Can financial inflows help reduce poverty in Central America?

Can financial inflows help foster growth and reduce poverty in

Central America?

The impact of Foreign Direct Investments, net Official Development Aid, and personal remittances

received on Panama, Honduras and Costa Rica's GDP per capita and poverty headcount.

Robin Huguenot-Noël - Graduate Diploma in Economics - ASE Project 2016

(Word count: 3133; Program used: MS Excel)

Abstract

I examine the relationship between financial inflows and poverty reduction in developing

economies, focusing on Panama, Costa Rica and Honduras between 1981 and 2013. This research

uses Foreign Direct Investments, net Official Development Aid (ODA), and personal remittances

received as independent variables, and the poverty headcount and the GDP per capita as dependant

variables. Our correlation analysis indicates a significant positive relationship between the level of

FDI, growth and poverty reduction as well as between remittances and economic development.

However, our findings suggests that no significant relationship can be drawn between the level of

ODA and these indicators.

2

Official Development Aid (ODA) has traditionally been viewed as a way to fill out the

“savings” and “foreign exchange” gaps. Recent debates on aid effectiveness have however focused

on the redefinition of this “two-gaps” approach, attempting to better integrate the lessons from

contemporary theories of economic growth. Recent research tends indeed to draw more attention to

the contribution of technology change, labour force skills, and the policy environment1 - with

Foreign Direct Investments (FDI) acting as the main vehicle of economic restructuring and

technology diffusion. In the context of an important increase of migration directed to developed

countries,2 in which immigrants generally send a portion of their earning home in the form of

remittances, one may also wonder about the role of remittances in promoting and supporting

development. These three indicators – ODA, FDI and remittances – clearly have distinguishable

features, but their common characteristic as financial inflows directed to economic development

makes for an interesting comparison of their impact on growth and poverty reduction. Due to its

limited size and its geographical situation, Central America tends to be the neglected in the debate

on aid effectiveness and economic development strategies. This situation appears unjustified

considering that this region offers several features that make it a very interesting case study for this

type of research. This study therefore attempts to investigate whether the evolution of the GDP per

capita and poverty headcount in Panama, Costa Rica and Honduras between 1981 and 2013 may be

correlated to changes in the level of the above-mentioned financial inflows. After discussing the

literature related to the impact of FDI, ODA, and remittances on poverty and growth, I will

introduce the selected data and chosen indicators. I will then use descriptive statistics to highlight

relevant trends in each country, and conduct a correlation analysis between independent variables

(FDI, ODA, and remittances) and dependant variables (GDP per capita, poverty headcount), before

drawing general concluding remarks.

1 Mike Tribe, “ODA, Economic Growth and Poverty Reduction,” Ideas4development, 1 December 2010. Available at:

http://ideas4develop.blogspot.fr/2010/12/oda-economic-growth-and-poverty.html (last consulted on 12/05/16).

2 “International Migration and the Millennium Development Goals,” in Selected Papers of the UNFPA Expert Group

Meeting, Marrakech, 11-12 May 2005. Available at: https://www.unfpa.org/sites/default/files/resource-

pdf/migration_report_2005.pdf (last consulted on 12/05/16).

http://ideas4develop.blogspot.fr/2010/12/oda-economic-growth-and-poverty.html

https://www.unfpa.org/sites/default/files/resource-pdf/migration_report_2005.pdf


3

BACKGROUND AND LITTERATURE

Existing literature on the impact of official aid on economic development and poverty

reduction focuses on two questions in particular. The first question relates to the nature of the

relationship between aid and growth, as some scholars found little robust evidence of a positive

or negative relationship between aid inflows and growth.3 This is explained by the fact that setting

out the direction of causation can be a real challenge in this area: if aid may foster growth, slow

growth may in turn also trigger aid. The other question relates to the link between aid effectiveness

and environment conditions, with some scholars arguing that this impact depends on the quality of

domestic policies, whilst others state that aid tends to work best in difficult environments.4 Our

analysis will attempt to establish (1) whether or not a clear relationship can be established

between aid, growth and poverty reduction; (2) to what extent aid may be linked to a more or

less favourable environment.

