Methods of International Services Trade Statistical Recording

There are presented suggestions of article authors for development of Lithuanian international trade of services statistical recording. And essential criteria for sample size selection for statistical informa tion collection, criteria for data collection according to special groups and variables for statistical information estimation there are, too. Besides that opportunity to develop a statistical registration in Lithuania at the end of article you will find, too.


Introduction
The actuality. More and more enterprises in Lithuania in the way of integration to European Union look for possibilities to supply selVices and goods through foreign affiliates abroad. The discussion is how to calculate a statistics of selVices supplied by foreign affiliates. Besides foreign selVices trade discussion we have no universal statistical registration of selVices, goods of industry in our country, too. Variables discussed in this article could be used for calculating and statistical registration of domestic selVices and goods, too.
Tire novelty of the theme is concerned with a majority countries and Lithuanian statisti-cal registration problem, because till now we have no suitable frame for analysis of selVices statistical data. Notwithstanding a fragmentary statistical registration of selVices in our country till the end of 20 century, two common indices were used: a) common inside product, and employment in this sector.
A methodic of statistical registration in countries is very various till now. A majority of countries uses a system of classification of selVices to three classes: transport, travel, and other selVices. All agreements on international trade of goods are settled into shape and practically realized.
Meanwhile situation in selVices is very different. Well-developed countries uses one methods of services classification, poor developed -the others. More developed countries calculate and import and export of services and does it rather successful, but less developed in majority cases just start to do it. Not unified criteria for services estimation do not allow to countries to compare them economical indices and achievement in global market. At the conditions of global market all countries should try to achieve a common system of statistical registration of services trade.
Scientific problem: even if a lot of foreign and Lithuanian authors recognize the necessity to expand variables for estimating services activity abroad, there is no sufficient recommendation that variable it could be.
TIui subject o/the research -methods of statistical registration on international services trade.
A goal o/this article -to survey possible variables for services registration and to present recommendations for collection a statistical registration data in Lithuania.
The methods o/the research -analysis of foreign and domestic literature, comparing analysis and systematic research of data.

The Essentials Aspects of Statistics on Foreign Affiliates Trade in Services
Direct investment enterprises or affiliates established in the countries of foreign customers very usually serves as a way to compete effectively in competing market" It is especially urgent in the services field, where the largest attention is paid for serving a customer, to satisfy his or her dynamic needs and demand. Statistics describing the overall operations of affiliates are tenned "foreign affiliates trade in services statistics" ("FATS statistics"). I Here, "affiliate" is used as synonym of "direct investment enterprise".

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The suggestions what we are going to present in this article (excluding a few of exemptions for the particular activity and product) could be used for statistical registration of goods, too.
Experience shows us that infonnation on the operations of affiliates is considered on their sales (apart services that may be donated). For example, this index is the most important index for estimating services statistics in Lithuania. However, but this index isn't a sufficient ground to calculate services from all perspectives. The newest researches and authors (Hoffman, Lawrence, 1996;Bilsborrow, Hugo, Oberai, Zlotnik, 1997; Manual on Statistics of International Trade in Services, 2(02) recommend using more indexes for statistical registration of services trade. A lot of countries limit themselves to collect a statistical data on sales because of control for commitment under GATS (General Agreement on trade in Services).
Even if infonnation on sales is important for FATS, for statistical services registration on the whole, it is necessary to coUect additional infonnation for estimating an economic effect of services. For example, value added could distinguish services supplied by affiliate from services (and goods, too) that supply ordinary intennediate.
The next example, which is used as a second and the last of indices for estimating services in Lithuania, is employment. Infonnation on employment is required to assess the impact of affiliates on labor markets.
It is necessary to note, that foreign direct investment financial transactions and related investment position (stock) and income measures are not FATS variables (but FDI (Foreign Direct Investment) because they do not reflect overall operations of foreign affiliate but relate only to transactions between.
Notwithstanding differences, FDI statistics is additional information for FATS statistics, which is necessary, too. Countries, for example Lithuania, which cannot implement the compilation of FATS statistics immediately, may use FDI statistics, which can provide an alternative data for services registration (mentioned above direct investment income, direct investment financial transactions, direct investment position). Below you can find main definitions of these conceptions.
• Direct investment incomean income on equity and on debt; and covers income accruing to a direct investor in one economy from the ownership of direct investment capital in an enterprise in another economy.

