MACROECONOMIC DETERMINANTS OF STOCK MARK
I nt er nat i onal Jour nal of D eci si on Sci ence, 1 ( 2) , July-D ecember 2010, pp. 135 –144
© International Science Press,
ISSN: 2229-5879
MACROECONOMIC DETERMINANTS OF STOCK MARKET
DEVELOPMENT, EVIDENCE OF IRAN
Hadi Akbarzade Khorshidi*, Farimah Mokhatab Rafiei and
Seyed Mehran Hoseini**
*Corresponding Author: Department of Industrial and Systems Engineering,
Isfahan University of Technology, Esteghlal Square, Isfahan 84156-83111, Iran,
E-mail: h.akbarzadekhorshidi@in.iut.ac.ir
**Department of Industrial and Systems Engineering, Isfahan University of
Technology, Esteghlal Square, Isfahan 84156-83111, Iran,
E-mail: farimah@cc.iut.ac.ir, sm.hoseini@in.iut.ac.ir
Abstract: The goal of our study is evaluation and determination of effective factors on stock market
development of Iran. In previous studies, the effectiveness of two groups of factors (macroeconomic and
institutional) has been examined by panel data method. However, in this paper the effect of
macroeconomic factors are analyzed using time series and traditional econometrics (OLS) models.
Income, saving, investment rate, financial intermediary development, stock market liquidity and
macroeconomic instability are important factors that are evaluated. In addition, results of this study
are compared with a similar study that performed on Middle-Eastern and North Africa (MENA)
countries. At the end, some suggestions are proposed to develop the stock market in Iran.
Keywords: Stock market development, Determinants, Macroeconomic factors, Iran, Econometrics.
1. INTRODUCTION
Stock market development is a multi-faceted concept and there are various agents that can
affect on, so identifying the effective indices has an especial importance. Dailami and Atkin
(1990) tried to reveal key factors that can be substantial in developing countries. In investigation
of effective agents on stock market, there are two criterion groups: macroeconomic criteria and
institutional criteria. In macroeconomic approach, some criteria such as income growth, saving
and investment, financial development and inflation are considered. Also in institutional
approach, property laws, clearance and settlement issues, transparency and the inside information
problems, taxation issues and accounting standards are evaluated.
Garcia and Liu (1999) probed effect of macroeconomic factors on stock market development
using data of 13 countries of Latin America and South-East Asia plus USA and Japan. T hey
136
International Journal of Decision Science
showed that real income, saving rate, financial intermediary development and stock market
liquidity are important. Ben naceur et al. (2007) used Garcia and Liu model to assess the effect
of economic factors in 12 countries of Middle-Eastern and North Africa (MENA).
Pagano (1993) showed effect of institutional and regulatory factors on stock markets. La
Porta et al. in duration of their study perceived that rule of law, anti-director rights and oneshare = one-vote are the most effective factors on stock market.
Furthermore Calderon-Rossell in 1990 presented a model for elucidation of stock market
development. In this model, economic growth and stock market liquidity are considered as
main indices. Yartey (2008) extended Calderon-Rossell’s model and examined economical and
institutional factors simultaneously. Macroeconomic criteria that were involved in this model,
are income level, investment and saving, stock market liquidity, macroeconomic stability and
private capital flows. Institutional criteria included political risk, bureaucratic quality, law and
order, corruption and democratic accountability.
In this study, we want to determine effect of each macroeconomic factor on stock market
development in Iran, so we use Garcia and Liu model as a basic model with marginal difference
and apply time series econometric approach on it.
In Section 2, some explanations are brought about Iran’s Stock market, Section 3 describes
relationship between financial and economical development. Determination of econometric
model and definition of variables are lied in Section 4. Section 5 shows and interprets output of
empirical investigation. Conclusion and guidelines for stock market development of Iran are in
Section 6.
2. STOCK MARKET DEVELOPMENT TREND IN IRAN
In recent decades, most of the middle-eastern countries tried to implement the economical
reforms and structural adjustments. Major part of these plans was involved with financial section,
so that many of them were able to establish and resurrect their stock markets. As a result of this
progress, stock exchanges in these countries are considered as an important phenomenon and
their roles increased in international financial system (Ben naceur et al, 2007). T herefore, Iran
was not separated from middle-eastern evolution trend and performed these reforms in its
financial structure. Especially, Iran’s financial structure that it could be observed in middleeastern countries, is Islamic financial market (for more detailed about Islamic financing can
refer to Ramady and Kantarelis, 2009).