The positive contribution of Foreign Direct Investment to growth and poverty

reduction is more widely accepted with existing research indicating strong empiric evidence

for this relationship.5 FDIs have notably been proven to reduce poverty by funding the delivery of

social services to the poor and to have a positive impact on employment and exports. However, as

Calvo and Hernandez rightly pointed out, the poverty impact of FDI varies across countries, and

research with an empirical focus on Latin America is missing to establish a clear relationship

in these countries.6 We shall investigate in this paper (1) whether this relationship is

confirmed for Central American economies; (2) from when a relationship between FDI and

poverty reduction can be established.

The impact of remittances on poverty and economic development has recently received

considerable attention from international institutions, with recent studies finding very

encouraging results, though again too often only focusing on African countries. Evidence

3 Rajan Raghuram and Arvind Subramanian, “Aid and Growth: What Does the Cross-Country Evidence Really

Show?” Working Paper 05/127, IMF, Washington D.C, 2005.

4 Patrick Guillaumont and Lisa Chauvet, ‘Aid and Performance: A Reassessment,’ Journal of Development Studies,

2001, 37(6): 66-92.

5 Kevin Honglin Zhang, “Does International Investment Help Poverty Reduction in China?,” The Chinese Economy,

Volume 39, Issue 3, 2006. Available at: http://www.tandfonline.com/doi/abs/10.2753/CES1097-

1475390306?journalCode=mces20 (last consulted on 08/05/16).

6 Cesar C. Calvo and Marco A. Hernandez, “Foreign Direct Investment and Poverty in Latin America,” Paper prepared

to be delivered at the Globalisation and Economic Policy, Leverhulme Centre for Research on Globalisation and

Economic Policy, University of Nottingham, 21-22 April 2006. Available at:

https://www.nottingham.ac.uk/gep/documents/conferences/2006/postgradconf2006/hernandez-postgradconf2006.pdf

(last consulted on 10/05/16).

http://www.tandfonline.com/doi/abs/10.2753/CES1097-1475390306?journalCode=mces20



4

notably suggests that a 10 % increase international remittances can produce a 3.5% decline in the

share of people living in poverty in African countries. The relationship would notably be explained

by their tendency to a) be disproportionately spent on human capital-building areas; b) be

countercyclical in nature; c) increase the level of income for the poor rather than the growth of the

economy as a whole.7 In fact, the primary gap in evidence regarding remittances' development

impact is the lack of research supporting their positive impact on economic growth. This is

notably due to the fact that it is often difficult to separate the cause from the effect, if remittances

react counter-cyclically to growth.8 We shall therefore investigate further in this paper (1)

whether the positive impact of remittances on poverty reduction can be confirmed for Central

American economies; (2) whether there is a causation relationship between remittances and

economic growth.

DATA

I selected out Panama, Costa Rica and Honduras as the sample representing Central America.

These three countries were relatively similar in size in 1981, have a similar geographical situation

and would be expected to have similar migration levels. These three selected countries have

however pursued different economic development strategies in recent years, which have been more

or less successful. This combination may allow us to draw more practical conclusions on the

effectiveness of these strategies.

For the purpose of this research, I used the following data, available on the World Bank's website:9

Independent variables

Foreign direct investment, net inflows (BoP, current US$). According to the World Bank

definition, FDI refers to “a category of cross-border investment associated with a resident in

one economy having control or a significant degree of influence on the management of an

enterprise that is resident in another economy.” The matadata points out that FDI represents

“the sum of equity capital, reinvestment of earnings, and other capital.” This means that

investment in non-productive assets, such as assets being transferred to shale companies (as

7 Dilip Ratha “The impact of Remittances on Economic Growth and Poverty Reduction,” MPI paper, September

2013. Available at: http://www.migrationpolicy.org/research/impact-remittances-economic-growth-and-poverty-

reduction (16/05/16).

