Measuring value chains - Use of input-output tables
Measuring value chains Use of input-output tables Ali Yedan, Ph.D., Associate Statistician, Africa Centre for Statistics, United Nations Economic Commission for Africa The Gambias transport sector: Measuring its value chain and exploiting its potential 12-13 June 2019 Addis Ababa, Ethiopia 1 Context In development studies, the global value chain (GVC) describes the people and activities involved in the production of a good or service and its supply, distribution, and post-sales activities (also known as the supply chain) when activities must be coordinated across geographies. GVC is similar to Industry Level Value Chain but encompasses operations at the global level. Objective: Better assess the contribution of services to regional value chains Provide good indicators for Measuring value chains 3 Context
Two methodological approaches to the study of services in regional value chains: Qualitative approach, based on firm-level interviews as the basis for case studies, Quantitative approach using multi-region input output tables (MRIOs), based on the literature on trade in value added. The quantitative approach based on the literature on trade in value added, uses multi-region input output tables (MRIOs), uses algebraic formula and computation in software like R 4 Outlet 1. Literature on trade in value added 2. Input-Output table 3.
How to measure the DVA, GVC? 4. Outcomes 5. Application in the context of transport sectors 6. What is needed to get data/analysis 7. Quality of data 8. ECA contribution 1. Literature on trade in value added Shepherd, B. GVCs Methodology Paper, Jan 2019, Aslam, A., N. Novta, and F. Rodrigues-Bastos. 2017. Calculating Trade in Value Added. Working Paper WP/17/178, IMF. Johnson, R., and G. Noguera. 2012. Accounting for Intermediates: Production Sharing and Trade in Value Added. Journal of International Economics, 86(2): 224-236.
De Backer, K., and S. Miroudot. 2013. Mapping Global Value Chains. Trade Policy Paper No. 159, OECD. Jones, L., W. Powers, and R. Ubee. 2013. Making Global Value Chain Research More Accessible. Working Paper No. 2013-10A, US International Trade Commission. Low, P., and G. Pasadilla (eds). 2016. Services in Global Value Chains: Manufacturing-Related Services. Singapore: World Scientific. 2. Input-Output table 2. Input-Output table 2. Input-Output table Input-Output Table: Intermediate Use + Finale Use = Production Intermediate Use Country A Sector 1A Sector 2A Country B Sector 1B Sector 2B Final Demand Country A
Country B HouseholdsA HouseholdsB Gross Output Sector 1A Intermediate Intermediate Intermediate Intermediate Final use of Final use by B of Production of use by 2A of use of domestic domestic output use by 1B of use by 2B of domestic output exports from 1A 1A output exports from 1A exports from 1A from 1A from 1A Sector 2A Intermediate Intermediate Intermediate Intermediate Final use of Final use by B of Production of use by 1A of use of domestic use by 1B of
use by 2B of domestic output exports from 2A domestic output 2A output exports from 2A exports from 2A from 2A from 2A Sector 1B Intermediate Intermediate Intermediate Intermediate Final use of use of 2B of Final use by A of domestic output Production of use by 1A of use by 2A of use of domestic domestic output exports from 1B 1B exports from 1B exports from 1B output from 1B from 1B
Sector 2B Intermediate Intermediate Intermediate Intermediate Final use by A of Final use of use of 1B of use of use by 1A of use by 2A of domestic of domestic exports from 2B domestic output Production output 2B exports from 2B exports from 2B output from 2B from 2B Country A Country B Total Intermediate use by 1A Total Intermediate use by 2A Total Intermediate use by 1B
Total Intermediate Final use by A use by 2B Final use by B 2. Input-Output table Example: Consider 3 countries (G=3) and 4 sectors (N=4) in each country, so 12 sectors in all (GN = 12) as in the figure 2. Input-Output table Note: These numbers are just some example and not real numbers Agri Mining Kenya Transp finance Agri Mining Ethiopia Transp finance Agri Mining Nigeria Transp finance Agri 346 354
209 37 165 419 886 800 355 501 338 320 194 479 14 608 269 814 559 700 822 729 2. Input-Output table Two parts: Intermediate Use & Finale Use Many countries that interact Production, gross Exportations, gross Importations,
Values added, GVC participation Index, The Intermediate Use is square matrix Same country-sectors on row and column Intermediate Use of domestic output on diagonal parts Off diagonal elements represent exports of intermediates Final consumption from output of each sector 2. Input-Output table Difference between Supply-Use-Tables (SUTs) and Input-Output Tables In SUT, there are 2 tables: Supply Table (Production and Importation) and Use Table (Intermediate and Final Consumptions, and Exportation) In SUT, exportations and importations are aggregate, no need to know the origin while in Multi-Region Input Output (MRIO), it is needed to know the origin In MRIO, knowledge of the using of exportations and importations
Whether for intermediate or final uses, Using by which sector for Intermediate Use The Intermediate Use in SUT is not square matrix Products on row and industries on column National input-output tables is derived from harmonized national supply and use tables with international trade in goods and services statistics The SUTs are very useful to compile Input-Output table, but not enough. Information from foreign is necessary 3. How to measure the DVA, GVC? AX Y X 14 3. How to measure the DVA, GVC?
