Impact of Remittances on Financial Development and Economic Growth

Supervisor:

Professor Moisă Altăr

Student: Nita Olivia Georgiana

Academy of Economic Studies, BucharestDoctoral School of Finance and Banking

Structure: Introduction

Literature review

Methodology and data

Empirical results

Conclusions

Bibliography

Introduction Remittances - transfers of resources from individuals in one country to

individuals in another - are an important source of private funds in developing countries.

Remittances have grown from U.S. $31.2 billion in 1990 to U.S. $338 billion in 2008.

Migrants from developing countries sent home $316 billion during 2009 or 6% less than they did during the previous year. The World Bank forecasts a 6.2% increase in remittances this year.

The research subject: remittances and their impact on growth and financial development.

The main goal of the research: the theoretical and methodological study of remittances, the economic analysis and the use of remittances, the importance of remittances in promoting growth, by looking at the interaction between remittances and financial sector and also the impact of remittances on financial development.The Economist, Apr 29th 2010, “Remittances”

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Literature review More than 60% of remittances are used to purchase daily necessities such

as food, clothes and shelter, remittances are a key poverty reduction tool (Adams and Page 2005; Acosta et al. 2008).

The 20-40% of remittances that is used to save or invest is the key to achieving a family’s longer-term financial independence.

IMF surveys have shown that 30-50% of remittances recipients have access to a bank account. To expand this area, banks can offer a greater range of financial products such as: microcredit, insurance and remittance-backed mortgages.

The fact that remittances might affect financial development in developing countries is based on the concept that money transferred through financial institutions give access for recipients to other financial products and services, which they might not have otherwise (Orozco and Fedewa, 2005).

DY ICD SCY IS

Economic Models using RemittancesThe Keynesian Model

Variable used: the effective demand for goods (D), total final consumption (C), savings (S), global investment (I), income or production (Y), imports (M) and exports (X) .

An increase in Y due to the increase in the remittances R flows can be represented either by an independent increase of exports receipts, either through additional investment.

An additional inflow in R will increase the income balance from point A to point B.

The final income balance will depend essentially on the R influence on the propensity to saving and consumption of imports.

The Keynesian Model

The equilibrium condition is:

For an open economy equilibrium condition must be supplemented with the influence of external transactions:

XDMY

XIMS

The IS-LM Model

Variable used: the real sector (IS), the monetary sector (LM) and the external one (BP) are in equilibrium (point E), at a given level of income and a certain interest rate .

BP curve is perfectly inelastic. Forced by remittances flow, the

monetary expansion will lead to increased revenue ( ), which, in turn, will condition the cheaper domestic credit as the real sector will be growing.

The IS-LM Model

1Y

1i

2Y

The National Accounts System

The additional remittance flows increases the aggregate demand and is integrated in the gross national income available.

This can be expressed as follows:

- gross national income; - consumption and private investment; - consumption and government investment; - foreign income; - net current transfers from abroad (remittances); X - exports of goods and services; M - import of goods and services. The available gross national income contains the current account of the

balance of payments Transmitted in the country, these resources can be saved, consumed or

invested.

)()()( MXTrYICICY ffgp

Y

pIC )(

gIC )(

fY

fTr

ff TrYMXCAB )(

Methodology and data This paper uses balance of payments data on remittance flows received by

10 European developing countries. I worked with a panel data using Eviews 7 econometric tools.

I start by estimating the impact of remittances on economic growth by ordinary last squares (OLS), without using any financial development variables:

where i refers to the country and t to the time period from 1994 to 2009

L_GDP, denotes the logarithm of initial level of GDP per capita;

Rem refers to the ratio of remittances to GDP. The data on remittances are constructed as the sum of three items in the Balance of Payments Statistics Yearbook (IMF): workers’ remittances, compensation of employees and migrant transfers.

tiitititi uXmGDPL ,,2,1, Re_

Figure1

Figure1 shows the European remittance recipient countries used in this sample for the year 2009, measured as a percentage of GDP.

Moldova (18.16%), Albania (15.22%), Serbia (9.81%), Bulgaria (3.66%) and Romania (1.64%) are among the largest recipients of remittances as percentage of GDP .

