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GMJACS Volume 7 Number 2 2017
50
Deriving Forces of Macroeconomic Instability: A Case of Developing Nations
Shazia Kousar
1
, Muqqadas Rehman
2
and Ch Abdul Khaliq
3
Abstract
The purpose of this study is to investigate empirically the role of internal and external shock in
macro-economic fluctuations. This study used quarter data for internal, monetary policy, fiscal policy, and
external shocks, foreign direct investment, foreign aid, trade openness, from world development indicator
for 56 developing countries over the period of 1960Q1 - 2013Q4. Study employed Vector Error Correction
Model (VECM) to assess long run relationship between internal and external shocks and macroeconomic
instability. Moreover, study employed variance decomposition and impulse response function to assess
the relative importance of internal and external shocks and to forecast the response of macroeconomic
fluctuation in time t + n when one standard positive or negative shock is given to VAR system of internal
and external sources at time t while no other shock hits the system in developing nations. The results
show that fiscal policy causes to amplify the macroeconomic fluctuation while monetary policy causes to
dampen them. Moreover, external factors FDI and trade openness positively and significantly affect
economic fluctuations while official development assistance negatively and significantly affects economic
fluctuations. The results indicate that in developing countries combination of internal and external policies
are required to stabilize the economic fluctuation. Study helps the policy maker to formulate appropriate
policies to stabilize the economic activities.
Keyword: Economic Instability, Variance Decomposition, Impulse Response, VAR System.
1. Introduction
Before 1930s, macroeconomic fluctuations were seen periodically and classical economists
considered them as a normal fact of life. They believed that automatic forces resolved them, so no serious
attempt was made to identify the sources behind macroeconomic instability but the tragic effects of great
depression left profound influence on economic and political thinking. Since then, economists are identifying
different internal and external sources that can be utilized as stabilizing tool to smooth economic fluctuations
(Altug, Neyapti, & Emin, 2012). Therefore, the role of internal and external sources of macroeconomic
fluctuations has been on the theoretical and applied research agenda for economists and policymakers
since the evolution of macroeconomics. Although macroeconomic instability strongly affects the economy
but the size of impact differs across countries depending on the policies and structural characteristics of
the country. In the context of developing nations, sharp and persistent economic fluctuations are observed;
thereby, in developing economies the determination of driving forces of macroeconomic fluctuation is
crucial.
Theoretical literature regarding policy variables can be divided into two main stand point;
Keynesians and monetarists. In the early decades of sixties, Keynesian economists argued that counter
cyclical role of fiscal policy during macroeconomic instability can save the economy from disastrous effects
but empirically it has been observed that fiscal policy is pro cyclical in developing countries and aggravates
business fluctuations rather to stabilizing them (Altug et al., 2012; Calderón & Hebbel, 2008). Narrow and
rigid tax structure and inappropriate execution of government development project in developing economies
exacerbate economic instability (Popa & Codreanu, 2010). Contrary, monetarists presented famous “K-
percent” money growth rule to stabilize macroeconomic fluctuations (Gramlich, 1971). Moreover, it has
been observed in developing economies that government adopts pro-cyclical policies, monetary and fiscal,
to stabilize the economic fluctuation which ultimately results high output volatility. Likewise during 2008,
recession, U.S government executed fiscal policy with more than 1 trillion budget deficit and monetary
policy with minimum interest rate to control rapid decline in economic activities but failed to stabilize
macroeconomic fluctuations (Tassey, 2012). Contrary, it has been recognized that unanticipated monetary
policy effect output six times larger than anticipated policy and play a decisive role in price and output
instability (Blanchard, Dell’Ariccia, & Mauro, 2010; Stock & Watson, 2005). Therefore, the role of policy
1
Assistant Professor Management Sciences, The Superior Collage Lahore. Shazia.kousar@superior.edu.pk
2
Assistant Professor, Hailey College of Commerce, Lahore. muqqadasrehman@hcc.edu.pk
3
Assistant Professor, Hailey College of Commerce, Lahore. cakm786@yahoo.com
GMJACS Volume 7 Number 2 2017
51
variables in theoretical and empirical literature clashes, it motivate the researcher to investigate their role
in economic fluctuations (Burnside, Eichenbaum, & Fisher, 2004; Cotis & Coppel, 2005).
The economic instability is two to five times larger in poor nations as compare to rich countries; it
indicates that developing countries are unable to absorb the consequences of internal and external shock.
