BANK PARIKRAMA
A Journal of Banking & Finance
Volume
September 2020 - June 2021
XLV (3&4) & XLVI (1&2)
- Mirza Azizul Islam, Ph.D.
The Role and Functions of a Central Bank
- Atiur Rahman, Ph.D.
Ethics in Banking: Interfacing Financial Inclusion for Socially Responsible
Development
- Mousumi Choudhury, Ph.D.
- Ranjit Singh, Ph.D.
Measuring Customers' Satisfaction in Bancassurance Channel: An
Investigation Using Gap Model
- Md. Rostam Ali, Ph.D.
Examining Cost and Accessibility to Institutional Trade Credit by SMEs of
Bangladesh in an Environment of Financial Crisis
- Md. Thasinul Abedin
- Kanon Kumar Sen
- Muhammad Shafiur Rahman
Chowduhury
- Sharmin Akter
Revisiting the Investment-Remittance Nexus in Bangladesh: Do Interest
Rate, Exchange Rate, and Per Capita GDP Matter?
- Mohammad Monirul Islam Sarker
Determinants of Bangladesh’s Trade: A Gravity Model Approach
- Jubair Ahmad
- Tahamina Akter
Effectiveness of Monetary Transmission Mechanism in Bangladesh:
A Price-based Approach
- Mohammad Mohidul Islam
Determining the Monetary Dynamics of Inflation in Bangladesh
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QUARTERLY JOURNAL
OF
BANGLADESH INSTITUTE OF BANK MANAGEMENT
BANK PARIKRAMA
A Journal of Banking & Finance
Volume XLV (3 & 4) & XLVI (1 & 2)
September 2020 - June 2021
BANGLADESH INSTITUTE OF BANK MANAGEMENT
ISSN 1019-7044
Mohammed Farashuddin, Ph.D.
Qazi Kholiquzzaman Ahmad, Ph.D.
Former Governor, Bangladesh Bank and
Chief Advisor and Founder Vice Chancellor
East West University
Chairman, Palli Karma-Sahayak Foundation and
Chairman, Dhaka School of Economics
Mustafa K. Mujeri, Ph.D.
Executive Director, Institute of Inclusive Finance and
Development; and Former Director General,
Bangladesh Institute of Development Studies
Fahad Khalil, Ph.D.
Professor, Department of Economics
University of Washington
United States of America
Motiur Rahman, Ph.D.
JP Morgan-Chase Endowed Professor of Finance and
MBA Director, McNeese State University
United States of America
Barkat-e-Khuda, Ph.D.
Dr. Muzaffer Ahmad Chair Professor, BIBM and Former
Professor of Economics, University of Dhaka
Professor Mustafizur Rahman
Distinguished Fellow, Centre for Policy Dialogue
Chairman
Md. Akhtaruzzaman, Ph.D.
Director General, Bangladesh Institute of Bank Management (BIBM)
Members
Shah Md. Ahsan Habib, Ph.D.
Professor (Selection Grade), BIBM
Md. Nehal Ahmed
Professor (Selection Grade) and Director (Dhaka
School of Bank Management), BIBM
Prashanta Kumar Banerjee, Ph.D.
Professor (Selection Grade), BIBM
Ashraf Al Mamun, Ph.D.
Associate Professor and Director (Research,
Development & Consultancy), BIBM
Ashraf Al Mamun, Ph.D.
Associate Professor and
Director (Research, Development & Consultancy), BIBM
Md. Sirajul Islam
Faculty Member (on Deputation), BIBM and
General Manager, Bangladesh Bank
Md. Mosharref Hossain, Ph.D.
Associate Professor, BIBM
Md. Shahid Ullah, Ph.D.
Associate Professor, BIBM
Md. Mahabbat Hossain, Ph.D.
Assistant Professor, BIBM
Papon Tabassum
Research Officer, BIBM
Bank Parikrama
Volume XLV (3 & 4) & XLVI (1 & 2), September 2020 - June 2021 (pp. 89-120)
Revisiting the Investment-Remittance Nexus in
Bangladesh: Do Interest Rate, Exchange Rate, and
Per Capita GDP Matter?
- Md. Thasinul Abedin
- Kanon Kumar Sen*
- Muhammad Shafiur Rahman Chowduhury*
- Sharmin Akter*
Abstract
Due to the existence of intriguing association and mixed conclusions from the past studies, this study
reexamines the linkage between domestic investment and remittances in Bangladesh by using time series
data from 1976 to 2016. Employing Fully Modified Ordinary Least Square (FMOLS), this study reveals that
remittances unlike domestic interest rate have a significant positive impact on domestic investment in the
long-run. This study also exposes the significant positive impact of both foreign exchange rate and per capita
GDP on remittances in the long-run. Hence over time, depreciation in Bangladeshi currency and an increase
in per capita GDP increase remittances which afterwards increase domestic investment. Significant positive
impact of foreign exchange rate and per capita GDP on remittances and significant positive impact of
remittances on domestic investment in the long-run claim the dominance of investment motive of
remittances. This study suggests that to boost up remittance, depreciation of domestic currency should be in
a convenient level for the greater interest of the economy. Besides the double-digit interest rate affects
negatively to domestic investment and our domestic lending interest rate is not lower enough to increase
domestic investment.
Keywords: Bangladesh, Domestic Investment, Domestic Interest Rate, Foreign Exchange Rate, Per Capita
GDP, Remittances.
JEL Classifications: C01, C02, C31
1. Introduction
The remittances usually inflowing through the formal channels stimulate the
macroeconomic scenarios of a country. For example, boosting savings and
investment, shrinking poverty, and building up capital (Akter, 2016). Increasing
private expenditures and incurring more household consumption, remittances

The authors are Assistant Professor, Department of Accounting, University of Chittagong, Chittagong;
Lecturer, Department of Business Administration in Accounting and Information Systems, Bangladesh
University of Professionals, Dhaka; Assistant Professor, Department of Accounting, University of
Chittagong, Chittagong; and Lecturer, Department of Accounting and Information Systems, Jashore
University of Science and Technology, Jashore; Bangladesh, respectively. The views expressed in this paper
are the authors’ own.
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Bank Parikrama
fuel the grass root development of a country (Connell and Conway, 2000). The
large extent of foreign reserves built from remittances makes the domestic
currency stronger (Taylor and Wyatt, 1996). Moreover, remittances improve the
balance of payment deficits, sanction and education, infrastructure development,
and quality of life (Matuzeviciute and Butkus, 2016). However, the effect of
remittances swells inflation in an economy (Chami et al., 2003; Faini, 2002;
Narayan et al., 2011; Pradhan et al., 2008). Hence, remittances have both positive
and negative impact on the economy. Previous empirical studies conclude that
the influence of remittances highly depends on country specific factors such as
government policies, restriction in the flow of remittances, investment
environment, politics, and corruption.
75% of worldwide remittances come into developing countries (MRF, 2016).
