Macroeconomic Factors Affecting Merger and Acquisition (M&A) Activity in Vietnam Nguyen Quyet (1)* (1) University of Finance-Marketing, Hanoi, Vietnam * Correspondence: nguyenquyet@ufm.edu.vn Abstract: The purpose of this paper is to analyze the macroeconomic factors influencing M&A activity in the Vietnamese market, analyzing both short-run and long-term The theoretical foundation is analyzed and synthesized from previous studies Quantitative research methods and vector error correction model were employed to analyze time series data The results of the study indicate that, in the long run, M&A activity is affected by money supply, political risk and economic growth In the short term, the impact on M&A is the tax burden, institutional and regulatory factors Keywords: Merger and acquisition (M&A); vector error correction model; political risk; institutional factors; regulatory factors; Vietnam Introduction M&A activity on the world has been quite bustling and so long However, for the Vietnamese market, this trend has just started about two decades ago From 1986 to 1995, this was the early stage of M&A activity in Vietnam, as the legal framework for this activity was not available or sufficient As a result, historical data show that very few M&A deals are recorded during this period In the period 1996-2005, M&A trend in Vietnam started to develop lightly, with the small size of value as well as the number of transactions, particularly two deals reaching 6.8 (billion usd) at the lowest and 39 transactions reaching 123.5 (billion usd) at the highest Also, the wave of rural banks being merged into the urban banks appeared in this period These deals are mostly due to the arrangement of state management agencies but not from the market The period 2006-2013, this activity is considered as a milestone when the Vietnamese market welcomes a strong and vibrant M&A trend The main reason is that laws are enacted such as Competition law, Enterprises law, Investment law, Securities law which have created a legal framework for the sale and transfer of contributed capital In addition, data from the IMAA (2018) shows that there are 47 sales in 2006, reaching 587.3 billion US dollars, 19 transactions higher than 2005 (67.8%), worth $ 520.5 billion (779.18%) These numbers are gradually increasing and reaching $ 4,177.8 billion at the highest in 2012 with 363 deals It shows the recovery of M&A after a decline of more than 50% in value in 2013 from 2014 to 2017 The reason is that during this period the legal and institutional framework continued to improve in order to attract potential foreign investors to invest in local businesses Moreover, M&A activity is mainly from the participation of foreign corporations, accounting for over 81% and retailing is leading in M&A deals in this stage Especially, the TCC Group buys Metro Vietnam's supermarket system at $879 million, AEON buys Fivemart and City Mark, and ThaiBev buys Sabeco In general, the trend of M&A activities in Vietnam is growing unevenly, with periods of significant decline Which factors cause this situation and their impacts on the market will be addressed and be discussed in more depth The purpose of this paper is to examine the macroeconomic factors affecting M&A activity in Vietnamese market by a quantitative method, analyzed by the vector error correction model (VECM) Based on this research, the research suggests a number of policies with the expectation of promoting M&A activity in Vietnamese maket Litterature review So far, many studies on this topic have shown the complexity and diversity of the factors that affect M&A activity, depending on the space, time and subject of the study According to Hitt et al (2006), M&A activity is influenced simultaneously by factors such as the legal system, economic development efficiency, political environment, culture and geographical distance On this topic, Scott and Whitaker (2016) classify factors that affect M&A activity into four groups of varying degrees Group 1: Factors of financial market, economic growth Group 2: Governance, institutional and regulatory factors Group 3: Organizational structure of the sector and policy Group 4: Education and training, corporate culture and national culture In this study, the factors are summarized and classified as follows: 2.1 Economic and financial factors M&A activity is a complex process that depends on many factors in the economic system, financial markets and especially capital markets (Weston 1953) It depends on the size of the economy (Boateng et al 2011; Nakamura 2004) In addition, stock