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Demography Of Small and Medium Enterprises

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Frequently Asked Questions

( on PECO and DOSME panel projects)

 

CONTENTS

What do PECO and DOSME actually mean?
What is the main objective of the project?
When and how was the project started?
What is the relation between PECO and DOSME?
Which countries are involved in the project?
Who are the main partners in the project?
What is the basic set of questions on the questionnaire?
What is the size of samples and how is the sample selected?
How many surveys have been carried out?
How are the surveys carried out?
What is the logic of survey data processing?
What types of software products are used?
Which imputation method has been applied?
What data sets have been produced?
What types of analysis can be provided?
How the longitudinal data base looks like?
What publications have been prepared?
Where are the publications available?
How the transfer of knowledge worked?
What is the aim of Working Group Meetings?
When and where were the WG-Meetings held?
What types of training session were held?
What seminars have been organised?
What are the communication channels, how the communication works?
How is the project documented?
How is the Web site of the project organised?

What do PECO and DOSME actually mean?

PECO is an acronym from French „Pays Europeannes Centrales et Orientales“, that is, Central and Eastern European Countries. The first “PECO Panel” project was designed to look at the development of businesses in these countries. The name for this grouping of countries was changed to “Central European Countries” or CECs during the project. Thus CEEC and CEC mean the same thing. DOSME stands for „Demography of Small and Medium Enterprises in Central European Countries“.

What is the main objective of the project?

The main objective of the “PECO Panel project of newly created enterprises“ was: the establishing and observing the enterprises existing in the participating countries in order to obtain data on the size and characteristics of the active enterprise population and its development. Asthe panel had to be established on the basis of business registers of the national statistical institutes, analysis of the quality of register was included into the main aims of the project.

Besides that the project was designed to teach the participating countries the methodology of sample surveys, experiencing the whole life-cycle of a panel survey within a large multi-national project. The transfer of knowledge and development of skills was concentrated in such way that the CECs will be able to continue the panel of newly created enterprises independently in the future and apply the methods to other areas of enterprise statistics. The knowledge and skills that have been developed include panel methodology and statistical methods such as sampling, imputation, estimation and grossing-up.

When and how was the project started?

The idea of the project emerged from the seminar on "Business registers in statistical practice" which was organised by the statistical office of the Czech and Slovak Federal Republic in Bratislava in November 1992 with support from the French INSEE and Eurostat. In working out a technically feasible project and to implement it Eurostat also agreed to provide substantial financial aid under the multi-country PHARE programme.

After a long period of preparation, the first PECO survey started in September 1995. The first survey on the units existing at 1 January 1995 was followed by two annual surveys on newly created enterprises and by a follow-up panel survey after two years. During these three years all participants have gained experience in designing panels, sample surveys and imputation.

What is the relation between PECO and DOSME?

Project PECO was carried out in years 1995-1997. From methodological point of view the DOSME project is a continuation of the PECO Panel Project. Also the previously created databases have been utilised in the process of analysing the survey results.

One of the products of the PECO project has been the calculation of preliminary estimates of the creation of enterprises since the beginning of transition and their characteristics. The results are very valuable, because, for the first time since the fall of the Berlin Wall, the impact of the transition on the emergence of new production structures has been quantified and the data for the different countries are fully comparable. The importance of the data has been widely recognised: the demand is large and the press coverage of the first publication of results was remarkable. Insight in the quality of the national business registers was another output of the project.

The success of the panel project made it possible to take a next step in creating the conditions for good enterprise statistics, which is particularly important for those countries that need to present reliable and harmonised information on their economic structure prior to entry to the European Union (EU).

Thus the DOSME project has been introduced, wherein the main issues to address in the coming years were set as follows:

1) There is a high demand for a follow-up of the introduction to statistical methods concerning enterprise panels provided in recent years. Such a follow-up should be aimed at building the ability to apply those methods without further support and at extending the expertise to other areas of statistics.

2) After the development of the business registers in the CECs and the measurement of their quality it is now time to use these registers more extensively as the basis for surveys and to further develop their co-ordinating role in the production of economic statistics, especially macro-economic statistics culminating in national accounts.

