SME takeovers as a contributor to regional productivity gaps

Abstract

New economic geography models typically predict centripetal economic development. One process by which this might be brought about is if large companies based in the core of the economy buy up and remove small dynamic enterprises from peripheral regions, thereby suppressing development outside the core. This hypothesis is investigated by analysing the very large UK administrative firm-level Business Structure Database. Contrary to the experience of big firms, more productive small businesses are more subject to takeover—although this effect is weaker if they are located in peripheral regions. Takeovers also increase the chances of a small and medium-sized enterprise (SME) closing, but the exit consequence is greater for the core region. Takeovers raise productivity after acquisition in all regions but by less for the most productive SMEs. Ignoring any productivity gains to acquiring firms, the positive impact in the core region during the years considered is slightly larger than in the periphery, principally because takeovers are more common in the core. As this impact is a contributor to regional divergence, policy should aim to improve the operation of the market for SMEs in the periphery.

Appendices

Appendix A

1.1 Appropriate weights for averaging SME’s labour productivity

The appropriateness of employment weights with labour productivity can be shown below. There are two firms each with employment (e) and output (q).

$$ P = Q/E, $$

where q ₁ + q ₂  =  Q, e ₁ + e ₂  =  E and p _I   =  q _I /e _I

$$ Q/E = p_{ 1} \,*\,\left( {e_{ 1} /\left( {e_{ 1} + e_{ 2} } \right)} \right) + p_{ 2} *\left( {e_{ 2} /\left( {e_{ 1} + e_{ 2} } \right)} \right) = \left( {q_{ 1} /e_{ 1} } \right)\,*\,\left( {e_{ 1} /\left( {e_{ 1} + e_{ 2} } \right)} \right) + \left( {q_{ 2} /e_{ 2} } \right)\,*\,\left( {e_{ 2} /\left( {e_{ 1} + e_{ 2} } \right)} \right) = \left( {q_{ 1} /\left( {e_{ 1} + e_{ 2} } \right)} \right) + \left( {q_{ 2} /\left( {e_{ 1} + e_{ 2} } \right)} \right) = \left( {q_{ 1} + q_{ 2} } \right)/\left( {e_{ 1} + e_{ 2} } \right) $$

The inappropriateness of output weights can also be shown;

$$P = Q/E \, \ne \, \left( {q_{ 1} /e_{ 1} } \right)\,*\,\left( {q_{ 1} /\left( {q_{ 1} + q_{ 2} } \right)} \right) + \left( {q_{ 2} /e_{ 2} } \right)\,*\,\left( {q_{ 2} /\left( {q_{ 1} + q_{ 2} } \right)} \right) = \left( { 1/q} \right)\,*\,\left( {\left( {q_{ 1}^{ 2} /e_{ 1} } \right) + \left( {q_{ 2}^{ 2} /e_{ 2} } \right)} \right) $$

Given that output weights to productivity do not aggregate appropriately, we recommend using only employment weights when labour productivity is used.

Appendix B

Table 8 Bivariate probit of exit and takeover 2004–2006 (takeover in 2005)

2.1 Appendix C

Table 9 DiD productivity (2004–2007) regressions