## Trade OPENNESS AND ITS EFFECTS ON ECONOMICA GROWTH IN SELECTED SOUTH ASIAN COUNTRIES: A PANEL DATA STUDY

The survey investigates the causal nexus between trade openness and economic growing for four South Asiatic states for period 1972-1985 and 1986-2007 to analyze the scenario before and after the execution of SAARC. Panel cointegration and FMOLS techniques are employed for short tally and long tally estimations. In 1972-85 short tally unidirectional causality from GDP to openness is found whereas, in 1986-2007 there exists bi-directional causality between GDP and openness. The long tally snap magnitude between GDP and openness contains negative mark in 1972-85 which shows that there exists long run negative relationship. While in clip period 1986-2007 the snap magnitude has positive mark that indicates positive causing between GDP and openness. So it can be concluded that after the execution of SAARC overall state of affairs of selected states got better. Besides long run coefficient of error term suggests that short term equilibrium accommodations are driven by accommodation back to long tally equilibrium.

IINTRODUCTION

NTERNATIOANL trade plays an of import function in the development of any economic system and assumed to be an engine of growing [ 1 ] . Trade is taking topographic point non merely in footings of trade goods but besides in footings of engineering, flows of thoughts and cognition spillover.

International trade affects economic system through different channels. It creates employment, generate capital formation that leads to better life criterions in footings of higher degree of GDP and GDP per capita. Over the past few old ages, the universe trading system is going increasingly unfastened and competitory. Duties are cut downing in both developed and developing states and limitations are extinguishing. Economies are seeking to follow outward-looking economic policies, besides looking for the ways to advance growing and employment through spread outing export production and pulling inward investing.

The construct of trade openness and free trade is extremely debated subject in economic sciences. It is ever assumed to be a really of import beginning of economic growing. Trade openness can advance growing through several ways. It creates monolithic benefits, addition investings as a consequence of enlarged markets and economic systems of graduated table, flow of information, engineering and cognition spillovers. As, it creates efficient use of resources, improved technological efficiency and trade facilitation that returns in higher foreign exchange which is used to spread out the less developed sectors of the economic system. It is besides supported by many economic experts in different surveies. Some surveies concluded that openness played effectual function largely in developed states [ 2 ] whereas many surveies concluded that openness can play important function in less developed states every bit good [ 3 ] [ 4 ] [ 5 ] .

South Asia is economically one of the less developed parts of the universe which accommodates more than 20 per cent of the universe ‘s population that is 1,542.95 million with the mean GDP per capita of US $ 1,565 [ 6 ] . The South Asiatic economic systems largely followed protectionist trade policies during their initial stages of development. The premier rules behind the restrictive trade governments were protection of the domestic industries from foreign competition and preservation of foreign exchange for balance of payments support [ 7 ] . Besides, South Asia is assumed to be less incorporate part of the universe in footings of the trade of trade goods, capital and thoughts [ 8 ] whereas, Intraregional trade is really low for South Asia i.e. intraregional trade is less than 2 per centum of GDP, compared to more than 20 per centum for East Asia [ 8 ] .

LITERATUTRE REVIEW

The relationship between openness and economic growing has been extensively examined in the theoretical and empirical literature.

Dollar [ 9 ] used existent exchange rate deformations to prove that the jurisprudence of one monetary value holds in the long tally. The survey found a important negative correlativity between existent exchange rate deformations and growing, which shows a positive trade-growth nexus. Harrison [ 10 ] investigated the association between openness and economic growing. The survey concluded that the correlativity between these two variables was strong. Frankel and Romer [ 11 ] examined the relationship between trade and growing and besides considered geographic features as an of import ingredient in trade. The survey concluded that trade has a big but reasonably positive and important impact on income of the state. Rodriguez and Rodrik [ 12 ] applied the Dollar [ 9 ] process to an updated version of the same information and found that the same arrested developments now yielded the antonym signed consequence. Ekanayake, Vogal and Veeramacheneni [ 3 ] checked the causal relationship between end product degree, inward FDI and exports for a cross-section of both developed and developing states for period 1960-2001. The survey concluded that there was bi-directional causality between export growing and economic growing. Dollar and Kraay [ 13 ] investigated the effects of trade on growing and poorness for 137 states. The survey concluded that at single degree and at transverse state level the unfastened governments lead to faster growing and poorness decrease in hapless states. Din [ 14 ] examined the export-led growing hypothesis for the five largest economic systems of the South Asiatic part and found that long-term causality merely existed in Pakistan and Bangladesh while all other states had short tally causality. Hassan and Kamrul [ 4 ] investigated the insouciant relationship between trade openness and economic growing and the construction of international trade for Bangladesh. The survey explored that there was long-term uni-directional equilibrium relationship between trade openness and economic growing.