Starting from , we can perform some rearrangements, and solve for X: (no worry about compatibility of matrix size) as the value added coefficients matrix: E with gross exports by country-sector on the main diagonal, and zeros elsewhere 15 3. How to measure the DVA, GVC? For application, many softwares could be used. UNCTAD has developed a methodology on R G <- 3 # number of countries N <- 4 # number of sectors by country GN <- G * N # total number of sectors data1
value added content of production in each country shipped to each other country the knowledge sharing platform of the project, there is an 16 online course which will facilitate the learning of the quantitative tool. https//knowledge.uneca.org/stp/ 4. Outcomes Allow to know the requirements for an extra unit of output in each country-sector. If a sector in a country needs an extra unit of output: Determine the direct input requirements for each country-sector: C1: S1 coefficients C1: S2 C1: S3 C1: S4 C2: S1 or C2: S2matrix C2: S3 C2: S4 of C3: S1technical C3: S2 C3: S3 C3: S4 A input-output Country 1: S1 0.05 0.02 0.01 0.07 0.10 0.01 0.11 0.059 0.05 0.08 0.033 0.064 0 3 3 6 4 6 7 8 7
coefficients Country 1: S2 0.05 0.06 0.00 0.11 0.00 0.01 0.07 0.126 0.06 0.11 0.011 0.043 Country 1: S3 C1: S1 1.27 Determine Country 1: S1 Country 1: S2 Country 1: S3 2 0.26 6 0.27 9 1 0.04 2 C1: S2 7 0.11 9
1 1.27 6 0.34 6 4. Outcomes The Domestic Value Added (DVA) in exports are the value added in exports whose the outputs are produced by domestic industries The Foreign Value Added (FVA) in exports are the value added in exports whose the outputs are produced by foreign industries Known as VS in the technical literature. Known of backward participation in the policy literature The Indirect Domestic Value added (DVX) in exports, i.e., Value Added that is embodied in the exports of other countries, upstream contributions of DVA of other industries Known as VS1 in the technical literature.
