Discuss design for imputation for non-response of establishment/enterprise respondents.

Transcription

1 BACKGROUND PAPER: Survey Planning Discuss design for imputation for non-response of establishment/enterprise respondents. Introduction 1. A survey will rarely return a response rate of one hundred percent, and so problems of non-response and partial response need to be overcome. The editing process will also highlight erroneous responses, that are contradictory to other responses. Imputation is used to fill the gaps in the survey data file, by creating approximate responses, or imputes for the missing value. The imputes are created using information from the clean (correct response) units on the survey data file, and in some cases, use previous survey data information. 2. This paper outlines the use of imputation in the Australian Bureau of Statistics (ABS) for the information of workshop participants in their consideration of survey planning issues. Methods of Imputation 3. There are four basic methods of imputation used in ABS economic collections: Mean imputation - the imputed value is the average of clean responses of units considered to be similar to the unit requiring imputation. Mean imputation can be performed using live respondent means or respondent means. Live respondent mean calculates the impute as an average, using units that are live and clean. By restricting the contributing units to the live clean units, the resulting imputes are more likely to be representative of the non-responding live units - assuming that the non-respondent units are live, which is the case in most of our economic collections Respondent mean calculates the impute as an average of clean units that are either live or dead. The respondent mean imputation method is useful for situations where units requiring imputation have an unknown operational status. By including both live and dead units, the unknown operational status is accounted for. This imputation is less rigorous than live respondent mean as it is more likely that there will be more contributing units available in each imputation class. Ratio imputation - the imputed value for a data item is calculated by taking a clean response for the same unit (from a previous cycle of the survey or from a different data item) and applying an adjustment to the clean response. This adjustment is usually based on the ratio of clean responses from similar units. The adjustment may also apply a predetermined factor whose values are contained in a data set which is specified. In the case of partial imputation, we sometimes have a correct response for a data item which is known to be the

2 total of other (component) data items. In this case ratio imputation can be used to pro-rate the correct response to the total to any non-responding component data item. Donor imputation - impute values are obtained by 'borrowing' clean survey responses from another unit considered to be similar to the unit requiring imputation. The donor may be from the current cycle (hot deck) or the previous cycle (cold deck). Look-up table imputation - imputation is done using a look-up table which assigns impute values to a unit according to its characteristics (such as state and industry classification). The impute value is obtained by matching the characteristics of the unit requiring imputation with those present in the table. Look-up table imputation is basically mean imputation or ratio imputation using predetermined values (rather than system generated values). 4. The majority of ABS economic collections use imputation to address nonresponse and partial responses. Many collections use mean imputation although a number use different strategies for the completely enumerated sector and the sampled sector. In addition to the methods above most collections use clerical imputation. This is often applied during input editing and where partial data or other relevant information is available from other sources. Using the above imputation methods 5. Mean imputation is generally easy to perform, and is useful for situations where auxiliary information is not available. Care should be taken in using mean imputation particularly with regard to response rates and frequency of errors. It can introduce a non-response bias if respondents are not considered to be typical of non-respondents. 6. Ratio imputation is closely related to ratio estimation in finite sampling theory and might be considered a natural choice of an imputation method, particularly if the same variable for ratio estimation is used in the estimation method for the survey in question. However it may be suitable even when ratio estimation is not being used. Ratio imputation relies on the fact that we do not know the true value of the item of interest but we have a reasonable idea of the value of its ratio to another known item. The ratio must be logical or have a sound basis and hence be highly correlated. The ratios derived from units with good data must also be valid for those units with faulty or missing data. 7. For donor imputation, the cold deck procedure can only be used where past data exist. The imputed values could be well out of date or based on definitions different to those in use. In some cases a rate of change is applied to the previous response to allow for the change between timepoints eg. by taking account of inflation. There are various methods available using the hot

3 deck procedure to determine the donor. Determining the criteria may create difficulties, and may be expensive. Donor imputation will generally use a clean, edited record to donate a response to a non-respondent. Other methods (such as mean imputation) give imputes which need to be checked to make sure they satisfy the editing rules. 8. Look-up table imputation relies on having relevant information available in order to assign a value to a unit according to its characteristics. Minimising the load on businesses 9. In planning collections, statistical agencies may take account of the load on businesses imposed by the collection requirements, to minimise nonresponse. ABS collections are designed so that the number of overall businesses approached are kept to a minimum; thereby imposing the lowest load possible while meeting its obligations to provide Government and the community with a high quality official statistical service. This is achieved by using: a sampling techniques, wherever appropriate, rather than complete enumerations; b size cut-offs, or other coverage restrictions, in order to exclude from collections those businesses which in total do not have a significant effect on the important statistical aggregates produced by the collection, or which can be adequately accounted for in some other way, for example, by carrying forward or modelling estimates from less frequent surveys; and c other synthetic estimation techniques, for example, by deduction (by confronting data from different sources), by using administrative by-product in conjunction with directly collected data, and by pro-rating estimates down to a finer level of detail than standard estimation procedures allow by use of twophase sampling. While business income tax data is being used increasingly to supplement ABS annual collections, taxation reform in Australia including the introduction of the goods and services tax and regular reporting on key financial information will offer further opportunities to the ABS in improving survey design and reducing business load. Generalised systems 10. As part of the strategy to integrate economic collections, the ABS has introduced generalised systems including a generalised imputation system (called GenImp). This facility provides a means of performing automatic imputation in a wide range of subject matter areas. In addition, the ABS has

