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Effects of Workers' Remittances and its Volatility on Economic Growth in
South Asia
Article in International Migration · May 2014
DOI: 10.1111/imig.12151
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University of Karachi
Iqra University
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doi: 10.1111/imig.12151
Effects of Workers’ Remittances and its
Volatility on Economic Growth in South Asia
Syed Tehseen Jawaid* and Syed Ali Raza*
ABSTRACT
This study investigates the effect of workers’ remittances and its volatility on economic growth
of five South Asian countries by employing long time series data from 1975 to 2009. Cointegration results confirm a significant positive long run relationship between remittances and
economic growth in India, Bangladesh, Sri Lanka and Nepal, but a significant negative relationship in Pakistan. Conversely, the volatility of workers’ remittances has a negative and significant effect on economic growth in Pakistan, Indian, Bangladesh and Sri Lanka, but a
negative but insignificant impact in Nepal. All sensitivity analyses confirm that the results are
robust. A less volatile inflow of workers’ remittances is growth-enhancing for all countries. It
is suggested that policy makers should make policies to reduce the transaction cost to welcome
remittances into the region. Furthermore, countries like Pakistan should make the policies to
discourage voluntary unemployment.
POLICY IMPLICATIONS
•
•
•
This study show the positive effect of remittances on economic growth in India, Bangladesh, Sri-Lanka and Nepal. These countries should create friendly policies to reduce the
transaction cost to ensure the continuous inflows of workers’ remittances.
Results indicate a negative effect of remittances on economic growth in Pakistan. Remittances are considered an uninterrupted source of income, which may increase voluntary
unemployment, leading to decreased economic growth. The government should make policies to discourage this voluntary unemployment.
Policymakers should create effective systems to ensure this inflow comes through formal
financial channels for better control.
INTRODUCTION
South Asia has been an important source of migrant workers for countries suffering from labour
shortages. Simultaneously, migrant workers’ remittances have become an increasingly important
source of income for the South Asian region. Remittances sent by migrant workers to their home
countries have played an important role in promoting economic development in these countries
(Siddique et al., 2010). Due to its relatively stable nature, remittance is different from other external
capital inflows, such as foreign direct investment, foreign loans, and aid (Shahbaz and Aamir,
2007). Similarly, remittances tend to go up when the recipient economy suffers an economic
* IQRA University, Karachi, Pakistan
Published by John Wiley & Sons Ltd.
© 2014 The Authors
International Migration © 2014 IOM
International Migration
ISSN 0020-7985
2
Jawaid and Raza
recession as result of financial crisis, natural disasters, or political conflicts, as migrants send more
home during hard times to help their compatriots (Orozco, 2003).
A sufficient amount of foreign exchange reserves is very much needed to pay the import bills;
shortages of foreign exchange reserve is a main problem for developing countries. Remittances provide a main source of foreign exchange earnings in developing countries. Increases in the inflows
of remittances provide an opportunity to minimize the problem arising from shortage of foreign
exchange reserves. Most of the empirical studies use the cross sectional and panel data to analyse
the impact of workers’ remittances on economic growth (Faini, 2006; Fayissa and Nsiah, 2010;
Chami et al., 2003; Mohammed, 2009). Furthermore, some time series empirical studies have also
been conducted (Karagoz, 2009; Azam and Khan, 2011; Waheed and Aleem, 2008). Mostly empirical studies found positive impact of workers’ remittances on economic growth (Fayissa and Nsiah,
2010; Faini, 2006; Azam and Khan, 2011). Some empirical studies, however, found negative
impact of workers’ remittances on economic growth (Waheed and Aleem, 2008; Chami et al.,
2003; Karagoz, 2009; Jawaid and Raza, 2012).
From Table 1 it is clear that there has been a significant increase in inflows of remittances in
South Asian countries in the last ten years. One possible reason for this increase may be the massive increase in the immigration of peoples from developing countries to developed countries in last
two decades (World Bank, 2007).
Motivation of the Study
In many studies mentioned in Section 2, cross country data have been used to analyse the relationship between workers’ remittances and economic growth. The use of panel data may be suitable
for answering larger questions on average. It provides only the aggregate average results of a sample but it fails to explain the effect on each individual country for formulating and managing
domestic policies. This article make a unique contribution to the literature on South Asia, being a
pioneering attempt to investigate the impact of workers’ remittance, and its volatility, on economic
growth there by using the long annual time series data from the period of 1975 to 2010 and by
applying more rigorous econometric techniques. Our study is different from the past studies on a
remittances-growth nexus in four novel ways.
First, this study is a pioneering attempt to analyse the volatility of workers’ remittances on economic growth in South Asia. South Asia has been an important source of migrant workers for
countries suffering from labour shortages. Simultaneously, migrant workers’ remittances have
become an increasingly important source of income for the South Asian region. Workers’ remittances are a main source of foreign capital inflow for developing countries. The developing countries depend greatly on such foreign capital inflows; and volatility in these foreign capital inflows
TABLE 1
DECADE WISE SUMMARY STATISTICS
Worker’s Remittances
Countries
1970’s
1980’s
1990’s
2000’s
Pakistan
India
Sri-Lanka
Bangladesh
Nepal
1.023
0.921
0.027
0.096
0.021
2.322
2.481
0.295
0.571
0.045
1.518
6.317
0.735
1.265
0.052
4.971
29.021
2.143
5.475
1.397
Note: All figures are in billion US Dollar.Source: Author’s Construction
© 2014 The Authors. International Migration © 2014 IOM
Effects of Workers’ Remittances on Economic Growth in South Asia
3
may affect their economic growth. Hence it is essential to analyse the effect of workers’ remittances and its volatility on the economic growth in South Asia.
