Parves Sultan
This study is unique as it considers industry value added as a possible
source of economic growth in addition to export and import. The key
research questions of this study are: to what extent trade and industry
value added contribute to the economic growth of Bangladesh? Are
there any causal and long run relationships among export, import,
industry value added and gross domestic product in Bangladesh? As
expected, the regression results show that growth rate of industry value
added can contribute more than the growth rate of export and import to
increasing the growth rate of GDP for Bangladesh. We find that there is
cointegration and a long run relationship between GDP and industry
value added in the bivariate cointegration test. We also perform
causality tests. The results clearly show that only import and/or export
cannot contribute to the economic growth unless industrial sector is
taken into account.
- Introduction
Bangladesh practiced restrictive trade policies since its independence in
1971, which continued for one decade. In 1982, Bangladesh started
moving towards outward orientation by initiating the structural
adjustment programs in different sectors of the economy. During the
period between 1971 and 1982 four military coups occurred, which
continued until the end of 1990. Therefore, the socio-economic
conditions were vulnerable between 1971 and 1990. This is, in turn, one
of the important reasons for which the democracy of Bangladesh and the
process of institutionalization have been affected repeatedly. However,
the 1982 measures were followed by further comprehensive changes in
1985–1986 and 1991 (Hossain and Karunaratne, 2001).
A country‟s trade is closely related to its stage of development and
degree of industrialization. As a nation advances economically, the
structure of its foreign trade alters to correspond with a shifting pattern
of resource endowment and comparative advantage (Hultman, 1967).
Hultman also states that in most development planning exercises, the
importance of exports to domestic growth has been approached in terms
of the acquisition of foreign exchange for the import of goods and
services. In other words, export growth is seen as a determinant of
import capacity, which in turn, is a determinant of the level of domestic
economic activities. In recent years, Bangladesh has been achieving not
only a substantial increase in the volume of exports but also an
important change in the composition of exports away from traditional
items such as jute and jute products, and towards new manufactured
products such as ready-made garments. Table 1 shows the trends and
shifts of commodity exports of Bangladesh. This table shows that in
1981–1982, 61.8% of the total exports were raw jute and jute goods,
10.1% of the total exports were leather, 6.1% of the total exports were
tea and 1.1% of the total exports were woven garments. However, in
2002–2003, 5.2% of the total exports were raw jute and jute goods,
2.9% of the total exports were leather, 0.2% of the total exports were
tea, 49.8% of the total exports were woven garments and 25.3% of the
total exports were knitwear.
Table 1: Major export by commodities (% of total export)
Year Jute
Goods
Raw
Jute Leather Tea Frozen
Foods
Chemical
Products Others Woven
Garments Knitwear
1972-
1973 51.4 38.5 4.6 2.9 0.9 0.9 0.9 – –
1981-
1982 45.5 16.3 10.1 6.1 8.5 1.1 10.4 1.1 –
1990-
1991 16.9 6.1 7.8 2.5 8.3 2.6 5.4 42.8 7.6
2002-
2003 3.9 1.3 2.9 0.2 4.9 1.5 10.2 49.8 25.3
Source: Export Promotion Bureau of Bangladesh (as on 16 Oct 2005).
Trade, Industry and Economic Growth in Bangladesh 73
Bangladesh has been experiencing the shift from the traditional sector
(agricultural sector) to the non-traditional sector (industrial and
service sectors) in recent years. The contributions of industrial sector
and service sector to GDP in 2005 were 28% and 51%, respectively
and in 2004, those were 27% and 52%, respectively. The share of
agricultural sector in GDP was 20.5% in 2005 and 21% in 2004,
respectively.
Although the foreign trade sector of Bangladesh constitutes an
important part of its economy, the country suffers from a chronic
deficit in its balance of trade. The balance of trade in Bangladesh
with other countries, especially with SAARC countries, does not
show any hopeful sign for the desirable contribution to country‟s
economic development (Rahman, 2003). Figure 1 shows gross
domestic product, export, imports, and balance of trade in millions of
taka (the local currency of Bangladesh), from 1984 to 2004. The
figure shows that the balance of trade has never been positive in
Bangladesh.
