Djibouti is a lower middle-income country located in the Horn of Africa and bounded by Eritrea to the north, Ethiopia to the west and southwest, and Somalia to the south. Djibouti is one of the smallest countries in Africa, with an area of 23 200 km2. It is also a member of the Intergovernmental Authority on Development (IGAD), an eight-country regional bloc in Africa with ambitions to embark on regional integration. Compared to its peers in the Horn of Africa, Djibouti enjoys relative peace and stability and regularly goes through the motions of elections.

Djibouti’s natural resources are very limited. The country has no proven oil or natural gas reserves, and only 1% of the territory is forest. Djibouti’s main natural asset is probably its strategic location, which is at the southern entrance to the Red Sea, marking a bridge between Africa and the Middle East, and adjacent to some of the World's busiest shipping lanes (between Asia and Europe). As a result, Djibouti hosts a multitude of foreign military bases. The United States (US) installed a military base in Djibouti after the 9/11 attacks to pursue its war against terrorism (al-Qaeda and al-Shabaab). China’s first overseas military base since the Second World War is also in Djibouti. With a French military base (which includes troops from Germany), tiny Djibouti, with fewer than a million people, is also home to military bases from Italy, Japan and Spain. The country relies heavily on the associated rent.

Chart 1: Political map of Djibouti
Chart
Demographics: Current Path

Demographics: Current Path

Djibouti had a population of approximately one million (0.97 million) in 2019, and on the Current Path it is forecast to reach 1.27 million by 2043, an increase of about 31% over the next 24 years. Djibouti has the lowest fertility (TFR) rate among the Horn of Africa countries, estimated at 2.7 children per woman in 2020 – above the average for African lower middle-income countries, which is 4.3. On the Current Path, TFR will slowly decline to 2.1 births per woman by 2043.

Djibouti is host to a considerable number of refugees. In addition to thousands of economic migrants who, on an ongoing basis, clandestinely enter Djibouti and illegally assume a variety of jobs (usually in Djibouti city), the country has been inundated periodically with waves of refugees fleeing political persecution in neighbouring countries [1Britannica, Djibouti.]. With a median age of 25, Djibouti has a less youthful age structure than its peers in the Horn of Africa. As of 2019, 29.3% of the population was under the age of 15; 27.5% was under 30, while 4.6% was in the 65 and above dependency age group. On the Current Path, the shares of these age groups are projected to be, respectively, 22.5%, 23.9% and 9.5% by 2043. 

The working-age group, 15 to 64 years of age, represents the largest share of the population (65.9% in 2019), and is forecast to increase to 68% by 2043. The large share of the working-age group in Djibouti’s population could be a potential source of growth (reaping the demographic dividend), provided that the labour force is well trained and sufficient jobs are created.

Djibouti is the most urbanised country in sub-Saharan Africa, with 78.2% of the population classified as urban in 2019, up from 76% in 1990. This is roughly 29 percentage points below the average of 49.2% for lower middle-income countries in Africa. On the Current Path development trajectory, 81.6% of the population will be urban by 2043, while the rural population will have dropped to 18.4% from 24.1% in 1990 and 21.8% in 2019. If these projections materialise, more than four out of every five Djiboutians will live in a town or city by 2043. Urban growth has mainly been driven by urban centres, and mostly Djibouti city, the country’s capital city, that has 58% of the urban population.

This rapid urbanisation, if not well managed, could lead to challenges such as unemployment, poverty, inadequate health, poor sanitation, urban slums and environmental degradation. Balbala, west of the city of Djibouti, is the country’s biggest slum, and urban poverty has become a challenge for the Djiboutian authorities. However, since 2007 the government has undertaken a policy to reduce urban poverty via the Program for Urban Poverty Reduction in Djibouti (PREPUD) [2Agence Francaise de Developpment (AFD), Djibouti.]. Good urban planning could foster an inclusive economy by improving service delivery and reducing urban poverty. In addition, adequate and appropriate urban planning is essential to mitigate the impacts of climate change, such as flooding.

Djibouti is virtually a city-state, since about two-thirds of the population lives in or near the capital. Outlying towns are small trading centres that experience periodic population increases as camel caravans and sheep and goat herders encamp. The density of Djibouti’s population amounted to less than one inhabitant per hectare in 2019, on par with the average for lower middle-income countries in Africa. The population density is forecast to increase, but will remain below one inhabitant per hectare in 2043.

Chart 4: Population density map for 2019
Chart
Economics: Current Path

Economics: Current Path

The small size of Djibouti's economy limits its ability to diversify production and increases its reliance on foreign markets, making it more vulnerable to market downturns and hampering its access to external capital. Therefore, the economy relies on financial, telecommunications and trade-related services, solidifying the country’s position as an important regional business and trade hub in the Horn of Africa. Djibouti’s economy is driven by a state-of-the-art port complex, among the most sophisticated in the world. Trade through the port is expected to grow rapidly in parallel with the expanding economy of the country’s largest neighbour and main trading partner, Ethiopia. As a result, Djibouti's economy relies heavily on the service sector.

With sufficient tourism-related infrastructure, Djibouti could harness its enormous tourism potential, which remains untapped. Recognising the need for economic transformation, the government of Djibouti has initiated, through its Vision 2035, a programme to boost economic transformation and diversification. Through this development plan, Djibouti aims to develop a digital technology hub, promote light manufacturing, create more than 200 000 jobs and triple its GDP per capita by 2035 [3World Bank, Republic of Djibouti, 2014, High-Level Development Exchange: Launch of Vision Djibouti 2035.].

After Ethiopia, Djibouti is the fastest-growing economy in the Horn of Africa. Djibouti’s economy has been less affected by the pandemic so far than expected. Output growth slowed down to 0.5% in 2020, rather than contracting further, thanks to buoyant free zone re-exports and exports of transportation, logistics and telecommunication services to and from Ethiopia [4 World Bank, Country overview: Djibouti.]. The country’s medium-term economic outlook remains positive. In 2019, the size of Djibouti’s economy was US$2.2 billion, up from US$1.1 billion in 1990. By 2043, the economy is projected to grow to US$6 billion. In terms of economic size, Djibouti ranked 48th out of 54 countries in Africa in 2019. In the Current Path forecast, it will have the 50th largest economy in Africa by 2043. 

Although many of the charts in the sectoral scenarios also include GDP per capita, this overview is an essential point of departure for interpreting the general economic outlook of Djibouti.

The GDP per capita (PPP) for Djibouti was US$ 4 005 in 2019 and is forecast to increase to US$ 7 085 in 2043, about 29% lower than the projected average for lower middle-income countries in Africa. In 2020, the GDP per capita of Djibouti shrank by 4.1% compared to its level in 2019 due to the COVID-19 pandemic and its associated economic crisis.