. Sarkar [ 15 ] investigated the relationship between openness and growing. Study found no positive long-run relationship between openness and growing in bulk of LDC ‘s. Klasra [ 5 ] examined the long-term relationship between Foreign Direct Investment ( FDI ) , trade openness and economic growing for Pakistan ad Turkey and found that there was bi-directional causality between openness and growing in Pakistan whereas for Turkey at that place existed bi-directional relationship between FDI and exports

Data and Variables

The analysis is based on one-year informations for four South Asiatic states ( N=1aˆ¦aˆ¦.,4 ) that are Bangladesh ( BNG ) , India ( IND ) , Pakistan ( PAK ) and Srilanka ( SLK ) for the sample period 1972 to 2007 ( T=1aˆ¦aˆ¦.36 ) . The information is divided into two clip spans that are from 1972 to 1985 and 1986 to 2007 to analyse the state of affairs before and after the execution of SAARC.

The variables used in the survey are Gross domestic merchandise ( Current US $ ) as dependant variable. Whereas, the independent variables are the labour force, Gross fixed capital formation ( Current US $ ) , and openness. The variable openness is proxied by the ratio of imports plus exports to GDP. The information is taken from the World Development Indicators [ 6 ] .

Model Specification

The undermentioned neoclassical production map is used to happen out the consequence of trade openness on economic growing

lnY= degree Fahrenheit { ln ( OP, K, L ) } ( 1 )

The dual Ln theoretical account is used to stand for the growing theoretical account, to explicate all the variables in growing footings.

The panel version of equation ( 1 ) can be written as follows:

lnYi, t= I±0, i+ I?1iln Opi, t+ I? 2ilnKi, t+ I?3i lnLi, t+Iµi, T ( 2 )

Where i=1aˆ¦..4 denote the states, t=1972, aˆ¦1985 and 1986aˆ¦..2007 denotes clip period. i??it is the error term with the usual statistical belongingss while i?? and i?? are coefficients.

The usage of panel informations has advantage that it can work both the clip series and transverse sectional dimensions of informations and supply more efficient appraisals of parametric quantities by sing wider beginnings of fluctuation.

Methodology

To gauge equation ( 2 ) , panel Cointegration technique is used. The cointegration of panel informations consists of four stairss

Panel Unit Root Trials

The survey uses unit root trial to look into the stationarity of the clip series by utilizing three different statistics proposed by Im, Pesaran, and Shin [ 16 ] , Maddala and Wu [ 17 ] , and Levin, Lin, and Chu [ 18 ] panel unit root and stationary trials. Stationary series are integrated of order nothing.

Cointegration Trials

After look intoing the stationarity of informations and corroborating that each series is integrated of the same order, the following measure is to look into whether these series can be combined together into a individual series, which itself must be non-stationary, that is known as cointegration. Cointegrated series move in the same way in long tally and are in equilibrium relationship. So, the cointegration between openness and economic growing will explicate that how these variables are related in the long tally. For this heterogenous panel cointegration trial developed by Pedroni [ 19 ] and Kao [ 20 ] are employed.

Panel Fully Modified OLS estimations

When long tally relationship among the variables is found so for the appraisal of long tally effects of openness on economic growing panel FMOLS is used, proposed by Pedroni [ 21 ] .