Data Source: World Development Indicators (WDI)
74 Journal of Economic Cooperation
The trade and industrial policy of Bangladesh undertaken in 1980s have
been changing from being highly import substituting and government
controlled to being more liberalized and deregulated. To promote
exports, several measures were undertaken in the 1980s. For example,
the government has established the first export processing zone in
Chittagong. It has been followed by other measures such as tax holidays,
income tax rebates, and other infrastructural benefits to the exportoriented enterprises. In the 1990s, three more export processing zones
were established in Dhaka, Khulna, and Iswardi. In Bangladesh, the
1990s was the milestone for starting towards democracy.
- Uniqueness and Research Questions
Cross-country evidence appears to strongly support the link between
trade and growth (SPDC, 2006). For example, Sachs and Warner (1995)
find that countries with a high trade orientation have an average growth
rate of 2.5%, which is greater than the average growth rate in countries
that are relatively closed. Similarly, Frankel and Romer (1999) state that
a 1% increase in trade-to-GDP ratio is associated with a 2% increase in
per capita income. However, these cross-country studies need to be
qualified for several reasons. First, the direction of causation in the
relationship between trade and growth is difficult to establish
(Rodriguez and Rodrik, 2000). Second, in general, it is agreed that a
degree of macro-economic stability is required for having a positive and
sustained effect of trade liberalization on economic growth. Third, even
if trade has a positive long-run effect on growth, in economies with
certain characteristics the adjustment costs may be large and make the
effects on growth negative in the transitional period (Winters et al,
2004). Thus, there may be a difference between the short-run and the
long run effects. Therefore, one cannot rely on cross-country evidence
alone to make inferences about a specific issue, for example, the effects
of trade on economic growth. This kind of research must be undertaken
on a case by case basis and in a country context (SPDC, 2006).
Therefore, our endeavor is to measure the impact of international trade
and industry value added on economic growth in Bangladesh using the
time series econometric method.
Trade policies (or trade liberalization policies) work only in combination
with other appropriate policies. For example, investment has been
identified as a key link through which openness affects growth (Taylor,
Trade, Industry and Economic Growth in Bangladesh 75
1998 and Wacziarg, 2001). Trade policies are integrated with economic
growth and development strategies. Therefore, the linkages between
trade policy and development-cum-industrialization strategy are crucial
(Krueger, 1998). Trade policies that hurt investment could damage the
benefits of trade and which, in turn, could hurt domestic economic
growth and overall development. To the best of our knowledge, the prior
studies have not used the variable, industry value added, as a possible
source of economic growth. We use the variable, industry value added,
as a possible source of economic growth in addition to export and
import, which is a unique feature of this study. Therefore, the key
research questions of this study are: to what extent trade and industry
value added contribute to the economic growth of Bangladesh? Are
there any causal and long run relationships among export, import,
industry value added and gross domestic product in Bangladesh?
It has been argued that openness is a better measure for economic
growth than export alone. If only export is used it is implicitly assumed
that import does not contribute to economic growth. Import of capital
goods and energy can accelerate economic growth (Sinha and Sinha
1999, 1996; Krueger 1998, 1997). Therefore, import and export policies
of a particular country have direct impact on economic growth and
overall development. Lastly, this study uses the longer time series data.
Data are for 1965–2004. The longer period of time series data can
produce better results in predicting the impact of trade and industry
value added on economic growth, and their causal and long run
relationships. - Literature Review
Empirical studies to date by and large support the hypothesis that
openness of trade leads to economic growth and vice versa. However,
there are some studies that show that there is no causal relationship
between the growth of trade openness and the growth of GDP, for
example, Narayan and Smyth (2005) and Abhayaratne (1996).
A number of empirical studies on export and economic growth of
Bangladesh have shown diverse findings. Islam and Ifthekharuzzaman
(1996) examine the relationship between total export and economic
growth. They find no significant relationship between export and growth
of Bangladesh. They use time series data from 1971 to 1990. The study
76 Journal of Economic Cooperation
may be criticized on the ground that the time series data used in this
study are non-stationary. In contrast, Islam (1998) conducts the Granger
causality tests along with the Johansen and Juselius (1990) cointegration
tests and the error correction modeling technique to examine the nature
and direction of causality between the growth of export and GDP of
Bangladesh. On the basis of annual data from 1969 to 1991, the study
shows that growth in exports Granger causes economic growth
positively and significantly but not vice versa. Since the period 1982–
1991 can be described as the transitional period towards outward
orientation, the results may not reflect the true nature of the causal
relationship between export and gross domestic product.
