Using Administrative Data in the Production of Business Statistics - Member States experiences

Transcription

1 Using Administrative Data in the Production of Business Statistics - Member States experiences Rome, 18 th and 19 th March 2010 The use of national and international administrative data for the compilation of FATS statistics Mr. S. Menghinello, Ms. E. Trinca, Ms. E. Bilotta, Ms. S. Palmieri (ISTAT, Italy). 1. Introduction This paper focuses on the use of administrative data in a new statistical domain: Statistics on the Structure and Activities of Foreign Affiliates (FATS). The motivation is twofold. First, the compilation of FATS statistics represents a relevant additional burden for businesses. Second, the production of FATS statistics according to high data quality and consistency standards induces to explore alternative sources of information with respect to direct reporting. Sine the definition of the variables requested by the FATS Regulation, both for Inward and Outward FATS target populations, is fully in line with the Structural Business Statistics Regulation, company balance sheets are the primary source of administrative data. ISTAT has a consolidated experience in the use of balance sheets data in the framework of SBS statistics. As a result, methodological approach and best practice can be sourced from that. The use of administrative data in the framework of FATS statistics presents some challenging methodological and data source issues linked to the peculiar characteristics of the two target business populations considered by the FATS Regulation. For the population of businesses resident in the compiling country (Inward FATS), balance sheet data available from national and local authorities, and are standardised and fully integrated with the Italian Business Register. The availability of balance sheet data for a population of non resident business (Outward FATS) calls for an innovative use of international administrative data and the development of a more complex and statistically sound methodological approach. This document is organised as follows. Section 2 provides some basic information on the FATS Regulation as well as it describes the administrative data sources that are relevant for the compilation of Inward and Outward FATS statistics. Section 3 focuses on the use of national administrative data for the compilation of Inward FATS statistics. Section 4 illustrates the experimental use of international administrative data sources for the compilation of Outward FATS statistics. Section 5 draws the final conclusions. 2. FATS framework and relevant administrative data sources Following the entry into force of a new Regulation, (n. 716, 20 th June 2007), EU MS are obliged to produce business statistics for two new business populations: enterprises under foreign control that are resident in the compiling economy (Inward FATS population) and enterprises under domestic control but that are resident abroad (Outward FATS population). As Figure 1 shows, the Inward FATS population is a qualified sub-population of all resident businesses, while the Outward FATS population is a qualified sub-population of non resident businesses (Italian foreign affiliates are potentially resident in all countries excluding Italy). 1

2 Figure 1 - Inward FATS, Outward FATS and all resident businesses populations A B c A = resident enterprises under foreign control B = resident enterprises under domestic control C = non resident enterprises under domestic control Grey = resident enterprises White = non resident enterprises The current version of the FATS Regulation requires a quite uneven set of variables for the Inward FATS (8 SBS variables plus 2 R&D variables) and the Outward FATS (3 SBS variables) populations. However, these two sets of variables are expected to converge in the medium long terms, following the results of ongoing EU feasibility studies, and given the collection of additional variables at the national level. Indeed, ISTAT has started the collection of additional variables for the Outward FATS population, which includes total purchases of good and services, gross investment in tangible goods, personnel costs and share of exports (as a share of turnover). The relevant administrative data source for the compilation of Inward FATS statistics is represented by balance sheet data compiled by resident companies and submitted to local or national administrative authorities (Chambers of commerce). These data are standardised and fully linked to the Italian BR providing a census like business data source for all enterprises with a limited liability legal form (companies). In Italy, there are about companies with respect to a total population of 4,4 millions of firms. Given the not resident nature of the Outward FATS business population, a possible data source of administrative data can be represented by ORBIS, the well known international commercial data base produced by Bureau Van Dijk Publishing. This commercial database presents an extensive international coverage. It includes business data (key balance sheet variables plus economic activity and ownership information) at the firm level. These data are mostly sourced from national and local authorities acting at the national level as official collectors of business administrative data. It is out of question that this international data source, also used by the OECD and Eurostat, represents an impressive source of business data information. However the presence of limited and uncertain standards of data quality and consistency, as well as of remarkable differences across countries, in terms of definitions, data quality and coverage, calls for a cautious approach in the use of these data for statistical purposes. In particular, coverage, completeness, and data quality is more problematic outside EU27: the number of variables is usually very limited, being restricted to the number of employees and turnover, while variable measurement, coverage and data quality is plagued by national specific business practices The use of national administrative data for the production of Inward FATS statistics In order to reduce the burden on the respondents, the Italian survey on foreign affiliates resident in Italy only collects ownership information and additional characteristics, such ad intra-firm trade variables, not included in other official surveys. The production of Inward FATS statistics is essentially based on the 1 There are few exceptions in this respect. Business data for Extra EU27 are relatively complete for some key countries, such as Russia and Ukraine and partially Japan. 2

