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International Research Journal of Finance and Economics
ISSN 1450-2887 Issue 56 (2010)
© EuroJournals Publishing, Inc. 2010
http://www.eurojournals.com/finance.htm


                Political Instability and Economic Development:
                          Pakistan Time-Series Analysis

                                       Muhammad Nadeem Qureshi
                               PhD Research Scholar, Department of Economics
                               Bahauddin Zakariya University Multan, Pakistan
                                    E-mail: nadeembinislam@yahoo.com
                                  Tel: +92-321-3020162, +92-22-3864776

                                           Karamat Ali
              Chairman, Department of Economics, Islamia University Bahawalpur, Pakistan

                                            Imran Rafi Khan
                               PhD Research Scholar, Department of Statistics
                               Bahauddin Zakariya University Multan, Pakistan

                                                      Abstract

                In case of Pakistan, only economic variables are observed as causes to high
        economic volatility while political variables are completely ignored. Although, it is
        apparent that the development pattern in Pakistan is highly volatile during the years of
        political instability that spans almost over the half history of the country. By taking the
        sample of 1971 to 2008 and using simple OLS technique, we observe how far political
        instability hampers the economic development of Pakistan. For the political instability
        measurement, ignoring all traditional measures of political instability, we construct political
        instability index by using seven different variables for Pakistan by employing Principal
        Component Technique; while for economic development measurement frequently
        economic development variables are used. Through analysis, the negative relationship is
        found between political instability and economic development in Pakistan.


        Keywords: Political Instability, Economic Development
        JEL Classification Code: O40

1. Introduction
The Economic development record is mixed one for Pakistan throughout its life i.e. now more than a
half century. Away from poor initial endowments and dismal forecast of crumbling on economic front
after its independence the growth rate is fair enough to counter the forecasts. The growth rate till the
date averages to five percents approximately (Zaidi, 2006) throughout the history despite of all types of
fluctuations the country has seen on economic, political, geographical fronts etc. In 2004-05, it
defeated every nation in the region except China with an approximate growth rate of 8.6 %1.


1
    Under the heading ‘Economic Growth’, the figures are taken from Government of Pakistan. (Various issues) Pakistan
    Economic Survey, Islamabad.
International Research Journal of Finance and Economics - Issue 22 (2008)                               180

        Since independence, notably the economy of Pakistan shows high Economic Growth in three
different periods: 1958 to 1970, 1977 to 1988 and 1999 to 2008; surprisingly all the time periods are
military-led governments. By keeping in view the type of government and high or low economic
performance, the sixty-three years are divided in seven periods:
    1. Post-Independence era (1947-1958)
    2. Military-led government era (1958-1971)
    3. Elected governments era (1971-1977)
    4. Military-led government era (1977-1988)
    5. Elected governments era (1988- 1999)
    6. Military-led government era (1999- 2008)
    7. Elected governments era (2008 to present)
        In the above mentioned periodical categories, first eleven years were just the foundation time
period. During military regime in second (1958-71), forth (1977-1988) and the sixth period (1999-
2008) high economic growth trend was observed and unfortunately after every military government the
elected government did not even maintain the economic growth, on the contrary the economic
conditions became that much worse that sometimes the country was near to default.
        On the political side, since its birth Pakistan could never enjoy a stable political scenario. It has
experienced almost all types of political controls from democracy-presidential and parliamentary- to
repeated military coups with economic theses from capitalism to socialism and a mix of these theoretic.
Pakistan experienced military government for almost 33 years and other 30 years practiced different
forms of government including democracy, which is approximately always dissolved before time. In
these 30 years the early 9 years was without any defined political system (1947-1956).
        In the current study, by keeping in view the fluctuations in the economic development with the
political scenario, it is hypothesized that besides other factors political instability plays a vital role in
the fluctuation of the economic development of Pakistan.


2. Literature Review
The relationship between political instability and economic growth is not new, a good number of
studies are present in this area. In the coming lines the most prominent literature is reviewed.
        Alesina, Ozler, Roubini and Swagel (1992) investigate the connections between economic
growth and political instability. For the period of 1950-82, he uses the sample of one hundred and
thirteen countries. The study uses simultaneous equations model and measure economic growth and
political instability simultaneously by using Amemiya’s Generalized Least Square technique (AGLS).
The authors conclude that where there are high chances of government collapse, growth is considerably
lower and vice versa, further they do not find any indication that economic growth is significantly
different when authoritarian regimes are compared to democracies.
        Barro and Lee (1994) observe the growth rates in 116 economies from 1965 to 1985. They
estimate five different variables impact on economic growth including political instability that is
measured by number of revolutions per year. The authors conclude that Political instability negatively
affects economic growth.
        Haan and Siermann (1996) examine whether lack of political stability and lack of political
freedom are negatively correlated with economic growth. By using a sample of 97 countries (excluding
major oil-exporters) for the period of 1963-88, the authors estimate cross-section model based on a
simple neo-classical production function. In conclusions, the study shows that the political instability
reduces economic growth in Africa and in continuation in Asia political instability hampers
investment.
        Feng (1997) examines the interrelationships among democracy, political instability and
economic growth. The author uses the technique of three-stage least square on the cross country data of
ninety six countries for the time period of 1960 to 1980 by using simultaneous equation system. The
estimation facts point out either there is constitutional government change or regime change, both have
181                         International Research Journal of Finance and Economics - Issue 56 (2010)

the significant reverse effects on growth; on the other hand the growth is affecting regime change
negatively and affecting positively the probability of the ruling party staying in power.
        Guillaumont, Jeanneney and Brun (1999) examine the role of instabilities on Africa’s low rates
of growth during 1970 to 1990 on a sample of African and non-African countries by using cross-
section statistical estimates. Among other instabilities, the authors estimate impact of political
instability on economic growth. The findings depict that the political instability lowered the rate of
GDP growth more through their effect on total factor productivity growth than by diminishing the rate
of investment.
        Gyimah-Brempong and Traynor (1999) investigate the linkages between economic growth and
political instability. He uses a big sample of 39 Sub-Saharan African countries. The researchers use
simultaneous equations model and a dynamic panel estimation method for the estimation of time-series
cross-national data for the period of 1975-88. In the findings the negative relationship is identified
between economic growth and political instability.
        Haber, Razo and Maurer (2000) presents rather surprising conclusions, clearly that it is not
compulsory that Political instability hamper the economic growth significantly by focusing on a single
country, Mexico, for the period of 1910-1934 (this time period in Mexico was noticeable by
revolutions, counter-revolutions, civil wars, military coups, and presidential assassinations). The
research is basically a discussion on the said topic on the basis of facts and figures over the said period.
They analyze descriptively and extensively and also with some regression analysis. Then they exert
that either there is political instability or not, the government can flourish the economic performance
just protecting the private property rights. Opposing the general phenomena that political instability
always worsens the economic performance.
        Asteriou and Price (2001) test the influence of political instability on economic growth for
United Kingdom for the period of 1961-1997 by using time-series data. They use GARCH and
GARCH-M models and OLS regression technique. Besides the direct use of proxies, they construct the
political instability index by employing principal component method. The researchers find that
political instability and growth of UK GDP per capita are strongly negatively related to each other.
        Fosu (2001) scrutinizes the inter-linkages between political instability and economic growth.
He uses the Cobb–Douglas production function. He uses the data of different events of coups d’etat of
the Sub-Saharan African countries for the period of 1960–1986. In conclusion, the author says that
political instability greatly hampers the economic growth in the Sub-Saharan African countries.
Further, he adds that political instability index is giving much more appropriate results than the coup
variables separately.
        Berthelemy, J.C., Kauffmann, C., Renard, L. and Wegner, L. (2002) observe that how
Government behaves on the political and economic level when social and political disturbances take
place. The researchers work on the dataset of twenty-two African countries for the time period of 1996
to 2001. They analyzed on quarterly basis from January 1996 to December 2001 to understand the
interlinks between nature of political regime and political unrest; while annual data is also used to
observe the economic and political dynamics. Besides other conclusions, the researchers come to the
points that not only political events controlled the political developments, the economic factors also
responsible to them.
        Fosu (2002) examines the degree to which a range of coup events of political instability in the
thirty one Sub-Saharan African countries bothered the economic growth in the post-colonial period for
the period of 1960-86. The author uses augmented production framework that integrates political
instability events. The study uses OLS technique for the analysis. Political instability is measured as of
three events, they are as given: Abortive coups, Coup plots and Successful coups. Initially, the impact
on economic growth of Abortive coup, Coup plots and Successful coups are observed separately and
then re-estimated with all three political instability events together. But the results remain same that
Abortive coups are found largest adverse effect on GDP growth and Coup plots effects are found
adverse and significant but less than Abortive coups and at last Successful coup, surprisingly, are
International Research Journal of Finance and Economics - Issue 22 (2008)                                              182

