Business Environment and Enterprise Performance Survey 2003

Moldova Business Environment and Enterprise Performance Survey (BEEPS) 2003 is the continuation of Moldova BEEPS 2002. The survey for 2003 focused only on manufacturing sector, services industry was excluded.

The description of BEEPS 2002 sampling technique is taken from "The Business Environment and Enterprise Performance Survey - 2002. A brief report on observations, experiences and methodology from the survey" prepared by MEMRB Custom Research Worldwide (now part of Synovate), a research company that implemented BEEPS 2002 instrument.

The general targeted distributional criteria of the sample in BEEPS II countries were to be as follows:

1. Coverage of countries: The BEEPS II instrument was to be administered to approximately 6,500 enterprises in 28 transition economies: 16 from CEE (Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, FR Yugoslavia, FYROM, Hungary, Latvia, Lithuania, Poland, Romania, Slovak Republic, Slovenia and Turkey) and 12 from the CIS (Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia, Tajikistan, Turkmenistan, Ukraine and Uzbekistan).

2. In each country, the sector composition of the total sample in terms of manufacturing versus services (including commerce) was to be determined by the relative contribution of GDP, subject to a 15% minimum for each category. Firms that operated in sectors subject to government price regulations and prudential supervision, such as banking, electric power, rail transport, and water and wastewater were excluded.

Eligible enterprise activities were as follows (ISIC sections):

• Mining and quarrying (Section C: 10-14), Construction (Section F: 45), Manufacturing (Section D: 15-37)
• Transportation, storage and communications (Section I: 60-64), Wholesale, retail, repairs (Section G: 50-52), Real estate, business services (Section K: 70-74), Hotels and restaurants (Section H: 55), Other community, social and personal activities (Section O: selected groups).

3. Size: At least 10% of the sample was to be in the small and 10% in the large size categories. A small firm was defined as an establishment with 2-49 employees, medium - with 50-249 workers, and large - with 250 - 9,999 employees. Companies with only one employee or more than 10,000 employees were excluded.

4. Ownership: At least 10% of the firms were to have foreign control (more than 50% shareholding) and 10% of companies - state control.

5. Exporters: At least 10% of the firms were to be exporters. A firm should be regarded as an exporter if it exported 20% or more of its total sales.

6. Location: At least 10% of firms were to be in the category "small city/countryside" (population under 50,000).

7. Year of establishment: Enterprises which were established later than 2000 should be excluded.

The sample structure for BEEPS II was designed to be as representative (self-weighted) as possible to the population of firms within the industry and service sectors subject to the various minimum quotas for the total sample. This approach ensured that there was sufficient weight in the tails of the distribution of firms by the various relevant controlled parameters (sector, size, location and ownership).

As pertinent data on the actual population or data which would have allowed the estimation of the population of foreign-owned and exporting enterprises were not available, it was not feasible to build these two parameters into the design of the sample guidelines from the onset. The primary parameters used for the design of the sample were:

• Total population of enterprises;
• Ownership: private and state;
• Size of enterprise: Small, medium and large;
• Geographic location: Capital, over 1 million, 1 million-250,000, 250-50,000 and under 50,000;
• Sub-sectors (e.g. mining, construction, wholesale, etc).

For certain parameters where statistical information was not available, enterprise populations and distributions were estimated from other accessible demographic (e.g. human population concentrations in rural and urban areas) and socio-economic (e.g. employment levels) data.