Second, we study the desired relationship of workers’ remittances and economic growth in South
Asia by using the long annual time series data for specifically analysing and estimating the relationship for each country separately. We have included those South Asian countries in the top 10 of
largest recipients of workers’ remittances from 2010 to 2012. According to the World Bank, India,
Pakistan and Bangladesh are in top eight recipients of officially recorded remittances (World Bank,
2011; 2012). In the 2012 report, India, Pakistan and Bangladesh are ranked as first, seventh and
eighth top recipients of workers’ remittances respectively. So it is very important to analyse the
impact of remittances and its volatility on economic growth in the top recipient South Asian countries, by using time series data for each country.
Third, we have not restricted our study to any particular econometric technique to estimate the
long run coefficients, as is mostly done in the past studies (See Srivastava and Chaudhary, 2007;
Ahortor and Adenutsi, 2009; Karagoz, 2009; Paul and Das, 2011; and Azam and Khan, 2011). In
this study, to ascertain the robustness of the results of long-run coefficients, we use two different
sensitivity analyses to check the robustness of initial results, first by using additional variables in
basic models of remittances and volatility of remittances and secondly by using the different proxies of volatility of workers’ remittances.
Fourth, some of the empirical studies have used a bivariate model to examine the relationship
between workers’ remittances and economic growth in South Asian countries (Paul et al., 2011;
Siddique et al, 2012). An econometric issue that arises in bivariate modeling is that of omitted variable bias, which is likely to produce “spurious results” (Stern, 1993; Tang, 2009). We avoid the
problems of this bivariate argument. In this study we use the production function framework and
argue that along with labour and capital, workers’ remittances and their volatility affect the growth
of the economy.
The rest of the article is organized as follows: Section 2 reviews the theoretical and empirical literature on the relationship between workers’ remittances and economic growth. Section 3 discusses
the modeling framework; Section 4 shows estimations and results; Section 5 represents the robustness of results through sensitivity analysis; and final section concludes the study and provides some
policy implications.
REVIEW OF LITERATURE
This section reviews some theoretical and selected cross country as well as time series empirical
studies.
Theoretical Background
Remittances and Growth Theories
Remittances can be presumed likely to have considerable effects on growth rate in receiving countries. There are three main channels, namely capital accumulation, labour force growth and total
factor productivity, through which remittances affect the economic growth of receiving countries.
Remittances and Capital Accumulation
Remittances increase capital accumulation by increasing funds directly to the investor and recipient
household’s rate of accretion of human and physical capital. In contrast, remittances also increase
© 2014 The Authors. International Migration © 2014 IOM
4
Jawaid and Raza
the credit rating of the domestic investor, which leads to
Consequences for decreasing cost of capital are increase in
neously, remittances may increase the economic stability
receiving economy less volatile. This leads to reduced
increases investment.
a decreased cost of capital investment.
borrowing for new investment. Simultaof the receiving country and make the
risk in the receiving economy which
Remittances and Labor Force Growth
Capital inflows in the form of remittances may also have a negative effect on the economic growth
of the receiving country, through a decrease in labour force participation. This inflow may be considered as nothing but income transfer. Many households in the receiving country may consider
this inflow as a substitute for their labour-income. Additionally, this transfer may be beleaguered
by severe moral hazards. This problem may encourage recipients to switch this resource for leisure
consumption; in that way their efforts in the labour market will be fewer.
Remittances and Total Factor Productivity
Remittances may effects total factor productivity by increasing the effectiveness of investment
through changing the eminence of the receiving country’s financial intermediation. If remittances
are considered as capital inflow and recipients are investing on behalf of the remitter, then the
effectiveness of investment is reduced because of informational drawback as compared with formal
domestic financial intermediaries. Remittances also increase the quantity of funds flowing through
the banking system. This flow leads to improved financial expansion and therefore to higher
economic growth.
From the above discussion based on Barajas et al., (2009), it is clear that remittances may have
positive effects on economic growth. However, these effects are very dubious in term of magnitude
and direction. Overall, the effect of remittances on the economic growth of recipient country is
hypothetically ambiguous. Therefore, the relationship between workers’ remittances and economic
growth can be settled only by looking at the empirical evidence.
Empirical Studies
Large number of studies suggest a positive relationship between workers’ remittances and economic
growth. On the other hand some studies show a negative relationship between workers’ remittances
and economic growth. Some selected studies are discussed below.
Bliss (1989) argues that most of the countries do not achieve a higher rate of economic development because of shortage of foreign exchange. Thus the sizeable amounts of remittances may come
in handy here, in filling the gap of foreign exchange receipts. The OECD report (1985) contends
that the most important benefit of workers’ remittances is the supply of additional foreign
exchange. Russel (1986) argues that workers’ remittances are a main source of savings and investments and also raise the standard of living. Adams (1998) concludes that workers’ remittances help
to increase investment by raising the marginal propensity to invest for migrant households in
Pakistan.
