A. Framework and compilation

Transcription

1 Framework for data integration in support of SNA compilation and modeling: Exercise for use of SNA in early estimates and projections in Central America By Jan W. van Tongeren, IVO. April A. Framework and compilation... 1 B. Transactor classification... 3 C. Transaction classification... 5 D. Compilation of integrated accounts for selected sectors... 7 E. Statistical discrepancies and other data relations... 8 F. Use and adaptation of framework and classifications... 9 A. Framework and compilation Table 1 presents the entire framework and table 1(s) is a synoptic version of it, which can be much easier printed and reviewed. When reference is made below to table 1, the reader may consult either the synoptic presentation of table 1(s) or the full presentation of table 1. The integrated sector sector/industry/product classification of transactor units in the column of table 1 is reproduced separately in table 2. The classification of transactions, as represented in the rows of table 1, is reproduced in table 3. Table 4 includes a set of tables for selected key and other sectors, including banks, insurance, GOV and Rest of the World (ROW), which are important sectors in the economy of most countries, and have special data features that require adaptation to SNA concepts. The tables of the framework are for compilation purposes only. They are not conceptual tables, as suggested in the SNA and also not tables for use in data analysis. The tables are exclusively meant for compilation purposes. Tow alternative uses are envisaged. One refers to a future use, when national accounts compilers and modelers will start a joint compilation for early estimates. At that time micro data aggregated to the macro categories of the framework will be used. The other purpose is the immediate one of the present exercise, in which available data for a past year are incorporated in the framework. The available data are mostly macro data, which were already aggregated for SNA compilation purposes in the past and will now be used again in the present exercise. The latter use is only an approximate use of the framework; the description below therefore mainly refers to the use in the future of aggregated micro data. The columns of the table accommodate data relating to aggregations of micro units, which are classified at the same time by ISIC categories, sectors and also by the main products they produce. The integration of the three classification criteria involves a number of assumptions, which are explained in section B below. As sector and industry classifications are integrated, all SNA transaction categories are to be compiled for each transactor column. This includes the transactions of the SNA production and generation of income accounts of the SUT and CCIS, which are traditionally classified by ISIC categories, as well as the transaction categories that are

2 only compiled for sectors in the IEA. Thus all transaction categories are to be compiled for each micro unit and aggregated to the macro categories presented in the columns of table 1. For a more detailed description of the transaction categories, the reader is referred to section C below. The data to be included in the framework for each country should satisfy certain consistency conditions, which include among others, supply and use and revenue and expenditure balances that should be satisfied, as well as predetermined values of binary ratios or coefficients defined between the variables of the framework. The consistency requirements are explained in section E below. A Bayesian estimation approach will be used to implement the consistency requirements and arrive at an integrated set of estimates which is also briefly discussed in section E. In addition to specification of transactor and transaction categories, a few additional features of the framework should be highlighted. Margins of product taxes less subsidies and trade margins are presented in the table rows as global adjustments. These adjustments are needed to convert the data on output and imports in basic prices in each column of the table to market prices, so that they can be confronted with uses which are also valued in market prices. See also section C on the transaction classification. Separate rows are included in the table for price indices. A distinction is made between price indices of supply and use. The price indices of use reflect the tax/subsidy and trade margins; the price indices of supply do not reflect those margins. The price index information is reflected in the relation between current and constant price estimates presented in the first columns of the table. For more information on the derivation of price indices and constant price estimates, see section C below on the transaction classification. There are two columns for the total economy, i.e. one in current and another one in constant prices. Those columns include major aggregates, such as GDP, saving and net lending. The values in the constant price column are derived from those in the current price column with help of price indices and vice versa. Further information on these transaction concepts is provided in section C. The last columns of the table refer to products that are only imported. They still need to be specified, as part of the classification exercise. See also section B on the transactor classification, and section F on the adaptation of the framework. In line with the Bayesian estimation approach a few terminological principles are adhered to in the present paper. The cells in the framework referring to SNA concepts will be called variables. The term basic data will be used for the data included in the framework prior to integration, and the final values after integration are estimates. The balances will be referred to as identities defined between the variables of the framework. The values

