Report on “Analysis of Factors Affecting Remittance in Bangladesh
1.0 Introduction
Remittance: Transfer of money by a foreign worker to his or her home country. Money sent home by migrants constitutes the second largest financial inflow (primary inflow being exports) for many developing countries, exceeding international aid.
Non-resident Bangladeshi (NRB): Legally, any Bangladeshi citizen living abroad for more than one year is categorized as non-resident Bangladeshi (NRB). Once a Bangladeshi citizen disowns Bangladeshi passport and takes foreign citizenship s/he is no more considered as NRB. However, the Bangladeshi origin people having dual citizenship are also included in the NRB category.
Gross National Product (GNP): The final value of all new goods and services, produced within a specific time period, by nationally owned factors of production.
Inflation: The overall general upward price movement of goods and services in an economy, usually as measured by the Consumer Price Index (CPI).
Consumer Price Index (CPI): An inflationary indicator that measures the change in the cost of a fixed basket of products and services, including housing, electricity, food, and transportation.
Pearson’s Correlation Coefficient(r): The Pearson correlation coefficient explains the magnitude and direction of the association between two variables that are on an interval or ratio scale.
This report is a detailed study of three independent factors that affect the level of remittance inflows:
· the number of migrant laborers,
· inflation (CPI) and
· the income level (indicated by the GNP of Bangladesh)
A time-series analysis investigates the volume of remittance in Bangladesh during the period 1979-2009. The report also analyzes the effects of the global financial crisis on remittance inflows and the economy of Bangladesh.
Remittance: Transfer of money by a foreign worker to his or her home country. Money sent home by migrants constitutes the second largest financial inflow (primary inflow being exports) for many developing countries, exceeding international aid.
Non-resident Bangladeshi (NRB): Legally, any Bangladeshi citizen living abroad for more than one year is categorized as non-resident Bangladeshi (NRB). Once a Bangladeshi citizen disowns Bangladeshi passport and takes foreign citizenship s/he is no more considered as NRB. However, the Bangladeshi origin people having dual citizenship are also included in the NRB category.
Gross National Product (GNP): The final value of all new goods and services, produced within a specific time period, by nationally owned factors of production.
Inflation: The overall general upward price movement of goods and services in an economy, usually as measured by the Consumer Price Index (CPI).
Consumer Price Index (CPI): An inflationary indicator that measures the change in the cost of a fixed basket of products and services, including housing, electricity, food, and transportation.
Pearson’s Correlation Coefficient(r): The Pearson correlation coefficient explains the magnitude and direction of the association between two variables that are on an interval or ratio scale.
2.0 Literature Review
Remittances have been growing rapidly in the past few years and now represent the largest source of foreign income for many developing countries. According to the Bangladesh Bank, between 1976 and 2009, Bangladesh received more than USD 62 billion from its migrant population. The official data on the inflow of remittances into Bangladesh refers to the transfer of funds made by migrant workers through the banking channel (and through post offices). The records of such transfers can be easily separated from other foreign exchange transactions since these take place under what is known as the Wage Earners’ Scheme (WES).
According to the International Organization for Migration, it is hard to estimate the exact size of remittance flows because many transfers take place through unofficial channels. Worldwide, officially recorded international migrant remittances are projected to exceed $232 billion in 2005, with $167 billion flowing to developing countries. These flows are recorded in the balance of payments. Unrecorded flows through informal channels are believed to be at least 50 percent larger than recorded flows (Freund 2005).
The ‘portfolio approach’ views remittance as similar to capital flows. In this approach, variables typically of macroeconomic nature such as GNP of home countries, rate of inflation etc. are hypothesized as determining factors of remittances.
An IMF study (Chami, et al, 2005) based on panel data (annual) of 87 countries during the period 1980-2003 suggests that variables like financial development, political risk, law and order, relative investment opportunity were found to be of little significance in influencing inward remittance flows.
Remittance flows tend to be more stable than capital flows, and they also tend to be counter-cyclical—increasing during economic downturns or after a natural disaster in the migrants’ home countries, when private capital flows tend to decrease. In countries affected by political conflict, they often provide an economic lifeline to the poor. The World Bank estimates that in Haiti they represented about 17 percent of GDP in 2001, while in some areas of Somalia, they accounted for up to 40 percent of GDP in the late 1990s.