In 2017, estimated remittances to developing countries are 465.7 billion USD;
3.7% greater than those of 2016, whereas remittances into South Asia are 129.3
billion USD; 4.6% greater than those of 2016. Bangladesh has placed fifth in the
stocks of emigrants in 2013 (MRF, 2016) and among the top remittances
receiving countries, Bangladesh has placed tenth in 2015. Moreover, Bangladesh
has among the lowest cost corridors for sending remittances from Singapore to
Bangladesh and from Saudi Arabia to Bangladesh; increasing the remittances to
the economy (MRF, 2016). In 1976, the amount of remittances in Bangladesh
was only USD 24 million (Barua et al., 2007) whereas in 2016, the amount of
remittances was USD 13.6 Billion (source: Bangladesh Bank). This high growth
rate of remittances contributes into the domestic investment to change the
economic structure of Bangladesh (Barua et al., 2007). The trends of domestic
investment, remittances, foreign exchange rate (BDT/USD), per capita GDP, and
the domestic interest rate are given below:
Abedin, Sen, Chowduhury and Akter: Revisiting the Investment-Remittance Nexus
Figure 1: Remittances
Figure 2: Domestic Investment
% of GDP
% of GDP
15
10
5
0
1960
1980
2000
1976-2016
40
20
1980 2000
1976-2016
2020
Source: WBDI
Figure 3: Lending Interest Rate
Figure 4: Per Capita GDP
1500
In USD
In %
60
0
1960
2020
Source: WBDI1
20.0000
15.0000
10.0000
5.0000
0.0000
1960
91
1980 2000
1976-2016
Source: WBDI
2020
1000
500
0
1960
1980 2000
1976-2016
2020
Source: WBDI
BDT/USD
Figure 5: Foreign Exchange Rate (BDT/USD)
100
80
60
40
20
0
1960
1980
2000
1976-2016
2020
Source: WBDI
From above figures, it has been observed that remittances in Bangladesh
have an increasing trend from 1976 to 2016. Domestic investment and per capita
GDP have an upward trend from 1976 to 2016. An increase in domestic
investment can be supported by an increase in remittances. For example, as the
local currency has been depreciated from 1976 to 2016, it is seemingly expected
that due to depreciation in Bangladeshi currency, more remittances inflow into
1
World Bank Development Indicators
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Bank Parikrama
the Bangladesh economy and as a result domestic investment goes up due to
increase in the households’ savings. However, the relationship is not that much
straight forward rather it is more inter-winded. For example, due to depreciation
in Bangladeshi currency, households’ expenditure on import goes up due to
increase in import costs. The relative increase in import cost increases the
inflation leading to a subsequent increase in the interest rate. However, in
Bangladesh, both inflation and lending interest rates are decreasing over years.
Even real lending interest rate is also in decreasing trend. Therefore, among
numerous factors affecting lending interest rate of an economy, increased import
cost, theoretically a contributing factor, might affect inflation rate and thereby to
the lending interest rate of Bangladesh. The high interest rate negatively affects
the domestic investment. The domestic investment is also affected by the fall
households’ savings due to increase in households’ consumption expenditure. It
is well known in the economic literature that a country’s part of domestic
investment is usually backed by the country’s domestic savings. Even though
remittances increase as a result of the depreciation in foreign exchange rate, the
households do not change the consumption behavior overnight. In fact, the
households do not significantly increase their consumption expeditiously. As a
result, the increase in the households’ savings due to increase in remittances
increases the domestic investment. Hence, the domestic investment increases due
to depreciation in foreign exchange rate, if and only if the impact of households’
savings can outweigh the impact of domestic interest rate. The empirical
literatures (Hall, 1977; Osundina and Osundina, 2016; Wuhan et al., 2015) have
explained the negative relationship between domestic investment and interest
rate. Moreover, domestic investment and per capita GDP have a common upward
trend from 1976 to 2016. Therefore, it will not be unwise to expect a positive
relationship between domestic investment and per capita GDP.
There is dearth of literature that per capita GDP indicating the economic
condition of a country has a positive impact on remittances. Most of the studies
considered remittances as determinant of per capita GDP. However, per capita
GDP may have either positive or negative impact on remittances inflow. Now the
question is how? It depends on three motives: altruistic motive, insurance motive,
and investment motive. Migrants use income level to judge the economic
Abedin, Sen, Chowduhury and Akter: Revisiting the Investment-Remittance Nexus
93
condition of home country with that of the host country. For example, due to
decrease in income level, migrants send more remittances from altruistic motive
of remittances. If the altruistic motive dominates the remitting behavior, the
expected sign of this variable is negative. For example, when the income of the
family in the home country decreases, the migrant will send more money in order
to assure the same level of the utility for his family. Moreover, the migrants
transfer remittances for the welfare (health and education, etc.) of wives and
children. However, given the dominance of altruistic motive, the depreciation in
local currency avails less remittances in dollars that ensure same level of national
currency. When the income of the family in the home country increases, the
migrant will send more money for financial investments or for inheritance
reasons, because his potential of inheritance will increase. This is known as
investment motive. For example, if a country like Bangladesh is on the
development stage, the people of Bangladesh working abroad may send money
to Bangladesh to invest into real estate (buying home) and other sectors offering
better returns. Since Bangladesh is on the development stage, it is trying to attract
more remittances to improve its socioeconomic structure like construction and
development of schools, colleges, health centers, water supply and sanitation, and
rural electrification etc. Hence, to stimulate the investment motive, the economic
policies designed by the officials in Bangladesh may offer several facilities to the
senders of remittances. For example, banks are crediting the proceeds of
remittances to the beneficiary's account promptly within maximum by 3(three)
days and foreign banks, exchange houses, and subsidiaries or overseas branches
of Bangladeshi scheduled banks are drawing remittance facilities with different
banks in Bangladesh. If the investment motive dominates, the depreciation in
local currency avails more remittances for financial investments or for inheritance
reasons, because his potential of inheritance increases. Therefore, it is expected
to decrease the amount of remittances in the case of an appreciation of the local
currency if investment motive dominates.
In case of insurance motivation, a decrease in the income of the family in the
home country also decreases the remittances. The migrants take time to remit for
offsetting the impact of the appreciation of the local currency (because he must
send more money in the foreign currency). Insurance motive is also based on
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Bank Parikrama
Intra-familial arrangements against income volatility. It is a contractual
arrangement between the migrant and his family. In the rural areas of most
developing counties, where financial and assurance markets are incomplete, the
revenues are subject to risks such as drought and price fluctuations, etc. To
diversify the risk of rural income volatility, families can decide to allocate some
members to urban or foreign migration. Although urban and foreign jobs are also
subject to risks, these risks are independent from the agricultural income
variations. At the beginning of the contract, family pays the migration costs in
exchange of future remittances. In the case of these types of family contracts,
remittances flow to the family in case of agricultural income drops and to the
migrant in case of unemployment (Rapoport and Docquier, 2006).
Due to the existence of a strong relationship between the per capita GDP and
foreign exchange rate, the impacts have been drawn from separate equations. The
growth in per capita GDP reflects the increased productivity and economic
growth, increasing domestic investment. To retain economic growth, a significant
portion of GDP is reinvested (Demers et al., 2003), particularly in frontier and
emerging economies. The foreign exchange rate (BDT/USD) also has significant
impact on domestic investment, depending on the country specific factors (Darby
et al., 2000) such as trade openness, cost of capital goods, higher capital mobility,
and external debt. Again, depreciation in domestic currency has a positive impact
on domestic investment when the import quantity of capital products is larger
relative to the extent of capital mobility (Serven, 1990).