On the other side, some researchers find insignificant or negative effects for workers’ remittances on the economic growth of different countries. Becker (1974) argues that workers’ remittances flow is not profit-driven but compensatory. Gilani et al. (1981) conclude that most of the
workers’ remittances in Pakistan are spent on consumption followed by residential investment.
Kritz et al. (1981) argue that remittances raise imports into the country and widen the balance of
payment deficit. Keely and Tran (1989) consider remittances a risky source of finance because
© 2014 The Authors. International Migration © 2014 IOM
Effects of Workers’ Remittances on Economic Growth in South Asia
5
any sort of barrier to migration may reduce the numbers of migrant workers, leading to a sharp
decline in foreign exchange receipts. Sofranko and Idris (1999) argue that workers’ remittances
cannot play a major part in savings because workers’ remittances are mainly used in daily consumption. Kapur and McHale (2003) conclude that workers’ remittances may create idleness
among recipients.
A large numbers of studies have been done on the subject. Table 2 shows the overview of some
selected studies on the relationship between workers’ remittances and economic growth.
Chami et al. (2003) investigate the remittances as a source of capital development by using
the panel data of 113 countries from the period 1970 to 1998. Regression results indicate a
negative and significant long run impact of workers’ remittances on economic growth. Fayissa
and Nsiah (2008) investigate the impact of remittances on economic growth of African countries.
Regression results indicate a positive and significant relationship between remittances and
economic growth.
Waheed and Aleem (2008) investigate the impact of workers’ remittances on economic growth
in Pakistan. Findings indicate a positive and significant relationship between workers’ remittances
and economic growth in short term. On the other hand, a significant negative relationship is found
between workers’ remittances and economic growth in the long run. Qayyum et al. (2008) empirically identify the impact of workers’ remittances on economic growth and poverty reduction in
Pakistan. Results indicate the positive and significant effect of remittances on both economic
growth and poverty reduction.
Karagoz (2009) investigates the long run effect of workers’ remittances on economic growth in
Turkey. Results show the significant negative impact of workers’ remittances on economic growth
there. Mohamed (2009) investigates the effect of workers’ remittances on economic growth in
seven MENA countries, where results indicate significant positive relationship between remittances
and economic growth. Fayissa and Nsiah (2010) empirically examine the long run impact of
workers’ remittances on economic growth in Latin American countries. Regression results indicate
a significant positive long run relationship exists between workers’ remittances and economic
growth.
Das and Chowdhury (2011) empirically examine the impact of workers’ remittances on economic
growth in 11 top remittance-receiving developing countries. Results indicate significant positive
relationship between remittances and economic growth. They suggested that policy makers in
developing countries should formulate policies to utilize the remittance resources into more productive sectors. Siddique et al. (2012) examine the causal relationship between workers’ remittances
and economic growth in South Asian countries. Results indicate that no causal relationship exists
between workers’ remittances and economic growth in India; unidirectional causality is found
between workers’ remittances to economic growth in Bangladesh and bidirectional causality
between remittances and economic growth in Sri Lanka.
Yasmeen et al. (2011) investigate the effect of workers’ remittances on total consumption and
private investment in Pakistan. Regression results indicate significant positive relationship of workers’ remittances with both private investment and total consumption. They recommend that developing countries may ask developed countries to soften policies for workers’ remittance in favour of
their countries. Azam and Khan (2011) investigate the relationship between workers’ remittances
and economic growth in Azerbaijan and Armenia. Results indicate a positive and significant relationship of workers’ remittances with economic growth.
Jawaid and Raza (2012) investigate the effect of workers’ remittances on economic growth in
China and Korea. Results indicate positive and significant impact of workers’ remittances on economic growth in Korea, while a significant negative relationship is found in China. On the other
hand, in the short run, a significant positive relationship is found in Korea. The results of China
were found insignificant.