observed as insignificant. McGowan & Johnson (1984) find that successful coup was the most
destabilizing event to economic growth but on the contrary this work finds that it is insignificant in
case of 31 SSA countries.
         Ghura and Mercereau (2004) provide econometrical proof that through deteriorations in terms
of trade and low tax revenues, the chances of political instability in the Central African Republic has
been augmented. Although econometrically the direct impact of political instability on economic
growth is not significant. With the intention to test the proposition, the researchers estimate a probit
model for the Central African Republic annual data series for the period of 1967- 2002. In conclusion,
it is said that political instability and social unrest adversely affect the Central African Republic
economy from time to time.
         Institute of Integrated Development Studies, Katmandu, Nepal (2005) conduct research to
observe the very active topic of today’s research, i.e. how political instability affect the economic
growth. The study is conducted particularly for the country Nepal. They construct two political
instability indexes to capture the political unstable environment of Nepal. For the construction of
indexes, they use Principal component method for one and for the other index Arbitrary method. The
researchers used following six variables (Demonstrations, Politically motivated killings, general
strikes, the sum of the total numbers of political prisoners, Change of government and Change of
cabinet) in the construction of Political instability indexes. Through the econometric analysis, the study
reveals that economic growth is badly affected by the political instability in Nepal. The impact of
political instability on the economy of Nepal is extensive.
         Zureiqat (2005) studies the connections between political instability and economic
performance, where Polity II democratization score2 is used as the political instability measurement
variable, while GDP per capita is used for the measurement of economic performance. The author uses
the data of twenty five countries of five different regions: Africa, Central and Eastern Europe, Latin
America, the Middle East, and Southeast Asia. The sample is of 1985 to 2002. The results of the
empirical models demonstrate significant evidence supporting the proposition that political instability
slow down the economic growth and, on the other hand, there is no significant sign observed that
economic growth and political instability are endogenous and mutually determined. Regarding the
question that how different economies behave with political instability, vary greatly among the regions.
It is found that Southeast Asia with the lowest Polity II score has the highest GDP per capita, while the
Middle East with the highest Polity II score has the highest GDP per capita.
         Campos and Karanasos (2008) analyze the impact of political instability on the economic
growth of by using time series data for Argentina over a long time period of 1896 to 2000. They use
Power-ARCH framework for the study. They find strong negative impact of political instability on the
economic growth of Argentina.
         Through the literature review, we come to the conclusion that political instability exclusively
hampers the economic growth either there is time series analysis or the panel data analysis.


3. Research Design and Sample
This research is associated with the relationship between political instability and economic
development of Pakistan. To examine this relationship econometric tools have been used. The sample
of the study is 1971 to 2008. Annual time series data of this period has been used.




2
    Polity2 was published in the Polity IV dataset project by Monty G. Marshall of the University of Maryland, College Park
    and Keith Jaggers of Colorado State University in 2002. The score ranges from -10 (strongly autocratic) to +10 (strongly
    democratic).
183                         International Research Journal of Finance and Economics - Issue 56 (2010)

4. Models
To observe the overall impact of political inability on the economic development in Pakistan, some
single equation models are established to check our hypothesis.
        We are going to observe the relationship of dependent variables with the political instability;
wherever necessary we convert dependent variable series in the log form, because our variable Political
Instability which is independent variable here, is in the form of index with mean 10. The political
instability index is self-constructed and discussed in the coming lines. So, now equations in the
functional forms are:
  1.    Manf =         f (PI)
  2.    LInv =         f (PI)
  3.    Exp =          f (PI)
  4.    Inf     =      f (PI)
  5.    LExtdt =       f (PI)
  6.    Emp =          f (PI)
        Where political instability (PI) is independent variable and manufacturing production growth
rate (Manf), log of total investment (LInv), total exports growth rate (Exp), inflation rate (Inf), log of
external foreign debt (LExtdt) and employment rate (Emp) are the dependent variables, manufacturing
production is used as a proxy of domestic output.


5. Sources of the Data
All the data is taken from the World Development Indicators 2010, except total investment data is
taken from the Government of Pakistan, Pakistan Economic Survey, Various issues and for political
instability an index is constructed.
        The data for all the variables of political instability is self-calculated on the basis of quality data
taken from the book, Razi and Shakir (2005) “Pakistan 58 years”; which is based on a research of all
leading newspaper news.


6. Construction of Political Instability Index
Quantitative studies of the relation between political instability and economic growth have to tackle
one major issue that is how to define political instability.
        Researchers have defined and measured political instability in two ways. One way is to use one
or more variables suitable for study i.e. some studies used only one variable as an indicator of political
instability. Haan and Siermann (1996), Benhabib and Spiegel (1997) focuses on executive turnover,
namely, on the frequency of government collapses as an indicator; Alesina et al. (1992) and Alesina et
al. (1996) used an estimated probability of government termination; Guillaumont, Jeanneney and Brun
(1999) and Stevens (2000) used Government longevity; Fosu (2002a), Fosu (2002b), Fosu (2004), and
Ghura and Mercereau (2004) used coup events and Zureiqat (2005) used Polity II democratization
score as an indicator. Some researchers used two or three different variables to define political
instability, such as Easterly and Rebelo (1993) used assassinations and war casualties; Barro and Lee
(1994) used revolutions, assassinations war casualties; Sala-i-Martin (1997) used revolutions, coups,
and war dummy; Ley and Steel (1999) used revolutions, coups, and war dummy; Berthelemy et al.
(2002) used occurrence of strikes, demonstrations, violence and coup d’etat; etc. The other way is to
use an index of socio-political unrest that summarizes several indicators of more or less violent forms
of political protest and social violence such as riots, political prisoners, demonstrations against the
government, strikes against government, purges, political motivated killings and assassinations etc.
        Earlier, Hibbs (1973), Vaniers and Gupta (1986) and Gupta (1990) used Principal Component
Method for the construction of Political Instability index, but this method become prominent, when it
is used by Alesina and Perotti (1996). Later on by following them some of the researchers also used the
International Research Journal of Finance and Economics - Issue 22 (2008)                             184

Principal Component Method to construct an aggregate Political Instability index i.e. Perotti (1996),
Campos and Nugent (1999a), Gyimah-Brempong and Traynor (1999), Annett (2000), Asteriou and
Simon Price (2001) and Ponzio (2005) and Institute of Integrated Development Studies, Katmandu,
Nepal (2005). Although, all of them used same technique, but definitely of different indicators as
suited them for the study.
        Political instability in Pakistan normally observed only through democratic or non-democratic
government, but in fact, this criterion is failed to describe political stability in Pakistan, There is
democracy or not, this is only one factor of political stability. As it is mentioned in earlier that in
military regimes Pakistan showed much more good performance in economic indicators than in
democratic era. Although, it is believed that it is only due to government longevity, so government
longevity is another factor of political stability. Some believe that frequent government changes plays
vital role in political instability. So we cannot only justified by one of these phenomenons. For proper
measurement of political instability, following the methodology of Alesina and Perotti (1996) but
different indicators that can best define the political instability in Pakistan are being used to construct
political instability index for Pakistan for the year 1971-2008.
        The total number of general strikes, demonstrations, riots, government longevity, change of
government including coups, war and regime type have all been used as indicators of political
instability and thus are used to construct a composite index of political instability. This Political
Instability Index is constructed by Principle Component Method by using computer software “Minitab
13 for Windows”.
        Above-mentioned studies, which used Principal Component technique for constructing index,
used only first principal component index for the analysis except Asteriou and Simon Price (2001)
(who used all principal component indexes as that study scope was). Therefore, we also use the first
principal component index as the index of political instability.

6.1. Definitions of Political Instability Index Variables
Although detailed description of variables is given in Appendix D, for general view brief definitions
are outlined here.

General Strikes
General strikes called by political actors for a complete closedown or blockade of economic activities
that can last anywhere from a single to several days.

Demonstrations
It is an assembly of people or procession with an explicit political purpose.

Riots
It is explained as any violent demonstration or clash of more than 100 citizens involving the use of
physical force.

Government Longevity
Years of Government longevity.

Government change
An instance of change of government including military coups.

War
Dummy.

Regime Type
Democracy, Military led democracy or Military government.
185                              International Research Journal of Finance and Economics - Issue 56 (2010)


6.2. Summary of Political Instability Index
As earlier mentioned that political instability is measured as the sum of the total numbers of general
strikes called by political actors, demonstrations, riots, government longevity, government change
including military coups, war and regime type. We consider that these particular above mentioned
parameters, rather than any other set of variables, are able to better represent the politically unstable
environment of Pakistan.
         The rational in selecting these particular parameters is that they, not only, are able to capture
politically unstable situations but also their possible effect on economic growth in Pakistan. General
statistical features of these indicators are given below in table 6.1 and the brief summary of first
principal component is given below in table 6.2.