The informal economy comprises activities that have market value and would add to tax revenue and GDP if they were recorded. Djibouti has a dual economy in which a modern sector, based on rent income from port activities and military bases, coexists with a large informal sector. The informal sector plays an important role in the economy, with informal enterprises comprising 60% of all business activity in the country, according to the African Development Bank (AfDB).

In 2019, the size of the informal economy represented about 27.8% of the country’s GDP, and by 2043 it is projected to modestly decline to 22.8%, slightly below the projected average of 26.3% of GDP for lower middle-income countries in Africa. This projected improvement in the formalisation of the economy augurs well for government revenue. Reducing informality will allow more people to benefit from better wages and redistributive measures. Therefore, Djiboutian authorities need to take steps to reduce the size of the informal economy with the least friction possible by lowering the hurdles to registering a business, tackling corruption and improving access to finance.

The IFs platform uses data from the Global Trade and Analysis Project (GTAP) to classify economic activity into six sectors: agriculture, energy, materials (including mining), manufacturing, services and information and communications technologies (ICT). Most other sources use a threefold distinction between only agriculture, industry and services, with the result that data may differ.

Djibouti’s economy relies heavily on the service sector. The country’s geographical location, its political and economic stability and dynamic port sector offer the opportunity to strengthen its position as a regional hub for various financial, information and communications technology (ICT), and logistics services. In 2019, the services sector accounted for 78% of GDP (US$1.7 billion). On the Current Path, the share of the service sector in GDP will slightly decrease to 75.7% (US$4.5 billion) by 2043.

The service sector is followed by the manufacturing sector at 18.6% of GDP (US$0.42 billion) in 2019 and will slightly increase to 19.6% of GDP (US$1.2 billion) by 2043. There are no significant manufacturing clusters in Djibouti and the government is prioritising sectors other than manufacturing for development. The rapid expansion of free trade zones in cooperation with Chinese firms will create a potential for investment in manufacturing capacity. However, the small size and low skill levels of the local labour force will limit the scope for manufacturing clusters [5 HKTDC Research, Manufacturing in East Africa: Djibouti, 2019.].

The share of the agriculture sector in Djibouti’s GDP is negligible (about 1.4% in 2019), and it is projected to remain stable at this level across the Current Path forecast. Most of the country is semi-arid to arid, and water resources are limited; the high cost of irrigation makes imported agricultural produce cheaper, [6FAO, Irrigated agriculture in Djibouti, 2009. ] hindering agriculture production. The share of ICT in GDP was 1% in 2019, and it is projected to rise to 2.4% by 2043. Energy contributed 1.6% (US$0.04 billion) in 2019, and its contribution to GDP is forecast to be US$0.06 billion in 2043. 

The data on agricultural production and demand in the IFs forecasting platform initialises from data provided on food balances by the Food and Agriculture Organization (FAO). IFs contains data on numerous types of agriculture but aggregates its forecast into crops, meat and fish, presented in million metric tons. Chart 9 shows agricultural production and demand as a total of all three categories.

Approximately 30% of Djibouti’s rural population depends on the agriculture sector. However, it is poorly developed and faces numerous challenges and climatic impediments. Djibouti is highly food insecure, owing to recurrent droughts, natural disasters and poor governance that hamper crop and livestock production. Of Djibouti’s 23 200 km2 of land, only 1 000 km2 are arable, and the country receives an average annual rainfall of only 130 mm [7The Borgen Project, The top 10 facts about agriculture in Djibouti, 2019.]. As a result, Djibouti has the biggest food deficit in the Horn of Africa and imports up to 90% of foodstuffs. This situation makes the country highly dependent on international market prices. Any variation in global prices has a considerable impact on the poorest segment of the population, who spend 77% of their household budget on food [8WFP, Djibouti Country Brief, March 2020.].

Agricultural production in 2019 stood at 0.09 million metric tons, up from 0.05 million metric tons in 1990. This is significantly lower than the demand of 1.86 million metric tons in 2019. Across the forecast horizon, the excess demand will continue to increase. In 2043, agricultural production and demand are forecast to be 0.12 million metric tons and 2.78 million metric tons, respectively. This is equivalent to excess demand of 2.66 million metric tons. In other words, 95.6% of total agricultural demand will likely be met through imports by 2043.  
Given Djibouti’s limited agricultural potential, the only way to increase agricultural production and reduce food insecurity is to improve productivity. Djibouti could follow the example of the Netherlands, which has become the second-largest agricultural exporter globally after the US despite its small land area. However, this will require significant investment in climate-smart technologies and productivity-enhancing farming methods.

Poverty: Current Path

Poverty: Current Path

There are numerous methodologies for and approaches to defining poverty. We measure income poverty and use GDP per capita as a proxy. In 2015, the World Bank adopted the measure of US$1.90 per person a day (in 2011 international prices), also used to measure progress towards the achievement of Sustainable Development Goal 1 of eradicating extreme poverty. To account for extreme poverty in richer countries occurring at slightly higher levels of income than in poor countries, the World Bank introduced three additional poverty lines in 2017:

  • US$3.20 for lower middle-income countries 
  • US$5.50 for upper middle-income countries
  • US$22.70 for high-income countries.

Despite Djibouti’s small population, the nation has historically struggled with poverty – a similarity shared with other countries in the Horn of Africa. The harsh, dry climate has exacerbated poverty in Djibouti, especially in rural areas where most of the population practises nomadic farming. Prolonged droughts coupled with high unemployment rates keep many people in extreme poverty. Cognisant of this situation, the National Development Plan (Vision Djibouti 2035) adopted in 2014 intends to diversify the economy and speed up job creation to help Djiboutians find gainful employment and reduce extreme poverty.

In 2019, 49.8% of the population lived below the lower middle-income country poverty line (US$3.20). This is equivalent to 0.5 million people. The poverty rate increased to 57.5% in 2020 due to the COVID-19 pandemic and associated economic slowdown. The extreme poverty level at US$3.20 is forecast to decline to 27.4% (0.35 million people) by 2043, below the average for lower middle-income countries in Africa, which will then be at 38.3%.

To sustain economic growth over the long term, it must be inclusive. Policymakers in Djibouti should make growth more inclusive by integrating the most vulnerable segment of the population, including women, into the economy and enhancing human capital formation to meet the needs of the labour market and hence create more gainful jobs and accelerate poverty reduction.