8 Paolo Giuliano and Marta Ruiz Arranz, “Remittances, Financial Development and Growth,” Working paper 05/234,

International Monetary Fund, 2005. Available at: http://www.imf.org/external/pubs/cat/longres.aspx?sk=18607.

9 Indicators, The World Bank. Available at: http://data.worldbank.org/indicator (last consulted on 15/05/16).

http://www.migrationpolicy.org/research/impact-remittances-economic-growth-and-poverty-reduction


http://www.imf.org/external/pubs/cat/longres.aspx?sk=18607

http://data.worldbank.org/indicator

5

one could reasonably assume in the case of Panama) will also be included. We should hence

be aware of a possible type 2 error in the relationship between FDI and GDP per capita, as

this wide definition of FDI may artificially increase this relationship.

Net ODA received per capita (current US$). This indicator is notably based on

disbursements of loans made on concessional terms and grants by individual countries

and by multilateral institutions. The caveat here is that it may be difficult to understand

which factor causes the relationship as negative relationship between ODA received and

GDP per capita may reflect either a negative impact of ODA on growth, or, perhaps more

likely, the reimbursement of a loan in a context of positive economic development.

Personal remittances, received (current US$). Personal remittances as defined by the World

Bank rest upon personal transfers (transfers in cash or in kind from migrants) and

compensation of employees. It is worth noting that the personal remittances received

will directly be linked to the level of migration out of the country.

Dependent variables

Poverty headcount ratio at $1.90 a day (2011 PPP) (% of population) indicates the

percentage of the population living on less than $1.90 a day at 2011 international prices.

This data is limited between 1981 and 1988. The fact that the poverty headcount ratio is

used as a dependant variable of our analysis mitigates the impact. However, the

relationship between independent variables and the poverty headcount will be more

significant for the years starting from 1988.

GDP per capita (current US$): GDP is the sum of gross value added by all resident

producers in the economy plus any product taxes and minus any subsidies not included in

the value of the products. It is worth noting that this indicator does not include the

contribution of the informal economy, which may relevant for the study of an economy like

Panama whose culture and practice of secrecy is set to attract such kind of investment.

I also look at the evolution of the total population in each country, in order to transform all

indicators on a per capita basis, and to make the comparison more insightful. All these data are from

the World Bank website and are the data being used in the graphs realised in this paper.

6

ANALYSIS

DESCRIPTIVE STATISTICS

Looking at the mean, the standard deviation, and the coefficient of skewness for GDP per capita

and poverty we note that:

Panama and Costa Rica have had similar development levels between 1981 and 2013, with

an average GDP per capita (about $4 000 per capita for both countries) and an average

poverty headcount ratio (averaging 7% for Costa Rica and 11% for Panama) reaching

similar results. On the other hand, we can see that Honduras was at a lower development

level between 1981 and 2013, with an average GDP per capita reaching only 1159 $ and a

poverty headcount ratio averaging 25% of its population over the period studied.

Standard deviation

344.37

49.92

181.06

16.46

20.11

32.48

28.30

150.04

50.05

6.02

7.89

5.06

2474.26

563.92

2466.66

MEAN

FDI, net inflows par capita (BoP, current US $) 1981-2013

Panama 319.97

Honduras 46.21

Costa Rica 174.77

Net ODA received per capita (current US$) 1981-2013

Panama 16.49

Honduras 70.00

Costa Rica 29.38

Personal remittances received per capita (current US$) 1981-2013

Panama 47.41

Honduras 123.24

Costa Rica 48.66

Poverty headcount ratio at $1.90 a day (2011 PPP) (% population) 1981-2013

Panama 11.24

Honduras 24.97

Costa Rica 6.90

GDP per capita 1981-2013

Panama 4215.77

Honduras 1159.03

Costa Rica 4061.58

TABLE 1: Mean and standard deviation for all indicators

7

FIGURE 1 (Source: World Bank)

