Trading Partners and Iranian Manufactured Exports
Sedigheh Atrkar Roshan
This study is devoted to examine the performance of
Iranian Manufactured exports in terms of their destination over the 1980-2006
period. Using time series techniques, an export demand model is applied
and the income and price elasticities of demand for Iranian manufactured
exports by country of destination are estimated. As after 1979, Iranian
trading partners were diversified in the direction of more inter-LDCs.
The applied export demand model is then simulated by the Newton technique.
As it is assumed that trade flows respond to changes in relative prices
and exchange rate, the magnitude of the response will then be investigated
through a historical simulation. The empirical results demonstrate that
trading partner`s income, real effective exchange rate along with commodity
price do affect the Irans manufactured export demand. The findings of
the historical simulation also suggest that, the size of changes in the
endogenous variables is relatively smaller under the first Scenario, whereas
the second policy Scenario causes exports to rise significantly. The estimation
outcomes also emphasize the sensitivity of exports to a devaluation of
domestic currency especially to LDCs.
A basic issue in applied economics is the role of exports in the process
of growth. From a demand-side perspective, it is argued that sustained
demand growth cannot be maintained in small domestic markets, since any
economic impulse based on the expansion of domestic demand is bound to
be exhausted quickly. Export markets, in contrast, are almost limitless
and hence do not involve growth restrictions on the demand side. Hence,
exports can be a catalyst for income growth, as a component of aggregate
demand (Agosin, 1999). However, the role in the literature is distinguished
between the manufactured and primary export categories when referring
to their impact on the countrys economic performance. As according to
the Prebish-Singer thesis, export diversification from primary into manufactures
may be useful if there is a general trend toward declining terms of trade
for primary products (Athukorola, 2000). Besides, primary exports are
subject to extreme price and volume fluctuations (Dawe, 1996). Furthermore,
primary products tend to offer no sustainable potential for knowledge
spillovers and an increase in primary exports can draw resources away
from the externality-generating manufacturing sector (Herzer and Nowak-Lehman,
2006; Siliverstovs and Herzer, 2007).
In this respect, the estimation of income and price elasticities of exports
(and also imports) has been a traditional area of research in international
economics. It attracted substantial amount of literature, because of its
implications for trade policy and balance of payment questions. The trend
toward disaggregating trade elasticity measures into their component parts
has accelerated over the last three decades. However; there is some debate
in the growth-openness studies as to what extent trade with LDCs or DCs
is beneficial for growth. The main argument is that, LDCs benefit from
the large knowledge stock of their more developed trading partners.
As it has been pointed out in the literature, a countrys economic growth
is positively influenced by growth in its trading partners (although a
number of economists are skeptical about it). This occurs through the
impact of innovation and technological spillovers from trading partner
countries (Grossman and Helpman, 1989; Rivera-Batiz and Romer, 1991).
In addition faster growth in partner countries can contribute to a larger
market for a countrys exports, leading in the short run to an increase
in the utilization of available resources and in the longer run to an
increase in investment in the exported goods sectors to satisfy higher
future demand (Vamvakidis, 2002). Similarly, this could further produce
incentives for local research and development. Trade especially with DCs,
expand the number of possible buyers and thus, the potential for economic
profits associated with innovation, brand recognition, patent registrations
and any improvements over competing firms products. In addition this will
force the producer to react to a new environment and innovate in the process.
These innovations might take the form of necessary adjustments to packaging
and transportation methods due to local climates and infrastructure, product
adjustments made to entice consumers with different tastes, innovations
in the production process that comply with foreign sanitary regulations,
etc. (Kali et al., 2007).
Recent empirical researches have also found that the economic conditions
in the trading partners of a country have important implications for domestic
growth. This issue which has less been explored in growth-openness literature,
attracted more attention in recent years. Clemens and Williamson (2004)
included growth of trading partners in their study, covering the 1869-1999
years for 35 countries. Their estimate turned to be insignificant in both
economic and statistical terms. The focus of the work by Arora and Vamvakidis
(2005) is how much economic condition in trading partners matter for growth.
