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The Journal of Real Estate Finance and Economics

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19.10.2021

Acquisitions and the Opportunity Set

verfasst von: Jarl G. Kallberg, Yoshiki Shimizu

Erschienen in: The Journal of Real Estate Finance and Economics | Ausgabe 4/2023

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Abstract

This study analyzes the impact of various proxies for an acquirer’s opportunity set on its post-acquisition abnormal performance and on its likelihood of making an acquisition. Our initial empirical analysis consists of a sample of acquisitions by Real Estate Investment Trusts (REITs) of public and private targets over the period 1994 to 2015. Using REIT acquisitions allows us to utilize an alternative measure, the cap rate, of the firm’s opportunity set, in addition to those available for regular corporations: Tobin’s Q and short momentum. Specifically, we use the regional cap rate that corresponds to the target’s headquarters. Controlling for multiple factors that influence post-acquisition performance, we find that buy-and-hold abnormal returns to REIT acquirers are highly positively related to the cap rate at the time of the acquisition; however, Tobin’s Q has no significant impact. Short momentum has a negative impact on performance. We also show that higher cap rates, Tobin’s Q and short momentum all lead to more frequent acquisitions. In addition, we analyze a sample of 25,851 property acquisitions and find that the cap rate and Tobin’s Q are positively related to the number of property acquisitions a REIT makes. The results of this empirical analysis support the notion that positive investment opportunities in real markets (organic growth) are associated with positive acquisition opportunities (inorganic growth). We perform several robustness tests to corroborate our results.

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Andrade and Stafford (2004: p.2): ... mergers and internal investment should be related, since they are similar ways of adding to a firm’s asset base and productive capacity. Therefore, the choice between investing internally and acquiring another firm boils down to considering the relative net benefits of the alternatives. They find neither complementarity nor substitutability between acquisitions and other investments.

For example, Andrade and Stafford (2004).

As in Martin (1996) or Klasa and Stegemoller (2007).

In an earlier version of this study we also explored the impact of the net asset value (NAV) premium on acquisition frequency and likelihood without finding any significant relation. However, Kim and Wiley (2019) show that NAV premiums (lagged one year) are positively correlated with the frequency of property investment.

In our analysis we exclude the M/B ratio. Adam and Goyal (2008) use real option analysis to test different proxies for the firm’s opportunity set; they find that Q outperforms the alternatives. An earlier version of this study incorporated M/B and found results consistent with Adam and Goyal.

Source: NAREIT.com. The acquisitions we study are from 1990 to 2015 but we use data up to 2018 in order to compute 3-year performance.

Campbell et al. (2001); however, Mulherin and Womack (2015) provide evidence that there is a competitive market for REIT acquisitions.

This topic is analyzed in Cremers and Nair (2005) and Masulis et al. (2007).

Jensen (1993).

Hardin et al. (2009) document that REIT cash holdings average about 1.57% of total assets; the comparable figure for regular corporations is 18.5%. Using a longer sample period, Ghosh et al. (2012) obtain an average of 4.9%. In their sample they find that 16% of REITs are cash-rich, therein defined as having cash holdings more than 1.5 standard deviations above average.

REIT capital structure is analyzed in, i.a., Feng et al. (2007); Boudry et al. (2010); Harrison et al. (2011).

See, i.a., Campbell et al. (2008).

See Hasan et al. (2014) for empirical results.

In a univariate analysis (Table 4), we show that the post-acquisition abnormal performance is a significant 13.3% higher for acquisitions announced when cap rates are in the highest versus lowest quartile.

Including Andrade et al. (2001); Martynova and Renneboog (2008); Eckbo (2009).

A similar result is found in McIntosh et al. (1989), while Campbell et al. (1998) find slightly negative announcement effects.

This differs from the typical results for public targets; see, i.a., Loughran and Vijh (1997).

E.g., Capozza and Seguin (1999).

Garcia and Norli (2012).

Garmaise and Moskowitz (2004); Ling et al. (2021a, b).

See, i.a., Cao et al. (2011).