Granger Causality Test

Finally, if the variables are cointegrated and long tally relationship exists, following measure is to use the Granger causality trial. For this intent a panel-based mistake rectification theoretical account ( ECM ) is used to explicate the long-term relationship by utilizing the Engle and Granger [ 22 ] processs. The two-step process of Engle-Granger [ 22 ] is performed as: foremost, the appraisal of the long-term theoretical account for Equation ( 2 ) in order to obtain the estimated remainders i??it. Second, to gauge the Granger causality theoretical account with a dynamic mistake rectification:

The beginnings of causing between Y and OP are recognized by proving for the significance of the coefficients of the dependent variables in Eqs. ( 3 ) and ( 4 ) . For short-term causality, analyze test H0: i?±12i, k = 0 for all I and K in Eq. ( 3 ) or H0: i?±21i, k = 0 for all I and K in Eq. ( 4 ) . While, the long-term causality is tested by looking at the significance of the i?¬ , which is the coefficient of the mistake rectification term, i??i, t-1. The significance of i?¬ indicates the long-term relationship of the cointegrated procedure, and so motions along this way can be considered lasting. For long-term causality, trial H0: i?¬1i =0 for all I in Eq. ( 3 ) or H0: i?¬2i =0 for all I in Eq. ( 4 ) is used. Similarly, beginnings of causing between Y and other two variables ( capital and labor ) are identified.

Empirical consequences

Panel Unit Root Results

Panel unit root trial consequences are reported in table 1-a and 1-b for 1972-85 and 1986-07 severally. All trials consequences do non reject the void hypothesis of non-stationary at degree with both single consequence and single additive tendency consequence for both clip periods.

TABLE I-a

Panel Unit Root Tests Results 1972-85

LLC

Information science

MW ( ADF )

Decision

Intercept

Intercept and Trend

Intercept

Intercept and Trend

Intercept

Intercept and Trend

Ln Y

-1.76 ( 0.23 )

-1.54 ( A 0.46 )

0.20 ( 0.57 )

-0.70 ( 0.22 )

5.99 ( 0.67 )

9.89 ( 0.27 )

## —

Ln OP

-3.66 ( 0.60 )

-1.33 ( 0.39 )

-2.34 ( 0.70 )

-0.39 ( 0.65 )

18.31 ( 0.51 )

7.68 ( 0.46 )

## —

Ln K

-1.28 ( 0.29 )

0.51 ( 0.69 )

1.19 ( 0.88 )

1.12 ( 0.87 )

2.53 ( 0.96 )

3.26 ( 0.91 )

## —

Ln L

0.21 ( 0.58 )

-2.81 ( 0.30 )

1.03 ( 0.85 )

-0.46 ( 0.32 )

7.07 ( 0.52 )

11.71 ( 0.16 )

## —

a?†Ln Yttrium

-7.75 ( 0.00 )

-11.52 ( 0.00 )

-6.26 ( 0.00 )

-6.02 ( 0.00 )

43.64 ( 0.00 )

35.08 ( 0.00 )

I ( 1 )

a?†Ln OP

-3.29 ( 0.00 )

-7.12 ( 0.00 )

-2.08 ( 0.00 )

-3.37 ( 0.00 )

16.91 ( 0.00 )

24.88 ( 0.00 )

I ( 1 )

a?†Ln K

-5.33 ( 0.00 )

-0.86 ( 0.00 )

-3.69 ( 0.00 )

-1.54 ( 0.00 )

26.84 ( 0.00 )

13.94 ( A 0.00 )

I ( 1 )

a?†Ln L

0.33 ( 0.00 )

-1.80 ( 0.00 )

1.18 ( 0.00 )

0.19 ( 0.00 )

5.32 ( 0.00 )

5.70 ( 0.00 )

I ( 1 )

Notes: LLC, IPS, MW and indicated the Levin et Al. ( 2002 ) , Im et Al. ( 2003 ) and Maddala and Wu ( 1999 ) panel unit root and stationary trials. All trials examine the void hypothesis of non-stationary ( unit root ) . The four variables were grouped into one panel with sample N= 4, T=14. The parenthesized values are the chance of rejection. Probabilities for the MW ( ADF Fisher Chi-square ) and PP ( Fisher chi-square ) trials are computed utilizing an asymptotic I‡2 distribution, while the other trials follow the asymptotic normal distribution.

However, all trials reject the void hypothesis of non-stationarity at first difference. This shows that all the variables Y, OP, K and L are integrated of order one, an I ( 1 ) procedure. So, as pooled information is stationary in first difference hence, the series can be cointegrated.

