Overseas M & A under Economic Policy Uncertainty
—An Empirical Study Based on Overseas M & A in the United States

DOI: 10.4236/me.2020.1111118   PDF   HTML   XML   71 Downloads   258 Views  

Abstract

Past studies have shown that overseas mergers and acquisitions, whether developed or developing countries, are usually affected by natural resources, strategic resources, market search, institutional quality, business environment and so on. In addition, American economic and environmental policies often take the initiative to change, thus affecting the world’s other economies. On December 2016, global biggest economic policy uncertainty is the election of USA President Donald Trump. The effects of it to liberalized trade and global capital flows on the world are spreading. From this, it enlightens the empirical exploration of this paper: whether usepu (which means the uncertainty of the economic policy of the US) will affect the behavior of USA cross-border M & A and how it will affect the influence of cross-border M & A. Based on panel data from the United States of America for overseas mergers and acquisitions in 22 countries, including China, Britain, Germany and Japan, from 1997 to 2016, it is concluded that: First, every 1% change of the economic policy uncertainty index of the last period relative to the mean value will cause the reverse change of the next M & A amount by about 0.7%; For every 1 unit increase in the uncertainty index of home country’s economic policies in the last period, the number of outbound mergers and acquisitions decreased by about 0.5. Second, There is no obvious relationship between the foreign M & A amount of the home country and epu (which means the economic policy uncertainty), epu1 (which means the uncertainty difference between the two countries) and epu2 (which means the absolute value of the uncertainty difference between the two countries). There is an inverse relationship between the number of mergers and acquisitions and the uncertainty difference.

Share and Cite:

Shi, S. (2020) Overseas M & A under Economic Policy Uncertainty
—An Empirical Study Based on Overseas M & A in the United States. Modern Economy, 11, 1719-1741. doi: 10.4236/me.2020.1111118.

1. Introduction

The United States is the country with the most foreign direct investment stock in the world and the country with a long history of foreign direct investment. From the GDP data recorded by the World Bank since 1960, the United States has always ranked first in the world and maintained an absolute gap with the second in the world. Such a large economy has always remained attractive to world capital, while at the same time it has strong financial strength to seek overseas development. Although the United States is a developed economy, as the world’s largest foreign investor, the driving and influencing factors of foreign investment are similar to those of all other economies, mainly expanding overseas markets, seeking natural resources, or strategic assets or maintaining markets. As an innovative country like the United States, it is mainly seeking overseas markets, seeking natural resources and reducing costs and increasing profits.

From the development course of the OFDI of the USA, based on technology and transferable advantages, U.S. investment in developed countries is dominated by M & A, while investment in developing countries is dominated by greenfield investment. This is due to the increasingly liberal international trading environment, breaking through market barriers, local production, local sales as the traditional factors affecting the location of U.S. OFDI, its importance is greatly weakened. It is more important to reduce production and R & D costs, improve the technical strength of enterprises and the competitiveness of products in order to adapt to the more intense international competition under the background of economic globalization, access to cheap natural resources, labor, knowledge, technology, technical talent and other “creative assets” in developing countries.

From these years on the driving factors of U.S. OFDI (Yang, 2011) summarized as follows: First, multinational corporations are the main driving force of U.S. OFDI; Second, the international status of the dollar is an important pillar of U.S. OFDI; Third, the incentive policy of the U.S. government is a strong guarantee for the rapid development of U.S. OFDI.