The study contributes into the literature in three ways. Firstly, the study
critically examines the investment, altruistic, and insurance motives unlike the
existing studies (Barua et al., 2007and Hasan, 2008) in Bangladesh. Secondly,
they study proves the dominance of investment motive in Bangladesh employing
large sample size and controlling endogenous feedback. Finally, the study
recommends that lowering the interest rate and encouraging more remittances
boost up domestic investment.
Abedin, Sen, Chowduhury and Akter: Revisiting the Investment-Remittance Nexus
95
2. Literature Review and Hypotheses Development
Several studies have been found inspecting the linkage among remittances,
domestic investment, domestic interest rate, foreign exchange rate, and per capita
GDP. The findings of these studies have been outlined below.
2.1 Domestic Investment and Remittances
Giuliano and Ruiz-Arranz (2006) have found that remittances work as
catalyst to increase domestic investment in a country, particularly countries,
which have a weak financial sector. Zeisemer (2006) has found that remittances
in a country build up a large extent of saving, decrease the rate of interest, and
increase the level of investment. Adams (2006) has found that remittance
receiving households spend more on investment goods and invest more on
entrepreneurial activities than other households. Mundaca (2009) has found that
remittances have a positive impact on investment (see also Gupta et al., 2007).
Still very few studies have been found about the impact of remittances on
domestic investment in Bangladesh.
H1: It is expected that remittances have a positive impact on domestic investment
in the short-run and in the long-run.
2.2 Domestic Investment and Domestic Interest Rate
Wang and Yu (2007) have identified the impact of interest rate on the
domestic investment, which is significant and negative (see also Aysan et al.,
2005; Hall, 1977; Osundina and Osundina, 2016; Wuhan et al., 2015). However,
Larsen (2004) has found positive impact on interest rate on real estate investment,
and Greene and Villanueva (1990) have found a positive relationship between
investment and the interest rate in Least Developed Countries (LDCs).
H2: It is expected that domestic interest rate has either positive or negative
impact on domestic investment in the short-run and in the long-run.
2.3 Remittances and Foreign Exchanges Rate
Barua et al. (2007) have found that depreciation in local currency positively
affects remittances in Bangladesh. Bouhga-Hagbe (2004) has stated that
exchange rate positively affects the remittances flow due to the wealth effect
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Bank Parikrama
(investment motive). Pant and Budha (2016) have found that foreign exchange
rate has a significant positive impact on remittances (see also Barajas et al., 2010;
Faini, 1994; Hasan, 2008; Rajan and Subramanian, 2005). Chamon et al., (2005)
have found that sometimes transient workers take loans to send desired
remittances to take advantage of favorable foreign exchange rate. However,
Swamy (1981) and Straubbaar (1986) have found insignificant positive effect of
exchange rate on remittances and Elbadawi and Rocha (1992) and Freund and
Spatafora (2005) have found a negative and significant effect of exchange rate on
remittances.
H3: It is expected that foreign exchange rate has either positive or negative
impact on remittances in the short-run and in the long-run.
2.4 Remittances and Economic Growth
Matuzeviciute and Butkus (2016) have found that remittances have a
significant positive impact on economic growth (see also Imai et al., 2014;
Nwaogu and Ryan, 2015; Tahir et al., 2015; Zizi, 2014). However, Lim and
Simmons (2015) have found that there is no significant relationship between
economic growth and remittances and Feeny et al. (2014) have found that
remittances have no impact on economic growth (see also Jouini 2015).
Therefore, it can be said that remittances have either positive impact or no impact
on economic growth. However, those papers have avoided to examine the impact
of economic growth on remittances. Therefore, this study fills out the gap by
addressing the impact of per capita GDP on remittances. It is also notable that
Barua et al. (2007) have used ratio of foreign GDP to domestic GDP as a
determinant of remittances. The study varies in this regard by using solely per
capita GDP as a determinant of remittances. In this regard, the study considers
the altruistic motive of remittances. If altruistic motive dominates, high income
negatively affects remittances. In absence of altruistic motive (presence of
investment motive), high income positively affects remittances.
Abedin, Sen, Chowduhury and Akter: Revisiting the Investment-Remittance Nexus
97
H4: It is expected that per capita GDP (usually used as a proxy of economic
growth) has either positive or negative impact on remittances in the short-run
and in the long-run.
2.5 Domestic Investment and Economic Growth
Khatib et al. (2012) have found a significant positive impact of per capita
GDP on domestic investment in the long-run (see also Acosta and Loza, 2004;
Ajide and Lawanson, 2012; Harupara, 1998; Karagoz, 2010; Nghifenwa, 2009).
However, Sohail et al. (2014) have found that domestic investment in Pakistan
increased real GDP growth.
H5: It is expected that per capita GDP (usually used as a proxy of economic
growth) has positive impact on Domestic Investment both in the long-run and in
the short-run.
2.6 Domestic Investment and Foreign Exchange Rate
Buffie (1986) has found that the exchange rate is an important determinant
of domestic investment (see also Chavali, 2014). He has found that permanent
domestic currency appreciation has a positive impact on domestic investment in
the long-run. On the other hand, Campa and Goldberg (1999) have found that
domestic currency depreciation has a significant positive impact on the domestic
investment in the United States and Japan. Moreover, Serven (1990) has stated
that the depreciation in the domestic currency has a positive impact on domestic
investment when import quantity of capital products is larger relative to the extent
of capital mobility. However, Darby et al. (2000) have found that the impact of
exchange rates on domestic investment vary across countries.
H6: It is expected that foreign exchange rate has either positive or negative
impact on domestic investment in the short-run and in the long-run.
Most of the past studies in abroad have not critically examined the three
motives of remittances – investment, altruistic, and insurance and proved the
existence of dominance of a specific or two or all the motives. In fact, in
Bangladesh, all the studies (Barua et al., 2007 and Hasan, 2008) are less thought
provoking without considering any motive of remittances. This study fills the gap
in this regard. This study has critically examined all the three motives of
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Bank Parikrama
remittances and claimed the dominance of investment motive. Moreover, no
study in Bangladesh has analyzed the linkage between domestic investment and
remittances where the foreign exchange rate, per capita GDP, and domestic
interest rate matter. The study suggests that depreciation of local currency and
lower domestic interest rate are important to boost up domestic investment which
subsequently contributes to the economic growth.
3. Data, Methodology, and Model Formation
The study uses remittances data, domestic investment, domestic interest rate,
per capita GDP, and foreign exchange rates from 1976 to 2016 of Bangladesh
from the World Bank Development Indicators of the World Bank. The definitions
of the key variables used in this study has been described in Table-1.
Table 1: Defining Key Variables
Variables
DINV
REM
FOREX
INT
Explanation
Domestic Investments (DINV) represent the total investment in a fiscal year
within the border of the Bangladesh.
Remittances (REM) show the amount foreign currency sent by the migrant
Bangladeshis and through outsourcing.
Foreign Exchange Rates (FOREX) determines the value Bangladeshi currency
with respect to USD.