4 implemented a unified procedure for treatment of units (called sample and frame maintenance procedures) in all our business register-based collections. This ensures that economic surveys in the ABS use the same set of impute rules, and they are applied and regulated in the same manner. This standardisation allows for the comparison of imputation rates between collections.

5 BACKGROUND PAPER: Linking census, annual and quarterly surveys Conducting censuses, annual and quarterly surveys are often done by many countries. Issues often arise in reconciling the levels of quarterly to annual, and annual to census. The total of four quarterly survey results does not match with annual survey results. Similarly, there are inconsistencies in the results of annual surveys and censuses. The causes of these differences will be discussed and possible strategies to minimize these differences would be explored. Introduction 1. The ABS, in common with other statistical agencies, has devoted considerable effort over many years to ensure that the various statistical outputs it produces have a strong conceptual basis and are as integrated as possible i.e. statistics from different surveys are produced on a consistent basis without duplication or gaps and therefore provide comparable statistics across different segments of the economy. 2. Statistical units, data items and classifications comprise the main conceptual standards for statistical collection activity. Apart from conceptual integration, other key integrating elements include the application of consistent methodologies (e.g. scope, coverage) and procedures, use of integrated business registers and despatch and collection control facilities, processing systems integration, and how the data are finally disseminated. Issues 3. There are various issues which can emerge in confronting the levels of quarterly to annual surveys, and annual survey to census data. Some of these are discussed further below. Purpose of collection outputs and differences in collection design requirements 4. When confronting data across surveys it is important to understand the purpose of the collections being confronted. Differences in collection design requirements can affect the comparisons that are undertaken; for example, there will be differences in comparing the outputs from a quarterly survey designed to produce best estimates of movement at a fairly broad industry level to the outputs for an annual survey designed to produce best estimates of level by detailed industry. 5. Requirements of clients will differ across collections and this will drive the purpose and collection design. For example, the output for one collection may be designed to meet National Accounts requirements and use national accounting

6 frameworks and concepts. Another collection may have similar data items but may use standard accounting concepts as it is designed for business analysis. 6. Quality requirements such as the design standard errors may differ across collections and these should be taken into account when comparing estimates. Differences in statistical units 7. Differences in the statistical unit exist where collections may approach different types of statistical units. For example, in the ABS, while many surveys use the management unit as a statistical unit, some of the labour surveys use a hybrid of the management unit which is state bounded (whereas the management unit can cross state boundaries). Another example in the ABS, is that the international and financial accounts collections typically collect their information at the enterprise level, and some collections use a concept of a 'top' enterprise within an enterprise group reporting on behalf of other enterprises within the group who are in scope of the survey. The collection of information at this level has some inconsistencies with other collections which use business structures held on the ABS Business Register and this makes data confrontation more complex. 8. In most instances, businesses report data to the ABS for the statistical unit as defined. However, non-standard reporting arrangements are sometimes used by some collections for some businesses. A "special reporting unit" exists whenever data are reported by respondents for units other than the statistical unit i.e. involving aggregations or dissections of statistical units. Inappropriate or incorrect use of special reporting units by ABS collections has highlighted problems for data quality and data comparability. To manage these issues, various best practice procedures have been prepared on establishing and maintaining special reporting units. Associated with expected business changes resulting from tax reform, the ABS has developed a Reporting Unit Facility to provide a central store accessible by survey areas which will store information on changed structures; and provide advice to survey areas on best practice for the use of special reporting units. Differences in data items and question wording 9. Conceptual differences in data items can make comparisons more complex. For example, in the ABS some collections request items on an accruals basis, while others collect it on a cash basis. This difference stems from the different source data being sought in the respective surveys or the purpose for which the data are collected. In relation to wages and salaries, one survey seeks information from standard business accounts, while the other seeks data sourced from payrolls which are generally on a cash payments basis.