market capitalization is considered an important factor reflecting the size of the financial market and has a significant impact on M&A activity Nelson (1959) reviewed the change in M&A activity in the US market during the period 1895-1920 and showed a positive correlation between changes in M&A activities and stock prices Similarly, Melicher and Ledolter and D'Antonio (1983) suggest that rising stock prices show the prospect of future economic growth leading to increased M&A activity In support of this view, Benzing (1991) and Evenett (2003) affirm that there is a relationship between stock market and M&A activity 2.2 Institutional and legal factors Institution is a set of formal and informal rules that regulate human behaviors These rules include the laws, regulations and systems for enforcing regulations (Roumeen 2002) The basic characteristic of the law is the modeling of social relationships, including economic relations Thus, the law may protect, prohibit or encourage the economic relations of each country to adapt to each historical period (Bittlingmayer and Hazlett 2000) A good legal system means that it does well in protecting intellectual property rights and respects copyright law and property rights of investors (Jory and Ngo 2011) Furthermore, Dikova, Rao Sahib and Witteloostuijn (2010) argue that a poorly regulated country will have a negative impact on foreign investment, including M&A activity Similarly, Alfaro et al (2008) also argues that institutional quality is one of the most plausible reasons for explaining the paradox of why capital flows not pour from rich countries to poor countries 2.3 Political risk factor Political risk is the risk by which the actions of governments can reduce the cash flow that investors expect from their investments In general, this is not simply a mismanagement of the economy which makes increasing inflation and damages the real value of investments This result can lead to social unrest which will cause companies to go bankrupt and hurt corporate stocks and bonds (Buttonwood 2017) Delios and Henisz (2000) and Kobrin (1979) show that investors tend not to participate in or withdraw capitals from countries with high political risk However, it is not entirely the case that in emerging economies there is a high political risk but they still attract large numbers of foreign investors involved in M&A activities In this case, Casson and Lopes (2013) and Peng et al (2008) argue that investors wishing to pursue profitability and expectation will have the opportunity to expand rapidly, even if these markets are at risk 2.4 Tax factor Taxation is a powerful tool used by governments to regulate macroeconomics and social life The main aim of tax is to mobilize revenues for the state budget and ensure equality between economic sectors and social justice However, for investors, a tax burden is one of the barriers to investment decisions Ang (2008) argues that international capital flows are directly influenced by the host country's tax policy, as increased corporate taxes lead to less attractive investment In this regard, Huizinga and Voget (2009) analyze the impact of taxation on the number of M&A deals in European countries, Japan and the United States during 1985-2004 They found that if the higher taxing country resulted in less attractiveness to market participants and smaller scope for conducting M&A transactions On this topic, Martin et al (2012), Chow et al (2013) and Col (2012) confirm that there is a strong link between taxation and M&A activity Methodology 3.1 Data gathering procedures Research variables are defined as follows: Dependent variable (denoted ma) is the M&A value of Vietnam from 1996 to 2018 (time series data) Independent variables are selected on the theoretical foundations and inheritance of the results of previous studies, including five variables measuring macroeconomic factors such as economic and financial factors, institutional and legal factors, political risk factor, tax burden Table Independent variables Factors Variables Symbol Expected signs Economics/Finance Economic growth gdp Real GDP growth rate (%) (+) Money supply m2 Deep financial market (%) (-) Institution/legality Property rights index pr Value from to 100 (+) Political risk Polcon index pol Value from to (+) Tax Tax burden index tax Value from to 100 (-) Source: Author’s summary The property rights index (value from to 100) is employed to measure the quality of institutions and law Similarly, the POLCON index (Political Constraints Index, Henisz, 2000) is used to represent political risk (value