The extent of external shock depends on structural characteristic of the developing nations. The business
activities of developing economies are usually dependent on trade integration, foreign aid and foreign direct
investment and cause the economy more open to external shocks, so any sudden shock grounds to upset
the economic activities. Therefore, the reliance of developing countries on foreign resources for growth
invites the researchers to investigate the quantitative impact of external shocks in macroeconomic
fluctuations.
Some studies (Buckle, Kim, Kirkham, McLellan, & Sharma, 2007; Kamin, 2010), emphasized that
internal shocks are more important while explaining the causes of fluctuations in developing nations.
Contrary some studies (Raddatz, 2007), found that external shocks are more contributive than internal
shocks. The aim of this study is to assess the role of internal and external forces in macro-economic
instability and to forecast the response of macroeconomic fluctuation in time t + n when one standard
positive or negative shock is given to VAR system of internal and external sources at time t while no other
shock hits the system in developing nations.
2. Literature Review
2.1 Internal Shocks and Macroeconomic Instability
No doubt, fiscal policy play vital role in economic activities of developing nations and almost 30%
variations in economic activities across the countries are caused by the difference in government
expenditure and revenue system (Blanchard & Perotti, 2002; Taylor, 2000). Fiscal policy stabilizes ups and
downs in economic activities through automatic stabilizers like progressive tax system, unemployment
allowance and subsidies (Y. Lee & Sung, 2007). However, some studies found that fiscal policy are unable
to stabilize economic disturbance because when government expenditure increases that ultimately crowd
out private investment and exacerbate economic fluctuations. Negative crowding out effect of private
investment offset the benefits of increase in govt. expenditure and increase the intensity of economic
fluctuations (Mountford & Uhlig, 2009) and government developmental projects deepen the macroeconomic
instability rather than to stabilize them (Romer & Romer, 2010). Similarly, theoretical literature stated that
monetary policy help the policy makers to stabilize economic instability but empirical literature documented
that quantity of money is unable to stabilize fluctuation in output and inflation (Gerlach & Svensson, 2003;
Ireland, 2007). Therefore, theoretical literature recommended the role of monetary policy and fiscal policy
in output, investment and consumption fluctuation (Bouakez, Cardia, & Ruge-Murcia, 2005) but empirical
literature unable to offer conclusive evidence and open the door for further investigation.
2.2 External Shocks and Macroeconomic Fluctuations
Continuous and persistent fluctuations in economic activities of developing countries reflect two
important realities; first these countries are more exposed to external shock such as foreign direct
investment, foreign aid and trade openness and second they are defenseless against these shocks.
It has been observed that at initial stage of growth, the process of trade liberalization is more rapid
in developing economies than developed (Tomz & Wright, 2007) and last two decades witnessed that the
trade integration policies got popularity generally within economies of the world and particularly in
developing nations. Although trade openness enhance total production of goods and services by
introducing specialization in production process but at the same time, if developing economies failed to get
access in international market (Arellano & Mendoza, 2002; Mendoza, 1991; Mendoza & Uribe, 2000), it will
causes a sudden collapse of economic activities and push the economic toward macroeconomic instability.
Therefore, the countries which are integrated horizontally and vertically through tight knit supply chain
network have greater exposure to trade shocks (Charlton & Stiglitz, 2008; Torres & Vela, 2003). Therefore,
trade liberalization augment economic prosperity in developing nations by providing greater access to
international markets and by minimizing country-specific risk. Similarly, trade liberalization leads can also
lead them to greater fluctuation in output as they lose their share in international markets. During last few
decades, empirical literature debated a lot about the relationship of trade integration and macroeconomic
GMJACS Volume 7 Number 2 2017
52
instability but did not reach on a decisive conclusion because some studies (Wacziarg & Welch, 2008),
found that trade and financial liberalization increase macroeconomic stability and reduce the amplitude of
the business cycle, whereas other studies (Ranciere, Tornell, & Westermann, 2006) found that trade
liberalization may increase the probability of large but rare crises.
Therefore, it has been concluded that higher TO brings vibrant changes in the production pattern of
tradable industries and could generate fluctuation in aggregate economic activities because more open
economies have a lower ability to react to specific shocks in traded industries and their transmission across
countries.
The empirical literature is unable to present a clear picture of the significant impact of trade
liberalization on the economy’s overall long-term output fluctuations. There has been much discussion in
the empirical literature on the view that trade integration causes business cycle synchronization (Baxter &
Kouparitsas, 2005; De Haan, Inklaar, & JongAPin, 2008; McKinnon, 1963; Mundell, 1961), but the size of
influence of trade integration on country-specific macroeconomic volatility is a less researched area.