Their results suggest that a countrys growth is positively associated
with the growth rate and relative income of its trading partners. Additionally,
a country`s productivity growth is shown to depend not only on its domestic
R&D investment but also on the R&D investment of its trading partners.
Trade expansion induced by greater market access appears to cause a quantitatively
large acceleration in the growth rates of developing countries (Evenson
and Singh, 1998; Romalis, 2007). Similarly, the effects of having a greater
number of rich trading partners could be different from those of having
a greater number of poor trading partners (see Schneider, 2005, for an
empirical analysis of a similar argument).
To date the vast majority of the researches on the estimation of income
and price elasticities in international trade have been directed toward
relatively advanced economies such as the Japan or the United States.
Since a limited number of studies aimed at developing countries, especially
on the issue of the role of trading partners in domestic growth, a country
case study approach focusing on Iran is intended in this study. In view
of the considerable growth of Irans manufactured exports over the last
three decades, the dramatic changes in her trading partners which occurred
after 1979 revolution could possess implications for the economic growth
of the country. The purpose of this study is to estimate elasticities
of Iranian manufactured exports in terms of her trading partners, i.e.,
individual countries, as well as in terms of group of countries. The reason
for selecting this category of exports is based on empirical findings
of Atrkar Roshan (2007), in which Iran`s industrial goods was found to
have relatively higher price and income elasticity compared to other export
categories. Taking into account of the estimation results of this section,
it is then intended to simulate parameter estimates identified from the
export demand model to show the response of the model to changes in policy
variables, arising from a shock to key variables. The purposes
is firstly, to test the reliability of the export demand model for predicting
the changes of the dependent variables and secondly, to quantify the fluctuations
in exogenous policy variables.
THE MODEL AND DATA
From an econometric point of view, the elasticity approach which is one
of the most successful areas of empirical economics is based on estimating
the export (and import) demand functions. To investigate the effects of
a real devaluation on the trade balance of a country, the ‘elasticity
is also an appropriate approach. In most studies, export/import volumes
are regressed on world/domestic real income, relative export/import price
and effective exchange rates. The underlying framework is the imperfect
substitutes model of the trade literature, as it was discussed in Goldstein
and Khan (1985) in detail. They argued that, if domestic and foreign goods
were perfect substitutes, then we should observe either of the goods having
market share of unity and each country acts as an importer or exporter
of a traded goods but not both.
Equations relating trade flows to relative prices and importer income
have been derived and estimated since the 1950s, with generally good statistical
fit and sensible economic interpretation. The basic structure and theoretical
motivation of export demand equations are covered in Goldstein and Khan
(1985) who provide a thorough review of published empirical findings;
whilst Hooper et al. (1998) and Marquez (2002) present updated
estimates and discuss recent methodological advances (see also Atrkar
Roshan, 2007, for a review of literature).
In order to assess the effects of exchange rate on export flows, following
a number of economists e.g., Bahmani-Oskooee (1986), an exchange rate
variable is added in log-linear form. Since each variable is defined in
logarithmic terms, the estimated coefficients are the elasticities of
exports with respect to the corresponding variables. Thus, following Bahmani-Oskooee
(1986), the model is specified in log-linear terms as:
where, X is the quantity of Irans manufactured exports in terms of each trading
partner, YW is the weighted average of real GNP of the country`s trading partners,
PX is the unit value of Iranian manufactured exports, PXW is the unit value
of competitors exports and E is the real effective exchange rate. The model
dominated the empirical literature for more than a quarter century, because
of the empirical success of this specification and the data limitations prevailing
in LDCs. It is worth noting that, various previous studies use a static framework.
The use of static models in trade econometrics is consistent with the formulation
of Marshall-Lerner stability condition, which did not involve any dynamics.
