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Do target-country legal institutions affect cross-border mergers and acquisitions? A quantitative literature survey


We undertake a meta-analysis of 1296 estimates of the effect of target-country legal environments on cross-border mergers and acquisitions (CBMAs) compiled from 60 published studies. Although these studies provide effect estimates that are statistically significant, none of the legal variables considered, save civil law, has an effect on either CBMA intensity or the CBMA premium that is large enough to be meaningful. Thus, the studies fail to provide support for legal origins theory or for theories based on cultural distance as explanations for CBMA activity. Studies of the CBMA premium are plagued by inadequate statistical power, by unexplained inter-study differences in effect and by publication-selection bias. Based on our meta-analysis, we suggest reasons why the empirical evidence fails to support theories that have wide acceptance.

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  1. Canabal and White (2008) find that the choice of entry mode is one of the top topics in international business research, and Shen et al. (2017) report that two-thirds of the empirical research on entry mode published in ten leading international business journals deals with predicting the determinants of the entry mode while only slightly over 13 percent deal with the consequences of the entry mode decision for affiliate or acquiring firm performance.

  2. Positive effects include increases in the stock of capital and technology, skill spillovers to domestic industries, effects on the market structure in the host country, etc. There may also be negative effects such a monopolization of target-country markets, repatriation of profits, etc. Whether these effects improve or reduce the welfare of the target country is a matter of some controversy. See, for example, Arnold and Javorcik (2009), Blonigen and Pierce (2016), Chari et al. (2004), Zehty (2022).

  3. Authors may also normalize the intensity measure by dividing the measure of CBMA intensity by target country size, the size of its corporate sector, the number of listed companies, etc. In cases where such adjustment is not made to the intensity measure itself, the inclusion of a measure of target-country size in the specification used to explain CBMA activity may also be seen as implicitly adjusting for target-country size. Alternative measures of CBMA activity drawn from balance of payments data on FDI, whether FDI stocks or flows, are a poor measure of intensity because there are wide disparities between reported stocks and flows and because FDI data are distorted by borrowing from host-country banks and investors and FDI data do not capture the effects of exchange rate changes, forgiveness of affiliate debt by parent companies, reinvested profits of the affiliate, etc. (Fujita, 2008).

  4. See Armitage (1995) for an explanation of event study methodology.

  5. The hypothesis that cultural differences influence how MNCs enter potential host countries is a central component of many theoretical models of FDI including the Uppsala model (Johansen and Vahlene, 1977), Dunning’s (1980) theory of locational advantages, the transaction costs theory of Williamson (1996), etc.

  6. We are grateful to an anonymous referee for bringing this point to our attention.

  7. We chose not to use working papers in our study to keep the literature search manageable. Later in the paper, however, we test for publication-selection bias in the published studies.

  8. The selection and coding of the studies followed the meta-analyses guidelines proposed by Havránek et al. (2020). Estimates in each paper are counted as different from one another if they differ in the dependent variable, the explanatory variables, the time period or countries covered, the specification of the regression equation, or the method of estimation. As necessary, variables were recoded so that higher values of an explanatory variable meant more or better legal protection for investors or greater cultural similarity between investing and target countries.

  9. Combining all estimates of the effect of all legal variables into one overall estimate implicitly assumes that all legal variables have the same effect on CBMA activity and on the CBMA premium. We provide this summary effect estimate as a benchmark against which to compare the effects of individual legal characteristics of the target countries, which also provides a test of our assumption that all legal variables have the same effect.

  10. Coefficient estimates in all studies were recoded if necessary so that a higher value of each explanatory variable would lead to a higher value of the dependent variable.

  11. We caution the reader not to interpret the small effect value for the cultural distance variable as a claim that studies using cultural distance do not find an important effect for cultural distance. This is because we only consider studies that use both legal factors and cultural distance as explanatory variables. Any conclusions about the effect of cultural distance on CBMAs would have to use a different sample that includes all studies that use cultural distance as an explanatory variable, not just studies that use both legal factors and cultural distance.

  12. We discuss this finding at greater length in the Conclusions.

  13. We follow Stanley (2001) in cautioning the reader not to draw conclusions regarding the “true” effect of legal variables on CBMAs on the basis of “vote counting” of the number of studies that report significant positive or negative effects. Heterogeneity of estimated effects is not unusual. For example, Nijkamp and Poot (2005) report that over 200 estimates of the elasticity of wages with respect to unemployment cluster between + 0.1 to − 0.5. Accounting for such heterogeneity is a key aspect of meta-analysis.