Moreover, as trade and financial integration increases among the economies of the world, concerns about
the impact of globalization on economic activities have grown (Abiad, Mishra, & Topalova, 2014) and efforts
have been made to investigate the role of trade integration in economic disturbance in the theoretical
literature as well as in the empirical literature.
Another important external source of fluctuation in output is foreign aid. Foreign aid is a flow of
financial and non-financial resources from developed countries toward developing economies. Developing
economies are heavily dependent on foreign aid to execute their developmental projects smoothly and
successfully but it has been observed that disbursement of foreign aid is highly volatile and causes disturb
the fruits of economic development projects. Therefore, aid disbursement patterns contribute to fluctuations
in disposable income and output of developing countries. The behavior of macroeconomic activities in aid-
recipient countries is several times irregular than donor countries which reflect volatility in disbursement to
developing nations. Although the welfare cost of massive macroeconomic disturbance have larger
consequences for the economies of developing nations (Pallage & Robe, 2001) but it is very difficult for
developing nations to adopt customary ways to smooth output fluctuation. Usually literature considered that
foreign aid provide relief at time of need and emergency in developing nations but the role of foreign aid in
economic instability is not clear (Asiedu & Villamil, 2002). Three different stand points about the role of
foreign aid in economic activities of developing nations exists; first, foreign aid generates Dutch disease
and is harmful and ineffective for economic prosperity because it nurture the problem of corruption and
dishonesty (Booth, 2012; Wright & Winters, 2010), second, foreign aid foster economic progress and
alleviate poverty in poor nations (Angeles & Neanidis, 2009; Stiglitz, 2002) and third The third group of
studies identified an effective and specific role of aid for those countries that are trapped in perpetuating
destitution and are trying to foster macroeconomic activities (Banerjee, 2011; Collier & Hoeffler, 2007).
Therefore, the literature does not provide clear explanation of foreign aid in economic activities and invites
the researchers to rethink about the role of foreign aid in business cycle fluctuations.
2.3 Research Questions
What is relationship between monetary policy and macroeconomic fluctuation?
What is relationship between fiscal policy and macroeconomic fluctuation?
What is relationship between FDI and macroeconomic fluctuations?
What is relationship between ODA and macroeconomic fluctuations?
What is relationship between trade openness and macroeconomic fluctuations?
What is relative contribution of internal sources in macroeconomic fluctuations?
What is relative contribution of external sources in macroeconomic fluctuations?
What is the response of macroeconomic fluctuation in time t + n when one standard shock is
given to VAR system of internal and external sources at time t?
3. Methodology
Mostly, empirical literature utilized Vector Auto Regressive (VAR) models to investigate the
effectiveness of internal and external shocks (Buckle et al., 2007). VAR is appropriate methodology when
the researcher wants to estimate a system of equations because it incorporates concurrent and lagged
GMJACS Volume 7 Number 2 2017
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interconnections that exist between variable of interest. Similarly VAR models produce more reliable
estimates of multivariate time series analysis and enables the researcher to perform impulse response
function to forecast error variance of each of the variables that can be explained by exogenous shocks to
the other variables (Campbell & Ammer, 1993). The decision criteria to adopt restricted or unrestricted VAR
models depend on the order of integration and the presence of long-run equilibrium among stationary time
series. In this study the variables are stationary at first difference and co integration among variable exist,
so study employed VECM to realize the purpose of estimation and forecasting, impulse response analysis.
Moreover, , VECM is useful to estimate the short-term and long-term impact of one time series on another
(Lütkepohl, 2007) and error correction term depicts short-term dynamics of the model (Mulligan, 2005).
Error Correction Model is simply defined as:
δβΠ
β depicts size of impact on dependent variable due to changes in the independent variable in
short-run period. Π is the ECT, which indicates the speed of recovery from period to period if any external
shock deviates the model from equilibrium path. When we use above single equation of ECM in a
multivariate system it will be extended into VECM. Furthermore, study defined VECM as:
4. Results
Prior to statistical analysis, study checked the staionarity, constant means, variances and covariance
of data, of the variable to avoid spurious relationships. Staionarity of data implies assurance of sensible
relationships to derive policy implications. This study used Levin, Lin, and Chu (2002), and Im, Pesaran,
and Shin (2003) test to check the stationarity of data. The results of unit root test are reported in table 1
which indicates that all series are non-stationary at level, so all variables are differenced once to make them
stationary. The calculated values of LLC and IPS clearly reject null hypothesis that variables do have unit
root at first difference. In the next step study used Johansen system co integration test to detect long run
relationship among variables. Results are reported in table 2 which shows there in the VAR system at least
two time series equations are co integrated in the long run. Furthermore, study proceeded with VECM to
estimate the short run association among multivariate time series.