Sinha and Sinha (1999) conduct time series analysis for 124 countries in
order to examine the causal relationship between economic growth and
growth of trade openness. They define openness for a country for year t
as Ot
= (imt
- ext). The import (imt) and export (ext) at time t are in real
terms. The estimated model for empirically testing the relationship
between openness and growth is GOPt= a + b GRGDPt - errort
, where
GOP is the growth rate of trade openness and GRGDP is the growth rate
of GDP. The unit root and cointegration tests show that the variables are
either integrated of order zero I(0) or cointegrated. The Granger
causality tests show that the growth in openness Granger causes the
growth in GDP for 11 countries and the growth in GDP Granger causes
the growth in openness for 18 countries. The results show that there is a
positive and significant relationship between the growth in openness and
the growth in GDP for 94 countries. However, openness of an economy
also depends on tariffs and tax on international trade. Therefore, there is
a scope for further research.
Hossain and Karunaratne (2001) examine the export-led-growth
hypothesis for Bangladesh. They also examine whether or not
manufacturing export is a new engine of export-led-growth instead of
total export. The results show that the first differences of the variables
are stationary using the ADF and the PP tests. The bivariate Granger
causality tests show that there are significant and positive bi-directional
causalities between total exports and GDP, manufacturing exports and
GDP, total exports and manufacturing output, and manufacturing
exports and manufacturing output. However, the multivariate models
confirm only unidirectional causality from manufacturing exports to
GDP and from manufacturing exports to manufacturing output. Total
Trade, Industry and Economic Growth in Bangladesh 77
exports neither causes nor is caused by manufacturing output. The
existence of Granger causality from total exports to GDP, and from
manufacturing exports to GDP and manufacturing output in the presence
of the investment variable is indicative of an improvement in efficiency.
The Engle-Granger error correction method confirms causality from
total exports to GDP, from manufacturing exports to GDP as well as
from manufacturing exports to manufacturing output. Once again, total
exports appear not to cause manufacturing output. However, the study
finds that there is a long run and, a stable relationship between
expansion of exports and economic growth in Bangladesh. As to the
relative importance of total exports and manufacturing exports in
enhancing the growth of GDP vis-à-vis the manufacturing output, the
empirical results of this study do not claim that manufacturing exports
has become a new engine of export–led growth. The whole range of the
non-nested and the encompassing tests suggest that total exports, as
opposed to manufacturing exports, is the main engine of growth in terms
of GDP. As to the manufacturing output, both total exports and
manufacturing exports emerge as engines of growth. This implies that
manufacturing exports cannot be claimed to be the sole determinant of
growth of Bangladesh. Although Hossain and Karunaratne (2001)
establish the bivariate causal relationship between exports and economic
growth, there is the possibility for no causal relationship between
exports and economic growth since other variables in the economic
system may determine the growth paths of the time series (Yaghmainan,
1994).
Mamun and Nath (2005) examine the export-output relationship for
Bangladesh using time series data. More specifically, they examine the
time series evidence of export-led- growth in Bangladesh. The unit root
test (augmented Dickey-Fuller) results show that the quarterly data on
industrial production index, exports of goods and services, and exports
of goods only are integrated of order one, i.e. I (1). The Engle-Granger
cointegration equation results show that there is a long run equilibrium
relationship between industrial production and exports. The estimated
cointegrating equation also indicates that there is a significant and
positive long run relationship between exports and industrial production
in Bangladesh. The error correction model (ECM) and Granger causality
test results show that there is no causal relationship between export
growth and industrial growth. The results also show that there is a
positive long run equilibrium relationship between exports and industrial
78 Journal of Economic Cooperation
production, and there is no evidence of short-run causal relationship
between these two variables. They state that the long run causality
seems to run from exports to industrial production.
- Objectives
As international trade consists of exports and imports, we take these two
variables. The trade policies are integrally tied up with overall growth
and development strategies. The productivity and output growth in
agriculture, services, and manufacturing are all essential for economic
growth. Therefore, the linkages between trade policy and developmentcum-industrialization strategy are crucial (Krueger, 1998). Thus, we
consider industrial value added as a possible source of economic growth
in our study. In this empirical study, we use export, import, and
industrial value added as the independent variables and gross domestic
product as the dependent variable. The objectives of this study are as
follows:
1) To study the nexus among exports, imports, industrial value added
and economic growth in Bangladesh.