3) There is a clear need for a follow-up of the initial panel in order to obtain a longitudinal database which covers in particular small and medium enterprises (SMEs) and which will provide key information on the transition process. The value of such a database will be significant for policy makers and other users inside the EU, in the CECs, and elsewhere, since it would contain data essential to many macro-economic statistics including national accounts, information about the growth process of enterprises, data for employment analyses, etc.

Which countries are involved in the project?

The following countries participated in the project from the beginning: Albania, Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Rumania, Slovakia and Slovenia. In 1998, the Former Yugoslav Republic of Macedonia (FYROM) joined the project.

Who are the main partners in the project?

The project is co-ordinated by Eurostat and experts from EU countries (France, UK, Netherlands and on occasions from Finland and Denmark) also contribute to the project. The international data processing is provided centrally in Infostat where also a standard set of documentation is kept and maintained. The working group of the participating countries has met twice a year and also some training sessions and other special working sessions have been held.

What is the responsibility of partners?

The main responsibilities of participating partners can be briefly outlined in key words.

EUROSTAT

INFOSTAT

COUNTRIES

Project management
Budget co-ordination
Methodology
Documentation
Result data analysis
Data distribution
Publication
Processing management
Communication with countries
Sample creation
Processing statistical tables
Entry package preparation
Result file processing
Imputation of missing data
Documentation
National survey management
Applied methodology
Sample selection
Questionnaire preparation
Conducting the survey
Data entering and checking
National central processing
Analysis and publication

What is the basic set of questions on the questionnaire?

For characterising the data scope of the project we can have a look at the structure and contents of the basic questionnaire for yearly surveys B (which differs only slightly from the questionnaire used in the first survey A and in the follow up survey C).

It has 3 chapters, each with modules of one or more questions. It begins with a mailing window and end with a return window.

First chapter: Identification of the enterprise

includes one module with these 7 questions:
Name
Address
Identification number
Telephone
Fax
Trading name
Legal form

Second chapter: Current position of the enterprise

includes 10 modules:
1) State of activity
2) Condition of cessation
3) Composition of capital
4) Number of local units
5) Employment
6) Characteristic word of activity
7) Main products
8) Description of activity
9) Evolution of activity
10) Bookkeeping condition

Third chapter: Starting and development conditions

includes 8 modules:
11) Characteristics of founder
12) Date of registration
13) Starting date
14) Origin of the enterprise
15) Starting capital
16) Investment
17) Demand side difficulties
18) Offer side difficulties

How many surveys have been carried out?

Each survey has a code:

A: initial survey of stock of businesses registered up to the end of 1994
B1: Newly registered businesses in 1995
B2: Newly registered businesses in 1996
C1: Follow-up of A and B1 surveyed units
B3: Newly registered businesses in 1997
B4: Newly registered businesses in 1998

The characteristics of the surveys are:

A1 1995 - first and unique, large starting survey 1995, units selected from years <90, 90-94, first questionnaire, about 50 questions
B1 1996 - some changes in comparison to the A, new questionnaire that became the regular yearly questionnaire
B2 1997 - no basic changes in the questionnaire
C1 1997 - the first follow up, with C questionnaire, the first longitudinal data base, complications with units surveyed first with questionnaire B2 or repeatedly with C; new feature: B2 and C1 provided in the same year
B3 1998 - new project, the questionnaire as the standardised B
B4 1999 - standard questionnaire B

What is the size of samples and how is the sample selected?

The calculated and allocated sample sizes of survey B4 characterise the average sample sizes in the standard yearly B surveys. In the initial survey A, the sizes were 4-5 times higher. In the follow up survey C1, the sizes were dependent on the number of units still active from previous surveys A and B1.

Country

Legal

Natural

Total

Albania

550

850

1400

Bulgaria

800

950

1750

Czech Republic

1000

1000

2000

Estonia

900

400

1300

Hungary

750

1050

1800

Latvia

950

650

1600

Lithuania

800

950

1750

Poland

1000

1000

2000

Romania

1000

1000

2000

Slovakia

950

1050

2000

Slovenia

700

700

1400

FYROM

1000

1000

2000

DosmE

10350

10650

21000

The real selected sample sizes (as the sum of selected units in small strata) were different by plus or minus 2-5 units due to the random character of selection.