TABLE I-b

Panel Unit Root Tests Results 1986-2007

LLC

Information science

MW ( ADF )

Decision

Intercept

Intercept and Trend

Intercept

Intercept and Trend

Intercept

Intercept and Trend

Ln Y

1.01 ( 0.84 )

0.60 ( 0.72 )

2.34 ( 0.99 )

2.93 ( 0.99 )

0.02 ( 0.98 )

0.006 ( 0.99 )

## —

Ln OP

-2.62 ( 0.12 )

-2.93 ( 0.16 )

-1.41 ( 0.07 )

-0.72 ( 0.23 )

5.26 ( 0.07 )

2.98 ( 0.22 )

## —

Ln K

1.48 ( 0.93 )

1.61 ( 0.94 )

2.57 ( 0.99 )

3.61 ( 0.99 )

0.01 ( 0.99 )

0.001 ( 0.99 )

## —

Ln L

-0.78 ( 0.21 )

-1.11 ( 0.13 )

0.99 ( 0.84 )

1.60 ( 0.94 )

0.33 ( 0.84 )

0.09 ( 0.95 )

## —

a?†Ln Yttrium

-4.83 ( 0.00 )

-5.91 ( 0.00 )

-4.91 ( 0.00 )

-5.24 ( 0.00 )

24.35 ( 0.00 )

23.99 ( 0.00 )

I ( 1 )

a?†Ln OP

-9.39 ( 0.00 )

-10.60 ( 0.00 )

-8.64 ( 0.00 )

-8.63 ( 0.00 )

31.26 ( 0.00 )

34.19 ( 0.00 )

I ( 1 )

a?†Ln K

-6.10 ( 0.00 )

-7.33 ( 0.00 )

-4.86 ( 0.00 )

-5.10 ( 0.00 )

24.07 ( 0.00 )

23.24 ( 0.00 )

I ( 1 )

a?†Ln L

-11.49 ( 0.00 )

-6.48 ( 0.00 )

-9.56 ( 0.00 )

-5.34 ( 0.00 )

25.66 ( 0.00 )

24.57 ( 0.00 )

I ( 1 )

Notes: LLC, IPS, MW and indicated the Levin et Al. ( 2002 ) , Im et Al. ( 2003 ) and Maddala and Wu ( 1999 ) panel unit root and stationary trials. All trials examine the void hypothesis of non-stationary ( unit root ) . The four variables were grouped into one panel with sample N= 4, T=22. The parenthesized values are the chance of rejection. Probabilities for the MW ( ADF Fisher Chi-square ) and PP ( Fisher chi-square ) trials are computed utilizing an asymptotic I‡2 distribution, while the other trials follow the asymptotic normal distribution.

Cointegration

Table 2-a and 2-b nowadays the consequences of Pedroni Cointegration for 1972-85 and 1986-2007 severally. Pedroni provides seven statistics for trials of the void hypothesis of no cointegration in heterogenous panels. Under this technique two theoretical accounts are developed theoretical account ( 1 ) with no deterministic tendency and theoretical account ( 2 ) with deterministic intercept and tendency. Results show that void hypothesis of no-cointegration is rejected for seven statistics for both theoretical accounts at 5 and 10 per centum degree demoing grounds of cointegration for the group as a whole and single states of the panel for both clip spans.

TABLE II-a

Heterogeneous Panel Cointegration Results 1972-85

Trial

Statisticss

No Deterministic Trend

Deterministic Intercept and Trend

Panel Cointegration Statistics ( Within-Dimension )

Weighted

Weighted

Panel v-statistics

-0.141 ( A 0.095 )

-0.326 ( 0.078 )

0.810 ( 0.107 )

-0.636 ( 0.125 )

Panel pp type i??-statistics

0.782 ( 0.093 )

0.388 ( 0.169 )

1.432 ( 0.143 )

1.257 ( 0.101 )

Panel pp type t-statistics

-0.408 ( 0.107 )

-1.804 ( 0.078 )

-3.034 ( 0.001 )

-1.799 ( 0.079 )

Panel ADF type t-statistics

-1.314 ( 0.068 )

-2.263 ( 0.078 )

-1.409 ( 0.147 )

-3.124 ( 0.003 )

Group Mean Panel Cointegration Statisticss

( Between-Dimension )

Group pp type i??-statistics

1.344 ( 0.141 )

2.251 ( 0.031 )

Group pp type t-statistics

-1.559 ( 0.118 )

-2.089 ( 0.044 )

Group ADF type t-statistics

-4.375 ( 0.000 )

-4.463 ( 0.000 )

Note: This tabular array studies Pedroni ( 2004 ) residuary cointegration trials. The figure of lag shortnesss used in the computation of statistics is fixed at 1. The void hypothesis is no cointegration. Probability values are in parenthesis.

