www.akademiya2063.org The economic impacts of mitigation pathways in Rwanda Henry Okodua Department of Economics Covenant University, Nigeria [email protected] [email protected] Victoria Sedegan Department of Capacity and Deployment AKADEMIYA2063 [email protected] Comprehensive Africa Climate Change Initiative (CACCI) Project knowledge Seminar , Kigali, Rwanda Wednesday March 27, 2024

www.akademiya2063.org Introduction • As a result of good leadership qualities and an excellent management of national resources, Rwanda has maintained an enviable track record of sustained economic growth over recent years. • The country has also undertaken strategic measures across diverse sectors to reduce the emissions footprint of the economy. • However, maintaining a balance between the imperatives of economic prosperity and an emissions pathway to a net-zero economy, will always certainly require a conscious transition from traditional energy sources to an economy with very low carbon footprint. • The assumption here is that historically, growth is closely associated with greenhouse gas emissions.

www.akademiya2063.org Introduction/…2 • But one unanswered question remains; is there really a correlation between greenhouse gas emissions and economic growth? • Available statistics from the World Emissions Index show the following for Rwanda. • In 2019, gross domestic product (GDP) in Rwanda grew by 7.4% from the previous year. • Measured in US dollars, the economy went from $9.64bn to $10.4bn. • In the same period, carbon emissions increased by 1.3%. • Over a ten-year period from 2009 to 2019, GDP grew by 82.6%, while emissions also increased by 5.7%. • To put this into context, the compound annual growth rate(CAGR) of GDP in Rwanda over ten years (2009 to 2019) was 6.2% and the CAGR for greenhouse gas emissions was 0.56%.

www.akademiya2063.org An overview of emissions from major sectors of the Rwandan economy • Rwanda Climate Change Portal, available on the REMA website, has the country’s most recent greenhouse gas (GHG) inventory data (for 2018). Table 1: Rwanda’s GHG emissions by source in 2018 in MtCO2 e S/N Reporting Categories GgCO2 e MtCO2 e 1. Total emissions - Energy 2,630.1 2.630 2. Total emissions - IPPU 151.41 0.151 3. Total emissions - AFOLU 4,298.99 4.299 4. Total emissions - Waste 917.16 0.917 Source: Government of Rwanda available @ https://climatechange.gov.rw/index.php?id=23

www.akademiya2063.org An overview of emissions from major sectors of the Rwandan economy/…3

www.akademiya2063.org • From available statistics, an observed upward emissions growth trajectory for Rwanda is both undesirable and unsustainable for a cleaner world. • The country has made commitments to consciously reduce GHG emissions in order to contribute to climate change mitigation efforts globally. • Rwanda's commitment to mitigation involves a targeted reduction in greenhouse gas (GHG) emissions compared to a business-as-usual (BAU) baseline from 2015 to 2030. This commitment comprises two key components: Mitigation measures in major sectors of the Rwandan economy

www.akademiya2063.org Mitigation measures in major sectors of the Rwandan economy/…2 • Unconditional Contribution: A 16% reduction relative to BAU by the year 2030. This amounts to an estimated mitigation level of 1.9 million tonnes of carbon dioxide equivalent (tCO2e) in 2030. This target is unconditional and relies on domestically supported and implemented mitigation measures and policies. • Conditional Contribution: An additional 22% reduction relative to BAU by the year 2030. This represents an estimated mitigation level of 2.7 million tCO2e in 2030. This contribution is contingent on international support and funding. • The combined impact of the unconditional and conditional contributions results in a substantial 38% reduction in GHG emissions compared to BAU in 2030, equivalent to an estimated mitigation level of up to 4.6 million tCO2e. • This study focuses on emissions from the energy sector to simulate the mitigation pathways for Rwanda over the period 2021 – 2030.