7 10. Another example is capital expenditure, where our annual surveys include expenditure on second-hand assets and land and intangibles, whereas the quarterly survey excludes these. 12. Another example is profits where both the annual and quarterly economic activity surveys produce estimates for an item approximating national accounts gross operating surplus. These measures are not consistent in terms of the items included in the calculation and the method in which the estimates are derived. The quarterly survey uses net operating profit as the starting point and attempts to exclude certain items to derive gross operating surplus. The annual survey uses a bottom up approach from the individual income and expense items which are included on the survey forms. Recent changes to the quarterly economic activity survey may address this problem as the quarterly survey is now collecting some more detailed income and expense items to facilitate comparisons; however some of these more detailed items are not always available on a quarterly basis. In addition, the quarterly survey now collects some detailed information not collected the annual collection. Differences in methodology, processing and systems 13. There is generally a tension between having the 'best' methods and systems for a particular collection compared to using standardised methods and systems which require less individual statistical/technical support. Differing methods and systems need to be taken into account when confronting data across collections. For example, different imputation techniques can affect comparison of estimates. When comparing quarterly and annual data, more timely historical imputation information is available from quarterly surveys (i.e. the unit's response last quarter), and so imputation may be more accurate. Annuals may have historical information which is less up to date. This is especially true if the issue of selection is considered, as in the ABS, there is usually much greater overlapping sample between successive quarterlies, than would be expected for successive annuals. This will impact on estimates of movements, more than estimates of level. 14. There are differences in the treatment of outliers across collections. In the ABS, winsorisation (involving modification to the value of an item in accordance with specified bounds) is used by a number of quarterly surveys but is less common in the annual surveys. Timing of confrontation 15. Comparing aggregate data across collections is dependent on the completion of processing for all of the source collections and therefore occurs `after the event'. In one sense this is advantageous because it enables the stocktake to consider the impact of all elements of the statistical process on data then published and used as input to the national accounts. While it allows

8 general conclusions to be drawn about where efforts can be best directed to improve the quality and consistency of data reported, it does not fix the problems as they occur. 16. Comparing unit record data across collections can be done in time to impact on the estimates produced by the latest survey being confronted. For example, comparing annual and quarterly data can allow amendments to data for the annual survey but if amendments are required for the quarterly data, this can take place sometime after the data has been released. Confronting annual and quarterly data can be difficult if it is necessary to go back to respondents to query data reported well after the reference period. Timing of reporting and differences in data sources 17. The ABS accepts data from businesses with off-june year accounting periods on that basis for its annual collections. It currently includes this data in estimates relating to the financial year ended 30 June without adjustment, although the possibility of using quarterly survey or administrative data to adjust off-june year reporters will be investigated. Data reported on this basis cannot be simply and systematically compared with aggregated or selected data from subannual surveys, because of the different reference periods/dates. 18. Businesses are often faced with a choice as to whether they use their statutory or management accounts to complete ABS forms. Statutory accounts are required by law, and must adhere to the Australian Accounting Standards. They are compiled in respect of legal entities and certain groupings of them, and are compiled at least annually. Management accounts are prepared as internal accounts and compiled as often as needed (generally monthly, quarterly or six monthly). Because of the potentially different units for which management accounts are prepared and differences in accounting practices, they may bear a very complex relationship with the statutory accounts. They may also be identical, as they are derived from the same underlying sources. 19. Factors determining whether to use statutory or management accounts include the frequency with which management accounts are prepared, the timing/due date (statutory accounts are not usually released until audited), the data items requested in the survey, and the wording used in the survey questionnaire. For the annual economic activity survey, the ABS requests that information reported should comply with Australian Accounting Standards whereas the quarterly economic activity survey requests that businesses report as per the business' financial or management accounts. 20. The same input sources (lower level accounts) are used to compile both the statutory and management accounts. However there are differences in data compiled using statutory and management accounts, and this tends to relate mostly to end of year adjustments that may not be reflected in management