from to 1) Identically, the tax burden index is spoken on behalf of the government's tax burden on the business (Index of economic freedom, 2018) 3.2 Empirical model To learning about a potential long-run and short run behavior between two series, the concept of cointegration will be analyzed with Vector Error Correction Model (VECM) If the variables xt-i and yt-i are integrated of order and there is a linear combination, represented by the equation y t 0 i y t i jx t i ECTy.t i u y.t x t i y t i jx t i ECTx.t i u x.t Where 0 , i , j , 0 , i , j are the model coefficients; x t i , y t i indicate the first variables differences to be tested, lagged by i periods; , is the long-term adjustment coefficient; uy.t and ux.t are the terms of random error; ECTt-i is, the long-term equilibrium of the deviation between x t i and y t i lagged in i periods Results and discussion 4.1 Descriptive statistics The mainly aim of descriptive statistics which provide a historical background for the behavior of our data All series are converted into natural logarithms for estimation purposes Table summarizes the basic statistical features of the data under consideration including the mean, the minimum and maximum values, standard deviation, kurtosis, skewness Table Descriptive statistics results Mean ma gdp m2 pr pol tax 6.123516 1.863085 4.057863 2.562428 -3.331043 4.185035 Median 7.028822 1.859418 4.204693 2.302585 -2.267073 4.308111 Maximum 9.032839 2.234306 4.866765 3.906005 -1.780811 4.378270 Minimum 1.916923 1.497388 3.091042 2.302585 -5.912777 3.756538 Std Dev 2.223274 0.158161 0.671910 0.453481 1.669862 0.215049 Skewness -0.298577 0.023591 -0.274912 2.129768 -0.535257 -0.940748 Kurtosis 1.622135 3.452769 1.503182 6.705381 1.514100 2.440057 Jarque-Bera 2.161140 0.198592 2.436820 3.545431 3.214153 3.692996 Probability 0.339402 0.905475 0.295700 0.144670 0.200473 0.157789 Observations 23 23 23 23 23 23 Source: Output from Eviews 8.0 The results illustrate in the Table indicate that the variables are collected over a 23year period, all of which have shape of normal distribution (Statistical Jarque-Bera is greater than 5%) The gdp and pr variables have the right-handed distribution (because the skewness coefficient is greater than zero), the remaining variables have left-handed distributions The standard deviation value (Std.Dev) shows that the deviation (M&A value) is greater than the other variables Mean value shows that during the 23-year period, the value of M&A deals is about 448 (USD billion), an average economic growth rate of about 6.5% The property rights index of about 14.83 (less than 50) indicates that legal institutions are not really good quality In particular, the average tax burden of 67,065 (greater than the average number) indicates that the tax burden is a burden on the business 4.2 Stationary tests and order of integration There are many tests for stationarity, the Augmented Dicky-Fuller (ADF) test is most popular one The null hypothesis for the ADF test is that the time series has a unit root which implies non-stationary Table Stationary tests Augmented Dicky–Fuller test H0: Existence of unit roots Variables Level First-order difference No trend With trend No trend With trend ma 0.451269 -2.816144 -7.926882 *** -8,131221** gdp 0.662677 -3.346692 -4.645744*** -4.557905*** m2 3.071574 -0.9598573 -2.855934*** -3.21242** pr 1.234433 -1.317340 -4.701548*** -5.627038*** pol -0.585101 -1.80024 -4.472136*** -4.465135*** tax 0.882079 -1.264289 -0.992060 -6.683197*** Notes: ∗∗∗, ∗∗, and ∗ denote the significant levels of 1%, 5% and 10%, respectively The test results are reported in Table 3, which reveals that The ADF test cannot reject the null hypothesis for all level variables, but can for the first-order difference of all variables The results indicate that all variables are I(1) processes 4.3 Cointegration test The optimum lag length for the Johansen cointegration test determined based on the minimum Akaike criterion (AIC) through the unconstrained VAR estimation (1 lag) To test for the presence of a long-run relationship, the maximum likelihood method developed by Johansen (1988, 1991) is utilized The results of the Johansen maximum likelihood cointegration tests are presented in Table Table Cointegration test results Unrestricted Cointegration Rank Test (Trace) Hypothesized Trace 0.05 H0 H1 Eigenvalue Statistic Critical Value Prob r=0 r >=1 0.963560 163.1544 95.75366*** 0.0000 Unrestricted Cointegration Rank Test (Maximum Eigenvalue) Hypothesized Max-Eigen 0.05 H0 H1 Eigenvalue Statistic Critical Value Prob r=0 r =1 0.963560 