How are the surveys carried out?

The logic of surveys can be characterised by a review of tasks at central and national level.

CENTRAL LEVEL NATIONAL LEVEL

Questionnaire design (adaptation)

Sample package preparation

Creating Sampling base

Generating statistical tables

Checking Statistical tables

Finalising sample sizes

Allocation package preparation

Sample allocation, fraction generation Sample selection

Generating statistical tables

Establishing working groups

National version of questionnaire

Adapted national documentation

Matching Sample with Register

Generating tables and transfer files

Addresses of survey units

Data entry package preparation

Starting the Survey

Mailing questionnaires

Conducting the Survey

Training the staff

Interviewing respondents

Entering data from questionnaires

Manual and automatic checking

Reporting on survey progress

National central processing

Result file creation and transfer

Result checking package

Result file checking and correcting

Creating the Central data base (CDB)

Imputation package distributed

Imputation of non responses

Analysing result data

International publication

National analysis and publication

Register quality measurements

What is the logic of survey data processing?

The sequence of treatments for survey data processing has been defined as follows:

a) National level

1. Entering the dates of questionnaire reception

2. Manual control and coding

3. Entry and entry validation

4. Automatic control (next step if correction needed, otherwise do the final step)

5. Manual correction and validation

6. Entry of correction or validation (after that go back to 4)

7. Final preparation of transfer file in national central office

We can see that items 4, 5 and 6 are connected in a cycle. In other words, the automatic checking and the manual correction and validation process is iterative.

b) International processing

Tasks and procedure of central processing can be grouped into two major sets: 1) checking and correcting the result files, 2) creating the Central data base (CDB) and the process of imputation. In the following paragraphs we will simple list these tasks and procedures just to illustrate the complexity of provided works.

A. Checking the result file

a) Formal and range checks

1. Manual/visual checking of the result file

2. Range check of variables

3. Checking the completeness and correctness of variables on activity codes

4. Completing and correcting the result file

b) Checking of errors, anomalies and non responses

1. Running the adjusted program for record checking

2. Running the program for file checking

3. Correcting correctable errors, otherwise send the file back to the country

4. Generating the output table on characteristics of the final result file

B Creating the CDB and the process of imputation

a) Creating the CDB

1. Sorting and converting working files

2. Computing final control variables and non responses

3. Merging the result file with transfer file containing data from sampling base and from the register

4. Creating a record description of the central database and converting the file into a standard database file (dBase4).

b) Auto-corrections and imputations

1. Running the program for auto-corrections

2. Recalculating the non responses

3. Generating an output table for deciding the strategy of imputation

4. Generating auxiliary output table showing the variables that need imputation

5. Exercise the imputation of active units with partial or full response

6. Provide global imputation, i.e. the imputation of active units indirectly controlled

What types of software products are used?

For checking and analysing the statistical (counting) files and for analysing the CDB mainly MS Excel and SAS are used at both level of data processing.

The data processing packages have been created in Infostat. Here is a short review of them.

PACKAGE USED SOFTWARE NOTES

Sample Clipper Integrated package, menu driven

Allocation Pascal Tailor-made programs and utilities

Data entry Blaise, Pascal, Delphi Entry program written in Blaise, checking programs in Pascal, Menu shell for Windows in Delphi

Result checking Manipula, Pascal Manipula programs and Pascal utilities

Creating CDB Pascal Own special programs and utilities

Imputation Pascal, Delphi DOS version written in Pascal, Windows version written in Delphi (including an SQL module)

Which imputation method has been applied?

Assessing the character of data on the questionnaire from methodological point of view the hierarchical hot deck method was recommended and chosen. Then there was nothing to do than design and create a specific application.

Let us have a look at the defined and used principles of imputation by hierarchical hot deck method.

We distinguished independent and dependent or hierarchical variables. The defined types of hierarchical variables were primary, secondary and tertiary. We say that a variable is secondary if it comes after a switch question (or variable). Tertiary variables are then related to the secondary ones.