In this study, the time series technique is applied, since evidence of
significant parametric variations across countries suggest that aggregate
cross country analyses may be highly misleading. The Iranian annual data
from 1980 to 2006 is employed and all the data are in constant 1990 prices.
The data for Iran`s real effective exchange rate and figures for the income
of trading partners were obtained from the IMF, International Financial
Statistics (various issues). The export weights that is, the share of
each trading partner in the countrys total exports for which a time series
is constructed using data from the Iranian Foreign Trade Statistics and
CBI (Central Bank of Iran) Economic Report and Balance Sheet. Unlike a
number of studies which used the average share of trading partner for
5 years, the share of Irans trading partner has been used for 20 years
in this study. This is because, trading partners were more often changed
and the set of the most important partners remained relatively unstable
after 1980 in the case of Iran.
On the basis of Eq. 1, manufactured export demand is
estimated in terms of trading partners, namely Germany and Italy as the
two most important destinations of Iranian manufactured exports amongst
developed countries (which is named Eq. 1.1 and 1.2 in Table
3). The external demand is also estimated for the same export category
in terms of United Arab Emirates, (herein UAE) and Turkey (namely Eq.
1.3 and 1.4, respectively), as the two significant destinations of Irans
trading partners amongst developing countries. This is followed by the
estimation of demand for manufactured exports to developed and less developed
countries (herein DCs and LDCs, respectively) that is called Eq. 1.5 and
1.6 in Table 2 and 3.
The period under consideration in this research contains a range of different
episodes for Iran; such as a sharp collapse of oil price during 1986-1988
and 1997, the commencement of the Iraqi invasion to Iran in 1980 and also
the trade embargos in 1982, 1987 and 1996. In order to capture the data
break and examine the effects of these sudden changes on dependent variables,
three dummy variables are constructed and introduced in the model, which
takes the value of 1 for the specified period and zero otherwise. D1:
for the collapse of the oil price, resulting in a sharp reduction from
1986 to 1988 and also 1997 years. D2: for the trade embargo imposed by
the US, European countries and Japan in 1982 and by the US government
(alone) in 1987 and 1996 years. D3: for the aftermath of revolution and
the first year of the Iraqi invasion to Iran in 1980. Finally, the estimation
is carried out by Ordinary Least-Squares (OLS) method.
TESTING FOR UNIT ROOTS IN THE DATA
Primarily, the stationarity of the series is tested by using the Augmented
Dickey-Fuller (ADF) test procedure. Tests are performed both in level
and first difference forms. The ADF test statistics which are presented
in Table 1 suggest that the unit root null can not be
rejected at 5% significance level for all the variables in the analysis.
In contrast to level forms, the unit root null is strongly rejected at
5% significance for the first difference forms. In other words, all variables
appear to be integrated of order 1.
The next step is to test for cointegration that is applied in the sense
of Engle and Grange (1987), which tells us whether the long-run behavior
of export demand is adequately specified.
||Augmented Dickey-Fuller (ADF) test results
Variables are defined as follow: the volume of real
manufactured exports to Germany, Italy, UAE, Turkey, DCs an LDCs are
LGX, LIX, LUX, LTX, LXDCs and LXLDCs, respectively. The real GDP for
Germany Italy, UAE, Turkey, DCs an LDCs are shown as LGI, LII, LUI,
LTI, LIDCs and LILDCs). Real effective exchange rate (LE) and relative
price of manufactured exports LM. Critical values are based on Mackinnon
(1991). Sufficient lags were included to eliminate serial correlation,
*, **Significant at 1, 5 and % level, respectively
Table 2 reports
the residual-based Critical values are based on Engle and Yoo (1987).
Sufficient lags were included to eliminate serial correlation *, **Significant
at 1, 5 and % level, respectively ADF test results for cointegration.
The simulated critical values reported in Engle and Yoo (1987) is used,
which also takes into account the number of variables for the Z(tα)statistic
at a 1, 5 and 10% significance level (Table 2). As regards
involved equations, results appear to support stationarity of residuals
most at 1 and 5% level of significance and it can be concluded that the
relevant variables are cointegrated.