Known as forward linkages in the policy literature. GVC Participation Index (VS+VS1)/Gross Exports is the best indicator which shows how the sector involved in RVCs/GVCs through both backward and forward linkages. 5. Application in the context of transport sectors Quantifying the value generated in the transport value chain makes it possible to identify which type of transport activities add more value, .. better understanding of these bilateral exchanges (the direct and indirect impacts of transport) identification of source markets which generate more value added in the domestic economy. how upstream domestic industries (backward linkages) contribute to transport exports Whether the increased participation in GVCs can be good for economic growth and social development. 5. Application in the context of transport sectors
Quantifying the value generated in the transport value chain makes it possible help to respond to key policy/statistics questions such as: How much value does transport add to economies? Does transport create additional trade? Do transport services have high or low domestic value added content? How does transport compare to the rest of the economy? What is the upstream impact of transport on other domestic industries? 5. Application in the context of transport sectors Transport sectors Includes: Transport Equipment:
1. Motor vehicles, trailers and semi-trailers; parts and accessories thereof 2. Bodies (coachwork) for motor vehicles; trailers and semi-trailers; parts and accessories thereof 3. Ships 4. Pleasure and sporting boats 5. Railway and tramway locomotives and rolling stock, and parts thereof 6. Aircraft and spacecraft, and parts thereof 7. Other transport equipment and parts thereof Passenger Transport Services: 1. Local transport and sightseeing transportation services of passengers
2. Long-distance transport services of passengers 5. Application in the context of transport sectors Transport sectors Includes: Freight transport services: 1. Land transport services of freight 2. Water transport services of freight 3. Air and space transport services of freight Rental services of transport vehicles with operators Supporting transport services: 1. Cargo handling services 2. Storage and warehousing services 3. Supporting services for railway transport 4. Supporting services for road transport 5. Supporting services for water transport 6. Supporting services for air or space transport 7. Other supporting transport services Postal and courier services 6. GVC outcomes GVC participation indices, 2011 Highest for high income,
Lowest for low income Lowest in South Asia, then Latin America Highest in Europe and Central Asia In MENA, the forward linkages are among the highest while the backward linkages are among the lowest 6. GVC outcomes Domestic and foreign value added content of gross exports, million USD, in in Thailands transport equipment industry in 1995 and 2011.
Source: OECD-WTO TiVA. 6. GVC outcomes Domestic and foreign value added content of gross exports, shares, in Thailands transport equipment industry in 1995 and 2011. Source: OECD-WTO TiVA. 6. GVC outcomes Domestic and foreign value added content of gross exports, thousand USD in Ethiopias textiles and apparel sector, 1996 and 2011. Source: Eora MRIO database 6. GVC outcomes Domestic and foreign value
added content of gross exports, shares, in Ethiopias textiles and apparel sector in 1996 and 2011. Source: Eora MRIO database 7. Quality of data Bases on some questions: 1.Is the data publicly available for stakeholders and users? In which format (Excel, Stata, Word, PDF, html, )? Need to register? Need password? 2.When was the most recent data produce? 3.How frequently is the data produced? (Quarterly, Annually, 5 years) 4.What methodology is used? Are international guidelines followed? Are International classification used (CPC, ISIC)? 5.Are data comparable year to year? Is the same methodology used each year? 6.Is there metadata? 7.Is data collected or estimated? 7. Quality of data Prerequisites of quality. Prerequisites of quality refer to all institutional and organizational conditions that have an impact on the quality of transport statistics. These
include: Relevance. The relevance of transport statistics reflects the degree to which transport statistics meet users needs. the legal basis for compilation of data; the adequacy of data sharing and coordination among data producing agencies; assurance of confidentiality; the adequacy of human, financial, and technical resources for implementation of transport statistics programmes and implementation of measures to ensure the cost-effective; and quality awareness; Absence of significant gaps between the key user needs and compiled transport statistics in terms of variables, coverage and details is an indicator of relevance; Credibility. The credibility of transport statistics refers to the confidence that users place in the data based on the image of the agency responsible for production and dissemination of the data. Indicators of credibility should provide evidence that production of transport statistics is not manipulated and that their release is not timed in response to political pressure; 7. Quality of data
Accuracy. The accuracy of transport statistics is the degree to which the data correctly estimate or describe the quantities or characteristics they are designed to measure. In general, accuracy can be characterized in terms of errors in statistical estimates and is traditionally decomposed into bias (systematic error) and variance (random error) components. Validity refers to whether a data collection tool or concept truly captures what it is intended to measure. In other words, a variable or measure is valid if the values estimated are close to the true values Reliability of data refers to whether the instrument or source of the data would produce consistent results under identical circumstances regardless of who uses it. Precision refers to an aspect of the reporting of data, or of statistics or indices derived from original data and is not, in itself, an intrinsic quality of the original data. 7. Quality of data Timeliness. The timeliness of transport statistics refers to the delay between the end of the reference period to which the data pertain and the date on which the data are released and available to the public.
