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FINANCE-SPECIFIC DETERMINANTS OF MERGERS AND ACQUISITIONS-TYPE FDI:FIRM-LEVEL ANALYSIS FOR THAILAND

Benjalux Sakunasingha1,*, Hikari Ishido2, and Licheng Liang3
Lecturer in Finance, Business Administration Division, Mahidol University International College (MUIC),
Nakonpathom, Thailand.
2
Vice Dean of Faculty of Graduate School of Global and Transdisciplinary Studies, Chiba University, Japan.
3
PhD Candidate, Graduate School of Economics, Keio University, Japan.
*
Corresponding author e-mail: benjalux.sak@mahidol.edu
1

Received 25 May 2023
Revised 29 August 2023
Accepted 14 September 2023

Abstract
This study explores finance-specific determinants that encourage domestic firms toreceive foreign direct investment (FDI), especially those with a focus on mergers and acquisitions
at the firm level, using firms operating in Thailand. Two main objectives of this study: to identify
significant finance-specific determinants that make Thai companies more likely to receive foreign
investment; and to explore the heterogeneity at the firm level and the impact of financial
constraints. Our findings are: larger firms and younger firms draw more foreign attention and havea higher probability of receiving foreign investment, and companies with a larger amount ofintangible assets attract more investment from abroad. The results point to the appropriate
practical business policy of accumulating intangible assets with flexible formal/informal linkages
with potential partners is key to promoting FDI. Research implications falls into two categories:
first, the government policy implication, the government in emerging economies could securebusiness environment for scaling-up of business operations so that FDI is further promoted; also,
the government could facilitate nurturing of firm-level intangible assets. Second, on managerial
implications, business companies in emerging countries could act on such government policies
to pursue scaling-up of business activities based on intra company intangible assets. This research
has contributed to the macro-level consequence of micro-level M&A with firm-level data in
Thailand, specifically the financial determinants.
Keywords: Foreign direct investment, Multifactor productivity, Intangible capital,
International investment, Mergers and Acquisitions.

Introduction
For most developing and emerging countries, it has been recognized that the benefitsof foreign direct investment (FDI) in the host country are significant, although their benefits
and importance differ according to the host country and condition (Kurtishi-Kastrati, 2013). The
benefits from FDI include the transfer of technology and human capital support, improvementวารสารวิชาการสถาบันเทคโนโลยีแห่งสุวรรณภูมิ ปีที่ 9 ฉบับที่ 2 กรกฎาคม – ธันวาคม 2566

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the quality and skills of the local labour force, enhancement of the competitive businessenvironment, and great contributions to international trade and enterprise development andimprovement (Kurtishi-Kastrati, 2013; Lipsey, 2004; Patterson, Montanjees, Motala, & Cardillo,2004). In this context, as a source of external funding, FDI plays a key role in the economy of
the host country, affecting the balance of payments and supporting long-term economic
growth and productivity (Patterson et al., 2004). Theoretically speaking, determinants of FDIfrom institutional economics, e.g., (Dunning, 1973, 2000) and a strand of its off-shoot analyses
include firm-level and finance-specific determinants as well as consequence, or macro-level
impacts, of FDI. Theoretically speaking, determinants of FDI from institutional economics, e.g.,
Dunning (1973, 2000) and a strand of its off-shoot analyses include firm-level and financespecific determinants as well as consequence, or macro-level impacts, of FDI. With the above
considerations in mind, this study analyses the factors that make firms attractive to foreign
investors.
This article focuses on M&A-type FDI because of its significant impacts on technology
and administration transfer needed for business and country-level economic development.
Empirically, this research focuses on companies based in Thailand with equity participationfrom abroad, it aims to determine which of the finance-specific determinants relatively easily
to obtained and meaningful for comparison a standardized concept, that encourage local
firms to receive FDI deserve attention. That is, this paper addresses the determinants of crossborder mergers and acquisitions (hereafter, M&A-type FDI) in the country. Table 1 shows themacrolevel volume of M&As relative to that of FDI by region and by country across the world.
As shown, M&As comprise approximately forty percent of the total FDI in the world, albeit
with a significant fluctuation at the regional level and over the 1990-2021 period. In the AsiaPacific region, the situation differs greatly across its subregions: in North America, Oceania, andEast Asia (due to the high figure for Japan), the relative size of M&As is larger than fifty percent,while in South America and Southeast Asia, the presence of M&As remains lower. In Thailand(shown in bold in Table 1), M&As make up sixteen percent of the total FDI amount across theentire period. In the reference region of Europe, a high level of M&As is recorded, whereas inAfrica, M&As make up much lower than fifty percent of the total FDI. There is heterogeneity
in terms of the relative size of M&As vis-à-vis the size of FDI, and it seems that emerging
countries register lower levels of M&As than developed countries.