3 that ratios between final estimates should adhere to are the values of so-called priors or indicator ratios. The framework and the tables as presented are not final. In particular the n umber of classification categories may be reduced, mainly by eliminating transactor categories that are not relevant in the country. They need to be adapted in the course of the exercise, as explained in section F. B. Transactor classification There are two principal criteria used in the development of the transactor classification, as presented in table 2. Firstly, the number of categories should be limited, as the data compilation will be carried out at a point in time (early estimates and projections) when few data are available and quick estimates need to be made. On the other hand, more detail is introduced in order to facilitate compilation and also analysis of the data. One way of reducing the number of variables is by introducing an integrated industry, sector and product classification, which is reflected in the multiple headings of each row of the classification scheme in table 2. Thus, each transactor grouping listed in the table has an ISIC dimension (ISIC name and code in cols. 1,2,4), a sector dimension (HH, NFC, FC, GOV and NPI in col. 7), a CPC dimension (recorded only occasionally in col. 3, if significantly different from the ISIC dimension), and also indications for each product whether it is produced locally or imported (P or M in col. 5) and used in HH consumption, intermediate consumption and capital formation (C, I or K corresponding to the CIK/BEC 1 dimension in column 6) The integration of the various dimensions of the transactor classification is accomplished on the basis of a number of assumptions, which are only partly satisfied in the table: Each industry has a main dominant product, which (CPC row) corresponds in each column to the industry in the ISIC rows Each industry preferably belongs to one sector only Each product preferably is either only produced in the country or only imported Each product preferably has one destination, i.e. intermediate consumption, HH final consumption or gross fixed capital formation. As the assumption of precise correspondence between the different dimensions, however, would not be compatible with actual situations, it is only partly applied in the classification that is presented in the table. Thus, many categories have multiple sector dimensions (e.g. NFC/HH), multiple origins (PM) and multiple CIK/BEC destinations (CI). The multiple product dimension of each ISIC category is not used in the table. This means that secondary products are assumed not to exist in any of ISIC categories listed. It 1 UN Classification on uses of imported products by main SNA categories of intermediate and final uses is published in United Nations, Classification by Broad Economic Categories (defined in terms of SITC, Rev. 3, Statistical Papers, Series M53Rev3, Presently work is carried out at UNSD to broaden this classification from goods (imported) to all goods and also services.

4 is expected, however, that the impact of this assumption is made less significant, due to aggregation of ISIC categories and corresponding products. The number of integrated classification categories in the rows of table 2 is tentatively 57. It will be most probably reduced to a much lower number of categories, when in the course of the exercise, the classification is adapted to available data and economic reality of each country (see section F). The selection of the integrated transactor categories is based on the following criteria: All two digit-isic categories are explicitly represented, or can be derived by aggregation from the categories distinguished in the table. Within manufacturing a distinction is made between ISIC categories that involve processing of primary products of agriculture, fishing, forestry and mining. This is done partly for (i) analytical purposes in order to determine the extent to which countries process their primary products in the county and thus generate additional value added and (ii) also for compilation purpose, as output of manufactured products based on primary products can measured or checked with help of data on output of primary products. Examples are manufacturing activities of processing of agricultural products from mono-cultures including rice and grain milling, coffee, tea and cacao preparation, sugar refining, etc. (ISIC 15-16), processing and preserving of meat and meat products (1511), processing and preserving of fish and fish products (1512), manufacturing of coke, refined petroleum products and nuclear fuel (23), manufacturing of basic precious and non-ferrous metals, including diamond cutting, gold refining, etc. (272), and also sawmilling and planing of wood (201). Another distinction is made, if possible, between transactor categories that correspond to different sectors. For instance in agriculture a distinction may be made between production of sugar and some other staples that are in some countries mainly cultivated in large NFC type agricultural holdings, and other agricultural products that may be mainly cultivated by small (HH) farmers. Similarly in mining, copper, bauxite and similar mineral exploitation and gold, diamond and similar mining operations, that are carried out at a small scale by HH type establishments or at large scale by NFC s. In fishing a distinction is made between traditional and modern fishing, as the former activities are often carried out by HH type enterprises. Also in manufacturing and services such ISIC distinctions are made in order to separate small (HH) from large (mainly FC) production operations. Informal sector activities are identified separately, where possible. This is done for at least two reasons. One is that those categories always correspond to the HH sector, while formal sector activities may correspond exclusively to the NFC sector or sometimes to a NFC/HH sector combination. Another reason is that data on those activities are generally scarce and estimates often can only be based on rough estimates. Four types of informal activities are identified in the table: i.e. forestry: wood collection (ISIC 02), Handicraft and other informal manufacturing (ISIC & ISIC 20 excluding 201), electricity generation managed separately from the main network (40), water carrying (41), street vendors and other informal trade (525), and HH employees (95).