TABLE II-b

Heterogeneous Panel Cointegration Results 1986-2007

Trial

Statisticss

No Deterministic Trend

Deterministic Intercept and Trend

Panel Cointegration Statistics ( Within-Dimension )

Weighted

Weighted

Panel v-statistics

1.144

( 0.007 )

0.973

( 0.048 )

3.123

( 0.003 )

1.231

( 0.106 )

Panel pp type i??-statistics

0.112

( 0.096 )

0.055

( 0.098 )

1.194

( 0.105 )

0.693

( 0.113 )

Panel pp type t-statistics

-0.753

( 0.100 )

-1.009

( 0.139 )

-1.010

( 0.239 )

-1.397

( 0.150 )

Panel ADF type t-statistics

-2.380

( 0.023 )

-1.297

( 0.102 )

-2.211

( 0.034 )

-0.035

( 0.098 )

Group Mean Panel Cointegration Statisticss

( Between-Dimension )

Group pp type i??-statistics

0.954

( 0.053 )

1.550

( 0.119 )

Group pp type t-statistics

-0.630

( 0.121 )

-1.258

( 0.100 )

Group ADF type t-statistics

-1.005

( 0.140 )

-1.522

( 0.105 )

Note: This tabular array studies Pedroni ( 2004 ) residuary cointegration trials. The figure of lag shortnesss used in the computation of statistics is fixed at 1. The void hypothesis is no cointegration. Probability values are in parenthesis.

The consequences of Kao [ 21 ] residuary cointegration trial are reported in table 3 before and after the execution of SAARC. The consequences show that void hypothesis of no cointegration is strongly rejected at one per centum degree of significance. So there exists a long-term relationship among Y, OP, K, and L for the panel of South Asiatic states.

Table III

Kao Residual Cointegration Test Consequence

Model Specification: No Deterministic Trend

Time Time periods

1972-85

1986-2007

ADF t-statistics

-3.5196

( 0.0002 )

-3.7458

( 0.0002 )

Notes: This tabular array studies Kao ( 1999 ) residuary cointegration trial. The figure of lag shortnesss used in the computation of statistics is fixed at 1. The void hypothesis is no cointegration. Probability values are in parenthesis and computed utilizing asymptotic Chi-square distribution.

FMOLS Estimates

Tables 4-a and 4-b exhibit the consequences of the long-term snaps for each state and a panel of these states based on Pedroni ‘s group mean FMOLS calculator for 1972-85 and 1986-2007 severally. The consequences of arrested development equation in which Y was taken as the dependant variable show that the variables OP, K, and L, are statistically important at 1 per centum, 5 per centum and 10 per centum degree of significance.

At state degree, trade liberalisation played negative function that is coefficient of OP is negative for three out of four states in the clip period of 1972-85. Openness played a positive function merely for Pakistan before the execution of SAARC and is statistically important. One major ground for positive impact of OP on GDP for Pakistan is the green revolution. That took topographic point in the late 1960 ‘s and led to the growing of agribusiness merchandises to duplicate about. Whereas, due to the separation of East Pakistan ( Bangladesh ) from West Pakistan ( Pakistan ) severely affected the Bangladesh ‘s economic system as it was left with really few industries and was chiefly an importer state. .

TABLE IV-a

Fully Modified OLS Estimates Results 1972-85

Independent Variables

States

Intercept

a?† Ln OP

a?† Ln K

a?† Ln L

BNG

-28.812 ( -2.17 ) ***

-1.019 ( -5.512 ) *

0.086 ( 0.755 )

2.779 ( 3.176 ) *

IND

39.668 ( 5.449 ) *

-0.256 ( -5.274 ) *

1.224 ( 13.056 ) *

-2.248 ( -4.597 ) *

PAK

-10.058 ( -3.284 ) *

0.434 ( 4.177 ) *

0.587 ( 16.265 ) *

1.243 ( 5.718 ) *

SLK

-0.908 ( -0.808 )

-0.620 ( -3.528 ) *

0.336 ( 2.394 ) **

1.023 ( 1.163 )

Panel Group

5.518 ( 5.847 ) *

-0.129 ( -0.617 ) *

0.499 ( 6.319 ) *

0.407 ( -0.752 ) *

Notes: The figure of lag shortnesss used in computation is 2. The values in parentheses denote the t-statistics following a standard normal distribution. Asterisk * , ** and *** indicate statistical significance at 1 % , 5 % and 10 % degrees, severally.