The stratification variables were defined in this way:

a) Country code CC

b) Unit Type (natural/legal) RD3

c) Zone code (urban/ rural) PD6

These variables were mandatory while other characteristics could be added for imputation of specific variables:

d) Registration period (year) RY

e) Condensed activity code R02

f) Broad Size Category RD4

We were imputing both item or partial non-responses and unit or global non-responses of active units

First principle

Strictly respect the order of variables in the process of imputation. We start imputing tertiary variables, then secondary ones and finally first rank variables.

Second principle

When we impute a value of secondary variable, we impute in the same time all the tertiary variables linked to this secondary variable. The same is valid when imputing a first rank variable.

Third principle

Values of imputed variables come from another unit with same characteristics. The population of possible donors is automatically selected by value 0 of a control variable V-ACXX while the value 1 automatically gives the population of units that need imputation.

Fourth principle

In order to get better results we will select the donor in sub population as homogeneous as possible with the known characteristics of the unit.

Fifth principle

For each unit the donor unit for imputation of one variable (or group of variable) will be selected randomly in the sub population of donors. One donor unit can be used for imputation of only one unit

Limits in definition of sub populations at the first approximation were taken from French experiences:

a) size of sub populations of donors must be > 10

b) proportion of units needing imputation must be < 30%

For having information to define the optimal choice of criteria for definition of sub population of donors for each variable, analytical output tables were generated. Also tables were produced to show the distribution of donors and acceptors for the imputed variables. Such tables can be generated in any good table generator, spreadsheet or statistical analytical package. In our case, these tables are generated by tailor-made programs.

What data sets have been produced?

We can consider the basic data types according to the following groupings: space, time, content. Then the variety of contents of data can be outlined by some related notions as subject, observation and calculation.

The basic file types can be outlined according to the level of observation indicated above and processing in the following way:

National level

enterprise register
sampling base
initial survey file
survey administration file
data entry file
statistical tables (counts)
on sampling base
on sample image in register
on register at reference date
allocation parameter file
transfer files
register image of enterprises in the panel
survey result file
central data bases
longitudinal data bases
aggregated (analytical) data sets

Central level

statistical tables (counts)
on sampling base
on sample image in register
on register at reference date
transfer files
register image of enterprises in the panel
survey result files
sample allocation files
counting and calculating files
sampling fraction files
allocation parameter files
central data bases
longitudinal data bases
aggregated (analytical) data sets

We have marked withitalics those files that are present only at the given level. For example, the sampling base is always present only at the national level and the counting and calculating files are always present only at central level. We can see that the majority of files are present at both levels. However, at central level they are multiplied not only by years but also by countries.

This simple list well illustrates that, even at the national level and within one survey, we have to deal with many files. After five finished surveys the number of files will be much greater and we need a logical grid to view them properly.

What types of analysis can be provided?

Some files are primarily devoted to analytical purposes while some others can also be used for analysis. Some new files can be prepared from existing files.

Here we outline the character of the central database as the final survey result and its possible analytical exploitation.

Let us start with outlining the basic or standard contents of our central data base file (CDB). We have the following groups of data in the file:

Enterprise identifier in the Panel
Data in sampling base
Data in register on first of September
Direct results of survey
Derived direct results of survey
Management data of Survey
Corrected or imputed results of survey
Analytical auxiliary variables
Intermediate auxiliary variables

Besides the identifiers, management and auxiliary data the central database contains three major groups of data:

data from the register (sampling base, register at reference date)
data as survey results
imputed survey results

Considering the differences between these groups of data and the basic structure of the questionnaire we can provide the following types of analyses:

structural analyses (numbers of units)
some quantitative data about enterprises
profile of entrepreneurs
problems in developing the enterprise
quality of the register.

Nearly all of these possible analyses are prepared regularly for our international publications and countries are also providing some of them for their national publications.

Here we are just trying to briefly characterise all of the possible analytical approaches in more detail.

1. Structural analyses

Considering that in the national imputed central database each record contains the weight of the enterprise, we can generate a lot of estimates for the whole active population. Of course, we can use both weighted numbers and percentages. The main groups of variables that can be utilised for structural analyses:

basic type of units (natural person, legal person, UnitType)
legal forms of enterprises (ILegForm)
size category of enterprises according to the number of employees (ISizeCat, RD4)
main activity codes (Nace3 or Nace3 in 2 digits (INace3)
condensed activity code (ICondNac), super condensed activity code (RD2)
rural or urban zone (PD6).