Carbon Emissions/Energy: Current Path

Carbon Emissions/Energy: Current Path

The IFs platform forecasts six types of energy, namely oil, gas, coal, hydro, nuclear and other renewables. To allow comparisons between different types of energy, the data is converted into billion barrels of oil equivalent (BBOE). The energy contained in a barrel of oil is approximately 5.8 million British thermal units (MBTUs) or 1 700 kilowatt-hours (kWh) of energy. 

The energy needs of Djibouti are met mainly through the import of fossil fuels. Before 2011, Djibouti was 100% dependent on heavy fuel oil and diesel thermal power plants for energy, which exposed the country to fluctuating oil prices. Now, 65% of the country’s electricity needs are met through an interconnection with the Ethiopian grid. Local power production, now accounting for about 35% of the energy supply, continues to be generated through local heavy fuel oil or diesel thermal. 

In 2019, hydro accounted for 9% of the energy produced in the country, while gas accounted for 91%. Gas will continue to be the dominant energy produced in Djibouti until 2032. By 2033, other renewable energies will take over and account for 62.5% of the energy produced. This is not surprising as the government of Djibouti has taken steps to increase energy security by emphasising renewable energies. The country’s National Development Plan, Vision 2035, plans a transition from fossil thermal to 100% renewable energy. The law provides a tax exemption for all renewable energy equipment. By 2043, renewable energies will represent 62.5% of the total energy produced while gas will account for 18.7%. Hydro, nuclear and oil will account for 6.2% each.

Carbon is released in many ways, but the three most important contributors to greenhouse gases are carbon dioxide (CO2), carbon monoxide (CO) and methane (CH4). Since each has a different molecular weight, IFs uses carbon. Many other sites and calculations use CO2 equivalent.

Carbon emission is very low in Djibouti. It increased from 0.1 million tons in 1990 to 0.2 million tons in 2019. On the Current Path, it is forecast to reach 0.6 million tons by 2043, increasing 200% from a very low base between 2019 and 2043. Developed economies must help the country and many other African countries to deal with the impact of climate change, which will affect them disproportionately.

Stability scenario

Stability scenario

The Stability scenario represents reasonable but ambitious reductions in risk of regime instability and lower levels of internal conflict. Stability is generally a prerequisite for other aspects of development and this would encourage inflows of foreign direct investment (FDI) and improve business confidence. Better governance through the accountability that follows substantive democracy is modelled separately.

The intervention is explained in here in the thematic part of the website.

Compared to its peers in the Horn of Africa, Djibouti, which hosts a multitude of foreign military bases, enjoys relative peace and stability. Despite some latent clan-level grievances, there are no separatist or insurgent movements, and the authority of the government is established nationwide. The IFs governance security index ranges from 0 (low security) to 1 (high security). The Current Path forecast shows higher stability in Djibouti than the average for lower middle-income Africa. The score for Djibouti on the government security index is forecast to increase from 0.71 in 2019 to 0.79 in 2043. 

By 2043, the score in the Stability scenario is 0.87, or 10.1% higher than the Current Path forecast and 14.5% higher than the projected average of 0.76 for Africa’s lower middle-income countries in the Current Path forecast. The war in Ethiopia has shown how instability can imperil an impressive economic growth record. Ethiopia’s case demonstrates that a state’s capacity to maintain order is the most important condition for development. 

Recent calls from al-Shabaab for attacks on ‘American and French interests’ in Djibouti indicate that the country may not be insulated from instability trends elsewhere in the Horn of Africa. Therefore, the government and policymakers in Djibouti should take proactive measures to preserve the social and political stability the country has been enjoying so far. 

More stability promotes peace and political consensus in a country and encourages greater domestic and foreign investment, positively affecting income per capita growth.

By 2033 Djibouti’s GDP per capita would be US$100 higher in the Stability scenario than in the Current Path forecast for that year. In 2043, the difference would increase to US$275. Hence, by 2043, Djibouti would record a GDP per capita of US$7 362, a 4% increase from the Current Path forecast (at US$7 087). In the Current Path assumptions for other countries, the GDP per capita of Djibouti in the stability scenario is US$1 781 below the projected average of US$9 142 for African lower middle-income countries in 2043. 

Stability in a country is an important condition for economic growth and poverty reduction. When using the lower middle-income countries’ extreme poverty threshold of US$3.20, 0.5 million Djiboutians (49.8% of the population) were considered to be extremely poor in 2019. The number of poor people stands at 0.31 million (24.7%) by 2043 in the Stability scenario, compared to 0.35 million (27.4%) in the Current Path forecast for that year, a difference of 40 000 fewer people in extreme poverty. The poverty rate in Djibouti in the Stability scenario (at $3.20 per day) in 2043 is 13.6 percentage points below the projected average of 38.3% for African lower middle-income countries in the Current Path forecast.

Demographic scenario

Demographic scenario

This section presents the impact of a Demographic scenario that aims to hasten and increase the demographic dividend through reasonable but ambitious reductions in the communicable-disease burden for children under five, the maternal mortality ratio and increased access to modern contraception. 

The intervention is explained in here in the thematic part of the website.

Demographers typically differentiate between a first, second and even a third demographic dividend. We focus here on the contribution of the size of the labour force (between 15 and 64 years of age) relative to dependants (children and the elderly) as part of the first dividend. A window of opportunity opens when the ratio of the working-age population to dependants is equal to or surpasses 1.7. 

Djibouti is at a later stage in the demographic transition than its peers in the Horn of Africa. When the working-age population far outnumbers the dependant population, the opportunity for a demographic dividend arises. But this is so provided the growing labour force acquires the needed skills and is productively employed in the formal economy. Specifically, a nation must reach at least 1.7 people of working age for each dependant to potentially experience a demographic dividend, an economic growth generated by a change in the population structure. Djibouti has reached this ratio, recording an estimated 1.9 people of working age for each dependant in 2019. 

In the Current Path forecast, it is predicted to be 2.13 by 2043. In the Demographic scenario, the working-age population to dependants ratio is set to be 2.31 by 2043. If sufficient education and employment are generated, Djibouti could harness the productive power of this large working-age population.  

The infant mortality rate is the number of infant deaths per 1 000 live births and is an important marker of the overall quality of the health system in a country. As of 2019, the infant mortality rate in Djibouti was 35.4 deaths per 1 000 live births, below the average of 46 for Africa's lower middle-income countries. 

In the Current Path forecast, the country is on track to meet the 2030 SDG target to reduce infant mortality to fewer than 25 deaths per 1 000 live births. The infant mortality rate is projected to decline to 21.4 in 2030. By 2043 the infant mortality rate in the Demographic scenario is 11.8, compared to 13.8 in the Current Path forecast. In 2043, the infant mortality rate in the Demographic scenario is about 17.8 percentage points below the average for lower middle-income countries in Africa – which, in the Current Path forecast, still do not achieve the infant mortality SDG target even by 2043, at which point the average would be at 29.6 deaths per 1 000 live births.