9 accounts. For some businesses, dividend income are not recorded in management accounts. 21. Businesses may provide estimates for sub-annual collections if actual data are not available; whereas the same businesses may provide actual data to the annual collections. Recent ABS developments 22. The National Accounts are an integrating framework for business surveys, in terms of the data sought and classifications used, and they also provide ongoing pressure to produce cohesive data. Over the last decade, the ABS has established a range of initiatives aimed at improving the consistency and relatability of data produced. 23. The ABS has introduced an effective annual process for establishing data requirements, coordinating survey development and testing, consideration and approval of collection strategies, and use of consistent data content and question wording. 24. In recent years, the ABS has made substantial progress by applying standardised best practice across surveys. For example, business surveys now draw their frames at a common date each quarter, and use a common estimation method to ensure that all collections have consistent and complete coverage. As well, the ABS has successfully introduced a unified procedure for treatment of units (called sample and frame maintenance procedures) in all our business register-based collections. Standard rules are adopted for frame maintenance, and estimation. The ABS is thereby able to ensure the coherence of estimates across different business surveys even when, for example, the survey frame experiences substantial changes from the tax reform recently introduced in Australia. 25. Systems have been introduced to support current best practice. The ABS has invested in generalised tools for collection and processing. Generalised tools have been, or are being developed, for all major processing steps for economic collections include sample frame management, data input and editing, imputation, estimation, aggregation and dissemination. 26. One important quality improvement initiative that the ABS has pursued is the development of an Information Warehouse to manage and store all of our publishable data. By drawing together different datasets into a single database, the Warehouse enables the confrontation of statistics from different collections. There has been an increased emphasis on good documentation to support review activity and facilitate dissemination of quality information to users, so they can assess the fitness of the data for the purposes they have in mind. Collection areas are required to include documentation of economic

10 classifications, standards, questions and other metadata on the information warehouse for use by all survey areas in the development and processing of their collections and for possible publication in their own rights. 27. The ABS has implemented case management for large businesses, called Key Provider Management (KPM). One of the primary aims of this approach was to establish a clear focal point within the ABS to resolve any data inconsistencies for a particular business that may arise across a range of data collections. Infrastructure to confront data live across surveys was implemented and data transferred. One of the major achievements of KPM has been the insight provided into a range of data quality problems and has lead to action to address cross-cutting issues. It has also resulted in an improvement in ABS understanding of key providers. 28. The ABS has recently introduced a Quarterly Economic Activity Survey involving the integration of samples, questionnaires, data collection, data processing and data dissemination for three existing surveys into a single survey with the aim of improving the consistency and coherence of these statistics particularly for the purposes of compiling the quarterly national accounts. 29. There has been a focus on increasing the understanding of ABS staff in collection areas of integration concepts and the reason they are important. The ABS has also expanded the use of the interim despatch and collection control facility, including a modest selection history functionality. 30. To take advantage of the current reforms of the Australian taxation system, the ABS is seeking every opportunity to improve the efficiency of our sample designs, and to use taxation data as a substitute for the data now gathered through direct collection. Use of administrative data provides further avenues for data confrontation. 31. An input data warehouse is currently under development aimed at delivering new functionality across our systems. It will provide a managed data store serving analysis, collection activities, research and management needs. It is expected to contribute significantly to provider management, data confrontation, cross collection comparisons and analyses, and analyses using survey and administrative data. Conclusion 32. A requirement for strict comparability of the estimates produced can restrict the scope of the analyses and investigations. As long as the data can be usefully compared, it should be in scope for confrontation i.e. any differences in data reported can be contrasted with the known conceptual and methodological differences in the surveys. Where differences occur, it is important that the

11 reasons for these differences are documented and made available so that users are informed.

12 ESTABLISHMENT SURVEY IN LARGE AND MEDIUM MANUFACTURING INDUSTRY INDONESIAN EXPERIENCE Presented by: Slamet Mukeno and Aminul Akbar INTRODUCTION BPS Statistics Indonesia, is the Agency which responsible in collecting data on basic statistics in Indonesia. BPS has some directorates that responsible in conducting establishment surveys. One of them is the Directorate of Industrial Statistics, which is responsible in conducting surveys on manufacturing sector as well as mining, construction and electricity sectors. The Agency has been adopting the concept of establishment instead of enterprise for its census and surveys. The reasons for choosing the concept of establishment to be used in its census and surveys as follows: 1. According to the concept, the activity of an enterprise can consists of several economic activities such as manufacturing, banking, trading, etc, which make it difficult to classify what is the main activity of that enterprise. 2. The activities of the manufacturing, banking, trading can take place in several different locations (provinces or districts). Considering that the provincial governments in Indonesia need data on the economic activities located in their own provinces, then the available data will be very useful for the purpose of development planning in their respective provinces, such as: the number of labor absorption, kind of economic activities operated in their provinces, amount of value added created by the economic activities, etc. 3. The availability of the data by provinces will ease the Provincial Statistical Office to compute the Gross Regional Domestic Product, and other kind of publications, which are important for the development planning in the autonomy regions. Establishment surveys in large and medium Manufacturing Industry have been conducting since 1969 in Indonesia. The survey methodology has been developed for a long time and has experienced some changes during the period of time. Before 1975, the 1

