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Risk attitude and corporate investment under output market uncertainty: Evidence from the mekong river delta, Vietnam

Risk attitude and corporate investment under output market uncertainty: Evidence from the mekong river delta, Vietnam. 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.



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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

59

Vol. 18, No.2, August 2016

1. Introduction

structured as follows. Section 1 introduces the
paper. Section 2 gives a review of the related
literature. Section 3 defines the empirical model out of the literature reviewed. Section 4 discusses the findings using a set of primary data
on 667 non-state firms in the MRD. Section 6
concludes the paper and renders recommendations.

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 uncertainty facing firm managers, among others
(e.g., competition and financing constraints).

2. Literature review
When making investment decisions, firm
managers do face output market uncertainty.
To put it differently, they do not know the exact future sales. Thus, they tend to postpone
investment in order to fetch more relevant information and determine the right time to invest (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 option) is analogous to owning a European call
option to buy a stock. Then, the owner can exercise 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 opportunity), 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 factory). 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 uncertainty, firm managers tend to wait for more information that helps to avoid failure.

As well perceived, investment decisions are
much dependent on firm managers’ risk attitude toward output market uncertainty (Bo and
Sterken, 2007; Femminis, 2008). Being skeptical about the loss that may result from poor investment decisions, risk-averse managers tend
to postpone investment intents so as to acquire
more relevant information. In this situation,
they possibly forgo good investment opportunities. On the other hand, risk-loving managers
who are normally over-optimistic about their
own competence and market prospect will proceed with investment opportunities, irrespective 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 drawbacks that should be avoided.
The aim of this paper is to examine the impact of managers’ risk attitude on investment
by non-state firms in the Mekong River Delta (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 proper long-term business strategies. This paper is
Journal of Economics and Development

Thus, researchers have tried to examine the
impact of output market uncertainty on firm
60

Vol. 18, No.2, August 2016

ies pay attention to full-fledged investment
decisions, thanks to the inevitable assertion
that output market uncertainty affects investment via the channel of managers’ risk attitude (Nakamura, 1999; Bo and Sterken, 2007;
Femminis, 2008; Chronopoulos et al., 2011;
Whalley, 2011; Aistov and Kuzmicheva, 2012).
According to them, risk-loving managers tend
to accelerate investment as the degree of uncertainty goes up because of self-confidence,
ambition to get over challenges and sanguineness about the future. For those managers, the
satisfaction resulting from a success surely
dominates the disappointment of failing. Thus,
a higher degree of uncertainty will induce them
to invest more.

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 relationships between the uncertainty and firm investment. According to them, the higher the degree of output market uncertainty, the lower the
level of investment, due to the fact that uncertainty may increase the user cost of investment.
A higher degree of uncertainty also makes firm
managers cautious in taking up investment
projects because, in that case, it is hard to control and mitigate the adverse impact of market
gyrations. As a result, investment will decline.
However, these studies have ignored firm managers’ risk attitude or implicitly assumed that
their risk attitude is virtually identical.

On the other hand, risk-averse managers
who do prefer certain values to uncertain ones
will opt for investment projects with more certain profits. In terms of utility, risk-averse managers feel worse off if losing more, than better
off if winning. Being skeptical about losing,
they need time to acquire more relevant information before making investment decisions so
as to minimize the possibility of failure and regret. Thus, investment will drop as the degree
of output market uncertainty picks up. In other
words, the relationship between output market
uncertainty and investment depends on firm
managers’ risk attitude.

As a matter of fact, firm managers would belong to either risk-averse or risk-loving group
of people, due to differences in utility and motivation, among others (Block et al., 2015).
Thus, researchers started to examine the relationship between managers’ risk attitude and
firm investment. For them, investment decisions of managers are normally aimed at maximizing expected profits rather than actual ones.
Then, the utility function U(π) of a risk-averse
manager is a concave curve of profit π, because
of the law of diminishing marginal utility. On
the other hand, the utility function U(π) of a
risk-loving manager is a convex curve of profit
π, due to the law of increasing marginal utility. As a result, investment decisions by those
groups of managers largely diverge.

3. Empirical model
Given the argument previously presented,
the empirical model used to detect the impact
of managers’ risk attitude on the relationship
between the degree of output market uncertainty and firm investment is specified as follows:

Different from those studies that just focus
on single aspects of relevant issues (such as
output market uncertainty, risk attitude, competition or financing constraints), recent studJournal of Economics and Development

INVi = β0 + β1UNCERi + β2UNCERi x RISKi­
+ β3RISKi­ + εi
(1)
61

Vol. 18, No.2, August 2016

In Model (1), INVi is the ratio of planned
investment in machinery, land and buildings
to total fixed assets of firm i. UNCERi is the
degree of output market uncertainty, measured
by the coefficient of variation of expected sales
of firm i (Guiso and Parigi, 1999; Le, Hermes
and Lanjouw, 2004).1 Coefficient β1 is expected
to be negative since the theory postulates that
output market uncertainty may have a negative
impact on firm investment.

tainty and investment for risk-averse managers. For those managers, since RISKi = 0 then
∂INVi / ∂UNCERi = β1 . Thus, it is expected
that β1|β1|. εi is an
error term.
To be complete, the empirical model should
include the determinants of investment identified by other studies (Bo and Lensink, 2005;
Guiso and Parigi, 1999; Polder and Veldhuizen,
2012), such as retained profit, growth rate of
sales, degree of competition, etc. Given these
factors, the empirical model of this paper then
becomes:

RISKi is used to proxy for risk attitude of the
top manager of firm i. To construct this variable, the manager was asked to choose between
two hypothetical cases: (i) investing a certain
amount of money to earn 10% profit for sure or
(ii) investing the same amount of money to earn
20% profit with a probability of 50% or nothing
with the remaining probability of 50%. RISKi
takes a value of 0 (risk-averse) for the manager
who chooses case (i) and 1 (risk-loving) for the
one choosing case (ii). The previous empirical
studies proved that risk-loving managers tend
to invest more as the degree of output market uncertainty increases (Antonides and Van
der Sar, 1990; Driver and Whelan, 2001; Andrade and Stafford, 2004; Akdoğu and Mackay,
2008). Therefore, coefficient β3 is supposed to
be positive.

INVi = β0 + β1UNCERi + β2UNCERi x RISKi­
+ β3RISKi­ + β4PROi + β5IRRi + β6DSALi +
β7COMPi + β8COMPi2 + β9FAGEi + β10BRIi +
β11BRIi2 + β12FSIZEi + β13MANUi + β14SERVi
+ εi
(2)
PROi is the ratio of after-tax profits to total
assets of firm i. Bo and Lensink (2005) and
Bayraktar (2014) argue that, in the case of
credit rationing due to information asymmetry, transaction cost and limited liability, firm
investment is largely related to internal finance
(mainly retained profits) because of difficulties
in getting access to external finance (e.g., bank
credit). Therefore, coefficient β4 is thought to
be positive.

UNCERi x RISKi is an interaction of UNCERi and RISKi. This interactive term is used
to detect the impact of managers’ risk attitude
on the relationship between output market uncertainty and investment of firm i. Studies (Bo
and Sterken, 2007; Femminis, 2008; Chronopoulos et al., 2011; Whaley, 2011; Aistov
and Kuzmicheva, 2012) argue that there is a
negative impact of managers’ risk attitude on
the relationship between the degree of uncerJournal of Economics and Development

IRRi is a proxy for the irreversibility of used
assets of firm i. Managers of the surveyed firms
were asked to evaluate the possibility to resell
used assets in order to construct variable IRR1i,
which takes a value of 1 if the answer is “easy”
and 0 if the answer is “not easy”. We also use
the information about the expected resell value
62

Vol. 18, No.2, August 2016

of used assets to construct variable IRR2i (i.e.,
the ratio of the expected resell value of used
assets to their replacement cost). Since the irreversibility of used assets depends on both IRR1i
and IRR2i (Guiso and Parigi, 1999), we utilize
the principal component technique to combine
these two variables to create IRRi = w1IRR1i
+ w2IRR2i , with w1 and w2 being component
parameters. The higher the value of IRRi , the
higher the possibility for firms to resell used
assets. Since investment decisions are normally hard to reverse (either partially or totally), a
higher possibility to resell used assets induces
firms to invest more, other things being equal.
Coefficient β5 is then expected to be positive.

not plausible to add up the quantity of different
goods (Polder and Velhuizen, 2012). In sum,
PEi can be written as follows:

PEi =

As just explained, fierce competition may
squeeze PEi. Therefore, in order to make it easier to grasp the impact of the degree of competition on investment, we use COMPi = |PEi|.
A higher value of COMPi means a higher degree of competition facing firm i. COMPi2 is
also used to reveal the presence of an inverted-U shaped relationship between the degree
of competition and investment by the firm.
Nielsen (2002), Aghion et al. (2005), Moretto
(2008), Akdoğu and Mackay (2008) and Polder
and Veldhuizen (2012) assert that firms operating in a less severely competitive environment often have high costs due to moral hazard that results in inefficiency. As competition
pressure strengthens, firms are forced to raise
investment to mitigate costs, enhance efficiency and preempt competitors so as to tackle the
risk of squeezed market share. Yet, if competition pressure goes beyond a certain point, it
becomes too fierce, market niches evaporate
and benefits from investing are no longer present, firms will then scale down investment.
Thus, coefficient β7 is expected to be positive
and β8 negative. FAGEi is the number of years
in operation (age) of firm i. Since young firms
are more eager to invest to grow and expand
market share so as to avoid failing. Thus, β9 is
supposed to be negative (Hansen, 1992; Moohammad et al., 2014).

DSALi is the annual growth rate of sales by
firm i (%). A fast growth of sales means a better
prospect for firms. Therefore, firms will embark
on more investment to make use of good available opportunities (Guiso and Parigi, 1999; Bo
and Sterken, 2007). As a result, coefficient β6 is
supposed to be positive.
COMPi is the degree of competition facing
firm i, measured by its profit elasticity (PEi).
PE was coined by Boone (2000) and further
developed by Boone (2001, 2008), Polder and
Veldhuizen (2012), etc. According to those
studies, the degree of competition can be identified by the ratio of percentage change of profit (π) to percentage change of marginal cost
(MC), which means:

Since it is often difficult to measure MC, researchers replace it by average cost (AC). In
addition, the average cost of firms that operate in different sectors will be the ratio of total
cost (TC) to total revenue (TR), because it is
Journal of Economics and Development

∆π i / π i (%)
< 0, π i = π i / TRi
∆ACi / ACi (%)

BRIi is the ratio of bribes that firm i paid to
public officials to its total assets. BRIi2 is included to detect the non-monotonic relation63

Vol. 18, No.2, August 2016

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