Risk attitude and corporate investment under output market uncertainty: Evidence from the Me Kong river delta, Viet Nam

Journal of Economics and Development Vol. 18, No.2, August 201659
Journal of Economics and Development, Vol.18, No.2, August 2016, pp. 59-70 ISSN 1859 0020
Risk Attitude and Corporate Investment 
under Output Market Uncertainty: Evidence 
from The Mekong River Delta, Vietnam
Le Khuong Ninh
Can Tho University, Vietnam
Email: lekhuongninh@gmail.com
Le Tan Nghiem
Can Tho University, Vietnam
Email: letannghiem@gmail.com
Huynh Huu Tho
Can Tho University, Vietnam
Email: huynhhuuthoct@gmail.com
Abstract
This paper aims to detect the impact of firm managers’ risk attitude on the relationship between 
the degree of output market uncertainty and firm investment. The findings show that there is a 
negative relationship between these two aspects for risk-averse managers while there is a positive 
relationship for risk-loving ones, since they have different utility functions. Based on the findings, 
this paper proposes recommendations for firm managers to take into account when making 
investment decisions and long-term business strategies as well. 
Keywords: Competition; corruption; investment; market uncertainty; risk attitude.
Journal of Economics and Development Vol. 18, No.2, August 201660
1. Introduction
Investment is crucial to the development of 
firms since it helps enhance product quality and 
increase market share. Thus, good investment 
decisions will raise firms’ efficiency and then 
trigger economic growth (Maki et al., 2005). 
However, making right investment decisions is 
basically difficult, due to the output market un-
certainty facing firm managers, among others 
(e.g., competition and financing constraints).
As well perceived, investment decisions are 
much dependent on firm managers’ risk atti-
tude toward output market uncertainty (Bo and 
Sterken, 2007; Femminis, 2008). Being skepti-
cal about the loss that may result from poor in-
vestment decisions, risk-averse managers tend 
to postpone investment intents so as to acquire 
more relevant information. In this situation, 
they possibly forgo good investment opportu-
nities. On the other hand, risk-loving managers 
who are normally over-optimistic about their 
own competence and market prospect will pro-
ceed with investment opportunities, irrespec-
tive of their uncertain outcomes. This tendency 
is accentuated by successes in the past. Such 
over-optimistic behaviour may be problematic 
if output markets would somehow turn worse. 
Thus, investment decisions of both risk-averse 
and risk-loving managers seem to have draw-
backs that should be avoided.
The aim of this paper is to examine the im-
pact of managers’ risk attitude on investment 
by non-state firms in the Mekong River Del-
ta (MRD) under output market uncertainty. 
Findings of this paper will lay down a credible 
ground for recommendations that enable firms 
to make better investment decisions and prop-
er long-term business strategies. This paper is 
structured as follows. Section 1 introduces the 
paper. Section 2 gives a review of the related 
literature. Section 3 defines the empirical mod-
el out of the literature reviewed. Section 4 dis-
cusses the findings using a set of primary data 
on 667 non-state firms in the MRD. Section 6 
concludes the paper and renders recommenda-
tions.
2. Literature review
When making investment decisions, firm 
managers do face output market uncertainty. 
To put it differently, they do not know the ex-
act future sales. Thus, they tend to postpone 
investment in order to fetch more relevant in-
formation and determine the right time to in-
vest (Berk, 1999). According to Nishihara and 
Shibata (2014), unless firms have to invest to 
preempt competitors, most investment projects 
can be postponed, since for most of the time, 
investment opportunities remain for a certain 
period prior to absolutely expiring. Indeed, 
having an investment opportunity (a real op-
tion) is analogous to owning a European call 
option to buy a stock. Then, the owner can ex-
ercise it right away, or later, to get a financial 
asset with a certain value (e.g., a stock). When 
possessing a real option (i.e., an investment op-
portunity), the firm can decide to invest right 
away or at any future point of time to obtain 
a real asset with a certain value (e.g., a facto-
ry). Like call options, the value of real options 
stems from the managerial flexibility in making 
use of the uncertainty about the future value of 
the real asset (Luehrman, 1998). Due to uncer-
tainty, firm managers tend to wait for more in-
formation that helps to avoid failure.