Finally, based on the actual factors of American outward investment and the influence factors of foreign direct investment in other developed countries, there are mainly macro-national political, economic, geographical, cultural, institutional and other levels. First, with the continuous development of trade globalization, the economies of various countries are open. Factors such as market size, income level, and qualified productive labor have a significant impact on the timing and location of U.S. investors in the region (FragKiskos Filippaios, Marina Papanastassiou, & Robert Pearce, 2003). Political and macroeconomic stability, as well as transparent legal provisions on foreign ownership and return of profits, are important variables for potential investors (Resmini, 2000). (Bevan & Estrin, 2004) Analysis of FDI flows between EU member States and economies in transition using data from 1994 to 1998, resulting in specific variables from sources and host countries including GDP, imports (from EU-15), investment risk ratings, physical distance and labour costs. The following year, Joel I Deichmann (2001) International trade is derived from empirical models, the investment environment measured by risk ratings is, the host transport infrastructure and labour costs, the host country’s unemployment rate and the host country’s market are influencing factors for outward investment, and similar “location-specific attributes” that determine FDI inflows are labelled, such as geographical proximity, cultural linkages, economic comparisons and information gaps, while exchange rate indices are introduced to measure risk (Janicki & Wunnava, 2004). Studies have shown that the main determinants of FDI inflows to Central and Eastern European countries are the size of host economies, host country risks, host country labour costs and trade openness.

On the impact of economic uncertainty index on the economy in the world can be summed up as macroeconomic, micro-finance, research shows that the epu index and economic growth index (GDP, PMI, industrial added value) has a negative correlation; the difference between the European and American epu index has a positive correlation with the dollar index and leads the dollar index for 1-2 months; China epu index is positively correlated with the bond market and negatively correlated with the stock market. Based on data from Japan after the bubble burst, Xiu-Mei Lin & Qing-Zhao Li (2018) found that economic policy uncertainty has a significant negative impact on final demand. This verifies that economic policy uncertainty itself is an important driving force leading to recession. Experience shows, the negative impact of policy uncertainty shocks on GDP, investment, consumption, exports and price movements, Causes the real effective exchange rate to depreciate, prompting stock prices and real estate prices to fall. The main mechanism by which policy uncertainty is found to affect the macroeconomy is the expected channel (Jin, Zhong, & Wang, 2014). (Rao, Yue, & Jiang, 2017) also found the impact of China’s economic policy uncertainty index on corporate investment and investment efficiency, and found that increased economic policy uncertainty led to a significant decline in corporate investment, The dynamic influence of economic policy uncertainty on short-term international capital flow in China is tested (Lin, Li, & Li, 2017). Based on short-term international capital data between China and the United States, to study the negative impact of economic policy uncertainty on short-term international capital, the impact is the biggest under high uncertainty; United States economic policy uncertainty has a significant positive impact on short-term international capital, with the greatest impact under moderate uncertainty. Large spreads between China and the United States do not necessarily attract short-term international capital inflows, while the expected depreciation of the renminbi will lead to short-term international capital outflows. Yu-Cheng Jia & Cheng Zhang (2018) used China’s overseas M & A data, and found that the “inverse cycle” characteristics of cross-border M & A of Chinese enterprises, economic policy uncertainty and M & A are positively correlated, and are more obvious in the sample of state-owned enterprises.

Economic uncertainty in the impact of international trade, Kyle Handley (2014) found that increased economic policy uncertainty in host countries will lead to reduced entry of exporting countries and reduced application for tariff relief. Hong-Duo Liu & He Chen (2016) used the World Export Dynamics Database developed by the World Bank, finding that the annual economic policy uncertainty index of export destination countries is constructed on the basis of the monthly index of economic policy uncertainty (BBD), and then the impact of economic policy uncertainty of destination countries on export dynamics of source countries is examined. The study finds that the economic policy uncertainty of host countries is inversely related to the trade exports of exporting countries, and the increase of uncertainty in destination countries will lead to export withdrawal and reduction of exports.

2. Issues

According to the summary of the previous studies, it can be found that the previous studies on the influencing factors of foreign direct investment in developed countries mainly focus on economic, cultural, institutional, geographical, natural resources, science and technology and so on. The economic aspect is mainly the market and labor cost, and even the exchange rate index is introduced to represent the risk in the influence factors of the previous foreign investment. The main body of the study is the whole investment, without distinguishing between overseas investment and domestic investment, nor the types of foreign direct investment. Yu-Cheng Jia & Cheng Zhang (2018) introduced the micro index of economic policy uncertainty to study the relationship between real enterprises’ overseas mergers and acquisitions. It affects the pre-judgment, investment enthusiasm and confidence of enterprises through expectation, and then affects the actual overseas M & A behavior.