5 A distinction is further made, if possible, between product categories that are only produced domestically and those that are only imported, and also between product categories that are only used for C, I or K in the CIK/BEC classification. Examples of products that are typically produced domestically are construction, most of electricity production and water distribution and treatment services, and also most of the personal services. On the other hand, in many developing countries, machinery and equipment and similar products are mainly imported. When combined categories (e.g. in sectors NFC/HH, or in product supply and destination (PM and CI), cannot be avoided, assumptions will need to be made in the processing of the categories, in order to arrive at separation of data between sectors and product origins and destinations. These assumptions may be based on structural coefficients of benchmark compilations or studies. C. Transaction classification The transaction classification presented in the rows of table 1 are reproduced in detail in table 3. There are the following groups of transactions represented in the table: Transactions of the SNA production and generation of income accounts, including output, intermediate consumption, value added and its components, and also data on employment and gross fixed capital formation 2. Imports Global adjustments for trade margins and product taxes less subsidies, including import duties Price indices of supply and use Use categories, including intermediate consumption, HH final consumption, GOV and NPI final consumption, gross fixed capital formation, and exports Income and outlay categories, including among others receipt categories such as compensation of employees received by HH s and product and production taxes received by GOV. Also included are receipts and payments of property income (interest, dividends, re-invested earnings), income taxes, social and other current transfers, capital transfers, and also outlays on gross fixed capital formation. Also included here are balancing items including disposable income, saving and net lending/borrowing. In the second column of the table are indicated the classifications by which the transaction categories are classified. Thus, transactions of the production accounts (including output, intermediate consumption, value added and compensation of employees and other value added components, and also gross fixed capital formation use and employment) are classified by industries (ISIC) and sectors. Output is, however, classified in addition by products (CPC). Imports, global adjustments and also all 2 Changes in inventories are assumed to be equal to zero in the present scheme. Measurement of (+) and (-) deviations from the zero average would be too unreliable to be taken into account

6 intermediate and final uses are classified by product categories (CPC). Transactions of the IEA are classified by industries/sectors; the latter include compensation of employees received, product taxes less subsidies received, and all receipts and payments of property income, current and capital transfers. Only data should be included that can be based on survey or administrative sources of micro (establishment) production units (aggregated to the macro transactor categories of table 2) and related to the transactions of the production and generation of income account, and if possible data on income and outlay categories. Data on imports and exports, import duties and other product taxes less subsidies (included as global adjustments), price indices and HH final consumption by use should be compiled on the basis of other data sources. Thus imports and exports are to be derived from a re-classification of foreign trade statistics to the product (CPC) categories of the framework. HH final consumption by use may be based on a reclassification of HH final consumption available from HH surveys, if available. Reclassification of foreign trade statistics on imports should also be used to estimate the import components of construction (materials) inputs and possibly inputs of other selected production activities for which such information can be derived, and also the import components of HH final consumption and gross fixed capital formation. The domestic output components of the latter categories will be based on the product and CIK/BEC dimensions of each industry/sector as indicated. Data on BANKS, INSURANCE, GOV and ROW, and possibly KEY sectors should be based on the integrated data compilation for these sectors, as described in the next section D. Dominant industries in the local economy that may be treated as Key sectors are generally production activities that are carried out by large enterprises with integrated financial statements (NFC s). The may include the production of coffee, bananas, sugar and other large scale agricultural production activities, oil, diamonds, gold and other mining, wood logging, and also major manufacturing and service activities. Price index information is presented separately in two rows referring to price indices of supply and use (i.e. price indices of output, imports and exports, intermediate consumption, gross fixed capital formation, HH final consumption) for each of the transactor categories in the table. In the present framework the price indices may be limited to one price index of use, i.e. the CPI and one price index of supply, i.e. producers price indices that are traditionally used in SNA compilation. Estimates of price indices of imports may be based on assumed relations with the producers price indices, and price indices of uses other than HH final consumption (exports destination, gross fixed capital formation destination and intermediate consumption destination) may be based initially and tentatively on the CPI and thereafter corrected at the time of the data integration (see section E). This is done through supply use identities that will be used not only for supply and use in current prices, but also in constant prices. The detailed price index information in the rows is used to derive composite price indices for major aggregates such as output, intermediate consumption, value added and also HH