RESULTS AND DISCUSSION
After estimating the equations, the results of diagnostic tests make
strength the validity of the empirical findings. The Lagrange Multiplier
(LM) test denotes that the computed χ2 is smaller than
the critical value at the 5% level of significance. Ramsey RESET test
indicates that there is no misspecification in the equations. The result
which is reported below the Table 3 also demonstrate
that, normality was achieved in all cases.
The empirical findings provide further evidence among the literature
that with expected coefficient signs, all three variables including trading
partner`s income, real effective exchange rate along with commodity price
do affect the export demand. The findings reported in Table
3 also demonstrate that, the income elasticities are larger than one
in all equations. This indicates that, trading partners income positively
affects Iranian export demand. Consequently, growth in Irans partner countries
will translate into growth at least at the same magnitude of the exports
and trade can be used as an important factor for the economic growth of
the country. However, a key outcome is the difference in the size of the
income elasticity for the estimated equations, which is higher for DCs.
These results are in line with the findings of Arora and Vamvakidis (2005),
who concluded that developing countries benefit from trading with manufactured
countries, which have higher relative incomes. Similarly, the Kali et
al. (2007) results present evidence supporting the argument that trade
relations established with rich countries are more beneficial for growth
than those established with poor countries.
In line with literature, the estimation results demonstrate that, relative
prices and real effective exchange rate with expected signs are two significant
determinants of the demand for exports. However, while relative prices
have a predictable and systematic impact on trade, price elasticities
tend to be low, in fact, they are well below unity. Not surprisingly,
the estimation in terms of group of countries confirm what the country
specific results showed, namely, that relative prices and real exchange
rate play a significant role in affecting export flows. Accordingly, the
developing countries demand for manufactured exports respond to relative
prices and exchange rate as predicted by theory. Such figures are also
in agreement with Bahmani-Oskooee (1986), Reinhart (1995) and Senhadji
and Montenegro (1999) who found evidence that relative prices play a significant
role in the determination of trade flows.
||Demand for Iranian manufactured exports (1980-2006)
Figures in parenthesis are t-statistics. DW is the test
statistic for the first order autocorrelation in the error term, +Indicates
that the equation is a re-estimate of the preceding one, with non-significant
variables dropped, Further diagnostic tests: For Eq. 1.1; Ramsey Reset
(specification) = 0.32, Jarque-Bera (normality) = 2.71, ARCH (LM)
test = 0.09, For Eq. 1.2; Ramsey Reset (specification) = 1.59, Jarque-Bera
(normality) = 0.95, ARCH (LM) test = 0.01, For Eq. 1.3; Ramsey Reset
= 2.72, Jarque-Bera (normality) = 2.39, ARCH (LM) test = 0.08, For
Eq 1.4.; Ramsey Reset = 2.51, Jarque-Bera 0.25, ARCH (LM) test = 0.51,
For Eq. 1.5.; Ramsey Reset = 1.06, Jarque-Bera = 2.63, ARCH (LM) test
= 0.08, For Eq. 1.6; Ramsey Reset, 0.01, Jarque-Bera = 0.72, ARCH
(LM) test = 0.67, Note that, a, Jarque-Bera (normality) is a test
statistic for investigation of whether the series is normally distributed.
b, Lagrange multiplier test for residual serial correlation. c, Ramsey
Reset test is a regression specification error test, *, **, ***Significant
at 1, 5 and 10% level, respectively
Thus, one can say for the findings
of estimated price and income elasticities, along with real exchange rate
for Iranian manufactured exports is that, DCs lower price elasticity for
Irans exports suggests the appropriateness of a different strategy from
that for the LDCs. These findings accompanied with the changes in Irans
trading partners towards further LDCs after 1979, emphasize the importance
of both price and exchange rate factors in increasing exports. Hence,
an important question would be whether changes in exchange rates and variations
in product prices affect the export flows differently.