The above graph highlights differences in the evolution of the GDP per capita in the three

countries, indicating an inability for Honduras’s economy to follow similar development as

its neighboring countries from the 1990's. This also reflects a more general feature of our

data, which indicates inconsistent development levels of most indicators (including FDI for

example) across the period studied. Looking at the standard deviations, as well as at the

confidence level, we can note that evolution of the indicators do not follow normal

distributions. For instance, the above graph indicates that the distribution is in fact

negatively skewed for the GDP per capita in Panama and Costa Rica, which can account for

the catching-up phase that these economies currently undergo.

Evolution of the independent variables over the period studied

Looking at the evolution of our independent variables on a country-by-country basis (see

graphs below), we can note that both Panama and Costa Rica have received a higher proportion of

FDI inflows than of development aid and personal remittances. By opposition, it is interesting to see

that Honduras mostly benefits from personal remittances and net ODA, reflecting a different level

of development.

8



9


Cross-country comparison of the evolution of each indicator

Comparing the evolution of each indicator across the countries studies also enables us to draw the

following conclusions:

The fact that the FDI curve is negatively skewed with FDI net inflows per capita showing a

rising trend since the 1990's reflect evidence highlighted by the existing literature on the

impact of globalisation. This trend indeed exacerbates from 2003 onwards, exclusion being

made from the 2008 to 2010 years. The shock observed in these years reflects the recession

of the last financial crisis. The capital flight observed in 1998 in Panama may also be related

to the 1997-1998 Asian financial crisis, to which Panama would have been more exposed

than its counterparts.10

10Juan Luis Moreno-Villalaz, “Lessons from the monetary experience of Panama: a dollar economy with financial

integration,” Cato Journal, Vol. 18, No. 3, Winter 1999. Available at:

http://object.cato.org/sites/cato.org/files/serials/files/cato-journal/1999/1/cj18n3-12.pdf ((last consulted on

15/05/16).

http://object.cato.org/sites/cato.org/files/serials/files/cato-journal/1999/1/cj18n3-12.pdf

10


The evolution of the ODA received also offers interesting insight. We can first note an

important decrease in Costa Rica's reliance on development aid from 1990 to 1996. This

raises the question of the extent to which this drop may be due to positive economic

development, a question which will be further analysed in the correlation analysis. Two

shocks also deserve specific attention: the 1998 peak in Honduras is likely corresponds to

the rise in international solidarity following the 1998 Mitch Hurricane; the sudden drop in

ODA received in Panama in 2007 is expected to reflect the impact of the crisis. It is

interesting to note, however, that no such evolution can be assessed in Honduras and Costa

Rica over the same period.


11

Finally, the evolution of the personal remittances data indicates a general increasing trend

for all countries from 2000 to 2007, but above all, a very important growth for Honduras

from the end of the 1990's until 2007. The increase in immigration from Honduras to the

United States in these years is certainly an important factor in this evolution.11


CORRELATION ANALYSIS

Having looked at the drivers behind the evolution of these indicators, we now look at

whether a correlation can be observed between our independent and our dependent variables.

We use Excel's formula to determine the R score of the Pearson's coefficient. Calculating the

P value and conducting a P test is necessary to find out the significance level of our correlation

coefficient. As Excel does not provide the appropriate function, we use the function provided by the

Social Science Statistics website to find these two indicators, and add them to our Excel table.12

We find that most of our correlation coefficient are both strong and significant, with the

exception of:

the relationship between net ODA received and poverty headcount;

11Elizabeth Ellen Cramer ‘Honduran immigrants,’ Immigration to United States. Available at:

http://immigrationtounitedstates.org/555-honduran-immigrants.html (last consulted on 14/05/16).