© 2014 The Authors. International Migration © 2014 IOM
© 2014 The Authors. International Migration © 2014 IOM
113 countries, 1970 to 1998
101 developing countries, 1970 to 2003
64 countries, 1980 to 2004
Nepal, 1975 to 2005
17 countries, 1993 to 2003
37 African countries, 1980 to 2004
39 countries, 1980 to 2004
Pakistan, 1981 to 2006
Pakistan, 1973 to 2007
49 Countries, 1970 to 2005 cross section data
Turkey, 1970 to 2005
73 Countries, 1975 to 2002
Nepal, 1991 to 2005
31 Developing countries, 1996 to 2006
84 Countries, 1970 to 2004
162 countries, 1970 to 2003
7 MENA countries, 1975 to 2006
15 Countries, 1978 to 2001
20 Asian countries, 1988 to 2007
25 Latin America and certain countries in the Caribbean (LAC),1970 to 2002
18 Latin American countries, 1980 to 2005
11 top remittances recipient developing countries, 1985 to 2009
Bangladesh, 1979 to 2009
24 Asia and Pacific Countries, 1980to 2009
Ghana, 1987 to 2004
Azerbaijan and Armenia, 1995 to 2010
36 Sub Saharan African countries, 1990 to 2008
122 Countries, 1980 to 2005
Korea, 1980 to 2009
China, 1980 to 2009
50 Countries, 1970 to 2004
Chami et al. (2003)
IMF (2005)
Faini (2006)
Srivastava and Chaudhary (2007)
Jongwanich (2007)
Fayissa and Nsiah (2008)
Pradhan et al. (2008)
Waheed and Aleem (2008)
Qayyum et al. (2008)
Le (2009)
Karagoz (2009)
Giuliano and Ruiz-Arranz (2009)
Majagaiya (2009)
Ahortor and Adenutsi (2009)
Barajas et al. (2009)
Catrinescu et al. (2009)
Mohammed (2009)
Ruiz et al. (2009)
Vargas-Silva et al. (2009)
Mundaca (2009)
Fayissa and Nsiah (2010)
Das and Chowdhury (2011)
Paul and Das (2011)
Imai et al. (2011)
Adenutsi (2011)
Azam and Khan (2011)
Lartey (2011)
Zuniga (2011)
Jawaid and Raza (2012)
Jawaid and Raza (2012)
Senbeta (2013)
Source: Author’s Construction
Sample
Author(s) and Year of Publication
Negative
Insignificant
Positive
Positive
Positive
Positive
Positive
Negative
Positive
Negative
Negative
Positive
Positive
Positive
Negative
Positive
Positive
Positive
Positive
Positive
Positive
Positive
Positive
Positive
Positive
Positive
Positive
Positive
Positive
Negative
Positive
Results
AN OVERVIEW OF SOME SELECTED STUDIES ON THE RELATIONSHIP BETWEEN WORKERS’ REMITTANCES AND ECONOMIC GROWTH.
TABLE 2
6
Jawaid and Raza
Effects of Workers’ Remittances on Economic Growth in South Asia
7
EMPIRICAL FRAMEWORK
After reviewing the empirical studies, the models to examine the relationship between the volatility
of workers’ remittances and economic growth are derived by using the production function framework. The general production function is:
Yt ¼ b0 þ b1 Lt þ b2 Kt þ b3 Rt þ et
ð3:1Þ
whereas ɛt is the error term, R represents the workers’ remittances and its volatility. (This study
examines two vectors. The first vector includes real GDP, labour, capital and workers’ remittances.
The second vector includes the same variables as in the first vector, except that workers’ remittances are replaced by volatility of workers’ remittances). The positive sign is expected for L and
K while, the sign of R is to be determined. Different annual time series data have been used for different countries (for Pakistan, India and Bangladesh (1980–2009); for Sri Lanka (1985–2009) and
for Nepal (1975–2009). It all depends on availability of data). All data are gathered from the official database of World Bank (http://data.worldbank.org/indicator). All variables are used in logarithm form. The volatility of workers’ remittances is measured by Generalized Autoregressive
Conditional Heteroscedasticity (GARCH). Bleaney and Greenaway (2001) and Jawaid and Haq
(2012) have adopted the same method for measuring volatility.
Augmented Dickey Fuller (ADF) (Dickey and Fuller, 1979) and Phillip Perron (PP) (Phillips and
Perron, 1988) unit root test are used to examine the stationary properties for a longterm relationship. Augmented Dickey Fuller (ADF) test is based on equation given below:
DYt ¼ a0 þ a1 Yt1 þ
k
X
dj DYtj þ et
j¼1
where ɛt is pure white noise error term, D is first difference operator, Yt is a time series, a0 is the
constant and k is the optimum numbers of lags of the dependent variable. ADF test determines
whether the estimates of coefficients are equal to zero. ADF test provides cumulative distribution
of ADF statistics. The variable is said to be stationary, if the value of the coefficient a1 is less than
critical values from fuller table. The Phillip and Perron unit root test is also based on t-statistics
associated with estimated coefficients of q∗. Phillip and Perron unit root test equation is given
below:
DYt ¼ a þ q Yt1 þ et
The present study employs the Johansen and Juselius (J.J., 1990) cointegration technique to analyse the existence of a long run relationship of workers’ remittances and volatility of workers’
remittances with economic growth in South Asian countries. The Johansen and Juselius cointegration test is based on ktrace and kmax statistics. First “trace test” cointegration rank ‘r’ is as follow:
ktrace ¼ T
n
X
lnð1 kj Þ
j¼rþ1
Second, kmaxmaximum number of cointegrating vectors against r + 1 is presented in following way:
kmax ðr; r þ 1Þ ¼ T lnð1 kj Þ
The null hypothesis of the Johansen and Juselius cointegration is that there is no long run cointegration among the variables. If null hypothesis is rejected, that means there is significant long run
© 2014 The Authors. International Migration © 2014 IOM
8
Jawaid and Raza
relationship among the series of variables and vice versa. We use two different sensitivity analyses
to check the robustness of initial results. First, by using additional variables in basic models, and
secondly by using the different proxies of volatility of workers’ remittance.
ESTIMATIONS AND RESULTS
Augmented Dickey Fuller (ADF) and Phillip Perron (PP) unit root test are used to examine the stationary properties for a longterm relationship. Table 3 represents the results of unit root test.
The results of Table 3 confirm the stationary of all variables at first difference in all countries.
