Expert Group Meeting on SDG Economic Indicators in Africa 14-16 November 2017, Addis Ababa, Ethiopia
A case study for Mauritius Indicators Covered 7.1.1 Proportion of population with access to electricity 7.1.2 Proportion of population with primary reliance on clean fuels and technology 7.2.1 Renewable energy share in the total final energy consumption 7.3.1 Energy intensity measured in terms of primary energy and GDP 9.4.1 CO2 emission per unit of value added 9.1.2 Passenger and freight volumes, by mode of transport A case study for Mauritius
Goal 7 – Affordable & clean energy 5 Targets & 6 Indicators
Goal 9 – Industry, Innovations & infrastructure 8 Targets & 12 Indicators Responsible organisations – Ministries: Land Transport, Environment, Finance & Economic Development & SM
Data source for monitoring the SDGs …. Common data sources Housing and Population Census Household surveys Economic surveys Administrative data Environment data Geospatial data up to date and quality data will be required to compile SDG indicators on environment
SDG Implementation- Government Commitment (1/2) September 25th, 2015 - Government endorsed the 2015 Agenda. Next Comprehensive program of implementation Develop a national strategy Set up a national monitoring framework and a process for annual reporting Establish multi-stakeholder advisory groups to support implementation SDG Implementation- Who are involved? SDGs cannot be implemented in isolation, they require inputs from all sectors to achieve the global and ambitious plan The SDGs will engage multiple stakeholders at all levels of society to actualize the agenda.
Institutional arrangement – Implementation of SDGs Steering Committee – Ministry of Environment, Sustainable Development, and Disaster and Beach Management has been called upon by the Cabinet Office to chair the Committee Objective - Coordination mechanism to oversee SDG-based national planning with a 15-year time horizon. The Committee on SDG Statistical Indicators Under the aegis of the Statistics Board Chaired by the Director of Statistics
Institutional arrangement – Implementation of SDGs Mandate of the Committee of SDG Statistical Indicators Consider the development of relevant indicators at the required disaggregated level Assess the data gaps and advise on how to address these gaps Identify the relevant data sources Recommend the coordination mechanism needed for compiling the indicators through appropriate and efficient data-sharing procedures among data producers Identify areas where technical assistance will be required
Approach for the study of the Goal 7 and 9 Indicators Comparison of national data with UNSD SDG data and UNECA Survey data Discrepancies found in methodologies (concepts and definitions/metadata) and data sources Analysis of accuracy: how far values deviate from each other Availability; National sources vs international ones used by SDG database and UNECA Methodologies; national v/s UNSD metadata Proposed improvements and gap filling
Methodologies 7.1.1 Proportion of population with access to electricity: PopElectAccss = ( PopElect 𝑖 𝑃 𝑜𝑝𝑇𝑜𝑡 𝑖 ×100 ) where PopElectAccss is the proportion of population with access to electricity, PopElect i is the population at time of census having access to electricity in area i (i=1 =urban, i=2=rural). The percent change from one period to another can be calculated from the formula: 𝑃𝑅 = ( 𝑉 𝑃𝑟𝑒𝑠𝑒𝑛𝑡 − 𝑉 𝑃𝑎𝑠𝑡 ) 𝑉 𝑃𝑎𝑠𝑡 ×100 Where: PR = Percent Rate; VPresent = Present or Future Value; VPast = Past or Present Value . The annual percentage growth rate is simply the percent growth divided by N, the number of years.
Methods 7.1.2 Proportion of population with primary reliance on clean fuels and technology. This indicator, also collected from HPC, is derived as: PopCleanFuel = ( PopLPG _Elect 𝑖 𝑃 𝑜𝑝𝑇𝑜𝑡 𝑖 ×100 ) where PopCleanFuel is the proportion of population using clean fuel, PopLPG_Elect i is the population at time of census using Liquefied Petroleum Gas (LPG) and electricity (i.e. clean fuels) for cooking in area i (i=1 =urban, i=2=rural). This is a calculation adapted to the country situation according to the SDG metadata and methods. The interpolations for intercensal years can be obtained by applying the same formula as for the previous indicator above. 7.2.1 Renewable energy share in the total final energy consumption, Percent (Units). The consumption by sector is presented as follows: Agriculture: Energy used for irrigation and by other agricultural equipment; Commercial & distributive trade: Energy consumed by the business and commercial sector; Residential: Consumption of energy by residential sector; Manufacturing: Consumption in industry and construction; and Transport: Includes consumption by land vehicles, ships and local aircrafts. The simple calculation formula for this indicator is: 𝑅𝑒𝑛𝑒𝑤𝐸𝑛𝑒𝑟𝑔𝑦𝑓𝑢𝑒𝑙 = ( Renew _EnergyFinal 𝑖 , 𝑗 𝐹𝑖𝑛𝑎𝑙_𝐸𝑛𝑒𝑟𝑔𝑦𝑇𝑜𝑡𝑎𝑙 ×100 ) where RenewEnergyfuel is the share of renewable energy in the final consumption, Renew _EnergyFinal is the renewable final energy consumption, and Final_EnergyTotal is the total final energy consumption. The subscript i and j denote the fuel type and sector where the energy is consumed respectively.
Methods 9.1.2 Passenger and freight volumes, by mode of transport, Metric Tons (Units): The SDG metadata defines this indicator as Passenger and freight volumes is the sum of the passenger and freight volumes reported for the air carriers in terms of number of people and metric tonnes of cargo respectively. For Mauritius, this indicators has been disaggregated as (i) Passengers by mode of transport: Air transport (Arrival and Departure), and Sea transport (Arrival and Departure); (ii) Freight volumes by mode of transport, including Air transport freight Loaded and Unloaded, and Sea transport freight Loaded and Unloaded. 9.4.1 CO2 emission per unit of value added, Metric Tons (Units): The CO2 emissions calculations are done by applying the simple formula from the inter- Governmental Panel on Climate Change (IPCC) greenhouse gas (GHG) Inventory guidelines and related software: CO 2 = 𝑖,𝑗 𝐴𝐷 𝑖𝑗 × 𝐸𝐹 𝑖𝑗 Where CO2 is the emission, AD is the activity (e.g. fuel combustions) by sector and EF is the emission factor for the corresponding fuel and if possible for the sector, i and j being the sector and fuel type respectively. Once the calculations are done for each sector/fuel, they are added to get totals.
Recommendations The national data that are collected mainly by the respective subject area statistical unit, energy, transport and environment in this case, provides the data for the compilation of the SDG indicators. It is to be noted that the UNECA survey may not reflect the real data and sources probably due to the questionnaire being filled by someone not working in the required sector. To overcome the difficulties and challenges to collect the required indicators, there is need for capacity building and to harmonise the concepts used, as well as to use the national data sources. For more effective ways of dissemination so that the data produced by the country can also be reflected in the global database, the hamonisations will be essential, for instance by using the proposed methodological improvements. Beside this, the global database should consult the disseminated data, e.g. from the NSO or other local database or website.
That’s All Thanks You Mercie