The impact of hiring top workers on productivity: what is the role of absorptive capacity?

ABSTRACT

We examine the heterogeneous productivity impacts of hiring top workers on small and medium-sized enterprises, exploiting matched employer–employee panel data and employing within-firm as well as matching and difference-in-difference estimators. The results provide robust evidence that the productivity impact is stronger for firms with higher absorptive capacity. Technological laggards within an industry benefit more strongly from hiring top workers if their workforce is more well-educated.

KEYWORDS:

• Recruitment
• knowledge spillover
• productivity
• SME
• absorptive capacity

JEL CLASSIFICATION:

• D21
• D24
• D83
• J24
• J62

Supplemental data

Supplemental data for the article can be accessed here.

Acknowledgements

We thank Kent Eliasson, Anton Gidehag, Pär Hansson, Niklas Jakobsson, Kristina Nyström and seminar participants at Aston and Örebro universities, Ratio and the Kiel Institute for the World Economy for comments. This work was supported by Growth Analysis and the Jan Wallander and Tom Hedelius Research Foundation under Grant W2013-0425:1.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ Bloom and Van Reenen (2010) substantiate the importance of management practices for firm performance.

² There is considerable evidence that firms’ own research and development is important for absorbing the insights from others’ R&D (e.g. Escribano, Fosfuri, and Tribó 2009; Griffith, Redding, and Van Reenen (2003)).

³ The ‘Penrose effect’ – hiring distracting managers from controlling costs – is only expected for larger firms (e.g. Coad and Broekel 2012).

⁴ Mion and Opromolla (2014) note the unfortunate lack of research on the nexus between manager mobility and firm productivity. Neither the study by Gidehag and Lodefalk (2017), nor the one by Parotta and Pozzoli (2012) consider the role of the absorptive capacity of firms.

⁵ Gidehag and Lodefalk (2017) fully account for the method.

⁶ Log of firm size and age; multinational affiliation; and legal form.

⁷ The model is lagged partly since knowledge transfer through new recruits and its TFP pay-off is likely to hinge on the intensity and length of the interaction between the recruit and the hiring firm, namely the pay-off, and partly to attenuate endogeneity concerns (e.g. Gidehag and Lodefalk 2017; Granovetter 1973).

⁸ The recruitment variables are not in logs because most SMEs do not recruit in a given year.

⁹ We follow Eurostat’s classification at the 3-digit industry level.

¹⁰ The index draws on the approach of Griffith, Redding, and Simpson (2005), which is intended to attenuate endogeneity concerns.

¹¹ That is, first, the firm’s TFP is evaluated relative to a common reference point (the geometric mean TFP of the industry) and, second, compared with the maximum TFP of the industry.

¹² For details, see the supplemental data.

¹³ We also require firms to grow organically to avoid the results being driven by factors related to merges and acquisitions.

¹⁴ The summary statistics, additional results and robustness checks are available in the supplemental data.

¹⁵ Firms with R&D expenditures or that are active in knowledge-intensive services industries stand out in terms of the hiring and employment of leading personnel.

¹⁶ Measured as an indicator for of the workforce having years of post-secondary education.

¹⁷ Echoing findings in Gidehag and Lodefalk (2017).

¹⁸ Tables B5–B7 in the supplemental data.

¹⁹ See Table A2 in the supplemental data.

²⁰ See Tables A3–A5 in the supplemental data.

Additional information

Funding

This work was supported by Growth Analysis and the Jan Wallander and Tom Hedelius Research Foundation under Grant W2013-0425:1.