Domestic Interest Rate (INT) represents the average domestic lending rate fixed
by banks and financial institutions.
This study assumes that the interest rate, per capita GDP, and foreign
exchange rate are strictly exogenous in estimating the long-run equation.
However, a few empirical studies have found that due to flush in remittances,
domestic investment goes up and as a result interest rate is affected. The study
assumes that only interest rate affects the domestic investment. Hence,
considering the domestic investment, interest rate is also strictly exogenous in
long-run equation. Again, the study assumes that remittance is not the strictly
exogenous factor in determining the level of domestic investment as the effect of
foreign exchange rate and economic growth is usually channeled to the domestic
investment through remittances. Hence, the underlying assumption of this study
can be delineated in the way that foreign exchange rate and economic growth
affect remittances, which affects domestic investment. However, it is notable that
Abedin, Sen, Chowduhury and Akter: Revisiting the Investment-Remittance Nexus
99
the inflow of remittance in an economy might be explained by the other
socioeconomic factors for example, political turmoil, tax regime, remittance cost,
rate of return on real estate, wage rate, inflation, the efficiency of the banking
system, income inequality, and working agents (Russell, 1986; Wahba, 1991; ElSakka and McNabb, 1999; Schiopu and Seigfried, 2006). To find out the linkage
among per capita GDP (PGDP), Domestic Investment (DINV), Foreign
Exchange Rate (FOREX), Domestic Interest Rate (INT), and Remittances
(REM), the following two models have been used:
DINVt = A0 .REM t1 .INTt2 .et
(1)
REMt = A1.FOREX t1 .PGDPt2 .et
(2)
The logarithmic transformation of these equations (Equation-1 and Equation-2)
is given below:
ln DINVt =  0 + 1 ln REM t +  2 ln INTt +  t
(3)
ln REM t =  0 + 1 ln FOREX t +  2 ln PGDPt + t
(4)
Let, ln A0 =  0 and ln A1 =  0 .
2016.
t
represents the time period from 1976 to
1 and  2 represent the elasticity of Domestic Investment (DINV) with
respect to Remittances (REM) and Domestic Interest Rate (INT).
 1 and  2
represent the elasticity of Remittances (REM) with respect to Foreign Exchange
Rate (FOREX) (BDT/USD) and Per capita GDP (PGDP).
 t and  t represent
the random error terms. Equation-4 will check whether Foreign Exchange Rate
(FOREX) and Per capita GDP (PGDP) have positive or negative impact on
remittances. Equation-3 will check whether Remittances (REM) and Domestic
Interest Rate (INT) have a positive or negative impact on Domestic Investment
(DINV). If Foreign Exchange Rate (FOREX) and Per capita GDP (PGDP) have
a positive impact on Remittances (REM) and Remittances (REM) have a positive
impact on domestic investment, then it can be concluded that both Foreign
Exchange Rate (FOREX) and Per capita GDP (PGDP) have a positive impact on
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Bank Parikrama
Domestic Investment (DINV). The negative (negative impact) can be true and
would thus have a negative impact on Domestic Investment (DINV).
To ensure whether the Foreign Exchange Rate (FOREX) and Per capita GDP
(PGDP) have positive or negative impact on domestic Investment (DINV), the
following two models have been used:
DINVt = Q0 .PGDPt1 .INTt2 .et ........................................... (5)
DINVt = R0 .FOREX t1 .INTt2 .et ........................................(6)
The logarithmic transformation of these equations (Equation-5 and Equation-6)
is given below:
ln DINVt = 0 + 1 ln PGDPt + 2 ln INTt + t ...................(7)
ln DINVt = 0 + 1 ln FOREX t +  2 ln INTt + t ...............(8)
Let, ln Q0 = 0 and ln R0 =  0 .
2016.
t
represents the time period from 1976 to
1 and  2 represent the elasticity of Domestic Investment (DINV) with
respect to Per capita GDP (PGDP) and Domestic Interest Rate (INT).
1 and  2
represent the elasticity of Domestic Investment (DINV) with respect to Foreign
Exchange Rate (FOREX) (BDT/USD) and Domestic Interest Rate (INT).
t and
t represent the random error terms.
It is notable that, due to high positive correlation (multicollinearity problem),
per capita GDP (PGDP) and Foreign Exchange Rate (FOREX) are used
separately in two equations instead of one equation.
Equation-3, Equation-4, Equation-7, and Equation-8 have been estimated by
the Feasible Modified Ordinary Least Square (FMOLS), which fixes out the
endogeneity and auto-correlation problems if exists (Philips and Hansen, 1990).
The appropriate lead and lag length for FMOLS has been selected by SBIC.
Abedin, Sen, Chowduhury and Akter: Revisiting the Investment-Remittance Nexus
101
3.1 Unit Root Tests
Before estimation of Equation-3, Equation-4, Equation-7, and Equation-8, unit
root problem has been checked. In this regard, the ADF test has been applied.
The form of this test is given below:
m
Zt = K0 + K1t +  Zt −1 +   j Zt − j + ut
.........(9) [With constant and trend terms]
j =1
m
Zt = K0 +  Zt −1 +   j Zt − j + ut ..........(10) [With constant term only]
j =1
Here, Z is the variable under investigation. The variable is of ( I (1) ) if 𝛿 = 0.
Appropriate lag length of equation (9) and (10) would be selected by the AIC and
SBIC criteria. Apart from ADF test (Dickey and Wayne, 1979), PP test (Phillips
and Perron, 1987) has been applied to get an overwhelming conclusion (Phillips,
1986). The unit root test results have been provided in Table-3. The test results
suggest all variables are integrated of order one ( I (1) ).
3.2 Cointegration Tests
Since all variables are integrated of order one (I(1)), at this stage cointegration
relationship among the variables across different equations has been checked. To
check cointegrating relationship, the Johansen and Juselius (1990) test has been
applied. A brief description of this test is given below:
p
X t = B0 + X t − p +  BX t − j + t ......... (11)
j =1
Where, X t represents the vector of endogenous I (1) variables, B0 represents
a vector of constant terms, B is the matrix of co-efficients,
 t is the vector of
residuals, and p denotes the lag length. All variables in Equation (11) seem to be
endogenous. The long-run relationship among X t determined by the rank of

If r = 0 , the variables in the level form do not have cointegrating
relationship and equation (11) can be transformed to VAR-model of pth order.
(say
r ).
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If 0 < r < n, then there are (n  r ) matrices of
 and
 such that: =  .
The strength of co-integration relationship is measured by
.
 is called the
cointegration vector and   X t is of I(0) even if X t is of I (1) . Johansen and
Juselius (1990) test suggests the existence of cointegration relationship among
the variables in Equation-3, Equation-4, Equation-7, and Equation-8. The results
of these tests have been provided in Appendix Table-2.