13 concept of large, medium, small and cottage manufacturing industry was based on the number of person s engaged and machine capacities. Since 1975, because of some difficulties to get measurement of machine capacities, and assuming that almost all of the establishments have machineries regardless their capacities, then the concept has been changed and only consider the number of person s engaged to size the manufactures, as also recommended by the UN. Manufacturing industry is classified into four categories as follows: Classification Number of person engaged Large 100 or more Medium From 20 to 99 Small From 5 to 19 Cottage From 1 to 4 ESTABLISHMENT SURVEYS 1. There are some surveys conducted by the Directorate of Industrial Statistics. In the last three years, which could be specified as follows: Surveys Reference Year Date Release Reference Year Date Release Reference Year Date Release (1) (2) (3) (4) (5) (6) (7) Manufacturing 1997 M a r c h 1998 M a r c h 1999 M a r c h (Annually) Manufacturing (Quarterly) quarterly 2 quarter after quarterly 2 quarter after quarterly 2 quarter after Mining 1997 M a r c h 1998 M a r c h 1999 M a r c h (Annually) Electricity 1997 Feb 1998 F e b 1999 F e b (Annually) Water Supply 1997 Feb 1998 F e b 1999 F e b (Annually) Construction 1997 M a r c h 1998 M a r c h 1999 M a r c h (Annually) Construction (Quarterly) quarterly 2 quarter after quarterly 2 quarter after quarterly 2 quarter after 2

14 2. Manufacturing industry is defined as an economic activity engaged in processing raw materials and transforming them mechanically, chemically, or by hand, into finished or semi finished product and/or converting them into other goods having higher value and closer to the final user. This activity includes establishment engaged in manufacturing services and assembling. a. Sampling Frame a.1. On the manufacturing survey, large and medium size of manufacturing industry is conducted with complete enumeration. Small and Cottage manufacturing industry is conducted with sample survey. In the case of large and medium manufacturing survey, it is important to have an updated sampling frame, since BPS adopting an establishment approach. a.2. The directory as a sampling frame of large and medium establishment industry have been updated every year. The compilation is carried out by: 1. Seeking the new candidates from other sources, such as Department of industry and Trade, Investment Coordinating Board (BKPM), the Chamber of Commerce and Industry (KADIN), Business Association, etc. 2. Matching them with the last year directory 3. Investigating the existence of new establishments. BPS only records the new economically active establishments. 4. Deleting the permanently closed establishments from the directory. 5. Applying a unique identity number for each establishment consists of 15 digits: - 6 digits for area code - 5 digits for ISIC code - 4 digits for serial number 3

15 The scheme of updating directory is as follows: Observation Last year Directory Matching Other sources: BKPM, KADIN, Ind & Trade Depart., etc -Temporarily in active -Re-activated Closed Permanent ly Adding new Candidates Candidate(s) was (were) not matched with our concept & definition Field Investigation Adding for Directory Inappropriate condition PRELIMENARY DIRECTORY (Economically Active Establishments). FINAL DIRECTORY b. Scope and Coverage b.1. Up until mid 70s, BPS-Statistics Indonesia conducted a sample survey on Large and Medium manufacturing industry. The sampling procedure adopted was a cut off sampling. All large establishments were covered in the sample, while for the medium establishments were sampled with a certain number of minimum sample size. There were several kinds of industries with quite large number of establishments such as; rice milling, saw mills, weaving mills, with approximately each of the industry producing relatively homogenous products. Hence we can reduce the number of establishments that have to be surveyed and definitely reduce the survey budget. Unfortunately, by adopting this system, we were not be able to make estimate by region (Province). We can only make the estimation at national level. This is one of the reasons why BPS has to adopt a 4

16 complete enumeration for the establishment survey since then, so that we will be able to produce the result by regions. The result by region (Province) is required by the provincial governments to know the potential of its economic activities. b.2. The industrial classification adopted in the manufacturing industry survey is the International Standard Industrial Classification of All Economics Activities (ISIC). Currently we adopt the ISIC revision-3 in our publications and modified according to the local condition in Indonesia (so called the KLASIFIKASI LAPANGAN USAHA INDONESIA or KLUI). The 1999 publication includes 351 manufacturing sub groups starting from to The main product (in term of its value) is used to determine the ISIC of the establishment. However, if a certain manufacturing establishment produces two or more kinds of products having the same value, the main product is determined by the highest quantity. c. Survey Operation, Processing and Dissemination c.1. Establishment surveys have been conducted by delivering questionnaires to the target respondents, which are recorded in the directory compiled by the BPS-Statistics Indonesia. Some surveys have conducted by direct interview with the respondents, the others have been conducted by mailing system, and the rest could be combining. In the case of the large and medium manufacturing industry survey, it has been conducted by delivering questionnaires to all large and medium manufacturing establishments. This survey is conducted by applying complete enumeration approach. c.2. There are some problems faced in the survey. The three main problems are Response Rate, Timeliness and Data Quality. BPS-Statistics Indonesia through Directorate of Industrial Statistics has made the system to monitor the survey so called KABSIS (KABUPATEN SISTEM or Regency system). The purposes of the system are to improve Response Rate, to accelerate questionnaires receive, to improve the quality of filled in questionnaires, and to encourage field s responsible ness in the District s offices to monitor the survey in their own areas. 5