This means that the combination of one or more series may exhibit a long run relationship among
the variables of equation 3.1.
Table 4 represents long run relationship among considered variables. Initial Results show that
autocorrelation exist in the model of Pakistan, India & Sri Lanka. Cochrane and Orcutt (1949)
iterative procedure has been used to remove autocorrelation in these models. Results indicate that
TABLE 3
STATIONARY TEST RESULTS
Country
Pakistan
India
Bangladesh
Sri Lanka
Nepal
ADF test
PP test
I(1)
I(1)
Variables
C
C&T
C
Y
L
K
R
VR
Y
L
K
R
VR
Y
L
K
R
VR
Y
L
K
R
VR
Y
L
K
R
VR
-3.954
-5.011
-3.433
-4.132
-5.064
-3.970
-3.780
-4.310
-6.280
-6.470
-3.950
-4.670
-3.530
-4.270
-5.857
-3.980
-6.418
-3.629
-5.261
-4.920
-2.937
-5.321
-2.786
-4.914
-4.710
-4.342
-5.348
-3.431
-4.456
-5.148
-4.940
-4.120
-4.790
-7.180
-6.329
-5.210
-5.950
-3.500
-5.890
-6.203
-4.944
-6.447
-4.050
-5.435
-4.420
-3.349
-5.599
-3.568
-5.030
-4.597
-3.921
-5.010
-3.014
-4.132
-5.063
-3.970
-3.830
-4.310
-6.160
-8.279
-3.950
-4.630
-3.560
-4.210
-5.857
-3.980
-8.939
-3.601
-5.308
-4.732
-3.655
-5.326
-5.814
-4.898
-6.733
C&T
-4.336
-5.384
-3.486
-4.385
-5.185
-4.940
-4.260
-4.790
-7.130
-8.101
-5.210
-5.910
-3.500
-5.020
-6.363
-5.129
-11.878
-4.180
-5.674
-4.552
-3.578
-8.664
-6.120
-5.415
-6.616
Notes: The critical values for ADF and PP tests with constant (c) and with constant & trend (C&T) 1%, 5%
and 10% level of significance are -3.711, -2.981, -2.629 and -4.394, -3.612, -3.243 respectively.
All variables of all selected countries are non-stationary at level.
VR shows the volatility of workers’ remittances
Source: Author’s estimations.
© 2014 The Authors. International Migration © 2014 IOM
Effects of Workers’ Remittances on Economic Growth in South Asia
9
significant positive long run relationships exist between workers’ remittances and economic growth
in India, Bangladesh, Sri Lanka and Nepal.
The findings are consistent with Fayissa and Nsiah (2010), Faini (2006), and Azam and Khan
(2011). The increase in remittances leads to increase in the purchasing power that will increase
total consumption. Investment and production are also increased by the rise in the transferred
amount of workers’ remittances. The increases in consumption, investment and production are the
major signs of economic development and all are increasing by the efficient usage of workers’
remittances.
On the other hand, results show the negative and significant long run relationship between workers’ remittances and economic growth in Pakistan. The findings are consistent with previous results
of Pakistan (Waheed and Aleem, 2008) and other studies (Chami et al., 2003) and Karagoz, 2009).
The possible reason for this negative relationship might be the luxurious consumption spending on
imported items, hence the decline in demand for domestically produced goods and domestic investment, which retards economic growth. The brain drain may be the another possible reason for the
negative relationship between workers’ remittances and economic growth. The highly skilled workers, when they leave the country, will not only cause a shortage of human capital but also transfer
their financial capital from the country, which limits domestic resource mobilization. Furthermore,
a continuous inflow of workers’ remittances considered as an uninterrupted source of income may
increase voluntary unemployment in the country, which leads to a decrease in economic growth in
Pakistan. However, the coefficient of R in Sri Lanka is 0.408 which shows the most efficient utilization of this inflow.
Table 5 shows estimates of the model of the volatility of workers’ remittances. Results indicate
the significant negative effect of the volatility of workers’ remittances on economic growth in
Pakistan, India, Bangladesh and Sri Lanka. On the other hand, negative but insignificant effect of
the volatility of workers’ remittances on economic growth is found in Nepal. Overall results
confirm that the volatility of workers’ remittances is proved to be an unfavourable condition for
economic growth in selected South Asian countries. Furthermore, the coefficient of R in Sri Lanka
is 0.957 which shows the most affected country due to volatilities of workers’ remittances.
Augmented Dickey Fuller (ADF) and Phillips Perron (PP) tests are used to analyse the unit root
test for stationary of residuals. The results of Tables 6 and 7 show that residuals of both models,
namely workers’ remittances and volatility of workers’ remittances of all countries, are stationary at
level and variables are at first difference. This confirms the valid long run relationship that exists
between the considered variables in selected South Asian countries.
Johansen and Juselius (1990) cointegration method is used to estimate the long run relationship
among the variables of equation 3.1. Table 8 and 9 represents the calculated and critical values of
Trace statistics and Maximum Eigen value statistics.
Results indicate the rejection of null hypothesis of no cointegration in models of workers’ remittances and its volatility at significance level of 5 per cent in all five countries, in favour of an alternative hypothesis that is the existence of one or more cointegrating vectors. Both residual
stationary test and cointegration test confirms the existence of a long run relationship among variables of equation 3.1 in all countries. To check the short run relationship we employed the error
correction model developed by Engle and Grange (1987), but the results were insignificant for all
selected South Asian countries.