The Demographic scenario’s impact on per capita income is marginal, at approximately US$37 more than the Current Path forecast of US$5 602 in 2033. By 2043, the difference increases to US$123, a 1.7% improvement on the Current Path forecast in that year. Moreover, this will be US$1 932 lower than the projected average for lower middle-income countries in Africa, at US$9 142 by 2043.

Using the lower middle-income extreme poverty threshold of US$3.20, 0.5 million Djiboutians (49.8% of the population) were considered to be extremely poor in 2019. The number of poor people stands at about 0.33 million or 26.3% of the population by 2043 in the Demographic scenario, compared to 0.35 million people or a poverty rate of 27.4% in the Current Path forecast for that year, a difference of 20 000 fewer people in extreme poverty. The poverty rate in the Demographic scenario in 2043 is about 12 percentage points below the projected average for Africa’s lower middle-income countries in the Current Path forecast.

Health/WaSH scenario

Health/WaSH scenario

This section presents reasonable but ambitious improvements in the Health/WaSH scenario, which include reductions in the mortality rate associated with both communicable diseases (e.g. AIDS, diarrhoea, malaria and respiratory infections) and non-communicable diseases (NCDs) (e.g. diabetes), as well as improvements in access to safe water and better sanitation. The acronym WaSH stands for water, sanitation and hygiene.

The intervention is explained in here in the thematic part of the website.

The quality of a nation’s health system can be gauged by indicators such as life expectancy, maternal mortality and infant mortality, among others. Access to health services in Djibouti is hindered by geographical and cultural barriers, low literacy, and other social and environmental determinants of health. 

As of 2019, life expectancy in Djibouti was about 67.4 years. The Health/WaSH scenario improves life expectancy at birth to 73.9 years, from 73.8 years in the Current Path forecast by 2043. In this scenario, life expectancy in Djibouti is about 0.3 years above the average for lower middle-income countries in Africa, at 73.3 years in 2043. On average, females have a higher life expectancy at birth of 69.8 years, compared to 65.3 for males in 2019. In the Health/WaSH scenario, life expectancy at birth for females is projected to be 76.8 years by 2043, compared to 72.5 years for males.

The Health/WaSH scenario reduces infant mortality to 18.8 per 1 000 live births from 19 in the Current Path forecast by 2033. By 2043, the infant mortality rate is 13.7, compared to 13.8 in the Current Path forecast. The infant mortality rate in the Health/WaSH scenario is below the average for lower middle-income countries in Africa, which in the Current Path forecast still does not achieve the infant mortality SDG target even by 2043 – at which point the average would be 29.6 deaths per 1 000 live births.

Agriculture scenario

Agriculture scenario

The Agriculture scenario represents reasonable but ambitious increases in yields per hectare (reflecting better management and seed and fertiliser technology), increased land under irrigation and reduced loss and waste. Where appropriate, it includes an increase in calorie consumption, reflecting the prioritisation of food self-sufficiency above food exports as a desirable policy objective.

The intervention is explained in here in the thematic part of the website.

The data on yields per hectare (in metric tons) is for crops but does not distinguish between different categories of crops.


In Djibouti, the agricultural sector makes a marginal contribution to GDP. Due to the country’s climate (arid to semi-arid) and the scarcity of freshwater resources (about 150 mm of rainfall per year), only irrigated and seasonal agriculture is possible. In its National Development Plan, Djibouti hopes to increase domestic production, including seafood, and encourage value addition with the aim of exporting to Gulf countries. By 2035, Djibouti aims to have its agricultural sector contributing 5% of GDP [9 Republic of Djibouti, Vision Djibouti 2035.]. Without significant efforts, this target will be very challenging to meet, given the difficult farming conditions in the country. Indeed, in the Current Path forecast, crop yields by 2043 are lower than in 2019. On the Current Path, the average crop yield is forecast to decline from 28.6 tons per hectare in 2019 to 26.7 tons per hectare in 2043. However, in the Agriculture scenario, the average crop yield is 41.3 tons per hectare in 2043, 14.5 tons per hectare larger than the Current Path forecast in 2043, and a 44.3% increase from its level in 2019. 

Djibouti’s dry, harsh climate and poor soils limit farm output. As a result, the country has the biggest food deficit in the Horn of Africa, and imports up to 90% of its foodstuffs. This situation makes the country highly dependent on international market prices and erodes its current account balance. In the Current Path forecast and the Agriculture scenario, the food import dependence is forecast to decline slightly but will remain above 90% of total food demand across the forecast horizon. In the Agriculture scenario, import dependence increases from 97.1% of total food demand in 2019 to about 94.8% by 2043, compared to 95.7% in the Current Path forecast in the same year. In other words, the Agriculture scenario reduces agricultural import dependence by nearly 1% of total demand compared to the Current Path in 2043. 

The agricultural sector makes a marginal contribution to economic growth in Djibouti, and only a few people work in farming. By 2043 the GDP per capita in the Agriculture scenario is US$7 069, US$18 lower than the Current Path forecast of US$7 087. Improvement in agriculture production in Djibouti will require heavy investment in climate-smart technologies and productivity-enhancing farming methods, given the harsh, dry climate and limited arable land. This may reduce investment in other sectors with high growth potential, negatively affecting GDP growth and lowering GDP per capita. In other words, it will likely be a trade-off between food security and economic growth.

The Agriculture scenario has a marginal impact on poverty reduction. Using the US$3.20 per person per day extreme poverty threshold, the poverty rate in the Agriculture scenario by 2043 is 26.7% compared to 27.4% in the Current Path forecast. This is equivalent to 9 000 fewer people in extreme poverty.

Education scenario

Education scenario

The Education scenario represents reasonable but ambitious improved intake, transition and graduation rates from primary to tertiary levels and better quality of education. It also models substantive progress towards gender parity at all levels, additional vocational training at secondary school level and increases in the share of science and engineering graduates.

The intervention is explained in here in the thematic part of the website.

Improving education in Djibouti is at the forefront of its government’s development policies. Although schooling in Djibouti still lags behind more developed nations, efforts to improve education have already made strides for the children of Djibouti and improvements and plans have been crafted. With continued attention and effort put towards education, the future for Djibouti youths is looking up and may very well continue to improve.

The average years of education in the adult population (aged 15 years and older) is a good indicator of the stock of education in a country. This stood at 5.3 years in 2019 and, on the Current Path, is projected to improve to 6.4 years by 2043. This is 2.1 years below the average of 8.5 years for lower middle-income countries in Africa in the Current Path forecast. Technically, this means that most Djiboutians will have at least primary education by 2043. In the Education scenario, the mean years of education improves by about half a year above the Current Path forecast in 2043. 