2) To empirically analyze and provide policy recommendations
regarding the growth nexus of GDP with exports, imports, and
industrial value added for Bangladesh. - Econometric Methodology
A handful of empirical studies used the econometric methodologies to
examine the theoretical justification and empirical relationship between
the international trade and the economic growth. Time series
econometric studies to date, by and large, support the hypothesis that
openness of trade leads to economic growth and vice versa (for example
Sinha and Sinha, 1999; Sinha, 1999; Hossain and Karunaratne, 2001;
Dutta and Ahmed, 2004; Jin, 2003; Nath and Mamun, 2004). However,
there are some studies that show that there is no causal relationship
between the growth of openness of trade and growth of GDP (e.g.
Narayan and Smyth, 2005; Abhayaratne, 1996). We use similar
econometric methodology as followed by other time series studies.
Annual data for 1965–2004 are used for this study. The data are in
constant local currency units for Bangladesh. Data are collected from the
World Development Indicators of the World Bank and from the
Trade, Industry and Economic Growth in Bangladesh 79
International Financial Statistics of the International Monetary Fund
(IMF). We take logarithms of the variables. The unit root test results
show that the data are non-stationary in their levels but stationary in
their first differences. Therefore, we take the first difference of the log
value to estimate the regression model using the ordinary least square
(OLS) method. The regression equation is estimated as:
lnGDPt = α0 + α1 lnEXPt + α2 lnIMPt +α3 lnIVAt + t
. (I)
The first difference of natural log of the respective variable is denoted
by (delta). The constant and the coefficients of the regression
equation are α0 and α (1, 2, 3), respectively. The variables lnGDPt
,
lnEXPt
, lnIMPt
, and lnIVAt
refer to the natural log of gross domestic
product, natural log of export, natural log of import, and natural log of
industry value added at time t (here 1965 to 2004), respectively. Finally,
t
is the error term.
First, we provide the descriptive statistics and the correlation table
among the variables (e.g. lnGDP, lnEXP, lnIMP, and lnIVA).
These statistics give a better understanding of the variables considered
for this study. Second, we provide the Phillips–Perron unit root test
results for each of the variables in their levels and in their first
differences. Trend assessment is particularly important for the unit root
tests, which we performed before conducting the unit root test. For the
unit root test, the null hypothesis is that the variable has a unit root.
However, we reject the null hypothesis if the test critical value at 5%
significance level is greater than the Phillips–Perron test statistic (t-stat)
and if their corresponding probability value is less than 0.05. Third, we
present the regression results. Fourth, the Johansen bivariate and
multivariate cointegration tests results are analyzed. Engle and Granger
(1987) point out that a linear combination of two or more non-stationary
series may be stationary. Since the variables including lnGDP, lnEXP,
lnIVA and lnIMP are non-stationary in their levels but stationary in their
first differences, we investigate whether these non-stationary variables
are cointegrated or not. The non-stationary time series are said to be
cointegrated, if a stationary linear combination exists. The stationary
linear combination is called the cointegrating equation and may be
interpreted as a long run equilibrium relationship among variables.
80 Journal of Economic Cooperation
However, if there is no evidence of a cointegration and a long run
relationship among the variables namely lnGDP, lnEXP, lnIVA and
lnIMP; an error correction model (ECM) based causality tests are not
appropriate. Therefore, causality tests using Granger approach within
the framework of VARs with first-differenced are appropriate (Toda and
Phillips, 1993). Finally, in our further investigation, pairwise and
multivariate Granger causality tests are performed within the VAR
framework with three lags in order to determine the causal relationship
between variables. The Granger causality tests measure precedence and
information content but does not by itself indicate causality in the more
common use of the term. The null hypothesis for the pairwise Granger
causality test is „x‟ does not Granger cause „y‟, if the p-value is not
significant at the 5% level. - Empirical Results
- 1. Descriptive Statistics
Table 2 shows the descriptive statistics for Bangladesh. The average
growth rates of gross domestic product, export, import, and industry
value added in Bangladesh are 3.2%, 6.8%, 23%, and 15.6%,
respectively.