3.0 Background
NRBs have been continuing to play a very important role in economic growth and development of Bangladesh. During the last two decades NRBs sent to Bangladesh more than USD 20 billion. In 1999 volume of remittance exceeded the amount of foreign reserve – the total volume of remittance was USD 2.1 billion whereas the foreign exchange reserve was USD 1.52 billion.
While the export earning is declining as a result of global recession, the importance of remittance further increased. According of Bangladesh Bank, the remittance flow during July-October period of FY2002 increased by 22% comparing the figure of same period of FY2001, that stood at USD 596 million. The growth of remittances played an important role and facilitated to defer any possible currency crisis. Remittance flow might be increased further given that the use of official channel for sending money to home is more attractive to the NRBs in terms of speed, security and cut of transaction.
The stabilizing contribution to the Balance of Payment (BoP) is mostly an unconscious or indirect contribution of the NRBs to the Bangladesh economy. The majority of NRBs are sending to Bangladesh only that minimum amount of foreign currency which is required for subsistence of their family or relatives. This type of remittance is a more than 60% of total remittance inflow. The rest of the amount is sent for investment in various businesses including real estate business and other industries. In the election years, a certain portion of fund in form of remittance is also transferred to the candidates and political parties for financing elections.
If we consider a scenario of no remittances from abroad, we can extrapolate a deep currency crisis leading towards major socio-economic turmoil. Given that the balance of trade is static, a 50% decline in remittance may trigger massive fall of Taka value against foreign currency.
4.0 Variables
There are four main variables considered for the purposes of this report.
4.1 Dependent Variable
The dependent variable considered here is the annual level of remittance inflow into Bangladesh as defined in Section 1.5 and will be measured in Bangladesh Taka (BDT).
The most important way an NRB will contribute to immediate economic growth of Bangladesh is through remittance. Bangladesh was the 10^{th} largest recipient of remittances among the developing countries considering the average period of 1990 to 2005 (IFS, October 2007). A list of the top recipient countries of remittance is included in Appendix A.
This time period considered is 30 years, during the period 1979-2009. The data are listed in Appendix B.
4.2 Independent Variables
There are four main variables that are hypothesized to affect the level of remittance – time, the number of migrants abroad, the level of income and the level of inflation. They have been considered after a detailed literature review (Section 2) to test their significance on the dependent variable.
Finally the report also analyzes the effect of the recent global financial crisis on the dependent variable.
4.2.1 Time
The time period under consideration is FY 1979- 2009. A time series analysis is carried out to investigate the impact of time on remittance this is described in Section 5.
4.2.2 Number of Migrants Abroad
One of the most significant factors is the number of workers abroad. They are classified as:
Professional
Skilled
Semi-skilled and
Less-skilled
4.2.3 Income Level of Home Country
The income level is identified in terms of the GNP (defined in Section 1.5). The GNP is considered as a standard to test what the effects are on remittance. The GNP data used is for the period 1979-2008. (See Appendix C)
4.2.4 Inflation
Inflation is considered as one of the independent variables. Using base year 1995-96, the CPI Index was used to find the rate of inflation. (See Appendix D)
The rate of inflation (defined in Section 1.5) is considered to see how a change in price levels at home affects the level of remittance. Data for 1996-2009 was utilized for this analysis.
4.2.5 Global Financial Crisis
The global financial crisis has had a significant impact on the economies if the world. This report takes a look at how the recent crisis has affected the remittance inflows of the country by comparing pre-crisis (2006-07) levels to post crisis levels (particularly 2008-09).
5.0 Remittance: Time Series Analysis
Robust remittance inflows in recent years (annual average growth of 81.7% in FY07-FY09) have been instrumental in maintaining the current account surplus despite widening a trade deficit.
Figure 1: Trends in Remittance Source:Bangladesh Bank
The graph above shows the trend of remittance to Bangladesh from 1979 till 2009. Total remittance to Bangladesh was only BDT 165.59 crore in FY79. In 2006-07, the remittances from expatriate Bangladeshi workers stood at BDT 41298.54. In 2007-08, the figure stood at BDT 54295.14 crore, reflecting 31.47 % rise over the previous year. By FY09, the amount stood at BDT 75040 crore, increasing at an average annual rate of 15 % in the last 30 years (1979-2009). Thus there has been an exponential growth in the level of remittance, particularly from 2000.