17 The implementation of KABSIS is to distribute the jobs based on the capacity of the surveyors, to differentiate for handling between the difficult and the ordinary establishments, means that the difficult respondents/establishment should be handled by higher ranking personals/staffs. The number of visits of the enumerators will be recorded in the computer on the KABSIS software. Some of the information which can be monitored are the number of establishments visited by the surveyor, the number of establishments response, the number of difficult establishments that already response, and the number of questionnaire that already valid. The rests are the difficult establishments and need to be revisited. c.3. Non-sampling error such as human error can arise in any statistical activity. The error might come from the enumerator and/or the respondent. Because of that reasons, the enumerators, before conducting the survey usually get training on how to manage the survey and how to understand the questions in the questionnaire. On the respondent side, unclear concept and definition can create a non-sampling error. However, if the error still comes out, like an inconsistency of the filled in data on the questionnaire, the enumerators have to revisit the respondent and ask the establishment to make corrections. c.4. When the enumerator or our District Office receives the questionnaire from the establishments, usually they validate the quality of the data. There is a summary page where they can check the validity of the data. We do not validate the data with that of the profit and loss statement of the establishment. We will accept the data as long as the data are consistent between the intermediate input and its output and seems reasonable. According to our Statistical Law, the establishments are obliged to answer the question from BPS, and as long as the data are reasonable and consistent there is no reason for us to ask more to the establishment. c.5. The questionnaires of the annual survey will be processed at the Regional Offices. Each Regional Office has the same software, whether for the data entry or for the tabulations. For the data entry the software used on the processing is the Clarion, and for the output tables is SAS. The processing for the kind of raw materials used and 6

18 commodity produced will be processed at the Central Office. Therefore the regional offices should send the processed data (mostly in value term) to central office by using e- mail or diskettes and also the filled in questionnaires to the head office for further data processing. c.6. The main users of the manufacturing data are Bureau of National Accounts, Department of Industry and Trade, National Planning and Coordinating Board and other local data users as well as international institutions or agencies. BPS disseminates the data either in soft or hard copies. The publications are Large and Medium Manufacturing Statistics (published in 3 volumes), Directory of Manufacturing Industry, and Large and Medium Manufacturing Indicators. d. Quarterly Survey and Linking Census, Annual and Quarterly Surveys d.1. Practically BPS conducts a complete enumeration survey for large and medium manufacturing industry every year. The result of the annual survey had been used as a sampling frame for quarterly survey. This sampling frame is updated every (around) 5 years based on the result of the annual survey. d.2. BPS has been conducting the quarterly survey after the Industrial Census The result of the Industrial Census was used to determine the important industries based on their share to the total value added created by the manufacturing sector. BPS selected some big companies, which created about 75 percents to the total value added of the manufacturing sector. The survey was aimed to compute the growth rate of the manufacturing sector, therefore we only ask simple questions to the establishments to give us the quarterly production and its value to be used as the weight for calculating the index of production. The index of production is mainly used to estimate the growth rate of the quarterly GDP of this sector and for other development planning purposes. 7

19 e. Data Providers and Data Users Forum BPS has socialized the Statistical Law to the establishments in some regions several times. We provide them with information on leaflet or booklet containing some data such as: Number of large and medium establishments, number of labor absorbed by manufacturing sector; value added, etc, by 2 digits ISIC, inflation rate, number of population, etc. We also conducted seminars where the data providers and data users attending the seminars. Unfortunately they are not very interested as we can see from quite small number of participants attending the meeting or seminars. We do believe that if they can trust the statistical agency like BPS and give us the actual data, the quality of our data can be improved and become more accurate. That in turn will help the data providers and consumers to obtain advantages from the available data for their business planning activities. f. Other Issues Many time BPS get complaints from the establishments, because of the complicated questions asked and why BPS conducts several surveys such as: annual and quarterly manufacturing industry surveys, and also the Wage survey where some of the sample are in fact the same manufacturers. Furthermore, other government institutions also conduct a certain kind of survey for their own purpose, which make the firms complaint why there is no such coordination between the government agencies in term of data collection. In this case we should explain to them that the purpose of the surveys are different and the government need to get information for the development planning in many aspects so that we need their cooperation and understanding. g. Surveys in the Countries of ASEAN There are some multi national corporation manufacturing industries have their units of production in several countries. One can take an example of an electronic industry. The components are produced in different countries and assembled in another 8

