Page 1 of 14
Journal for Studies in Management and Planning
Available at http://edupediapublications.org/journals/index.php/JSMaP/
e-ISSN: 2395-0463
Volume 02 Issue 7
July 2016
Available online: http://edupediapublications.org/journals/index.php/JSMaP/ P a g e | 41
Impulse-Response function Analysis: An application to
macro-economy data of Ghana.
Kwame Antwi, MSc. Applied Statistics1 & Emmanuel Amoah, Mphil Statistics2
1 Department of Mathematics, Kwame Nkrumah University of Science and technology-Ghana
Email: kantwi35@yahoo.com
2 Department of Statistics, University of Ghana
Email: emmanuelamoah27@gmail.com
ABSTRACT
This paper attempts an empirical
investigation of the impact of foreign direct
investment (FDI) on Ghana GDP growth
using impulse response function(IRF)
analyses for annual time series data from
1980 to 2013; whether FDI improves or
worsens GDP growth has been at the centre
of literature debate over time with varying
empirical evidences for developed and
developing nation. The empirical results
indicate that there exist a long-run
stationary relationship between GDP
growth and its determinant- FDI, money
supply (M2) and trade balance (TB); as
employed in the study. On the IRF analyses,
when the impulse is GDP growth rate,
almost all response of foreign direct
investment is positive, the value is only
negative at year two; every response of
trade balance is all positive at each time
responsive period; the response of money
supply fluctuates. The paper concludes with
important implications for policy makers
because it provides evidence supporting that
fact that level of TB has a major impact on
GDP growth in Ghana.
KEYWORDS: Impulse Response Function
(IRF), GDP, FDI
INTRODUCTION
Like many developing countries, the
primary focus of policies in Ghana is to have
high and sustainable growth. However, to
achieve and maintain a high growth rate,
policy makers need to understand the
determinants of growth as well as how
policies affect growth. Since World War II,
the trend growth of real GDP has become a
key policy objective in almost all countries
(See Crafts 2000).
A wide range of studies have investigated
the factors underlying economic growth.
Using differing conceptual and
methodological viewpoints, these studies
have placed emphasis on a different set of
explanatory parameters and offered various
insights to the sources of economic growth
(Lichtenberg, 1992; Lensink & Morrissey,
2006). Investment is the most fundamental
determinant of economic growth (Artelaris
et al., 2007) identified in the literature. The
importance attached to investment has led to
an enormous amount of empirical studies
examining the relationship between
investment and economic growth (Artelaris
et al., 2007).
Economic policies and macroeconomic
conditions have also attracted much
Page 2 of 14
Journal for Studies in Management and Planning
Available at http://edupediapublications.org/journals/index.php/JSMaP/
e-ISSN: 2395-0463
Volume 02 Issue 7
July 2016
Available online: http://edupediapublications.org/journals/index.php/JSMaP/ P a g e | 42
attention as determinants of economic
performance. This is because they can set
the framework within which economic
growth takes place (Barro & Sala-i-Martin,
1995). Economic policies can influence
several aspects of an economy through
investment in human capital and
infrastructure, improvement of political and
legal institutions. In addition, a stable
macroeconomic environment may favour
growth through the reduction of uncertainty,
whereas macroeconomic instability may
have a negative impact on growth through
its effects on productivity and investment.
Several macroeconomic factors with impact
on growth identified in the literature include
inflation, fiscal policy, budget deficits and
tax burdens (Fischer, 1993).
Foreign Direct Investment (FDI) has
recently played a crucial role of
internationalizing economic activity and as a
primary source of technology transfer and
economic growth. The empirical literature
examining the impact of FDI on growth has
provided more-or-less consistent findings
affirming a significant positive link between
the two (Lensink & Morrissey, 2006).