Table 6.1: Summary of the Political Instability Indicators

        S.No.            Variables                   Observations                Min                   Max
          1              General Strikes                 38                       0                    69
          2              Demonstrations                  38                       0                    31
          3              Riots                           38                      13                    258
          4              Government Longevity            38                       0                    10
          5              Government change               38                       0                     1
          6              War                             38                       0                     1
          7              Regime Type                     38                       1                     3
Source: Self calculation
Min: Minimum value of variable in a year
Max: Maximum value of variable in a year

Table 6.2: Factor Loadings of PC1

  Variables                                                                           PC1
  General Strikes                                                                    0.511*
  Demonstrations                                                                    0.384**
  Riots                                                                             0.329**
  Government Longevity                                                              -0.326**
  Government change                                                                 0.378**
  War                                                                                0.457*
  Regime Type                                                                        -0.158
Note:
* Denotes statistical significance at 1% level.
** Denotes statistical significance at 5% level
Critical values from Koutsoyiannis (1977)

         PI = 0.511 E1 + 0.384 E2 + 0.329 E3 – 0.326 E4 + 0.378 E5 + 0.457 E6 – 0.158 E7
         Where
         E1 = General Strikes                        E2 = Demonstration
         E3 = Riots                                  E4 = Government Longevity
         E5 = Government change including coups E6 = War
         E7 = Regime Type
         On the basis of above mentioned equation political instability is calculated and standardized as
required by the method for unbiased results, then the index is transformed with mean 103 for better
results.


3
    Institute of Integrated Development Studies, Katmandu, Nepal (2005), the index constructed transformed for better
    analysis
International Research Journal of Finance and Economics - Issue 22 (2008)                              186

7. Definitions of all Variables
Some of the variables in above-mentioned model are quite clear, but for a clear-cut understanding
summary of specification is given below for all of the variables.
      PI     =       Political Instability: Measured by political instability index which is self
                     constructed by using seven different variables (General Strikes, Demonstration,
                     Riots, Government longevity, Government change, War and Regime type) by
                     using Principal Component Method for the year 1971-2008.
      Manf =         Manufacturing production: Manufacturing production growth rate.
      LInv =         Log of Investment: Log of Total investment.
      Exp =          Total exports: Annual Growth rate of total exports.
      Inf    =       Inflation: Inflation rate.
      LExtd =        Log of total external foreign debt.
      Emp =          Employment rate


8. Estimation and Explanation
For observing the effects of political instability on the economic development of Pakistan for the time
period of 1971 to 2008, in this section we are going to present results and their explanation
       All the equations are estimated by the method of OLS and the base year for all observations is
same. All the equations and their parameters are already discussed. If autocorrelation is found in an
equation, it is re-estimated by Auto regression or Moving average; AR (1) or AR (2) or MA (1) or MA
(2). The results of the estimations are reported below.

8.1. Manufacturing Sector and Political Instability
   •   Dependent Variable: Manufacturing Sector Growth Rate
   •   Independent Variable: Political Instability Index
       In the table 8.1, the results show that the impact of political instability on manufacturing sector
is highly significant at 1%, and the relationship is negative which was expected. The found
autocorrelation is removed by using AR(1) and MA(1). High political instability reduces the growth in
the manufacturing sector. This is well proven fact that the manufacturing sector is directly inter-linked
with the government trade policy and if the overall political situation is poor in the country, it will
negatively affect the manufacturing organizations too, as it is depicted through our results.

8.2. Investment and Political Instability
   •    Dependent Variable: Log of total Investment
   •    Independent Variable: Political Instability Index
        In the investment equation, the political instability is negative and significant which shows that
the overall investment gets also hampered due to political instability in Pakistan (see table 8.2). The
result to this variable is significant at 10 percent level. The autocorrelation is removed through AR(1),
AR(2) and MA(1). High political instability adversely affects the overall investment in Pakistan. High
political instability puts off the coming investment and also disturbs existed investment; this is, in fact,
a long run loss in terms of loosing investors’ confidence for both: existed and expected future
investors. Hence, we can say on the basis of our results that stability in the political setup improves
investors’ confidence, which ultimately develop investment culture in the country.
187                              International Research Journal of Finance and Economics - Issue 56 (2010)
Table 8.1: Summary of results for single equations regressions Sample 1971-2008

                                    Manufacturing sector Equation Dependent variable:
                                               Manufacturing growth rate
 Variables                                                           Coefficient (t-statistics in parenthesis)
                                                                        Ordinary Least Square Method
 Intercept                                                                            20.86701
                                                                                    (3.946685)
 Political Instability                                                              -1.473978*
                                                                                   (-2.758455)
 AR(1)                                                                               -0.306533
                                                                                   (-1.279711)
 MA(1)                                                                               0.512507
                                                                                    (1.965698)
 R2                                                                                  0.289149
 Adjusted R2                                                                         0.218064
 F-Statistics                                                                        4.067640
 Sum of squared residual                                                              327.0565
 Durbin-Watson stat                                                                   1.857588
 Inverted AR Roots                                                                       -.31
 Inverted MA Roots                                                                       -.51
Note:
* Denotes statistical significance at 1% level or better.
** Denotes statistical significance at 5% level
*** Denotes statistical significance at 10% level

8.3. Export Growth and Political Instability
    •   Dependent Variable: Export Growth Rate
    •   Independent Variable: Political Instability Index
        On the basis of investment equation results, we can deduce that if investment is hampered due
to unstable political setup, the export will also be disturbed due to political instability; because if due to
high political instability, there is no good environment for investment how there could be good export
growth. So, the results in table 8.3 prove our hypothesis in the export equation that the exports in
Pakistan adversely affected due to high political instability. The result is significant at 5% level and
there is no autocorrelation found. F-statistics and T-statistics are quite significant in the equation.

Table 8.2: Summary of results for single equations regressions Sample 1971-2008

                                         Investment Equation Dependent variable:
                                                 Log of total Investment
                                                                       Coefficient (t-statistics in parenthesis)
 Variables
                                                                         Ordinary Least Square Method
                                                                                       15.78419
 Intercept
                                                                                      (12.38268)
                                                                                    -0.025031***
 Political Instability
                                                                                     (-1.740548)
                                                                                       0.260973
 AR(1)
                                                                                      (0.967450)
                                                                                       0.674779
 AR(2)
                                                                                      (2.602460)
                                                                                       0.839183
 MA(1)
                                                                                      (3.301599)
 R2                                                                                    0.996242
 Adjusted R2                                                                           0.995664
 F-Statistics                                                                          1723.289
 Sum of squared residual                                                               0.163992
International Research Journal of Finance and Economics - Issue 22 (2008)                                          188
 Durbin-Watson stat                                                                    2.022875
 Inverted AR Roots                                                     .96                -.70
 Inverted MA Roots                                                                        -.84
Note:
* Denotes statistical significance at 1% level or better.
** Denotes statistical significance at 5% level
*** Denotes statistical significance at 10% level

Table 8.3: Summary of results for single equations regressions Sample 1971-2008

                                        Export growth Equation Dependent variable:
                                                 Total export growth rate
                                                                       Coefficient (t-statistics in parenthesis)
    Variables
                                                                          Ordinary Least Square Method
                                                                                       31.93331
    Intercept
                                                                                      (2.484981)
                                                                                     -2.558662**
    Political Instability
                                                                                      (-2.018532)
 R2                                                                                    0.109900
 Adjusted R2                                                                           0.082927
 F-Statistics                                                                          4.074470
 Sum of squared residual                                                               5149.681
 Durbin-Watson stat                                                                    2.267069
Note:
* Denotes statistical significance at 1% level or better.
** Denotes statistical significance at 5% level
*** Denotes statistical significance at 10% level

8.4. Inflation and Political Instability
       •Dependent Variable: Inflation Rate
       •Independent Variable: Political Instability Index
        When we find out the impact of political instability on the inflation in Pakistan, our results
depict the positive relationship between the two variables; results are shown in table 8.4. When there is
high political instability in the country, there will be higher inflation and the results are highly
significant. There was autocorrelation found in the results which was removed through AR(1) and
AR(2). Fstatistics and T-statistics are also showing complete significance.
        For the country like Pakistan where inflation remains a constant issue to control over the
history, during 90s seven out of ten years, the inflation remains in two digits, that mean more than
10%4, then slow down during 1998 to 2003 and again has increasing trend since then. The 90s was
considered as unstable political environment too, due to frequent government changes and bad law and
order situation in the country. So, we can say that if there is high instability in the political
environment, the overall price level will also increase unexpectedly.