In terms of gender, males’ mean years of education was 6, 1.6 years more than the female average of 4.4 years in 2019. By 2043, the mean years of education for males is forecast to be 7.3 years compared to 6.1 for females in the Education scenario. This means that the materialisation of the Education scenario would reduce the gender gap in education in the country.

In the Education scenario, the score for the quality of primary education improves from 27.5 out of a possible 100 in 2019 to 36.8 in 2043, a 15% increase compared to the Current Path forecast. In addition, the score for the quality of secondary education goes from 37.7 in 2019 to 47.8 in 2043 in the scenario, a 19.5% improvement compared to the Current Path in 2043. These findings also reveal that the education quality at secondary level is better than that of the primary level in Djibouti. 

Quality education is crucial for economic development. Countries such as South Korea and Malaysia have succeeded in transitioning to emerging market status thanks to their investments in building some of the best education systems in the world. Education allows a country not only to increase its current value added, but also to create tomorrow’s technological innovations

By 2043, the Education scenario will increase GDP per capita by US$185 above the US$7 087 in the Current Path forecast. In other words, in 2043, the GDP per capita in the Education scenario is 2.6% larger than the Current Path forecast. Investment in education significantly impacts economic growth, but it takes time to materialise. It will take more than a decade for a child enrolled in primary school to contribute meaningfully to the economy. Investment in human capital affects labour productivity with a long lag, so it takes more than 15 years until output surpasses its counterpart in a program that invests mainly in infrastructure [10African Development Bank Group, African Economic Outlook 2021, March 2021.].

Using the US$3.20 lower middle-income country extreme poverty line, by 2043 the Education scenario will record a poverty rate of 25.2% (0.32 million people) compared to 27.4% (0.35 million people) in the Current Path forecast. This means that, by 2043, the absolute number of poor people in the Education scenario is 30 000 fewer than in the Current Path forecast. 


Education is an important tool for reducing poverty. It improves the job and income prospects of the poor segment of society. The Djiboutian government is taking steps to improve the quantity and quality of education in the country. Beyond securing universal education, the current priorities of the Ministry of National Education and Vocational Training concern the evaluation and improvement of teaching staff, the incorporation of ICT into classrooms, and strengthening technical and vocational education systems. To achieve these goals, 24% of the national budget was allocated to education in 2018 [11Oxford Business Group, Djibouti progresses with providing improved education outcomes with the help of international partners.].

Manufacturing/transfers scenario

Manufacturing/transfers scenario

The Manufacturing/Transfers scenario represents reasonable but ambitious manufacturing growth through greater investment in the economy, investments in research and development, and promotion of the export of manufactured goods. It is accompanied by an increase in welfare transfers (social grants) to moderate the initial increases in inequality that are typically associated with a manufacturing transition. To this end, the scenario improves tax administration and increases government revenues.

The intervention is explained in here in the thematic part of the website.

Chart 30 should be read with Chart 8 that presents a stacked area graph on the contribution to GDP and size, in billion US$, of the Current Path economy for each of the sectors.

The manufacturing sector is vital to creating jobs, improving productivity, changing the structure of an economy and ultimately reducing poverty. In the Manufacturing/Transfers scenario, the share of manufacturing in GDP (%) records the highest improvement compared to the Current Path. In 2043, its share in GDP is 0.8 of a percentage point above the Current Path forecast. However, in the Manufacturing/Transfers scenario, the share of the agriculture sector in GDP does not improve above the Current Path forecast in 2043. 

In absolute value, the contribution of the service sector experiences the largest improvement compared to the Current Path across the forecast horizon. The contribution of the service sector to GDP in the Manufacturing/Transfers scenario is US$0.32 billion larger than in the Current Path forecast in 2043. The service sector is followed by the manufacturing industry, with its value in the the Manufacturing/Transfers scenario being US$0.15 billion larger than the value forecast on the Current Path in 2043. Going forward, the service sector will continue to be the dominant sector of Djibouti’s economy.

Government to household welfare transfers are very low in Djibouti. Compared to the Current Path, the Manufacturing/Transfers scenario increases household transfers and welfare by 42.8% in 2043. This represents US$0.09 billion more than the Current Path forecast of US$0.30 billion. To make the social safety net programmes more effective at reducing poverty, better targeting and efficient approaches are critical.

Manufacturing is the engine of economic growth. It has backward and forward linkages with other sectors and transforms the productivity structures across the economy. Thus, a robust manufacturing sector is crucial for achieving sustained growth and significantly improving living standards. In the Manufacturing/Transfers scenario, GDP per capita is US$209 more than in the Current Path forecast, at US$5 602 in 2033. By 2043, GDP per capita would have increased to US$7 462 in the Manufacturing/Transfers scenario, compared to US$7 087 in the Current Path forecast. This is a US$ 375 increase above the Current Path forecast for that year.

Using the lower middle-income extreme poverty threshold of US$3.20, the number of poor people stands at 0.28 million or 22.6% of the population by 2043 in the Manufacturing/Transfers scenario compared to 0.35 million or 27.4% in the Current Path forecast for that year – a difference of 70 000 fewer people in extreme poverty. The poverty rate in the Manufacturing/Transfers scenario in 2043 is about 16 percentage points below the average for Africa’s lower middle-income countries in the Current Path forecast.

Leapfrogging scenario

Leapfrogging scenario

The Leapfrogging scenario represents a reasonable but ambitious adoption of and investment in renewable energy technologies, resulting in better access to electricity in urban and rural areas. The scenario includes accelerated access to mobile and fixed broadband and the adoption of modern technology that improves government efficiency and allows for the more rapid formalisation of the informal sector.

The intervention is explained in here in the thematic part of the website.

Fixed broadband includes cable modem Internet connections, DSL Internet connections of at least 256 KB/s, fibre and other fixed broadband technology connections (such as satellite broadband Internet, ethernet local area networks, fixed-wireless access, wireless local area networks, WiMAX, etc.).

Djibouti is among the rare countries that still maintain state monopoly on all telecommunication services, including fixed lines, mobile, Internet and broadband. Consequently, penetration rates have remained low despite the progress made in recent years. The fixed broadband subscription in Djibouti was 4.4 subscriptions per 100 people in 2019, above the average of 3.7 for lower middle-income countries in Africa. In the Leapfrogging scenario, fixed broadband subscriptions increase to 50 subscriptions per 100 people by 2043, 22.2% higher than the Current Path forecast of 40.9 in the same year.

