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The Explorer Islamabad: Journal of Social Sciences ISSN (E):
2411-0132, ISSN (P): 2411-5487 Vol-1, Issue (7):237-240
www.theexplorerpak.org
237
GOOD GOVERNANCE AS A TOOL TO COMBAT INFLATION Muhammad Waqas
Khalid, Aadil Hameed Shah
Students of MPhil Economics, PMAS-Arid Agriculture University,
Rawalpindi Corresponding Author : Muhammad Waqas Khalid PMAS-Arid
Agriculture University Rawalpindi, Pakistan
[email protected] Abstract: Now a days good governance is a
burning issue of the modern world. Good governance helps maintain
social equality as well as economic growth. The paper is presents
the effect of good governance on inflation. Good Governance is
divided into three basic dimensions; Economic Governance, Political
Governance and Institutional Governance while each dimension is
further divided into two dimension. The data used in this paper is
time series data, world governance indicators presented by Kaufmann
et al., which is Upper bound of 90% confidence interval for
governance, in percentile rank terms. By using methodology of Engle
Granger it is found that every dimension of basic dimension has
short run as well as long run relationship with inflation. Key
Words: Economic Governance, Political Governance, Institutional
Governance, World Governance Indicators INTRODUCTION Good
governance is a term that describes us how public institutions
manage public affairs and manage public resources. Governance is a
process through which government makes decisions and makes policies
to implement those decisions. The term governance correlates with
different sectors of society, international, national as well as
local governance. The concept of "good governance" often emerges to
compare ineffective economies or political bodies with sustainable
economies and political bodies. The concept cores lies on the
responsibility of governments and governing bodies to meet the
needs of the masses as opposed to select groups in society. Asian
Development Bank (1995) identified four basic elements of good
governance such as accountability, participation, predictability
and transparency. Governance is known to be good democratic
governance at domestic level if all these elements are to be
fulfilled; fair election & citizen participation, Citizen
expectations are met, Efficiency & Effectiveness, Transparency,
Law & Judicial decisions are respected, No Ethical Conduct ,
Skill and Capacity are continually improved ,Openness to change
& Innovation, Development is Sustainable , Sound Financial
Management , Respect for Human Rights &
Cultural Diversity and Accountability (Grindle 2010). Despite
some differences in the definition, the idea of good governance has
also reverberated across a wide political spectrum. For those on
the political right, good governance has intended order, rule of
law, and the institutional conditions for free markets to flourish.
For those on the political left, good governance include a concept
of equity and justice, security for the poor, for subgroups, and
for females, and a positive role for the state. Governance issues
at the macro and micro level. Constitution, size and resources of
government, and relationship among legislator, judiciary and the
military are included in macro issues, while commercial firms,
social institutions and civil society affairs are being included in
micro issues (McCawley 2005). Governance is the exercise of
political, economic and governmental ability to manage affairs at
all level of country. It consist of processes, mechanisms and
institutions through which citizens of the country articulate their
securities, use their legal rights, meet their obligations and
mediate their differences( United Nation Development Program 1997).
The definitions of governance used by international organizations
vary substantially (Weiss 2000). For the OECD, governance denotes
use political authority to exercise the control in economy to
manage resources
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for social and economic development (Kaufmann, et al. 2000). In
determining the component rating on the basis of ICRG, the
political category contributes 50 percent to the rating while other
two categories that are financial and economic categories
contribute 25% each. This development is predictable to improve the
quality and expand the scope of works to
find the determinants and consequences of good and bad
governance. Although this new dataset of the categories is suitable
for mapping out governance profiles and gaps across the countries
as well as within the country, it is less useful for making causal
inferences about the relationship between institutions and growth.
MATERIALS AND METHODS The good governance divided into three
dimensions i-e Economic Governance, Political Governance,
Institutional Governance while each dimension is further divided
into two dimensions i-e Government effectiveness, Regulatory
quality, Voice and accountability, Political instability and
violence, Rule of law, Control of corruption (Kaufmann, et al.