6.0 Remittance: Factor Analysis
6.1 Number of Migrants
Currently, Saudi Arabia, UAE, Kuwait, Qatar, Oman, Iraq, Libya, Bahrain, Iran, Malaysia, South Korea, Singapore, Hong Kong and Brunei are some of the major countries of destination for Bangladeshi migrant workers. Saudi Arabia alone accounts for nearly one half of the total number of workers who migrated from Bangladesh. The labor market of Bangladeshi workers is not static. In mid-1990s, Malaysia became the second largest employer of Bangladeshi workers. During the period 1976 to 2006, the migration of labour totalled 4.55 million with yearly migration being 6,087 in 1976 and 377,591 in 2006.However, since the financial crisis of 1997, Bangladeshis migrating to Malaysia dropped drastically. Now UAE has taken over its place.
Figure 2: Trend of Number of NRBs Source:Bangladesh Bureau of Statistics
The majority of the workers from Bangladesh are employed in semi-skilled or unskilled work. These include construction projects, garments factories, or in service sectors like hotels. A small proportion is professionals like doctors, business professionals, IT experts and so on. Usually these categories of workers go abroad to study and continue to work abroad.
Figure 3: Number of Expatriates Classified by Skills
Source: http://www.mof.gov.bd/en/budget/rw/external_sector.pdf
The figure above shows that:
The number of expatriate workers is mainly comprised of semi-skilled and unskilled workers. They accounted for 80.1% in 2007.
The share of professional and skilled laborers in the total expatriate workforce is 0.1 percent and 19.9 percent respectively.This shows that the workers are from rural areas or from poorer households.
Figure 4: Trends in Number of Migrants
Source:Bangladesh Bureau of Statistics
The Graph above shows the increasing trend of the number of migrant workers in the last 30 years. As we can see, the number increases substantially after 2005.
6.1.1 Scatter Diagram
Figure 5 : Scatter Plot – Remittance vs Number of Migrant Workers
As shown above, there is a positive correlation between the two variables. However, to find if the correlation is statistically significant, we analyze the data as shown in the next section.
6.1.2 Correlation
This section analyzes the relationship between the number of migrant workers and the remittance levels using SPSS to find if there is any significanct correlation, i.e. how much does a movement alng one variable affect the other. The relevant data list is included in Appendix B.
The data input is as follows:
Variable 1, V_{1} = Number of Workers Abroad
Variable 2, V_{2} = Remittance(in crores BDT)
Pearson correlation coefficient = r
Null Hypothesis, H_{0}: r = 0
Alternate Hypothesis, H_{a}: r > 0
The null hypothesis suggests that there is no association between V_{1} and V_{2}. The alternate hypothesis suggest that r > 0. From Section 6.1.1, it is quite apparent that there is a positive slope. So we can carry out a one-tailed test for investigating our hypothesis.
Correlations | |||
No. of Workers Abroad | Remittance (in crores BDT) | ||
No. of Workers Abroad | Pearson Correlation | 1 | .950^{**} |
Sig. (1-tailed) | .000 | ||
N | 31 | 31 | |
Remittance (in crores BDT) | Pearson Correlation | .950^{**} | 1 |
Sig. (1-tailed) | .000 | ||
N | 31 | 31 | |
**. Correlation is significant at the 0.01 level (1-tailed). |
Using the output above, we can deduce that r = 0.95. The 2 variables are therefore strongly and positively correlated. Also we are 99% confident that our results are correct (significance level is 0.01).
Thus the null hypothesis is rejected. The value of r is greater than zero, which means that there is a positive relation between the number of migrant workers and remittance levels.
6.1.3 Linear Regression
The conclusion drawn in Section 6.1.2 does not allow us to define a cause-effect relation. To find if there is such a relation, a linear regression analysis is carried out. The general model used is
Y= mX + c where Y = dependent variable
m = slope
X = independent variable
c = y-intercept
This model is used throughout the report for similar regression analyses.
Here Y = Remittance, X = Number of Migrant Workers
The relevant hypotheses are:
H_{0}: m = 0
H_{a}: m ? 0
The null hypothesis suggests that m is statistically not significantly different from zero. Alternately, H_{a} suggests that there is in fact a causal relationship between the two variables.
Model Summary | ||||
Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
1 | .950^{a} | .902 | .899 | 5568.303 |
a. Predictors: (Constant), No. of workers abroad |
Coefficients^{a} | ||||||
Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
B | Std. Error | Beta | ||||
1 | (Constant) | -2003.407 | 1297.505 | -1.544 | .133 | |
No. of workers abroad | .059 | .004 | .950 | 16.334 | .000 | |
a. Dependent Variable: Remittance (in crores BDT) |
R ^{2} = 0.902 R ^{2}_{adjusted} = 0.899 standard error = 5567.303
m = 0.59 c = -2003.407
The output above indicates that at a significance of .01, we can reject the null hypothesis. So we are 99% confident that m is statistically significantly different from zero. The model is valid because the value of R^{2} is 0.902. (See Appendix E for complete list of output)
The regression model is therefore:
Y = 0.59X – 2003.407
Hence remittance is dependent on the number of migrants abroad. The relation can be explained by the model tested above.