Table 2: Descriptive statistics for Bangladesh
lnGDP lnEXP lnIMP lnIVA
Mean 0.032958 0.068327 0.229725 0.156553
Std. Dev. 0.041517 0.165661 0.016376 0.041552
Figure 2 shows the growth rates of gross domestic product, export,
import, and industry value added for Bangladesh. We see that growth
rates of gross domestic product, industry value added, export and import
were volatile between 1965 and 1980. However, since 1980 the growth
rates of gross domestic product, industry value added, export and import
in Bangladesh were less volatile than the period between 1965 and 1980.
Trade, Industry and Economic Growth in Bangladesh 81
Figure 2: Growth rates of lnGDP, lnEXP, lnIMP, and lnIVA of Bangladesh
-.8
-.6
-.4
-.2
.0
.2
.4
.6
.8
1965 1970 1975 1980 1985 1990 1995 2000
LOGEXG
LOGGDPG
LOGIMG
LOGIVAG
The correlation matrix (Table 3) shows that the coefficients of the
growth rates of industry value added and the growth rates of gross
domestic product, and the growth rates of industry value added and the
growth rates of export have a strong and positive correlation. This
means that the increase in lnIVA would result in an increase in
lnGDP and lnEXP, respectively and vice versa. The negative
coefficient implies that an increase in lnIMP would result in a decrease
in lnEXP and lnIVA, respectively and vice versa.
Table 3: Correlation matrix for Bangladesh
Variables lnEXP lnGDP lnIMP lnIVA
lnEXP 1 0.339 -0.059 0.600
lnGDP 0.339 1 0.081 0.788
lnIMP -0.059 0.081 1 -0.311
lnIVA 0.600 0.788 -0.311 1
82 Journal of Economic Cooperation - 2. Unit Root Test Results
We find that lnGDP, lnEXP, lnIMP, and lnIVA have trends in their
levels. The variable lnGDP has a trend in its first difference and
variables lnEXP, lnIMP, and lnIVA have no trends in their first
differences.
The Phillips-Perron unit root test results (Table 4) shows that the critical
values at the 5% significance level are smaller than the Phillips-Perron
test statistics. The p–values of the corresponding variables are greater
than 0.05 at the 5% level of significance. Therefore, these variables are
non-stationary in their levels.
Table 4: Unit Root Test in Levels for Bangladesh
Variables Phillips-Perron test
statistic (t-stat.)
Test Critical
Value at 5% Probability
lnGDP -1.219938 -3.529758 0.8923
lnEXP -2.436661 -3.529758 0.3561
lnIMP -1.570112 -3.529758 0.7866
lnIVA -2.934906 -3.529758 0.1632
Test Equation: Trend and Intercept
Table 5: Unit Root Test in First Difference for Bangladesh
Variables Phillips-Perron test
statistic (t-stat.)
Test Critical
Value at 5% Probability
lnGDP -6.956815 -3.533083 0.0000
lnEXP -8.981766 -2.941145 0.0000
lnIMP -6.187644 -2.941145 0.0000
lnIVA -7.258375 -2.941145 0.0000
Test Equation–trend and intercept. The variable lnGDP has a trend in its first
difference.
However, Table 5 shows that the variables ΔlnGDP, ΔlnEXP, ΔlnIMP,
and ΔlnIVA are stationary. This is because the critical values at the 5%
level of significance are greater than the Phillips-Perron test statistics (tstatistics) and their corresponding probability values are less than 0.05.
Trade, Industry and Economic Growth in Bangladesh 83 - 3. The Regression Results
The regression results of the estimated model, lnGDPt = α0 +
α1 lnEXPt + α2 lnIMPt + α3 lnIVAt + t
, for Bangladesh are shown
in Table 6.
