PHOTO: Manop Boonpeng/Shutterstock.com
particular. These limitations translate into a significant obstacle for implementing evidence-informed policies for SDG 9. Reliable and timely industrial statistics could provide the information base required to guide policy programs, monitor their effectiveness and design corrective measures. This need was further highlighted during the recent COVID-19 crisis. Even if some data on the different areas of SDG 9 are available, in many cases they are only available after a long period and without enough disaggregation or detail (i.e. they are not sufficiently timely or granular). For example, many countries do not conduct regular establishment surveys. The available information comes from economic censuses, which are conducted once in every 5 or 10 years, and this does not allow a regular tracking of progress over time. The data are also released with a significant time lag. Conducting regular establishment surveys requires a well-maintained business register. Access to administrative data, one of the main sources for updating business registries, is hampered by data privacy concerns and lack of legal or logistical frameworks that would facilitate data flows between government entities. Moreover, many LDCs show a high level of informality and this is a big challenge for the complete tracking of economic activity. OFQ : Are there any other options for countries with limited data collection capacity? FCB: In the same vein, the use of alternative data sources, including administrative data, citizen-generated data and big data, remain untapped
Short-term statistics, such as a monthly or quarterly index of industrial production (IIP), allow monitoring trends and sectoral performance in a timely manner, especially after sudden shocks (such as during the COVID-19 pandemic). However, many low-income economies do not publish short-term indicators. For example, out of the 46 LDCs, only 13 publish a quarterly IIP on a regular basis and only five produce a monthly IIP. OFQ : Aren’t there universal data standards that everyone adheres to? FCB: The adoption of the most recent international statistical standards and classifications, which allow international comparability, remains problematic. For example, while the current standard for classifying economic activities is the International Standard Industrial Classification (ISIC) Revision 4 some countries, particularly low-income countries, still report in ISIC Revision 3. The World Bank’s Statistical Performance Indicators show that LDCs reached an average score of 49.0 in 2019 (on a scale from 0 to 100), compared to a score of 60.8 in other low- and middle-income economies. This is further evidence of the limited capacity to produce, access and use statistical information in LDCs. OFQ : Finally, what’s the biggest obstacle for knowing where we stand on the SDGs? FCB: The biggest obstacle for improving the availability of official data for tracking SDG progress is financing. National statistical offices are critically underfunded, especially in low-income economies, and they cannot respond to the increasing demand for data and statistics.
Industrial policy remains essential to support economic activity, increase productivity and enhance resilience to shocks.
Fernando Cantu Bazaldua, UNIDO, Industrial Statistics and SDG 9 Reporting Unit Chief Statistician
in many low-income economies. Data disaggregation [i.e. separated into component parts] is limited in many cases, especially in LDCs. Even if a survey or census is conducted, detailed statistics by gender or size of enterprise are not available. It makes it thus challenging to design and monitor policies to track progress on SDG 9.
34
Powered by FlippingBook