3.3 Causality Analysis
The cointegration test results only says the existence of a long-run relationship
among the variables, but it does not say the direction of causal relationship among
the variables. To know the direction of causal relationship among the variables,
Engel and Granger (1987) F-test has been applied on the first difference forms of
the variables in VAR framework. In order to capture the long-run relationships,
an error correction term has been included in the VAR system. The augmented
form of the Granger causality test in a multivariate VECM framework is
presented below for Equation-3, Equation-4, Equation-7, and Equation-8:
 X1t  C1  m 11k 12k 13k   X1t −k  1 
1t 

  

21k 22k 23k   X 2t −k  + 2  ECM t −1 +  2t  (12)
 X 2t  = C2  + 

 X 3t  C3  k =1 31k 32k 33k   X 3t −k  3 
 3t 
The C ' s ,  ' s ,  ' s are the parameters to be estimated. ECM t −1 is the one period
lagged error terms derived from the Equation-3, Equation-4, Equation-7, and
Equation-8.  ' s are serially independent with mean zero and finite covariance
matrix. The appropriate lag length for Equation-12 has been selected by the AIC
and SBIC.
3.4. Fully Modified Ordinary Least Square (FMOLS)
FMOLS considers endogeneity and serial correlation problems. Most of the
macroeconomic variables cause each other even if we assume that interest rate,
per capita GDP, and foreign exchange rate are strictly exogenous. Moreover, we
assume that only interest rate causes domestic investment. Sometimes, domestic
investment causes interest rate. Hence by default, the simultaneity might exist.
Abedin, Sen, Chowduhury and Akter: Revisiting the Investment-Remittance Nexus
103
This problem is also known as reverse causality. We could have identified it by
designing equation in simultaneous form and using formal test. Simulation
experience also suggests that FMOLS estimator performs very well in relation to
other methods of estimating cointegrating relations (Cappuccio and Lubian,
1992; Hansen and Phillips, 1991; Hargreaves, 1993; Phillips and Loretan, 1991;
and Rau, 1992).
4. Results and Interpretation
4.1 Descriptive Statistics
A few descriptive statistics of PGDP, DINV, REM, INT, and FOREX are given in
Table-2.
Table 2: Descriptive Statistics
Name of variables
Mean
Std. Dev.
CV (%)
REM (%)
4.5211
2.9762
65.83
DINV (%)
22.8317
5.1408
22.52
FOREX (BDT/USD)
45.3676
21.0215
46.33
INT (%)
13.0318
1.6155
12.39
PGDP (in USD)
424.267
262.9987
62.11
JB Statistics
16.3165***
(0.0003)
12.9315***
(0.0016)
2.6636
(0.2640)
2.0562
(0.3577)
15.8728***
(0.0004)
Note: ***P<0.01 denotes significant at 1% level, **P<0.05 denotes significant at 5% level, *P<0.10 denotes
significant at 10% level.
The distributions of FOREX and INT are normal unlike those of REM, DINV,
and PGDP. Remittances have the highest variability.
4.2 Causality Results
From the estimated results of VEC models, short-run unidirectional causality
exists from domestic investment to domestic interest rates (ln DINV  ln INT ) ,
from remittances to foreign exchange rate (BDT/USD) (ln REM  ln FOREX ) ,
from
foreign
exchange rate (BDT/USD) to per capita GDP
(ln FOREX  ln PGDP) , from domestic investment to per capita GDP
(ln DINV  ln PGDP) , from foreign exchange rate (BDT/USD) to domestic
investment (ln FOREX  ln DINV ) , and from foreign exchange rate (BDT/USD) to
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Bank Parikrama
domestic interest rate (ln FOREX  ln INT ) . The significance of ECM (−1) is each
case confirms the existence of long-run causality among the variables. In the long-
run, remittances along with domestic interest rate, per capita GDP along with
foreign exchange rate, domestic interest rate along with per capita GDP, and
domestic interest rate long with foreign exchange rate cause domestic investment,
remittances, domestic investment, and domestic investment respectively. The
results of Granger Causality Test have been provided in Table-5.
4.3 Long-run Analysis
From the estimated long-run coefficients of Equation-3, it can be said that
remittances have a significant positive impact on domestic investment (Gupta
et al., 2007; Adams, 2006; Mundaca, 2009) and domestic interest rate has a
significant negative impact on domestic investment (Hall, 1977; Greene and
Villanueva, 1990; Aysan et al., 2005; Wang and Yu, 2007; Osundina and
Osundina, 2014; Wuhan et al., 2015). From the estimated long-run coefficients
of Equation-4, it can also be said that both the foreign exchange rate (BDT/USD)
and per capita GDP have a significant positive impact on remittances (Elbadawi
and Rocha, 1992; Faini, 1994; Freund and Spatafora, 2005; Rajan and
Subramanian, 2005; Schiopu and Seigfried, 2006; Barua et al., 2007; Hasan,
2008; Barajas et al., 2010; Pant and Budha, 2016).
From the estimated long-run coefficients of Equation-7, it has been found
that per capita GDP has a significant positive impact on domestic investment
(Acosta and Loza, 2004; Nghifenwa, 2009; Karagoz, 2010; Ajide and Lawanson,
2012; Khatib et al., 2012; Sohail et al., 2014) and domestic interest rate has
significant negative impact on domestic investment. From estimated long-run
coefficients of Equation-8, foreign exchange rate has a significant positive impact
on domestic investment (Campa and Goldberg, 1999; Chvali, 2014) and interest
rate has a significant negative impact on domestic investment. The results have
been provided in Table-6.
Since per capita GDP and foreign exchange rate have a significant positive
impact on remittances, here the investment motive is dominant. When the income
of the family in the Bangladesh increases and Bangladeshi currency depreciates, the
migrant sends more money for financial investments or for inheritance reasons, because
Abedin, Sen, Chowduhury and Akter: Revisiting the Investment-Remittance Nexus
105
his potential of inheritance will increase. In the case of insurance motivation,
depreciation in Bangladesh currency will also decrease the remittances, as the
migrant prefers to take time to remit for offsetting the impact of the appreciation
of the local currency. If altruistic motive dominates, and income of the family in
the Bangladesh decreases, the migrant sends more money in order to assure the
same level of the utility for his family and the depreciation in Bangladeshi
currency avail less remittances since it will ensure same level of national currency
with relatively small amount of foreign currency. Hence, the study has not found
any dominance altruistic and insurance motives of remittances.
The investment motive is dominant has been also proved by a significant
positive impact of remittances on domestic investment. It can also be said that
remittances change the savings pattern of the households. Hence, a part of the
households’ savings is going to the domestic investment. Therefore, over time
depreciation in Bangladeshi currency and an increase in per capita GDP increase
remittances, which subsequently increase domestic investment. It can also be said
that to support the faster economic growth, it is inevitable to increase the level of
domestic investment. Over time, an increase in the domestic interest rate squeezes
down the level of domestic investment as the higher cost of funding makes
investors more risk-averse ultimately lowering the level of domestic investment.
The foreign exchange rate has a significant positive impact on domestic
investment, depending on the country specific factors (Darby et al., 2000) such
as trade openness, cost of capital goods, higher capital mobility, and external debt
apart from the investment motive. For example, depreciation in domestic
currency has a positive impact on domestic investment as the import quantity of
capital products is larger relative to the extent of capital mobility (Serven, 1990).