SENSITIVITY ANALYSIS
In this section two different sensitivity analyses have been performed to check the robustness of
the initial results, first by using additional variables in basic models, and secondly by using the
different proxies of volatility of workers’ remittance.
© 2014 The Authors. International Migration © 2014 IOM
878.283(0.000)
Source: Authors’ estimation.
F-stats (prob)
D.W stats
1.710
R
0.989
0.321
0.043
K
Adj. R
5.160
3.186
1.125
2
5.150
0.432
C
L
15.809
t-stats
Coeff.
Variables
Pakistan
1.583
0.998
2.394
11.909
9.051
4.114
t-stats
5008.818(0.000)
0.033
0.429
1.072
1.494
Coeff.
India
0.056
0.219
0.019
2.200
1.641
0.998
1.984
2.172
2.873
10.759
t-stats
4582.622(0.000)
Coeff.
Bangladesh
0.408
0.037
0.843
2.404
1.362
0.981
4.983
1.756
1.943
4.631
t-stats
424.011(0.000)
Coeff.
Sri Lanka
LONG TERM DETERMINANTS OF ECONOMIC GROWTH WITH WORKERS’ REMITTANCES
TABLE 4
0.049
0.705
0.738
2.668
1.537
0.997
1.744
19.104
2.121
9.869
t-stats
4692.101(0.000)
Coeff.
Nepal
10
Jawaid and Raza
© 2014 The Authors. International Migration © 2014 IOM
5.081
14.574
5.265
3.197
0.664
1.073
0.352
0.098
C
L
K
R
Adj. R2
D.W stats
F-stats (Prob.)
Source: Authors’ estimation.
0.993
2.291
2354.746 (0.000)
t-stats
Coeff.
Variables
Pakistan
6.645
14.561
12.036
2.084
t-stats
0.998
1.817
5511.967 (0.000)
2.025
0.418
1.235
0.404
Coeff.
India
5.999
3.462
1.786
2.357
t-stats
0.998
1.559
3526.587 (0.000)
1.842
0.026
0.214
0.094
Coeff.
Bangladesh
1.044
12.580
8.032
3.585
t-stats
0.989
1.558
770.471 (0.000)
0.263
1.729
0.061
0.957
Coeff.
Sri Lanka
LONG TERM DETERMINANTS OF ECONOMIC GROWTH WITH VOLATILITY OF WORKERS’ REMITTANCES
TABLE 5
16.568
5.089
17.901
0.733
t-stats
0.998
1.663
4549.459 (0.000)
2.253
1.127
0.709
0.385
Coeff.
Nepal
Effects of Workers’ Remittances on Economic Growth in South Asia
© 2014 The Authors. International Migration © 2014 IOM
11
12
Jawaid and Raza
TABLE 6
RESIDUALS STATIONARY TEST RESULTS OF WORKERS’ REMITTANCES MODELS
Country
Pakistan
India
Bangladesh
Sri Lanka
Nepal
Test
Without Trend
With Trend
ADF Test
PP Test
ADF Test
PP Test
ADF Test
PP Test
ADF Test
PP Test
ADF Test
PP Test
3.728
3.632
2.923
3.046
4.242
4.253
3.361
3.361
4.799
4.815
3.678
3.646
3.602
3.452
4.203
4.213
3.320
3.320
4.762
4.761
Note: The critical values for ADF and PP tests with constant (c) and with constant & trend (C&T) 1%, 5%
and 10% level of significance are -3.711, -2.981, -2.629 and -4.394, -3.612, -3.243 respectively.
Source: Authors’ estimation
TABLE 7
RESIDUALS STATIONARY TEST RESULTS OF VOLATILITY OF WORKERS’ REMITTANCES MODELS
Country
Pakistan
India
Bangladesh
Sri Lanka
Nepal
Test
Without Trend
With Trend
ADF Test
PP Test
ADF Test
PP Test
ADF Test
PP Test
ADF Test
PP Test
ADF Test
PP Test
4.067
3.964
4.863
4.522
4.144
4.130
3.433
3.895
4.576
4.531
3.885
3.862
4.819
4.413
4.196
4.082
3.372
3.847
4.526
4.475
Note: The critical values for ADF and PP tests with constant (c) and with constant & trend (C&T) 1%, 5%
and 10% level of significance are -3.711, -2.981, -2.629 and -4.394, -3.612, -3.243 respectively.
Source: Authors’ estimation.
Additional Variables
The degree of confidence among the relationship between dependent and independent variables is
tested through sensitivity analysis. If the coefficient of independent variable gives same sign and
significance after putting additional variables in the basic model, then they refer that the results are
robust. The results are ‘refer to fragile’ if coefficient of independent variables do not give same
sign or significance or both after putting additional variable in the basic model (Levine and Renelt,
1992). We used the following model to perform sensitivity analysis.