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Table 1 Percentage of M&As in Total FDI Inflow by Region and by Country
All period
1990-2000 2001-2010 2011-2021(1991-2021)
average average average
average(percent) (percent) (percent)(percent)
41.1
40.0
37.5
39.5

World
Asia-Pacific region
North America
59.8
60.3
61.2
60.4
South America
44.8
12.6
15.2
24.6
Oceania (Australia and New
94.7
32.1
37.4
55.4
Zealand)
East Asia (China, Japan and Korea)
84.9
21.1
23.3
43.7
China
13.3
12.0
12.5
12.6
Japan
212.2
24.1
50.2
97.7
Korea
29.3
27.3
7.1
20.8
10.3
19.8
9.8
13.1
South‒East Asia
Indonesia
-37.1
78.4
5.7
15.4
Malaysia
5.6
37.1
15.5
18.9
Philippines
52.2
-4.8
21.6
23.9
Singapore
6.2
26.8
12.2
14.7
Thailand
22.4
9.7
16.0
16.2
Vietnam
n/a
2.9
7.9
5.4
Europe
44.7
47.6
79.4
57.5
Africa
15.5
25.6
11.2
17.2
Source: Authors' calculation based on UNCTAD, 2022. World Investment Report, Annex
Table 1 and Table 5.

The Research Framework
The research question in this paper is: what factors serve as determinants of M&Atype FDI in the emerging part of the world, in which financial as well as non-financial (orinstitutional) factors of the local target firms (“at the firm level”) seem to play a crucial role.
Following this overarching question, this study focuses on Thailand, as a representative
emerging economy, and intends to add to the finance and trade literature by focusing on thefollowing two objectives: (1) to identify significant finance-specific determinants that make Thaicompanies more likely to receive foreign investment; and (2) to explore heterogeneity(different responses to investment decisions) at the firm level and the impact of financial

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constraints. In view of the above, this study, with its focus on firm-level determination andthe impact of FDI, is significant.
In terms of actual policy-making, especially for Thailand as a host country andpotential investors from around the world, there is policy-level significance since the focal
point of this research contributes to the fine-tuning of existing industrial policy while giving
due consideration to firm-level heterogeneity. Theoretically, firms with different productivity
levels engage in investment to various degrees. Firms with low productivity are forced to pay
higher fixed business costs to enter and operate in foreign markets. The least productive firms
may even exit the industry and predict negative operating profits. Only firms with highproductivity levels can benefit from investments because they expect to earn positive
operating profits from sales in foreign markets. Thus, they choose to invest in foreigncompanies, and the gap in profits between high-productivity and low-productivity firms may
widen. This is a serious socioeconomic concern.
If the necessary elements of production activities, such as labor and capital inputs,
can be smoothly transferred from firms with lower productivity to those with higher
productivity within a country (e.g., Thailand), the overall productivity in the country’s
domestic market will increase, and economic development will be possible in a way thatavoids fragmentation due to differences in productivity. However, owing to market
imperfections, it cannot be assumed that the transfer of workers and other "productive
resources" to high-productivity firms will be smooth within the same industry over a shortperiod of time.
In this context, trade and investment liberalization can contribute to an increase insociety’s productivity. Trade and investment liberalization make it easier for highly productive
firms to export and invest abroad. On the other hand, liberalization will increase market
competition, forcing firms with low productivity in their home countries to withdraw from themarket. As a result, market share is captured by firms that survive competition. This is anegative consequence of trade and investment liberalization. On the positive side, an increasein the productivity levels of these firms will also lead to an increase in the average productivityof the country (e.g., Thailand). To further promote the internationalization of business firms
and increase profits arising from trade and investment, it is essential to boost the productivity
and market competitiveness of firms by reducing the costs of trade and investment throughregional integration.
Thus, this research has real-world significance because it focuses on assessing theextent to which the heterogeneity theory of firms provides empirical support. This would also
eventually benefit countries (including Thailand and Japan) involved in foreign investment
activities at the firm level. Investigating the firm-level determinants of finance-specific and
M&A type FDI is expected to boost Thailand’s overall level of income at the crossroad of
COVID-impacted economic activities through practical policy arrangements.