This dimension usually involves a trade-off against accuracy. The timeliness of information also influences its relevance, as accurate data that are not timely are of limited usefulness; Methodological soundness. The methodological soundness of a data source refers to the application of international standards, guidelines and good practices in production of transport statistics. Metadata provided along with transport statistics play a crucial role for assessing the methodological soundness of data The methodological soundness is closely related to the interpretability of data. 7. Quality of data Coherence. Coherence reflects the degree to which the data are logically connected and mutually consistent, that is, they can be successfully brought together with other statistical information within a broad analytical framework and over time. The use of standard concepts, classifications and target populations promotes coherence, as does the use of common methodology across surveys when relevant. Coherence has four important subdimensions: (i) Coherence within a data set implies that the elementary data items are
based on compatible concepts, definitions and classifications and can be meaningfully combined; (ii) Coherence across data sets implies that the data are based on common concepts, definitions and classifications, or that any differences are explained and can be allowed for; (iii) Coherence over time implies that the data are based on common concepts, definitions and methodology over time, or that any differences are explained and can be allowed for; and (iv) Coherence across countries implies that the data are based on common concepts, definitions and methodology over countries, or that any differences are explained and can be allowed for; 7. Quality of data Accessibility. The accessibility of transport statistics refers to the ease with which they can be obtained from those agencies active in transport statistics. This includes the ease with which the existence of information can be ascertained, as well as the suitability of the form or the media of dissemination through which the information can be accessed. Accessibility requires the development of an advance release calendar
so the users will be informed well in advance about when the data will become available, and where and how to access them. The availability of metadata significantly improves accessibility and is, together with the existence of user support services, an indicator of this quality dimension. ECA contribution Use of input-output tables in countries with similar structure In Africa, only 29 countries out of 54 African countries have at least a Supply Use Table, 25 African countries have never compiled Supply Use Table, UNECA is estimating Supply Use Tables for these 25 African countries, Using technical coefficients (shares of outputs used as intermediate use) to build Intermediate consumption for each industry Countries with similar structure of industrial development
It can be one country or a group of countries With the same manner, it is possible to estimate input-out tables, but: These The estimations are inevitably biased, best compilations are from surveys ECA contribution ECA capacity building Three phases: E-trainings to form a large participants with little costs Seminar face-to-face Workshops and follow-up activities Official requests of the country Fill questionnaires of data availability
Conclusion Steps for the quantitative approach: Building the Input-Output Table, Using algebraic models or application in software, Know the outcomes, Quality of data Thank You
Page 2 of this presentation contains an example slide and page 3 contains a blank template. Adaptive Self-Correcting T/R Module PI: Wendy Edelstein / JPL Co-Is/Partners: Constantine Andricos, Gregory Sadowy, JPL Develop a practical and low cost adaptive L-band T/R...
Understanding verb tense What are the verb tenses? Present and present perfect ... By haytham kilani What are the verb tenses? Verbs do a lot of work in sentences. They show actions and states of being. They even take different...
• EOHSI/Rutgers Collaborators - Clifford Weisel - Tina Fan - Rob Laumbach - Charles Weschler - Leonard Bielory - Alan Robock - and many others…. • NYSDEC Collaborators - Christian Hogrefe - Gopal Sistla - Eric Zalewsky 26 * *
resources that can be used to increase reliability - A small group of cooperating peers can do a better job than the Internet by passing data between each other - RON enables this functionality Hari Balakrishnan Hari Balakrishnan Networks and...
Competencies and all MyQuest lessons are due by June 30th! These must be completed during downtime, cannot/will not be paid to finish these outside of work hours. Dr. Cawley's Key Messages. Emergency Management Update. ... MUSC User Company:
& Murtagh lwn Castello. > Ponnukon lwn Jebaratnam (m/s 119) - pembelian tanah yg dibiayi wang persendirian utk tujuan pembangunan tanah diputuskan sbg bkn harta perkongsian. c. Jika sesuatu harta diperolehi untuk firma, tidak kira samada ianya diperolehi melalui pembelian...
Habits of a Productive Mathematical Thinker. Standard of Mathematical Practice #1. Make sense of problems and persevere in solving them. Standard of Mathematical Practice #6. Attend to Precision. Reasoning and Explaining. Modeling Using Tools. Seeing Structure and Generalizing. Standard of...