Appendix 1 – Firm productivity database

To investigate the firm dynamics that underpin aggregate labour productivity it is necessary to form a measure of firm labour productivity. This requires the construction of a longitudinal firm productivity database that contains information on outputs and labour inputs for New Zealand firms. This appendix discusses the data sources used to form the firm productivity database, issues associated with merging and cleaning various datasets, and the construction of measures of firm labour productivity.

Data sources and construction

The firm productivity database was formed from three data sources:

1. Business Demography Statistics Database (BDS)
2. Producer Price Indexes (PPI)
3. Household Labour Force Survey (HLFS)

The New Zealand BDS contains demographic and employment (both employees and working proprietors) information on enterprises (firms) from the New Zealand Business Frame that are deemed to be ‘economically significant’.[11] These data are collected for mid February of each year as part of the Annual Business Frame Update (ABFU). Monthly data on enterprise Goods and Service Tax (GST) sales and purchases are also available.[12] These GST data are sourced from the Inland Revenue Department (IRD). From 1994 onwards an enterprise was deemed to be economically significant if it satisfied any one of the following criteria:

• The enterprise had annual GST expenses or sales greater than $30,000;
• The enterprise had more than two full time equivalent paid persons employed;
• The enterprise was in a GST exempt industry (except residential property leasing and rental);
• The enterprise was part of a group of enterprises;
• The enterprise was a new GST registration that was compulsory, special or forced (which normally means the enterprise was expected to have GST sales or expenses that exceed $30,000); or
• The enterprise was registered for GST and was involved in agriculture or forestry

The BDS has some limitations. First, small enterprises that have GST sales below $30,000 are excluded from the BDS. Second, company restructures and changes of ownership that are accompanied by new GST registrations will result in enterprise births and deaths even though these pertain to existing enterprises. Therefore, enterprise births and deaths may reflect administration changes in addition to genuine business start ups and closures.[13]

The PPI provide information on producer output and input prices. The output price indexes measure changes in the prices received by producers. The input price indexes measure changes in the cost of inputs to production (excluding labour and capital costs). These data were used as deflators when constructing measures of firm level output.

The HLFS is used to provide information on the average hours worked by full time and part time working proprietors and full time and part time employees for four digit industries. The HLFS is a private household based survey and has greater industry coverage than the alternative Quarterly Employment Survey (QES), which is a firm based survey, that contains information on the average hours paid to full time and part time workers within an industry.[14] The HLFS classifies a person as a full time working proprietor or employee if they work 30 hours or more per week. A person is classified as a part time working proprietor or employee if they work less than 30 hours per week.

The BDS industry coverage is not the same from year to year. Additional industries were included in the ABFU in some years; in other years industries were dropped. To maintain constant industry coverage over the period 1994 to 2003 it was necessary to drop enterprises in industries that were not included in the BDS in every year between 1994 and 2003. This means that agriculture and livestock production, residential property leasing and rental, commercial property and leasing, child care services, residential and non-residential services, business professional and labour organisations, religious organisations, social and community groups, and sporting and recreational services industries were excluded from the firm productivity database.

Data on monthly GST sales and purchases were collapsed to an annual frequency and merged with the BDS demographic and employment data. Because BDS data on numbers of working proprietors and employees are recorded for mid February in each year, the annual GST sales and purchases data were formed for the year ending August. When forming annual GST sales and purchases for entering and exiting firms that had monthly sales and purchases data for less than a full year, which suggests these firms were operating for only part of the year, the aggregated monthly sales and purchases were annualised to ensure entering, exiting and continuing firms were analysed on a comparable basis.[15]

Merging demographic and employment data with GST sales and purchases data highlighted several issues. First, there were enterprises that had GST sales information but no employment data for the entire period they existed, or conversely had employment data but no GST sales information. Because it was not possible to form a measure of firm labour productivity when either employment or GST sales data were missing for the entire period the firm existed these firms were dropped. Second, some enterprises had partial information on employment or GST sales for part of the period the firm was recorded as existing. When this occurred during the middle of a firm’s existence the missing data observations were filled using the last recorded observation. For example, a firm in existence between 1994 and 2004 with GST sales for the corresponding period but missing employment data in 1996 and 1997 would have the missing 1996 and 1997 employment data filled using employment in 1995. A partial explanation for situations similar to the example above is that some firms fail to respond to the Annual Business Frame Update (ABFU) questionnaire, despite the firm still operating (as indicated by the firm filing GST sales of $30,000 or greater). The non-response rate for the ABFU is estimated to be between 10% and 15%. The approach to imputing missing values is one that has been adopted by Statistic New Zealand in other contexts.

Cases occurred where a firm was in existence in the BDS but there was no recorded information on total employment and GST sales or purchases at the beginning or end of the firm’s life. In these situations the firm was deemed to be an entrant in the first period where employment or GST was available and was ‘ceased’ in the period following the last observation for employment or GST sales.[16]

Firm output

Measures of firm output were constructed using data on GST sales and purchases, and producer output and input prices. GST sales were used as a proxy for nominal gross output. A proxy for real gross output was constructed by deflating GST sales by the corresponding producer price output index at approximately the two digit industry level. If the price for a firm’s output is actually higher than the average industry price, then measured real gross output will be overstated and, hence, the firm’s labour productivity, ceteris paribus.

A proxy for firm value added was constructed by subtracting material purchases from firm gross output. GST purchases were used to proxy for nominal material purchases. Real material purchases were calculated by deflating GST purchases by the corresponding producer price index at approximately the two digit industry level. Owing to the unavailability of firm data on final goods inventories, firm value added is likely to be miss measured. More precisely, firm sales differ from firm output by the change in inventories of final goods. Because of this it is likely that a measure of value added based on firm sales would be more volatile than one based on firm output as inventories tend to be counter cyclical and act as a buffer to changes in demand.

Firm labour input

The BDS contains enterprise data on the number of full time working proprietors, part time working proprietors, full time employees, and part time employees for mid February of each year. These data were used to construct a ‘head count’ measure of firm labour input by adding the number of full time working proprietors, part time working proprietors, full time employees, and part time employees. A limitation of the ‘head count’ measure of labour input is that it does not take into account differences in the number of hours worked by different types of workers. Data on the number of total hours worked within an enterprise is the preferred measure of that enterprises labour input (or less preferred, but still better than the number of working proprietors and employees or the number of hours paid by the enterprise). However, the number of hours worked or hours paid is not available from the BDS. To overcome the limitation of the ‘head count’ measure in not taking account of differences in the hours worked by different types of workers, an alternative labour input measure was constructed where each worker type was assigned the average hours worked by the corresponding type of worker at the four digit industry level. This alternative measure of enterprise labour input assumes there is no variation in the average hours worked by different types of workers within an industry at the four digit level (although there will still be variation in labour inputs within a four digit industry because enterprises have different numbers and types of workers).

Firm labour productivity

Construction of two proxies for firm output – real gross output and real value added – and two measures of firm labour input – total number of workers and a proxy for the number of hours worked – means it is possible to construct four different measures of labour productivity: gross output per worker; gross output per hour; value added per worker; and value added per hour. However, analysis in this paper is conducted using value added per hour only.