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Literature Review
According to World Trade Organization (1996), FDI occurs when an investor based in
one country (home country) acquires an asset in another country (host country) to manage
that asset. According to the World Bank definition, FDI includes buying shares of an enterprise,
reinvesting earnings of a foreign-owned enterprise in a host country, and parent firms extendingloans to their foreign affiliates (Soubbotina & Sheram, 2000). The International Monetary Fund
guidelines define FDI as the foreign ownership of at least ten percent of an enterprise’s
ordinary shares or voting stock, which indicates a significant influence by an investor (Patterson
et al., 2004). Many countries, therefore, have set a threshold higher than ten percent, since a
foreign ownership level of only ten percent of is not sufficient to establish management
control of an enterprise (Patterson et al., 2004; Soubbotina & Sheram, 2000). Many schoolsof thought explain FDI issues, but there is still no single theory that is superior to others. The
related literature in this section is discussed under three headings as follows.
The literature on FDI concentrates mainly on identifying the determinants that
influence companies to invest abroad. Aw and Tang (2010), Brahmasrene and Jiranyakul(2002), Schneider and Frey (1985), Walsh and Yu (2010), Yang and Deng (2017) and Zhang
and Daly (2014) have studied macroeconomic levels and found that FDI is mainly
determined by the market size and growth potential of the host country, its political andmacroeconomic stability, the relative exchange rate, the degree of openness of the hostcountry, and infrastructure. Another strand of literature by Buch, Kensternich, Lipponer, andSchnitzer (2014), Esaku (2020), Garavito, Iregui, and Ramirez (2014), and Tripathi and Thukral(2020) explored the determinants of FDI at firm level, these include human capital,
company ownership, wages, labor productivity, capital intensity, capital structure, growthrate, profitability, and firm size. In addition, the intangibles such as external knowledge andtechnologies from abroad are also found at the firm-level (Armas & Rodriguez, 2017).
For Thailand, as a host country, FDI positively contributes to the country’s economy
by supplying capital and technology and enhancing the competitive business environment,
trade integration, and enterprise development. Previous studies in Thailand explore
macroeconomic determinants, whereas firm-level determinants have not received sufficientattention, especially finance-specific determinants, which could play a key role in drawing
attention from foreign investors (Ang, 2009; Brahmasrene & Jiranyakul, 2002; Pansuwan, 2018).
Stiebale and Trax (2011) indicated the positive effects of cross-border acquisitions on domestic
firm production. In their research, various firm-level determinants were also selected, such as
firm size, wage, capital stock, sales growth, and working capital ratio. In an attempt tocontribute to the literature, this research aims to focus on the firm level and explore financespecific determinants of FDI in Thailand that make Thai companies more likely to receive
foreign investment attention.