4
    Government of Pakistan, Pakistan Economic Survey 2005-06.
189                              International Research Journal of Finance and Economics - Issue 56 (2010)
Table 8.4: Summary of results for single equations regressions Sample 1971-2008


                                                    Inflation Equation
                                              Dependent variable: Inflation Rate
 Variables                                                               Coefficient (t-statistics in parenthesis)
                                                                            Ordinary Least Square Method
 Intercept                                                                               -10.25975
                                                                                       (-2.628662)
 Political Instability                                                                  1.940467*
                                                                                        (5.141241)
 AR(1)                                                                                   1.069568
                                                                                        (8.728792)
 AR(2)                                                                                   -0.618196
                                                                                       (-5.645178)
  R2                                                                                     0.711400
  Adjusted R2                                                                            0.681545
  F-Statistics                                                                           23.82842
  Sum of squared residual                                                                286.0604
  Durbin-Watson stat                                                                     2.045941
  Inverted AR Roots                                                 .53+.58i              .53-.58i
Note:
* Denotes statistical significance at 1% level or better.
** Denotes statistical significance at 5% level
*** Denotes statistical significance at 10% level

8.5. Foreign Debt and Political Instability
    •    Dependent Variable: Log of Total Foreign Debt
    •    Independent Variable: Political Instability Index
         In external debt equation, we hypothesize that when there is higher instability in the political
environment, there will be higher external debt burden. Our results prove our hypothesis and the
political instability is quite positively significant (see table 8.5); which reveals that whenever there is
instability in the political setup in the country, the overall debt start increasing more. The result is
significant at 5% level. The found autocorrelation is removed through AR(2). T-statistics and F-
statistics are at significant level. External foreign debt remains a big burden on the Pakistan economy
since 1970s; no serious efforts were made to get rid of foreign loans. In 1998-99, it has reached
maximum to 61.48%1 of total GDP of Pakistan. Although, since then, it has a declining trend, but even
then it is still very high up to 32.6% of total GDP.
International Research Journal of Finance and Economics - Issue 22 (2008)                                          190
Table 8.5: Summary of results for single equations regressions Sample 1971-2008

                                    Foreign Debt Burden Equation Dependent variable:
                                                Log of Total Foreign Debt
                                                                       Coefficient (t-statistics in parenthesis)
 Variables
                                                                          Ordinary Least Square Method
                                                                                       24.76518
 Intercept
                                                                                      (87.11755)
                                                                                     0.013747**
 Political Instability
                                                                                      (2.022953)
                                                                                       0.905690
 AR(2)
                                                                                      (58.71782)
 R2                                                                                    0.992414
 Adjusted R2                                                                           0.991908
 F-Statistics                                                                          1962.289
 Sum of squared residual                                                               0.101145
 Durbin-Watson stat                                                                    1.540473
 Inverted AR Roots                                                 .95                    -.95
Note:
* Denotes statistical significance at 1% level or better.
** Denotes statistical significance at 5% level
*** Denotes statistical significance at 10% level

8.6. Employment Growth Rate and Political Instability
    •   Dependent Variable: Employment Growth Rate
    •   Independent Variable: Political Instability Index
        The employment rate is always a big question in Pakistan’s economy. The economist always
would like to find out the root causes of disturbances in employment generation. In the employment
growth equation (see table 8.6), political instability is negative, as it was expected. The result is highly
significant at 1% level. There was autocorrelation found in the results which was removed through
AR(1) and MA(1). In Pakistan, political instability highly disturbs the employment rate. The results
significance can be observed by T-statistics and F-statistics.

Table 8.6: Summary of results for single equations regressions Sample 1971-2008

                                 Employment Growth Rate Equation Dependent variable:
                                             Employment Growth Rate
                                                                  Coefficient (t-statistics in parenthesis)
 Variables
                                                                     Ordinary Least Square Method
                                                                                  -22.07097
 Intercept
                                                                                (-1.153483)
                                                                                 -0.325529*
 Political Instability
                                                                                (-2.626680)
                                                                                  1.012564
 AR(1)
                                                                                 (229.0833)
                                                                                  -0.957090
 MA(1)
                                                                                (-51.00997)
 R2                                                                               0.990045
 Adjusted R2                                                                      0.989050
 F-Statistics                                                                     994.5317
 Sum of squared residual                                                           15.11551
 Durbin-Watson stat                                                                1.762263
 Inverted AR Roots                                                                   1.01
 Inverted MA Roots                                                                   0.96
Note:
* Denotes statistical significance at 1% level or better.
** Denotes statistical significance at 5% level
*** Denotes statistical significance at 10% level
191                              International Research Journal of Finance and Economics - Issue 56 (2010)

Conclusion
Throughout the analysis, the impact of political instability on the economic development is quite
significant and robust. Political instability badly hampers most of the areas of the economy. It is
evident from the history that economic growth in Pakistan averages to a good throughout the past that
is approximately 5% per annum5. Yet the study has concluded a profound impact of political scene on
the economic development of the country that is a bad political situation is found to be a development
retarding one and the development pattern is highly volatile in the years of political instability that
spans almost over the half history. In fact, the decision makers are political actors, the policies are
made, executed but disturbed due to political instability, and most of the policies go in vain due to
government change particularly irregular government change. So, if the political scene is made stable
then at least the same pace of economic development can sum to the average number very easily and
even this contribution may lead to higher levels of economic development. Here the recommendation
of the study is to smooth the political scene of the country which broadly can contribute to the present
development and average growth rate of the country.
        The most important for Pakistan is, let any of the political system be flourished; there must not
be any discontinuation of it because every thing needs some time to grow up. The most harmful for the
development of Pakistan is non-stability of political system, which is actually the centre of decision, so
stable the political setup for the long term prosperity of the country.


References
[1]       Alesina, A., Ozler, S., Roubini, N. and Swagel, P. (1992) “Political Instability and Economic
          Growth” (September), NBER Working Paper # 4173.
[2]       Alesina, A. and Perotti, R. (1996) “Income Distribution, Political Instability and Investment”
          European Economic Review, 40, pp.1203-1228.
[3]       Annett, Anthony (2000) “Social Fractionalization, Political instability and the size of
          Government”, IMF Working Paper, WP/00/82.
[4]       Asteriou, D., and Price, S. (2001) “Political Instability and Economic Growth: UK Time Series
          Evidence”, Scottish Journal of Political Economy (September), Vol.48, No.4, pp.244- 249.
[5]       Barro, R. J and Lee. J. (1994) “Sources of Economic Growth”, Carnegie Rochester Conference
          Series on Public Policy.
[6]       Ben-Habib, Jess, and Mark Spiegel. 1992. “The Role of Human Capital and Political Instability
          in Economic Development.” Economic Research Report. New York University, C. V. Starr
          Center for Applied Economics, New York. Processed.
[7]       Berthelemy, J.C., Kauffmann, C., Renard, L. and Wegner, L. (2002) “Political Instability,
          Political Regimes and Economic Performance in African Countries”. African EconomicOutlook
          (March).
[8]       Campos, N. F, and Karanasos, M. G. (2008) “Growth, volatility and political instability:
          Nonlinear time-series evidence for Argentina, 1896–2000” Economics Letters, 100, pp.135–
          137.
[9]       Campos, N. F. and Nugent, J. B. (1999a) “Who is Afraid of Political Instability” University of
          Southern California, Mimeo.
[10]      Easterly, William, and Sergio Rebelo. (1993) “Fiscal Policy and Growth: An Empirical
          Investigation.” Journal of Monetary Economics 32, (December), pp.417-58.
[11]      Feng, Yi. (1997) “Democracy, Political Instability and Economic Growth”, British Journal of
          Political Science (July), Vol.27, No.3, pp.391-418.
[12]      Fosu, A. K. (2001) “Political instability and economic growth in developing economies: some
          specification empirics”, Economics Letters, 70, pp. 289–294.

5
    See, for example, Zaidi (2006) “Issues in Pakistan’s Economy” Oxford University Press, Karachi Pakistan.
International Research Journal of Finance and Economics - Issue 22 (2008)                          192

[13]   Fosu, A.K. (2002) “Political instability and economic growth: Implications of coup events in
       sub-Saharan Africa”, American Journal of Economics and Sociology, (Jan), Vol.61. No.1.
[14]   Ghura, D. and Mercereau, B. (2004) “Political Instability and Growth: The Central African
       Republic” IMF Working Paper/04/80, African and Asia and Pacific Department.
[15]   Government of Pakistan, “Pakistan Economic Survey”, various issues.
[16]   Guillaumont, P., Jeanneney, S.G, and Brun, J.F. (1999) “How Instability Lowers African
       Growth”, Journal of African Economies, Vol.8, No.1, pp.87-107.
[17]   Gupta, D. K. (1990) “The Economics of Political Violence: the Effect of Political Instability on
       Economic Growth” New York and London: Greenwood Press and Praeger.
[18]   Gyimah-Brempong, Kwabena and Traynor, Thomas L. (1999) “Political Instability, Investment
       and Economic Growth in Sub-Saharan Africa”, Journal of African Economies,Vol.8, No.1,
       pp.52-86.
[19]   Haan, J. and Siermann, C.L.J. (1996) “Political Instability, Freedom and Economic Growth:
       Some Further Evidence”, Economic Development and Cultural Change (Jan), Vol.44, No.2,
       pp.339-350.
[20]   Haber, S., Razo, A. and Maurer, N. (2000) “Political Instability, Credible Commitments and
       Economic Growth: Evidence from Revolutionary Mexico” Stanford University.
[21]   Hibbs, Douglas A. (1973) “Mass Political Violence: A Cross-Sectional Analysis”, New York:
       Wiley and Sons.
[22]   Institute of Integrated Development Studies, Katmandu, Nepal (2005) “The Relationship
       Between Political Instability and Economic Growth in Nepal (1975-2003)” South Asia Network
       of Economic Research Institutes (SANEI), New Delhi, India.
[23]   Ley, E. and Steel, M. (1999) “We Have Just Averaged Over Two Trillions Cross Country
       Growth Regressions” University of Edinburgh, Mimeo.
[24]   McGowan, P. J. and T. J. Johnson (1984) “African Military Coup d’etat and underdevelopment:
       A Quantitative Historical Analysis”, Journal of Modern African Studies, vol.22, No. 4, pp.633-
       666.
[25]   Perotti, R. (1996) “Growth, Income Distribution and Democracy: What the Data Say”
       Journalof Economic Growth, 1, pp.149-187.
[26]   Razi and Shakir (2005) “Pakistan 58 years- 14 August 1947 to 14 August 2005” Sang-e-Meel
       Publications Lahore.
[27]   Sala-i-Martin, Xavier (1997a) “I Just Ran Two Million Regressions” American Economic
       Review, 87 (2), pp.178-83.
[28]   Sala-i-Martin, Xavier (1997b) “I Just Ran four Million Regressions” NBER Working Paper No.
       4186.
[29]   Stevens, G. (2000) “Politics, economics and investment: explaining plant and equipment
       spending by US direct investors in Argentina, Brazil and Mexico” Journal of International
       Money and Finance, 19, pp.153-183
[30]   Vanieris, Yiannis P., and Gupta, D. K. (1986) “Income Distribution and Socio-political
       Instability as Determinants of Savings; A Cross-Sectional Model”, Journal of Political
       Economy, Vol.96, pp.873-83.
[31]   Zaidi, S. Akbar (2006) “Issues in Pakistan’s Economy” Oxford University Press, Karachi
       Pakistan.
[32]   Zureiqat, Hazem M. (2005) “Political Instability and Economic Performance: A Panel Data
       Analysis” Economics Department, Macalester College, Award Winning Economics Papers.

