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Dance with wolves: firm-level political risk and mergers and acquisitions

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Abstract

While previous studies primarily use economy-wide indicators for political risk, Hassan et al. (Quart J Econ 134(4):2135–2202, 2019) propose that a significant portion of political risk manifests itself at the individual firm level. We use their measure of political risk to examine whether and how acquirers’ firm-level idiosyncratic political risks affect their mergers and acquisitions (M&A) decisions based on a sample of U.S. firms. We find that firms exposed to a high level of perceived political risk are less likely to conduct M&As. Furthermore, the negative association between firm-level political risk and M&As is more pronounced when acquiring firms lack either financial capacities or non-financial political/social capacities. More importantly, while firms with high political risk generally delay M&As, we find evidence suggesting that acquiring firms may hedge against their firm-level political risk by strategically choosing low-risk M&A targets and conducting vertical integration. Finally, we show that effectively hedged deals exhibit superior post-M&A performance in terms of higher announcement return, lower likelihood of subsequent divestiture and higher post-acquisition change in financial performance.

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Notes

  1. In 2020 alone, the value of global M&A reached 3.59 trillion US dollars.

  2. For example, Amazon’s stock price declined by 4.5% after President Trump attacked the company on Twitter because of its aggressive tax avoidance practices in March 2018, while other firms were largely unaffected. For more details, see https://www.reuters.com/article/us-amazon-com-trump-idUSKBN1H51PY.

  3. We recognize Liu’s (2020) concurrent work, which also finds a negative impact of firm-level political risk in M&A transactions. However, our study differs in focus from Liu (2020), who examines how the negative relationship between firm-level political risk and M&A outcomes varies according to the acquiring firms’ characteristics. In contrast, our study explores the factors that can moderate the negative effect of firm political risk on M&A likelihood. We also provide insights to acquiring firms with high political risk on approaches to hedge the risk. We find that acquiring firms can effectively hedge against their political risk by appropriate M&A strategies, as evidenced by positive post-M&A performance.

  4. The data was accessed and downloaded from https://sites.google.com/view/firmrisk

  5. Therefore, the mean value of the overall political risk (ACQ_POLRISK) is lower than the mean values of the individual topic specific political risk index.

  6. We also conduct a regression to examine the number of acquisitions against firm-level political uncertainty with firm fixed effects. The untabulated results show that the coefficient of POLITICAL_RISK is negative but statistically insignificant. In conjunction with the findings presented in Table 3, we speculate that firm-level political risk mainly leads to a delay in M&A activity rather than a change in the total number of transactions. However, the results should be interpreted with caution due to the infrequency of M&A activity among firms; in other words, the number of acquisitions may not be responsive to political risk.

  7. The marginal effects of other individual components are not reported for brevity. They are all smaller than that of the economic policy and budget related political risk (0.99%).

  8. We do not include year fixed effects here because firms are subject to the same policy uncertainty in a given year. Year fixed effects capture most of the explanatory power.

  9. The results remain robust when five-day or seven-day event windows are examined.

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Acknowledgements

We thank the helpful comments from the audience of Hawaii Accounting Research Conference (2022). We are grateful for the constructive comments from the editor and two anonymous referees. Haina Shi acknowledges financial support from the National Natural Science Foundation of China (Grant No. 72372028) and from Sci-Tech Innovation Foundation of School of Management, Fudan University. Xin Chen acknowledges financial support from the Fundamental Research Funds for the Central Universities (No. 63232168). All errors are our own.

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Authors and Affiliations

  1. School of Economics and Management, Southwest Jiaotong University, Chengdu, China

    Xin Chen

  2. School of Management, Fudan University, Shanghai, China

    Haina Shi

  3. School of Business, Hong Kong Baptist University, Hong Kong, China

    Gaoguang Zhou

  4. College of Business, City University of Hong Kong, Hong Kong, China

    Xindong Zhu

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  1. Xin Chen
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Appendix

Appendix

Variable

Definition

Dependent variables

 

M&A_DUMMY

An indicator that equals one if a firm makes an M&A announcement in a given year and zero otherwise

TAR_POLRISK

An indicator that equals one if the M&A target belongs to an industry with an above-median political risk component, and zero otherwise

VERTICAL

An indicator that equals one if a merger is a vertical integration based on the benchmark input–output tables published by the BEA and zero otherwise. We use the “make” and “use” tables to estimate the output from industry i required to produce one dollar of output for industry j and vice versa. If either value exceeds 5%, we classify a merger as a vertical integration

LOW_CFVOL

An indicator that equals one if the variance in industry three-year cash flows scaled by assets is below the median and zero otherwise

CAR

The three-day cumulative abnormal return of the acquirer using the market model estimated using the return data of 200 trading days ending two months before the announcement date

DIVEST

An indicator variable that equals one if an acquisition has a subsequent divestiture (i.e., the M&A target has the same three-digit SIC code as the divested firm, whose parent is the acquiring firm in the original M&A) in the three-year period following an acquisition, and zero otherwise