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While there are many country- and industry-level studies on the determinants andimpacts of foreign direct investment (FDI), firm-level studies seem to be limited. A benchmark
framework, from the perspective of microeconomic FDI theories coupled with the ownership,
location-based, and internalization (OLI) paradigm (Dunning, 1973), would be useful forhighlighting the rationale of this research, i.e., to consider a basic framework illustrating FDI
determination and firm-level characteristics. Conceptually, suppose that a “local firm” locatedin a country outside of that of the potential investor can generate net positive profit P(x)utilizing managerial input x. Based on the OLI framework discussed in the literature review, apotential foreign direct investor has an ownership (O) advantage, and when combined withthe host country firm’s acceptance of FDI (to materialize an M&A type of FDI), an extra profit
can be generated. In other words, the higher profitability generated by the combination of
local assets and the input of foreign ownership assets can be expressed by a positive intrafirm
externality or synergy effect. Formally, scalar s (> 0) can be introduced as an exogenous
variable denoting the synergistic effect enabled by the utilization of the ownership asset. At
the same time, however, foreign investors with ownership assets must incur a fixed sunk cost,
F (> 0), when entering the business in the host country. Assuming that E, which takes a value
between 0 and 1, is the degree of controllability of the firm, the ex-post net profit of the local
firm is (1+Es)P(x*), where x* is the optimal level of managerial input.
Fukao, Ito, Kwon, and Takizawa (2008) indicated that cross-border or foreignacquisitions lead to significant improvements in target firms’ productivity and profitability,
measured by return on assets (ROA) (Fukao et al., 2008). Their results were confirmed by
combining propensity score matching and difference-in-differences techniques. Fukao et al.
(2008) and Stiebale and Trax (2011) showed the positive effects of foreign investment on target
firms (Fukao et al., 2008; Stiebale & Trax, 2011). In this study, comparing the situation without(before) FDI and with that (after) FDI, the increase in profit generated by the FDI-taken local
firm is EsP(x*). Of this amount, E2sP(x*) - F is the net benefit to the foreign investor. In thisconnection, the higher fixed sunk cost F serves as a deterrent against business operation.
Hymer points out in this connection that a negative impact of the presence of F (transaction
costs, i.e., haggling costs associated with contracting FDI, plus other monetary disadvantages
arising from foreign operation under FDI) exists but the positive impact of s overpowers it(Hymer, 1976). That is, E2sP(x*) > F. (It is assumed here that F is borne by the investor.) The
remaining portion, (1-E) EsP(x*), is the additional net profit captured by the local capital as alocal partner of the FDI, which the investor firm expects to be positive. This is a win-win
situation for both local capital and foreign investors and is indeed the determinant of FDI aswell as the impact of FDI. The assertion that the positive impact of s overpowers F and leads
to a win-win situation may not be universally applicable; this study assumes the ex-ante(before M&A) expectation to this effect, held by the acquirers, focusing on the determinants(rather than impacts) of M&A type FDI.