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Political Instability & Economic Development: Pakistan time-series Analysis

  • 1. International Research Journal of Finance and Economics ISSN 1450-2887 Issue 56 (2010) © EuroJournals Publishing, Inc. 2010 http://www.eurojournals.com/finance.htm Political Instability and Economic Development: Pakistan Time-Series Analysis Muhammad Nadeem Qureshi PhD Research Scholar, Department of Economics Bahauddin Zakariya University Multan, Pakistan E-mail: nadeembinislam@yahoo.com Tel: +92-321-3020162, +92-22-3864776 Karamat Ali Chairman, Department of Economics, Islamia University Bahawalpur, Pakistan Imran Rafi Khan PhD Research Scholar, Department of Statistics Bahauddin Zakariya University Multan, Pakistan Abstract In case of Pakistan, only economic variables are observed as causes to high economic volatility while political variables are completely ignored. Although, it is apparent that the development pattern in Pakistan is highly volatile during the years of political instability that spans almost over the half history of the country. By taking the sample of 1971 to 2008 and using simple OLS technique, we observe how far political instability hampers the economic development of Pakistan. For the political instability measurement, ignoring all traditional measures of political instability, we construct political instability index by using seven different variables for Pakistan by employing Principal Component Technique; while for economic development measurement frequently economic development variables are used. Through analysis, the negative relationship is found between political instability and economic development in Pakistan. Keywords: Political Instability, Economic Development JEL Classification Code: O40 1. Introduction The Economic development record is mixed one for Pakistan throughout its life i.e. now more than a half century. Away from poor initial endowments and dismal forecast of crumbling on economic front after its independence the growth rate is fair enough to counter the forecasts. The growth rate till the date averages to five percents approximately (Zaidi, 2006) throughout the history despite of all types of fluctuations the country has seen on economic, political, geographical fronts etc. In 2004-05, it defeated every nation in the region except China with an approximate growth rate of 8.6 %1. 1 Under the heading ‘Economic Growth’, the figures are taken from Government of Pakistan. (Various issues) Pakistan Economic Survey, Islamabad.
  • 2. International Research Journal of Finance and Economics - Issue 22 (2008) 180 Since independence, notably the economy of Pakistan shows high Economic Growth in three different periods: 1958 to 1970, 1977 to 1988 and 1999 to 2008; surprisingly all the time periods are military-led governments. By keeping in view the type of government and high or low economic performance, the sixty-three years are divided in seven periods: 1. Post-Independence era (1947-1958) 2. Military-led government era (1958-1971) 3. Elected governments era (1971-1977) 4. Military-led government era (1977-1988) 5. Elected governments era (1988- 1999) 6. Military-led government era (1999- 2008) 7. Elected governments era (2008 to present) In the above mentioned periodical categories, first eleven years were just the foundation time period. During military regime in second (1958-71), forth (1977-1988) and the sixth period (1999- 2008) high economic growth trend was observed and unfortunately after every military government the elected government did not even maintain the economic growth, on the contrary the economic conditions became that much worse that sometimes the country was near to default. On the political side, since its birth Pakistan could never enjoy a stable political scenario. It has experienced almost all types of political controls from democracy-presidential and parliamentary- to repeated military coups with economic theses from capitalism to socialism and a mix of these theoretic. Pakistan experienced military government for almost 33 years and other 30 years practiced different forms of government including democracy, which is approximately always dissolved before time. In these 30 years the early 9 years was without any defined political system (1947-1956). In the current study, by keeping in view the fluctuations in the economic development with the political scenario, it is hypothesized that besides other factors political instability plays a vital role in the fluctuation of the economic development of Pakistan. 2. Literature Review The relationship between political instability and economic growth is not new, a good number of studies are present in this area. In the coming lines the most prominent literature is reviewed. Alesina, Ozler, Roubini and Swagel (1992) investigate the connections between economic growth and political instability. For the period of 1950-82, he uses the sample of one hundred and thirteen countries. The study uses simultaneous equations model and measure economic growth and political instability simultaneously by using Amemiya’s Generalized Least Square technique (AGLS). The authors conclude that where there are high chances of government collapse, growth is considerably lower and vice versa, further they do not find any indication that economic growth is significantly different when authoritarian regimes are compared to democracies. Barro and Lee (1994) observe the growth rates in 116 economies from 1965 to 1985. They estimate five different variables impact on economic growth including political instability that is measured by number of revolutions per year. The authors conclude that Political instability negatively affects economic growth. Haan and Siermann (1996) examine whether lack of political stability and lack of political freedom are negatively correlated with economic growth. By using a sample of 97 countries (excluding major oil-exporters) for the period of 1963-88, the authors estimate cross-section model based on a simple neo-classical production function. In conclusions, the study shows that the political instability reduces economic growth in Africa and in continuation in Asia political instability hampers investment. Feng (1997) examines the interrelationships among democracy, political instability and economic growth. The author uses the technique of three-stage least square on the cross country data of ninety six countries for the time period of 1960 to 1980 by using simultaneous equation system. The estimation facts point out either there is constitutional government change or regime change, both have
  • 3. 181 International Research Journal of Finance and Economics - Issue 56 (2010) the significant reverse effects on growth; on the other hand the growth is affecting regime change negatively and affecting positively the probability of the ruling party staying in power. Guillaumont, Jeanneney and Brun (1999) examine the role of instabilities on Africa’s low rates of growth during 1970 to 1990 on a sample of African and non-African countries by using cross- section statistical estimates. Among other instabilities, the authors estimate impact of political instability on economic growth. The findings depict that the political instability lowered the rate of GDP growth more through their effect on total factor productivity growth than by diminishing the rate of investment. Gyimah-Brempong and Traynor (1999) investigate the linkages between economic growth and political instability. He uses a big sample of 39 Sub-Saharan African countries. The researchers use simultaneous equations model and a dynamic panel estimation method for the estimation of time-series cross-national data for the period of 1975-88. In the findings the negative relationship is identified between economic growth and political instability. Haber, Razo and Maurer (2000) presents rather surprising conclusions, clearly that it is not compulsory that Political instability hamper the economic growth significantly by focusing on a single country, Mexico, for the period of 1910-1934 (this time period in Mexico was noticeable by revolutions, counter-revolutions, civil wars, military coups, and presidential assassinations). The research is basically a discussion on the said topic on the basis of facts and figures over the said period. They analyze descriptively and extensively and also with some regression analysis. Then they exert that either there is political instability or not, the government can flourish the economic performance just protecting the private property rights. Opposing the general phenomena that political instability always worsens the economic performance. Asteriou and Price (2001) test the influence of political instability on economic growth for United Kingdom for the period of 1961-1997 by using time-series data. They use GARCH and GARCH-M models and OLS regression technique. Besides the direct use of proxies, they construct the political instability index by employing principal component method. The researchers find that political instability and growth of UK GDP per capita are strongly negatively related to each other. Fosu (2001) scrutinizes the inter-linkages between political instability and economic growth. He uses the Cobb–Douglas production function. He uses the data of different events of coups d’etat of the Sub-Saharan African countries for the period of 1960–1986. In conclusion, the author says that political instability greatly hampers the economic growth in the Sub-Saharan African countries. Further, he adds that political instability index is giving much more appropriate results than the coup variables separately. Berthelemy, J.C., Kauffmann, C., Renard, L. and Wegner, L. (2002) observe that how Government behaves on the political and economic level when social and political disturbances take place. The researchers work on the dataset of twenty-two African countries for the time period of 1996 to 2001. They analyzed on quarterly basis from January 1996 to December 2001 to understand the interlinks between nature of political regime and political unrest; while annual data is also used to observe the economic and political dynamics. Besides other conclusions, the researchers come to the points that not only political events controlled the political developments, the economic factors also responsible to them. Fosu (2002) examines the degree to which a range of coup events of political instability in the thirty one Sub-Saharan African countries bothered the economic growth in the post-colonial period for the period of 1960-86. The author uses augmented production framework that integrates political instability events. The study uses OLS technique for the analysis. Political instability is measured as of three events, they are as given: Abortive coups, Coup plots and Successful coups. Initially, the impact on economic growth of Abortive coup, Coup plots and Successful coups are observed separately and then re-estimated with all three political instability events together. But the results remain same that Abortive coups are found largest adverse effect on GDP growth and Coup plots effects are found adverse and significant but less than Abortive coups and at last Successful coup, surprisingly, are