12‘P Value from Pearson (R) Calculator,’ Social Science Statistics. Available at:

http://www.socscistatistics.com/pvalues/pearsondistribution.aspx (last consulted on 02/05/16).

http://immigrationtounitedstates.org/555-honduran-immigrants.html


http://www.socscistatistics.com/pvalues/pearsondistribution.aspx

12

the relationship between net ODA received and GDP per capita;

for Panama and Honduras.

The following graphs provide better visual representation of these findings:

FDI net inflows

The graphs below related to the impact of FDI clearly indicate a strong positive relationship

between FDI inflows and GDP in all three countries, as well as a clear negative relationship

between FDI inflows and the poverty headcount in Panama and Costa Rica, and to a lesser extent in

Honduras. This goes in line with existing research on FDI's positive impact on growth and poverty

reduction.


Panama

0 200 400 600 800 1000 1200 1400

0

5

10

15

20

25

FDI net inflows and Poverty Headcount in Panama

FDI net inflows per capita and Poverty Headcount

FDI net inflows par capita (current US$)

Pove

rty h

ea

dcou

nt

ratio

(%

po

p)


0 200 400 600 800 1000 1200 1400

0

2000

4000

6000

8000

10000

12000

FDI net inflows and GDP in Panama

FDI net inflows per capita and GDP per capita

FDI net inflows per capita (current US$)

GD

P p

er

ca

pita (

cu

rren

t U

S$

)

13

Honduras

0 20 40 60 80 100 120 140 160 180

0

5

10

15

20

25

30

35

40

45

50

FDI net inflows and Poverty Headcount in Honduras

FDI net inflows per capita and Poverty Headcount


Pove

rty H

ead

co

un

t ra

tio

(%

po

pu

lation

)


0 20 40 60 80 100 120 140 160 180

0

500

1000

1500

2000

2500

3000

FDI net inflows and GDP in Honduras



GD

P p

er

ca

pita (

cu

rren

t U

S$

)


Costa Rica

0 100 200 300 400 500 600 700 800

0

5

10

15

20

25

30

FDI net inflows and Poverty headcount in Costa Rica

FDI net inflows and Poverty Headcount

FDi, net inflows per capita (BoP, current US$)

Pove

rty h

ea

dcou

nt

ratio

(%

po

pu

latio

n)


14

0 100 200 300 400 500 600 700 800

0

2000

4000

6000

8000

10000

12000

FDI net inflows and GDP in Costa Rica



GD

P p

er

ca

pita (

cu

rren

t U

S$

)


Official Development Aid (ODA)

The below figures indicate that it is more difficult to find any correlation between official

development aid and growth, as well as between development aid and the poverty headcount for

Panama and Honduras. Costa Rica's example indicates a negative relationship between ODA and

GDP, and a positive one between ODA and the poverty headcount ratio.

Panama


-60 -40 -20 0 20 40 60 80

0

5

10

15

20

25

Net ODA received and Poverty Headcount in Panama

Net ODA received and Poverty Headcount

Net ODA received per capita (current US$)

Pove

rty H

ead

co

un

t ra

tio

(%

po

pu

lation

)

15


Honduras

20 40 60 80 100 120 140

0

5

10

15

20

25

30

35

40

45

50

Net ODA received and Poverty Headcount in Honduras



Pove

rty H

ead

co

un

t ra

tio

(%

po

pu

lation

)


20 40 60 80 100 120 140

0

500

1000

1500

2000

2500

3000

Net ODA received and GDP in Honduras

Net ODA received par capita and GDP per capita


GD

P p

er

ca

pita (

cu

rren

t U

S$

)


-60 -40 -20 0 20 40 60 80

0

2000

4000

6000

8000

10000

12000

Net ODA received per capita and GDP per capita in Panama



GD

P p

er

ca

pita (

cu

rren

t U

S$

)