Thus, researchers have tried to examine the 
impact of output market uncertainty on firm 
Journal of Economics and Development Vol. 18, No.2, August 201661
investment. Most of the empirical studies on 
this topic (Guiso and Parigi, 1999; Ghosal and 
Loungani, 2000; Le, Hermes and Lanjouw, 
2004) came up with evidence of negative rel ... cteristics of the surveyed firms
According to the survey, the average age of 
the firms is 10 years and their average asset 
value is 146,913 VND million (Table 2). There 
are 231 liability-limited firms (accounting for 
34.6% of the total number of firms surveyed), 
193 joint-stock ones (28.9%), and 180 sole 
proprietorship ones (27%). There are 154 firms 
exporting part of or total output (accounting for 
23.1% of total number of firms surveyed).
Average sales of the surveyed firms in 2013 
is 210,402 VND million (increasing by 17.4% 
compared to that in 2012). Average profits of 
those firms are 16,761 VND million (increas-
ing by 6.8% compared to that in 2012). How-
ever, their average costs went up markedly (by 
18.4% compared to that in 2012). Return on 
Table 2: General information about the surveyed firms (2013)
Source: Authors’ survey in 2014.
Indicators Mean Standard deviation Min Max 
Age (year) 10 9 2 52 
Total assets (VND million) 146,913 492,392 130 6,750,400 
Sales (VND million) 210,402 539,048 50 5,450,131 
Profit (VND million) 16,761 77,904 –705,087 1,200,000 
Investment (VND million) 14,402 60,835 0 793,000 
Journal of Economics and Development Vol. 18, No.2, August 201666
sales (ROS) of those firms was 8%. All this im-
plies that the firms had reasonable growth rates 
but did not well utilize resources, so the costs 
are high.
About 46.3% of the surveyed firms paid 
bribes and the average bribe per firm is 192.2 
VND million per year. Bribing seems to be per-
vasive as 45.6% of the firms did it on purpose 
to get things done faster and 48.5% saw it as 
an implicit norm. The firms bribed by giving 
gifts (accounting for 56.0% of total number of 
firms), travel (54.3%) or in cash (52.8%).
Average investment by the firms in 2013 is 
14,402.4 VND million. Due to economic down-
turn and suppressed market demand, planned 
investment of the firms in 2015 is just 8,779.8 
VND million (decreasing by 39.04% compared 
to that in 2013). Financing sources for invest-
ment by the firms are equity (mainly retained 
profits) and bank loans. According to the sur-
vey, equity is an important financing source of 
investment by the firms, which accounts for as 
much as 65.77% of total investment outlays 
of the firms in the sample. When making in-
vestment decisions, firm managers were also 
concerned with output market uncertainty. The 
coefficient of variation of the future sales of the 
firms is 37.7%.
Le, Hermes and Lanjouw (2004) also esti-
mated the coefficient of variation of expected 
sales for firms in the MRD in 2000 and came up 
with a figure of 17.9%. This result implies that 
the degree of output market uncertainty facing 
firms in the region has gone up substantially. 
The reason for that is the economic downturn 
during the time our data were collected.
5.2. Estimation results
This section aims to examine the impact of 
managers’ risk attitude on the relationship be-
tween the degree of output market uncertainty 
and investment by the surveyed firms. Before 
doing that, we carefully check the data for hy-
potheses on multicollinearity and heteroske-
dasticity. All coefficients between independent 
variables (rij) are smaller than 0,8 (0,0002 ≤ 
|rij| ≤ 0,532), proving that there is no multicol-
linearity effect. In addition, we have used the 
Robust estimation option in Stata to correct the 
Table 3: Investment by the firms
Source: Authors’ survey in 2014.