  • 4. International Research Journal of Finance and Economics - Issue 22 (2008) 182 observed as insignificant. McGowan & Johnson (1984) find that successful coup was the most destabilizing event to economic growth but on the contrary this work finds that it is insignificant in case of 31 SSA countries. Ghura and Mercereau (2004) provide econometrical proof that through deteriorations in terms of trade and low tax revenues, the chances of political instability in the Central African Republic has been augmented. Although econometrically the direct impact of political instability on economic growth is not significant. With the intention to test the proposition, the researchers estimate a probit model for the Central African Republic annual data series for the period of 1967- 2002. In conclusion, it is said that political instability and social unrest adversely affect the Central African Republic economy from time to time. Institute of Integrated Development Studies, Katmandu, Nepal (2005) conduct research to observe the very active topic of today’s research, i.e. how political instability affect the economic growth. The study is conducted particularly for the country Nepal. They construct two political instability indexes to capture the political unstable environment of Nepal. For the construction of indexes, they use Principal component method for one and for the other index Arbitrary method. The researchers used following six variables (Demonstrations, Politically motivated killings, general strikes, the sum of the total numbers of political prisoners, Change of government and Change of cabinet) in the construction of Political instability indexes. Through the econometric analysis, the study reveals that economic growth is badly affected by the political instability in Nepal. The impact of political instability on the economy of Nepal is extensive. Zureiqat (2005) studies the connections between political instability and economic performance, where Polity II democratization score2 is used as the political instability measurement variable, while GDP per capita is used for the measurement of economic performance. The author uses the data of twenty five countries of five different regions: Africa, Central and Eastern Europe, Latin America, the Middle East, and Southeast Asia. The sample is of 1985 to 2002. The results of the empirical models demonstrate significant evidence supporting the proposition that political instability slow down the economic growth and, on the other hand, there is no significant sign observed that economic growth and political instability are endogenous and mutually determined. Regarding the question that how different economies behave with political instability, vary greatly among the regions. It is found that Southeast Asia with the lowest Polity II score has the highest GDP per capita, while the Middle East with the highest Polity II score has the highest GDP per capita. Campos and Karanasos (2008) analyze the impact of political instability on the economic growth of by using time series data for Argentina over a long time period of 1896 to 2000. They use Power-ARCH framework for the study. They find strong negative impact of political instability on the economic growth of Argentina. Through the literature review, we come to the conclusion that political instability exclusively hampers the economic growth either there is time series analysis or the panel data analysis. 3. Research Design and Sample This research is associated with the relationship between political instability and economic development of Pakistan. To examine this relationship econometric tools have been used. The sample of the study is 1971 to 2008. Annual time series data of this period has been used. 2 Polity2 was published in the Polity IV dataset project by Monty G. Marshall of the University of Maryland, College Park and Keith Jaggers of Colorado State University in 2002. The score ranges from -10 (strongly autocratic) to +10 (strongly democratic).
  • 5. 183 International Research Journal of Finance and Economics - Issue 56 (2010) 4. Models To observe the overall impact of political inability on the economic development in Pakistan, some single equation models are established to check our hypothesis. We are going to observe the relationship of dependent variables with the political instability; wherever necessary we convert dependent variable series in the log form, because our variable Political Instability which is independent variable here, is in the form of index with mean 10. The political instability index is self-constructed and discussed in the coming lines. So, now equations in the functional forms are: 1. Manf = f (PI) 2. LInv = f (PI) 3. Exp = f (PI) 4. Inf = f (PI) 5. LExtdt = f (PI) 6. Emp = f (PI) Where political instability (PI) is independent variable and manufacturing production growth rate (Manf), log of total investment (LInv), total exports growth rate (Exp), inflation rate (Inf), log of external foreign debt (LExtdt) and employment rate (Emp) are the dependent variables, manufacturing production is used as a proxy of domestic output. 5. Sources of the Data All the data is taken from the World Development Indicators 2010, except total investment data is taken from the Government of Pakistan, Pakistan Economic Survey, Various issues and for political instability an index is constructed. The data for all the variables of political instability is self-calculated on the basis of quality data taken from the book, Razi and Shakir (2005) “Pakistan 58 years”; which is based on a research of all leading newspaper news. 6. Construction of Political Instability Index Quantitative studies of the relation between political instability and economic growth have to tackle one major issue that is how to define political instability. Researchers have defined and measured political instability in two ways. One way is to use one or more variables suitable for study i.e. some studies used only one variable as an indicator of political instability. Haan and Siermann (1996), Benhabib and Spiegel (1997) focuses on executive turnover, namely, on the frequency of government collapses as an indicator; Alesina et al. (1992) and Alesina et al. (1996) used an estimated probability of government termination; Guillaumont, Jeanneney and Brun (1999) and Stevens (2000) used Government longevity; Fosu (2002a), Fosu (2002b), Fosu (2004), and Ghura and Mercereau (2004) used coup events and Zureiqat (2005) used Polity II democratization score as an indicator. Some researchers used two or three different variables to define political instability, such as Easterly and Rebelo (1993) used assassinations and war casualties; Barro and Lee (1994) used revolutions, assassinations war casualties; Sala-i-Martin (1997) used revolutions, coups, and war dummy; Ley and Steel (1999) used revolutions, coups, and war dummy; Berthelemy et al. (2002) used occurrence of strikes, demonstrations, violence and coup d’etat; etc. The other way is to use an index of socio-political unrest that summarizes several indicators of more or less violent forms of political protest and social violence such as riots, political prisoners, demonstrations against the government, strikes against government, purges, political motivated killings and assassinations etc. Earlier, Hibbs (1973), Vaniers and Gupta (1986) and Gupta (1990) used Principal Component Method for the construction of Political Instability index, but this method become prominent, when it is used by Alesina and Perotti (1996). Later on by following them some of the researchers also used the
  • 6. International Research Journal of Finance and Economics - Issue 22 (2008) 184 Principal Component Method to construct an aggregate Political Instability index i.e. Perotti (1996), Campos and Nugent (1999a), Gyimah-Brempong and Traynor (1999), Annett (2000), Asteriou and Simon Price (2001) and Ponzio (2005) and Institute of Integrated Development Studies, Katmandu, Nepal (2005). Although, all of them used same technique, but definitely of different indicators as suited them for the study. Political instability in Pakistan normally observed only through democratic or non-democratic government, but in fact, this criterion is failed to describe political stability in Pakistan, There is democracy or not, this is only one factor of political stability. As it is mentioned in earlier that in military regimes Pakistan showed much more good performance in economic indicators than in democratic era. Although, it is believed that it is only due to government longevity, so government longevity is another factor of political stability. Some believe that frequent government changes plays vital role in political instability. So we cannot only justified by one of these phenomenons. For proper measurement of political instability, following the methodology of Alesina and Perotti (1996) but different indicators that can best define the political instability in Pakistan are being used to construct political instability index for Pakistan for the year 1971-2008. The total number of general strikes, demonstrations, riots, government longevity, change of government including coups, war and regime type have all been used as indicators of political instability and thus are used to construct a composite index of political instability. This Political Instability Index is constructed by Principle Component Method by using computer software “Minitab 13 for Windows”. Above-mentioned studies, which used Principal Component technique for constructing index, used only first principal component index for the analysis except Asteriou and Simon Price (2001) (who used all principal component indexes as that study scope was). Therefore, we also use the first principal component index as the index of political instability. 6.1. Definitions of Political Instability Index Variables Although detailed description of variables is given in Appendix D, for general view brief definitions are outlined here. General Strikes General strikes called by political actors for a complete closedown or blockade of economic activities that can last anywhere from a single to several days. Demonstrations It is an assembly of people or procession with an explicit political purpose. Riots It is explained as any violent demonstration or clash of more than 100 citizens involving the use of physical force. Government Longevity Years of Government longevity. Government change An instance of change of government including military coups. War Dummy. Regime Type Democracy, Military led democracy or Military government.