The effect of foreign direct investment on
economic growth is dependent on the level
of technological advance of a host economy,
the economic stability, the state investment
policy and the degree of openness. FDI
inflows can affect capital formation because
they are a source of financing and capital
formation is one of the prime determinants
of economic growth. Inward FDI may
increase a host’s country productivity and
change its comparative advantage. If
productivity growth were export biased then
FDI would affect both growth and exports.
A host’s country institutional characteristics
such as its legal system, enforcement of
property rights, could influence
simultaneously the extent of FDI and
inflows and capital formation in that
country.
Βorensztein, et al. (1998) highlight the role
of FDI as an important vehicle of economic
growth only in the case that there is a
sufficient absorptive capability in the host
economy. This capability is dependent on
the achievement of a minimum threshold of
human capital.
To better understand the growth process,
this paper develops an empirical model
using a time series data from 1980-2013,
which attempts to explain some of the
necessary ingredients for sustained
economic growth in Ghana.
METHODOLOGY
Source of Data and Data Collection
Procedure
All series examined in this study; trade
balance, real exchange rate, real GDP and
money supply- are collected from Bank of
Ghana and WDI, World Bank. The data is
annual and spans the time period 1980 to
2013, which gives thirty four (34) data
points which is statistically large to be used
for the study.
Definitions and Measurements of
Variables
GDP
GDP refers to the value of all final goods
and services produced within a country or an
Page 3 of 14
Journal for Studies in Management and Planning
Available at http://edupediapublications.org/journals/index.php/JSMaP/
e-ISSN: 2395-0463
Volume 02 Issue 7
July 2016
Available online: http://edupediapublications.org/journals/index.php/JSMaP/ P a g e | 43
area in a period of time (a quarter or a year),
and is often considered the best standard of
measuring national economic conditions
(Mankiw & Taylor 2007).
Foreign Direct Investment (FDI)
FDI net flows are the value of inwards direct
investment made by non-resident investors
in the reporting economy.
Money Supply (M2)
Are the currency and coins in circulation
plus the demand deposits held by non- banking institutions, deposits and
certificates of deposits held by public and
private sectors.
Trade Balance (TB)
Trade balance is the difference in monetary
value between exports and im-ports. This
was measured in terms of the US dollars.
Unit Root Tests
Confirming the order of integration is a pre- requisite for almost all time series analysis.
In this study, we applied the Augmented
Dickey-Fuller (ADF), Phillips-Perron (PP)
and Kwaitkowski-Phillips-Schmidt-Shin
(KPSS) unit root tests to determine the order
of integration for each series. Since the ADF
test is low power in small sample Cheung &
Lai, (1995), we also applied the PP and
KPSS unit root tests to check the robustness
of the estimation results.
Impulse response function
Impulse response function (IRF) of a
dynamic system is its output when presented
with a brief input signal, called an impulse.
More generally, an impulse response refers
to the reaction of any dynamic system in
response to some external change.
A VAR was written in vector MA(∞) form
as yt= μ + εt + Ψ1εt−1+ Ψ2εt−2+⋯
[1].Thus, the matrix Ψs has the
interpretation ∂yt+s
∂ε′t
=Ψs
that is, the row I,
column j element of Ψs
identifies the
consequences of one unit increase in the jth
variable’s innovation at date t (εjt) for the
value of the ith variable at time t+s(yit+s
),
holding all other innovations at all dates
constant.
∂yit+s
∂ε′jt
as a function of s is called the impulse
response function. It describes the response
of ∂yit+s
to a one-time impulse in yjt with
all other variables dated t or earlier held
constant.
Co-integration Test
Cointegration means that despite the data
being non-stationary at levels in each
variable, a linear combination of two or
more time series can be sta-tionary and this
means that there exist a long-run equilibrium
relationship among them (Gujarati 2003).
The null hypothesis is that the series is not
cointegrated against the alternative
hypothesis that the series is cointegrated. If
the series is cointegrated, modeling of the
long-run relationship among variables is
necessary. In such a case, the VECM is
applied to reconcile the static long-run
equilibrium relationship of cointegration