• Direct investment financial transactions -
capital provided by a direct investor to a direct investment enterprise or capital received from a direct investment enterprise by a direct investor; • Direct investment positionthe value of the stock of direct investment.
There are two prilTUJry sources for FATS statistics regi.stralion inUrest that are necessary to take in account in all countries and Lithuania, too: 1. GATS that created a new need for information describing the activities of foreignowned or foreign-controlled fiIlns in host countries. This information is available if employment by foreign affiliates is collected and if their foreign employees, who moves temporarily abroad can be identified; 2. Growing integration orglobalization ofthe world economy. Goods producers earlier, services firms latter have expanded their operations beyond the countries of their owners for a variety of motivations: benefits from geographic diversification, circumvent trade barriers, increase markets, reduce costs of labor, transportation and etc.
FATS statistics significance discern in conjunction with otherinfonnation on home or host country economy or on services supplied not for commercial presence. For example, estimating a number of employees of foreign-owned affiliates it is useful to compare it with the percentage of domestic employment accounted for by these affiliates. Estimating value added created by foreign-owned firms shows his created value difference from domestic ones.
Recommendations for statistical data collection in this article will be analyzed according the 1 scheme. N ex! parts of this article well explain essential issues of this scheme.

Universe of enterprises to be covered for FATS
There is no universal and well developed methodic for statistics of selVices almost in all well-economically developed or poor developed countries till now. For example, methodology of statistics of trade between residents and non-residents is clearly defined in . Problem is that there is no globally agreed ownership concept. So, there is no agreement that types of the firms should be covered in statistical data and whether the statistics should cover all producers or only selVices suppliers. The main criteria for firms covered for FATS are turn below.
Some of ownership criteria for statistical data collection we can find in roles, presented by GATS (World Trade Organization, 1995).
• Ownershiprefers to more than 50 percent of juridical person of the equity in- terest in business enterprise. This concept of ownership a dictionary (Webster's New World Dictionary, 1988) simply explains as the state or fact of being an owner. • Control -a juridical person have a majority of its directors or otherwise power to legally directs its actions. By a dictionary, it is a power to direct or regulate. • Affiliation -person is affiliated with other person, who control or is controlled by third person. As dictionary explains, it is to connect or associate fact.
GATS suggests to define "subsidiaries" as enterprises in which the direct investors owns more than 50 per cent, "associates" as enterprises -with 10--50 per cent and "branches" as wholly or jointly owned enterprises.

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Using the criteria for collecting the data of services firms to be registered for FATS (FDI methodic involves only foreign direct investment financial transactions and related investment position (stock) and income measures), it is relevant to consider criteria used or recommended not only at a global, but national and regional criteria, too. Eurostat report states to use "majority ownership" conception. There is presented a definition of majority ownership below.
Majority ownership is a presence, as direct investor owns more than 50 percent of shares or votingpowerin enterprise (Manual of Statistics of International Trade in Services, 2002 This cri terion is very clear and could be used by all countries globally and by Lithuanian sta-tistics, too. So data for seIVices trade registration have to be collected if firms correspond to these criteria. Besides there is no difference if an investors is a single person or associated group of investors. Thus fulfilling these criteria for globally universal statistical registration, countries with dominating single investor or investor group can solve a problem of data collection unification.
The next stage for firms to be covered is to define that kinds of firms have to be included. There are two main points for discussion: 1. Structure of the enterprise; 2. Purpose of the enterprise.
Answering for these points, we should note, that statistics should include all types of enterprises, supplying seIVices internationally -holding company, regional headquarters, -acting for variety of purposes -administration, management of foreign exchange risk and etc. Statistics should cover all majority-owned foreign affiliates, irrespective of whether the affIliates are held directly or indirectly, whether the direct investor is ultimate owner or intermediate owner.
A type of producers is a second thing for criteria of universe to be covered in statistics. If statistics covers only producers producing services, it neither would nor include each activity of seIVices. At the beginning of 21 centuries almost all producers sells them production at domestic or global market together with seIVices, produced by them. Some of firms produce both goods and seIVices and seIVices are just a second activity of them. Early defined conceptions of "goods society" and "seIVices society" becomes as seIVices society as one. The coverage of all producers allows for the activities of seIVices producers to be examined in the context of statistics covering all firms.
Thus statistics should not isolate services producers from goods producers.
Time of recording of data should be unified in all countries globally. Output; value added and other flow variables are calculated for reference year. Stock variables, for example, assets and net worth of the end of the reference year. Reference year is based on calendar year (if possible). Countries that have no possibility to register statistical data on calendar basis, should provide an explanatory notes for using data collected on fiscal or accounting year basis. Lithuania here uses a majority well developed countries practice and provides financial information on end year basis.
Statistical units for collection of statistical data in countries could be various. Statistics could be collected at enterprise level or the level of individual business or establishments. All data are unequivocally important. Of course to collect financial data is more understandable from enterprises that exist on commercial basis, than from establishments, that exists on non-commercial purpose. Meanwhile enterprises have more activities as establishments, and for former it is more difficult to classify data on this basis as for later. Thus information on statistical unit should be disclosed in explanatory note.