Financing sources 
Investment in 2013 Planned investment in 2015 Change in 2015 
compared to 
2013 (%) 
Amount 
(VND 
million) 
% of 
total 
Amount 
(VND 
million) 
% of 
total 
Equity 9,472.03 65.77 5,142.61 58.57 –45.71 
Loans from joint-stock banks 2,976.26 20.66 2,169.25 24.71 –27.11 
Loans from state banks 1,432.91 9.95 1,022.82 11.65 –28.62 
Loans from foreign-owned banks 221.11 1.54 90.67 1.03 –58.99 
Loans from government projects 30.58 0.21 19.34 0.22 –36.76 
Others 269.51 1.87 335.13 3.82 24.35 
Total investment 14,402.41 100.00 8,779.81 100.00 –39.04 
Journal of Economics and Development Vol. 18, No.2, August 201667
Table 4: Estimation results
Notes: In the first line is coefficient βi. In the brackets is iXINV ∂∂ / . ***: 1% significance level; **: 5% 
significance level; and *: 10% significance level.
Source: Authors’ survey in 2014.
Dependent variable: INV – planned investment in 2015
Variables Model 2a Model 2b Model 2c 
C –0.038 
–
–0.035 
–
–0.024 
–
UNCERi –0.115* 
(–0.045) 
–0.126* 
(–0.048) 
–0.151** 
(–0.059) 
UNCERi×RISKi 0.215** 
(0.084) 
RISKi 0.085* 
(0.035) 
PROi 0.252*** 
(0.098) 
0.246*** 
(0.094) 
0.251*** 
(0.098) 
IRRi 0.045*** 
(0.018) 
0.047*** 
(0.018) 
0.048*** 
(0.019) 
DSALi 0.002*** 
(0.001) 
0.002*** 
(0.001) 
0.002*** 
(0.001) 
COMPi 0.005*** 
(0.002) 
0.005*** 
(0.002) 
0.005*** 
(0.002) 
COMPi2 –0.000** 
(–0.000) 
–0.000** 
(–0.000) 
–0.000** 
(–0.000) 
FAGEi –0.002 
(–0.001) 
–0.002 
(–0.001) 
–0.002 
(–0.001) 
BRIi 7.375*** 
(2.856) 
7.223*** 
(2.763) 
6.972*** 
(2.722) 
BRIi
2 –58.675* 
(–22.722) 
–57.327* 
(–21.929) 
–55.203* 
(–21.557) 
FSIZEi –0.002 
(–0.001) 
–0.002 
(–0.001) 
–0.002 
(–0.001) 
MANUi –0.006 
(–0.002) 
–0.011 
(–0.004) 
–0.011 
(–0.004) 
SERVi –0.046 
(–0.017) 
–0.050 
(–0.018) 
–0.051 
(–0.019) 
Observations (n) 667 667 667 
F value 5.050 4.550 4.650 
Significance 0.000 0.000 0.000 
Log likelihood –334.551 –332.607 –331.879 
problem of heteroskedasticity.
The impact of output market uncertainty on 
investment by the firms with managers’ risk at-
titude being excluded (Model 2a) is presented 
in Table 4. The estimate shows that coefficient 
β1 of UNCERi has a value of -0.115 at a signif-
icance level of 10%, implying that the degree 
of output market uncertainty has a negative 
Journal of Economics and Development Vol. 18, No.2, August 201668
impact on investment by the surveyed firms. 
RISKi is added to Model 2b (Table 4) to esti-
mate the impact of managers’ risk attitude on 
investment, regardless of output market uncer-
tainty. The coefficient of RISKi is 0.085 at a sig-
nificance level of 10%. This would mean that 
risk-loving managers tend to investment more 
than risk-averse ones do, others being equal.
However, recent studies argue that there is an 
interaction between the degree of output market 
uncertainty and managers’ risk attitude to influ-
ence firm investment. Therefore, Model 2c (Ta-
ble 4) aims to find evidence for this argument. 
Indeed, coefficient β2 of the interactive term 
UNCERi×RISKi has a value of 0.215 at a signif-
icance level of 5%. Obviously, risk-loving man-
agers (RISKi = 1) tend to invest more as the de-
gree of output market uncertainty goes up, since 
025.0084.0059.0/ =+−=∂∂ ii UNCERINV
Yet, risk-averse managers (RISKi = 0) tend 
to scale down investment as the degree of 
output market uncertainty picks up, since 
059.0/ −=∂∂ ii UNCERINV . 