ΔROA

The change in industry-adjusted ROA from one year before the acquisition announcement to three years after the acquisition announcement

Test variables

 

ACQ_POLRISK

The natural logarithm of acquiring firms’ average of the eight individual political risk indexes (unadjusted), including ECONOMY, ENVIRONMENT, TRADE, INSTITUTION, HEALTH, SECURITY, TAX, and TECH. Data is provided by HHLT (2019)

ECONOMY

The natural logarithm of acquiring firms’ average economic policy and budget component of firm-level political risk. Examples of such risk include issues related to accounting, bankruptcy, economics and economic development, and economic policies and budgets related to particular industries, etc. Data is provided by HHLT (2019)

ENVIRONMENT

The natural logarithm of acquiring firms’ average environmental component of firm-level political risk. Examples of such risk include issues related to agriculture, environment and superfund, hazardous, and solid waste, etc. Data is provided by HHLT (2019)

TRADE

The natural logarithm of acquiring firms’ average trade component of firm-level political risk. Examples of such risk include issues related to commodities, foreign relations, tariffs, and trade, etc. Data is provided by HHLT (2019)

INSTITUTION

The natural logarithm of acquiring firms’ average institutions and political process component of firm-level political risk. Examples of such risk include issues related to government issues and torts. Data is provided by HHLT (2019)

HEALTH

The natural logarithm of acquiring firms’ average health component of firm-level political risk. Examples of such risk include issues related to Medicare, medical research and clinical labs, pharmacy, etc. Data is provided by HHLT (2019)

SECURITY

The natural logarithm of acquiring firms’ average security and defense component of firm-level political risk. Examples of such risk include issues related to defense, disaster and emergency planning, and homeland security, etc. Data is provided by HHLT (2019)

TAX

The natural logarithm of acquiring firms’ average tax policy component of firm-level political risk. Examples of such risk include issues related to taxes. Data is provided by HHLT (2019)

TECH

The natural logarithm of acquiring firms’ average technology and infrastructure component of firm-level political risk. Examples of such risk include issues related to aerospace, computers and information technology, and science and technology. Data is provided by HHLT (2019)

Control variable

 

SIZE

The book value of assets (in billion US dollars)

TOBINS_Q

(Book value of assets − book value of equity + market value of equity − deferred taxes)/book value of assets

PRIOR_RET

The buy and hold 12-month stock return of the year preceding an M&A announcement

GSALES

The average of the annual sales growth of the acquiring firms over the last 3 years

LEVERAGE

The acquiring firms’ long-term debt plus debt in current liabilities, all divided by total assets

NONCASH_WC

The ratio of (working capital–cash) to the book value of the acquiring firms’ assets

FIRMAGE

The natural logarithm of the number of years that the acquiring firms appear in Compustat

EPU

The natural logarithm of the average EPU Index of a year developed by Baker et al. (2016)

CASH%

The percentage of the deal value paid in cash

HIGHTECH

An indicator that equals one if an acquiring firm’s four-digit SIC code is equal to 3571, 3572, 3575, 3577, 3578, 3661, 3663, 3669, 3671, 3672, 3674, 3675, 3677, 3678, 3679, 3812, 3823, 3825, 3826, 3827, 3829, 3841, 3845, 4812, 4813, 4899, 7371–7375, 7378, or 7379 and zero otherwise

T_FEE

A continuous variable that equals the dollar value of the M&A target’s termination fee

HOSTILE

An indicator that equals one if the M&A deal is a hostile takeover and zero otherwise

DIVERSIFY

An indicator that equals one if the acquirer and target belong to different two-digit SIC code industries and zero otherwise

Variables in cross-sectional tests

 

WW

The WW index (Whited and Wu 2006) is calculated as − 0.091CF − 0.062DIVPOS + 0.021TLTD − 0.044LNTA + 0.102ISG − 0.035SG, where CF is cash flow deflated by total assets, DIVPOS is an indicator that equals one if the firm pays cash dividends and zero otherwise, TLTD is long-term debt deflated by total assets, LNTA is the natural log of total assets, ISG is the firm’s four-digit industry sales growth, and SG is firm sales growth

FCF

Free cash flow is defined as (cash flow − average investment over the past three years)/total market value

S_GOV

The natural logarithm of sales to government in an industry over the past five years

CSR

Total strengths minus total concerns based on KLD’s seven social rating categories: community, corporate governance, diversity, employee relations, environment, human rights, and product

B_ETHICS

An indicator that equals one if the acquiring firms have the appropriate communication tools to improve their general business ethics and zero otherwise

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Chen, X., Shi, H., Zhou, G. et al. Dance with wolves: firm-level political risk and mergers and acquisitions. Rev Quant Finan Acc (2024). https://doi.org/10.1007/s11156-024-01274-4

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