6.2 Income Level of Home Country
The income level of the home country is expected to play a role in the level of remittance sent home. Figure 6 on the next page shows the trends in GNP of Bangladesh over the period 1979-2008.
Figure 6 : Trends in GNP
Source:Bangladesh Bureau of Statistics
This graph shows the GNP figures of Bangladesh at constant prices. Except for a brief fluctuation after 1999 and 2000, GNP figures have stabilized again. The GNP reached its highest peak of BDT 347556 crore in FY 2000. It again spiked at BDT 303303 crore in FY 2002. However, since then GNP is showing a downward trend. This trend has continued in light of the recession from 2007.
Figure 7 : Comparison of GNP and Remittance
Source:Bangladesh Bureau of Statistics
The graph above compares the percentage changes in remittance and GNP over the same period. Remittance growth has stabilized in the past decade. However, real GNP growth is astonishingly at a negative since FY 03. There has been a steady decline at constant prices for the past decade.
6.2.1 Scatter Diagram
Figure 8 : Scatter Plot – Remittance vs Income Level
As shown above, there is a positive correlation between the two variables. However, to find if the correlation is statistically significant, we analyze the data as shown in the next section.
6.2.2 Correlation
This section analyzes the relationship between the income levels and the remittance levels using SPSS to find if there is any significanct correlation, i.e. how much does a movement alng one variable affect the other. The relevant data list is included in Appendix B and Appendix C.
The data input is as follows:
Variable 1, V_{1} = GNP (in millions BDT)
Variable 2, V_{2} = Remittance(in crores BDT)
Pearson correlation coefficient = r
Null Hypothesis, H_{0}: r = 0
Alternate Hypothesis, H_{a}: r > 0
The null hypothesis suggests that there is no association between V_{1} and V_{2}. The alternate hypothesis suggest that r > 0. From Section 6.2.1, it is quite evident that there is a positive slope. So we can carry out a one-tailed test for investigating our hypothesis.
Correlations | |||
Remittance (in crores BDT) | GNP of BD at constant prices ( in millions of BDT) | ||
Remittance (in crores BDT) | Pearson Correlation | 1 | .604^{**} |
Sig. (1-tailed) | .000 | ||
N | 29 | 29 | |
GNP of BD at constant prices ( in millions of BDT) | Pearson Correlation | .604^{**} | 1 |
Sig. (1-tailed) | .000 | ||
N | 29 | 29 | |
**. Correlation is significant at the 0.01 level (1-tailed). |
Using the output above, we can deduce that r = 0.604. The 2 variables are therefore moderately and positively correlated. Also we are 99% confident that our results are correct (significance level is 0.01).
Thus the null hypothesis is rejected. The value of r is greater than zero, which means that there is a positive relation between the income level and remittance levels.
6.2.3 Linear Regression
The conclusion drawn in Section 6.2.2 does not allow us to define a cause-effect relation. To find if there is such a relation, a linear regression analysis is carried out. The general model used is
Y= mX + c
Here Y = Remittance, X = GNP
The relevant hypotheses are:
H_{0}: m = 0
H_{a}: m ? 0
The null hypothesis suggests that m is statistically not significantly different from zero. Alternately, H_{a} suggests that there is in fact a causal relationship between the two variables.
Model Summary | ||||||||||
Model | R | R Square | Adjusted R Square | Std. Error of the Estimate | ||||||
1 | .604^{a} | .365 | .342 | 1.0744903E4 | ||||||
a. Predictors: (Constant), GNP of BD at constant prices ( in millions of BDT) | ||||||||||
Coefficients^{a} |
||||||||||
Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||||||
B | Std. Error | Beta | ||||||||
1 | (Constant) | -2760.534 | 3738.445 | -.738 | .467 | |||||
GNP of BD at constant prices ( in millions of BDT) | .008 | .002 | .604 | 3.941 | .001 | |||||
a. Dependent Variable: Remittance (in crores BDT) | ||||||||||
R ^{2} = 0.365 R ^{2}_{adjusted} = 0.342 standard error = 1.08
m = 0.008 c = -2760.534
The output above indicates that at a significance of .001, we can reject the null hypothesis. So we are 99.9% confident that m is statistically significantly different from zero. The value of R^{2} is 0.365. This is lower than that for the previous model but is still a good fit. (See Appendix E for complete list of output)
The regression model is therefore:
Y = 0.008X – 2760.534
Hence remittance is dependent on the level of income. The relation can be explained by the model tested above.