Stock exchange market in Tehran (capital of Iran) was established in 1967. Due to the raise
of Gross Domestic Product and its additional worth in industrial section and trading of the
Macroeconomic Determinants of Stock Market Development, Evidence of Iran
137
bond, the volume of transactions in this market increased by a good slope until 1978. Because
of strikes and shutting in manufacturing and commercial units during the Islamic Revolution,
legislating some laws and occurrence the war between Iraq and Iran, exchanges in stock market
were stopped between 1978 and 1983.
In 1984, regarding to government decision on privatization and submission of some factories
to workers, stock exchanges promoted a little. However, statistics show that there is no steady
trend in stock market activities in 1989 – 1997. Tehran’s stock market began a new period of
activities from 1997, so that foundation of many reforms and future evolutions in capital market
was created from this year (Sanginian, 2008).
To show the status of Iranian financial markets, annual time series of some important
indices are brought in diagrams 1, 2, 3, 4 (data of this diagrams extract from Central Bank of
Iran). T hese indices are number of listed companies, market capitalization by GDP, value traded
and turnover ratio.
Diagram 1: Changes Trend of Number of
Listed Companies in Iran
Diagram 2: Changes of Market Capitalization
by GDP Trend in Iran
Diagram 3: Changes of Value Traded
Trend in Iran
Diagram 4: Changes of Turnover Ratio
Trend in Iran
138
International Journal of Decision Science
3. STOCK MARKET DEVELOPMENT AND ECONOMIC GROWTH
T here are many works that implemented on relationships between economy and their factors,
they try to interpret the economic system (Cohen, 2010; Evaghorou, 2010). Financial system
is necessary for an economy because of responsibility for resource allocation. Financial
intermediaries have positive effect on economic growth by decreasing of the cost of information
and transactions, improving of resource allocation, promotion of saving rates and enhancement
of markets and tools development (Levin, 1997; Ben naceur et al., 2007).
Surveys that done based on empirical investigations admitted that there is a positive
relationship between financial development and economic growth. Goldsmith in 1969 for first
time used a panel data approach for 35 countries in 1860 – 1963. Some researchers found that
financial development cause increasing in economic prosperity and reinforcement in growth
trend (King and Levine, 1993; Levine and Zervos, 1998; Rousseau and Sylla, 2001).
Some of other studies discovered that economic growth leads to financial development. In
this view, financial markets uphold by economic expansion (Goldsmith, 1969). However, recent
researches have shown that there is a bi-directional effect between finance and economy, so that
each of them supports together (Shan et al., 2001).
4. RESEARCH MODEL
4.1 Econometric Modeling
T his survey uses time series information of Iran for analysis the model. In previous studies like
this model, due to lack of data, panel data often is employed. Whereas using time series data
has more flexibility because political and social turns that they have effected on statistical data
are not considered in panel data separately (Moinul islam and Salimullah, 2006). T his attitude
helps us to apply an appropriate dummy variable for illustration of Iran’s condition.
Basic model that is used in this essay is like below:
Yt = α + βXt + εt
t = 1, ..., T
... (1)
Where Yt is as a dependent variable, α is constant, Xt is a vector that involved K explanatory
variables, β is a vector of explanatory variable coefficients and εt is error’s amount of each
observation from estimated one.
T here is a test that can check if each coefficient is significant, so that this test performs
under below hypothesis:
H 0 : β = 0
H1 : β ≠ 0
... (2)
For this hypothesis, a t value is prepared that it can be useful by considering to given level
of significance (probability of committing a Type I error). T he null hypothesis rejects and the
coefficient is not significant, if the calculated t value be smaller than equivalent t value of level
Macroeconomic Determinants of Stock Market Development, Evidence of Iran
139
of significance. Also, if amount of P-value be greater than level of significance, the coefficient is
not significant.
An F value is defined to analyze this fact that right hand side variables of Eq. (1) can explain
the left hand side variable. Inability of this estimation will be proven, if its F value be small. In
addition, R2 is a measure to compare regressions in explanation of dependant variable
(Gujarati, 2004).
4.2 Data and Variables
In this study, the financial data of Iran’s market are extracted from Central Bank of Iran.
Furthermore, a M.Sc. thesis that carried out in IUT (Isfahan University of Technology) is
employed for finding economical data (Danesh, 2007). T his dissertation carefully exposed
some Iran’s economical factors.