At the same time, according to the reality observation, the uncertainty fluctuation of American economic policy since 2016 has an upward trend compared with the average, which leads to the increasingly difficult to predict the situation of the international economy and the uncertainty of foreign investment and trade. This is bound to affect overseas mergers and acquisitions of American companies and the flow of capital throughout the country. The unpredictable results of U.S. economic policies will increase domestic economic volatility and discourage investment enthusiasm and confidence. In view of the unreasonable economic policy implemented by the United States in recent years, the article wants to study the impact of economic policy uncertainty on American own overseas direct investment, to predict the impact of U.S. economic policy fluctuations on the United States itself and on the world. In addition, the overseas M & A investment in the United States has a long history, complete data, can obtain more complete information of the host country information and can improve the accuracy of the data.

Considering the increase of economic policy uncertainty and the suppression of investment enthusiasm and expectation of domestic investors, it will systematically reduce investment and reduce the scale of overseas mergers and acquisitions. Therefore, this paper puts forward the following assumptions:

Hypotheses 1, the uncertainty of American economic policy “usepu” have a negative impact on the scale of American overseas mergers and acquisitions.

Hypotheses 2, there is a negative correlation between the scale of overseas mergers and acquisitions in the United States and the uncertainty difference epu1 the economic policy of the host country.

Hypotheses 3, there is also a negative correlation between the size of overseas mergers and acquisitions in the United States and the absolute value epu2 of the uncertainty difference between the two countries.

In this paper, panel regression is used to verify the above three assumptions.

3. Data and Model Building

3.1. Data Sources and Sample Selection

The data comes from the BYD Global M & A Database zephyr, which contains more comprehensive U.S. data since 1997. This paper selects all the overseas M & A data from 1997 to 2018, the total number of overseas M & A cases searched was about 62,000, and the data were processed as follows: First, delete both parties are transactions in the United States; Second, delete the status of the transaction as cancelled or still in the state of announcement; Third, delete other countries that currently do not publish the economic uncertainty index, only retain 22 of China, Britain, Japan, Germany, France, Chile, Russia M & A countries, these M & A covered a total of 38,985 M & A events in various industries in the United States, accounting for more than half of all M & A events since 1997; Then, delete the time period after 2016 M & A transactions. And then, make the non-availability cases of M & A cases zero and record them as a M & A transaction. Finally, conservative estimates of the total amount of mergers and acquisitions in the United States of 22 countries that recorded EPU amounted to 2.9 trillion Euros, with about 38,985 acquisitions.

Additionally, in the treatment of other independent variables in the following, partial vacancy values were also processed in the absence of WGI (global governance indicators) in 1999 and 2001, in the case of relatively sound data in other years, and in the case of incomplete data on natural resources exports, to obtain balanced panel data for robust results.

3.2. Model Building

In the case that other variables are controlled, hypothesis 1, hypothesis 2 and hypothesis 3 are verified by regression of lusepu (which means the uncertainty of economic policy in the United States with a lag of one period) to see whether the uncertainty in the United States has an impact on the scale of overseas M & A in the United States and the direction of the impact. The model is as follows:

ln m i t = α 0 + α 1 lusepu i t + α 2 c c i t + α 3 ps i t + α 4 rl i t + α 5 metal i t + α 6 fuel i t + α 7 ln tapi i t + α 8 ln gdp i t + α 9 ggdp i t + α 10 ln pgdp i t + d 1 + d 2 + u i + u t + δ

The acquirer is always the United States, while the acquirer is a different country, i mean different M & A countries, t mean different years. The model also controls individual and temporal effects at the national level to ensure that the results are robust. The latter are the control variables representing political system, natural resources, strategic resources, market scale, cultural gap and geographical gap.