6.3 Rate of Inflation
Figure 9 : Trends in Inflation
Figure 9 shows the historical trend of inflation in Bangladesh:
Inflation fell dramatically in the late eighties. Inflation fell from double-digit increases recorded in the mid 1980s to a low of 3.1% in 1992-93.
In 1990-91, 1994-95, 1997-98 the spikes in the trend line were above 8% and were driven by natural calamities and supply shocks.
In 2000-01, annual inflation rate came down to its lowest point of below 2%, mainly due to lower prices of food items, but has been on an upward path since then.
In 2007-08, it again touched the two-digit rate, largely as a result of rising international prices of fertilizers, fuel and foods
6.3.1 Scatter Diagram
Figure 10 : Scatter Plot – Remittance vs Inflation
As shown above, there is a positive correlation between the two variables. However, to find if the correlation is statistically significant, we analyze the data as shown in the next section.
6.3.2 Correlation
This section analyzes the relationship between the rate of inflation and the remittance levels using SPSS to find if there is any significanct correlation, i.e. how much does a movement alng one variable affect the other. The relevant data list is included in Appendix B and Appendix D.
The data input is as follows:
Variable 1, V_{1} = Rate of Inflation (%)
Variable 2, V_{2} = Remittance(in crores BDT)
Pearson correlation coefficient = r
Null Hypothesis, H_{0}: r = 0
Alternate Hypothesis, H_{a}: r ? 0
The null hypothesis suggests that there is no association between V_{1} and V_{2}. The alternate hypothesis suggest that r ? 0. So we can carry out a two-tailed test for investigating our hypothesis.
Correlations | |||
Remittance (in crores BDT) | Inflation | ||
Remittance (in crores BDT) | Pearson Correlation | 1 | .187 |
Sig. (2-tailed) | .000 | ||
N | 12 | 12 | |
Inflation | Pearson Correlation | .187 | 1 |
Sig. (2-tailed) | .000 | ||
N | 12 | 12 |
From the output above, we can see that r = 0.187. The 2 variables are therefore weakly and positively correlated. Also we are 99% confident that our results are correct (significance level is 0.01).
Thus the null hypothesis is rejected. The value of r is greater than zero, which means that there is a positive relation between inflation and remittance levels.
6.3.3 Linear Regression
The conclusion drawn in Section 6.3.2 does not allow us to define a cause-effect relation. To find if there is such a relation, a linear regression analysis is carried out. The general model used is
Y= mX + c
Here Y = Remittance, X = Rate of Inflation
The relevant hypotheses are:
H_{0}: m = 0
H_{a}: m ? 0
The null hypothesis suggests that m is statistically not significantly different from zero. Alternately, H_{a} suggests that there is in fact a causal relationship between the two variables.
Model Summary | ||||
Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
1 | .187^{a} | .035 | -.053 | 21526.53358 |
a. Predictors: (Constant), Inflation |
Coefficients^{a} | ||||||
Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
B | Std. Error | Beta | ||||
1 | (Constant) | 20378.447 | 8980.047 | 2.269 | .044 | |
CPI Inflation | 721.487 | 1143.490 | .187 | .631 | .541 | |
a. Dependent Variable: Remittance |
R ^{2} = 0.035 R ^{2}_{adjusted} = -0.53 standard error = 21526.54
m = 721.487 c = 20378.447
The null hypothesis cannot be rejected because the significance level is very high (54.1%). The output shows that though there is a correlation between the two variables, there is no causal relationship. The value of m is not statistically significantly different from zero. (See Appendix E for complete list of output).
Hence remittance is not dependent on the rate of inflation.
6.4 Recession and Its Effects on Remittance
The world has been engulfed by financial crisis since 2007 and it was feared that the slump in economy and the continuous lay-offs would trouble the Bangladeshis working abroad. Despite these negative forecasts for Bangladesh by the World Bank and IMF, the country has actually done quite well in relation to other South Asian countries.