2. Quantitative data about enterprises

First of all we can analyse the number of workers (ISumWork) and the number of local units (ILocNumb). From these data we can calculate categories and averages. However, data about workers can be analysed also according to the types that are present on the questionnaire.

We can consider as quantitative also data on capital conditions of joint stock companies and limited liability companies because the quantitative aspect is included into the question in percents.

3. Profile of entrepreneurs

From characteristics of the sole proprietor or main manager of the enterprise we can analyse the profile of entrepreneurs. The related questions are:

sex
year of birth
educational level
professional qualification
at home business.

The question on the type of enterprise creation can be included also in this block.

From the year of birth we can calculate age categories that can be used in the process of further analyses.

Sex, education, profession and age we can correlate also with condensed activity code or super condensed activity code, with categories of the number of local units, etc.

4. Problems in development

Two blocks of questions have been devoted to this problem:

offer side difficulties, i.e. difficulties in selling products or services
demand side difficulties, i.e. difficulties in developing the business activity.

Also the question on type of enterprise creation can be included into this analytical block.

In analysing the related questions it is important to realise that they are constructed as hierarchical ones, or in other words, as secondary and tertiary (while the primary question is always the questions on activity of the enterprise). That means, that first we can get figures on having problems or not, and then we can get the percentages on the distribution of existing problem types. This comment on analysing hierarchical data is valid for all other not independent (secondary and tertiary) questions (reason for cessation and control of investment).

5. Quality of the register

First of all it must be stressed that while the previous types of analyses can be provided both at national and central level, analysing the quality of the register is a business at the national level by the definition. We have not enough information on how this kind of analyses has been carried out in countries.

The basic factors of the quality of registers can be outlined as follows:

correct identifiers
correct classifications of activity
good scope of registered population
up to date demography of the most important units

In the process of quality analyses some considerations and rules have to be taken into account:

we must work with original, not imputed survey data
only variables that are present both in the register and in the survey can be utilised
the sub-population of units must be carefully defined (active, unit type, legal form, etc.)

According to these considerations we can provide the following basic analysis:

correctness of identification data in the register (answers to questions 1-6 in percent)
correctness or identity of national activity code (comparing the answered activity code with the registered one, eventually revising the assignment of national activity code in the original entry database)
comparing other register data and survey data (NACE in 3 digits, condensed activity code, legal form, size category, etc.).

How the longitudinal database looks like?

Here is a short comparison of the contents of our first longitudinal database and the standard central database in their data groups.

Longitudinal data base Central database

I. Surveys A and B

Enterprise identifiers in the Panel Enterprise identifier in the Panel
Auxiliary record and sub-file identifiers
Data in Sampling base Data in sampling base
Data in register at ref. date 1995/1996 Data in register on first of September
Corrected/imputed results of A and B Corrected or imputed results of survey
Analytical auxiliary variables Analytical auxiliary variables
Intermediate auxiliary variables Intermediate auxiliary variables
Direct results of survey
Management data of Survey

II. Survey C

Data in register at 1st September 1997
Corrected and imputed variables of survey C
Analytical auxiliary variables
Intermediate auxiliary variables

Besides the difference inAuxiliary record and sub-file identifiers, there are two important differences. The first is that the longitudinal database does not contain data groups ofDirect results of survey andManagement data of Survey. The second difference can not be seen in the above listed comparison. While CDB files for survey A and for standard B surveys contain both direct survey data and imputed data, the primary CDB file for survey C contains only direct survey result data but there are no corrected and imputed data in it. It is obvious because the survey C results have been imputed within the longitudinal data base frame where in some cases also the data from A and B1 have been re-imputed. That is why the longitudinal database cannot simply replace the original or source databases. It is not a copy or a simple combination of the survey result databases.

What publications have been prepared?

Two basic types of analytical publications have been prepared:

international (containing data for all countries, basically in English)
national (containing the data of country only, in nation language).