www.akademiya2063.org Methodology • The study utilizes the Standard Applied General Equilibrium (STAND) Model developed by Fofona (2023) to simulate an economic modeling of climate change and mitigation measures in Rwanda. • The STAND model is an energy-focused dynamic recursive CGE model and it broadly comprises the agricultural and non-agricultural sectors of the economy. • We provide a description of the CGE model using a stepwise approach as follows. • First, the model is structured into the energy demand and supply sides. • The model is focused on the energy demand side, meaning that it has less emphasis on the supply side.

www.akademiya2063.org Methodology/…2 • Second, the model is also focused on emissions by energy products and emissions by production factors. • Emissions by energy products is of interest here because consumption of energy products such as fossil fuels are associated with emissions. • Third, the production block of the model follows a nested structure and this block represents the defining peculiarity of the STAND CGE model. • The model can accommodate different energy types that is combined with their own levels of emission. • The combination of each energy – emission bundle follows the Input-Output fixed complementarity CES function.

www.akademiya2063.org Methodology/…3 • There is substitution between the energy types. • What this means is that as new energy technologies become available to the economy, society can easily switch to other energy types, say for instance from fossil fuels to renewables. • The extended value-added is a unique feature of the STAND CGE model. • It is the addition of energy as a production factor to other production factors that makes this value added extended. • The interesting thing about energy as a production factor in the STAND CGE Model is that it is consumed within a business cycle, unlike the other production factors that are consumed within multiple business cycles. • Finally, the extended value added is combined with intermediate consumption (this is net of energy) to produce the aggregate output of the economy.

www.akademiya2063.org Data Source: 2021 Social Accounting Matrix (SAM) for Rwanda • The CGE model used in the study is anchored on the 2021 Social Accounting Matrix (SAM) for Rwanda published by the International Food Policy Research Institute (IFPRI). • The SAM has 41 sectors and commodities. • Labor and capital are the core production factors, however the SAM was adjusted to include energy capital and this produced the extended value-added component of the SAM. • There are 10 representative households (classified into rural and urban households and categorized along income quintiles). • Other economic agents include firms, government, and the rest of the world (row). • The SAM captures three tax components that form government revenue and include direct taxes (personal or corporate) import taxes on products, and sales taxes.

Structure of the Rwandan Economy based on the 2021 Social Accounting Matrix/…2 Table 2: Sectoral and Trade Structure of the 2021 Rwanda SAM Share of total (%) Exports/ output (%) Imports/ demand (%) GDP Exports Imports Sectors 100 100 100 11.0 18.8 Agriculture 23.5 12.9 1.3 1.4 0.2 Other-Industry 17.0 35.4 0.3 3.9 0.1 Manufacturing 8.4 30.4 82.4 3.3 15.5 Services 51.1 21.3 16.0 2.3 3.0 Source: Rwanda SAM 2021 • Services sector contributed the largest share to the GDP with 51.1%, • agriculture contributed 23.5%, and • Other-industry contributed 17% of the GDP in 2021. • The manufacturing sector contributed the least with 8.4%. • This result indicates that Rwanda's economy is predominantly driven by the services sector which is consistent with the quality of an emerging economy. • Also, the entire Industry sector (inclusive of the manufacturing sector) accounts for the bulk of Rwanda’s exports with a share of 65.8%. • The services sector on its part accounted for 21.3%, while the agricultural sector contributed 12.9% to Rwanda’s total exports in 2021.