3 merge of the list of foreign affiliates resident in Italy with SBS and R&D surveys 2. SBS surveys include the Italian Survey on the economic accounts of small and medium size businesses (PMI) and the Italian survey on large firms (SCI). SCI is a census like survey, which provides a complete set of SBS variables for all companies with 100+ persons employed. In contrast, PMI is a random sample survey based on a quite complex sample design. As a result, data integration problems between the list of foreign affiliates in Italy and SBS surveys are limited to foreign affiliates with less than 100 persons employed and not included in the PMI sample. Non matched data from the list of foreign affiliates were integrated with balance sheet data in order to obtain key accounting variables. Balance sheet data are used to integrate unit non response problems with respect to key SBS variables: turnover, production value, value added, total purchases of goods and services and personnel costs. Following the methodological procedures already developed for the use of administrative data in SBS statistics, these variables were calculated and adjusted to be in line with SBS definitions. For residual not merged companies and for variables not included in administrative data sources (gross investment in tangible goods), variables were estimated using a donor approach. Table 1 shows some empirical results for the three components (SBS surveys, balance sheets data) of this matching exercise based on non financial foreign affiliates (including M-N-O Nace Rev. 1.1 sections), while table 2 provides some additional information on the contribution of each component to Inward FATS final estimates. Table 1 - Matching between the list of foreign affiliates resident in Italy (FA) and SBS or administrative micro-data (values refer to number of companies in % of the total) Breakdown of FA by size and type FA matched with SBS data FA matched with administrative data FA not matched Total 24,4 41,0 34,6 Enterprises or branches with 100+ persons employed 100,0 0,0 0,0 Enterprises or branches with less than 100 persons employed of which 10,1 48,8 41,1 - Small Companies 10,2 51,7 38,1 - Small Branches 7,5 0,0 92,5 It clearly emerges from this table that the successful link with variables from SBS surveys is limited to ¼ of the list of FA. Conditional to the previous step, economic variables from administrative data sources are available for over 40% of FA, while there is a residual of 35% of FA unmatched with either SBS and administrative data. As expected, large companies (100+) are fully covered by the SBS survey named SCI. In contrast, only 10% of FA with less than 100 persons employed can be linked to the SBS survey on small businesses (PMI), showing the presence of a consistent mismatch between the list of FA and the sample adopted by this survey. A little less than 50% of these companies can be successfully linked to administrative data, while a large residual (more than 40%) remains unmatched with both information sources. In this context, it is important to distinguish legally independent enterprises from branches, for in the latter case balance sheet data are not available by definition. Focusing on small companies, the share of unmatched companies moderately decreases to 38,1%. Table 2 provides some basic figures on the impact of different data sources with respect to the final estimates of key Inward Fats variables. 2 The survey approach adopted by ISTAT to collect information on foreign affiliates resident in Italy is based on a census sample for large and medium size companies, and a dense random sample for micro businesses. This survey updates a panel of foreign affiliates set up and maintained by the FATS unit in SBS Division of ISTAT in close cooperation with the enterprise group register unit in BR Division of ISTAT. This panel dataset includes companies or branches. 3

4 Table 2 - Contribution in % of different data sources to Inward FATS estimates Variables excluding grossing up Variables including grossing up Sources of information Turnover Value added Number of persons employed (a) Gross investment in tangible goods Turnover Value added Number of persons employed (a) Gross investment in tangible goods SBS surveys 88,4 88,2 90,4 93,3 86,7 86,4 88,8 91,6 Balance sheets from administrative sources 8,9 8,6 6,3 0,0 10,2 9,9 7,2 0,0 Estimated variables 2,7 3,2 3,4 6,7 3,1 3,7 4,0 8,4 Total 100,0 100,0 100,0 100,0 100,0 100,0 100,0 100,0 (a) This variable is taken from the BR The results are reported for both final estimates (variables including grossing up) and for the list of FA integrated with all data sources (variables without grossing up) 3. The grossing up tends to amplify a little the contribution of both administrative data sources and estimated variables. The contribution of administrative data source to final estimates is around 10 per cent for turnover and value added. In particular, the gross investment in tangible goods variable presents a larger contribution of estimated variables since administrative data do not provide a good proxy variable. However, SBS data provide the very large contribution to Inward FATS variables final estimates (between per cent for all variables). A relevant constraint in the use of administrative data for the production of Inward FATS statistics is represented by the fact that Inward FATS statistics must be fully consistent with SBS data (Figure 2). Figure 2 Consistency between Inward FATS and SBS data by estimation strata Industry (a) Geography (a) Size classes (b) Variables FATS Estimation strata FATS Estimation strata aggregation Industry Variables Industry Size classes Variables SBS Estimation strata Industry Variables Industry Size classes Variables Domestic Estimation strata Industry Variables Industry Size classes Variables (a) Mandatory FATS regulation (b) Discretionary at national level 3 The production of Inward FATS statistics also includes the use of calibration weights to adjust the census like list of foreign affiliates for under coverage problems. Given a consistent improvement in the coverage of the list of foreign affiliates in Italy, which has increased from to units with respect to an estimated population of firms, the impact of this adjustment can be considered residual. Indeed, it represents only 2.8% of turnover and 2.8 % of value added.. 4