SIMULATION ANALYSIS AND SCENARIOS
The estimated model in the last section indicates the partial effect
of exogenous variables, as a shift in export demand arising from an exogenous
shock has an effect on endogenous variables. Accordingly, to investigate
how the model as a whole behaves in response to different shocks, more
importantly, to test the reliability of the export demand model for predicting
the changes of the dependent variables, it is of interest to carry out
a simulation analysis. The historical simulation is utilized by deploying
the estimated results of the model obtained from the last section. The
relative price and real exchange rate is assumed as the control and exogenous
variables in this model. As the impact of changes in the exogenous policy
variable depends upon the behavioral shocks within the model, an exogenous
shock may create a shift in export demand.
On the other hand, over the last three decades the Iranian non-oil and
manufactured exports suffered from uncompetitiveness in the world market.
As one of the main reasons for the poor performance of Irans manufacturing
exports after 1979, was the lack of international competitiveness, in
terms of both price and quality of the goods produced by Import substitution
industries. As Shatz and Tarr (2000) argued, the experience of LDCs shows
that protection to defend an overvalued exchange rate will significantly
retard the growth of the country. Because, the vast majority of developing
countries have downward price and wage rigidities and that with an external
trade deficit they require some form of nominal exchange rate adjustment
to restore external equilibrium. An argument in favor of fighting these
problems can then be conducted by devaluation or relative price changes
induced by e.g., export subsidies. It is worth noting that, subsidies
may be given directly and indirectly. Many countries subsidize their exports
indirectly, e.g., low interest rates on export credit, preferential tax
treatment for profits from exports and output subsidies to export industries
(typically in the form of wage subsidies and investment incentives). Accordingly, two scenarios are selected to conduct an analytical experiment.
Scenario one is chosen to identify the impact of commodity price changes
on export demand namely; a 25% price reduction on export demand. Scenario
two discovers the effect of a 10% devaluation of domestic currency on
demand. As, taking into account of the significance of exchange rate in
export demand and the key role of this variable in increasing exports,
it is of interest to investigate the impact of highly possible fluctuations
in the real exchange rate. On the other hand, Iran experienced an average
annual inflation rate of more than 20% over the last two decades. The
experience of 1993 unification and devaluation indicates that a high devaluation
with its adverse effects might suddenly generate a great shock to the
Iranian economy. It is assumed that a moderate devaluation would increase
export competitiveness in the world market and improves trade balances.
The method employed to solve the model is the Newton technique (which
is available in the TSP computer programmes). Given the new set of values,
the model is solved iteratively each time generating a new set of values.
Thus, the system iterates until convergence of the successive values is
achieved within some denoted tolerance level (Murinde, 1993). Using TSP
software and the results of the estimates from the last section, the historical
simulated (baseline) and the shocked values of the dependent variables
is obtained. In this respect, three common measures of predictive accuracy
according to Pindyck and Rubinfeld (1991) are used to evaluate ex-post
and ex-anti forecasts. These are including RMSE (Root Mean Square Error),
MAE (Mean Absolute Error) and TIC (Thils Inequality Coefficient). The
quantitative measures which are most often used to find out how closely
individual variables track their corresponding data series are, RMSE and
MAE. The RMSE is a measure of the deviation of the simulated variable
from its actual time path and the size of this deviation is evaluated
by comparing it with the mean of the relevant dependent variable. Besides,
a value of TIC greater than one is interpreted to mean that the simulation
is less correct than the simple simulation of no change.
The results that are shown numerically for each endogenous variable in
Table 4 reveal that, the model is appropriate for attempting
to evaluate different policy scenarios.
||Results of the simulation test for the model
|Note that, mean actual values are presented as index
The value of RMSE and MAE is small
relative to the average actual value of the dependent variables, whilst
the TIC is much less than one. Moreover, the relevant illustrated Figures
have emphasized the reliability of the simulation results further and
indicate that, the model tracks the actual movements of the endogenous
variables over the period well.
