05 Jun 2017

(by ) While it is widely recognised that last year’s EU referendum caused significant uncertainty for markets, some were that it had not reduced the level of business confidence. Almost a year on, our research – based on a careful study design of a treatment and control group and using data from – finds that the uncertainty surrounding the referendum has in fact led to a significant drop in merger numbers and the numbers have failed to recover to earlier levels. Apart from establishing a causal relationship, the study suggests that the post-referendum policy uncertainty is helping the largest M&A transactions, while hindering the smaller ones, with possible negative consequences.

The question of whether the referendum result had a positive or negative effect on M&A activity in the UK seems straightforward, yet the effect has been reported as both and by different commentators. Why the discrepancy? Probably because these analyses are limited to simply looking at how the numbers changed in comparison to M&A activity in the UK, pre-referendum. For example, the average monthly number of M&A announcements in the 11 months before the referendum was around 430. The same average in the 11 months since the referendum has been around 350. Can we conclude that the referendum caused the monthly number of M&A announcements to drop by 80? Some might say yes, but others could argue that the drop was caused by something other than the referendum. Before-after comparisons are unable to identify causal effects and, as such, are ill suited for identifying the impact of the referendum on M&A activity.

Study design

To determine if there has been a causal link between the referendum and M&A activity, we required a control group or counterfactual, against which the changes in the UK could be compared. For this, we used a set of other countries where, naturally, no referendum had taken place. If the selected countries are sufficiently similar to the UK, then we can assume that they represent how M&A activity would have evolved in the absence of the referendum in the UK. Therefore the difference between the UK and these other countries could be thought of as the effect of the referendum.

One way of ensuring the control group is sufficiently similar to the UK, is to examine their pre-referendum M&A activity. For example the figure below shows how the monthly number of M&A announcements have changed for the UK and Germany (the vertical dotted lines represent the start of the referendum campaign and the referendum). It appears that before the referendum there was a slight drop in the UK, but a slight rise in Germany. So using the difference between these countries as an estimator for the effect of the referendum is likely to pick up some other effect as well – something that caused the difference in trends even pre-referendum.

To find a comparator country that doesn’t suffer from the same problems, one would need to look at a number of factors at play that influence the level of M&A activity. For example how healthy a country’s economy is, or how easy it is to do business, and so on. Such multi-dimensional comparisons would be an arduous task to do manually, and even then it would be questionable whether a single best comparator country could be selected. One thing that researchers can do in these cases is rely on something called a group, which is a weighted average of a number of other countries, that is the most similar to the Treatment group and based on a comparison of many characteristics. It is as if we were saying that, given a list of attributes, the UK is a little bit like Germany, but also a bit like the US, and a bit like France too. When we create a synthetic Control group we allow the UK to be compared to many countries at the same time, each with a different weight.

For this preliminary study we selected 8 other countries (Australia, France, Germany, Italy, Netherlands, Spain, Sweden, and the US) to serve as the starting step for creating a synthetic Control group. Data on country characteristics were downloaded from the World Bank’s Databank. We made the comparison on the following attributes: GDP (level and growth); domestic credit to private sector (% of GDP); ease of doing business index (a World Bank index); foreign direct investment; net inflows (% of GDP); inflation (annual %); interest rate spread (lending rate minus deposit rate, %); lending interest rate (%), profit tax (% of commercial profits), research and development expenditure (% of GDP), tax revenue (% of GDP), unemployment (% of total labour force); average monthly value of transactions (million USD); and total monthly value of transactions (million USD). These are the attributes we expect will affect M&A activity in any country.

Based on these characteristics, the composition of countries that best matches the UK is: 44% France, 3% Netherlands, 35% Spain, and 18% US. Using this weighted set of countries as a synthetic Control group, we can make a better comparison.

The effect of the referendum of M&A activity

As the figure below shows, using the synthetic Control makes the M&A activity lines before the referendum campaign almost perfectly parallel, which is one of the indicators that the trend in the synthetic Control group is a good proxy for the trend in the UK. We could therefore assume that the trend in the synthetic group following the referendum is the trend that the UK would have experienced in the absence of the referendum. The figure shows a clear change after the referendum. The UK line diverges from the parallel trend and drops, whilst the Control line remains roughly around the same level, implying that the monthly number of M&As dropped as a result of the referendum. This is shown clearly by the dashed line, which is our estimate of how M&A activity would have evolved in the absence of the referendum. The figure also shows the referendum campaign period, between the two vertical dotted lines. It clearly shows that the start of the referendum campaign was the main trigger, and then M&A activity never recovered since.

We formally estimate the reduction in M&A activity that is observed after the referendum, amounts to 60 mergers per month or a 15% drop. Importantly, we suggest this is directly attributable to the referendum uncertainty.

Which mergers were most affected?

Using the same technique, the analysis has also shown an interesting divergence between high value and low value M&A activity. While the former has increased, the latter has decreased in relative terms.

Pre and post-referendum percentiles of M&A values (million $)

Summary statistics on how quantiles changed post-referendum, suggest the referendum had a differential impact on M&A activity. For example, the 25th percentile of M&A values was $5.7 million pre-referendum, and $4.5 million post-referendum. What does this mean? That the smallest 25% of all M&As in the UK are now smaller than what they were before the referendum. What about the largest mergers? The 90th percentile of M&A values was $214 million pre-, and $250 million post, i.e. the largest 10% of mergers have become larger.

We look at whether these differences hold in a design similar to the one presented above. The answer is yes, we formally show that the referendum had a different effect on M&As of various sizes (i.e. confirms our reading of the summary statistics). Moreover, we find that given the size of the business, it was mainly the larger deals that were foregone after the referendum (the deals that were small in comparison to the acquiring business’ size were not significantly affected). This makes sense, as with increased uncertainty and risk, firms would be most cautious about the deals that are large relative to their own size. Finally, we looked at which businesses were most likely affected by the referendum and found evidence that larger businesses have become more M&A active.

What do these results tell us?

What do these results tell us? First of all, the referendum caused a drop in M&A activity in the UK. This is bad news. The vast majority of mergers (unless they have a significant adverse effect on competition) have the potential to contribute to social welfare, for example by reducing transaction costs, or by enhancing the efficiency of the merging businesses. If competition is left undisturbed, these benefits are passed on to consumers in the form of lower prices. When there is a setback in M&A activity (and a 15% setback is a rather sizeable one), it means that some of these potential benefits are foregone.

Moreover, it appears that not all mergers were affected the same way. The finding that the distribution of mergers has changed as a result of the referendum implies that some mergers were more affected than others. Small mergers have become smaller and some of the very big mergers are now even bigger. Moreover, the largest businesses became more likely to carry on with their M&A activity, post-referendum.

This could be caused by the fact that cross-border mergers, that tend to be the larger in value, were less affected by the referendum. But it could also be a more worrying sign. Large businesses have better means for rent-seeking behaviour (manipulating political and economic conditions to increase profits). When we find that the largest transactions and the largest businesses were not hindered (and in some cases were even spurred) by the referendum, one inevitably worries: how much of this differential effect is due to the fact that these larger businesses are cushioned from the increased uncertainty, thanks to their rent-seeking behaviour.

Transitional periods are never good for businesses and consumers, but what makes it even worse, is that businesses do not seem to be equally exposed to the same risk from the increased policy uncertainty, and those that are more likely to have political influence seem more protected from these risks.

Special thanks to Ioannis Pappous and Luke Garrod for the stimulating discussions on this work.

This is only a preliminary analysis of the data and reflects ongoing work. More details of our study are provided in the following extended blog: