The Food and Agriculture Organization of the United Nations (FAO) today called for an acceleration in improvements to agriclturural data gathering and monitoring to ensure the targets set out in the Sustainable Development Goals are accurately reported in the world’s biggest region Asia and the Pacific.
As the clock ticks towards 2030, the year when the world’s 17 Sustainable Development Goals (SDGs)http://www.fao.org/sustainable-development-goals/en/ must be achieved, countries are working to improve their systems of statistic-gathering and analyses for better planning in crop, livestock, fisheries and forestry sectors.
However, the capacity to adequately monitor and analyse agricultural statistics varies dramatically country-by-country, and no where in the world is that variance more prevalant than in the Asia-Pacific region.
Pietro Gennari, Chief Statistician of FAO, noted the significant data gaps in Asia-Pacific in monitoring the SDGs, and the slow progress towards achieving its goals. Slow country commitment to measuring the SDGs, and the poor performance towards achieving the SDGs, are closely connected. We are witnessing an inversion of the familiar axiom whereby what gets measured gets done. We are not measuring the SDG indicators, and this is one of the crucial reasons why we are not on track to achieving the SDG targets.
FAO today opened the 28th Session of the Asia and Pacific Commission on Agricultural Statistics (APCAS)http://www.fao.org/economic/ess/ess-events/ess-apcas, in Bali, Indonesia. The Commission Session runs from 10-14 February. It is hosted by the Government of Indonesia with more than 100 participants from some 30 countries and 10 international and regional organizations attending.
Focusing on the specific needs of food and agricultural statistics of Asia-Pacific, this biennial meeting of agricultural statisticians and experts reviews and support the region’s preparedness to produce adequate statistics to monitor progress towards the 2030 SDG targets.
Food insecurity plays an important role as a determinant of many different forms of hunger and malnutrition. The majority of the world’s hungry, and children affected by stunting, live in Asia. Hunger has increased in many countries where the economy has slowed down or contracted, mostly in middle-income countries. Furthermore, economic shocks are contributing to prolonging and worsening the severity of food crises caused primarily by conflict and climate shocks. Even in upper-middle and high-income countries malnutrition is an issue, with obesity evident in school-age children, adolescents, and adults.
Collaboration among internal institutions within the government such as Statistics Indonesia, Ministry of Agriculture, relevant ministries/agencies with the FAO of the United Nations, is needed to produce high quality agricultural statistics that are accurate, timely and relevant to provide SDG’s indicators. said Chief Statistician of Statistics Indonesia, Dr. Suhariyanto, in his key note speech. Sharing of knowledge and good practices in the regional conference, such as APCAS, is a way to improve and accelerate production of agricultural statistics in Asia Pacific. Adding to that, the discussion at the forum will be effective to monitor the SDGs achievements in the region.
Agenda 2030 identifies 17 goals, 169 targets and some 232 indicators to monitor progress. This is a huge and daunting task for national statisticians, and the clock is ticking down to 2030. With only a decade to go, and nearly half a billion hungry people still struggling to survive in our region, we must strengthen partnerships among governments, international organizations and the private sector to meet these data needs, said Stephen Rudgard, FAO Representative to Indonesia. FAO stands ready to support national efforts through its technical assistance programmes.
The APCAS meeting provides a platform for Asia Pacific countries to directly engage in drawing attention to their unique challenges in development of agricultural statistics such as geographical remoteness, changing cropping patterns and livestock rearing due to climate change and transboundary diseases, and limited statistical infrastructure and resources.