We use division of Total Market Value on GDP for dependent variable that is proxy of
financial market development. Total Net Capital Stock employs to define the Total Market
Value that this parameter took out from Central Bank’s data. Here, we apply this division
rather than using the combination of the other development indices, because the other indices
have a severe correlation together (Demirguc-Kunt and Levine, 1996).
Principal variables select from Garcia and Liu (1999) but due to better coordination with
and explanation of financial development of Iran, some definitions change and some variables
add to model. Explanatory variables that are used in our model come as below:
Gross domestic product: In this paper, GDP represents the income of country. However, we
use logarithm of GDP for better estimation like Yartey (2008). LogGDP plays more significant
role to explain the stock market development than GDP. We expect that income be an important
factor in our purpose.
Saving and investment: Since financial intermediaries convert saving to investment, it’s
expected that these variables have determined effects. However, due to being severe
multicollinearity between these two variables, they are not brought in model together. Saving
rate and investment rate were taken from a method similar to Ben naceur et al. (2007). T hese
rates are computed as Eqs (3, 4)
Saving rate =
Investment rate =
Gross national saving
Gross national income
Gross national investment
Gross national income
... (3)
... (4)
To avoid from causality problem, we use last year amount of them.
Financial intermediary development: Whereof both bank system and stock market propel
saving to investment, these intermediaries can be substitute or complement. In Modigliani and
140
International Journal of Decision Science
Miller theory (1958) value of securities that are made by company could be autonomous from
their money support resource, if market be perfect with symmetric information. However, in
real world, market is imperfect and information is asymmetric. T herefore, being substitute or
complement depends on laws, incentives or taxation system of countries. Here, domestic credit
to the private sector divided by GDP is used as a proxy of financial intermediary development.
Stock market liquidity: Liquidity defines as a simplicity and velocity in security transactions
that is one of functions of stock markets (Miller, 1991). Also, liquidity gives a capability to
investors for economical and rapid improvement on their financial portfolios (Bencivenga et
al., 1996). In this study, Value traded and Turnover ratio are used for measurement of stock
market liquidity using Eqs (5, 6).
Value traded =
Turnover ratio =
T otal value traded
GDP
Total value traded
Market capitalization
... (5)
... (6)
These two factors are not employed in model simultaneously and last year data are used for them.
Macroeconomic instability: Macroeconomic stability is a positive factor on stock market
development. Much variation in national economic could disappoint investors and firms to
participate in stock market (Garcia and Liu, 1999). Also, stock return has a negative correlation
with inflation rate (Fama, 1981). Floros (2004) used OLS model, Johansen method and GrangerCausuality tests to evaluate relationship between stock return and inflation rate with Greece
data, he indicated that these two items are not correlated. T here are several criteria such as
inflation rate, inflation change and inflation standard deviation, to compute macroeconomic
instability. T herefore, we use last year Consumer Price Index (CPI) change to calculate this
factor. (Iran’s inflation data is not available).
Lagged variable of dependent variable: By reason of better estimation of stock market
development, amount of last year Total Market Value by GDP add to explanatory variables like
Yartey (2008).
Trend variable: Due to increase significance of estimators, this variable insert in model.
Dummy variable: Regarding Iran’s stock market history and Diagram 3, stock market between
1978 and 1983 was inactive. As a result, a dummy variable put in model for covering these
changes so that the value of this variable in 1978 – 1983 is zero and in the other years is one.
5. EMPIRICAL RESULTS
T he model is run by Microfit software in six times by different variables. T he regression statistical
method is used to estimate the coefficients of the model. T he results of these estimations are
displayed in Table 1. For each variable, there are amounts of coefficient, t value and P-value.