4.4 Short-run Analysis
Finally, the short-run equations have been estimated in the following formsp
q
r
j =1
l =0
k =0
 ln DINVt =  0 +   j  ln DINVt − j + 1l  ln REM t −l +  2 k  ln INTt −k + 1ECM1,t −1 + t .....(13)
m
n
s
g =1
h =0
i =0
 ln REM t =  0 +  g  ln REM t − g +  1h  ln FOREX t −h +   2i  ln PGDPt −i + 2 ECM 2,t −1 + t
..... (14)
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Bank Parikrama
u
v
w
j =1
m=0
n =0
 ln DINVt = 0 +   j  ln DINVt − j + 1m  ln PGDPt −m + 2 n  ln INTt −n + 3 ECM 3,t −1 + t ...(15)
q
r
s
j =1
k =0
l =0
 ln DINVt =  0 +  j  ln DINVt − j +  1k  ln FOREX t −k +  2l  ln INTt −l + 4 ECM 4,t −1 + t ...(16)
Equation-13, Equation-14, Equation-15, and Equation-16 have been
estimated by OLS.  0 ,
 0 ,  0 ,  0 ,  ' s ,  ' s ,  ' s ,  ' s 1 's , 1 ' s , 1 ' s , 1 's ,
 2 ' s ,  2 's ,  2 's , and  2 ' s are the parameters to be estimated. 1 , 2 , 3 ,
and
4 denote the speed of adjustments to approach into the long-run equilibrium
if there is any shock in the systems.
From the estimated results of short-run Equation-13, it can be said that
remittances have significant positive impact on domestic investment and the
domestic interest rate has a significant negative impact on domestic investment.
Therefore, in the short-run, an increase in the domestic interest rate slows down
the vehicle of domestic investment and an increase in remittances keeps the
vehicle of domestic investment going. The coefficient of error correction term for
Equation-13 is significant with an expected negative sign. If there is any shock to
domestic investment due changes in remittances and domestic interest rates, it
will adjust 74.55% in the first year. The entire convergence process will take
approximately 1.3 years to approach into the long-run equilibrium, if there is any
shock to the domestic investment. Therefore, the convergence process is
significantly faster, if there is any shock to domestic investment. From the
estimated results of short-run Equation-14, it can be said that both foreign
exchange rate (BDT/USD) and per capita GDP have a positive impact on
remittances, even the impact of per capita GDP is insignificant. Therefore, in the
short-run the increase in foreign exchange rate and per capita GDP boosts up
remittances. To generalize, an appreciation in the foreign exchange rate
(BDT/USD) and more per capita GDP scales up remittances, which subsequently
positively contributes to domestic investment in the short-run. The coefficient
error correction term for Equation-14 is significant with the expected negative
sign. If there is any shock to the remittances, due to changes in foreign exchange
rate and per capita GDP, it will adjust 24.02% in the first year. The entire
Abedin, Sen, Chowduhury and Akter: Revisiting the Investment-Remittance Nexus
107
convergence process will take approximately 4.16 years to approach the long-run
equilibrium, if there is any shock to the remittances due to changes in the foreign
exchange rate (BDT/USD) and per capita GDP. From the estimated results of
short-run Equation-15, it has been found that per capita GDP has an insignificant
positive impact on domestic investment, and the domestic interest rate has a
significant negative impact on domestic investment. The error correction term for
Equation-15 is significant with expected negative sign. If there is any shock to
domestic investment due to changes in per capita GDP and the domestic interest
rate, it will adjust 97.35% in the first year. The entire convergence process will
take approximately 1 year to approach equilibrium if there is any shock to
domestic investment due to changes in per capita GDP and the domestic interest
rate. From the estimated results of short-run Equation-16, it has been found that
the foreign exchange rate (BDT/USD) has an insignificant positive impact on
domestic investment and the domestic interest rate has an insignificant negative
impact on domestic investment. The error correction term of Equation-16 is
significant with the expected negative sign. If there is any shock to domestic
investment due to changes in the foreign exchange rate (BDT/USD) and
domestic interest rate, it will adjust 48% in the first year. The entire convergence
process will take approximately 2 years to approach the equilibrium level if
there is any shock to domestic investment due to changes in the foreign exchange
rate (BDT/USD) and domestic interest rate. The results have been provided in
Appendix Table-4.
4.6 Stability of the Parameters
Due to the use of FMOLS to estimate the long-run equations (Equation-3,
Equation-4, Equation-7, and Equation-8), stability checking of the long-run
parameters has been avoided. Stability of the short-run parameters has been
checked by CUSUM test and CUSUMSQ test (Borensztein, De Gregorio, and
Lee., 1998). The short-run parameters are stable for all equations (Equation-1e,
Equation-14, Equation-15, and Equation-16) since all parameter values lie within
the critical bounds during the estimation period. Therefore, short-run parameters
along with long-run parameters can be used for conclusions and policy
implications. The results have been provided in Appendix Figure-1.
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5. Conclusion and Policy Implication
The study exposes a significant positive impact of remittances unlike
domestic interest rate on domestic investment and a significant positive impact
of the foreign exchange rate (BDT/USD) and per capita GDP on remittances in
the long-run. In addition, in the long-run, per capita GDP and the foreign
exchange rate (BDT/USD) have a significant positive impact on domestic
investment. Over time, depreciation of Bangladeshi currency and increase in per
capita GDP increase remittances, which consequently increase domestic
investment. Hence the investment motive is dominant in the long-run. Again, per
capita GDP has an insignificant positive impact on domestic investment, and
foreign exchange rate has a significant positive impact on remittances. It can be
claimed that even in the short-run, investment motive of remittances is dominant
due to significant positive impact of remittances on domestic investment,
significant impact of foreign exchange rate on remittances, and insignificant
positive impact of per capita GDP on remittances. Hence, this study suggests that
to boost up remittance, depreciation of domestic currency should be in a
convenient level for the greater interest of the economy. Although movement of
domestic currency is in floating regime, embargoing on the import of luxury
items, restricting money laundering, and promoting foreign investment, the
increased demand of foreign currency can be restricted.
Besides, remittances have a significant positive impact on domestic
investment and domestic interest rate has a significant negative impact on
domestic investment in the short-run. Since, the main objective of remittances is
to change the socioeconomic structure (developing living standard, construction
and development of schools, colleges, health centers, water supply and sanitation,
and rural electrification, etc.), the level of domestic investment will be increased
by remittances. Contribution of domestic investment is not satisfactory, even if
inflation and real lending interest rate are in decreasing trend. Given many factors
affecting lending interest rate of an economy, our motive is to tell that increased
import cost, theoretically a contributing factor, might affect inflation rate and
thereby to the lending interest rate of Bangladesh. Therefore, the double-digit
interest rate affects negatively to domestic investment and our lending interest
Abedin, Sen, Chowduhury and Akter: Revisiting the Investment-Remittance Nexus
109
rate is not lower enough to increase domestic investment. Hence, boosting up
domestic investment via remittances would contribute into economic growth.