Table No. 1: Unit Root Test
Ind. var
Method
Level
1st difference
GDP
LLC
11.8394
-5.42932*
IPS W-stat
-6.21829*
-14.3912*
gexp.
LLC
3.73858
5.16586*
IPS W-stat
2.67851
-6.61152*
M2
LLC
0.56190
-2.07777*
IPS W-stat
0.78692
-15.8317*
FDI
LLC
3.53473
-25.6411*
IPS W-stat
-1.00306
-15.0573*
ODA
LLC
-1.16566
-23.2466*
IPS W-stat
-3.74127
-22.9811*
Trade
LLC
10.1711
-3.57342*
IPS W-stat
-6.09606
-13.3040*
GMJACS Volume 7 Number 2 2017
54
Table No. 2: Co-integration Test
Hypothesized
No. of CE(s)
Trace
0.05
Critical Value
Prob.**
Eigenvalue
Statistic
None *
0.529660
140.9844
95.75366
0.0000
At most 1 *
0.337558
77.62325
69.81889
0.0104
At most 2
0.190413
43.03013
47.85613
0.1318
At most 3
0.166704
25.28668
29.79707
0.1514
At most 4
0.090074
9.967935
15.49471
0.2832
At most 5
0.023981
2.038981
3.841466
0.1533
Study presented the summary of descriptive statistics in Table 3. Results indicate that all
variables are normally distributed. The skewness values indicate that GDP, M2, FDI, and trade openness
are slightly negatively skewed, whereas government expenditure, GE, and foreign aid, ODA, are slightly
positively skewed. The value of kurtosis for all variables, except the GDP, is less than 3, which confirms
that data is normally distributed and Jarque-Bera test statistics indicated that all variables are normally
distributed. The statistics of Breusch–Pagan-Godfrey test (Obs*R-squared 6.40820 with associated P-
value 0.1799) indicated that there is no problem of hetroscadaciticity in the data. Thus, we can proceed
with the data for significant policy implications.
Table No. 3: Descriptive Statistics
GDP
GE
M2
FDI
ODA
TRAD
Mean
4.205028
5.70E+11
28.05089
-73.19E+08
7.63E+08
16.53992
Median
4.572899
3.33E+11
28.19951
-73232657
7.59E+08
17.36442
Maximum
8.418324
3.12E+12
35.23259
-4972747.
1.17E+09
30.81904
Minimum
-1.992360
8.23E+10
20.07104
-7.87E+08
4.57E+08
-2.828850
Std. Dev.
1.896150
5.84E+11
4.337784
2.49E+08
2.20E+08
7.977460
Skewness
-1.125519
2.045302
-0.115263
-1.220724
0.226158
-0.247451
Kurtosis
4.914048
2.960721
1.889663
1.062681
1.668769
2.445948
Jarque-Bera
3.01275
5.5866
4.715304
2.87019
7.248145
2.023637
Probability
0.15500
0.06859
0.094642
0.08789
0.026674
0.363557
Sum
370.0424
5.02E+13
2468.478
-1.92E+10
6.72E+10
1455.513
Sum Sq. Dev.
312.7985
2.97E+25
1637.024
5.38E+18
4.22E+18
5536.669
Observations
88
88
88
88
88
88
Study also conducted lag length criteria to find appropriate lag length. Results are obtained by using
different criteria like LR, likelihood ratio, FPE, final prediction error, AIC, Akaike information criterion, SIC,
Schwarz information criterion, and HQ, Hannan and Quinn information criterion, to select appropriate lag
length. Results of all criteria indicate that 2 is appropriate lag length. Similarly study employed LM test to
check VAR residual serial correlation and results indicate that up to lag three there is no serial correlation.