Macroeconomic Determinants of Stock Market Development, Evidence of Iran
141
Table 1
Results of Statistical Estimation Amounts in the Parenthesis are t-value and Values
in Bracket are P-value
Estimators
(1)
(2)
(3)
0.670
(3.439)
[0.002]
Lagged variable
Logarithm of GDP
– 2.807
(– 6.479)
[0.000]
– 1.681
(– 3.434)
[0.002]
Saving rate
– 1.109
(– 1.881)
[0.071]
1.312
(1.524)
[0.140]
Investment rate
– 3.418
(– 12.561)
[0.000]
(4)
(5)
(6)
0.272
(2.048)
[0.051]
0.170
(1.145)
[0.282]
0.159
(1.014)
[0.340]
– 2.443 – 2.022 – 1.872
(– 4.519) (– 6.178) (– 4.005)
[0.000] [0.000] [0.004]
2.518
(3.688)
[0.001]
1.586
(2.011)
[0.055]
Financial intermediary development
1.836
(2.754)
[0.011]
2.075
(3.677)
[0.001]
1.878
(3.566)
[0.001]
1.646
(3.228)
[0.003]
Value traded
2.395
(0.627)
[0.536]
1.947
(0.606)
[0.550]
1.913
(0.58)
[0.567]
1.942
(0.623)
[0.538]
Turnover ratio
0.167
(0.644)
[0.535]
0.121
(0.419)
[0.686]
1.003
(3.811)
[0.004]
0.889
(2.431)
[0.041]
0.242
(1.564)
[0.152]
0.242
(1.498)
[0.172]
– 0.0011
(– 0.474)
[0.648]
Macroeconomic instability
Trend variable
Dummy variable
Constant
No. of observation
R
2
F value
0.084
(9.468)
[0.000]
0.027
(1.480)
[0.151]
0.096
(13.828)
[0.000]
0.064
(3.847)
[0.001]
0.071
(6.153)
[0.000]
0.068
(5.273)
[0.001]
– 0.341
(– 2.779)
[0.010]
– 0.087
(– 0.689)
[0.497]
– 0.46
(– 4.234)
[0.000]
– 0.301
(– 2.344)
[0.027]
37.126
(7.426)
[0.000]
20.539
(3.211)
[0.004]
43.326
(13.431)
[0.000]
31040
(4.615)
[0.000]
26.314
(6.653)
[0.000]
24.583
(4.454)
[0.002]
33
0.875
30.426
33
0.915
38.633
33
0.907
42.273
33
0.920
41.289
16
0.891
12.290
16
0.894
9.659
142
International Journal of Decision Science
Column (1) shows that income, saving rate and financial intermediary development have
significant effect on stock market development, but value traded is insignificance. It should be
mentioned that income and saving rate have negative sign. In column (2) lagged variable add
to the model for evaluation of its effect. As it can obtain from table, only significance of saving
rate reduces so that it’s not significant at 10 percent level. However, the other variables improve,
especially the coefficient of saving rate becomes positive. As a result of these observations,
lagged variable has a good effect on model. Although these improvements occurred, coefficient
of income is negative yet. T his event may be interpreted in this way that by income growing
money and capital push to other sections such as trading, purchasing real estate, etc. in Iran.
Also, stock markets in Iran are small. It must be cited that in study that performed by Ben
naceur et al for MENA countries, income had an insignificant outcome.
Saving rate and financial intermediary development have positive and significant effect
that these effects are according to Ben naceur et al. However, value traded is insignificant
whereas this criterion for MENA countries had significant positive coefficient.
Investment rate enters to model in third column. Coefficient of this factor is positive and
significant but this factor in MENA was negative insignificantly. Column (4) has a lagged
variable more than column (3) that this variable has the same before influences.
In column (5), turnover ratio substitutes with value traded. T his criterion has not significance
effect on stock market development. In general, estimation that created in column (5) is weaker
than column (2). Despite this observation, turnover ratio in compare to value traded is more
significant. It must be mentioned that data for turnover ratio is available for 1991 – 2007, so
this column doesn’t need to participate the dummy variable.
Column (6) evaluates effect of instability using last year CPI change. As we expected the
coefficient of this factor is negative but it’s not significant that these results are in accordance
with MENA countries.
6. CONCLUSION
We have utilized Garcia and Liu model to analyze the effect of macroeconomic factors on Iran’s
stock market development. For adaptation the model with Iran’s data, lagged, trend and dummy
variables are inserted to the model so that these variables enhance the impact of the estimation
equation. To sum up, income factor has negative coefficient and remains having inappropriate
effect on stock market. Saving and investment rates are positive and significant but investment
rate is more significant according to columns 1 to 4 of Table 1. Financial intermediary
development is positively effective. Although, they are positive, none of the liquidity criteria is
significant. Also, the macroeconomic instability is an insignificant negative factor.
Regarding to these results, there are some approaches that may be supposed for stock market
growth of Iran. First of all, a proper structure should be made to push national income to stock
Macroeconomic Determinants of Stock Market Development, Evidence of Iran
143
market. Second, due to promotion of investment rate, the investment share of national income
must be increased. At the end, along with the effect of financial intermediaries, privatization is
an accurate policy to expansion.