Structure of the Rwandan Economy based on the 2021 Social Accounting Matrix/…3 • The share of labor and capital in total value-added are 49.0%, 41.4% and 9.6% respectively in 2021. • 37.4% of demand for low-skilled labor, are in the agriculture sector. • Services sector accounts for 35.1% of this labor type, and 17.9% goes to other-industry. • The remaining 9.5% of low-skilled labor demand is accounted for by the manufacturing sector. • As for medium-skilled labor demand, agriculture accounts for 48.8%, services has 25.3% of this labor type, manufacturing has 13.2%, while other- industry absorbs the remaining 12.6%. • 80.2% of labor demand in the services sector are high-skilled labor and the remaining 19.8% are spread relatively evenly among the agriculture (6.1%), other-industry(6.6%), and manufacturing (7.1%). Table 3: Production structure of the Rwanda Economy based on the 2021 SAM Share of total (%) Labor Physical capital Energy capital Share in Value-added 49.0 41.4 9.6 Labor Low Labor Medium Labor High Land Other- Capital Natural gas Petroleum oil Electricity Sectors 100 100 100 100 100 100 100 100 Agriculture 37.4 48.8 6.1 100 15.9 0 12.3 0 Other-Industry 17.9 12.6 6.6 0 14.0 100 25.6 29.3 Manufacturing 9.5 13.2 7.1 0 15.6 0 10.8 43.8 Services 35.1 25.3 80.2 0 54.4 0 51.3 26.9 Source: Rwanda SAM 2021

www.akademiya2063.org Simulation Scenarios • Given the earlier stated overarching emissions reduction goals of the Rwandan government, four broad simulation scenarios were implemented for this study. • The BAU and SIM1 – SIM3 • Each of SIM1 – SIM3 are further divided into two representing respectively a gradual implementation and a more aggressive implementation strategy for each of the scenarios. • Details of the simulation scenarios include: • Business-as-usual (BAU) scenario. Essentially a “do nothing” scenario. • SIM1a - Unconditional Emissions Reduction Scenario - gradual implementation approach. Here, unconditional target is 16% emissions reduction by 2030. • SIM1b - Unconditional Emissions Reduction Scenario – aggressive implementation approach. The 16% emissions reduction target in this case is spread equally over a five-year implementation period (2022-2026).

www.akademiya2063.org Simulation Scenarios/…2 • SIM2a - Conditional Emissions Reduction Scenario - gradual implementation. Here, unconditional target is an additional 22% emissions reduction in the economy by 2030. • SIM2b - Conditional Emissions Reduction Scenario – aggressive implementation. The 22% emissions reduction target is spread equally over a five-year implementation period (2022-2026). • SIM3a - Combined Target with gradual implementation – Combined emissions reduction targets is 38% by 2030. • SIM3b - Combined Target with aggressive implementation of the combined emissions reduction targets. Here, the combined target of 38% emissions reduction by 2030 spread equally over a five-year implementation period (2022-2026).

Simulation Results • Energy intensity of GDP is simply a measure of the total cost of energy per unit of GDP. • Under the BAU results (not presented), there is an expected steady increase in energy intensity of GDP. • In each scenario, the emissions reduction impact on energy intensity of GDP would be negative. • For example, when emissions are reduced gradually by 1.78% annually in SIM1a, energy intensity of GDP would be lower by 0.48% in 2022 when compared to the BAU value for the same year. • The downward variation would be 3.12% in 2026 when compared to the BAU value for 2026, and 6.67% less emissions would be expected under the SIM1a scenario in 2030 when compared to the BAU value for this year. • The expected reduction in energy intensity of GDP would increase if the country decides to be more aggressive in the implementation of the emissions reduction targets. • The results show that the decrease from the BAU for 2022 and 2026 respectively would be 0.61% and 4.16% under SIM1b. -9.00% -8.00% -7.00% -6.00% -5.00% -4.00% -3.00% -2.00% -1.00% 0.00% 2022 2023 2024 2025 2026 2027 2028 2029 2030 (% VARIATION FROM BAU YEAR Figure 1: Rwanda - Estimated Energy Intensity of GDP (% variation from BaU) Sim_1a Sim_1b Sim_2a Sim_2b Sim_3a SIM_3b