Grouping the Data
The issues to be addressed in attributing variables by country differ as between inward FATS and outward FATS.
• For inward FATS two choices: ./ Attribution to the immediate investing country; ./ Attribution to the ultimate investing country.
• For outward FATS two choices, too: ./ Attribution to the immediate host country; ./ Attribution to the ultimate host country.
For foreign-owned affiliates problems arise is whether to attribute FATS variables to the country of the immediate investor (first foreign parent) or to that of the ultimate investor (ultimate beneficial owner). Not in every case the first foreign parent and ultimate investor is the same (although in many cases they concur).
BPM5 (Balance of Payments Manual, 1993) recommend attributing these variables to immediate investing country or immediate host country. Eurostat (Statistical Office of the European Communities and Organization for Economic Co-operation and Development, 2001) FATS recommend that the ultimate host country and ultimate investing country is more important because it shows the level of control of enterprise. This principle could be very complex in practices, so first foreign parent could be used as substitute with the possibility to obtain data on the basis of ultimate beneficialowner.
Lately United States has collected data on the second principle and does it rather successful for some years. Thus this principle could be more useful for calculate and used these data globally. And just if these data collection is impossible in some cases of practices, a data recording on first foreign parents level could be made.
There are two possibilities for attribution of statistical data for afflliates owned by residents: 1. The variables could be attributed to the country of location of the affiliate; 2. If the ownership is through a directly held affiliate located in another country -to the country of that affiliate.
Methodology of statistics should include a country of the affiliate whose operations are described by the variables, a country where the various activities (sales, employment) tracked by the statistics.
Problems arise then foreign owners of affiliate are more than two and if there are foreign owners having an equal share on this affiliate. Because the ownership is evenly split, the determination of the country of owner has to be made according criteria other than percentages of ownership (shares). Preference is for directly held affiliate before indirectly held affiliate in other country, if one of the owners is government entityfor the country of that Government and so on. There are a lot of cases in practices for interpretation of data, which are attempted to solve in different cases.
As practice shows, to group a statistical data by industrial activity of producers and on the basis of services products produced and sold are one of the easiest ways for statistical registration. Classification on the basis of specific types of services is made in the other statistical registration systems. This information is rather easy accessible and usable in all countries. The activity of affiliates is classified by primary activity in it (which gives the largest part of sales, employment and so on). Therefore an activity basis is recommended as the first priority for statistics of services.
However countries are forced to classify an activity on product basis, too. Under GATS all statistics of countries acting internationally should be specified in terms of services products, too.
Classifying on the basis of activity all countries should adopt ISIC categories for foreign affiliates (ICFA) for classifying of services. There are no detailed apportionment to subclasses or groups and subgroups of services in this table because of no matter to go to details of classification of services too much in this article as more detailed classification we can find almost in all classifications made and used by countries and by Lithuania, too.
There are excluded such categories as public administration and defense, compulsory social security, private household with employment and extraterritorial organizations and bodies, which are not relevant to foreign trade of services, i.e. is a matter of domestic statistical registration.
There are some advantages of classifying of activity of services enterprises by ICFA: • This basis is more detailed for services as for goods. • It allows activities of services enterprises to be viewed in the context of the activities of all enterprises.
• Enterprises classified as goods producers are allowed to display services produced as a secondary activity.
• This kind of statistical registration is adopted and used rather successful by the countries and international organizations that are know as well-developed statistics countries.
The next goal of statistical data attributing is to classify services producers by product, i.e. some or all variables of the product -sales (turnover), output, exports and imports. Product-based statistics correspond to commitments of GATS made and is rather generally used. It this level of specifying cannot be achieved countries may disaggregate sales in each industry between sales of goods and sales of services. For classifying by this basis it is possible (and often useful) to compare product-based classification with classifying according Harmonized System for trade in goods and to find more beneficial attribution.