Yt ¼ b0 þ b1 Lt þ b2 Kt þ b3 Rt þ b3 Zt þ 62t
ð5:1:1Þ
where ɛt represents the error term and Z represents a subset of variables that are theoretically
related to the economic growth. In our core model, foreign direct investment (FDI), education
expenditure (EEX), life expectancy (LEX), export as percentage of GDP (EXP) and fertility rate
© 2014 The Authors. International Migration © 2014 IOM
13
Effects of Workers’ Remittances on Economic Growth in South Asia
TABLE 8
COINTEGRATION TEST RESULTS OF WORKERS’ REMITTANCES MODELS
Country
Pakistan
India
Bangladesh
Sri Lanka
Nepal
Null Hypothesis
No. of CS(s)
None *
At most
None *
At most
None *
At most
None *
At most
None *
At most
1
1
1
1
1
Trace Statistics
5% critical
values
Max. Eigen Value
Statistics
5% critical
values
71.783
39.293
58.400
19.552
48.481
19.867
56.174
19.835
86.290
41.488
63.876
42.915
40.175
24.276
40.175
24.276
40.175
24.276
63.876
42.915
32.490
15.539
38.848
9.327
28.614
13.294
36.339
14.328
32.490
15.539
32.118
25.823
24.159
17.797
24.159
17.797
24.159
17.797
32.118
25.823
Source: Authors’ estimation.
TABLE 9
COINTEGRATION TEST RESULTS OF VOLATILITY OF WORKERS’ REMITTANCES MODELS
Country
Pakistan
India
Bangladesh
Sri Lanka
Nepal
Null Hypothesis
No. of CS(s)
None *
At most
None *
At most
None *
At most
None *
At most
None *
At most
1
1
1
1
1
Trace Statistics
5% critical
values
Max. Eigen
Value Statistics
5% critical
values
74.673
38.730
72.525
22.586
46.318
16.169
88.723
30.794
55.448
24.082
63.876
42.915
40.175
24.276
40.175
24.276
63.876
42.915
40.175
24.276
35.943
21.644
49.939
10.696
30.149
10.000
57.929
13.942
31.365
13.394
32.118
25.823
24.159
17.797
24.159
17.797
32.118
25.823
24.159
17.797
Source: Authors’ estimation.
(FER) are considered as determinants of economic growth. The results of sensitivity analysis are
reported in Table 10, where we have shown the coefficient of workers’ remittances on economic
growth with the inclusion of other relevant variables in the basic model.
It is confirmed from Table 10 and 11 that the coefficient of workers’ remittances and its volatility
remains the same sign and significance, despite the inclusion of relevant variables in the basic
model. Consequently it can be concluded that the relationship between remittances, their volatility,
and economic growth in South Asian countries, is robust.
Different Proxies of Volatility
The different measures of volatility used in empirical studies include: standard deviation, generalized autoregressive conditional heteroscedasticity, five-year moving averages, and five-year moving
standard deviations (Geol and Ram, 2001). To test the robustness of volatility of workers’ remittances, we considered a five-year moving standard deviation (MSTD) and five-year moving average
© 2014 The Authors. International Migration © 2014 IOM
0.040
0.034
0.054
0.043
-3.053
-1.976
-1.904
-2.619
-2.098
0.990
0.989
0.987
0.989
0.989
0.989
Adj R2
Source: Authors’ estimation
FER
Model 5
EXP
Model 4
LEX
Model 3
EEX
Model 2
FDI
Model 1
0.032
-3.186
0.043
Basic
Model
t-stats.
of R
Coeff.
Variables
Pakistan
701.841
649.502
943.974
632.575
684.170
878.284
F-stats
0.038
0.036
0.034
0.034
0.036
0.033
Of R
Coeff.
2.571
2.366
2.424
2.364
2.593
2.393
t-stats.
India
0.998
0.998
0.998
0.998
0.998
0.998
Adj R2
3742.581
3646.642
3662.535
3620.443
3798.292
5008.821
F-stats
0.056
0.053
0.059
0.059
0.055
0.056
of R
Coeff.
1.933
1.890
2.044
2.109
1.917
1.983
t-stats.
0.998
0.998
0.998
0.998
0.998
0.998
Adj R2
Bangladesh
3514.052
3659.287
3549.578
3712.411
3557.220
4582.622
F-stats
0.470
0.433
0.412
0.404
0.440
0.408
of R
Coeff.
4.678
5.112
5.828
4.547
5.781
4.983
t-stats.
0.981
0.981
0.986
0.981
0.984
0.981
Adj R2
Sri Lanka
322.595
321.087
429.764
303.212
380.351
424.012
F-stats
0.049
0.049
0.067
0.049
0.051
0.049
of R
Coeff.
RESULTS OF SENSITIVITY ANALYSIS WITH ADDITIONAL VARIABLES OF WORKERS’ REMITTANCES MODEL
TABLE 10
1.768
1.787
1.769
1.989
1.767
1.743
t-stats.
Nepal
0.998
0.998
0.997
0.998
0.998
0.998
Adj R2
3388.741
3456.244
3456.241
4527.078
3412.111
4692.120
F-stats
14
Jawaid and Raza
© 2014 The Authors. International Migration © 2014 IOM
0.087
0.044
0.043
0.057
2.991
1.847
1.863
2.140
5.629
3.197
0.098
0.065
t-stats.
of R
Coeff.