Simulation Results/…2 • Emissions intensity of GDP may be viewed as an indication of how efficiently an economy uses carbon- based resources to generate economic output. • Results of SIM1a show an expected steady decline in emissions intensity of GDP from 0.14% to in 2022 through to 0.55% in 2030 when these results are compared to their respective BAU values for each year. • Even when the aggressive emissions reduction approach is implemented in SIM1b, the pattern of decline in emissions intensity remains the same for all years in the simulation period. • The remaining two simulation scenarios also show results with remarkable decline in emissions intensity of GDP irrespective of whether the gradual or aggressive approach is implemented by the country. • What these results suggest up to this point is that every scenario of carbon emissions reduction holds undeniable potential environmental benefits for Rwanda. -0.70% -0.60% -0.50% -0.40% -0.30% -0.20% -0.10% 0.00% 2022 2023 2024 2025 2026 2027 2028 2029 2030 (% variation from BaU Year Figure 2: Rwanda - Emissions Intensity of GDP (variation) Sim_1a Sim_1b Sim_2a Sim_2b Sim_3a SIM_3b

Simulation Results/…3 • Expectedly, real GDP will decline in Rwanda throughout the simulation period when the shocks from emissions reduction are applied to the economy. • This is because the implementation of emissions reduction targets in the country is expected to constrain production as the economy endures the additional costs of transiting from carbon-based energy sources to cleaner energy sources. • This adverse economic impacts will be irrespective of whether the gradual or aggressive approaches are in force. • During the first year 2022, the negative impact of emissions reduction on real GDP is expected to vary between 0.11 percent and 0.13 percent across simulation scenarios. • The apparent stable outcomes across simulation scenarios will however begin to disappear as we progress in time to the effect that these variations become much more remarkable in later years. -8.00% -7.00% -6.00% -5.00% -4.00% -3.00% -2.00% -1.00% 0.00% 2022 2023 2024 2025 2026 2027 2028 2029 2030 (% variations from BAU Year Figure 3: Emissions Reduction Impact on RGDP (% variations from BAU) Sim_1a Sim_2a Sim_3a Sim_1b Sim_2b SIM_3b

Simulation Results/…4 • Total investment is expected to decline by about 0.46 percent in 2022 when compared to the BAU values for the same year under SIM1a. • This negative impact on investments would steadily decrease to -10.67 percent by 2030 when compared to the BAU value for that year under SIM1a. • SIM2b for year 2022 is expected to present the lowest negative impact on total investment in Rwanda, while SIM3a would return the worst negative impact on total investment in the country. • Thus, the maximum damage to total investment in the country would arise from the implementation of a combined target of 38 percent emission reduction using the gradual approach. • This damage is expected to be more pronounced towards the end of the implementation periods (2027 -2030). • On the contrary, the least damage to total investment in the country would arise from the implementation of an additional 22 percent emission reduction using the aggressive approach. -18.00% -16.00% -14.00% -12.00% -10.00% -8.00% -6.00% -4.00% -2.00% 0.00% 2022 2023 2024 2025 2026 2027 2028 2029 2030 (% variations of investment from BAU Year Figure 4: Rwanda - Emissions Reduction Impact on Investment (% variations from BAU) Sim_1a Sim_1b Sim_2a Sim_2b Sim_3a SIM_3b

Simulation Results/…5 • The percentage variations from the respective BAU values across simulation scenarios appear marginal and stable for agricultural value-added. • For year 2022 for example, the decline in agricultural value-added is approximately 0.05 percent for each scenario, meaning that agricultural value-added does not demonstrate considerable sensitivity to shocks to emissions across simulation scenarios during the initial periods following such shocks. • This trend is expected to continue until year 2026 when the decline in agricultural value-added increased from an average of 0.32 percent for most scenarios to 0.41 percent under SIM3b where the aggressive implementation approach was applied to the 38 percent combined targets emissions reduction scenario. • Year 2030 is however expected to record the greatest decline in percentage variation of agricultural value- added from the respected BAU values with SIM3a posting up to -1.47 Percent. -1.60% -1.40% -1.20% -1.00% -0.80% -0.60% -0.40% -0.20% 0.00% 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 5b: Rwanda - Emissions Reduction Impact on Agricultural Value-Added (% variations from BAU) Sim_1a Sim_1b Sim_2a Sim_2b Sim_3a SIM_3b