If there is any shock to domestic investment due to changes in remittances
and domestic interest rates, it will correct 74.55% in the first year. The entire
convergence process will take approximately 1.3 years to approach into long-run
equilibrium. If there is any shock to the remittances due to changes in the foreign
exchange rate and per capita GDP, it will adjust 24.02% in the first year. The
entire convergence process will take approximately 4.16 years to approach into
long-run equilibrium. If there is any shock to domestic investment due to changes
in per capita GDP and domestic interest rates, it will adjust 97.35% in the first
year. The entire convergence process will take approximately 1 year to approach
into long-run equilibrium. If there is any shock to domestic investment due to
changes in foreign exchange rates (BDT/USD) and domestic interest rates, it will
adjust 48% in the first year. The entire convergence process will take
approximately 2 years to approach into long-run equilibrium. All short-run
parameters are stable suggested by CUSUM test and CUSUMSQ test. Therefore,
all the long-run and short-run coefficients can be used for policy implications.
Finding the convenient level of the exchange rate and domestic lending interest
rate for the greater interest of the economy could be the further research
opportunity. Besides, the time variant parametric model could be used to consider
structural change of the Bangladeshi economy.
End Notes
a) Per capita GDP (PGDP) and foreign exchange rate (FOREX) are used
separately in two equations instead of one equation, due to the
multicollinearity problem (See: Equation-5 and Equation-6).
b) Interest rate, domestic lending interest rate, and domestic interest rate have
been used interchangeably in this study.
c) All short-run and long-run parameters have carefully been estimated in Eviews and RATS.
d) All short-run parameters are stable suggested by CUSUM test and
CUSUMSQ test.
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Bank Parikrama
e) Both the foreign exchange rate (BDT/USD) and per capita GDP have a
significant positive impact on remittances in the long-run, which will
positively contribute to domestic investment (Remittances have a
significant positive impact on domestic investment). Therefore, it can be
concluded that foreign exchange rates and per capita GDP have indirect
positive impacts on domestic investment.
f) All short-run error correction models are free from auto-regressive
conditional heteroscedasticity, autocorrelation, and functional
misspecification. The distribution of error terms in all error correction
models are normal.
g) AIC stands for Akaike information criterion and SBIC stands for Schwartz
Bayesian information criterion.
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116
Bank Parikrama
Appendices
Appendix Table 1: Unit Root Tests Results
Variables
ln DINV
Model with constant term [Level Form]
ADF test
P-value
PP test
-0.1829
0.9321
-0.7991
P-value
0.8082
ln REM
-1.7274
0.4078
-2.8441*
0.0614
ln FOREX
ln INT
ln PGDP
-1.8672
0.3438
-1.7814
0.3839
-2.2136
0.2050
-1.8681
0.3434
0.6453
0.9892
0.6000
0.9880
Variables
ln DINV
ln REM
ln FOREX
ln INT
ln PGDP
Model with constant and trend term [Level Form]
ADF test
P-value
PP test
-1.5691
0.7856
-3.0125
P-value
0.1419
-2.4400
-1.8550
0.3532
0.6578
3.0797
-1.0302
0.9992
0.9278
-2.1203
0.5184
-1.7659
0.7018
-1.0362
0.9268
-1.0362
0.9268
Variables
Model with constant term [Difference Form]
ADF test
P-value
PP test
-9.1055***
0.0000
-9.1165***
P-value
0.0000
 ln REM
-8.4449***
 ln DINV
 ln FOREX
 ln INT
 ln PGDP
Variables
 ln DINV
 ln REM
 ln FOREX
 ln INT
 ln PGDP
***P<0.01
0.0000
-8.4449***
0.0000
***
-4.2548
-4.1663***
0.0019
0.0023
***
-3.7157
-3.9613***
0.0077
0.0040
-5.3707***
0.0001
-5.3707***
0.0001
Model with constant and trend term [Difference Form]
ADF test
P-value
PP test
-9.0654***
0.0000
-9.0654***
-8.1156***
**
-3.9958
-4.2945***
-5.3108***
P-value
0.0000
0.0000
-8.2149***
0.0000
0.0178
0.0083
***
-5.6653
-4.0969**
0.0000
0.0135
0.0005
-5.3108***
**P<0.05
Note:
denotes significant at 1% level,
denotes significant at 5% level,
significant at 10% level. Appropriate lag length for these tests has been selected by SBIC.
Source:
0.0005
*P<0.10
denotes
CEs
None*
At
most 1
At
most 2
Case-1: Intercept (no trend) in CE and VAR
Equation (3)
Equation (4)
Equation (7)
Trace
Max-Eigen
Trace
Max-Eigen Trace Statistic
Max-Eigen
Statistic
Statistic
Statistic
Statistic
Statistic
30.4262**
21.5510**
33.1539**
25.0450**
40.3123***
36.0620***
[29.7971]
[21.1316]
[29.7971]
[21.1316]
[29.7971]
[21.1316]
(0.0423)
(0.0437)
(0.0198)
(0.0133)
(0.0022)
(0.0002)
8.8751
8.7452
8.1089
6.5262
4.2503
4.2495
[15.4947]
[14.2626]
[15.4947]
[14.2646]
[15.4947]
[14.2646]
(0.3771)
(0.3080)
(0.4538)
(0.5466)
(0.8823)
(0.8321)
0.1299
0.1299
1.5827
1.5827
0.0008
0.0008
[3.8415]
[3.8415]
[3.8415]
[3.8415]
[3.8415]
[3.8415]
(0.7185)
(0.7185)
(0.2084)
(0.2084)
(0.9784)
(0.9784)
Case-2: Intercept and trend in CE and no intercept in VAR
Equation (3)
Equation (4)
Equation (7)
Trace
Max-Eigen
Trace Statistic
Max-Eigen
Trace
Max-Eigen
Statistic
Statistic
Statistic
Statistic
Statistic
Equation (8)
Trace
Max-Eigen
Statistic
Statistic
26.0982
19.2480*
[29.7971]
[21.1316]
(0.1258)
(0.0899)
6.8501
6.7527
[15.4947]
[14.2646]
(0.5951)
(0.5188)
0.0974
0.0974
[3.8415]
[3.8415]
(0.7549)
(0.7549)
Equation (8)
Trace
MaxStatistic
Eigen
Statistic
None*
44.5900**
21.1496
56.2666***
29.0742**
47.9449**
36.3956***
39.9019*
21.1010
[42.9153]
[25.8232]
[42.9153]
[25.8232]
[42.9153]
[25.8232]
[42.9152]
[25.8232]
(0.0336)
(0.1421)
(0.0014)
(0.0180)
(0.0145)
(0.0014)
(0.0970)
(0.1861)
At
22.4404
17.2434*
27.1923**
22.1210**
11.5493
8.7520
18.8009
12.7137
most
[25.8721]
[19.3870]
[25.8721]
[19.3870]
[25.8721]
[19.3870]
[25.8721]
[19.3870]
1*
(0.1261)
(0.0997)
(0.0341)
(0.0195)
(0.8420)
(0.7497)
(0.2927)
(0.3517)
At
5.1970
5.1970
5.0714
5.0714
2.7973
2.7973
6.0871
6.0871
most 2
[12.5180]
[12.5180]
[12.5180]
[12.5180]
[12.5180]
[12.5180]
[12.5179]
[12.5179]
(0.5683)
(0.5683)
(0.5862)
(0.5862)
(0.8997)
(0.8997)
(0.4493)
(0.4493)
Note: Value under [ ] represents 5% critical value and value under ( ) represents p-value. ***P<0.01 denotes significant at 1% level, **P<0.05
denotes significant at 5% level, *P<0.10 denotes significant at 10% level. Appropriate lag length for this test has been selected by AIC and
SBIC. Case-1 suggests one cointegrating equation and Case-2 suggests two cointegrating equations.
