Foreign Aid vs. Economic Growth
A Case Study Analysis on the Impact of Foreign Aid on
Economic Growth in Nigeria
Bachelor Thesis
Author: Marfal Fontes da Costa (10102167)
Thesis supervisor: Andro Rilović
June 2015
Faculty of Economics and Business Programme: Bsc Economics and Business
Specialization: Economics Field: Development Economics
Abstract
This thesis investigates the relationship between foreign aid inflows to Nigeria and the effect it has on Nigeria’s GDP growth for the period 1981-2013. An OLS approach is used to determine this relationship and the weakly significant result is found that there seems to be no effect for that period on Nigerian GDP. The
theoretical framework designates importance towards import, export and investment such that these variables are also included in the model. For Nigeria it is concluded that policies seem to have a lot of influence in the effectiveness of aid, such that it is recommended that further research should give policies central attention in the aid effectiveness case for Nigeria.
Statement of Originality
This document is written by Student Marfal Fontes da Costa who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
Contents
1. Introduction………....4
2. Theoretical Framework………. 5
2.1 Foreign Aid: A Brief Historic Overview of Donor Considerations……… 5
2.2 Foreign Aid: An Overview of some Relevant Studies ………8
2.3 Foreign aid and Nigeria: Recent Empirical Evidence ………..12
3. Methodology………16
3.1 Description of Data and Variables……… 16
3.2 Model Specification……….. 17
4. Analysis and Discussion………. 20
5. Conclusion ………..21
6. References………... 23
Appendix A: Figures………... 25
1. Introduction
The subject of whether foreign aid has a significant impact on the economic growth of the recipient countries is one that is extensively studied in the field of development economics. Despite of this, or perhaps even because of this we find opposing results in the conducted studies that wish to assess the effectiveness of foreign aid or of other types of financial assistance. The results span the entire spectrum, from it having positive, inconclusive or even having negative effects on economic growth. These results can be observed across overlapping samples of countries or even for the exact same samples of countries. The range of publication dates of aid effectiveness studies go almost as far back as the emergence of foreign aid itself, which provides researchers with an extensive range of moments in aid-based history to evaluate the observed results.
Since the emergence of the framework of development-based aid transfers, that has its origins in the Bretton Woods system, an estimated 2 trillion dollars have been transferred from the developed countries of the world to Africa (Moyo, 2010). Intuitively, if a person might stop to think about this fact and then think about their general view of Africa, this might possibly lead to amazement. What is the intended goal of foreign aid and has it been successful in reaching its goal? This might then be a natural follow-up question that certainly deserves all the attention it has gotten so far. A nice way of gaining understanding in the workings and implications of foreign aid inflows to beneficiary countries is to just focus on a few countries or just on one for analysis purposes, given that most studies employ cross-country analysis for a larger set of countries some sets even nearing a hundred countries (Hansen & Tarp, 2001). A single focus approach could thus lead to more detailed insight specifically to the country under investigation. Regardless of the conclusion that is drawn it will add valuable information to the field of development economics on which policy-makers might draw from in their decision-making processes.
In the World Economic Outlook report published April 2015 by the
International Monetary Fund (IMF), Nigeria is classified as both being an emerging market as well as a developing economy. The most recent data of the World Bank on Nigeria classify her as having a lower middle-income level in 2013 and having 46% of their population living under the poverty line in 2010. However if you look at economic growth in the past years this has one period actually averaged 6.8% per year (Appendix A: figure 4), with its diverse economy accounting for about 35% of GDP
for Sub-Saharan Africa (IMF, 2015). It seems that in spite of the realized economic growth, that can to a large extent be attributed to the diversity of the economy (oil production, services sector and the abundance of natural and human resources), Nigeria has still not been able to improve their numbers when it comes to
development indicators (Fasanya, 2012). And even when we examine year-to-year growth of GDP we see that it is not consistent, with intermittent periods of slowdown and that for 2015 it is projected that GDP will decrease due to a decrease in oil prices (IMF, 2015). Nigeria is still a beneficiary of Official Development Assistance
(ODA)1 and it does not seem that this assistance will stop in the near future. Along with the aforementioned, having a population of over 170 million and having a big share in the GDP of Sub-Saharan Africa, Nigeria makes for an excellent candidate to study the effects of foreign aid on economic growth. This thesis will thus primarily focus on aid effectiveness in Nigeria and by extension some inferences could be drawn on the (Sub-Saharan) African region.