Simulation Results/…6 • services value-added is expected to post a very marginal decrease of about 0.04 percent from the BAU values in 2022 under each scenario, • Remarkable difference in impacts is however expected in year 2026 across simulation scenarios ranging from 0.40 percent decrease to 0.70 percent when compared to their BAU values in 2026. • In comparative terms, emissions reduction impact on services value-added for Rwanda appears to be more severe than that the impact on the agriculture value-added. • This is more pronounced when the impacts for the last four years of the simulation periods is considered across scenarios under the gradual implementation approach. -5.00% -4.50% -4.00% -3.50% -3.00% -2.50% -2.00% -1.50% -1.00% -0.50% 0.00% 2022 2023 2024 2025 2026 2027 2028 2029 2030 (% variations of iservices value-added from BAU Year Fig 6: Rwanda - Emissions Reduction Impact on Services Value-Added Sim_1a Sim_1b Sim_2a Sim_2b Sim_3a SIM_3b

Simulation Results/…7 • For manufacturing value-added, the simulation results suggest a much more pronounced adverse impacts when compared to the BAU values under all simulation scenarios. • Although the initial variations for year 2022 are identical to those of the agriculture and services value-added, • they become remarkably different as from year 2026 with the variation in manufacturing value- added rising up to -1.10 percent in SIM3a and SIM3b, and even up to 6.04 percent decline in manufacturing value-added when compared to the BAU. • Overall, the manufacturing value-added is expected to be the worst affected by the energy transition agenda of Rwanda when all three sectoral outputs as measured by value-added are compared. -7.00% -6.00% -5.00% -4.00% -3.00% -2.00% -1.00% 0.00% 2022 2023 2024 2025 2026 2027 2028 2029 2030 (% variations of manufacturing value-added from BAU Year Fig 7: Rwanda - Emissions Reduction Impact on Manufacturing Value-Added Sim_1a Sim_1b Sim_2a Sim_2b Sim_3a SIM_3b

www.akademiya2063.org Summary and Conclusion • The results presented above indicate the potential for immense environmental benefits arising from the implementation of the emission reduction agenda of the Rwanda government. • These benefits are obvious in the declining percentage variations of the energy and emissions intensities of GDP under all simulation scenarios. • The evidence from the study does not however support commensurate potential macroeconomic benefits accruable to the Rwandan economy when these policy scenarios are implemented at both the aggregate and sectoral levels and given the various simulation scenarios. • At the sectoral level, the results also reveal that the manufacturing sector will bear the brunt of implementing the energy transition agenda of the Rwandan government. • This is in terms of loss of annual value-added.

www.akademiya2063.org Recommendations • The findings of this study have considerable implications for sustainable growth and development of the Rwandan economy. • These findings should warrant several key recommendations to support a successful implementation of the emissions reduction commitments of the government as follows. • In view of the finding indicating immense environmental benefits inherent in the emissions reduction strategy of the government, as revealed in the expected decrease in both energy and emissions intensities of GDP, • it is recommended that the emissions reduction targets of the government should be vigorously implemented at all levels of the economy. • The gradual implementation approach will be more realistic in this case to allow the economy enough time to adjust to the shocks.

www.akademiya2063.org Recommendations/…2 • In view of the expected decrease in key macroeconomic variables in the economy, the government should mobilize enormous domestic resources by pursuing an appropriate carbon pricing framework to cover the huge cost of domestic investment needed to compensate for the expected decrease in real GDP and total investment. The introduction of a carbon tax regime should suffice in this case. • Foreign investors may complement domestic investment if provided incentives to invest massively in the renewable energy sector. The extension of commensurate tax-breaks to such foreign investors in designated priority sectors will suffice here. This will in effect, fast-track the transition to a green-growth economy. • The government should arm itself with findings from evidence-based studies such as the current study to make a strong case for external funding support from its international development partners under the conditional emissions reduction target.

Thank You