Variables should be covered
Variables used in Lithuanian statistical registration of services are commonly two (Vengriene, 1998):

A common inside product (CIP), it is a
turnover or sales (we are able to name them as we want); 2. An employment in this sector.
Getting more into detail of the first mentioned point, we should note, that statistics represent income of services enterprises, too. They are analyzed through (Paslaugos'2002(Paslaugos' , 2003: 1) distribution of income by services activities; 2) income of service enterprises perlOOO population; 3) number of services enterprises in operation and services rendered.
Detailing the variables of employment, we should note, that statistics represent these numbers: 1) distribution of service enterprises by numbers of persons employed; 2) number of service enterprises in operation and persons employed.
However these numbers are only a solution of the two mentioned.
But they are not sufficient ground for analytical purposes of statistical data. Analyzing the data of services industry a need to implement GATS in each country arises. So countries in selecting a set of variables for statistical data registration need to consider the usefulness of them in implementing GATS.
The second urgent moment in selecting a set of variables is globaliZJllion in all services and goods industry. Selecting the data for statistical registration there is need to consider if they are available in a majority of countries, i. e. in global market. In integration to global market process all poor developed countries (including Lithuania) should correspond to variables collected by largest well-developed economies, for example USA.
Main variables in statistical registration suggested in this article are: 1. Sales (turnover) and/ or output; 2. Employment; 3. Value added; 4. Export of goods and services; 5. Import of good and services; 6. Number of enterprises; 7. Other variables.
On of samples for statistical registration on the basis of ICFA frames are presented beolow. For example for recording the data on services each class of services should be detailed to subclasses, group of services should be detailed to subgroup, and etc. in the left side of the table. Then percentage or volume of each class, group or subgroup should be submitted in the right side of the table for: • sales, turnover, output; • employment; • value added; • export of goods and services; • import of goods and services; • number of enterprises; • and others usable variables. Statistical entity can use and additional tables of these variables. We can place an em-plo~ent at the left side of table and time series or geographic detail by time periods or country names in table heading. More explain of set suggested for statistical registration presented below.
Sales and turnover are used as substitutable things for statistics, meaning the same. Output differs from sales because it includes changes in stocks of finished goods and work in progress. Output is a superior and more refined measure of activity involving trade (wholesale and retail distribution) or financial intermediation but sales data is easier to collect for the rest larger activity of sales (because of services impossibility to stock). If it is possible we suggest including both measures in statistical registration in Lithuania.
Sales measures gross operating revenues and should be measured exclusive of consumption and sales taxes on consumers and value added. Sales are more comparable than value added with regard to such variables as export and imports, which are themselves measures of sales. As was mentioned above, sales of services should include both services than a primer activity and sales of services by enterprises that .produce goods as a primer activity but supplies services -as a secondary.
Employment is measured as a number of persons offoreign affiliates. Some countries is used a practice to convert time-worked workers to full-time equivalent, but a number of really working employers is more useful data in statistics as and equivalent of full-time employers. This variable is measured as of a point in time, such as the end of the year.
Data on employment by affiliates can be used for determine the share of foreign afmiates in host country employment, to examine compensation practices of affiliates relative to those of domestically owned firms and for other purposes.
Value added tax is a money expression of value of services and goods sold in the host country. Jlalue added defines gross value added of an establishment, enterprise, industry or sector as the amount by which the value of outputs produced exceeds the value of the intermediate inputs consumed. It is among the basic FATS variables because it is a particularly useful measure from the perspectives of both GATS and globalization analysis.
Export and import of goods and services are next categories for measurement, which include services and goods could be exported (imported). If it is possible, data for goods and seIVices should be separated. These data may give useful information, but it is rather difficult or impossible to separately identify the transactions of foreign-owned firms in those data. For more detailed information on export and import of seIVices of affiliates they could be attributed: to export to (import from) the parent enterprise; other export to (export from) the country of the parent; exports to (imports from) third countries.