16

Costa Rica

-20 0 20 40 60 80 100 120

0

5

10

15

20

25

30

Net ODA received and Poverty Headcount in Costa Rica



Pove

rty H

ead

co

un

t ra

tio

(%

po

pu

lation

)


-20 0 20 40 60 80 100 120

0

2000

4000

6000

8000

10000

12000

Net ODA received and GDP in Costa Rica



GD

P p

er

ca

pita (

cu

rren

t U

S$

)


Personal remittances

The below graphs clearly indicate a strong positive relationship between personal

remittances and GDP, as well as a strong negative relationship between personal remittances and

poverty reduction in all countries.

17

Panama

0 20 40 60 80 100 120 140

0

5

10

15

20

25

Personal remittances and Poverty Headcount in Panama

Personal remittances and Poverty Headcount

Personal remittances received per capita (current US$)

Pove

rty H

ead

co

un

t ra

tio

(%

po

pu

lation

)


0 20 40 60 80 100 120 140

0

2000

4000

6000

8000

10000

12000

Personal remittances and GDP in Panama

Personal remittances received per capita and GDP per capita


GD

P p

er

ca

pita (

cu

rren

t U

S$

)


Honduras

0 50 100 150 200 250 300 350 400 450

0

5

10

15

20

25

30

35

40

45

50

Personal remittances and Poverty Headcount in Honduras

Personal remittances and Poverty Headcount


Pove

rty H

ead

co

un

t ra

tio

(%

po

pu

lation

)


18

0 50 100 150 200 250 300 350 400 450

0

500

1000

1500

2000

2500

3000

Personal remittances and GDP in Honduras



GD

P p

er

ca

pita (

cu

rren

t U

S$

)


Costa Rica

0 20 40 60 80 100 120 140 160

0

5

10

15

20

25

30

Personal remittances and Poverty Headcount in Costa Rica

Personal remittances received per capita and Poverty Headcount


Pove

rty H

ead

co

un

t ra

tio

(%

po

pu

lation

)


0 20 40 60 80 100 120 140 160

0

2000

4000

6000

8000

10000

12000

Personal remittances and GDP in Costa Rica



GD

P p

er

ca

pita (

cu

rren

t U

S$

)


19

***

This study attempted to investigate whether the evolution of the GDP per capita and Poverty

headcount ratio indicators in Panama, Costa Rica and Honduras between 1981 and 2013 may be

correlated to changes in the level of (1) Foreign Direct Investments; (2) Personal remittances; (3)

Official Development Aid. Though these findings should be considered carefully for the period

between 1981 and 1988 due to the limitation of the data on poverty headcount, the following

conclusions have emerged from this research:

There is a strong relationship between the evolution of FDI, growth and poverty reduction

over the period studied, which confirms that existing evidence on the topic can also apply to

this sample of Central American countries. The increase of FDI in these countries seems to

really take off from the 2000's only, i.e. slightly later than expected. Though this clearly

represents evidence for a relationship on longer-term trends, it is worth noting that sudden

drops in FDIs, such as those seen in crises, are not necessarily reflected in growth rates (see

Panama in 1998 and in 2007). One should also note that the inclusion of non-financial assets

in the definition of FDI may also artificially increase this relationship, notably in the case of

Panama.

Establishing a clear relationship between ODA, growth and poverty reduction is difficult.

Our study shows that this relationship is neither strong in one direction in another nor

significant for Panama and Honduras. The case of Costa Rica suggests a negative

relationship between the aid and economic development, which tends to confirm the idea

that aid may increase in less favourable environments. The peak in ODA received by

Honduras after the country was severely impacted by the Mitch hurricane represents

anecdotal evidence confirming this relationship.

The positive relationship between remittances, growth and poverty reduction can clearly be

identified in our research. We warned of the risk of a possible inverse relationship between

the two due to the traditional counter-cyclical nature of remittances. However, considering

the strength and significance of the relationships found in this research, this study rather

brings further evidence for a causal relationship between remittances and economic growth.