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One thing to note is that there is a hidden “selection” effect, that is, the local firm
selected as the investment partner among heterogeneous firms in terms of profitability might
already be relatively highly profitable in the first place (even before M&A). In the empiricalanalysis in this study, no distinction is made between the two (selection effect and realized
profit), since only ex-post financial data of the firm are available. However, the profit-making
function P(x) is expected to be empirically specified in this study. This sort of firm-level
investigation into FDI determination in Thailand is limited and, hence, merits our investigation.
In the literature on FDI (which includes the M&A type of FDI), as mentioned above,
there are a wide variety of theoretical models to explain the determinants of FDI. Several
theories have contributed to identifying the firm-level determinants behind a firm’s decision
to undertake FDI, whereas the finance-specific determinants of the firm have received little
attention (Forssbaeck & Oxelheim, 2008). Because the financial characteristics of a firm provide
financial strength and advantages that can be exploited through cross-border investment
activity, the main purpose of this research is to suggest firm-specific financial factors thatdeserve attention that encourage companies to receive FDI. To the best of the authors’knowledge, in the Thai context, a number of studies have examined the relationships between
FDI and macroeconomic and institutional variables (Ang, 2009; Brahmasrene & Jiranyakul, 2002;
Pansuwan, 2018), but there has been no exploration of firm-level and/or finance-specificdeterminants in Thailand; thus, this research contributes by filling this research gap.
In efficient market theory, no firm has an advantage over another since all firms haveequal access to finance at equal costs. However, in the real world, there is imperfection incapital markets, and therefore, firms with better finance strategies, such as lowering the costof funds or increasing the availability of funds, should create a financial advantage, and they
are more likely to gain FDI attention (Forssbaeck & Oxelheim, 2008). Oxelheim, Randoy, andStonehill (2001) mentioned that under the “OLI paradigm” by Dunning (1973), the “O”, which
represents ownership advantages, may include various economies of scale and scope,advanced technology, managerial and marketing expertise, and differentiated products(Oxelheim et al., 2001). Oxelheim et al. (2001) also stated that the “firm’s financial
characteristics”, or so-called finance-specific factors, should be included under the economies
of scale and scope (Oxelheim et al., 2001). Therefore, the OLI paradigm does not explicitly
address the effect of finance-specific determinants on FDI. Since the firm from the homecountry will gain more advantage through ownership control and as a response to market
imperfections, the financial characteristics of a firm in a host country should be explicitly
addressed.
Finance-specific determinants are part of finance strategies and are important to all
firms but are particularly important to firms in host countries that wish to receive foreign
investment. This study follows the OLI and firm-level frameworks by identifying the firm’s

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finance-specific determinants that deserve explicit consideration since they create financial
advantages relevant to foreign investment decisions.
Research Data and Methodology
Research Sample and Data Description
Based on the prevailing literature survey, our research explores the relationshipbetween finance-specific determinants and the M&A type of FDI. Our research sample wasfrom the Zephyr and Orbis databases (released by Bureau van Dijk). Both databases are usedworldwide and cover the largest amount of firm-level data. Our research collected Thaicompanies’ operational and financial data as secondary data, both for listed and non-listedcompanies. The sample period was from 2012-2021. The final sample included 14,576 firmyear observations.
In this study, the incidence of M&A FDI was the dependent variable. Our dependent
variable was binary data, which takes “0” when there is no M&A involved and “1” in and after
the year when M&A FDI was undertaken. We included finance-specific variables for Thai local
companies as explanatory variables that are related to M&A FDI. In particular, we included
firm size (log of total assets); intangible assets (nonphysical assets/total assets) such as patents,
brands, trademarks, and/or copyrights; profitability (net income/total revenue); leverage of thetarget company (total debt/total assets); cash holdings (cash holdings/total assets); firm age(log of years since establishment); and growth in sales of target firms (year-on-year growthrate). To account for any unobservable characteristics that may have been omitted in theequation, we also include firm fixed effects. Table 2 shows descriptive statistics for the sample.
Table 2 Descriptive Statistics
Variable

No. ofObs.
142,635
129,915122,006

Mean

Std. Dev.

Min

Max

M&A_FDI
0.0047814 0.0689827
01
Size of the company
0.988496
1.311165 0.0022945 6.048172
Intangible assets
0.0027856 0.014707
00.1213909
Profitability (Net12,154 0.1272055 0.1143266 0.0000313 0.9956427
income margin)
Cash holdings
110,356 0.1568963 0.2306551 0.0001837 0.9965458
Age of the company
145,030 20.26566
8.57878
3
50
Leverage (TD/TA)
110,819 0.3618821 0.3014354 0.0009654
1
Notes: The variables are winsorized (for the purpose of suppressing the influence ofoutliers) at the 5% and 95% levels.
Source: Authors’ calculations based on the Zephyr and Orbis databases.