2000). Here in this paper we follow the dimensions of world good
governance indicators provided by Kaufmann et al. Functional form:
Y=F(X1, X2, X3 ,X4 ,X5 ,X6) Infl= F(G.E, R.Q, V.A, P.I.V, R.L, C.C
) Where Infl = Inflation G.E= Government effectiveness
R.Q=Regulatory quality V.A=Voice and accountability
P.I.V=Political instability and violence R.L= Rule of law C.C=
Control of corruption Engle Granger Methodology are used to show
short run as well as long run relationship among the variables. The
data used in this paper is time series data, world governance
indicators presented by Kaufmann et al., which is Upper bound of
90% confidence interval for governance, in percentile rank terms.
RESULTS AND DISCUSSIONS The above mentioned model is simple
regression model, the estimation of this model is taken through
ordinary least square (OLS) method which states that parameters are
chosen in such a way that residual sum of square is minimum. For
ordinary least square method the parameters and variables should be
linear; the model in this study satisfies this assumption so it is
the justification of using OLS method. The correctness of data set
is judged by applying unit root test for testing the stationarity
of data. It is important to decide whether the time series is level
or difference. The data is stationary when its mean, variance and
covariance are constant over time. Analysis of the above mentioned
tables is that all the variables are found non stationary at level
and intercept. The variables become stationary when the
t-calculated value is more negative than the t-critical value.
Consequently, ADF (Augmented Dickey Fuller) test has been used to
check the stationarity of the variables. However, all the variables
are stationary at 1st difference which are shown above table. It is
important to mention here that if the stationary variables are
used, then the results achieved, would be considerable and
non-spurious. There is also a problem of multicolinearity between
two independent variables which means that there is linear
relationship between two independent variables. The correlation
matrix has been used to see linear relationship between variables.
The results of correlation matrix is as follows.
G.E R.Q V.A P.I.V R.L C.C
G.E 1.00
0.29
7
-
0.031
0.58
7
0.563
0.546
R.Q 0.29
7
1.00
0.77
4
0.15
9
0.22
7
0.238
V.A
Augmented Dickey Fuller (ADF) Test for Stationary
At Level At 1st Difference
Variables
Intercept
Trend & intercept
Intercept
Trend & intercept
Difference
Infl -1.80 -2.82 -4.35 -4.07 I(1)
G.E -1.01 -2.29 -3.03 -3.94 I(1)
R.Q -2.35 -2.20 -3.32 -3.17 I(1)
V.A -2.63 -2.34 -3.70 -2.27 I(1)
P.I.V -1.37 -1.79 -4.60 -4.82 I(1)
R.L -0.95 -4.73 -7.32 -6.79 I(1)
C.C -2.19 -2.94 -3.90 -3.75 I(1)
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239
-0.03
1
0.774
1.00 0.156
0.223
-0.221
P.I.V
0.58
7
0.15
9
0.15
6
1.00
0.55
3
0.365
R.L 0.56
3
0.22
7
0.22
3
0.55
3
1.00
0.078
C.C 0.54
6
0.23
4
-
0.221
0.36
5
0.07
8
1.00
The variance inflation factors have also been used to detect the
multicollinearity; the value of VIF is 11.11 which show that no
multicollinearity exists in the independent variables. Another
problem that exists in the presence of two independent variables is
hetroscedasticity which means variance of error terms differs
across observations but hetroscedasticity is the problem of
cross-sectional data but here time series data has been used, so
there is no need of hetroscedasticity check. The other problem
which is associated with the time series data is autocorrelation,
which means correlation between members of observation ordered in
time. By Using Durbin Watson test there is no autocorrelation
detected in the data.
Variable Coefficients Std. Error
t-value
Prob.