Matrix X refers to a set of control variables that the literature has found to

affect economic growth and financial development:

Inflation, measured as the annual percentage change in the consumption

price index;

Openness to international trade, defined as the ratio of the sum of exports

plus imports of goods to total output;

Other flows to GDP measured as the ratio of capital inflows to GDP

(including aid, FDI, and portfolio flows), and

Population growth.

First I analyzed the relationship between remittances and economic growth

by running fixed effects and random effects regressions, ignoring the

potential for biases due to reverse causation or measurement error.

Hausman test is reported for comparing the efficiency of random and fixed

effect estimates.

To address the endogeneity problem the Generalized Method of Moments (GMM) panel data estimator, developed by Arellano, M. and Bover, O. (1995) is used for estimations with lagged regressors as instruments.

Regression estimated with the GMM method:

To explore the relationship between financial development and remittances the following equation is estimated:

FD, financial development, refers either to the ratio of bank credit to the private sector or the share of bank deposits expressed as a percentage of GDP.

tiiitittititititi uXFDmFDmGDPLGDPL ,5,4,3,21,10, *ReRe__

tiitititi uXmFD ,,2,1, Re

In Table 3 we can find the fixed effects estimates.

The relationship between remittances and growth is a positive one.

A one percentage point increase in the share of remittances to GDP suggests a 0.011 percentage point increase in the economic growth.

The economic growth is positively influenced by all variables, but negatively influenced by inflation.

Absolute values of t statistics are in brackets. The symbols *, ** and *** denote significance at the 10, 5 and 1 percent level, respectively.

Table 3Panel estimates of the Impact of Remittances on Economic

GrowthFixed Effects Results (OLS)

Log of GDP

Remittances to GDP

Openness

Other flows

Population growth

Inflation

Constant

ObservationsNumber of countries

0.011[8.55]***0.007[15.24***0.001[2.08]***0.169[12.27]***-0.003[-6.73]***7.031[153.16]***

15010

Empirical results

Using the random effects estimates, we also find that the relationship between remittances and growth is a positive one.

A one percentage point increase in the share of remittances to GDP suggests a 0.010 percentage point increase in the economic growth.

The economic growth is positively influenced by all variables, but negatively influenced by inflation.

The Hausman test shows that the fixed effects model is preferable.

Table 4Panel estimates of the Impact of Remittances on Economic Growth

Random Effects Results (OLS)

Absolute values of t statistics are in brackets. The symbols *, ** and *** denote significance at the 10, 5 and 1 percent level, respectively.

Log of GDP

Remittances to GDP

Openness

Other flows

Population growth

Inflation

Constant

Observations

Number of countries

Hausman testP-value for Hausman test

0.010[3.82]***0.006[7.82]***0.003[2.10]**0.189[8.64]***-0.002[-3.81]***7.016[57.35]***142

10

52.650.00

Absolute values of t statistics are in brackets. The symbols *, ** and *** denote significance at the 10, 5 and 1 percent level, respectively.

Table 5GMM Panel Data estimates of Remittances, Financial

Development and Economic Growth

To address the endogeneity problem I used the Generalized Method of Moments (GMM), following Arellano and Bover (1995). In order to ensure that the interaction term does not proxy for remittances or the level of development of financial markets, these variables are also included in the regression separately.Growth is positively influenced by both remittances and financial development. The interaction sign is negative, which indicates that remittances and financial development are used as substitutes to promote growth.The Sargan p-value shows the validity of the instruments, the null hypothesis cannot be rejected .

Log of GDP Log of GDPRemittances to GDP

Bank Deposits to GDP

RemGDP*BankDepGDP

Bank Credit to GDP

RemGDP*BankCreditGDP

Openness

Other flows

Population growth

Inflation

Lag 1 of Log of GDP

ObservationsSargan test for overidentifying restrictionsP-value Sargan test

0.010[3.29]***0.002[3.66]***-0.0001[-1.92]***

0.002[4.05]***-0.001[-3.25]***0.012[0.46]-0.001[-1.86]*0.760[12.23]***

1021.50

0.47

0.005[2.31]**

0.001[2.19]**-2.08[-0.37]0.002[3.46]***-0.002[-2.33]**0.046[2.14]**-0.001[-2.65]**0.719[8.29]***

1160.90

0.82

The next step now is to analyze the remittances direct impact on financial development.