  14. Another source of bias may be so-called publication bias, which may result from referees’ and editors’ preferences for papers that do find a significant effect of a variable on outcomes of interest. We address this in Sect. 5.3.

  15. The lack of elasticity estimates may be due to authors reporting regression coefficients but not sample means. In other cases, specifications may differ, and their elasticities may not be directly comparable. Finally, the dependent variable may differ between studies so that, for example, the elasticity of CBMAs with respect to investor protection in a study that uses the number of CBMAs as the dependent variable cannot be compared easily to one that uses the number of CBMAs normalized by the number of listed firms in a country. Using PCCs makes the results of different studies comparable.

  16. See the Appendix for a description of how journal quality weights were estimated.

  17. We can see that the coefficient γ1 in Eq. (5) may become the estimate of the publication bias–adjusted effect size in light of the fact that the following equation is obtained when both sides of Eq. (5) are multiplied by the standard error:

    $${\mathrm{Effect_{size}}}={\gamma }_{0}{SE}_{k}^{2}+{\gamma }_{1}+{w}_{k}. $$

    When directly estimating Eq. (5b), the WLS method, with \(1/{SE}_{k}^{2}\) as the analytical weight, is used.

  18. Nevertheless, we note that meta-analysis, by combining several underpowered estimates, does increase the statistical power of the combined estimate.

  19. Abnormal returns are generally measured by event study methods, although the length of the event window varies from study to study.

  20. We classify any specification that uses the distance between countries and their size as a gravity specification. Some such studies also use factors that explicitly reference cultural distance by means of variables such as same language, colonial ties, etc.

  21. The negative effect on CBMA intensity of using Europe as either the home or target country may be due to economic integration among EU countries, which makes it easier for firms from one country to set up a business in another EU member under the rules of the single market. Thus, CBMAs are not as necessary for entering foreign markets that are in other EU countries.

  22. Another instructive example is Aleksynska and Cazes (2014) who examine such problems with indices of labor market flexibility.

  23. To give a rather extreme example, how should the rating for legal system efficiency change if the system introduced the possibility of settling legal disputes by trial by combat, where the winner of the fight would be judged innocent and the dead party guilty? Those who identify legal efficiency with the impartial gathering of evidence and application of the relevant laws would see the ability to circumvent such legal procedures at a single stroke of the sword as a decline in legal system efficiency. On the other hand, believers in an omniscient and benevolent deity who is inclined to intervene is human affairs would view trial by combat as an improvement in legal efficiency because the outcome would be governed by an all-knowing and benevolent god, thus ridding the legal system of human errors and passions. For a real-world example, see Leeson and Coyne (2012) who argue that a form of “trial by poison” improves the efficiency of Liberia’s legal system.


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This research was financially supported by Czech Science Foundation Grant Number 18-04630S, the Japan Center for Economic Research (JCER), and the Zengin Foundation for Studies on Economics and Finance.

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Appendix: Method for evaluating the quality level of a study

Appendix: Method for evaluating the quality level of a study

This appendix describes the evaluation method used to determine the quality level of the studies subjected to our meta-analysis. All our studies are drawn from refereed journals, and we used the ranking of economics journals published as of February 1, 2018, by IDEAS, which is the largest bibliographic database dedicated to economics and available freely on the Internet ( for our evaluation of journal quality level. IDEAS provides the world’s most comprehensive ranking of economics journals; as of February 2018, 2159 academic journals were ranked. For academic journals that are not ranked by IDEAS, we referred to the Thomson Reuters Impact Factor and other journal rankings and identified the same level of IDEAS ranking–listed journals that correspond to these non-listed journals. We assigned each of them the same score as its IDEAS-listed counterpart.

We divided these 2159 journals into 20 clusters, using a cluster analysis based on overall evaluation scores. We then assigned each journal cluster a score (weight) from 1 (the lowest journal cluster) to 20 (the highest). Thus, in our quality-adjusted estimates, effects reported by articles from the highest-rated journals were given a weight twenty times that given to estimates published in the lowest-ranked journals.

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Brada, J.C., Iwasaki, I. Do target-country legal institutions affect cross-border mergers and acquisitions? A quantitative literature survey. Eur J Law Econ 55, 225–289 (2023).

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  • Foreign direct investment
  • Mergers and acquisitions
  • Legal environment
  • Meta-analysis
  • Capital flows

JEL classification

  • F21
  • F23
  • G32
  • G34
  • K22