Table No.4: Lag Length Criteria
Lag
LogL
LR
FPE
AIC
SC
HQ
0
-6385.069
NA
8.19e+57
150.3781
150.5505
150.4474
1
-5507.045
1611.432
2.04e+49
130.5658
131.7727
131.0512
2
-5333.233
294.4570*
8.08e+47*
127.3231*
129.5646*
128.2247*
3
-5321.154
18.75874
1.46e+48
127.8860
131.1620
129.2037
GMJACS Volume 7 Number 2 2017
55
Table No. 5: VAR Residual Serial Correlation LM Tests
Lags
LM-Stat
Prob
1
18.72167
0.9922
2
7.091114
1.0000
3
26.94363
0.8627
4
198.7022
0.0000
5
18.59994
0.9927
The results of VECM are reported in table 6 which depicts a long run relationship between
internal and external shock and macroeconomic disturbance. The VECM confirm a long run equilibrium
relationship among variables because estimated error correction term (ECT) is with negative theoretical
sign and and having statistical significant T value.
Table No. 6: Long-run Co-integration Equation Based on VECM
Dependent Variable GDP(-1)
Coefficients
T. Statistics
standard Error
GE(-1)
-1.79E-10
[-7.85211]
-2.30E-11
M2(-1)
3.19907
[ 5.02594]
-0.63651
FDI(-1)
-2.00E-07
[-7.05000]
-2.80E-08
ODA(-1)
5.25E-08
[ 5.41858]
-9.70E-09
TRAD(-1)
-0.70257
[-3.77278]
-0.18622
C
67.28176
Coint Eq 1
-0.13685
[-0.00580]
R-squared
0.569813
Log likelihood
-12.02685
Adj. R-squared
0.442102
Akaike AIC
0.762544
Sum sq. resids
6.548875
Schwarz SC
1.341310
S.E. equation
0.319885
Mean dependent
0.059580
F-statistic
4.461720
S.D. dependent
0.428268
Results indicate that fiscal policy has positive and significant association with macro-economic
instability, whereas monetary policy has significant and negative association with macroeconomic
fluctuations while FDI and trade openness has positive and significant relationship with macro-economic
instability and official development assistance has negative and significant association with macroeconomic
fluctuations.
Table No. :7 Variance Decomposition of GDP
Period
S.E.
GDP
GE
M2
FDI
ODA
TRAD
1
0.316372
100.0000
0.000000
0.000000
0.000000
0.000000
0.000000
2
0.638771
99.77221
2.95E-05
2.61E-05
7.12E-05
0.202431
0.025228
3
0.977297
99.44612
0.000178
3.20E-05
0.002677
0.483817
0.067181
4
1.317800
99.13663
0.000855
1.81E-05
0.010403
0.740063
0.112036
5
1.613551
97.73828
1.019901
0.024489
0.023933
1.074527
0.118865
6
1.872268
94.80868
3.398645
0.117663
0.210859
1.364207
1.099944
7
2.098697
91.15319
6.265279
0.312858
0.644582
1.544527
2.072563
8
2.296106
87.34186
9.057783
0.644257
1.271052
1.611187
2.073866
9
2.507971
80.85886
14.66118
1.114252
1.815038
1.477792
2.079869
10
2.745804
72.63852
22.02762
1.485568
2.485472
1.284671
3.078155
GMJACS Volume 7 Number 2 2017
56
Study measured the relative importance of internal and external shocks by utilizing variance
decomposition method and results are reported in Table 7. Results indicate that in short run period 100%
variation in GDP growth is caused by itself while in the long run its own contribution drops to 72%. Results
indicated that GEXP and M2 contribution is 22.63% and 1.48% in GDP fluctuation. However, the
contribution of FDI in variation of GDP growth increases from almost zero to 2.48%, while ODA accounts
for 1.28 per cent and trade liberalization explained 3.078 per cent variation in GDP. The results are
indicating that fiscal has greater contribution in economic instability as compare to monetary policy. Similarly
trade openness has greater contribution in macroeconomic fluctuations as compare to FDI and ODA.
Figure No. 1
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1 2 3 4 5 6 7 8 9 10
Response of GDP to GDP
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1 2 3 4 5 6 7 8 9 10
Response of GDP to GE
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1 2 3 4 5 6 7 8 9 10
Response of GDP to M2
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1 2 3 4 5 6 7 8 9 10
Response of GDP to FDI
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1 2 3 4 5 6 7 8 9 10
Response of GDP to ODA
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
1 2 3 4 5 6 7 8 9 10
Response of GDP to TRAD
Response to Cholesky One S.D. Innovations
GMJACS Volume 7 Number 2 2017
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Study used impulse response function to increases the credibility of VAR econometrics. The
impulse response function depicts that how one standard deviation (S.D) shock to one of the equation
series affect itself and other equation series in the entire VAR system (M. H. Pesaran & Y. Shin, 1998)
(H. H. Pesaran & Y. Shin, 1998). The results of impulse responses are in Figure 1 for 10 quarters
forecasted time horizon.