 

Mobile broadband refers to wireless Internet access delivered through cellular towers to computers and other digital devices.

Mobile broadband subscriptions per 100 people in Djibouti in 2019 (at 21.8) were significantly below the average for lower middle-income Africa (at 49 subscriptions per 100 people). In the Leapfrogging scenario, mobile broadband subscriptions per 100 people converge with the Current Path forecast, at roughly 132 in 2043.

The number of Djiboutians who had access to electricity in 2019 was 0.62 million people, representing 63.8% of the total population. However, access to electricity is skewed towards urban areas. In 2019, 73.1% of the urban population had access to electricity, compared to only 31% of the population in rural areas. 

In the Leapfrogging scenario, 91.4% of the population (1.2 million people) will have access to electricity by 2043. This is above the projected average of 81.7% for African lower middle-income countries. It is also roughly 6.8 percentage points higher than the Current Path forecast of 84.6%.  By 2043, 92.8% of the urban population will have access to electricity in the Leapfrogging scenario, compared to 88.7% in the Current Path forecast. Regarding the population in rural areas, 85% will have access to electricity by 2043 in the Leapfrogging scenario, compared to 66.7% in the Current Path forecast in the same year.

Widespread access to high-speed Internet can improve a country’s socioeconomic outcomes. Broadband can increase productivity, reduce transaction costs and optimise supply chains, positively affecting economic growth. By 2033, GDP per capita in the Leapfrogging scenario will be US$5 754, compared to US$5 600 in the Current Path forecast, a difference of US$154. In 2043, this difference is slightly more significant, at US$260 more than the Current Path forecast at US$7 087. The GDP per capita in the Leapfrogging scenario is US$1 795 lower than the average of US$9 142 for lower middle-income countries in Africa.

In the Leapfrogging scenario, the number of poor people in 2043 is 0.32 million, representing 25.5% of the population. This is 25 000 fewer poor people than the Current Path forecast in the same year. In the Leapfrogging scenario, the poverty rate is 12.8 percentage points lower than the average of 38.3% for Africa’s lower middle-income countries in 2043.

Free Trade scenario

Free Trade scenario

The Free Trade scenario represents the impact of the full implementation of the African Continental Free Trade Area (AfCFTA) by 2034 through increases in exports, improved productivity and increased trade and economic freedom.

The intervention is explained in here in the thematic part of the website.

Trade balance is the difference between a country’s export and import values at a given time, usually within a year. A country that imports more goods and services than it exports in terms of value has a trade deficit, while a country that exports more goods and services than it imports has a trade surplus. Djibouti’s trade deficit represented 13.5% of GDP in 2019 and is set to improve slightly to 8.4% of GDP in the Current Path forecast by 2043. 

Between 2023 and 2041, the country’s trade deficit as a percentage of GDP in the Free Trade scenario is lower than it is in the Current Path forecast. However, the trade deficit in the Free Trade scenario deteriorates further between 2042 and 2043 compared to the Current Path forecast. Thus, in 2043, the trade deficit in the scenario is 9.7% of GDP, compared to 8.4% in the Current Path forecast. When the AfCFTA is fully implemented, the trade deficit recorded in the Free Trade scenario is set to be higher than that in the Current Path forecast: with the removal of trade restrictions, it will become easier to import – while Djibouti’s firms will face intense competition in export markets.

In the Current Path forecast, GDP per capita increases from US$4 005 in 2019 to US$7 087 in 2043 but would be US$7 652 in the Free Trade scenario, an increase of US$565 above the Current Path forecast for that year. This shows that the full implementation of AfCFTA has the potential to enhance economic growth in Djibouti. Trade openness increases technology diffusion and competition, positively affecting productivity growth.

Trade openness will reduce poverty in the long term after initially increasing it due to the redistributive effects of trade. Most African countries export primary commodities and low-tech manufacturing products, and therefore a continental free trade agreement (AfCFTA) that reduces tariffs and non-tariff barriers across Africa will increase competition among countries in primary commodities and low-tech manufacturing exports. Countries with inefficient, high-cost manufacturing sectors might be displaced as the AfCFTA is implemented, thereby pushing up poverty rates. In the long term, as the economy adjusts and produces and exports its comparatively advantaged (lower relative cost) goods and services, poverty rates will decline.

Between 2027 and 2039, the poverty rate in the Free Trade scenario is higher than the rate in the Current Path forecast. However, in the period 2040 to 2043, the poverty rate at $3.20 in the Free Trade scenario is below the rate in the Current Path forecast. The initial increase in poverty rate arises from the redistributional effect of trade openness associated with the implementation of AfCFTA and, as firms and households adjust in the long run, poverty rates decline from 2040. By 2043, the poverty rate in the Free Trade scenario is forecast to be 24.16%, compared to 27.4% in the Current Path forecast in 2043. This is equivalent to 42 000 fewer poor people than in the Current Path forecast. Full implementation of the AfCFTA will improve growth and reduce poverty in Djibouti; however, it will increase the poverty rate in the short to medium term. This is because implementation will lead to creative destruction: inefficient firms will be kicked out of the markets and collapse under intense competition. This will lead to job losses and poverty, unless the government responds with a safety net programme. But in the long run, as the efficient firms grow with trade opportunities, the unemployment rate declines – and so does the poverty rate.

Financial Flows scenario

Financial Flows scenario

The Financial Flows scenario represents a reasonable but ambitious increase in worker remittances and aid flows to poor countries and an increase in the stock of foreign direct investment (FDI) and additional portfolio investment inflows to middle-income countries. We also reduced outward financial flows to emulate a reduction in illicit financial outflows.

The intervention is explained in here in the thematic part of the website.

Many countries in sub-Saharan Africa are still heavily dependent on foreign aid to provide basic services like education and health. In Djibouti, aid constituted 6.5% of GDP in 2019, above the average of 2.4% of GDP for Africa. In the Financial Flows scenario, foreign aid flows to Djibouti are forecast to reach 2.9% of GDP in 2043, compared to 2.8% in the Current Path forecast. This is above the projected average of 0.5% of GDP for lower middle-income countries in Africa. In the Financial Flows scenario and the Current Path forecast, aid (% of GDP) in 2043 is lower than in 2019. This is because donors prioritise low-income countries.

Foreign direct investment (FDI) can be an important catalyst for growth and development as it brings much-needed capital and technology into recipient economies. In percentage of GDP, Djibouti and Ethiopia are the recipients of the highest FDI inflows in the Horn of Africa. FDI flows to Djibouti amounted to 9.1% of GDP in 2019, before dropping to 5.9% in 2020 due to the COVID-19 pandemic and its associated economic crisis. This is above the average for Africa’s lower middle-income countries, which was 2.6% of GDP in 2019. 