5 Indeed, the FATS regulation requires to produce statistics for both the domestic and the foreign owned sectors of the national business economy, and to be fully consistent with SBS data with respect to any estimation strata. The adoption of an additional information source as compared to more standard estimation procedures, where these latter are usually designed and implemented to be consistent with SBS data, can lead to inconsistency in between FATS and SBS figures, indeed negative values for key variables in the domestic sector. 4. The use of international administrative data for the production of Outward FATS statistics The production of high quality estimates for the Outward FATS business population represents a very challenging task for EU MS. Key problems in the compilation of these data concern the correct and accurate identification of the target population, based on the UCI definition, and the collection of classification (economic activity and country of location) as well as economic variables (number of enterprises, persons employed and turnover) for a population of business units resident abroad. Given the quite detailed estimation domains requested by the FATS Regulation, ISTAT carries out a dedicated survey on Italian foreign affiliates resident abroad based on a quasi-census population. Parent companies of enterprise groups based in Italy and under domestic control are considered as the respondent units for the collection of information on one or more foreign affiliates resident abroad, where these latter represent the statistical units of the survey. The survey response rate in this kind of survey is expected to be lower than average. This is due to the nature of information requested, which refer to activities carried out abroad by controlled firms, with respect to which limited information is usually available by the parent company. In the first edition of this survey, the response rate was 46 % in terms of response units and 56 % in terms of statistical units. Although the list of respondent units includes the very large majority of key Italian multinational enterprises (MNE), a relevant number of not respondents is concentrated in the class of medium-size Italian MNEs and moreover in the class of small businesses. As is well understood, standard methodological techniques to manage unit non response problems are quite ineffective in the presence of multiple and varying statistical units for each respondent unit and incomplete information on the target population. In addition, there is a relatively weak correlation between respondent unit and statistical unit characteristics in terms of both classification and economic variables (economic activity, turnover, number of persons employed). As an example, a manufacture company can carry out abroad real services or financial FDI. The availability of an additional source of information on business activities carried out abroad by Italian MNEs plays therefore a crucial role in improving the quality of Outward FATS statistics. In section 2, the commercial database named ORBIS was pinpointed as one of the possible sources of administrative data from which balance sheet data on Italian foreign affiliates abroad can be extracted. The same section highlighted that this administrative data source is plagued by coverage and data quality problems, and that these problems tend to vary remarkably across countries. As a result, the design of a statistically consistent approach to implement the use of international administrative data within an official statistical framework has to be very selective. In line with that ISTAT approach on the use of ORBIS data to integrate unit non response problems 4 from the Outward FATS survey relies on the following two restrictive criteria: 1) Use of a limited set of classification and economic variables 2) Partial integration of non respondent problems As far as point one is concerned, the use of administrative data from ORBIS is limited to one classification variable (economic activity of the foreign affiliate codified as NACE codes) and two variables from 4 The use of ORBIS data for the integration of item non response problems is ignored in this document. Indeed, ORBIS company profiles have been successfully used to check and integrated single variables from the respondent questionnaires. 5