7 final consumption, gross fixed capital formation and exports and imports, which are presented in a second column of table 1, after the column of current price estimates. When deriving the price indices of major aggregates, the current price values presented in the row corresponding to each major aggregate are used as weights. 3 D. Compilation of integrated accounts for selected sectors The micro data referred to in the previous section are those of production units, as classified in table 2. Micro data information for these units generally are compiled through production type surveys and censuses. These sources may include some of the information on income and outlay transaction categories. For many of the aggregated production units, however, this income and outlay information may be missing, and needs to be imputed with help of assumptions. To make sure that these assumptions do not dominate the compilation of the attached framework, integrated compilation tables are created for selected sectors, for which the income and outlay data are very important and may be available through financial statements and other administrative data sources. These are the GOV, BANK and INSURANCE sectors, and the ROW based on BOP data. Also integrated sector accounts are included for selected KEY sectors that are very important in terms of finance and investments related flows, such as the mining and subsequent processing in manufacturing (i.e. refining) of oil and other minerals in some countries, or agricultural (e.g. cacao, coffee) and forestry activities in other countries that are carried out on a large scale. Once the data are compiled for the special sector accounts, they can be incorporated into the relevant columns of table 1. Each sector, together with the transaction categories that are relevant for this sector, can be accessed through the macro-buttons for the KEY, BANK, INSURANCE and GOV sectors and also for the ROW. An additional button is available to present all sectors and all transaction categories, and another button generates the reduced transaction classification as included in table 1 and also available through table 3. Table 4 includes the sector accounts for these selected sectors. The transaction classification is the same as in table 3, but is more limited, as it does not cover any of the transaction categories of imports, prices, and uses, that need to be measured indirectly through the other data sources mentioned in the previous section. Also not in all instances, output data are included, as output is an SNA concept, which can be derived, but is not directly available as part of the basic data of the selected sectors. For instance, output in 3 When using the product flows in each year as weights, effectively a Paasche price index is derived. This and other elements of the price index derivation may need to be reviewed, and possibly adjusted, in order to achieve close compatibility with the price factors used in the present projection model for Central America. The use of this price index methodology is illustrated in a demo, which was earlier distributed to the participants of the Central American Workshop.

8 the banking sector is derived on the basis of the difference between interest received and paid, while output in the insurance sector is defined as premiums minus claims minus additions to insurance technical reserves (savings of the premium paying sector) plus interests on those reserves. None of these derived SNA concepts are recognized in the financial statements of banks and insurance, and therefore, for those sectors only the components that are needed to derive output i.e. actual fees paid to banks and insurance schemes, interest received and paid by banks, and premiums received and claims paid by insurance companies, and also changes in the technical reserves and interest received thereon are recorded. With help of these components that are actually recorded in the books of insurance companies, pension funds and banks, output estimates can be derived with help of the SNA definitions. E. Statistical discrepancies and other data relations Table 1 should be completed with help of the data sources indicated in the previous sections. However, such compilation may not result in a data set that satisfies SNA consistency criteria. Such consistency will be imposed with help of a Bayesian integration approach, which takes into account three types of inputs: Identities (balances or statistical discrepancies), defined between variables of the framework Priors or binary ratio relations defined between variables of the framework, and Reliabilities of the basic data and priors These three Bayesian inputs of the framework have not been defined yet. However some indications may be given. The main identities are the balances between supply (output and imports) and use categories presented in the column of table 1. Thus output plus imports in each column should be equal to the sum of intermediate consumption destination, HH final consumption destination, GOV and NPI final consumption destination, gross fixed capital formation destination, and exports destination. The supply-use identities should hold both in current and also in constant prices. Other identities may be defined between revenues and outlays in the lower income and outlay segment of table 1. For instance, the receipts and payments of compensation of employees, product taxes less subsidies, income taxes, property income and current and capital transfers should be equal. Also identities are defined between the output of trade (column Wholesale and retail trade, sale and maintenance of motor vehicles in table 1) and the total of trade margins, or between the total of product taxes less subsidies, paid on output and imports of products and the total receipts by the GOV sector. Similarly, identities should be defined between HH final consumption by use (based on HH budget surveys) and by destination, based on the C- code (of the CIK/BEC classification) of products identified in each column of table 1. Binary ratios may be defined between output and employment, or between output and intermediate consumption or value added in each of the columns of table 1. The ratio values may be based on the values of the data included in the table or on external