Table 6: Regression Results for Bangladesh
Variable Coefficient t-Statistic Probability
C 0.024742 7.186829 0.0000
Δ lnEXP -0.072614 -2.963643 0.0054
Δ lnIMP 0.072795 4.895259 0.0000
Δ lnIVA 0.288431 10.59107 0.0000
R-squared (R2
) 0.792014 F-statistic 44.42698
Adjusted R-squared
( R
2
)
0.774187 Prob. (F-statistic) 0.000000
S.E. of regression 0.019729 Durbin-Watson stat 2.376078
The coefficient for ΔlnEXP is –0.072614, implying that if there is a 1%
increase in the growth rate of export, growth rate of GDP would face a
decrease by 0.07%. The associated probability for ΔlnEXP is 0.0054,
which is significant at the 5% level. Likewise, growth rate of GDP
would increase by 0.07% and 0.29%, respectively if there is a 1%
increase in the growth rates import and industry value added,
respectively. The p-values for Δ lnIMP and Δ lnIVA are significant at
the 5% level. The p-values for all the variables are statistically
significant for rejecting the null hypothesis that the true coefficient is
zero at the 5% significance level. Therefore, the growth rate of industry
value added can contribute more than the growth rate of export and
import to increasing the growth rate of GDP for Bangladesh. It is
imperative to state that import of capital goods and technology, and
efficient use of them can accelerate industrial production and value
addition, which in turn, contribute to export earning and domestic
economic growth.
We use the Breusch-Godfrey LM test for testing the serial correlation
among variables. The results of Table 7 show that the Observation*Rsquared statistic is greater than F-statistic and the chi-square value is
greater than 0.05, therefore, we accept the null hypothesis that there is
no serial correlation up to the first lag order.
84 Journal of Economic Cooperation
Table 7: Breusch-Godfrey Serial Correlation LM Test for Bangladesh
F-statistic Obs*R-squared Prob. F(2,33) Prob. Chi-Square(2)
2.992543 5.987375 0.063923 0.050102
- 4. Johansen Bivariate and Multivariate Cointegration Tests
Results
The unit root test results show that lnGDP, lnEXP, lnIMP, and lnIVA
are non-stationary in their levels but stationary in their first differences
for Bangladesh. Therefore, we conduct both bivariate and multivariate
Johansen cointegration tests for these variables. The purpose of the
cointegration test is to determine whether a group of non-stationary
variables is cointegrated or not. Table 8 shows the results of trace and
maximum eigenvalues of the bivariate cointegration tests for
Bangladesh.
Table 8: Johansen Bivariate Cointegration Tests for Bangladesh
Variable
Cointegration Rank Test
(Trace)
Cointegration Rank Test
(Maximum Eigenvalue)
Trace
Statistic
Critical
Value at 5% Prob. Max-Eigen
Statistic
Critical
Value at 5% Prob.
lnGDP and
lnIMP
10.57630 15.49471 0.2390 10.32118 14.26460 0.1917
lnGDP and
lnEXP
13.04375 15.49471 0.1132 9.540789 14.26460 0.2439
lnGDP and
lnIVA 42.62053 15.49471 0.0000 36.90257 14.26460 0.0000
The trace test indicates that there is no cointegration between lnGDP and
lnIMP, and between lnGDP and lnEXP at the 5% significance level. We
find that there is cointegration between lnGDP and lnIVA at the 5%
significance level. The maximum eigenvalue test shows that the critical
values are higher than the test statistics for lnGDP and lnIMP, lnGDP
and lnEXP. Therefore, there is no long run relationship between lnGDP
and lnIMP, and lnGDP and lnEXP. The results also indicate that the
variables lnGDP and lnIVA have a long run relationship in Bangladesh.
The maximum eigenvalue test also shows that there is no cointegration
Trade, Industry and Economic Growth in Bangladesh 85
for lnGDP and lnEXP, and lnGDP and lnIMP in Bangladesh. The pvalues in both trace test and maximum eigenvalue test for lnGDP and
lnIVA are significant at the 5% level.
The Johansen multivariate cointegration test results are shown in Table - The trace test and the maximum eigenvalue test indicate that there is
no cointegration. This is because the critical values at 5% level are
smaller than the trace statistic and the maximum eigenvalue statistic,
respectively for the first hypothesized cointegrating equation (CE).
Table 9: Johansen Multivariate Cointegration Tests for Bangladesh
Hypothesize
d
No. of CE(s)
Unrestricted Cointegration Rank
Test (Trace)
Unrestricted Cointegration Rank
Test (Maximum Eigenvalue)
Trace
Statistic
Critical
Value at 5% Prob.
MaxEigen
Statistic
Critical
Value at 5% Prob.