In the Financial Flows scenario, FDI flows to Djibouti in 2043 represent 7.3% of GDP compared to 6.2% in the Current Path forecast. Djibouti offers a stable political environment and a strategic geographic position with growing opportunities for foreign investment. However, its poor business climate deters investment. For instance, in the 2020 Doing Business report by the World Bank, Djibouti ranked 110 out of 190 countries. The government of Djibouti should prioritise efforts to improve the business climate.

Djibouti is a net receiver of remittances. About 54% of the inbound remittances to Djibouti are sent from France [12UNHCR, Remittances.]. Net remittance flows to Djibouti were estimated at 1.7% of GDP (US$ 0.04 billion) in 2019. Across the forecast horizon, Djibouti remains a net receiver of remittances. In the scenario, the total net remittances to Djibouti are forecast to be US$0.2 billion (2.7% of GDP) by 2043, compared to US$0.15 billion (2.5%) in the Current Path forecast.

In the Financial Flows scenario, Djibouti’s GDP per capita increases from US$4 005 in 2019 to US$7 203 in 2043, which is a 79.8% increase – compared to 76.9% in the Current Path forecast over the same period. In 2043, GDP per capita in the Financial Flows scenario is US$116 higher than in the Current Path forecast. Overall, the Financial Flows scenario has a modest impact on GDP per capita in Djibouti. 

In contrast to FDI, other external financial flows such as remittances and aid do not clearly correlate with economic growth. FDI, which can boost growth and development through capital accumulation and technology transfer, has not yet reached the level that would make it a game-changer in the country.

Using the US$3.20 poverty threshold, the Financial Flows scenario reduces the number of extremely poor Djiboutians by 15 000 in 2043 compared to the Current Path forecast. Whereas 49.8% of Djibouti’s population lived in extreme poverty in 2019, by 2043 it would be 26.2% in the Financial Flows scenario compared to 27.4% in the Current Path forecast. Remittances improve the economic conditions of recipient households; they also help to invest in education, improving the poor’s job and income prospects.

Infrastructure scenario

Infrastructure scenario

The Infrastructure scenario represents a reasonable but ambitious increase in infrastructure spending across Africa, focusing on basic infrastructure (roads, water, sanitation, electricity access and ICT) in low-income countries and increasing emphasis on advanced infrastructure (such as ports, airports, railway and electricity generation) in higher-income countries.

Note that health and sanitation infrastructure is included as part of the Health/WaSH scenario and that ICT infrastructure and more rapid uptake of renewables are part of the Leapfrogging scenario. The interventions there push directly on outcomes, whereas those modelled in this scenario increase infrastructure spending, indirectly boosting other forms of infrastructure, including that supporting health, sanitation and ICT. 

The intervention is explained in here in the thematic part of the website.

In 2019, the total number of people with access to electricity in Djibouti was 0.62 million, representing 63.8% of the population. The Infrastructure scenario increases this to 1.13 million in 2043, constituting 88.8% of the population. This is slightly above the projected 1.08 million, representing 84.6% of the population, in the Current Path forecast in 2043.

By 2043, it is projected that 91.6% of the urban population in Djibouti will have access to electricity, compared to 88.7% in the Current Path forecast. However, only 76.4% (0.18 million people) and 66.7% (0.16 million people) of the rural population in the Infrastructure scenario and the Current Path forecast respectively will have access to electricity in 2043, indicating a disparity in access to electricity between the urban and rural population in both the Current Path and the Infrastructure scenario.

Indicator 9.1.1 in the Sustainable Development Goals refers to the proportion of the rural population who live within 2 km of an all-season road and is captured in the Rural Access Index.

Accessibility to rural areas is important in spurring the socio-economic development of a country and improving the living standards of the rural population. Better rural roads facilitate trade between rural and urban areas. For instance, they enable the rural population to enjoy amenities from nearby urban areas while allowing the urban population to benefit more easily from the agricultural products supplied by rural areas.

In 2019, 64.8% of the rural population in Djibouti resided within 2 km of all-weather roads, above the average of 61.4% for lower middle-income African countries. In the Infrastructure scenario, it is projected to increase to 75.6% by 2043, above the 72.6% in the Current Path forecast and the average of 67.7 % for lower middle-income countries in Africa.

Increased investment in infrastructure improves connectivity and reduces transaction costs, positively affecting productivity and growth. Djibouti’s GDP per capita is forecast to rise to US$7 274 by 2043 in the Infrastructure scenario. This is US$187 more than the Current Path forecast in the same year, but below the average of US$9 142 for Africa’s lower middle-income countries.

Infrastructure development enables business and industry development, and increases efficiency in delivering social services. Critical basic infrastructure such as roads and electricity play a vital role in achieving sustainable and inclusive economic growth. Thus, in the Infrastructure scenario, the extreme poverty rate at $3.20 is projected to decline from 49.8% in 2019 to 25.6% in 2043. This is equivalent to 0.32 million poor people in 2043, compared to 0.35 million in the Current Path forecast. This suggests 30 000 fewer poor people in the Infrastructure scenario than in the Current Path forecast in 2043. The extreme poverty rate of 25.6% in the Infrastructure scenario by 2043 is about 13 percentage points lower than the projected average of 38.3% for Africa’s lower middle-income countries.

Governance scenario

Governance scenario

The Governance scenario represents a reasonable but ambitious improvement in accountability and reduces corruption, and hence improves the quality of service delivery by government.

The intervention is explained in here in the thematic part of the website.

As defined by the World Bank, government effectiveness ‘captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies’.

In the Current Path forecast and Governance scenario, Djibouti’s government effectiveness score is projected to increase across the forecast horizon. The projected score for government effectiveness in the Governance scenario by 2043 is 2.37 (out of a maximum of 5). This is 4.8% higher than the score in the Current Path forecast in the same year. Djibouti's government effectiveness score in 2043 will also be on par with the average for Africa’s lower middle-income countries.

 

In the Governance scenario, Djibouti’s GDP per capita is projected to increase to US$7 277 in 2043, which is US$190 more than the Current Path forecast in the same year. The GDP per capita of US$7 277 in the Governance scenario in 2043 is, however, lower than the projected average of US$9 142 for lower middle-income countries in Africa in the same year. Critical determinants of growth depend on governance and institutional setting in a country. Authorities in Djibouti should improve governance to enhance economic growth and income levels.

Using the US$3.20 poverty threshold for lower middle-income countries, the poverty rate in Djibouti is projected to decline to 25.6% in 2043 in the Governance scenario, which is lower than the average of 38.3% for lower middle-income countries in Africa. The poverty rate of 25.6% in 2043 is equivalent to 23 000 fewer poor people than in the Current Path forecast for 2043.

