New needs and training modalities for the sustainable transfer of know-how on food and agriculture statistics in the COVID-19 era1

Abstract

The Sustainable Development Goals (SDGs) Global Indicator Framework (GIF) has multiplied training needs due to the large number of new indicators to be monitored by countries, whereas COVID-19-related social distancing restrictions have provided an unexpected springboard for the proliferation of cutting-edge virtual training tools and modalities. This has exposed a panoply of new data-related skills needed by contemporary statisticians, and therefore the types of training that could be most appropriate for acquiring these skills. This paper analyses the changing context and nature of training, with particular reference to the experience of FAO as a custodian agency for a large share of SDG indicators. The combination of different learning modalities, appropriately blended into a coherent learning programme, is shown to have the greatest impact, with one modality reinforcing the strengths and dampening the limitations of another.

Statistical challenges for achieving Sustainable Development Goals: Some reflections on Indicator 14.7.1

“…That means, while collecting data for SDG Indicator 14.7.1 is challenging, especially for developing economies whose national statistical capacities are relatively weaker, most countries do not submit requests for improving statistical capacity to collect data for this indicator. As shown in the previous section, the custodian agency (FAO) only offers technical assistance to countries upon request (Gennari et al, 2021). This suggests that not all countries that submitted requests for capacity development to collect data for SDG Indicator 14.7.1 have actually obtained the assistance as needed.…”

“…The most recent refinements of the SDG indicators show that near 40% or 91 of the 231 indicators are Tier 2 indicators, which means data for these indicators are not regularly produced even though these indicators are conceptually and methodologically clear (IEAG‐SDGs, 2022). Gennari et al (2021) mentioned that around two fifths of SDG indicators were initially classified as Tier 3, which means the concepts, methodologies and standards were not clear yet. As for SDG Indicators 17.18.2 and 17.18.3, up to 2019, only 81 of 249 countries and territories in the SDG Global Database have national statistical legislations as well as fully funded statistical plans under implementation (UN Department of Economic and Social Affairs, 2022).…”

“…For example, in the context of travel bans and border closures (e.g., Masood et al, 2022), statistical assistance for the Global South (such as capacity building programmes) from developed countries and international organizations were disrupted. It severely affected traditional in‐person‐based data collection approaches (such as surveys and censuses) for achieving the SDGs (Gennari et al, 2021). In comparison with developed countries, the Global South has fewer opportunities to use modern techniques and remote data collection approaches as substitutes due to the weaker infrastructure development, lower education level and less access to digital technologies (e.g., Bennett et al, 2022; Liu, 2020).…”

Role of international, regional and country organizations in adapting to statistical standards and regional differences: The case of food and agriculture statistics

“…With almost 200 countries in the world, limited resources at their disposal (see Section 3.4 above) and the absenceuntil very recently -of global SDG data funding instruments [18], custodian agencies have hitherto had the unenviable task of constantly trying to "do more with less", coming up with a number of innovative solutions to solve this conundrum. These include innovative training modalities [19], system-wide Plans for strengthening synergies among international organizations' efforts [20], and the UN Secretary General's Data Strategy [21] suggesting useful steps that international agencies can take to ensure a more effective, integrated governance structure of data and statistics that is more responsive to emerging needs and geared toward unlocking the full potential of new/alternative data sources, Artificial Intelligence capabilities and other cutting-edge technologies. This is not to say that there isn't still ample scope for custodian agencies to enhance their support to countries, particularly by better coordinating among themselves in order to leverage synergies and reduce duplications.…”

Promoting Sustainable Agricultural Waste Management and Industrial Symbiosis through an Innovative Web Platform

“…Moreover, the Food and Agriculture Organization of the United Nation, provides free and unrestricted access to 22 databases (e.g. FAM, FAOSTAT, AGRIS, AGROS) containing statistical data on food, agriculture, and sustainable management of natural resources [20][21][22]. However, despite the fact the agriculture is the major pillar on the national economy, no systematic effort is observed to provide the required information, especially as far as farmers are concerned, in an everchanging era [23].…”