  • 7. 185 International Research Journal of Finance and Economics - Issue 56 (2010) 6.2. Summary of Political Instability Index As earlier mentioned that political instability is measured as the sum of the total numbers of general strikes called by political actors, demonstrations, riots, government longevity, government change including military coups, war and regime type. We consider that these particular above mentioned parameters, rather than any other set of variables, are able to better represent the politically unstable environment of Pakistan. The rational in selecting these particular parameters is that they, not only, are able to capture politically unstable situations but also their possible effect on economic growth in Pakistan. General statistical features of these indicators are given below in table 6.1 and the brief summary of first principal component is given below in table 6.2. Table 6.1: Summary of the Political Instability Indicators S.No. Variables Observations Min Max 1 General Strikes 38 0 69 2 Demonstrations 38 0 31 3 Riots 38 13 258 4 Government Longevity 38 0 10 5 Government change 38 0 1 6 War 38 0 1 7 Regime Type 38 1 3 Source: Self calculation Min: Minimum value of variable in a year Max: Maximum value of variable in a year Table 6.2: Factor Loadings of PC1 Variables PC1 General Strikes 0.511* Demonstrations 0.384** Riots 0.329** Government Longevity -0.326** Government change 0.378** War 0.457* Regime Type -0.158 Note: * Denotes statistical significance at 1% level. ** Denotes statistical significance at 5% level Critical values from Koutsoyiannis (1977) PI = 0.511 E1 + 0.384 E2 + 0.329 E3 – 0.326 E4 + 0.378 E5 + 0.457 E6 – 0.158 E7 Where E1 = General Strikes E2 = Demonstration E3 = Riots E4 = Government Longevity E5 = Government change including coups E6 = War E7 = Regime Type On the basis of above mentioned equation political instability is calculated and standardized as required by the method for unbiased results, then the index is transformed with mean 103 for better results. 3 Institute of Integrated Development Studies, Katmandu, Nepal (2005), the index constructed transformed for better analysis
  • 8. International Research Journal of Finance and Economics - Issue 22 (2008) 186 7. Definitions of all Variables Some of the variables in above-mentioned model are quite clear, but for a clear-cut understanding summary of specification is given below for all of the variables. PI = Political Instability: Measured by political instability index which is self constructed by using seven different variables (General Strikes, Demonstration, Riots, Government longevity, Government change, War and Regime type) by using Principal Component Method for the year 1971-2008. Manf = Manufacturing production: Manufacturing production growth rate. LInv = Log of Investment: Log of Total investment. Exp = Total exports: Annual Growth rate of total exports. Inf = Inflation: Inflation rate. LExtd = Log of total external foreign debt. Emp = Employment rate 8. Estimation and Explanation For observing the effects of political instability on the economic development of Pakistan for the time period of 1971 to 2008, in this section we are going to present results and their explanation All the equations are estimated by the method of OLS and the base year for all observations is same. All the equations and their parameters are already discussed. If autocorrelation is found in an equation, it is re-estimated by Auto regression or Moving average; AR (1) or AR (2) or MA (1) or MA (2). The results of the estimations are reported below. 8.1. Manufacturing Sector and Political Instability • Dependent Variable: Manufacturing Sector Growth Rate • Independent Variable: Political Instability Index In the table 8.1, the results show that the impact of political instability on manufacturing sector is highly significant at 1%, and the relationship is negative which was expected. The found autocorrelation is removed by using AR(1) and MA(1). High political instability reduces the growth in the manufacturing sector. This is well proven fact that the manufacturing sector is directly inter-linked with the government trade policy and if the overall political situation is poor in the country, it will negatively affect the manufacturing organizations too, as it is depicted through our results. 8.2. Investment and Political Instability • Dependent Variable: Log of total Investment • Independent Variable: Political Instability Index In the investment equation, the political instability is negative and significant which shows that the overall investment gets also hampered due to political instability in Pakistan (see table 8.2). The result to this variable is significant at 10 percent level. The autocorrelation is removed through AR(1), AR(2) and MA(1). High political instability adversely affects the overall investment in Pakistan. High political instability puts off the coming investment and also disturbs existed investment; this is, in fact, a long run loss in terms of loosing investors’ confidence for both: existed and expected future investors. Hence, we can say on the basis of our results that stability in the political setup improves investors’ confidence, which ultimately develop investment culture in the country.
  • 9. 187 International Research Journal of Finance and Economics - Issue 56 (2010) Table 8.1: Summary of results for single equations regressions Sample 1971-2008 Manufacturing sector Equation Dependent variable: Manufacturing growth rate Variables Coefficient (t-statistics in parenthesis) Ordinary Least Square Method Intercept 20.86701 (3.946685) Political Instability -1.473978* (-2.758455) AR(1) -0.306533 (-1.279711) MA(1) 0.512507 (1.965698) R2 0.289149 Adjusted R2 0.218064 F-Statistics 4.067640 Sum of squared residual 327.0565 Durbin-Watson stat 1.857588 Inverted AR Roots -.31 Inverted MA Roots -.51 Note: * Denotes statistical significance at 1% level or better. ** Denotes statistical significance at 5% level *** Denotes statistical significance at 10% level 8.3. Export Growth and Political Instability • Dependent Variable: Export Growth Rate • Independent Variable: Political Instability Index On the basis of investment equation results, we can deduce that if investment is hampered due to unstable political setup, the export will also be disturbed due to political instability; because if due to high political instability, there is no good environment for investment how there could be good export growth. So, the results in table 8.3 prove our hypothesis in the export equation that the exports in Pakistan adversely affected due to high political instability. The result is significant at 5% level and there is no autocorrelation found. F-statistics and T-statistics are quite significant in the equation. Table 8.2: Summary of results for single equations regressions Sample 1971-2008 Investment Equation Dependent variable: Log of total Investment Coefficient (t-statistics in parenthesis) Variables Ordinary Least Square Method 15.78419 Intercept (12.38268) -0.025031*** Political Instability (-1.740548) 0.260973 AR(1) (0.967450) 0.674779 AR(2) (2.602460) 0.839183 MA(1) (3.301599) R2 0.996242 Adjusted R2 0.995664 F-Statistics 1723.289 Sum of squared residual 0.163992
  • 10. International Research Journal of Finance and Economics - Issue 22 (2008) 188 Durbin-Watson stat 2.022875 Inverted AR Roots .96 -.70 Inverted MA Roots -.84 Note: * Denotes statistical significance at 1% level or better. ** Denotes statistical significance at 5% level *** Denotes statistical significance at 10% level Table 8.3: Summary of results for single equations regressions Sample 1971-2008 Export growth Equation Dependent variable: Total export growth rate Coefficient (t-statistics in parenthesis) Variables Ordinary Least Square Method 31.93331 Intercept (2.484981) -2.558662** Political Instability (-2.018532) R2 0.109900 Adjusted R2 0.082927 F-Statistics 4.074470 Sum of squared residual 5149.681 Durbin-Watson stat 2.267069 Note: * Denotes statistical significance at 1% level or better. ** Denotes statistical significance at 5% level *** Denotes statistical significance at 10% level 8.4. Inflation and Political Instability •Dependent Variable: Inflation Rate •Independent Variable: Political Instability Index When we find out the impact of political instability on the inflation in Pakistan, our results depict the positive relationship between the two variables; results are shown in table 8.4. When there is high political instability in the country, there will be higher inflation and the results are highly significant. There was autocorrelation found in the results which was removed through AR(1) and AR(2). Fstatistics and T-statistics are also showing complete significance. For the country like Pakistan where inflation remains a constant issue to control over the history, during 90s seven out of ten years, the inflation remains in two digits, that mean more than 10%4, then slow down during 1998 to 2003 and again has increasing trend since then. The 90s was considered as unstable political environment too, due to frequent government changes and bad law and order situation in the country. So, we can say that if there is high instability in the political environment, the overall price level will also increase unexpectedly. 4 Government of Pakistan, Pakistan Economic Survey 2005-06.