3.3. Variable Definitions

Main explanatory variables:

1) Economic policy uncertainty. Uncertainty is measured by the Economic Policy Uncertainty Index (epu), from the home and host country perspectives, respectively. Among them, usepu is the uncertainty of America as a home country, epu is host country uncertainty. After all, taking into account the causal endogenous problem, Delayed processing of home country uncertainty indices is lusepu. On that basis, Representation of bilateral uncertainty differences in absolute values of uncertainty differences between home and host countries, into the analytical framework. Uncertainty indicators data from Baker et al. (2013) constructed the Economic Policy Uncertainty Index website (Economic Policy Uncertainty), the data is updated in time on the website. This paper chose the data from 2000 to 2016. The reason for this index is that EPU concerned about the degree of change in national economic policies, Representing the magnitude of the uncertainty factors from the external environment (policy environment) in the process of institutional transformation, The index focuses only on the extent of changes in economic policy, does not regulate the merits of the policy, Both objective and neutral characteristics.

In addition, many research results use this index to measure uncertainty and explain the effectiveness of the index. By counting the number of articles in the media (newspapers) with greater influence in countries that deal with “discussion of economic policy uncertainty”, According to the following formula to

calculate the uncertainty index: EPU i m = ln ( 100 × n N ) , The EPU i m is the i

country of the m months uncertainty index of economic policy, n the number of articles in accordance with statistical rules, N the total number of articles counted for the month. For articles that belong to economic policy uncertainty, according to a series of similar or contain “vague, hesitant, uncertain, suspicious, uncertain, unconfirmed, vague” or word meaning determination (Baker et al., 2013), our data are annual. Therefore, the average conversion of EPU raw data

(in monthly terms) is required: epu i t = m = 1 12 epu i m 12 . As the EPU index website

has been published so far, the number of sample countries expands gradually, until 2018, the sample can be obtained by the number of countries including the AU, BR, CL, CA, CL, CN, CO, DE, ES, FR, GB, HK, and IN IT, IE, JP, KR, MX, NL, RU, SE, SG 22 countries, so there are differences in the number of samples used in specific tests.

Other control variables:

2) The market of the host country. Especially for developed countries with ownership advantages, the purpose of foreign investment is mainly trade-based investment. Generally speaking, the greater the market size and market growth potential of the host country, the more favorable it is for the M & A country to enter the country to obtain growth benefits to reduce costs and give full play to the advantages of economies of scale.

Market-specific measures include three variables, GDP, per capita GDP (PGDP) and GDP growth rates (GGDP); and GDP used to measure the market size of the host country (Buckley et al., 2007); PGDP used to measure the market purchasing power of a country’s inhabitants (Bénassy-Quéré et al., 2007); GGDP used to measure a country’s market potential (Billington, 1999; Zhang & Daly, 2011). The data comes from the World Bank database (World Bank Data), And GDP, PGDP at the same dollar level as in 2010. Therefore, the indicator is comparable in different years worldwide.

3) Mineral resources (metal) and oil and gas resources (fuel) in the host country’s natural resources. In general, Natural resources are a natural endowment, the day after tomorrow is not easy to change, but energy demand is a rigid demand. National firms view mergers and acquisitions as complementing domestic energy supply gaps, Meeting energy needs an important way to ensure national economic security. Therefore, the richer the host country’s natural resources. M & A is also more likely to occur. The main motivation of international direct investment in enterprises summarized in traditional international literature includes the acquisition of natural resources, This article uses it as a control variable, the selection of specific indicators is based on Buckley et al. (2007) and Kolstad & Wiig (2010), The abundance of mineral metals (ORE) and oil and gas resources (fuel) in a country is measured by the proportion of mineral metals and oil and gas resources exports to the export of goods in that country.

Since the scarcity of oil and gas resources in the United States changed from a small number of exporters to a leading country after 2012, in this paper, oil and gas export fuel and ore exports are metal measured separately. And the data is derived from the United Nations Conference on Trade and Development database.