Figure 1 shows response of economic fluctuation to Cholesky One Standard internal and external
Source Innovation in developing nation. The study used cholesky-dof adjusted method to serve the
purpose of forecasting. Results indicate that one S.D. innovation to GDP increases economic fluctuation
up to four quarter but after that it starts to decreases. Similarly when a shock of one S.D is given to fiscal
policy, up to four quarter it doesn’t affect economic fluctuation but after that it positively contribute in
economic fluctuations while a shock to monetary policy doesn’t affect economic fluctuations up to 5th
quarter and after that it start to contribute positively in economic fluctuations. Similarly, a one S.D shock
to FDI, positively affect business cycle after 3rd quarter. However, a Shock to other external forces like
ODA and trade openness has negligible role in economic disturbance.
5. Discussion and Conclusion
Results indicate that fiscal policy has significant and positive association with macroeconomic
fluctuations and it causes to flare the economic fluctuation rather than to reduce them. Although
conventional wisdom stated that rapid countercyclical response of fiscal policy to aggregate demand
instability causes to lower output and consumption volatility significantly (M. J. Lee, Laxton, Kumhof, &
Freedman, 2009), through two main channels; first, government can attempt to cushion instable national
expenditure by making deficit budget to support spending during recession (Blinder & Solow, 1974). Such
automatic stabilization occur, if tax structure is directly related with national income and expenditure and
government expenditures are independent of economic activities. Second, public finance measures helps
to offset macroeconomic fluctuations. Unfortunately it has been observed during 1970-1990 that fiscal
policy did efficiently use these stabilizing tools and poorly perform in stabilizing their economies (Fatás, Von
Hagen, & Hallett, 2003). During some episodes, it has been observed that fiscal policies aggravated
economic fluctuations rather than regulating them and fiscal contractions took place in periods of downturn,
whereas fiscal expansions occurred during economic upturn. Thus, deliberate fiscal policies have frequently
been pro-cyclical, overriding automatic stabilizers and possibly contributing to economic instability.
The results of this study indicated that monetary policy has negative and significant association
with economic instability; so monetary policy paly stabilizing role in developing economies. in developing
nations the primary goal of monetary policy is to maintain prices at low level or to control inflation rate
because price stability tend to produce macroeconomic stability. Monetary authorities deliberately can
change the supply of money during economic downturn and upturn, play significant role in achieving
macroeconomic stability (Folawewo & Osinubi, 2006). Therefore, monetary policy held by state bank
moderate economic fluctuation by keeping output close to potential level and to keep inflation at lower level.
For this purpose money supply is most effective instrument used by monetary authorities at time of
macroeconomic instability.
Similarly, in case of developing nations along internal sources, there are some external sources
that can help to reduce economic instability or can aggravate economic disturbance. Results indicate that
FDI and trade openness has positive and significant relationship with macro-economic instability, whereas
official development assistance has negative and significant association with macroeconomic fluctuations.
it mean the movement in FDI and economic fluctuation is in same direction. Practically we can observe that
foreign investors are interested to invest their money in those countries where they expect high rate of
return, so at time of prosperity, FDI increases which in turn aggravate economic boost and at time of
recession FDI will decreases which ultimate increase the severity of the economic situation. Similarly, the
results are consistent with Razin, Sadka, and Coury (2002), and with large class of international trade
theories which stated that trade openness has the potential to destabilize the economy because trade
openness leads toward lack of diversification which increase the probability of economic volatility by
increasing the country’s exposure to shocks specific to the sectors in which the country specializes.
Moreover, results indicate that ODA has negative and significant association with macro-economic
instability. The results of this study are consistent with the perception that developing economies utilize
GMJACS Volume 7 Number 2 2017
58
foreign aid as a tool to stabilize economic fluctuation through effective management (Isard, Lipschitz,
Mourmouras, & YONTCHEVA, 2006). Primary objective to take foreign aid is to attain sustainable rate of
economic growth and reduction of poverty among masses (Burnside & Dollar, 2000; Hansen & Tarp, 2000;
Iyoha, 2004). This study concluded that developing economies used a combination of domestic and foreign
policies to achieve desired growth rate and to stabilize economic instability. This study helps the policy
maker to formulate the domestic fiscal and monetary policy to stabilize the economic fluctuations. Moreover,
study also provide detailed empirical analysis of foreign factors that significantly affect business cycle
fluctuation and help the policy maker that in which direction these resources should be utilized to smooth
economic instability.
References
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