RDP 2026-04: Tracking Mergers and Acquisitions Using Australian Administrative Data 2. Literature Review

Our paper relates to previous overseas studies that seek to measure merger and acquisition activity using indirect methods in the absence of formal reporting requirements.

One method used in the literature is to use surveys, or private sector databases on known mergers or acquisitions (such as Bloomberg or SDC Platinum investment banking deal activity database). However, private sector databases pose several limitations for research. Most notably, they fail to capture the full spectrum of mergers and acquisitions within an economy, often skewing towards large publicly announced transactions. For instance, Sharma and Ho (2002) relies on a small sample of just 36 Australian acquisitions. Second, while these databases usually contain some firm-level and industry-level information, they do not have a full range of information on subsidiaries, workers or wages. As a result, the effects of mergers, productivity and workers cannot be analysed.

Another method is to use administrative data to identify restructures (including mergers) by tracking worker flows between firms in a linked employee-employer dataset. This method can identify mergers, but also improve overall administrative data quality by allowing researchers to identify cases where a firm appears to have closed, but there has actually been a re-structuring Hethey-Maier and Schmieder (2013), which can be important in exploring the effect of job loss and firm closure on workers. This method for identifying mergers is built on the assumption that workers from a target firm move together to the new acquiring firm. Since not all workers in a target firm may move (and the acquiring firm may rationalise the target workforce) a merger is usually taken to have occurred if a certain percentage or number of workers move together to a new firm. For example, Benedetto et al (2007) and Hethey-Maier and Schmieder (2013) use both shares and numbers, classifying a worker cluster transition to occur either where five or more workers move together between the firms or when 80 per cent of employees from the target move to the acquirer. Similarly, Geurts and Van Biesebroeck (2014) uses a minimum cluster of three to five employees in addition to a set of percentage thresholds. This method will normally exclude very small firms to remove the chance that natural turnover in these firms are erroneously identified as mergers. For example, Benedetto et al (2007) and Geurts and Vets (2013) exclude firms with five or fewer employees.

One difficulty in using this approach is differentiation between mergers and other types of restructures, such as where a part of a firm is spun off to create a new firm. For example, Geurts and Vets (2013) links two firms using threshold worker flows and then identifies whether the firms are start ups, exiting or continuing firms, using the relative size of these flows. Geurts and Van Biesebroeck (2014) differentiates between mergers, where at least 50 per cent of employees move to acquirer, and takeovers, where over 75 per cent of workers move to the acquirer. Fackler, Schnabel and Schmucker (2016) follows an approach used by Eriksson and Kuhn (2006) to identify start up firms, in which more than 50 per cent of the initial workforce were employed together in the same firm in the year before, but only if this group of workers did not make up more than 50 per cent of the predecessor firm's workforce.

This paper adopts the second method outlined above – that is, by tracking both flows of workers. We also add two other methods, using data not previously available to researchers: tracking flows of entities between tax consolidated groups; and tracking firms' lodgments of merger forms to the securities regulator, the Australian Securities and Investments Commission (ASIC).