6 the foreign affiliate business profile (turnover and number of persons employed) 5. Other variables, such as for instance value added and labour costs, are assumed to be sensitive to national level specific requirements and need further analyses before being implemented in an official framework. About point two, the ORBIS database presents relevant data quality and coverage problems with respect to specific countries, such as China and India. Therefore, the ORBIS database cannot be used to integrate unit non response problems associated to foreign affiliates located in these countries (given few exceptions associated to large MNEs). Figure 3 shows how the ORBIS database is used in the data integration process with respect to a large Italian MNE as non respondent unit. Figure 3 Example of data integration for a non respondent Italian MNE Italy Country A Orbis Country B Orbis Country C The missing reply to the Outward FATS survey questionnaire of this respondent unit generates 4 unit non response problems, one for each foreign affiliate, where foreign affiliates are located in 3 different countries. In country A there is one foreign affiliate for which ORBIS data are not available. In country B there are two foreign affiliates, but only for one of them ORBIS data are available. Finally, in country C there is only one foreign affiliate with data available from ORBIS. As a result, the data integration process leads to a successful resolution of only two out of four unit non response problems for this non respondent unit. The residual two unit non response problems are considered in the final estimation procedure together with the other non respondent units. The final estimation procedure is based on a system of weights to correct for unit non response problems. These weights are constrained to converge to the geographical distribution of Italian foreign affiliates abroad, where information on the target population breakdown by country is given by administrative data sources available at the national level, and adjusted to take into account respondent information 6. The sys- 5 Quality checks on ORBIS data were performed for both turnover and number of persons employed. The variable number of persons employed usually has a limited coverage or presents poor data quality in ORBIS, since this information is not standardised in economic accounts. Additional controls were performed to check the quality of this information in terms of time series. 6 ISTAT approach in detecting the target population of Italian foreign affiliates abroad is based on an intensive use of administrative data, and in particular balance sheet information available at the national level, in combination with business register information. This has been proved to be very successful in identifying the Outward FATS target population. In particular, it is possible to jointly identify both the list of controlling resident units and controlled foreign resident companies and to have this latter broken down by country. However, information on the economic activity of foreign affiliates is not available from this data source. In addition, the number of foreign affiliates reported in balance sheet data can be affected by some sources of errors: unconsolidated balance sheet do not report information on indirect control, while non active units are included in the list of controlled enterprises. In addition there is the problem of overestimation in the number of foreign affiliates abroad due to the presence of nested balance sheets related to complex enterprise group structure. 6

7 tem of weights is set up and implemented to be consistent with the ORBIS data integration approach. Weights are designed to deal with unit non response problems (indeed missing variables for each foreign affiliate), where these latter can be related to either full non respondent units or to partial non respondent units, where these latter have been partially integrated with ORBIS data. Indeed, the set of weights is based on strata which take into account both respondent characteristics (economic activity and size of the enterprise group) and the location of the foreign affiliates. The extension of weights to include in their strata not only non respondent unit characteristics but also the geographical area of location of the foreign affiliates leads not only to more accurate estimates for fully non respondent units 7 but also to realise estimates for partially non respondent units, after ORBIS integration has successfully solved some unit non response problems. Table 3 summarises the contribution in % of different data sources and estimation procedures to Outward FATS final estimates. The contribution of ORBIS data to final estimates is 5,1 per cent in terms of number of foreign affiliates, 17,1 per cent in terms of number of persons employed and 11,5 per cent in terms of turnover. Since this contribution is cumulative with respect to the contribution of respondents from ISTAT survey, it leads to increase the overall contribution of the deterministic component of Outward FATS data, and consequently to decrease the contribution of estimation procedure. Table 3 - Contribution in % of different components to Outward FATS final estimates Data sources and estimation procedures Number of foreign affiliates Number of persons employed Turnover Deterministic component of Outward FATS data, of which: 53,3 75,9 88,2 - Respondents from ISTAT survey 48,2 58,8 76,7 - Unit non response integration with the ORBIS database 5,1 17,1 11,5 Estimation component of Outward FATS data (weights to correct for unit non response problems) 46,7 24,1 11,8 Total 100,0 100,0 100,0 This latter is still relevant in terms of number of foreign affiliates (38,7 %) but rather limited in terms of number of persons employed (24,1 %) and especially turnover (11,8 %). Another interesting extension in the use of ORBIS data concerns the possibility to detect under coverage problems in the Outward FATS population. This can be occasional or related to specific typologies of UCI, as the case of a natural person as direct controller of foreign affiliates. 5 Conclusions This paper describes the approach adopted by ISTAT in the use of administrative data sources with respect to the production of FATS data, a relatively new domain of official business statistics. In line with what has already been done by ISTAT in the production of Italian SBS statistics, balance sheet data have been extensively used in the production of FATS statistics to reduce the burden on the respondents as well as to increase the quality of final estimates. The peculiar characteristics of the Outward FATS business population, which focuses on a population on non resident enterprises, have led to the adoption of a new source of administrative data, represented by international commercial databases, and to the adoption of innovative methodological solutions. Advantages and drawbacks in the use of national and international administrative data sources in the production of FATS statistics have been highlight and discussed in the paper, although a more in depth empirical analysis, comparing different approaches, is still to be developed. Finally, it is important to pinpoint that the nature of the approach adopted by ISTAT on the use of administrative data in the production of Outward FATS data is so far relatively mild, as these data are essen- 7 Non respondent units may present different characteristics with respect to respondent ones in terms of number and geographical distribution of foreign affiliates abroad. 7

8 tially used for the treatment of unit and item non response problems. However, in the medium-long terms, a more intensive and expensive use of national and international administrative data sources is expected following the restructuring of SBS statistics as well as the adoption of more efficient way to reduce the burden on the respondents. References Eurostat (1999), Use of Administrative Sources for Business Statistics Purpose, Handbook of Good Practices. Eurostat (2009), Foreign Affiliates Statistics (FATS), Recommendation Manual. 8