4) Host country strategic assets (TAPI). Pak & Park (2005) according to the research, the ODI of Japan have different motivations to invest in different countries, and the investment in developed economies such as the United States and Europe is to acquire knowledge of strategic resources. Similarly, the internationalization management theory of latecomer enterprises points out that developing country enterprises regard transnational investment as an important way to obtain strategic assets as a “springboard” to complete technology catch-up, enhance core competitiveness, and enhance the income of operating added value (Luo & Tung, 2007; Wu & Su, 2014). As the world’s largest economy, the United States is in the world’s advanced level of technology, but cannot do absolute technology in all aspects leading any economy in the world. Therefore, in terms of strategic resources, the number of strategic resources of the host country can still have an impact on foreign mergers and acquisitions in the United States.

A country’s total annual strategic assets, measured by the total number of patents filed by local and non-local residents in one year, are calculated in logarithmic form it contains both the level of knowledge and the level of knowledge conversion to technology. That’s according to the World Bank’s World Development Indicator (WDI) database.

5) Institutional quality. The system quality of this paper mainly examines the political environment of the potential target country, especially the stability, law and order, and the degree of corruption of the political system closely related to economic activities. Among them, political stability, law and order show the stability of a country’s political environment and the predictability of trading rules, represent the degree to which a country provides a fair and secure environment for market participants, and measure more the political and economic risks of investment; while the degree of corruption measures more the transaction costs of economic activities. Robock (1971) believes that political risks have an important impact on a country’s business environment. Blonigen (2005) shows that a good host country rule of law environment can help reduce transaction risk and the additional costs, and commissions or bribes are caused by corruption can increase transaction costs, which is an important obstacle to overseas investment. Wei (2000) believes that corruption has an important impact on the scale and distribution of investment. Naude & Krugell (2007) view host country law and order as important determinants of ODI, while corruption is often used as an important measure of host country business environment.

Therefore, this paper mainly chooses three dimensions: political stability index PS, corruption control CC and legal system index RL to measure the institutional quality of host country to investigate the impact of these factors on overseas M & A in China. The higher the index value of these three dimensions, the better the quality of the system, and the more attractive the host country is to the M & A country, then it is speculated that the M & A country is more inclined to invest many times and invest more funds.

6) Cultural differences. It is generally believed that, when other conditions are the same, countries with small economic cultural differences have a stronger incentive to cross the transaction than the cultural gap, larger M & A and more opportunities for multiple M & A transactions. The variables used here to express cultural gaps take the simplest and rougher way of traditional language representation. The common language countries in the article mainly regard English as the mother tongue and the main language country as the common language country, and let the mute variable d 1 = 0 , otherwise d 1 = 0 . Data comes from the CEPH database.

7) Common border. Countries with common borders have a natural advantage in space cooperation. Countries with common land borders with the United States here d 2 = 0 , otherwise d 2 = 0 . Data comes from the CEPH database.

Table 1 is the basic statistical description of the variables, which covers mergers and acquisitions in 22 countries and 22 host countries from 1997 to 2016. It can be seen that at the level of national annual M & A, 422 annual M & A transactions occurred in 22 countries in 20 years. Among them, the dependent variable m is the sum of the M & A amount of the United States to the host country for one year, and the M & A amount unit (thousands of Euros). N represents the total number of mergers and acquisitions in a country by the United States in a year and the sample number of mergers and acquisitions. The variable country is a stata defined national variable, a total of 22. And time t is the time period that occurs in each country. The meaning of other explanatory variables is the same as that of index selection.

First of all, the correlation coefficient of each variable is tested, by testing Pearson correlation coefficient, the test results are given in Table 2 below. The results show that the correlation coefficient between political stability, legal order quality and corruption control index is very high, And more than 0.6. The solution to this situation is to put the institutional quality variables in the basic regression equation to show the influence of each variable. Moreover, the correlation

Table 1. Descriptive statistics for variables.

Table 2. Pearson correlation coefficient.

Note: the coarsening part of the same row for each variable is the Pearson correlation coefficient, the next row is the P value, and the * in the table represents all cases of P < 0.1. Specific significance level can see the specific P value of the next line.