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Research Methodology
This research explores the relationship between finance-specific determinants and
FDI. Multiple regression analysis with fixed effects was applied, and one-period lagged
explanatory variables were used to avoid causality-related issues. This research investigatedfirm fixed effects, and an equation model [Eq. 1] was constructed to indicate the influence offinance-specific variables on M&A-type FDI, as follows:
𝑀&𝐴_𝐹𝐷𝐼𝑖,𝑡 = 𝛼𝑖,𝑡 + 𝑋𝑖,𝑡−1 𝛽 + 𝑍𝑖,𝑡−1 𝛿 + 𝜏𝑡 + 𝜀𝑖𝑡[Eq. 1]
where 𝑋𝑖,𝑡−1 is a vector of the control variables, which are firm-level characteristics,
including firm size, firm age and the square term of firm age. 𝑍𝑖,𝑡−1 represents firm-level
financial factors, such as leverage ratio and cash holdings. We also controlled the time-fixed
effects and firm-specific fixed effects in our linear models.
Results Discussion & Analysis
Regression Analysis
In this research, the dependent variable was the M&A type of FDI. We began byexamining the effect of finance-specific variables on M&A_FDI. Table 3 shows the results frompooled-linear probability model (pooled-LPM) regression for comparison in Column 1, and thebaseline estimation results of a fixed-effect linear probability model (Fixed Effects-LPM) in
Column 2. In Column 1, with the pooled-LPM regression; size, intangibility, and cash holdings
show positive and significant effects, while firm age shows a negative and significant effect.
Our main interest results are presented in Column 2, with the fixed-effect LPM, the size andintangibility show positive and significant effects. The effect of age is negative and significant,while profitability shows a positive effect on M&As. As consistently shown in Table 3, underboth specifications (pooled-LPM and fixed-effect LPM), the size of the company has a positiveand significant impact on the probability of a local company in Thailand receiving FDI, andlarger Thai firms are more attractive to M&A FDI. Concerning intangibility, this variable has apositive impact on the dependent variable (the probability of the company receiving M&A
FDI).
This result can be interpreted as indicating the presence of a synergy effect, that is,
the foreign company is attracted by the local company’s intangible assets and undertakes
M&A-type FDI to engage in profit-making activities in Thailand. The result from pooled-LPM
analysis shows that there is a positive and significant effect of cash holdings on M&A FDI. The
result showed that firm age had a negative impact on the probability of being an M&A target.
This could be interpreted as Thai firms with shorter track records since their establishment
tending to receive more foreign investment attention. We also include the square of the age
in the regression to check whether there is a quadratic relationship between firm age and M&A
propensity, and we found that the square term is positive, which indicates that the negative
impacts of age are decreasing for older firms.

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Table 3 Pooled-LPM Regression and Fixed-effect LPM of Equation Model [1](1)(2)
Dependent Var: M&A FDI (t)Pooled-LPM with year
Fixed Effects-LPM
dummies0.0107***0.0791***Size(t-1)（0.00111）（0.0112）0.0178*0.00204
Cash(t-1)（0.0101）（0.0259）
0.697***
0.661***
Intangibility(t-1)（0.132）（0.23）-1.01E-05
0.0390*
Profitability(t-1)（0.013）（0.0209）-0.00601***-0.0115*Age(t-1)（0.000914）（0.00656）
9.29e-05***-1.95E-05
Age^2 (t-1)（1.55E-05）（5.23E-05）
Observations
10,4049,830
R-squared
0.034
0.36
Firm FE
YES
Year FE
YES
YES
Clustered robust standard errors at the firm level in parentheses*** p<0.01, ** p<0.05, * p<0.1
The researchers worked on the probit model and the marginal effect results areshown in Tables 4-6.
Table 4 shows the results from the probit model without year-effect (in Column 3)
and with year dummies (in Column 4). The results in Column 3 and Column 4 show that outof six variables, only one variable (profitability) was not significant. According to the results inthe table, foreign companies that seek to acquire local firms do not view the profitability ofthe target firms as an important factor. In both columns, the coefficients of firm size,
intangibility, and cash holdings are positive and significant for the M&A type of FDI, while thecoefficients of firm age are negative and significant for the M&A type of FDI. The results inTable 4 imply that firms that are larger, have more intangibles, and possess larger cash holdings
have a higher potential to draw-in M&A FDI. Firms with low liquidity and fewer operation years
may have more potential to be acquired by foreign firms. Nevertheless, M&A propensity tends
to have a quadratic relationship with firm age.