For the further research, it could be a good suggestion to determine the causality between
stock market development and economic growth in Iran. In addition, the relationship between
financial intermediaries and stock markets may be evaluated in Iran. If they are complements
or substitutes in growth process.
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© International Science Press,
ISSN: 2229-5879
MACROECONOMIC DETERMINANTS OF STOCK MARKET
DEVELOPMENT, EVIDENCE OF IRAN
Hadi Akbarzade Khorshidi*, Farimah Mokhatab Rafiei and
Seyed Mehran Hoseini**
*Corresponding Author: Department of Industrial and Systems Engineering,
Isfahan University of Technology, Esteghlal Square, Isfahan 84156-83111, Iran,
E-mail: h.akbarzadekhorshidi@in.iut.ac.ir
**Department of Industrial and Systems Engineering, Isfahan University of
Technology, Esteghlal Square, Isfahan 84156-83111, Iran,
E-mail: farimah@cc.iut.ac.ir, sm.hoseini@in.iut.ac.ir
Abstract: The goal of our study is evaluation and determination of effective factors on stock market
development of Iran. In previous studies, the effectiveness of two groups of factors (macroeconomic and
institutional) has been examined by panel data method. However, in this paper the effect of
macroeconomic factors are analyzed using time series and traditional econometrics (OLS) models.
Income, saving, investment rate, financial intermediary development, stock market liquidity and
macroeconomic instability are important factors that are evaluated. In addition, results of this study
are compared with a similar study that performed on Middle-Eastern and North Africa (MENA)
countries. At the end, some suggestions are proposed to develop the stock market in Iran.
Keywords: Stock market development, Determinants, Macroeconomic factors, Iran, Econometrics.
1. INTRODUCTION
Stock market development is a multi-faceted concept and there are various agents that can
affect on, so identifying the effective indices has an especial importance. Dailami and Atkin
(1990) tried to reveal key factors that can be substantial in developing countries. In investigation
of effective agents on stock market, there are two criterion groups: macroeconomic criteria and
institutional criteria. In macroeconomic approach, some criteria such as income growth, saving
and investment, financial development and inflation are considered. Also in institutional
approach, property laws, clearance and settlement issues, transparency and the inside information
problems, taxation issues and accounting standards are evaluated.
Garcia and Liu (1999) probed effect of macroeconomic factors on stock market development
using data of 13 countries of Latin America and South-East Asia plus USA and Japan. T hey
136
International Journal of Decision Science
showed that real income, saving rate, financial intermediary development and stock market
liquidity are important. Ben naceur et al. (2007) used Garcia and Liu model to assess the effect
of economic factors in 12 countries of Middle-Eastern and North Africa (MENA).
Pagano (1993) showed effect of institutional and regulatory factors on stock markets. La
Porta et al. in duration of their study perceived that rule of law, anti-director rights and oneshare = one-vote are the most effective factors on stock market.
Furthermore Calderon-Rossell in 1990 presented a model for elucidation of stock market
development. In this model, economic growth and stock market liquidity are considered as
main indices. Yartey (2008) extended Calderon-Rossell’s model and examined economical and
institutional factors simultaneously. Macroeconomic criteria that were involved in this model,
are income level, investment and saving, stock market liquidity, macroeconomic stability and
private capital flows. Institutional criteria included political risk, bureaucratic quality, law and
order, corruption and democratic accountability.
In this study, we want to determine effect of each macroeconomic factor on stock market
development in Iran, so we use Garcia and Liu model as a basic model with marginal difference
and apply time series econometric approach on it.
In Section 2, some explanations are brought about Iran’s Stock market, Section 3 describes
relationship between financial and economical development. Determination of econometric
model and definition of variables are lied in Section 4. Section 5 shows and interprets output of
empirical investigation. Conclusion and guidelines for stock market development of Iran are in
Section 6.
2. STOCK MARKET DEVELOPMENT TREND IN IRAN
In recent decades, most of the middle-eastern countries tried to implement the economical
reforms and structural adjustments. Major part of these plans was involved with financial section,
so that many of them were able to establish and resurrect their stock markets. As a result of this
progress, stock exchanges in these countries are considered as an important phenomenon and
their roles increased in international financial system (Ben naceur et al, 2007). T herefore, Iran
was not separated from middle-eastern evolution trend and performed these reforms in its
financial structure. Especially, Iran’s financial structure that it could be observed in middleeastern countries, is Islamic financial market (for more detailed about Islamic financing can
refer to Ramady and Kantarelis, 2009).