Coefficient β4 of PROi has a positive value 
at a significance level of 1%, implying that re-
tained profits have a positive impact on invest-
ment by the firms, since they are usually credit 
rationed by commercial banks. In addition, co-
efficient β5 of IRRi also has a positive value at a 
significance level of 1%, meaning that the easi-
er it is to resell used assets, the higher the level 
of investment. Similarly, coefficient β6 of DSA-
Li also has a positive value at a significance lev-
el of 1%. In addition, most coefficients of other 
variables have expected signs, except for those 
of FAGEi, FSIZEi, MANUi, and SERVi.
6. Conclusion and recommendations
The findings show that the impact of output 
market uncertainty on investment is negative if 
managers’ risk attitude is not considered. This 
relationship becomes stronger for risk-averse 
managers since they need time to acquire more 
relevant information before making investment 
decisions so as to minimize the possibility of 
failure and regret. Yet, there exists a positive 
relationship between output market uncertainty 
and investment of risk-loving managers since 
they tend to accelerate investment as the degree 
of uncertainty goes up due to self-confidence, 
ambition to get over challenges and sanguine-
ness about the future. In addition, the impacts 
of the degree of competition and bribes on firm 
investment both have the shape of an invert-
ed-U. In addition, the higher the reversibility, 
the higher the investment by the firms.
As argued, investment decisions of both 
groups of managers (i.e., risk-averse and 
risk-loving) may bring about bad outcomes if 
the perceptions about the degree of output mar-
ket uncertainty are not precise. To make good 
predictions of the future, firms should have an 
own unit that is in charge of forecasting mar-
ket tendency that will help firm managers make 
better investment decisions. In addition, to a 
certain extent, firms should consider diversify-
ing operations to mitigate risks resulting from 
market gyrations and using risk hedging instru-
ments (such as forwards, futures and swaps). 
The Government can also consider establishing 
an agency specializing in providing market in-
formation to firms.
Journal of Economics and Development Vol. 18, No.2, August 201669
Notes:
1. From the data gathered, we are able to calculate the conditional mean and variance 
 of the growth rate of sales in 2015 as perceived in 2014 ( 0S is the sales in the base 
year (2013), ed is the expected mean of the growth of sales in 2015 and e)( 2σ is the expected variance 
of the growth rate of sales in 2015). Based on those variables, we calculate the coefficient of variation 
of expected sales .
References
Aghion, P., Bloom, N., Blundell, R., Griffith, R. and Howitt, P. (2005), ‘Competition and Innovation: An 
Inverted–U Relationship’, Quarterly Journal of Economics, 120(2), 701–728. 
Aistov, A. and Kuzmicheva, E. (2012), ‘Investment Decisions under Uncertainty: Example of Russian 
Companies’, Proceedings in Finance and Risk Perspectives, 12, 378–392.
Akdoğu, E. and MacKay, P. (2008), ‘Investment and Competition’, Journal of Financial and Quantitative 
Analysis, 43(2), 299–330.
Andrade, G. and Stafford, E. (2004), ‘Investigating the Economic Role of Mergers’, Journal of Corporate 
Finance, 10, 1–36.
Antonides, G. and Van der Sar, N. L. (1990), ‘Individual Expectations, Risk Perception and Preferences in 
Relation to Investment Decision Making’, Journal of Economic Psychology, 11, 227-245.
Bayraktar, N. (2014), ‘Fixed Investment/Fundamental Sensitivities under Financial Constraints’, Journal of 
Economics and Business, 75, 25–59.
Berk, J. (1999), ‘A Simple Approach for Deciding When to Invest’, American Economic Review 89(5), 
1319–1326.
Block, J., Sandner, P. and Spiegel (2015), ‘How Do Risk Attitudes Differ within the Group of Entrepreneurs? 
The Role of Motivation and Procedural Utility’, Journal of Small Business Management, 53(1), 183–
206.
Bo, H. and Lensink, R. (2005), ‘Is the Investment–Uncertainty Relationship Non-Linear? An Empirical 
Analysis for the Netherlands,’ Economica, 72(286), 307–331.
Bo, H. and Sterken, S. (2007), ‘Attitude towards Risk, Uncertainty, and Fixed Investment,’ The North 
American Journal of Economics and Finance, 18(1), 59–75.