THE IMPACTS OF POLICY SIMULATION SCENARIOS
In the next step, the impact of the ex-post policy experiments on the
dependent variables is examined. This can be performed by comparing the
shocked values of each variable in each scenario to its historical (baseline)
solution and conclude the changes and possible average growth rates of
dependent variables. The index of the Percentage Deviation from the Control
Solution (PDCS) for each dependent variable that is reported in Table
5, is defined as:
||Shocked value of an endogenous variable
||Baseline solution of the variable
The effect of a 25% price reduction on export demand (Scenario one) is
now analyzed. Referring to Table 5, the simulation results
clearly show that the performance of this policy Scenario has no serious
effect on demand for manufactured exports. As it is shown in Fig.
1, all variables follow the same path tracking the control solutions.
The results indicate that, there is a very small average annual rise of
about 0.44 and 0.98% in manufactured exports to DCs and LDCs. So, differences
in the results for both cases are not substantial. Overall, referring
to Table 5 and Fig. 1, the differences
between the simulation results are not significant. Thus, the impact of
these experiments on such variables irrespective of the destination of
exports appears to be negligible and is only slightly affected by changes
in relative price. Given the likely effectiveness of price reduction upon
its export demand these results suggest that even with a 25% price fall,
the outcome is not significant increase in export demand and the impact
of these experiments on such variables appears to be small partly due
to large and lengthy overvaluation of domestic currency after 1980 in
Iran. Therefore, as Reinhart (1995) suggested for many LDCs, large relative
price swings, such as those produced by devaluation, might be required
to have an appreciable impact on export demand.
||The annual average growth rate of endogenous variables
||The effects of various policy Scenarios
Besides, as Goldfajn and
Valdes (1999) (who investigated the probability of whether a significant
real appreciation will require a nominal devaluation) findings demonstrate;
indeed in the last 35 years policy makers in most countries preferred
to correct large real appreciations through nominal devaluation.
Hence, the focus is on the effect of a nominal devaluation of domestic
currency on export demand. The simulation results reported in Table
5 indicate that, DCs respond to the shock of the real exchange rate
variable and is affected by an increase of about 14% annually in manufactured
exports to this group. Whilst, this scenario results in an immediate increase
of about 16% per annum in exports to LDCs. Corresponding Figures show
clearly that, the shocked values for variables track closely the baseline
solution. The performance of this policy suggests that the economy will
be able to increase significantly manufacturing exports if devaluation
is perused. In fact, the experiences of many countries have shown that
defending the exchange rate has no medium-run benefits, since falling
reserves will force devaluation eventually. It is better that the devaluation
be accomplished without further debilitating losses in reserves and lost
productivity due to import controls (Shatz and Tarr, 2000). This is especially
acute for manufactured exports, which are subject to further impair in
In this study the demand elasticities of Iranian manufactured exports
in terms of her major trading partners over the 1980 to 2006 years was
estimated. A historical simulation was then carried out to perform some
policy experiments and evaluate alternative policies, by using the estimation
results of the applied model. The results demonstrate that the income
elasticities are larger than one, indicating that trading partners income
positively affects Iranian export demand. Consequently, growth in Irans
partner countries will translate into growth of the same magnitude of
the exports. The estimation outcome also reveals that external demand
for Irans manufactured exports varies according to its trading partners
level of development. The results also show that the real exchange rate
and the export prices are two powerful determinants of the export demand.
Finally, the result of the shocks to the key policy variables in the form
of various scenarios demonstrate the significance of exchange rate in
export growth, as the real exchange rate may be regarded as the key mechanism
for transiting the effects of the external shocks such as the oil price
variation. Additionally, it implies that, attempts such as devaluation
of domestic currency can be beneficial for increasing competitiveness
to assist in achieving export expansion.
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