0.997
0.995
0.995
0.989
0.997
0.993
Adj R2
Source: Authors’ estimation
FER
Model 5
EXP
Model 4
LEX
Model 3
EEX
Model 2
FDI
Model 1
Model
Basic
Variables
Pakistan
2056.398
1798.229
1823.490
2109.213
1932.672
2354.746
F-stats
0.268
0.426
0.344
0.422
0.391
0.404
Of R
Coeff.
2.389
2.196
4.702
1.874
2.104
2.084
t-stats.
India
0.998
0.998
0.998
0.998
0.998
0.998
Adj R2
5787.851
4183.267
4715.695
3959.084
4526.812
5511.971
F-stats
-0.093
-0.048
-0.071
-0.038
-0.072
-0.094
of R
Coeff.
-2.530
-1.977
-3.114
-3.597
-2.434
-2.357
t-stats.
0.998
0.998
0.998
0.996
0.998
0.998
Adj R2
Bangladesh
3130.210
2875.652
2721.181
2807.858
2718.544
3526.593
F-stats
-0.398
-0.836
-0.371
-0.957
-0.732
-0.957
of R
Coeff.
-2.960
-4.777
-3.937
-4.045
-8.149
-3.585
t-stats.
0.990
0.990
0.989
0.990
0.989
0.989
Adj R2
Sri Lanka
457.638
621.249
573.260
595.172
589.718
770.471
F-stats
-0.38
-0.378
-0.438
-0.701
-0.395
-0.385
of R
Coeff.
-0.708
-0.713
-0.809
-1.454
-0.707
-0.733
t-stats.
Nepal
RESULTS OF SENSITIVITY ANALYSIS WITH ADDITIONAL VARIABLES OF VOLATILITY OF WORKERS’ REMITTANCES MODEL
TABLE 11
0.998
0.998
0.998
0.998
0.998
0.998
Adj R2
3282.710
3344.815
4294.882
3318.324
3281.392
4549.461
F-stats
Effects of Workers’ Remittances on Economic Growth in South Asia
© 2014 The Authors. International Migration © 2014 IOM
15
16
Jawaid and Raza
TABLE 12
TEST FOR ROBUSTNESS OF VOLATILITY OF WORKERS’ REMITTANCES MODEL BY DIFFERENT
PROXIES
GARCH
Variables
Pakistan
India
Bangladesh
Sri Lanka
Nepal
MSTD
MAVG
Coeff.
of R
t-stats
Prob.
Coeff.
of R
t-stats
Prob.
Coeff.
of R
t-stats
Prob.
0.098
0.404
0.094
0.957
0.385
3.197
2.084
2.357
3.585
0.733
0.004
0.049
0.026
0.002
0.470
0.094
0.072
0.043
0.169
0.494
1.810
2.950
2.451
2.247
1.005
0.082
0.008
0.024
0.036
0.326
0.083
0.026
0.021
0.096
0.184
2.223
2.162
2.654
2.673
0.485
0.038
0.042
0.015
0.014
0.633
Source: Authors’ estimation.
(MAVG) as other measures of volatility of workers’ remittances. Table 12 represents the results of
sensitivity analysis of volatility of workers’ remittances.
Table 12 clearly confirms that it does not matter what proxy of volatility of workers’ remittances
is considered, the results showed the same sign and significance level of volatility of workers’
remittances on economic growth. This confirms that our initial results are robust.
CONCLUSION AND POLICY RECOMMENDATIONS
This study investigates the effect of workers’ remittances and their volatility on the economic
growth of five South Asian countries, namely Pakistan, India, Bangladesh, Sri Lanka and Nepal,
by employing long time series data from 1975 to 2009. Cointegration results confirm that there
exists significant positive long run relationship between remittances and economic growth in India,
Bangladesh, Sri Lanka and Nepal while, significant negative relationships exist between workers’
remittances and economic growth in Pakistan. Conversely, the volatility of workers’ remittances
has a negative and significant effect on economic growth in Pakistan, India, Bangladesh and Sri
Lanka, while a negative but insignificant effect is found in Nepal. Sensitivity analysis confirms that
the results are robust.
The results of this study show the positive effect of workers’ remittances on economic growth in
India, Bangladesh, Sri-Lanka and Nepal. We can probably conclude that inflows of remittances
may increase capital accumulation and the effectiveness of financial intermediation in these countries. These countries should form friendly policies to reduce the transaction cost to ensure the continuous inflows of workers’ remittances. On the other hand, results indicate that the negative effect
of worker’s remittances on economic growth in Pakistan. In the long run, policymakers in Pakistan
should rely more on increasing exports rather than on workers’ remittances as foreign exchange
earnings. The continuous inflow of workers’ remittances regarded as an uninterrupted source of
income may increase voluntary unemployment in the country, which leads to decrease in the economic growth of Pakistan. The government should create policies for the labour market that discourage this voluntary unemployment.
Overall, less volatile inflow of workers’ remittances is growth-enhancing for all countries.
Policymakers of all the countries mentioned should form an effective system to ensure the inflow
of remittances comes through formal financial channels for better control. In addition to this,
workers’ remittances should be efficiently utilized to create sustainable economic growth in these
countries.
© 2014 The Authors. International Migration © 2014 IOM
Effects of Workers’ Remittances on Economic Growth in South Asia
17
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