Boone, J. (2000), ‘Competitive Pressure: the Effects on Investments in Product and Process Innovation’, 
Rand Journal of Economics, 31(3), 549–569.
Boone, J. (2001), ‘Intensity of Competition and the Incentive to Innovate’, International Journal of 
Industrial Organization, 19, 705–726.
Boone, J. (2008), ‘A New Way to Measure Competition’, Economic Journal, 118, 1245–1261.
Chronopoulos, M., De Reyck, B. and Siddiqui, A. (2011), ‘Optimal Investment under Operational Flexibility, 
Risk Aversion, and Uncertainty’, European Journal of Operational Research, 213, 221–237.
Driver, C. and Whelan, B. (2001), ‘The Effect of Business Risk on Manufacturing Investment Sectorial 
Survey Evidence from Ireland’, Journal of Economic Behavior & Organization, 44, 403–412.
Femminis, G. (2008), ‘Risk-Aversion and the Investment–Uncertainty Relationship: The Role of Capital 
Depreciation’, Journal of Economic Behavior & Organization, 65, 585–591.
Ghosal, V. and Loungani, P. (2000), ‘The Differential Impact of Uncertainty on Investment in Small and 
Large Businesses’, Review of Economics and Statistics, 82(2), 338-343.
Journal of Economics and Development Vol. 18, No.2, August 201670
Guiso, L. and Parigi, G. (1999), ‘Investment and Demand Uncertainty’, Quarterly Journal of Economics, 
114, 185–227.
Hansen, J. A. (1992), ‘Innovation, Firm Size, and Firm Age’, Small Business Economics, 4(1), 37-44.
Le Khuong Ninh (2008), ‘Bribing and Investment Decisions by Non-state Firms in the Mekong River 
Delta’, Economic Review, 3-2008 (in Vietnamese), 68–76.
Le Khuong Ninh, Hermes, N. and Lanjouw, G. (2004), ‘Investment, Uncertainty and Irreversibility: An 
Empirical Study of Rice Mills in the Mekong River Delta, Vietnam’, Economics of Transition 12(2), 
307–332.
Le Khuong Ninh, Phan Anh Tu, Pham Le Thong, Le Tan Nghiem and Huynh Viet Khai (2007), ‘An Analysis 
of Factors Affecting Investment Decisions by Non-state Firms in the Mekong River Delta’, Economic 
Review, 4-2007 (in Vietnamese), 47–55.
Luehrman, T., (1998), ‘Investment Opportunities as Real Options: Getting Started on the Numbers’, 
Harvard Business Review, July-August, 3–15.
Maki, T., Yotsuya, K. and Yagi, T. (2005), ‘Economic Growth and the Riskiness of Investment in Firm-
Specific Skills’, European Economic Review, 49, 1033–1049.
Moohammad, A. Y., Nor’Aini, Y., and Kamal, E. M. (2014), ‘Influences of Firm Size, Age and Sector 
on Innovation Behavior of Construction Consultancy Services Organizations in Developing 
Countries’, Culture, 4(4), 01-09.
Moretto, M. (2008), ‘Competition and Irreversible Investments under Uncertainty’, Information Economics 
and Policy, 20, 75–88.
Nakamura, T. (1999), ‘Risk-Aversion and the Uncertainty-Investment Relationship: A Note’, Journal of 
Economic Behavior & Organization, 38, 357–363.
Nielsen, M.J. (2002), ‘Competition and Irreversible Investments’, International Journal of Industrial 
Organization, 20(2002), 731–743. 
Nishihara, M. and Shibata, T. (2014), ‘Preemption, Leverage, and Financing Constraints’, Review of 
Financial Economics, 23, 75–89.
Polder, M and Veldhuizen, E. (2012), ‘Innovation and Competition in the Netherlands: Testing the 
Inverted–U for Industries and Firms’, Journal of Industry, Competition and Trade, 12(1), 67–91. 
Svensson, J. (2005), ‘Eight Questions about Corruption’, Journal of Economic Perspectives, 19(3), 19–42. 
Whalley, A. E. (2011), ‘Optimal R&D Investment for a Risk-Averse Entrepreneur’, Journal of Economic 
Dynamics & Control, 35, 413–429.