Stock exchange market in Tehran (capital of Iran) was established in 1967. Due to the raise
of Gross Domestic Product and its additional worth in industrial section and trading of the
Macroeconomic Determinants of Stock Market Development, Evidence of Iran
137
bond, the volume of transactions in this market increased by a good slope until 1978. Because
of strikes and shutting in manufacturing and commercial units during the Islamic Revolution,
legislating some laws and occurrence the war between Iraq and Iran, exchanges in stock market
were stopped between 1978 and 1983.
In 1984, regarding to government decision on privatization and submission of some factories
to workers, stock exchanges promoted a little. However, statistics show that there is no steady
trend in stock market activities in 1989 – 1997. Tehran’s stock market began a new period of
activities from 1997, so that foundation of many reforms and future evolutions in capital market
was created from this year (Sanginian, 2008).
To show the status of Iranian financial markets, annual time series of some important
indices are brought in diagrams 1, 2, 3, 4 (data of this diagrams extract from Central Bank of
Iran). T hese indices are number of listed companies, market capitalization by GDP, value traded
and turnover ratio.
Diagram 1: Changes Trend of Number of
Listed Companies in Iran
Diagram 2: Changes of Market Capitalization
by GDP Trend in Iran
Diagram 3: Changes of Value Traded
Trend in Iran
Diagram 4: Changes of Turnover Ratio
Trend in Iran
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3. STOCK MARKET DEVELOPMENT AND ECONOMIC GROWTH
T here are many works that implemented on relationships between economy and their factors,
they try to interpret the economic system (Cohen, 2010; Evaghorou, 2010). Financial system
is necessary for an economy because of responsibility for resource allocation. Financial
intermediaries have positive effect on economic growth by decreasing of the cost of information
and transactions, improving of resource allocation, promotion of saving rates and enhancement
of markets and tools development (Levin, 1997; Ben naceur et al., 2007).
Surveys that done based on empirical investigations admitted that there is a positive
relationship between financial development and economic growth. Goldsmith in 1969 for first
time used a panel data approach for 35 countries in 1860 – 1963. Some researchers found that
financial development cause increasing in economic prosperity and reinforcement in growth
trend (King and Levine, 1993; Levine and Zervos, 1998; Rousseau and Sylla, 2001).
Some of other studies discovered that economic growth leads to financial development. In
this view, financial markets uphold by economic expansion (Goldsmith, 1969). However, recent
researches have shown that there is a bi-directional effect between finance and economy, so that
each of them supports together (Shan et al., 2001).
4. RESEARCH MODEL
4.1 Econometric Modeling
T his survey uses time series information of Iran for analysis the model. In previous studies like
this model, due to lack of data, panel data often is employed. Whereas using time series data
has more flexibility because political and social turns that they have effected on statistical data
are not considered in panel data separately (Moinul islam and Salimullah, 2006). T his attitude
helps us to apply an appropriate dummy variable for illustration of Iran’s condition.
Basic model that is used in this essay is like below:
Yt = α + βXt + εt
t = 1, ..., T
... (1)
Where Yt is as a dependent variable, α is constant, Xt is a vector that involved K explanatory
variables, β is a vector of explanatory variable coefficients and εt is error’s amount of each
observation from estimated one.
T here is a test that can check if each coefficient is significant, so that this test performs
under below hypothesis:
H 0 : β = 0
H1 : β ≠ 0
... (2)
For this hypothesis, a t value is prepared that it can be useful by considering to given level
of significance (probability of committing a Type I error). T he null hypothesis rejects and the
coefficient is not significant, if the calculated t value be smaller than equivalent t value of level
Macroeconomic Determinants of Stock Market Development, Evidence of Iran
139
of significance. Also, if amount of P-value be greater than level of significance, the coefficient is
not significant.
An F value is defined to analyze this fact that right hand side variables of Eq. (1) can explain
the left hand side variable. Inability of this estimation will be proven, if its F value be small. In
addition, R2 is a measure to compare regressions in explanation of dependant variable
(Gujarati, 2004).
4.2 Data and Variables
In this study, the financial data of Iran’s market are extracted from Central Bank of Iran.
Furthermore, a M.Sc. thesis that carried out in IUT (Isfahan University of Technology) is
employed for finding economical data (Danesh, 2007). T his dissertation carefully exposed
some Iran’s economical factors.
We use division of Total Market Value on GDP for dependent variable that is proxy of
financial market development. Total Net Capital Stock employs to define the Total Market
Value that this parameter took out from Central Bank’s data. Here, we apply this division
rather than using the combination of the other development indices, because the other indices
have a severe correlation together (Demirguc-Kunt and Levine, 1996).
