3  Summary statistics

In this section summary measures are presented for key variables to give a profile of the productivity and size of firms. Section 3.1 discusses how the mean values and standard deviations of labour productivity and its components vary across industries. The distribution of labour productivity within industries is also discussed. Cohorts of firms are examined in Section 3.2 for any systematic differences in labour productivity. In Section 3.3 the distribution of labour productivity is examined in more detail. All sales per hour, purchases per hour and labour productivity per hour are weighted by mean annual total hours worked.

3.1  Aggregate and industries

The means and standard deviations of sales per hour, purchases per hour and labour productivity for all one digit industries and the aggregate are given in Table 4. Average aggregate labour productivity for the years 1994 to 2003 was 39 dollars. That is, an average of 39 dollars of value-added was generated for every hour worked. This was made up of an average of 151 dollars of sales less 112 dollars of purchases for every hour worked.

There is considerable variation in average sales, purchases and labour productivity across industries. Electricity gas and water supply has the highest mean for all variables: 14.8 times the lowest industry (Personal and other services) for sales per hour, 23.3 times the lowest industry (Health and community services) for purchases per hour, and 10.3 times the lowest industry (Retail trade) for labour productivity. There is also considerable variation within industries, with the standard deviation on each variable being several times the mean for most industries.

Differences in labour productivity across industries are, for the most part, not surprising given that there will be differences in capital intensity. Industries with relatively high levels of labour productivity include for example Electricity, gas and water supply, Transport and storage, and Communication services. Industries with relatively low levels of labour productivity include Accommodation, cafes and restaurants, and Retail trade.

Table 5 shows the distribution of labour productivity within industries. For each one digit industry several percentiles of the distribution are given. It is immediately apparent that there exists a great deal of heterogeneity in firms’ labour productivity within all industries. For the aggregate, the median firm is more than twice as productive as the firm at the 25^th percentile. The firm at the 75^th percentile is almost twice as productive again. Some industries have much greater variation than others. Firms in the Mining, electricity, gas and water supply and in the Wholesale trade industries for example have much higher variability in labour productivity than those in the Retail trade and in the Accommodation, cafes and restaurants industries.

Variation in labour productivity outcomes isn’t really any less within one digit industries than it is across the economy. For eleven out of seventeen one digit industries the median firm is more than twice as productive as the firm at the 25^th percentile. For eight industries the firm at the 75^th percentile is more than twice as productive again. Between the 75^th and 25^th percentiles the difference in labour productivity can be quite marked. For instance, in Mining the firm at the 75^th percentile is more than nine times as productive as the firm at the 25^th percentile. There are likely to be several reasons for such variation within industries. Firms may be at different stages of their life cycles,[13] employ very different production technologies, buy and sell large chunks of capital or may simply be better than others at converting labour input into value-added.

Although not shown here, a similar degree of heterogeneity is present in the sales per hour and purchases per hour of firms within the same industry. One difference however between the distribution of labour productivity and those of sales per hour and purchases per hour is that a significant proportion of observations on labour productivity are negative, in total approximately 13 percent. In almost all industries, at least 5 percent, and in the case of Finance and insurance more than 25 percent, of observations are negative. While negative labour productivity is theoretically quite possible it does cause difficulties when calculating labour productivity growth for individual firms.

There is now a large body of evidence for many countries that productivity dispersion is very large across industries and across firms within the same industry. In their survey of longitudinal studies of firm productivity, Bartelsman and Doms (2000, p. 278) comment that “Of the basic findings related to productivity and productivity growth uncovered by recent research using micro data, perhaps most significant is the degree of heterogeneity across establishments and firms in nearly all industries examined.” They point out moreover, that while some of this dispersion may reflect “dirty data”, there are several reasons to believe that it reflects real productivity differences. These reasons include the long history of research based on diverse data sets and that this heterogeneity in productivity appears in both developed and developing countries where the extent of statistical error is likely to vary. Moreover, relative productivity across plants has been shown to be correlated with wages, technology use, export success and knowledge differences (see for example Criscuolo, Haskel and Slaughter, 2005). Further, high productivity firms have been found to have higher growth and are less likely to exit. The wide dispersion in sales, purchases and labour productivity that we find amongst New Zealand firms is therefore not surprising and is consistent with international evidence.