20

An important finding of this research is linked to the absence of a positive and significant

relationship between ODA and poverty reduction, as this finding may go against popular belief that

ODA should lead to poverty reduction. This may be explained by exogenous factors such as the

historical focus of aid on geopolitical considerations (with only a recent shift towards poverty

reduction objectives), or endogenous ones, such as the question of the direction of the causation. As

these findings may have policy consequences (as we have seen during the crisis with important

drops in ODA-spending), further research on the nature of this correlation is expected to be more

and more relevant.

21

BIBLIOGRAPHY

Calvo, Cesar C., Hernandez Marco A. “Foreign Direct Investment and Poverty in Latin America.”

Paper prepared to be delivered at the Globalisation and Economic Policy, Centre for Research on

Globalisation and Economic Policy, University of Nottingham, 21-22 April 2006. Available at:

https://www.nottingham.ac.uk/gep/documents/conferences/2006/postgradconf2006/hernandez-

postgradconf2006.pdf.

Ellen Cramer, Elizabeth. ‘Honduran immigrants.’ Immigration to United States. Available at:

http://immigrationtounitedstates.org/555-honduran-immigrants.html.

“International Migration and the Millennium Development Goals.” in Selected Papers of the

UNFPA Expert Group Meeting, Marrakech, 11-12 May 2005. Available at:

https://www.unfpa.org/sites/default/files/resource-pdf/migration_report_2005.pdf.

Giuliano, Paolo, Ruiz Arranz, Marta. “Remittances, Financial Development and Growth,” Working

paper 05/234, International Monetary Fund, 2005. Available at:

http://www.imf.org/external/pubs/cat/longres.aspx?sk=18607.

Guillaumont, Patrick, Chauvet, Lisa. ‘Aid and Performance: A Reassessment.’ Journal of

Development Studies, 2001.

Indicators, The World Bank. Available at: http://data.worldbank.org/indicator.

“International Migration and the Millennium Development Goals.” in Selected Papers of the

UNFPA Expert Group Meeting, Marrakech, 11-12 May 2005. Available at:

https://www.unfpa.org/sites/default/files/resource-pdf/migration_report_2005.pdf.

Moreno-Villalaz, Juan Luis. “Lessons from the monetary experience of Panama: a dollar economy

with financial integration.” Cato Journal, Vol. 18, No. 3, Winter 1999. Available at:

http://object.cato.org/sites/cato.org/files/serials/files/cato-journal/1999/1/cj18n3-12.pdf.

‘P Value from Pearson (R) Calculator,’ Social Science Statistics. Available at:

http://www.socscistatistics.com/pvalues/pearsondistribution.aspx.

Raghuram, Rajan, Subramanian, Arvind. “Aid and Growth: What Does the Cross-Country

Evidence Really Show?” Working Paper 05/127, IMF, Washington D.C, 2005.

Ratha, Dilip “The impact of Remittances on Economic Growth and Poverty Reduction,” MPI

paper, September 2013. Available at: http://www.migrationpolicy.org/research/impact-remittances-

economic-growth-and-poverty-reduction.

Tribe, Mike. “ODA, Economic Growth and Poverty Reduction.” Ideas4development, 1 December

2010. Available at: http://ideas4develop.blogspot.fr/2010/12/oda-economic-growth-and-

poverty.html.