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Table 4 Baseline Results (Probit model)
Dependent Var: M&A(3)
FDI (t)ProbitSize(t-1)
0.0145***(0.00213)
Cash(t-1)
0.0227*(0.0122)
Intangibility(t-1)
0.394***(0.0659)
Profitability(t-1)
0.0178(0.017)Age(t-1)-0.00474***(0.000666)Age^2 (t-1)
7.19e-05***(1.21E-05)
Observations
10,404
Year Dummies
YES
Pseudo R-squared
0.683
Likelihood-ratio test of rho=0
2.219
Log-Likelihood-1369
Wald chi2
195
Prob > chi20Prob Wald0
Clustered robust standard errors at the firm level in parentheses*** p<0.01, ** p<0.05, * p<0.1

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(4)
Probit0.0154***(0.00182)
0.0242**(0.0115)0.410***(0.0634)
0.0196(0.0152)-0.00491***(0.000614)
7.46e-05***(1.13E-05)
10,404
NO
0.681
4.942
-1378
170.7
0
0

Robustness Checks with Leverage and Sales Growth
To ensure that our results were robust, we carried out several robustness checks byadding in and removing some explanatory variables from the equation model [Eq. 1], as shown
below in Tables 5-6. This approach exploits the relationships inherent in the explanatory
variables, but the results are similar. First, it is conceivable that profitability may have a positiveeffect on M&A_FDI. To confirm the results, we add leverage (total debt/total assets) as anotherexplanatory variable in equation model [Eq. 1], and we find that the results in Table 5, which
includes the leverage ratio of target firms, are consistent with the results reported in Table 3
and Table 4 in terms of size, firm age and intangibility. The results in Table 5 (in columns 5
and 6) indicate that the leverage ratio does not contribute to the probability of receiving M&Afrom abroad; profitability might have a positive impact, yet its explanatory power seems to belimited, judging from the limited statistical significance; and that size as well as intangibleวารสารวิชาการสถาบันเทคโนโลยีแห่งสุวรรณภูมิ ปีที่ 9 ฉบับที่ 2 กรกฎาคม – ธันวาคม 2566

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assets play a significant and positive role in the M&A determination by a foreign acquiring
company.
Table 5 Leverage Ratio of Target Firms Included(5)
Fixed Effects
0.0816***Size(t-1)(0.0129)0.00825
Leverage (t-1)(0.0235)
0.687***
Intangibility(t-1)(0.244)0.0409*Profitability (t-1)(0.0227)-0.0125*
Age (t-1)(0.007)-1.93E-05
Age^2 (t-1)(5.32E-05)
Observations
9,492
R-squared
0.361
Firm FE
YES
Year FE
YES
Year Dummies.
Pseudo R-squared.
Likelihood-ratio test of rho=0.
Log-Likelihood.
Wald chi2.
Prob > chi2.
Prob Wald.
Clustered robust standard errors at the firm level in parentheses*** p<0.01, ** p<0.05, * p<0.1
Dependent Var: M&A FDI (t)(6)
Probit0.0134***(0.00168)
0.00626(0.00686)
0.403***(0.0622)0.0226(0.0153)-0.00466***(0.000647)
7.16e-05***(0.0000115)
10,032
.
.
YES
0.687
1.023
-1352
197.4
0
0

To further confirm the results, we also investigate by adding leverage and growth insales of target firms into equation model [Eq. 1]. Table 6 shows that sales growth may increase
the propensity of a firm to be a target (by 3.4%), although the factor is not statisticallysignificant under the fixed effect specification; under these specifications, size of the target
firm consistently contributes to the higher probability of receiving M&A. Age of the company
has mixed effects (positive or negative), depending on the model specification; in either casethough, the magnitude remains rather low, as compared with other factors including size ofthe company and possession of intangible assets.