From here on Section 2 of this thesis will start off with providing a theoretical background on general foreign aid literature and foreign aid as it relates to Nigeria. Section 3 will set out the methodology that will be used for the analysis part, where Section 4 will then analyze and discuss the results. Finally in Section 5 a conclusion will be presented.
2. Theoretical framework
2.1 Foreign Aid: A Brief Historic Overview of Donor Considerations
In the wake of World War II, the world and especially the European continent were left in need of restructuring and rebuilding. At the start of July 1944 the Bretton Woods Conference was held with over 700 delegates from 44 countries, with the intention to establish an outline for global cooperation on several international economics topics (Hjertholm & White, 2000). It is from this conference that two important institutions for the advancement of international development were created,
1
The DAC defines ODA as “those flows to countries and territories on the DAC List of ODA Recipients and to multilateral institutions which are:
i. Provided by official agencies, including state and local governments, or by their executive agencies; and ii. each transaction of which:
a) is administered with the promotion of the economic development and welfare of developing countries as its main objective;
b) is concessional in character and conveys a grant element of at least 25 per cent (calculated at a rate of discount of 10 per cent).”
namely the International Monetary Fund (IMF) and the International Bank for
Reconstruction and Development (IBRD, later: became part of the World Bank). The former then being responsible for managing the global financial system and the latter occupying itself with reconstruction through capital investments (Moyo, 2010). Now both play a central role as they oversee and facilitate the disbursements of foreign aid, determine the necessary prerequisites for recipient countries to receive aid and they themselves closely assess the impact that foreign aid has.
Hjertholm & White (2000) set out the post-World War II development of aid distribution in their paper ‘Survey on Foreign Aid: History, Trends and Allocation.’ and Moyo (2010) also provides a timeline in her book ‘Dead Aid: why aid is not
working and how there is another way for Africa’. Hjertholm & White (2000) recount
that in the 1950s aid was heavily influenced by the U.S. as about 2/3 of total aid administered in that period came from U.S. institutions. During the Cold War this influence intensified and led to increased disbursements of aid towards Africa with the primary intention to prevent communism from spreading. Another element strengthening this concern of the U.S. was the start of the decolonization process in Africa as the first wave of African countries gained their independence and African leaders were now open to international cooperation. Hjertholm & White (2000) also explain that the establishment of the Development Assistance Committee (DAC) in 1961, which is a part of the Organization for Economic Co-operation and
Development (OECD) founded in 1948, came out of the wish of the U.S. to share the burden of foreign aid as the benefits from halting communism would accrue to the entire Free World. It is in this period were the emergence of bilateral aid (direct government-to-government aid) took off as new donors joined who recognized the benefits from aid programmes.
The 1960s were characterized by project-based given aid with the aim to help the industrialization process of Africa through large infrastructural programmes that would help spur economic growth, of which the donor countries believed that these could not yet be achieved by the private sector (Moyo, 2010). However Moyo (2010) notes here that there is a lack of statistical records to measure the width and depth of these aid flows and that by the beginning of the 1970s there was not much
infrastructure to account for. The 1960s also saw the second wave of decolonization as more African countries gained their independence (Hjertholm & White, 2000).