While, the consequences are assorted for L and K for all four states. The mark of the coefficients of L is positive for three out of four states except India before the execution of SAARC but for Sri lanka L played positive but undistinguished function. Whereas, after the execution of SAARC in the period of 1986-2007 labour played positive and statistically important function for three out of the four states. L responded negative merely for Bangladesh.

After the execution of SAARC openness played positive and statistically important function for all the four states.

TABLE IV-b

Fully Modified OLS Estimates RESULTS 1986-2007

Independent Variables

States

Intercept

a?† Ln OP

a?† Ln K

a?† Ln L

BNG

10.274

( 2.326 ) **

0.148 ( 1.422 ) ***

0.839 ( 6.650 ) *

-0.290 ( -0.860 )

IND

-20.477 ( -8.577 ) *

0.356 ( -7.251 ) *

0.834 ( 35.754 ) *

1.291 ( 13.282 ) *

PAK

-5.591 ( -2.853 ) *

0.192 ( -1.237 ) **

0.716 ( 12.379 ) *

0.776 ( 4.596 ) *

LKA

-12.1929 ( 5.200 ) *

0.430 ( -4.289 ) *

0.700 ( 15.824 ) *

1.265 ( 6.350 ) *

Panel Group

3.450 ( 8.077 ) *

0.034 ( -2.488 ) *

0.914 ( 12.393 ) *

0.120 ( -0.125 ) *

Notes: The figure of lag shortnesss used in computation is 2. The values in parentheses denote the t-statistics following a standard normal distribution. Asterisk * , ** and *** indicate statistical significance at 1 % , 5 % and 10 % degrees, severally.

From the panel consequences of estimated arrested development the coefficients can be interpreted as long-term snaps for group of states. The consequences suggest that 1 percent addition in openness leads to about 0.13 per centum lessening in GDP for clip period 1972-85, whereas after the execution of SAARC in the period of 1986-2007 the overall state of affairs got better as a 1 per centum addition in openness leads to 0.03 per centum addition in GDP. Whereas, the function of capital besides got better after SAARC that is a 1 per centum alteration in capital leads to 0.91 per centum alternatively of 0.50 per centum. But the function of labour decreased from 0.40 to 0.12 that is because of the ground that technological promotions took topographic point of labour.

So it can be clearly concluded that overall state of affairs of the panel of four states got better

Granger Causality Test Results

Table 5-a and 5-b nowadayss the short-term and long-term panel Granger causality consequences from gauging panel based mistake rectification theoretical account set out in Eqs. ( 3 ) , ( 4 ) , ( 5 ) and ( 6 ) . The optimum slowdown length is obtained ( 2 ) by utilizing SIC[ iˆ? ]iˆ?iˆ?iˆ?

TABLE V-a

Panel Granger Causality Results

Beginning of Causation ( Independent Variables )

Short- tally

i?„In Yttrium

i?„Ln OP

i?„In K

i?„Ln L

ECM t-1

Dependent Variable

I§2-statistics ( p-value )

Coefficient

( t-ratio )

i?„Ln Yttrium

## —

5.715 ( 0.457 )

0.815 ( 0.665 )

3.764 ( 0.152 )

-0.357 ( -3.467 ) *

i?„Ln OP

4.867 ( 0.087 ) **

## —

5.737 ( 0.056 ) **

1.184 ( 0.911 )

0.201 ( 2.104 ) *

i?„Ln K

2.601 ( 0.272 )

2.348 ( 0.309 ) *

## —

1.682 ( 0.431 )

-0.301 ( -2.137 ) *

i?„Ln L

0.440 ( 0.802 )

0.388 ( 0.823 ) *

2.991 ( 0.224 ) *

## —

-0.0003 ( -0.402 )

Notes: Wald Chi-square trials reported with regard to short-term alterations while error term coefficient as long-term alterations. Parenthesiss values are the chance of rejection of Granger non-causality. Asterisks * and ** indicate statistically important at 1 % and 5 % degree severally.