Principal variables select from Garcia and Liu (1999) but due to better coordination with
and explanation of financial development of Iran, some definitions change and some variables
add to model. Explanatory variables that are used in our model come as below:
Gross domestic product: In this paper, GDP represents the income of country. However, we
use logarithm of GDP for better estimation like Yartey (2008). LogGDP plays more significant
role to explain the stock market development than GDP. We expect that income be an important
factor in our purpose.
Saving and investment: Since financial intermediaries convert saving to investment, it’s
expected that these variables have determined effects. However, due to being severe
multicollinearity between these two variables, they are not brought in model together. Saving
rate and investment rate were taken from a method similar to Ben naceur et al. (2007). T hese
rates are computed as Eqs (3, 4)
Saving rate =
Investment rate =
Gross national saving
Gross national income
Gross national investment
Gross national income
... (3)
... (4)
To avoid from causality problem, we use last year amount of them.
Financial intermediary development: Whereof both bank system and stock market propel
saving to investment, these intermediaries can be substitute or complement. In Modigliani and
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International Journal of Decision Science
Miller theory (1958) value of securities that are made by company could be autonomous from
their money support resource, if market be perfect with symmetric information. However, in
real world, market is imperfect and information is asymmetric. T herefore, being substitute or
complement depends on laws, incentives or taxation system of countries. Here, domestic credit
to the private sector divided by GDP is used as a proxy of financial intermediary development.
Stock market liquidity: Liquidity defines as a simplicity and velocity in security transactions
that is one of functions of stock markets (Miller, 1991). Also, liquidity gives a capability to
investors for economical and rapid improvement on their financial portfolios (Bencivenga et
al., 1996). In this study, Value traded and Turnover ratio are used for measurement of stock
market liquidity using Eqs (5, 6).
Value traded =
Turnover ratio =
T otal value traded
GDP
Total value traded
Market capitalization
... (5)
... (6)
These two factors are not employed in model simultaneously and last year data are used for them.
Macroeconomic instability: Macroeconomic stability is a positive factor on stock market
development. Much variation in national economic could disappoint investors and firms to
participate in stock market (Garcia and Liu, 1999). Also, stock return has a negative correlation
with inflation rate (Fama, 1981). Floros (2004) used OLS model, Johansen method and GrangerCausuality tests to evaluate relationship between stock return and inflation rate with Greece
data, he indicated that these two items are not correlated. T here are several criteria such as
inflation rate, inflation change and inflation standard deviation, to compute macroeconomic
instability. T herefore, we use last year Consumer Price Index (CPI) change to calculate this
factor. (Iran’s inflation data is not available).
Lagged variable of dependent variable: By reason of better estimation of stock market
development, amount of last year Total Market Value by GDP add to explanatory variables like
Yartey (2008).
Trend variable: Due to increase significance of estimators, this variable insert in model.
Dummy variable: Regarding Iran’s stock market history and Diagram 3, stock market between
1978 and 1983 was inactive. As a result, a dummy variable put in model for covering these
changes so that the value of this variable in 1978 – 1983 is zero and in the other years is one.
5. EMPIRICAL RESULTS
T he model is run by Microfit software in six times by different variables. T he regression statistical
method is used to estimate the coefficients of the model. T he results of these estimations are
displayed in Table 1. For each variable, there are amounts of coefficient, t value and P-value.