Impact of scenarios on carbon emissions

Impact of scenarios on carbon emissions

This section presents projections for carbon emissions in the Current Path for Djibouti and the 11 scenarios. Note that IFs uses carbon equivalents rather than CO2 equivalents.  

In 2019, Djibouti released 0.25 million tons of carbon and, in the Current Path forecast, will release 0.56 million tons by 2043, an increase of 124%. Although carbon emissions are set to increase with increased economic activity, Djibouti’s carbon emissions come off a very low base. Like many developing countries, Djibouti will disproportionately suffer the impact of climate change, to which it has contributed very little. Nonetheless, the country must reduce its carbon emissions, move towards renewable energy for sustainable growth and mitigate the devastating impacts of climate change. Djibouti has taken a critical step towards the exploration of its untapped renewable energy resources (geothermal, wind and solar resources). For instance, the country's National Development Plan, Vision 2035, plans a transition from fossil thermal to 100% renewable energy. In this vein, legislation has been passed to open electricity generation to private sector involvement. The law provides a tax exemption for all renewable energy equipment [13 International Renewable Energy Agency, By 2020, Djibouti Can Meet 100% of Energy Through Renewables, 25 May 2015.].

The Free Trade scenario has the most significant impact on carbon emissions, followed closely by the Manufacturing/Transfers scenario. The Demographic scenario has the lowest level of carbon emission. The reduction of population growth reduces population pressure on the utilisation of resources and hence minimises environmental degradation. Except for the Demographic scenario, the quantity of carbon emissions in all the scenarios is higher than in the Current Path forecast in 2043. By 2043, carbon emissions range from 0.59 million tons for the Free Trade scenario to 0.53 million tons for the Demographic scenario

Combined Agenda 2063 scenario

Combined Agenda 2063 scenario

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The Combined Agenda 2063 scenario consists of the combination of all 11 sectoral scenarios presented above, namely the Stability, Demographic, Health/WaSH, Agriculture, Education, Manufacturing/Transfers, Leapfrogging, Free Trade, Financial Flows, Infrastructure and Governance scenarios. The cumulative impact of better education, health, infrastructure, etc. means that countries get an additional benefit in the integrated IFs forecasting platform that we refer to as the synergistic effect. Chart 55 presents the contribution of each of these 12 components to GDP per capita in the Combined Agenda 2063 scenario as a stacked area graph.

The synergistic effect of all the scenarios on GDP per capita is US$196.2 in 2043, meaning that the impact of the Combined Agenda 2063 scenario on GDP per capita is more than a mere sum of individual scenario impact. The scenario with the most significant impact on GDP per capita by 2043 is the Free Trade scenario, followed by the Manufacturing/Transfers scenario, while the Agriculture scenario has the least impact on GDP per capita. This suggests that policies to strengthen the manufacturing sector associated with trade liberalisation will have the most significant potential to improve human and economic development in Djibouti.

Whereas Chart 55 presents a stacked area graph on the contribution of each scenario to GDP per capita as well as the additional benefit or synergistic effect, Chart 56 presents only the GDP per capita in the Current Path forecast and the Combined Agenda 2063 scenario.

In the Combined Agenda 2063 scenario, the government makes a concerted effort to remove the binding constraints on growth and development in Djibouti. The Combined Agenda 2063 scenario has a greater impact on GDP per capita than the individual thematic scenarios. By 2033, Djibouti’s GDP per capita is US$907 larger than in the Current Path forecast, and by 2043 it is US$9 549 – that is, US$2 462 more than in the Current Path forecast for that year. The Combined Agenda 2063 scenario shows that a policy push across all the development sectors is necessary to achieve sustained growth and development in Djibouti. 

Using the US$3.20 poverty line for lower middle-income countries, by 2033 30.3% of Djiboutians will be living in extreme poverty in the Combined Agenda 2063 scenario, compared to 36.29% in the Current Path forecast. This translates to 81 000 fewer people living in extreme poverty than in the Current Path forecast. In 2043, the extreme poverty rate declines to roughly 12.7% (157 000 people) compared to 27.4% (350 000 people) in the Current Path forecast. In 2043, the poverty rate in the Combined Agenda 2063 scenario is far below the average of 38.3% in the Current Path forecast for lower middle-income Africa.

See Chart 8 to view the Current Path forecast of the sectoral composition of the economy.

Across the forecast horizon, the share of manufacturing in GDP (%) records the highest improvement compared to the Current Path. By 2043, the share of manufacturing in GDP (%) in the Combined Agenda 2063 scenario is 7.6 percentage points larger than the Current Path forecast. That of the service sector is 6.7 percentage points lower than the Current Path forecast in 2043.

In absolute value, the contribution of the service sector will experience the largest improvement compared to the Current Path forecast across the forecast horizon. The contribution of the service sector to GDP in the Combined Agenda 2063 scenario is US$1.7 billion larger than in the Current Path forecast in 2043. The service sector is followed by the manufacturing industry, with its value in the Combined Agenda 2063 scenario US$1.3 billion larger than the value forecast on the Current Path in 2043. Going forward, the service sector will continue to be the dominant sector of Djibouti's economy.

The Combined Agenda 2063 scenario dramatically impacts the expansion of Djibouti’s economy. In this scenario, GDP is projected to expand from US$2.2 billion in 2019 to US$9 billion in 2043, a 309% increase over the period compared to 172% on the Current Path over the same period. 

In 2043, Djibouti’s GDP in the Combined Agenda 2063 scenario is US$3 billion larger than the in Current Path forecast. The Combined Agenda 2063 scenario shows that a policy push across all the development sectors is necessary to achieve sustained growth in Djibouti.

In the Combined Agenda 2063 scenario, carbon emissions increase from a very low base (0.25 million tons of carbon in 2019) to 0.64 million tons by 2043 (a 156% increase between 2019 and 2043) compared to 124% on the Current Path over the same period. In 2043, carbon emissions in the Combined Agenda 2063 scenario are 80 000 tons higher than in the Current Path forecast.

The materialisation of the Combined Agenda 2063 scenario would stimulate high economic growth in Djibouti, but the cost in terms of environmental degradation could also be high. To mitigate the environmental impact of the Combined Agenda 2063 scenario, its implementation should be accompanied with concrete steps to accelerate the energy transition.

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Cite this research

Kouassi Yeboua (2022) Djibouti. Published online at futures.issafrica.org. Retrieved from https://futures.issafrica.org/geographic/countries/djibouti/ [Online Resource] Updated 25 August 2022.