Zhang, Kevin Honglin. “Does International Investment Help Poverty Reduction in China?.” The

Chinese Economy,Volume 39, Issue 3, 2006. Available at:

http://www.tandfonline.com/doi/abs/10.2753/CES1097-1475390306?journalCode=mces20.






http://www.imf.org/external/pubs/cat/longres.aspx?sk=18607

http://data.worldbank.org/indicator


http://object.cato.org/sites/cato.org/files/serials/files/cato-journal/1999/1/cj18n3-12.pdf

http://www.socscistatistics.com/pvalues/pearsondistribution.aspx






22

APPENDIX: Definition of World Bank indicators


Net official development assistance (ODA) per capita consists of disbursements of loans made on

concessional terms (net of repayments of principal) and grants by official agencies of the members

of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC

countries to promote economic development and welfare in countries and territories in the DAC list

of ODA recipients; and is calculated by dividing net ODA received by the midyear population

estimate. It includes loans with a grant element of at least 25 percent (calculated at a rate of

discount of 10 percent).

Development Assistance Committee of the Organisation for Economic Co-operation and

Development, Geographical Distribution of Financial Flows to Developing Countries,

Development Co-operation Report, and International Development Statistics database. Data are

available online at: www.oecd.org/dac/stats/idsonline. World Bank population estimates are used

for the denominator.

Personal remittances, received (current US$)

Personal remittances comprise personal transfers and compensation of employees. Personal

transfers consist of all current transfers in cash or in kind made or received by resident households

to or from nonresident households. Personal transfers thus include all current transfers between

resident and nonresident individuals. Compensation of employees refers to the income of border,

seasonal, and other short-term workers who are employed in an economy where they are not

resident and of residents employed by nonresident entities. Data are the sum of two items defined in

the sixth edition of the IMF's Balance of Payments Manual: personal transfers and compensation of

employees. Data are in current U.S. dollars.

World Bank staff estimates based on IMF balance of payments data.

Foreign direct investment, net inflows (BoP, current US$)

Foreign direct investment refers to direct investment equity flows in the reporting economy. It is the

sum of equity capital, reinvestment of earnings, and other capital. Direct investment is a category of

cross-border investment associated with a resident in one economy having control or a significant

degree of influence on the management of an enterprise that is resident in another economy.

Ownership of 10 percent or more of the ordinary shares of voting stock is the criterion for

determining the existence of a direct investment relationship. Data are in current U.S. dollars.

International Monetary Fund, Balance of Payments database, supplemented by data from the

United Nations Conference on Trade and Development and official national sources.

GDP per capita (current US$)

GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross

value added by all resident producers in the economy plus any product taxes and minus any

subsidies not included in the value of the products. It is calculated without making deductions for

depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in

current U.S. dollars.

World Bank national accounts data, and OECD National Accounts data files.

Poverty headcount ratio at $1.90 a day (2011 PPP) (% of population)

Poverty headcount ratio at $1.90 a day is the percentage of the population living on less than $1.90

a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for

individual countries cannot be compared with poverty rates reported in earlier editions. Note: five

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countries -- Bangladesh, Cabo Verde, Cambodia, Jordan, and Lao PDR -- use the 2005 PPP

conversion factors and corresponding $1.25 a day and $2 a day poverty lines. This is due to the

large deviations in the rate of change in PPP factors relative to the rate of change in domestic

consumer price indexes. See Box 1.1 in the Global Monitoring Report 2015/2016

(http://www.worldbank.org/en/publication/global-monitoring-report) for a detailed explanation.

World Bank, Development Research Group. Data are based on primary household survey data

obtained from government statistical agencies and World Bank country departments. Data for high-

income economies are from the Luxembourg Income Study database. For more information and

methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).

Population, total

Total population is based on the de facto definition of population, which counts all residents

regardless of legal status or citizenship--except for refugees not permanently settled in the country

of asylum, who are generally considered part of the population of their country of origin. The values

shown are midyear estimates.

(1) United Nations Population Division. World Population Prospects, (2) United Nations Statistical

Division. Population and Vital Statistics Report (various years), (3) Census reports and other

statistical publications from national statistical offices, (4) Eurostat: Demographic Statistics, (5)

Secretariat of the Pacific Community: Statistics and Demography Programme, and (6) U.S. Census

Bureau: International Database.

http://iresearch.worldbank.org/PovcalNet/index.htm

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