  • 11. 189 International Research Journal of Finance and Economics - Issue 56 (2010) Table 8.4: Summary of results for single equations regressions Sample 1971-2008 Inflation Equation Dependent variable: Inflation Rate Variables Coefficient (t-statistics in parenthesis) Ordinary Least Square Method Intercept -10.25975 (-2.628662) Political Instability 1.940467* (5.141241) AR(1) 1.069568 (8.728792) AR(2) -0.618196 (-5.645178) R2 0.711400 Adjusted R2 0.681545 F-Statistics 23.82842 Sum of squared residual 286.0604 Durbin-Watson stat 2.045941 Inverted AR Roots .53+.58i .53-.58i Note: * Denotes statistical significance at 1% level or better. ** Denotes statistical significance at 5% level *** Denotes statistical significance at 10% level 8.5. Foreign Debt and Political Instability • Dependent Variable: Log of Total Foreign Debt • Independent Variable: Political Instability Index In external debt equation, we hypothesize that when there is higher instability in the political environment, there will be higher external debt burden. Our results prove our hypothesis and the political instability is quite positively significant (see table 8.5); which reveals that whenever there is instability in the political setup in the country, the overall debt start increasing more. The result is significant at 5% level. The found autocorrelation is removed through AR(2). T-statistics and F- statistics are at significant level. External foreign debt remains a big burden on the Pakistan economy since 1970s; no serious efforts were made to get rid of foreign loans. In 1998-99, it has reached maximum to 61.48%1 of total GDP of Pakistan. Although, since then, it has a declining trend, but even then it is still very high up to 32.6% of total GDP.
  • 12. International Research Journal of Finance and Economics - Issue 22 (2008) 190 Table 8.5: Summary of results for single equations regressions Sample 1971-2008 Foreign Debt Burden Equation Dependent variable: Log of Total Foreign Debt Coefficient (t-statistics in parenthesis) Variables Ordinary Least Square Method 24.76518 Intercept (87.11755) 0.013747** Political Instability (2.022953) 0.905690 AR(2) (58.71782) R2 0.992414 Adjusted R2 0.991908 F-Statistics 1962.289 Sum of squared residual 0.101145 Durbin-Watson stat 1.540473 Inverted AR Roots .95 -.95 Note: * Denotes statistical significance at 1% level or better. ** Denotes statistical significance at 5% level *** Denotes statistical significance at 10% level 8.6. Employment Growth Rate and Political Instability • Dependent Variable: Employment Growth Rate • Independent Variable: Political Instability Index The employment rate is always a big question in Pakistan’s economy. The economist always would like to find out the root causes of disturbances in employment generation. In the employment growth equation (see table 8.6), political instability is negative, as it was expected. The result is highly significant at 1% level. There was autocorrelation found in the results which was removed through AR(1) and MA(1). In Pakistan, political instability highly disturbs the employment rate. The results significance can be observed by T-statistics and F-statistics. Table 8.6: Summary of results for single equations regressions Sample 1971-2008 Employment Growth Rate Equation Dependent variable: Employment Growth Rate Coefficient (t-statistics in parenthesis) Variables Ordinary Least Square Method -22.07097 Intercept (-1.153483) -0.325529* Political Instability (-2.626680) 1.012564 AR(1) (229.0833) -0.957090 MA(1) (-51.00997) R2 0.990045 Adjusted R2 0.989050 F-Statistics 994.5317 Sum of squared residual 15.11551 Durbin-Watson stat 1.762263 Inverted AR Roots 1.01 Inverted MA Roots 0.96 Note: * Denotes statistical significance at 1% level or better. ** Denotes statistical significance at 5% level *** Denotes statistical significance at 10% level
  • 13. 191 International Research Journal of Finance and Economics - Issue 56 (2010) Conclusion Throughout the analysis, the impact of political instability on the economic development is quite significant and robust. Political instability badly hampers most of the areas of the economy. It is evident from the history that economic growth in Pakistan averages to a good throughout the past that is approximately 5% per annum5. Yet the study has concluded a profound impact of political scene on the economic development of the country that is a bad political situation is found to be a development retarding one and the development pattern is highly volatile in the years of political instability that spans almost over the half history. In fact, the decision makers are political actors, the policies are made, executed but disturbed due to political instability, and most of the policies go in vain due to government change particularly irregular government change. So, if the political scene is made stable then at least the same pace of economic development can sum to the average number very easily and even this contribution may lead to higher levels of economic development. Here the recommendation of the study is to smooth the political scene of the country which broadly can contribute to the present development and average growth rate of the country. The most important for Pakistan is, let any of the political system be flourished; there must not be any discontinuation of it because every thing needs some time to grow up. The most harmful for the development of Pakistan is non-stability of political system, which is actually the centre of decision, so stable the political setup for the long term prosperity of the country. References [1] Alesina, A., Ozler, S., Roubini, N. and Swagel, P. (1992) “Political Instability and Economic Growth” (September), NBER Working Paper # 4173. [2] Alesina, A. and Perotti, R. (1996) “Income Distribution, Political Instability and Investment” European Economic Review, 40, pp.1203-1228. [3] Annett, Anthony (2000) “Social Fractionalization, Political instability and the size of Government”, IMF Working Paper, WP/00/82. [4] Asteriou, D., and Price, S. (2001) “Political Instability and Economic Growth: UK Time Series Evidence”, Scottish Journal of Political Economy (September), Vol.48, No.4, pp.244- 249. [5] Barro, R. J and Lee. J. (1994) “Sources of Economic Growth”, Carnegie Rochester Conference Series on Public Policy. [6] Ben-Habib, Jess, and Mark Spiegel. 1992. “The Role of Human Capital and Political Instability in Economic Development.” Economic Research Report. New York University, C. V. Starr Center for Applied Economics, New York. Processed. [7] Berthelemy, J.C., Kauffmann, C., Renard, L. and Wegner, L. (2002) “Political Instability, Political Regimes and Economic Performance in African Countries”. African EconomicOutlook (March). [8] Campos, N. F, and Karanasos, M. G. (2008) “Growth, volatility and political instability: Nonlinear time-series evidence for Argentina, 1896–2000” Economics Letters, 100, pp.135– 137. [9] Campos, N. F. and Nugent, J. B. (1999a) “Who is Afraid of Political Instability” University of Southern California, Mimeo. [10] Easterly, William, and Sergio Rebelo. (1993) “Fiscal Policy and Growth: An Empirical Investigation.” Journal of Monetary Economics 32, (December), pp.417-58. [11] Feng, Yi. (1997) “Democracy, Political Instability and Economic Growth”, British Journal of Political Science (July), Vol.27, No.3, pp.391-418. [12] Fosu, A. K. (2001) “Political instability and economic growth in developing economies: some specification empirics”, Economics Letters, 70, pp. 289–294. 5 See, for example, Zaidi (2006) “Issues in Pakistan’s Economy” Oxford University Press, Karachi Pakistan.
  • 14. International Research Journal of Finance and Economics - Issue 22 (2008) 192 [13] Fosu, A.K. (2002) “Political instability and economic growth: Implications of coup events in sub-Saharan Africa”, American Journal of Economics and Sociology, (Jan), Vol.61. No.1. [14] Ghura, D. and Mercereau, B. (2004) “Political Instability and Growth: The Central African Republic” IMF Working Paper/04/80, African and Asia and Pacific Department. [15] Government of Pakistan, “Pakistan Economic Survey”, various issues. [16] Guillaumont, P., Jeanneney, S.G, and Brun, J.F. (1999) “How Instability Lowers African Growth”, Journal of African Economies, Vol.8, No.1, pp.87-107. [17] Gupta, D. K. (1990) “The Economics of Political Violence: the Effect of Political Instability on Economic Growth” New York and London: Greenwood Press and Praeger. [18] Gyimah-Brempong, Kwabena and Traynor, Thomas L. (1999) “Political Instability, Investment and Economic Growth in Sub-Saharan Africa”, Journal of African Economies,Vol.8, No.1, pp.52-86. [19] Haan, J. and Siermann, C.L.J. (1996) “Political Instability, Freedom and Economic Growth: Some Further Evidence”, Economic Development and Cultural Change (Jan), Vol.44, No.2, pp.339-350. [20] Haber, S., Razo, A. and Maurer, N. (2000) “Political Instability, Credible Commitments and Economic Growth: Evidence from Revolutionary Mexico” Stanford University. [21] Hibbs, Douglas A. (1973) “Mass Political Violence: A Cross-Sectional Analysis”, New York: Wiley and Sons. [22] Institute of Integrated Development Studies, Katmandu, Nepal (2005) “The Relationship Between Political Instability and Economic Growth in Nepal (1975-2003)” South Asia Network of Economic Research Institutes (SANEI), New Delhi, India. [23] Ley, E. and Steel, M. (1999) “We Have Just Averaged Over Two Trillions Cross Country Growth Regressions” University of Edinburgh, Mimeo. [24] McGowan, P. J. and T. J. Johnson (1984) “African Military Coup d’etat and underdevelopment: A Quantitative Historical Analysis”, Journal of Modern African Studies, vol.22, No. 4, pp.633- 666. [25] Perotti, R. (1996) “Growth, Income Distribution and Democracy: What the Data Say” Journalof Economic Growth, 1, pp.149-187. [26] Razi and Shakir (2005) “Pakistan 58 years- 14 August 1947 to 14 August 2005” Sang-e-Meel Publications Lahore. [27] Sala-i-Martin, Xavier (1997a) “I Just Ran Two Million Regressions” American Economic Review, 87 (2), pp.178-83. [28] Sala-i-Martin, Xavier (1997b) “I Just Ran four Million Regressions” NBER Working Paper No. 4186. [29] Stevens, G. (2000) “Politics, economics and investment: explaining plant and equipment spending by US direct investors in Argentina, Brazil and Mexico” Journal of International Money and Finance, 19, pp.153-183 [30] Vanieris, Yiannis P., and Gupta, D. K. (1986) “Income Distribution and Socio-political Instability as Determinants of Savings; A Cross-Sectional Model”, Journal of Political Economy, Vol.96, pp.873-83. [31] Zaidi, S. Akbar (2006) “Issues in Pakistan’s Economy” Oxford University Press, Karachi Pakistan. [32] Zureiqat, Hazem M. (2005) “Political Instability and Economic Performance: A Panel Data Analysis” Economics Department, Macalester College, Award Winning Economics Papers.