69.55384 40.07757*** 0.0000 Notes: ∗∗∗, ∗∗, and ∗ denote the significant levels of 1%, 5% and 10%, respectively The test results are reported in Table confirmed that there exists the presence of cointegration It means that cointegrated variables have an error correction system Thus a vector error-correction (VEC) model (with lag) is constructed and the long-run and shortrun dynamics are examined Table Vector-error correction model estimation Variables Coefficient Std Error T-statistics ectt-1 -0.02717 0.014486 -2.22898** gdpt-1 1.21107 0.24369 4.96972*** m2t-1 -2.13470 0.48771 -4.37698*** prt-1 -1.76509 1.07894 -1.63596 polt-1 0.22859 0.09685 2.36036** taxt-1 -0.56565 1.30591 -0.43315 ma t 1 -0.352840 0.21998 1.60395 gdpt 1 0.009784 2.09186 0.00468 m2t 1 0.026635 2.23989 0.01189 prt1 0.489811 0.13376 3.66186*** polt 1 0.24606 0.12125 2.02936** tax t 1 -2.694469 1.07216 2.51312** C 0.241732 0.34257 0.70564 R-squared=0.69336, F-statistic=5.20057; Prob(F-Statistics)=0.0351 Notes: ∗∗∗, ∗∗, and ∗ denote the significant levels of 1%, 5% and 10%, respectively Results Table shows that the correction coefficient (-0.02717) is negative and significant statistics at the 5% level It means that M&A values are below equilibrium and in the long run, if the impact of independent variables push M&A on average increase (decrease) this year, the M&A value will decrease (increase) towards the equilibrium level of -2.717% the following year In the Long-term: The results show that economic growth, money supply (measured by financial depth) and political stability affect M&A activity (because gdpt-1, m2t-1 has 1% statistical significance, polt-1 at 5%) Assuming other factors remain the same, in the long term if the economic growth rate is increased by 1%, the M&A value will increase by 1.21107% on average If the political risk increases by point, the value of M&A deals will increase by 0.22859% on average However, as the financial depth increased by 1%, the M&A value fell by an average of 2.13470%, which could explain that as the financial depth increased the big amount of money circulating in the market while low commodities lead to an imbalance between commodity and money, which is the source of increased inflation, which causes investors to be less concerned about M&A activities In the short run: The results of statistical analysis (Table 6) also confirm that institutional and legal factors, political risk and tax burden affect M&A value (as statistical significance at 1%, 5% and 5% respectively With a lag of year, if the tax burden increases by 1, the M&A value will fall by an average of 2.694469% (Assuming other factors remain unchanged) Conclusion The results of research on the macroeconomic factors affecting the value of M&A transactions in the Vietnamese market by quantitative method, analyzed by error correction model (VECM) have shown that M&A activity was affected by the economic growth, money supply and political risk in the long term In the short run, this activity is affected by the tax burden, institutions and legal factors, and political stability From the results of study, the paper draws some conclusions as follows: Firstly, political stability is an important factor contributing to Vietnam's peace, prosperity, sustainable economic development and investment attractions Therefore, Vietnam should further promote this advantage to create confidence for investors, especially foreign investors In addition, the government should continue to improve the legal system in a uniform, stable, complete and consistent manner from central to local levels Secondly, the government should implement prudent and effective monetary policy, manage the money supply and credit growth accordingly and avoid putting pressure on inflation It is necessary to totally combine with other macro policies to ensure macroeconomic stability, create a fair investment environment, and be transparent to encourage investors to participate in domestic investment activities including M&A activities Finally, the government, in the long run, should have a roadmap to reform tax policies and incentive tariffs to 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Governance, institutional and regulatory factors Group 3: Organizational structure of the sector and policy Group 4: Education and training, corporate culture and national culture In this study, the factors. .. stock market and M&A activity 2.2 Institutional and legal factors Institution is a set of formal and informal rules that regulate human behaviors These rules include the laws, regulations and systems