9 information, for instance benchmark structures. If they are based on the values of the data in the tables, they are used as checks in the Bayesian estimation approach, which ensures that the ultimate estimates would not alter too much the structural relations embedded in the basic data. If externally determined ratio values are used, and no data are available for all variables, the ratio values will be used to estimate the value of the missing items. In addition to these so-called i-o coefficients in table 1, there are many other ratios (priors) that may be used as checks or as means of imputations for missing variables. They may include the ratio between imports and output in total supply of each product, the share of exports as percent of output, the trade and tax margin ratios defined for each product, or the share of compensation of employees in total value added of each column in table 1. Also ratios may be included for shares of compensation of employees, mixed income, social and other current transfers in HH disposable income. Furthermore ratios may be defined for the finance share of NFC saving in total investments of Key and other NFC sectors. Finally may be included as priors the ratios between gross premiums and claims of insurance schemes and pension funds, or between interest received and paid by banks, which are used respectively to estimate the imputed insurance and bank service charges. The reliabilities of the basic data and priors may be based on common sense assessments of basic data sources, and must be defined in a relative manner. For instance, foreign trade data on merchandise (goods) may be considered more reliable than BOP data on services, or than production data from economic surveys. Furthermore, data of all or selected sectors obtained through economic surveys may be considered more reliable than data from HH budget surveys. Similarly CPI price indices may be more reliable than producers price indices. Employment data based on employment or HH budget survey may be considered to be more reliable than employment data from economic surveys. Also ratio values may be given different reliabilities. Thus i-o ratios based on benchmark information may generally be more reliable than, say, the ratio between imports and output for each product, or between exports and output of each products. The latter ratios may easily changes over time, when prices develop differently between foreign trade and domestic output. Also, IEA ratios of income shares in HH sector disposable income or finance shares of NFC saving in NFC investments, may be less reliable than the i-o ratios. The i-o ratios, which reflect technical relations (coefficients), which are generally more stable than IEA shares that are more institutionally based and can thus change easily over time. F. Use and adaptation of framework and classifications As mentioned earlier, all tables are still tentative, and this applies in particular to the classifications used therein. Use of the framework may need to be adapted to data availability and data structures relevant in each country. The tables will also evolve, depending on the extent to which model and SNA variables will be brought closer together in scope and detail.

10 It is envisaged that the following adaptations of the framework may be considered in the course of the exercise: Selected product and industry categories may not be relevant in each country. For instance, if there are no oil or mineral resources in the country, this industry/sector detail in table 2 may be omitted. It is expected that this adaptation of the classifications would considerably reduce the number of categories represented as columns in table 1. Further analysis of classifications for each country may result in the following refinements o Industry/sector assignment in column 7 of table 2 may be improved o CIK/BEC assignment of products in column 6 may be improved o PM assignment of products (column 5) may be refined, resulting, if possible in more P assignments products o Products that are only imported (M) may be identified Price information may be incorporated more extensively in the framework, bringing the monetary/fiscal/financial model closer to the SNA scope and detail Transaction categories identified in the special sector compilations may be reduced, resulting in a simpler presentation of the sector accounts