CEs
Abedin, Sen, Chowduhury and Akter: Revisiting the Investment-Remittance Nexus
Appendix Table 2: Cointegration Test Results
117
118
Bank Parikrama
Appendix Table 3: Causality Analysis Results
Equation (3)
Causalities: Short-run
 ln DINV
 ln REM
 ln INT
 ln DINV
0.000007
(0.9979)
5.1705**
(0.0296)
 ln REM
ECM (−1) [ t-statistic]
0.4791
(0.4937)
-
0.3856
(0.5389)
0.1402
(0.7104)
-
-1.8656*
(0.0710)
-0.7599
(0.4527)
-2.8728***
(0.0071)
0.2662
(0.6093)
Equation (4)
Causalities: Short-run
 ln REM
 ln FOREX
 ln PGDP
 ln REM
 ln FOREX
-
0.8576
(0.5052)
-
4.4442***
(0.0093)
0.7334
(0.5794)
4.7784***
(0.0067)
0.1785
(0.9470)
0.4159
(0.7953)
-
 ln DNIV
 ln PGDP
 ln INT
 ln DNIV
-
 ln PGDP
3.4123*
(0.0737)
2.4315
(0.1285)
0.0775
(0.7824)
-
0.0367
(0.8492)
1.3365
(0.2560)
-
0.4139
(0.5244)
Equation (8)
Causalities: Short-run
 ln DNIV
 ln FOREX
 ln INT
 ln DNIV
 ln FOREX
 ln INT
-
6.8132**
(0.0135)
-
0.1454
(0.7054)
1.2142
(0.2785)
-
0.0742
(0.7870)
6.3758**
(0.0166)
6.4679**
(0.0159)
Causality: Long-run
 ln PGDP ECM (−1) [ t-statistic]
Equation (7)
Causalities: Short-run
 ln INT
Causality: Long-run
 ln INT
-1.7572*
(0.0935)
-1.3985
(0.1766)
2.4263**
(0.0243)
Causality: Long-run
ECM (−1)
[ t-statistic]
-3.7947***
(0.0006)
-3.3465***
(0.0021)
-1.9711*
(0.0571)
Causality: Long-run
ECM (−1)
[ t-statistic]
-4.4095***
(0.0000)
1.6344
(0.1117)
-3.3686***
(0.0019)
Note: ***P<0.01 denotes significant at 1% level, **P<0.05 denotes significant at 5% level, *P<0.10 denotes
significant at 10% level. Significance of ECM (−1) has ensured the existence of long-run causality among the
variables.
Variables
Equation
(3)
ln REM
ln INT
0.1211***
(0.0000)
-0.6540***
(0.0001)
-
Long-run Coefficients
Equation
Equation
(4)
(7)
Equation
(13)
Equation
(16)
-
-
-
-
-
-
-
-0.6120***
(0.0000)
-
-0.9495***
(0.0001)
0.3557***
(0.0000)
-
-
-
-
-
-
-
-
-
-
-
-
0.2253*
(0.0705)
-0.6258**
(0.0492)
-
-
-
-
-
-0.4142*
(0.0992)
-
-0.4520
(0.1789)
0.2004
(0.6335)
-
ln PGDP
-
 ln REM
-
 ln INT
-
 ln FOREX
0.3322***
(0.0000)
-
-
-
-
-
-
-
-
 ln PGDP
-
-
-
-
-
ECM(-1)
-
-
-
-
Constant
2.2231***
(0.0000)
-
7.1157***
(0.0000)
-
2.7257***
(0.0000)
-
4.2042***
(0.0000)
-
ARCH Test
-
-
-
-
Normality Test
-
-
-
-
Misspecification Test
-
-
-
-
-0.7455***
(0.0007)
-0.0087
(0.7465)
0.1898
(0.8281)
0.5096
(0.7668)
3.3282
(0.1894)
0.0884
(0.7680)
Auto-correlation Test
Short-run Coefficients
Equation
Equation
(14)
(15)
-
2.1843***
(0.0000)
1.6203***
(0.0000)
-
ln FOREX
Equation
(8)
1.3697**
(0.0337)
0.5983
(0.3077)
-0.2402**
(0.0370)
-0.0292
(0.6996)
0.2623
(0.7710)
1.2543
(0.3067)
3.3133
(0.1899)
1.3106
(0.2605)
0.0751
(0.7254)
-0.9735***
(0.0000)
0.0102
(0.5830)
0.5546
(0.5797)
0.1382
(0.9365)
0.3535
(0.8380)
1.7748
(0.1919)
-0.4800***
(0.0099)
0.0242
(0.3308)
0.8052
(0.4558)
0.3986
(0.7548)
5.7729*
(0.0558)
0.1781
(0.6758)
Abedin, Sen, Chowduhury and Akter: Revisiting the Investment-Remittance Nexus
Appendix Table 4: Long-run and Short-run Coefficients
Note: ***P<0.01 denotes significant at 1% level, **P<0.05 denotes significant at 5% level, *P<0.10 denotes significant at 10% level. The Short-run Equation
has been estimated by OLS and Long-run Equation has been estimated by FMOLS. The lead and lag in FMOLS have been selected by SBIC.
119
120
Appendix Figure 1: Stability of Short-run Parameters
Figure 1(a): For Equation (13)
Figure 1(b): For Equation (14)
20
1.4
20
1.4
15
1.2
15
1.2
1.0
10
0.8
0.8
5
1.0
10
5
0.6
0.6
0
0
0.4
0.4
-5
-5
0.2
0.2
-10
0.0
-15
-0.2
-20
-0.4
84
86
88
90
92
94
96
98
00
CUSUM
02
04
06
08
10
12
14
84
86
88
5% Significance
90
92
94
96
98
00
CUSUM of Squares
02
04
06
08
10
12
-10
0.0
-15
-0.2
-20
-0.4
86
14
88
90
92
94
96
98
CUSUM
5% Significance
Figure 1(c): For Equation (15)
00
02
04
06
08
10
12
86
14
92
94
96
98
00
02
04
06
08
10
12
14
5% Significance
Figure 1(d): For Equation (16)
1.4
20
1.4
15
1.2
15
1.2
10
1.0
1.0
10
0.8
0.8
5
0.6
0.6
0
90
CUSUM of Squares
20
5
88
5% Significance
0
0.4
0.4
-5
-5
0.2
0.2
-10
0.0
-15
-0.2
-20
1985
1990
1995
CUSUM
2000
2005
5% Significance
2010
2015
-10
0.0
-15
-0.2
-0.4
-20
-0.4
1985
1990
1995
CUSUM of Squares
2000
2005
5% Significance
2010
2015
1985
1990
1995
CUSUM
2000
2005
5% Significance
2010
2015
1985
1990
1995
CUSUM of Squares
2000
2005
2010
2015
5% Significance
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