As we can see the remittances have a positive coefficient for both measures of financial development.

Assuming a causal relationship, a one percentage point increase in the share of remittances suggests a 0.77 percentage point increase in the ratio of deposits to GDP, while it leads to a 0.71 percentage point rise in the share of credit to GDP.

Table 6Panel estimates of the Impact of Remittances on Financial

Development Fixed Effects Estimates (OLS)

Bank Deposits to GDP

Bank Credit to GDP

Remittances to GDP

GDP per capita

Other flows

Population growth

Inflation

Openness

Constant

0.770[13.28]***2.935[3.29]***0.163[3.88]***9.126[4.45]***-0.039[-1.86]*-0.023[-0.78]

29.37[15.93]***

0.718[10.48]***7.529[7.28]***0.664[7.20]***4.973[3.805]***-0.062[-2.25]**-0.114[-2.29]**

13.93[4.27]***

Absolute values of t statistics are in brackets. The symbols *, ** and *** denote significance at the 10, 5 and 1 percent level, respectively.

Forecast 2010-2011 Remittance flows are broadly

affected by three factors: the migrant stocks, incomes of migrants in the destination country and incomes in the source country.

Figure 2 reports the results of the forecast for the ratio of credit to GDP and Figure 3 presents the differences between the two series actual and fitted for the ratio of credit to GDP by analyzing the line graph.

A 1% fall in remittances suggests a fall of about 0.23% in the ratio of the credit to GDP.

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Alb

ania

- 9

4

Alb

ania

- 0

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Alb

ania

- 0

6

Alb

ania

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2

Bu

lgari

a -

99

Bu

lgari

a -

05

Bu

lgari

a -

11

Czech

Re

pu

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98

Czech

Re

pu

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04

Czech

Re

pu

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10

Hun

ga

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97

Hun

ga

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03

Hun

ga

ry -

09

Mold

ova -

96

Mold

ova -

02

Mold

ova -

08

Po

land

- 9

5

Po

land

- 0

1

Po

land

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7

Rom

an

ia -

94

Rom

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Rom

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06

Rom

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12

Se

rbia

- 9

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D_BC D_BCF

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4

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95

Alb

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D_BCF ± 2 S.E.

Forecast: D_BCFActual: D_BCForecast sample: 1994 2011Adjusted sample: 1995 2011Included observations: 139Root Mean Squared Error 6.956537Mean Absolute Error 3.938316Mean Abs. Percent Error 177.0869Theil Inequality Coefficient 0.778159 Bias Proportion 0.000000 Variance Proportion 0.896889 Covariance Proportion 0.103111

Figure 2

Figure 3

Figure 4 reports the results of the forecast for the ratio of deposits to GDP and Figure 5 presents the differences between the two series actual and fitted for the ratio of credit to GDP by analyzing the line graph.

A 1% fall in remittances suggests a fall of about 0.65% in the ratio of the deposits to GDP.

From these forecasts we continue to find that remittances are an important source of external funds.

That’s why migrants should be stimulated to continue to send remittances home which will bring economic growth and will also have a positive influence on financial development.

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Alb

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Hun

gary

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Hun

gary

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oldo

va -

98

Mol

dova

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Pol

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Pol

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Rom

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D_BDF1 ± 2 S.E.

Forecast: D_BDF1Actual: D_BDForecast sample: 1994 2011Adjusted sample: 1994 2011Included observations: 135Root Mean Squared Error 4.002412Mean Absolute Error 2.438890Mean Abs. Percent Error 169.8499Theil Inequality Coefficient 0.730591 Bias Proportion 0.000000 Variance Proportion 0.875672 Covariance Proportion 0.124328

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0

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Alb

ania

- 9

4

Alb

ania

- 0

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Alb

ania

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6

Alb

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Bu

lgaria

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lgaria

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2

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Rom

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Se

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- 9

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98

Slo

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Ukrain

e - 9

7

Ukrain

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D_BD D_BDF

Figure 4

Figure 5

Factors affecting remittances flows in 2009

Effect of current crisis on migration stocks and flow Remittance flows in a given year are not directly related to migration flows

during the same year; remittances are sent by almost the entire existing stock of migrants.