Note: the coarsening part of the same row for each variable is the Pearson correlation coefficient, the next row is the P value, and the * in the table represents all cases of P < 0.1. Concrete significance level can see the specific P value of the next line.

coefficient between variable PGDP and system quality is also higher than 0.6 and between GDP and tapi is also higher than 0.6. Here, the regression will take lnPGDP and lnGDP to reduce the collinearity. In addition to the serious collinear relationship between the variables mentioned above, there is no obvious serious collinearity problem between other variables

4. Analysis of Results

Before the results are displayed, the regression model is tested for the model selection of fixed effect and immediate effect, and the fixed effect model is selected by Hausman test results. The specific inspection results are in the attached table.

Table 3 shows the basic regression results based on the data of the unbalanced panel 1998-2016. First of all, the article wants to study the impact of uncertainty of American economic policy on M & A. Considering the lag effect of economic policy uncertainty on M & A. Therefore, Lusepu, a lagging phase of economic policy uncertainty in the United States, is adopted as an independent variable, and it can be used as tool variable to prevent endogenous influence to accurately study the influence of American policy uncertainty on M & A. it can be seen from the regression results of the basic regression equation in the case of political system and other control variables that the quality of the legal order is added separately in the case of corruption control, political stability and legal order. The impact of the uncertainty of US economic policy on its own overseas mergers and acquisitions is significantly negative at 5% level. Because past studies have shown that economic policy uncertainty is inversely related to a country’s economic growth rate, the greater the uncertainty of a country’s economic policy, the greater the negative impact on the economy. Then, when the overall environment is relatively negative, individual enterprises will also be affected. Therefore, the overall amount of M & A is a decreasing trend. Then, the symbols

Table 3. Regression results of the basic model.

t statistics in parentheses; *represent p < 0.05, **represent p < 0.01, ***represent p < 0.001.

of other control variables are also consistent with expectations. The larger the market size is, the more favorable it is for American foreign M & A. The richer the host country’s oil and gas resources, the more mergers and acquisitions the United States will make. Then the influence factors of host country’s system are not significant in this case. In addition, due to the number of samples, the common boundary and common language mute variables have serious collinear problems in the regression equation and are not reported.

The result is that for every unit of the U.S. economic policy uncertainty index that goes up, the amount of foreign M & A falls by about 0.6%. If the last uncertainty index LUSEPU a standard deviation, the amount of foreign M & A will change by 18% in the next period: equivalent, the uncertainty index will change by 0.7% relative to the average, and the average amount of foreign M & A will change by 0.7%, which has a great impact on American overseas M & A. For every percentage increase in the proportion of oil and gas exports from the host country, the amount of mergers and acquisitions by the United States on average increases by about 4.6 percentage points. For every percentage increase in the host country’s GDP, the amount of foreign mergers and acquisitions in the United States rose by about 2.6 percentage points. It can be understood that the uncertainty of economic policy in the United States has a similar impact on the amount of mergers and acquisitions per 1% change in the mean value and the change of 0.27% GDP. So it can be predicted that the uncertainty of economic policy is very important to the real economy.

Table 4, Table 5 are also based on the data regression results of the non- equilibrium panel 1998-2016, mainly for the hypothesis 2 and 3. Hypothesis 2 is to test whether the difference and absolute value of the uncertainty of economic policy between the United States and the host country have an impact on the M & A from the United States to the host country. Other control variables, like those in the basic regression model, are the difference between the main independent variables and the uncertainty of the two countries. Based on the results of the external data of 22 countries, the difference of economic policy uncertainty index between the United States and the host country has less and less significant impact on the amount of foreign mergers and acquisitions in the United States. Then the market size of other control variables and the influence of oil and gas resources in natural resources on American overseas mergers and acquisitions are smaller and smaller than the size of the basic regression significantly positive in the same direction as expected. Other results are similar to Table 3.