The basic publications from the project are:

Survey A summary publication - the main points from the survey A, produced a year after the survey reference period;
Survey A detailed publication - in-depth analysis of results for survey A, produced two and a half years after the survey reference period (note that this is a long publication that is available only in electronic form);
Survey B1 publication - the main information from survey B1, including some comparisons with results taken directly from survey A;
Survey B2 publication - the main information from survey B2, including some comparisons with results taken directly from surveys A and B1;
Survey C1 publication – information on changes in businesses from 1995 to 1997 and from 1996 to 1997, taken from survey C1

Where are the publications available?

The publications are available for public at these sources:

in official printed publications of Eurostat
on the web site of the project in electronic forms.

References to Eurostat publications:

Enterprises in Central and Eastern Europe, Office for Official Publications of the European Communities, 1996
New enterprises in Central and Eastern Europe in 1995 (Supplement 3, 1997, of the distributive trade and services series)
New enterprises in Central European Countries in 1996, Office for Official Publications of the European Communities, 1999
Enterprises in CEC: 1995-1997
New Enterprises in Central European Countries in 1997

How the transfer of knowledge worked?

The main aims of the project, i.e. a) teach the CECs about sample surveys and panel surveys and b) establishing an international longitudinal data base on the transition process have been fully achieved.

Besides that we can outline some experiences of countries gained from the project in several fields.

A. Methodology of sample surveys and panel surveys

using a permanent random number in Bernoulli sampling
the importance of sample allocation in a stratified sample survey
using variables characterising the state of activity of units both in surveys and in the register
using survey management data in data entry files

B. Organising sample and panel surveys

the existence of a steering committee or a co-ordination team is absolutely necessary
thenecessity of having involved into the project equally managers, statistician, informaticians and field workers
a consistent project documentation is necessary and preferably it have to be kept on computer files

C. Managing the field-work of panel surveys

in sample surveys mailing the questionnaires is not enough, reviewers also have to be involved
involving reviewers also in indirect control of existence of units and identifying the state of activity of units
instead of a simple data entry using a consistent entry package containing also record checks, file checks, table generations and so on

D. Editing and imputing sample survey data

there is a close relation between auto corrections and the imputation process
a review of various methods of imputing and choosing the suitable ones
experiencing the hot deck method of imputing missing data within a tailor-made software package

What is the aim of Working Group Meetings?

The working group meetings are devoted to the following main problem areas:

reporting on provided works
planning future actions
discussing methodological issues
co-ordination and communication

The provisional agenda of the meeting was always prepared in advance and was distributed to all participants. Besides that nearly all working papers of the meeting are prepared in advance and distributed before meeting via e-mail or published on the project web site.

As an example here are listed the main topics discussed at 3rd Working Group Meeting in Brasov (April 19999):

Progress on survey B3
Report on B2 and C publications
Review of imputation work for B3 survey
Planning issues for B4 survey
Making population estimates
Proposals for the second DOSME project.

The progress report on central processing in Survey B3 prepared and presented by Infostat can also be shortly characterised by its contents:

Sequence of tasks in central processing:

Receiving result transfer file
Checking and correcting the result files
Creating the central data base
Revising the imputation process provided by countries
The new imputation package

Modification of sampler package

Other issues (corrections, communication, working meetings).

When and where were the WG-Meetings held?

The first four meetings, devoted to prepare the project and start the first survey, was held in Bratislava. Then the standard spring and autumn meetings were organised by countries. Here is a list of meetings, dates and places.

Project PECO

Meeting Date Place

1 April 1994 Bratislava, Slovakia
2 July 1994 Bratislava
3 September 1994 Bratislava
4 April 1995 Bratislava
5 October 1995 Budapest, Hungary
6 April 1996 Prague, Czech Republic
7 November 1996 Bratislava
8 April 1997 Warsaw-Jachranka
9 September 1997 Ljubljana-Bled, Slovenia
10 April 1998 Bratislava

Project DOSME

1 April 1998 Bratislava
2 October 1998 Tallinn, Estonia
3 April 1999 Bucarest-Brasov, Romania
4 October 1999 Vilnius, Lithuania
5 April 2000 Riga, Latvia

What types of training session were held?

Sample package and Entry package (for Baltic countries in Riga)
Sample package and Entry package (for the other countries in Bratislava)
On job training on imputing yearly survey data (Bratislava)
On job training on imputing longitudinal data (Bratislava)
Special training for the newcomer FYROM (Vilnius)

What seminars have been organised?