None
90.1664
4 47.85613 0.0000
62.0374
9 27.58434
0.000
0
At most 1 28.1289
5 29.79707 0.0769
15.3641
5 21.13162
0.264
2
At most 2 12.7648
1 15.49471 0.1237
10.8906
5 14.26460
0.159
8
At most 3 1.87415
8 3.841466 0.1710
1.87415
8 3.841466
0.171
0 - 5. Granger Causality Test Results
The pairwise Granger causality test results for Bangladesh (Appendix A)
show that ΔlnEXP Granger causes ΔlnGDP and ΔlnIMP, respectively
and that the p-values are significant at the 5% level. The results also
show that ΔlnIVA Granger causes ΔlnEXP and ΔlnIMP, respectively,
and ΔlnGDP Granger causes Δ lnIMP at the 5% significance level.
These causal relationships are unidirectional. The multivariate Granger
causality test for the variables (Appendix B) show that the variable,
ΔlnGDP is Granger caused by the variables ΔlnIMP and ΔlnIVA, and
that the variable ΔlnEXP is significant at the 5% level. The results also
show that ΔlnGDP is Granger caused by ΔlnIMP, ΔlnEXP, ΔlnIVA as
the p-value is significant at the 5% level. Similarly, ΔlnIMP and ΔlnIVA
are Granger caused by ΔlnGDP and ΔlnIVA, and ΔlnGDP and ΔlnIMP,
86 Journal of Economic Cooperation
respectively as ΔlnEXP is significant at the 5% level and when ΔlnIMP
and ΔlnIVA are dependent variables, respectively. The results also show
that ΔlnIMP is Granger caused by ΔlnGDP, ΔlnEXP and ΔlnIVA, and
that the p-value is significant when all the variables are considered. The
variable ΔlnIVA is Granger caused by ΔlnGDP, ΔlnEXP and ΔlnIMP,
and that the p-value is significant at the 5% level.
Thus, the results show that export orientation and industrialization
(industrial value added) would accelerate the demand for imports of
capital goods and technology, which in turn, will increase the economic
growth of Bangladesh. - Policy Recommendations and Conclusion
Our regression results support the findings of Islam and
Ifthekharuzzaman (1996), which states that there is no significant
relationship between the growth rate of export and the growth rate of
gross domestic product of Bangladesh. Our pairwise Granger causality
test results also support the findings of Islam (1998). Islam finds that the
growth of total export Granger causes growth of GDP positively and
significantly but not vice versa. Although Mamun and Nath (2005) find
no causal relationship between export growth and industrial growth, our
estimation results show that growth rate of export is Granger caused by
the growth rate of industry value added but not vice versa.
Therefore, the policy implications are simple from these results. The
results clearly show that only import and/or export cannot contribute to
the economic growth unless industrial sector is taken into account. The
results also show that GDP will grow if the import demand is derived
from the export and industrial sectors. Therefore, diversification of
exports, export promotion, careful import liberalization strategies,
foreign and domestic investment, favorable infrastructure and
industrialization policies can lead to rapid economic growth in
Bangladesh. Trade policies should focus on import liberalization. Tax,
tariff and non-tariff barriers among the trading countries, especially in
the South Asian region should be reduced.
Bangladesh suffers from a huge trade deficit with the neighboring country,
India. The low level of intra-regional trade in South Asia partly reflects the
similarity of the comparative advantage pattern within the region. It also
Trade, Industry and Economic Growth in Bangladesh 87
reflects the structural rigidities created by political constraints. The
competitive nature of the SAARC economies suggests that mere removal
of trade barriers is not likely to have a significant impact on intra-regional
trade (Hassan, 2000; Ahmed and Sultan, 2004). Therefore, it is imperative
that the bilateral and the multilateral trade and investment negotiations
among the South Asian countries should be strengthened and it must
focus on industrial, agricultural, and service sectors in order to improve
the balance of trade and socio-economic development in this region
(Ahmed and Sultan, 2004). Strengthening SAARC and SAPTA could be
one of the main strategies for regional growth and development in the
South Asian Nations.
Imports of industrial goods and technologies can increase productivity
and can contribute to the growth of industry and economy. Export
policies and export incentives in Bangladesh should be such that these
can accelerate economic growth. There are some comparative
advantages in these South Asian countries. Moreover, they share
common geographic and climatic conditions, culture and religion.
Therefore, these advantages should be explored, shared and utilized for
their mutual benefits and growth.
88 Journal of Economic Cooperation
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