วารสารวิชาการสถาบันเทคโนโลยีแห่งสุวรรณภูมิ ปีที่ 9 ฉบับที่ 2 กรกฎาคม – ธันวาคม 2566

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From the perspective of the OLI framework (Dunning, 1973; Dunning & Lundan, 2008),
the ownership-specific assets correspond to the intangibility in the regression. While
profitability does not seem to strongly explain the M&A determination, intangible assets havea stronger and positive explanatory power, indicating the importance of local companies’
possession thereof for attracting M&A-type FDI from abroad.
Table 6 Sales Growth of Target Firms Included(7)
Dependent Var: M&A FDI (t)Fixed Effects
0.0925***Size(t-1)(0.0219)-0.0264
Sales growth(t-1)(0.0234)
0.615
Intangibility(t-1)(0.405)0.0691*
Profitability(t-1)(0.0388)0.00998***Age(t-1)(0.00377)-0.0000323
Age^2 (t-1)(8.36E-05)
Observations
5,279
R-squared
0.046
Firm FE
YES
Year FE
YES
Year Dummies
Pseudo R-squared
Likelihood-ratio test of rho=0
Log-Likelihood
Wald chi2
Prob > chi2
Prob Wald
Clustered robust standard errors at the firm level in parentheses*** p<0.01, ** p<0.05, * p<0.1(8)Probit0.0176***(0.003)0.0344*(0.0201)
0.596***(0.0988)0.0295(0.0252)-0.00756***(0.0013)0.000115***(2.25E-05)
5,279

YES
0.824
9.085
-762.163.89
1.05E-08
1.05E-08

Conclusion
This research addresses finance-specific and firm-level determinants of M&A-type FDI
in Thailand. The main results of this research are as follows: (1) firm size as well as theวารสารวิชาการสถาบันเทคโนโลยีแห่งสุวรรณภูมิ ปีที่ 9 ฉบับที่ 2 กรกฎาคม – ธันวาคม 2566

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intangible assets of target companies in the country have significant and robust positive effects
on the probability of a firm becoming a target of M&A-type FDI, and intangibility assets inparticular may substantially increase the probability of a firm being a target firm; (2) from thefindings, as for finance-specific considerations, cash holdings is a positive determinant for target
firms, implying that acquirers are more interested in target firms with sufficient liquidity or cash
holdings, because there is higher chance for business success; (3) growth pace in sales havebarely significant positive impact, although it does not show the consistency in the otherspeciation (column 7, in table 6); (4) given the statistically positive significance of the size oftarget companies and intangible assets (which is idiosyncratic across companies), firm-level
heterogeneity seems to play a crucial role in the determination of M&A-type FDI in Thailand.
Of these results, the third one seems to indicate the importance of the intangible assets that
accompany M&A-type transactions, the higher potential for more profits because of the larger
size of the firm and the expected positive synergy effects after M&A.
As Thailand is a representative emerging country, local “emerging” companies could
be expected to nurture firm-specific intangible assets to attract more M&A-type FDI. On
managerial implications, business companies in emerging countries could act on suchgovernment policies to pursue scaling-up of business activities on the basis of intra company
intangible assets. As policy implications, the government in emerging economies (including
Thailand) could secure business environment for scaling-up of business operations so that
M&A-type FDI is further promoted; also, the government could facilitate nurturing of firm-level
intangible assets through, e.g., allowing double tax deduction for innovative activities by small
and medium sized firms, however piecemeal and incremental these activities might be. This
research has contributed to the macro-level consequence of micro-level M&A with firm-level
data in Thailand, specifically the financial determinants.
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