The return migration is as a result of the financial crisis in the US and Europe and the new migration flows, which have been impacted by the financial crisis and weak job markets in the destination countries. Efforts by migrants to cut consumption

Remittances are a small share of migrants’ incomes, and they typically continue to send remittances even when hit by income shocks.

Currency effects An important factor affecting the currency valuation of remittances is the

change in the exchange rates between the relevant local currency and the remittance’ s currency. Exchange rate changes also appear to affect the consumption/investment motivation for remittances.

Conclusions Remittances promote growth in less financially developing countries by

providing an alternative way to finance investment.

Remittances acted as substitutes for financial services in promoting

growth, by offering the response to the credit needs and insurance that the

market has failed to provide.

The fact that remittances contribute to overcome liquidity constraints and

help undertake profitable investment in developing countries is important

for future research.

Increasing the official inflow of remittances

Migrant transfers should be stimulated; the role played by migrants should

be recognized and reinforced.

A low–cost and secure remittances transfer service should be provided.

Strategic policies should be combined with measures to encourage the

transfer and investment of remittances to promote economic growth.

One way of bringing more remittances and increasing financial development implies that banks reconsider the conditions for bank credits and deposits.

Banks can make themselves and their services appealing to remittances senders and receivers.

Some of the policies that banks can implement are:

include the remittances received when calculating the income in order to determine creditworthiness;

implement mechanisms to channel remittances directly and conveniently to financial products or regular expenses;

market financial products to remittance senders and receivers; facilitates remittance withdrawals and deposits and develop financial

products targeted specifically at the remittance market.

Selected Bibliography Paola Giuliano, Marta Ruiz- Arranz (2009), “Remittances, financial development, and

growth”, Journal of Development Economics 90, 144-152.  Reena Aggarwal, Asli Demigruc-Kunt, Maria Soledad Martinez Peria (June 2006), “Do

Workers’ Remittances Promote Financial Development”, The World Bank. Thomas H.W. Ziesemer (2010), “The impact of the credit crisis on poor developing countries:

Growth, worker remittances, accumulation and migration”, Economic Modelling.  Richard H. Adams JR (2007), “The Determinants of International Remittances in Developing

Countries”, World Bank, Washington, DC, USA.  Dilip Ratha, Sanket Mohapatra (2007), “Increasing the Macroeconomic Impact of

Remittances on Development”, The World Bank, Development Prospects Group.  Conrad Heilmann (2006), “Remittances and the migration–development nexus—Challenges

for the sustainable governance of migration”, Ecological Economics, 231-236. Caroline Freund, Nikola Spatafora (2008), “Remittances, transaction costs, and informality”,

Journal of Development Economics 86,356–366.  Bradford Barham, Stephan Boucher, (1998), “Migration, remittances, and inequality:

estimating the net effects of migration on income distribution”, Journal of Development Economics, vol. 55, 307-331.

Denise Stanley, Radha Bhattacharya (2008), “The informal financial sector in the U.S.: The role of remittances”, The Quarterly Review of Economics and Finance, 48,1–21.

Arellano, Manuel and Olympia Bover, “Another Look at the Instrumental Variable Estimation of Error-components Models”, Journal of Econometrics 68, 29-51, 1995

Thank you for your time!

Back up slides The Hausman Test

Hypothesis:

If is true, both fixed effects estimator and random effects estimator are consistent, but only the random one is efficient.

If is true, the fixed effects estimator is consistent and the random one is not.

In this case the null hypothesis is rejected, the fixed effect estimator is preferable.

Correlated Random Effects - Hausman Test

Equation: GDP_RE

Test cross-section random effects

Test SummaryChi-Sq. Statistic

Chi-Sq. d.f. Prob. 

Cross-section random 52.654297 5 0.0000

0H

aH

The Sargan Test

Sargan test is used for over identifying restrictions.

Under the null hypothesis that the over-identifying restrictions are valid,

the Sargan statistic (J-statistic) is distributed ,where k is the

number of estimated coefficients and p is the instrument rank.

The p-values show that the validity of the instruments ,the null hypothesis

can not be rejected .

The high p-values 0.47, 0.82 respectively suggest almost certain

acceptance of the null hypothesis , that the variables are valid.

)( kp