The consequences find that there exists important one-sided causal relationship between Y and OP in the short-term before SAARC i.e. in 1972-85 running from Y to OP. This shows that Y caused OP through mistake rectification term. Hence, H2 is verified. Besides, there exists bi-directional causality between OP and K, and uni-directional causality between OP and L and between K and L running from OP to L and from K to L. For GDP equation, the estimated coefficient on the mistake rectification term is negative and statistically important. It shows that short-run accommodations to equilibrium are driven by accommodation back to long-term equilibrium through mistake rectification term.

TABLE V-b

Panel Granger Causality Results

Beginning of Causation ( Independent Variables )

Short- tally

i?„In Yttrium

i?„Ln OP

i?„In K

i?„Ln L

ECM t-1

Dependent Variable

I§2-statistics ( p-value )

Coefficient

( t-ratio )

i?„Ln Yttrium

## —

3.312 ( 0.090 ) ***

0.2110 ( 0.109 ) ***

1.312 ( 0.118 ) ***

-0.102

( 2.674 ) *

i?„Ln OP

2.027 ( 0.042 ) **

## —

3.855 ( 0.145 ) ***

11.264 ( 0.003 ) *

-0.160

( -4.355 ) *

i?„Ln K

2.463 ( 0.091 ) ***

1.621 ( 0.444 )

## —

4.359 ( 0.113 ) ***

0.070

( 1.172 )

i?„Ln L

6.390 ( 0.041 ) **

2.557 ( 0.278 )

2.046 ( 0.359 )

## —

-0.011

( -0.724 )

Notes: Wald Chi-square trials reported with regard to short-term alterations while error term coefficient as long-term alterations. Parenthesiss values are the chance of rejection of Granger non-causality. Asterisks * and ** indicate statistically important at 1 % and 5 % degree severally.

The consequences for clip period after the execution of SARRC find that there exists important bilateral causal relationship between Y and OP, between Y and K and besides between Y and L in the short tally. This shows that both of the variables in each set caused each other through error rectification term. Hence, H2 is verified. While, there exists uni-directional causality between OP and K, OP and L, L and K running from K to OP and from L to OP and from L to K.

For GDP equation, the estimated coefficient on the mistake rectification term is negative and statistically important. It shows that short-run accommodations to equilibrium are driven by accommodation back to long-term equilibrium through mistake rectification term. For OP equation, the estimated coefficient on mistake rectification term is negative and statistically important bespeaking that OP is antiphonal to accommodations back to equilibrium. It specifies long-term feedback between Y and OP.

Drumhead and policy deductions

The end of this survey is to find the way of causal relationship between openness and economic growing in four South Asiatic states for two clip spans that is from 1972-85 and from 1986-2007 to analyze the scenario of economic growing before and after the execution of SARRC.

The panel cointegration technique and panel based mistake rectification theoretical accounts ( ECM ) are used to happen out the causing consequences. Besides, to the full modified ordinary least squares ( FMOLS ) technique is used to happen the long-term relationship.

The consequences of the survey have of import policy deductions. There exists short tally unidirectional causality running from Y to OP but non frailty versa in the clip period of 1972-85. While, negative relation exists between the two in the long-term whereas, in 1986-2007 there exists short-term bi-directional causing between Y and OP. The FMOLS consequences explored positive mark which show that there exists a long-term positive causing between these two variables. The magnitude of long tally snap is non really high after the execution of SAARC but the good point is that it shows positive reactivity in GDP due to Openness. The consequences show that a one per centum addition in OP will take to 0.03 per centum addition in GDP.

To increase this long tally reactivity magnitude the South Asiatic states should present export oriented policies to heighten more and more exports that will assist in the net incomes of foreign exchange and will take to the economic growing quickly. Besides these states should seek to exchange from the exports of natural stuff and semi manufactured goods to concluding merchandise. It is basically needed to alter the export and import forms in the part. Furthermore there is demand of technological promotion, production of capital intensive trade goods alternatively of more labour intensive trade goods and besides there must be proper vocational institutes to develop and increase the figure of skilled labour force which can efficaciously lend towards the trade sector every bit good as GDP of the part.