Number of enterprises (or establishments) is
a basic indicator of the prevalence of majority ownership by foreigners in the host economy. That number may be compared with the total number of firms in the countries economy. It may also be assessed in relation to the other FATS variables because it allows the computation of ratios -such as value added or number of employees per enterprise -that may be compared with the same ratios for domestically owned firms. The number of firms may not give an accurate view on the overall importance of foreign-owned firms, because they rather are larger than domestically owned, so their share in the total number of firms would be smaller than their share in the various measures of operations. Thus information on number of enterprises should be analyzed together with other variables for statistics.
Other variables for statistical data in practices of countries are used, too. Even if they are not priority items for variables to be collected, they may give an equal or greater importance than some of those previously discussed. Some countries (Manual on Statistics of International Trade in SeIVices, 2002) already collect some of these variables, and they could be as sample variables for Lithuanian statistical registration: 1. Assets: entities over which ownership rights are enforced and from which economy benefits may be derived by their owners by holding or using them, including both financial assets and non-financial assets, whether produced or non-produced; 2. Compensation of employees: the total remuneration, in cash or in kind, payable by an enterprise to an employee in return for work done by the employee during the accounting period; 3. Net worth: the difference between the value of all assets -produced, non-produced, and financial -and all liabilities; 4. Net operating surplus: measured as value added (gross ),less compensation of employees, consumption of fixed capital and taxes on production, plus subsidies receivable; 5. Gross jUed capital: measured by the total value of the producer's acquisitions,less disposals, of fixed assets during the accounting period, plus certain additions to the value of non-produced assets realized by productive activity; 6. Taxes on income: these consist of corporate income taxes, corporate profit taxes, corporate surtaxes etc. as well as taxes that accrue to owners of unincorporated enterprises as a result of the income of those enterprises. Taxes on income include only taxes in the host country of the affiliate; 7. Research and development expenditures: expenditures for activities undertaken for the purpose discovering or developing new products (goods and seIVices), including improved versions or qualities of existing products, or discovering or developing new or more efficient processes of production; 8. Other variables, that Lithuanian entity may find useful for statistics of international services trade.

Opportunities for Development of Services Statistics
There are two approaches to developing FATS statistics:

To conduct surveys directly requesting infornuJlion on the operations of resilJent affiliates offor-eignfinnsandforeignaffiJiaJesofdomesticfirms·
In other words, statistics entity organize surveys for foreign-owned finns and these surveys are assigned for FATS, but not for other statistical data, collected by countries; 2. To identify a subset of existing data on resident enterprises foreign-owned firms account thalfor. In other words, statistical entity uses information, collected for other purposes than FATS. Whichever of these approaches is suitable and gives useful information for registration on or another services activity in Lithuania in concrete way we cannot say exactly. First of all, it is need to relate them to existing data on foreign investment. Besides FATS variables should be added to FDI (foreign direct investment) data for more detailed analysis of statistical infonnation. Each of this approach has its own advantages or disadvantages.
In many cases, a mix of the two approaches works best. FDI used for outward FATS stotistics and for the identification offoreign-owned companies; and enterprise statistics works for inward FATS statistics, with more detailed activity. Recommendations to use both of approaches because of coordination of them advantages and disadvantages, a flexibility of countries in adapting the recommendations to their statistical infrastructures and maximizing the use of existing data.

Conclusions
1. Foreign affiliate's trade in services statistics should cover affiliates in which the direct investor (or an associated group of investors) holds a majority of the ordinary shares or voting power. Countries should provide supplemental statistical data, covering cases 118 in which foreign control may be deemed to be present, even though no single foreign direct investor holds a majority stake. 2. FATS variables should be compiled for all foreign affiliates producing both services and goods. 3. For statistics on foreign-owned affiliates (inward FATS) the first priority for geographical attribution should be the country of ultimate beneficial owner. Statistics for foreign affiliates (outward FATS) should be attributed based on the country of location of the affiliate whose operations are being described. 4. Spreading out the priorities for variables should be included in statistical classification, the first range is attributed for activity, the second -product based classification. However, data on product basis is as a longer-tenn goal, and countries are going to work providing product detail for such variables as sales (turnover and/or output, exports and imports. 5. Attempting to unify a statistical data collection International organization should attribute them activity according the ISle Categories for foreign affiliates. Lithuania should follow this practice. 6. Lithuanian statistical registration should be expand in such variables as: a) sales (turnover) and/or output, b) employment, c) value added, d) exports and imports of goods and services, e) number of enterprises; f) other expanded data used by another countries rather successful; 7. Statistical entities in our country could use a variety of sources and methods for FATS statistics registration. If additional financing is possible, separate and individual surveys may be implemented. Surveys made by domestic finns may be used and/or supplement. Existing data on FDI may be analyzed together with FATS.