20 country. This kind of system probably one of the most efficient system and will get the cheapest price because of a certain competitive advantage in international market. With this kind of condition, we think that we need some kind of cooperation in the sense that the statistical agencies in each country can communicate and helping each other when they get difficulties to obtain data of a multi national corporation. At least the country where the head office is located can help to get the required data. As an illustration, suppose there is a computer industry producing some of its parts in Indonesia and other parts in Malaysia and the head office is located in Singapore. BPS-Statistics Indonesia can only get the data on the quantity of the production, but not able to get data on the value of production. The reason is because the manufacturer in Indonesia does not know the value of the commodity produced in Indonesia and only the head office in Singapore who knows the value of that product. In this illustration, Indonesia is not able to calculate the value added created by that manufacturing industry from the production side. The value added actually can be obtained by adopting an income approach, but the data on taxes and profit are even more difficult to be obtained. Therefore, we think that this kind of such cooperation might help to improve the quality of our statistical data. 9

21 Lao people s Democratic Republic Peace Independent Democracy Unity Prosperity Country Paper On status of Establishment/Enterprise Survey In Lao PDR Workshop on Establishment/Enterprise Survey 14 to 18 January 2002 Chiang Mai Province, Thailand January 2002

22 I. Introduction. Lao PDR. has a decentralized data collection system as well as statistical survey, in order to compile and provide official data for the government and international organization. Therefore, government has set up the National Statistical Center (NSC) under Committee for Planning and Cooperation to assume the responsibility for the collection and dissemination statistics data and also being the coordinating agency in the areas of the statistical activities in Lao PDR. In fact, our country has a number of different agencies and projects, which are directly responsible for compiling and collecting specific data. However, in most sectors such as information is limited, fragmented, and generally of limited reliability. II. Recent trend and status of Establishment/Enterprise Survey in Lao PDR. The National Statistical Center, under the sponsorship of the SIDA, were conducted the Establishment/Enterprise Survey in Lao PDR in the years 2001, this is pilot survey where conducted only in 4 provinces. The Establishment Survey was harmonized with the Business Tendency Survey. Survey Design. The National Statistical Center has conducted Establishment Survey in July-August 2001 with the propose in order to have of basic information on Establishment Survey in Lao PDR. Questionnaire The volume questionnaire is 12 pages including the cover sheet. The cover sheet is content the name of the Establishment and tax identification number and contact address. The questionnaire had consisted of 12 items variables as following: i) Economic activity ii) Date of operated business, iii) Legal organization iv) Institutional unit v) Ownership vi) Economic organization vii) Book keeping status viii) Employment ix) Total revenue x) Expenditure on input/cost ( current expenditure and expenditure on fix capital formation) 2

23 xi) xii) Changing in stock Tax, tariff payment and subsidies received Sample design In the past we conducted 2 surveys on Establishment/Enterprise, but there were not good enough, because of the register is poor and not have been up-dated yet, the list name of the companies, manufactories and enterprises getting from tax department, tax offices in provincial and Economic line Ministry (Statistics sector). The list is not clear and very difficult for conducted sample design. Therefor, we have experience from the past 2 surveys, therefore this survey in 2001is conducted as pilot on Establishment/Enterprise Survey and we have updated the sample frame to be more accurate, the pilot survey have been selected only 4 provinces for conducted (1 province in Northern, 2 provinces in Central and 1 province in Southern). The Establishment/Enterprise Survey were conducted in differences sectors such as: Agriculture, fishery and Forestry, Industry, Construction, Transport and Communication, Trade, Services. Referring to the currently economic situation, in order to conducted the survey the sample size were selected all big, middle and small units for interviewed. The total of sample size is 1862 units. Training and fieldwork - Duration of the training for fieldwork was 5 days ( 4 days in the class and 1 day for practice) at the National Statistical Center. - The fieldwork started from beginning to the end of July, the survey carried out by using the enumerators(interviewers) which directly visit each sample unit and interviewed, the questionnaire response by managers or directors of sample units. Data Processing - All questionnaires send to the central, checking, coding and data entry was spend for 2 weeks - 1 week for data editing and - 2 weeks for tabulation SPSS software were used for data entry. 3

