Adjusting to skill shortages in Australian SMEs

Abstract

Skill shortages are often portrayed as a major problem for advanced economies, yet there is surprisingly little empirical evidence about how firms adjust to skill shortages and their associated effects on firm performance. This article provides new evidence from the Business Longitudinal Database, an Australian data set with unusually rich information on the causes and consequences of skill shortages in small- and medium-sized enterprises. We document the range of alternative strategies that firms adopt when responding to skill shortages and show that certain types of adaptation are used in some cases and not in others, depending on the type of shortage encountered and other attributes of the firm. Further, we show that certain types of skill shortage are more likely to be long-lasting and difficult to resolve, while others are alleviated relatively quickly with minimal adjustment. Our findings yield lessons for the skill utilization strategies of firms and for the labour market policies of governments.

Keywords:

• skill shortages
• firm performance
• labour demand
• SMEs

JEL Classification:

• J00
• J20
• J23
• J24

Acknowledgements

This article draws from a study undertaken for the National Centre for Vocational Education Research (NCVER) by the National Institute of Labour Studies, Flinders University, Adelaide. See Healy, J., Mavromaras, K., and Sloane, P.J., 2011, Skill Shortages: Prevalence, Causes, Remedies and Consequences for Australian Businesses, NCVER, Adelaide. The authors share equal first authorship.

Notes

¹ For a general discussion covering 19 countries on the view that what constitutes a skill shortage is not straightforward, see Cohen and Zaidi (2002).

² A recent addition to the range of available data sets is the New Zealand Business Operations Survey, which included a skills module in 2008 (see Mok et al., 2012). We are not aware of this data set being used to study the performance consequences of skill shortages.

³ This section draws on ABS (2009).

⁴ Firms in the food industry were over-sampled at the request of the Australian Government. We retain these firms and include a dummy variable to distinguish them.

⁵ Unfortunately, the BLD provides no information about the presence of trade unions, the gender or occupational composition of employees, or the use of immigrant workers by sampled firms.

⁶ The measure of wages includes salaries, leave loadings and other allowances, but excludes regular superannuation payments and amounts that employees ‘salary-sacrifice’ from their pre-tax income.

⁷ We do not weight these regression estimations. Instead, we include as control variables in our models those firm characteristics that were used to stratify the BLD, which accounts for the sampling design in a manner analogous to the use of weights (Winship and Radbill, 1994).

⁸ For instance, estimating the probability that a firm faces any kind of skill shortage would ignore the information on the different causes that is available in the BLD. Similarly, treating each cause separately would ignore the evidence that most skill shortage firms cite multiple causes (see Table 1). Finally, using data reduction methods, such as factor analysis, to group the causes, is not appropriate because the correlations between the individual causes are weak (r < 0.25 in all cases).

⁹ We do not present the results for two responses – ‘more use of external training’ and ‘other (please specify)’ – because their observed frequencies are too small to generate reliable estimates.

¹⁰ Our analyses are (implicitly) conditional on firm survival. We have shown elsewhere (Healy et al., 2011, pp. 48–50) that there is no significant association between skill shortages and the probability of firm survival.

¹¹ Nonetheless, some firms exhibit extreme volatility in the value of their year-to-year sales. We drop from the analysis a small number of these firms (N = 26), with significant improvements in the fit of our regression equation. The excluded firms are predominantly small enterprises with 0–4 employees. Their average increase in sales was more than 1000% over 1 year and more than 2000% over 2 years.

Additional information

Funding

The authors gratefully acknowledge funding received from the National Vocational Education and Training Research and Evaluation (NVETRE) Program.