Macroeconomic Determinants of Stock Market Development, Evidence of Iran
141
Table 1
Results of Statistical Estimation Amounts in the Parenthesis are t-value and Values
in Bracket are P-value
Estimators
(1)
(2)
(3)
0.670
(3.439)
[0.002]
Lagged variable
Logarithm of GDP
– 2.807
(– 6.479)
[0.000]
– 1.681
(– 3.434)
[0.002]
Saving rate
– 1.109
(– 1.881)
[0.071]
1.312
(1.524)
[0.140]
Investment rate
– 3.418
(– 12.561)
[0.000]
(4)
(5)
(6)
0.272
(2.048)
[0.051]
0.170
(1.145)
[0.282]
0.159
(1.014)
[0.340]
– 2.443 – 2.022 – 1.872
(– 4.519) (– 6.178) (– 4.005)
[0.000] [0.000] [0.004]
2.518
(3.688)
[0.001]
1.586
(2.011)
[0.055]
Financial intermediary development
1.836
(2.754)
[0.011]
2.075
(3.677)
[0.001]
1.878
(3.566)
[0.001]
1.646
(3.228)
[0.003]
Value traded
2.395
(0.627)
[0.536]
1.947
(0.606)
[0.550]
1.913
(0.58)
[0.567]
1.942
(0.623)
[0.538]
Turnover ratio
0.167
(0.644)
[0.535]
0.121
(0.419)
[0.686]
1.003
(3.811)
[0.004]
0.889
(2.431)
[0.041]
0.242
(1.564)
[0.152]
0.242
(1.498)
[0.172]
– 0.0011
(– 0.474)
[0.648]
Macroeconomic instability
Trend variable
Dummy variable
Constant
No. of observation
R
2
F value
0.084
(9.468)
[0.000]
0.027
(1.480)
[0.151]
0.096
(13.828)
[0.000]
0.064
(3.847)
[0.001]
0.071
(6.153)
[0.000]
0.068
(5.273)
[0.001]
– 0.341
(– 2.779)
[0.010]
– 0.087
(– 0.689)
[0.497]
– 0.46
(– 4.234)
[0.000]
– 0.301
(– 2.344)
[0.027]
37.126
(7.426)
[0.000]
20.539
(3.211)
[0.004]
43.326
(13.431)
[0.000]
31040
(4.615)
[0.000]
26.314
(6.653)
[0.000]
24.583
(4.454)
[0.002]
33
0.875
30.426
33
0.915
38.633
33
0.907
42.273
33
0.920
41.289
16
0.891
12.290
16
0.894
9.659
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International Journal of Decision Science
Column (1) shows that income, saving rate and financial intermediary development have
significant effect on stock market development, but value traded is insignificance. It should be
mentioned that income and saving rate have negative sign. In column (2) lagged variable add
to the model for evaluation of its effect. As it can obtain from table, only significance of saving
rate reduces so that it’s not significant at 10 percent level. However, the other variables improve,
especially the coefficient of saving rate becomes positive. As a result of these observations,
lagged variable has a good effect on model. Although these improvements occurred, coefficient
of income is negative yet. T his event may be interpreted in this way that by income growing
money and capital push to other sections such as trading, purchasing real estate, etc. in Iran.
Also, stock markets in Iran are small. It must be cited that in study that performed by Ben
naceur et al for MENA countries, income had an insignificant outcome.
Saving rate and financial intermediary development have positive and significant effect
that these effects are according to Ben naceur et al. However, value traded is insignificant
whereas this criterion for MENA countries had significant positive coefficient.
Investment rate enters to model in third column. Coefficient of this factor is positive and
significant but this factor in MENA was negative insignificantly. Column (4) has a lagged
variable more than column (3) that this variable has the same before influences.
In column (5), turnover ratio substitutes with value traded. T his criterion has not significance
effect on stock market development. In general, estimation that created in column (5) is weaker
than column (2). Despite this observation, turnover ratio in compare to value traded is more
significant. It must be mentioned that data for turnover ratio is available for 1991 – 2007, so
this column doesn’t need to participate the dummy variable.
Column (6) evaluates effect of instability using last year CPI change. As we expected the
coefficient of this factor is negative but it’s not significant that these results are in accordance
with MENA countries.
6. CONCLUSION
We have utilized Garcia and Liu model to analyze the effect of macroeconomic factors on Iran’s
stock market development. For adaptation the model with Iran’s data, lagged, trend and dummy
variables are inserted to the model so that these variables enhance the impact of the estimation
equation. To sum up, income factor has negative coefficient and remains having inappropriate
effect on stock market. Saving and investment rates are positive and significant but investment
rate is more significant according to columns 1 to 4 of Table 1. Financial intermediary
development is positively effective. Although, they are positive, none of the liquidity criteria is
significant. Also, the macroeconomic instability is an insignificant negative factor.
Regarding to these results, there are some approaches that may be supposed for stock market
growth of Iran. First of all, a proper structure should be made to push national income to stock
Macroeconomic Determinants of Stock Market Development, Evidence of Iran
143
market. Second, due to promotion of investment rate, the investment share of national income
must be increased. At the end, along with the effect of financial intermediaries, privatization is
an accurate policy to expansion.
For the further research, it could be a good suggestion to determine the causality between
stock market development and economic growth in Iran. In addition, the relationship between
financial intermediaries and stock markets may be evaluated in Iran. If they are complements
or substitutes in growth process.
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