5.1. Change the Dependent Variable into the Number of Acquisitions

Dependent variables are replaced by the number of mergers and acquisitions by the United States to range of 0 to 1538. Other explanatory variables have the same meaning as explained above. The Hausmann test of model selection was also carried out before the double fixed effect was selected. The results are as follows:

Table 4. Other regression results.

t statistics in parentheses; *represent p < 0.05, **represent p < 0.01, ***represent p < 0.001.

Table 5. Other regression results.

t statistics in parentheses; *represent p < 0.05, **represent p < 0.01, ***represent p < 0.001.

n i t = α 0 + α 1 lusepu i t + α 2 cc i t + α 3 ps i t + α 4 rl i t + α 5 metal i t + α 6 fuel i t + α 7 ln tapi i t + α 8 ln gdp i t + α 9 ggdp i t + α 10 ln pgdp i t + + d 1 + d 2 + u i + u t + δ

From the results in Table 6, it can be seen that there is a negative correlation between the number of mergers and acquisitions in the host country and the economic uncertainty index of the United States itself at a significant level of 5%, indicating that under other conditions, the United States’ own economic uncertainty index dropped 0.5 times per unit. It shows that the adverse effects of the uncertainty of American economic policy on the economy spread to the behavior of overseas investment, the enterprises as a whole reduce the economic

Table 6. Robustness test regression results—Indicators to replace.

t statistics in parentheses; *represent p < 0.05, **represent p < 0.01, ***represent p < 0.001.

investment activities, and the frequency of foreign investment M & A activities is also reduced. For each percentage increase in the GDP of the host country, the impact on the number of overseas mergers and acquisitions in the host country is significantly increased. It shows that the search for market size is an important motive for overseas M & A for the United States. Overall, the four regression equations in Table 6 confirm that the uncertainty index of the United States has a negative effect on the amount and number of overseas mergers and acquisitions.

In addition, a supplementary test of Table 7 was performed, let the number

Table 7. Robustness test regression results—Indicators to replace.

t statistics in parentheses; *represent p < 0.05, **represent p < 0.01, ***represent p < 0.001.

of mergers and acquisitions regress the host country uncertainty index (1) to (4), the difference between the United States and the host country uncertainty index (5) to (8), and the absolute value of the difference (9) to (12), respectively. The result is not exactly the same as the amount of the merger, Only (5) to (8), the effect of the uncertainty difference between the two countries on the number of mergers and acquisitions in the United States is significantly negative at a significant level of 5%, that is, the greater the difference between the United States and the host country, then the number of American mergers and acquisitions in the host country will decrease, this shows that companies tend to go to countries with greater economic policy uncertainty than the United States for overseas mergers and acquisitions. This shows that the greater the uncertainty of the host country’s economic policy, the more attractive the United States to carry out overseas mergers and acquisitions. The results of other (1) to (4) and (9) to (12) are the same as the results of the merger amount, and it shows that the absolute value of uncertainty and the uncertainty of home country have no effect on M & A in the United States.

5.2. Replace Unbalanced Panel with Balanced Panel

In the overall data from 1997 to 2016, due to the discontinuity of some countries’ indicators of some years, the balance panel from 2003 to 2016 was used to conduct a regression to test the impact of the uncertainty of the US’s own economic index on the amount and number of M & A.

As can be seen from Table 8, America’s own economic policy uncertainty has a negative impact on the amount and number of overseas acquisitions in the United States, And the effect was significant at 5%, After balancing the panel, The impact of economic policy uncertainty index on M & A has increased, The underlying regression was a 1 unit increase in the economic policy uncertainty index, M & A fell 0.6%, Now here is a drop of 0.7% with a small increase. It shows that overseas mergers and acquisitions are more sensitive to economic policy uncertainty. The impact of oil and gas resource fuel and market size GDP on M & A amount has not changed much. In the same way, the impact on the number of mergers and acquisitions is similar. The impact of the previous unit on the number of mergers and acquisitions was 0.5 to 0.6 here. It shows that American overseas mergers and acquisitions are more sensitive to their own uncertainty index.