C 29.25 10.51 2.78 0.027
G.E -0.36 0.24 -1.49 0.17
R.Q 0.44 0.28 1.56 0.16
V.A -0.16 0.31 -0.51 0.63
P.I.V -0.08 0.13 -0.65 0.53
R.L -0.30 0.27 -1.10 0.31
C.C -0.20 0.18 -1.11 0.30
After applying simple OLS and applying ADF test on residual at
level the value of residual -4.12 which is more negative then Engle
Granger table value -3.17. SO results shows that there exist long
run relationship and result are not spurious according Engle
Granger while results are against the classicals point of view
which said that if we run OLS on with making data stationary our
results are spurious. So our results are supporting the theory of
Engle Granger and reject the theory of Classicals. The theory of
Engle Granger are detailed discuss in methodology. Engle Granger
result with 1st difference and ECM
Variable
Coefficients
Std. Error
t-value Prob.
C 0.69 1.19 0.58 0.58
G.E -0.50 0.28 -1.74 0.14
R.Q 0.55 0.27 2.10 0.08
V.A -0.07 0.25 -0.27 0.80
P.I.V 0.23 0.38 0.61 0.57
R.L -0.31 0.17 -1.82 0.13
C.C -0.43 0.20 -2.11 0.08
ECM -0.58 0.19 -3.06 0.02
R-Squared (0.907)
Adj-R-Sqr (0.77)
F-Stat (7.01) Prob (0.024)
J-B Test (2.41) Prob (0.298)
DW (1.98)
After using the methodology of Engle Granger we get the results
above. As ECM is used to identify the short run relationship among
the variables so in our model p-value of ECM is 0.02 which
indicates that there is short run relationship among the variables
of our model. R2 show the goodness of fit of the model as Value of
R2 is 0.907 which states that 90.7% variation in the inflation due
to explained variables i-e Government Effectiveness, Regulatory
Quality, Voice & Accountability, Political instability, Rule of
law, Control of corruption and rest of the 9.3% due to other
factors which are not included in our model. Which states that our
model is good fitted. As F-Stat shows the overall significance of
the model so value of F-Stat is 7.01 which shows that our model is
overall significant. As Durban Watson test is used to identify the
problem of autocorrelation here value of it is 1.98 which shows
that model is not affected by this problem. As JB test tell us
either residual of our model is normally distributed or not so here
value of it is 2.41 which indicates that residual of our model is
normally distributed. CUSUM test is used to check the stability of
the model which is represented below
-8
-6
-4
-2
0
2
4
6
8
8 9 10 11 12 13 14
CUSUM 5% Significance
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As the values lies in the 5% interval this show that the model
structurally stable over the period of the time. CONCLUSION One of
the major macroeconomic targets of the countries is to keep the
inflation low. Low levels of inflation represent good economy while
higher levels of inflation are harmful for the economy. All the
main dimensions of governance i-e Average Economic, Average
Institutional and Average Political governance inversely effect the
inflation. While some are highly affected and some are little
depend upon the elasticity of their trend lines. When econometric
model is used to check the short run as well as long run
relationship among inflation and each dimension of main dimension;
government effectiveness, regulatory quality, voice and
accountability, political instability, rule of law and control of
corruption, then according to Engle Granger methodology it was
found that there exists short run as well as long run relationship
among the dependent and independent variables. REFERENCES Asian
Development Bank
1995 Governance: Sound Development Management. Asian Development
Bank, Manila.
Grindle, Merilee Serrill 2010 Good Governance: The Inflation of
an Idea. HKS Faculty Research Working Paper Series. John F. Kennedy
School of Government, Harvard University.
Kaufmann, Daniel, Kraay Aart and Zoido Pablo
Governance Matters II: Updated Indicators for 2000-01 (January
2002). World Bank Policy http://ssrn.com/abstract=297497
McCawley, Peter 2005 Governance in Indonesia: Some Comments.
Asian Development Bank Institute, Tokyo.
Weiss, Thomas G.
2000 Governance, Good Governance and Global Governance:
Conceptual and Actual Challenges. Third world quarterly 21 (5):
795-814.
2015The Explorer Islamabad Journal of Social
Sciences-Pakistan