Until now only one seminar has been organised on the use of Business Registers and the CEC pilot project on demography of small and medium enterprises held in Luxembourg, in February 1999.

The seminar can be briefly characterised by an overview of submitted and presented document:

Regulation and recommendations for business registers in the EU
Registers as a tool for co-ordination
Delineation of units
Local units - the Hungarian viewpoint
The use of business registers in the Central European Countries
The use of business registers in Latvia
Business surveys in the FYROM
Business registers from the viewpoint of the Polish users
Co-ordination of the feedback to the business register in Romania
Business Demography
Estimation of business populations from imperfect frames
Quality of business registers
The DOSME project
Communication in the context of the DOSME project
Proposals for second DOSME project
Uses of administrative data for business statistics
Registration of Local Units in Central European Countries

What are the communication channels? How the communication works?

Communication within the project either PANEL PECO or DOSME is obviously multidirectional following from the multinational character of the project. The basic communication links in the project are as follow:

Project co-ordinator with the countries
Project co-ordinator with the technological centre – INFOSTAT
Technological centre with the countries
Project co-ordinator with the EUROSTAT, CESD on administrative issues
Country to country (in exceptional cases)
Consultants to each party in the project

Subjects of the communication in the project in general are:

Instructions on methodical issues in the project
Instructions on technological issues
Distribution of software to the countries
Collection the information on the national registers
Collection of resulting files
Distribution of Central Data Base files
Distribution and commenting the project publications
Administrative issues (contracts, monitoring the time tables)
Consultations on methodical and technological issues

From the above lists we can see that the communication in the project is rather complex and in many cases, depending on the subjects, must be fast, in time and reliable. New information and communication technology we had at disposal at each communication point when both projects came into operation helped us to fulfil the tasks to a large extent.

How is the project documented?

The basic documentation of the project was designed and developed in software package Fore Front Help Author in a form of a WINHELP file.

The general structure of the help system can be illustrated by its contents and the scope of topic types in the index of topics.

The main screen or the contents of the help file for Survey B looks like this:

Survey B

Last changes

Structure of the Documentation

Index of topics

General instruction S-B1 Questionnaire F-B1

Sampling base D-P01           Sampling program T-P1

Sequence of treatment T-SBSP              Sampling manual S-P1

Statistical tables D-ST            Transfer files D-TF

Entry manual S-EP

Survey A

Version March 21, 1997

Author: InfoStat Bratislava

For CESD-Communautaire

The general documentation of the project is a set of forms, i.e. the forms are basic instrument to document the project. Each of the forms receives an identifier and each form belongs to one series or type. The following ten types of forms have been defined and used:

F Questionnaire forms
Q Questions
D Files
V Variables
N Codes and nomenclatures
P Position or value of one code
T Processing or treatments
C Concepts
S Specifications
R Regulations

Topics are connected with jumps that can be defined individually or in groups as sequences. From this electronic form of the documentation various printout selections can be produced.

While this documentation is concentrated on methodological issues, a lot of working papers and software documentation is present on the project web site now. Software packages also contains their own documentation.

How is the Web site of the project organised?

In order to promote the communication with the all parties (the project manager, INFOSTAT, participating countries and consultants) involved in the DOSME project we have designed and developed the DOSME home page accessible via Internet.

The basic aim is to provide a universal and flexible tools for communication, distribution of important document and software and for an exchange of the project documents mainly those presented to working sessions. At present we have put on the DOSME home page the all documents produced so far in the project and presented to the working session as well as some other useful information related to the project activities.

The basic contents of the site is the following:

Information on Working sessions
List of participants
Agenda of the session
Working papers and other documents
Report from the session
Publications produced in the project
Content of detailed publication of A-survey results
Content of B1-survey and B2-survey publications
Content of B3-survey and C-survey publications
Seminars
Information on Luxembourg seminar
List of countries participating in the project with contact persons
Information on last update of the DOSME page
Comments from users of DOSME page for feed back

The site is regularly updated and some new improvements have been also introduced.

(From project documents compiled by Ladislav Meszaros, Infostat Bratislava, March 2000)