In their robustness tests they use a longer time period (beginning in 1985) for a subset of their data and find very similar results.

See also Plazzi et al. (2008) for related results.

Corroboration for these results is found in Koijen et al. (2018).

An examination of cap rates and expected IRRs obtained from surveys conducted by PWC Korpacz shows a correlation over 92%.

https://www.ncreif.org/

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/index.html

We follow Harris et al. (1982), which performs a probit analysis to determine the impact of firm-level financial and product market characteristics on the probability of acquisition.

We follow the method of Seok et al. (2020) to calculate funds from operations (FFO).

The majority of acquisitions by typical corporations are made by repeat acquirers (e.g., Ahern, 2008). A common finding in the literature is a declining trend in the success of subsequent acquisitions, usually attributed to hubris (Roll, 1986).

See Ghosh et al. (2012) and Campbell et al. (2011).

Given the merger wave patterns reported in Table 2, we incorporate a dummy variable into our regressions: Wave is set to one if the observation is during the 1995–1998, 2004, 2006 or 2013–2014, and zero otherwise. This partition is similar to that analyzed in Mulherin and Womack (2015), which describes the links between these groupings and deregulation.

In a previous version, we used the price-to-earning (P/E) ratio. Given that earnings are not the best measure of REITs’ cash flow, we substitute FFO for earnings and include P/FFO in the regressions.

Compared to other variables, dividend payout (DPR) and debt-to-equity (D/E) ratios have more extreme observations that lead to higher averages. We winsorize both DPR and D/E at 10% and 90% levels (all other variables are winsorized at 1% and 99% levels). Nevertheless, our main results are unchanged when we winsorize DPR and D/E at 1% and 99% levels.

Cf., Wang et al. (1993).

Before we winsorize the variables at 1 and 99% levels, the mean number of property transactions per year is 8.41 in our sample, which is comparable to the mean value of 8.50 reported in Kim and Wiley (2019). Whether we winsorize the variables or not does not change our main results.

In a previous version we also computed the CARs using 3 other models: The standard CAPM, the Fama-French 3-factor model (FF) and a market model using the NAREIT index. While these results are qualitatively similar, but somewhat weaker, than those reported here for the FF model with momentum, for brevity they are omitted.

These results are thus more in line with the results in Loderer and Martin (1992) than with numerous other studies that document post-acquisition under-performance of acquirers.

This is consistent with Rau and Vermaelen (1998), who shows that the post-acquisition return on value firms is significantly better than for glamour firms.

In the probit analysis, we use the regional cap rate based on the REIT’s headquarters. We obtain similar results when we aggregate cap rate data at the national level.

The relevance of Q as a measure of the likelihood of investment is explored in Erickson and Whited (2000).

These results are similar to those in Ghosh et al. (2012), although that study is more focused on corporate governance and cash holdings.

These observations are related to the statement made in Mulherin and Womack (2015; p. 155): REIT merger activity appears to be positively correlated with the broader commercial real estate market cycle.

We also estimated a probit model using the approach in Table 8 but the large number of small property acquisitions lead to weaker statistical results than those using the total number of acquisitions.

We also ran regressions on post-acquisition performance but these results were very weak statistically. This fact is possibly attributable to the much smaller size of property acquisitions relative to REIT acquisitions: The median size of the top 200 property acquisitions in our data set is less than 15% of the median size of our REIT acquisitions.

We select 50 random REITs for acquisitions announced during 1994–1998, 2008 or 2009 due to fewer non-acquirer/non-target REITs during these years.

Because these random REITs were not involved in acquisitions, such variables cannot be used as control variables.

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Titel: Acquisitions and the Opportunity Set
verfasst von: Jarl G. Kallberg
Yoshiki Shimizu
Publikationsdatum: 19.10.2021
Verlag: Springer US
Erschienen in: The Journal of Real Estate Finance and Economics / Ausgabe 4/2023
Print ISSN: 0895-5638
Elektronische ISSN: 1573-045X
DOI: https://doi.org/10.1007/s11146-021-09859-9

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