5.3. Regression of the Balance Panel Data from 2008 to 2016 after the Financial Crisis

Because of the subprime mortgage crisis in the United States in 2008, the data after this point should be returned separately to test the robustness of the impact. From the regression results: the impact of the United States’ own index on its own overseas mergers and acquisitions is no longer significant. However, the control variables appear new significant variables, the results show that the M &

Table 8. Robustness test regression results—Data to replace.

t statistics in parentheses; *represent p < 0.05, **represent p < 0.01, ***represent p < 0.001.

A amount and the strategic resources of the host country show a reverse relationship, which is not completely consistent with the facts. Therefore, the results are checked and found after excluding the sample data. A large number of sample size is missing, resulting in the original linear irrelevant indicators also become relevant. There is a serious collinearity between lntapi and lngdp here. So the symbol is wrong. But there is the fact that uncertainty about U.S. economic policy has no longer had a significant impact on U.S. overseas acquisitions. The explanation is as follows: First, the economic crisis has affected the economy of the United States itself and the whole economy, at this time the United States is in the low valley of cyclical economic fluctuations, the capital market of the United States has been seriously hit, at this time the capital is lacking. Therefore, in the system, the total amount of foreign mergers and acquisitions will be affected and will absorb the impact of economic policy uncertainty. Second, because the amount of panel data is not large, it is easy to lose the sample information by balancing twice, which leads to the result that it is easy not to be significant.

Table 9 also shows that the impact of economic uncertainty on the number of mergers and acquisitions in the United States can still be partially significant.

Table 9. Robustness test regression results—Data to replace.

t statistics in parentheses; *represent p < 0.05, **represent p < 0.01, ***represent p < 0.001.

The results show that at the significant level of 5%, the economic policy uncertainty index rises by 1 unit, and the number of overseas mergers and acquisitions drops 0.6 times. This shows that even after the economic crisis, the activity of foreign M & A is still based on the uncertainty of domestic economic policy. The more uncertain the domestic economic policies are, the more conservative enterprises are and the less willing they are to make transnational investments, which will reduce overseas M & A activities.

6. Conclusions and Implications

According to the regression results of American M & A data from 1997-2016, there is a negative relationship between American overseas M & A and its own economic policy uncertainty index. It shows that the uncertainty of economic policy in the United States will dampen the enthusiasm of investment and restrain the expansion of enterprises. And from the overall regression results, under other unchanged conditions, for every 1% change in the uncertainty of economic policies in the United States relative to the mean, the amount of overseas mergers and acquisitions in the United States changes by 0.7%, which is equivalent to the impact of 0.27% change in the GDP of host countries. The number of foreign mergers and acquisitions in the United States is also negatively affected by the uncertainty of its own economic policies. The degree of influence is that for every 1 unit change in the previous index, the number of mergers and acquisitions in the host country also decreases by about 0.5 times. The relationship between American overseas M & A and host country uncertainty (epu) and the difference (epu1) of economic policy uncertainty between the two countries is not significant.

Compared with objective geographical and natural factors, scientific and technological factors brought by long-term human capital accumulation, as well as macro-economic growth and other market factors, the stability of economic policies is more easily controlled by a country’s government. Therefore, maintaining the stability of economic policies is of positive significance for overseas M & A. Therefore, based on the real situation, the United States should continue to maintain normal economic activities with the other economies of the world, while the ruling party of the United States should maintain policy continuity and predictability, and should implement more robust economic policies, to maintain the information and enthusiasm of domestic investors to promote U.S. foreign investment activities to promote sustained economic development. In addition, there are some limitations in this paper. For example, the number of sample countries of M & A is not large enough, and qualified scholars can further expand the number of sample countries of M & A, which can not only improve the accuracy of data, but also further verify the correctness of the research results of the article.

Acknowledgements

Here I would like to thank not only my advisor Mr. Chen, but also everyone who has helped me.

Conflicts of Interest

The author declares no conflicts of interest regarding the publication of this paper.

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