Globally, the recession has affected migrants’ remittance flows in four ways:
Opportunities for new migration have slowed down in some regions. The manufacturing and construction sector of Malaysia and the construction sector of Dubai have been particularly hard hit by the global recession. Malaysia and UAE are two major countries where 65 to 70% of the workers went over last 2 years.
Retrenchments have taken place in some of the receiving countries followed by return of a section of workers
Decline in wage rate at destination country
Over the last few months a section of migrants are returning. Since there is no data on returning migrants of earlier years, it is not possible to ascertain what portion of this is normal return and what portion is due to recession and retrenchment. However, the country’s foreign exchange reserve is currently at over USD 10 billion and reflects a stable inflow of remittance that has defied experts.
Figure 11: Inward Remittance Flows
Source: http://www.mof.gov.bd/en/budget/rw/external_sector.pdf
As the graph shows, remittance has actually grown in the past 2 years, against all odds. The remittance flow for the first six months of FY 09 increased by 31% over the corresponding period of the previous year. On a year-to-year basis, the trends are as shown in the next figure.
Figure 12: Effects of Global Financial Crisison Remittance
It seems that rather than declining as experts suggested, the level of remittance as actually jumped since the recession started. This short term increase is due to the following factors:
Many migrants are returning to Bangladesh, and they are bringing their savings with them.
Many NRBs are now investing in the national stock exchanges and other local investment projects.
Many NRBs have shifted their earnings to Bangladesh in light of the banking crisis, which affected their savings in reputed international banks.
Figure 13: Effects of Global Financial Crisis on Number of Migrant Workers
A dilemma seems to present itself when one considers the figure above. If migrants are returning, then how is the number of migrant workers increasing at the pace shown above?
There is no official data regarding the number of migrants who returned in the past. So there is no benchmark to compare with to assess the post-crisis scenario. Moreover, many migrants who are returning are undocumented and low-skilled workers. In addition, Malaysia has stopped recruiting Bangladeshi workers. Yet the growing trend shows that more and more human resources are being exported and this improves our remittance inflows.
7.0 Summary of Findings
The chart below summarizes the findings of this report:
Independent Variables | Dependent Variable | Model | Correlation Coefficient, r | Coefficient of Determination, R^{2} | Significance Level (%) | Conclusion |
Number of Migrant Workers | Remittance | Y = 0.59X – 2003.407 | 0.95 | 0.902 | 1% | There is a significant cause-effect relation. The model is also a good fit. |
Income Level | Remittance | Y=0.008X – 2760.534 | 0.604 | 0.365 | 1% | There is a significant cause-effect relation. The model is valid. |
Rate of Inflation | Remittance | – | 0.187 | 0.035 | 54.1% | The model is not statistically significant |
The graph below shows a comparison of the factors considered in this report. The most important factor in determining remittance levels is the number of migrant workers. The remittance shows a steady growth with this factor.
Figure 14 :Comparison of Factors
Conclusion
Remittances have emerged as a key driver of economic growth and poverty reduction in Bangladesh, increasing at an average annual rate of around 20 percent in the last 30 years (1979-2008).
This report has empirically investigated the effects of three factors- number of migrant workers, income level and rate of inflation on the levels of remittance. It found that a strong relation exists between remittance and the number of migrant workers. Using appropriate tools it was possible to form statistical models for these factors. However the effect of inflation was found to be insignificant and therefore was not considered in the model.
Remittance trends over time were also analyzed. Finally an analysis of the effects of the global financial crisis was carried out. It was found that despite all odds, the remittance levels were increasing at a staggering pace. It was revealed that remittance have grown by 38.2% in the last fiscal year.
Although this is a highly positive aspect, the government and other concerned institutions must step forward to ensure that there is an increasing the number of migrants abroad and they are channelling remittances through formal arrangements.
Some other policies that may be adopted in this regard are:
The Government may give migrant workers the right to import goods that can be considered as remittance in kind. Such remittance in kind may be exempted from custom duties.
There is a general decline in the supply of skilled and professional categories of migrants from Bangladesh. Under such conditions, a number of measures need to be taken by BMET. Our human resources have to be trained and marketed. Initiatives must be taken for proper certification of skills that a good section of migrant workers possess, such as electrician, mason, bricklayer, plumber, fitter, turner etc. In this respect, special incentives may be provided to private recruiting agencies who export skilled manpower.
Bangladeshi banks overseas should periodically mount drives in a planned way for opening of accounts of Bangladeshi migrant population overseas.
The central bank should allow banks to appoint brokers/agents on payment of commission who help mobilizing individual remittances.
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