24 Response Rate Sectors Sample size Response Response Rate Forest % Industrial % Construction % Transport and Communication % Trade % Services % Problem The response rate show that more than half were non-response in Forest sector, Industrial sector were non-response 20%, Construction sector were non- response 39%, More than half were non- response in Transport and communication sector, Trade sector were non-response 34.9%, and Services sector were non- response 25.6%. The concerning issue was: - The register is not good enough and not yet up-dated - Moving and can not find the location - A lot of units was closed - Some units refused and no co-operated with enumerators - Insufficiency of fund to carry out the survey Future activities. For the purpose of National Statistical Center plans to carry out the annual sample establishment survey. For doing this priority activities are: - Create the complete system of registration - Improve the sample design and frame - Upgrade skill of the staffs in the field of survey - Developing relationship between statistical office and unit of the companies, enterprises, manufactories and establishments in term of data collection. 4

25 Conclusion Under funded by SIDA, the National Statistical Center were conducted the Establishment/ Enterprise Survey in 2001, it is pilot survey and conducted only 4 provinces, about 1862 sample units were selected. The survey result indicated the situation of the business in the pass, currently and future and able to evaluate progress of business in the country. The establishment survey conducted in 2001 by NSC. Although the survey covered all enterprises and establishment in the 4 provinces, but the result not yet complete and we are doing the tabulation and prepare reporting. This paper provides briefly overview of the Lao Establishment / Enterprise Survey. Through the experiences from this particular survey we found that, the NSC need more to strengthen the capacity on the Lao Establishment / Enterprise Survey in order to providing the accuracy information. Therefore, I hope this workshop on Lao Establishment / Enterprise Survey will fruitful experiences that we would utilize for our next Lao Establishment / Enterprise Survey. 5

26 Workshop on Establishment/Enterprise Surveys Chiang Mai; January Jan 2002 Mat Noh Bin Hussin Department of Statistics, Malaysia Construction and Real Estate Survey 1. Introduction The Construction survey was first conducted by the department in the year Meanwhile, the first census for the Real Estate was conducted eight years later. The on-going Census/surveys are conducted at different frequency i.e. the Construction survey was conducted annually until 1996 and thenceforth it was conducted biennially, whereas the Real Estate survey was conducted biennially since it started. 2. Objective The main objectives of the surveys are to collect information pertaining to growth, contribution, composition and distribution of the industries to assist the government in formulating policies and for development planning. The private sector and individuals can also use the data for specific purposes such as for economic projection and analysis. 3. Scope and Coverage 3.1 Construction Survey Before reference year 2000, the Census/survey of Construction sector covered all industries as classified under Malaysian Industrial Classification (MIC) 1972 updated 1979 (based on ISIC Rev. 2). Since reference year 2000, the new Malaysian Standard Industrial Classification (MSIC 2000) was introduced and applied to all establishment and enterprise surveys/ Censuses. The new MSIC was constructed based on ISIC Rev.3. Under the New MSIC, Construction sector covered all units mainly engaged in constructing buildings, roads, railroads, electricity or other transmission lines or towers, pipelines, oil refineries or other specified civil engineering projects. In general, units mainly engaged in the repair of buildings or of other structures are also included in this category, as are those engaged in the alteration or renovation of buildings, preparation of sites, demolition or excavation. Unit mainly engaged in providing special building or construction trade services such as structural steel erection, carpentry, bricklaying, concreting, plumbing, plastering,

27 floor and wall tiling or roof tiling and the installation or laying of floor coverings such as carpets or linoleum, are also included in this category. 3.2 Real Estate As mentioned in paragraph 3.1, for reference year 2000, the Census of the Real Estate covered all units mainly engaged in Real Estate Activities with Own or Leased Property and Real Estate Activities on a Fee or Contract Basis. In general, units mainly engaged in the developing and subdividing real estate into lots, development and sale of land and cemetery lots are also included in this category. Units mainly engaged in buying, selling, renting and operating of self-owned or leased real estate such as land, apartment buildings and dwellings, non-residential buildings, apartment hotels and residential mobile home sites and for others on fee or contract basis, real estate management and maintenance and other real estate activities on fee or contract basis are included in this category. However, units mainly engaged in activities such as development on own account involving construction, which are classified under Building of complete construction or parts thereof; civil engineering (classified under construction), and Operation of hotels, camps, trailer camps, and other short-term lodging places, which are classified under hotel industries are excluded. 4. Survey Methodology 4.1 Construction Since the first census was canvassed, the methodology of data collection varies from time to time. The full census of establishments covered since the first census was conducted for reference year 1963 until reference year The background of this methodology data collection can be summarized as below: - Ref. Year Methodology Coverage 1963 to 1979 Census All establishments (Pen. Malaysia) 1980 Census Value of work done < RM 100,000 (Malaysia) 1981 Census Value of work done > RM 100,000 (Malaysia)