The 1970s saw the development of two trends with the two oil crisis at its backdrop, namely the provision of quick disbursing assistance (QDA)(also:
emergency loans) by the IMF and later a focus on import support aid and the trend of structural adjustment loans (or: programme aid) by the World Bank (Hjertholm & White, 2000). This is also the decade were the share of multilateral distributed aid (aid donated by multiple donors distributed through one institution) started to increase. Moyo (2000) also reports that after the last oil crisis occurred in 1980 another shift in thinking about aid happened in that it now leaned towards a more poverty-focused approach. This resulted from the severe debt problems the
developing countries were left with as a great deal of surpluses from oil-exporting countries were loaned to them through international banks often denominated in the currency of the lender (mostly dollars) at a floating interest rate. This affected the least developed countries in (Sub-Saharan) Africa in a negative manner leading to scarcity in the provision of commodities. She also mentions that as the 1982 debt crisis came about donor countries were concerned about a major default in these loans that could lead to the destabilization of the international financial system. Therefore the IMF and the World Bank gained even more influence during this period, as the IMF created the structural adjustment facility to loan to defaulting countries thereby also increasing aid-dependency. Hjertholm & White (2000) further recount that criticism increased on the objectives of these bilateral and multilateral aid flows, as they did not serve the best interest of the developing countries, but rather those of the developed world.
From the 1990s onwards the tendency on aid disbursements moved back to a more poverty-based approach this time also accompanied by good-governance policies. The intention here was to bring democracy values to African countries and promote free-market growth with the idea that aid would then be utilized most effectively and then subsequently would eventually lead to economic growth
(Hjertholm & White, 2000). Moyo (2010) notes on this period that the liberalization of African markets not only allowed African companies to succeed, but that it also allowed room for them to fail, which many of them did as they were not strong enough to reap the benefits of liberalization immediately.
Moyo (2000) further ends her recount of the history of aid with noting that the 2000s saw the culmination of the idea that aid is the only way to solve Africa’s problems so that the policy stances did not change that much anymore. The form in
which aid is administered could differ as NGOs and other types of smaller-scale agencies also gained prominence in the foreign aid field. It may be that the amount to spend on foreign aid may find itself in the middle of a public debate, but the main idea remained, namely that aid indeed could lead to economic growth and thus also ultimately lead to poverty reduction (Moyo, 2000). Today the DAC still maintains the target that 0.7% of Gross National Income should be provided by the donor countries as ODA, with however only a few members actually meeting this target (OECD, 2003).
2.2 Foreign Aid: An Overview of some Relevant Studies
Burnside & Dollar published their highly influential paper ‘Aid, Policies and
Growth’ in the American Economic Review in 2000. It became a popular reference
point for donor policy makers as it was often used to justify aid distribution choices. Their paper set out to investigate the relationship between foreign aid and economic growth per capita and focuses on the effects of the presence of “good” economic policies in the recipient countries. For this they conducted panel growth regressions for 56 developing countries, including countries from Sub-Saharan Africa (also Nigeria) over six four-year periods ranging from 1970-1993. In short their paper corroborated the intuitive result that foreign aid has a positive impact on developing countries with “good” economic policies (Burnside & Dollar, 2000).
Burnside & Dollar (2000) constructed a policy index to determine when an economic policy is considered to be good by regressing data on budget surplus, inflation and trade openness numbers to in turn use this index in the model for aid effectiveness. The complete model they used is a modified version of the neoclassical growth model, which is generally considered to be the Solow-Swan growth model. This model intends to explain long-run economic growth by relating the rate of capital accumulation, population growth, savings and technical progress (Ray, 1998). Ray also explains in his book that a labor abundant country will initially see higher growth-rates from steady increases in capital.
In total three questions were addressed and investigated in Burnside & Dollar’s papers. The first being whether foreign aid has as positive impact on growth when there are good economic policies present. The Ordinary Least Squares (OLS) and the Two-Stage Least Squares (2SLS) methods are used with and without
For their dataset they found robust results that foreign aid indeed has a positive impact on economic growth in the presence of a good policy environment.
The second question concerned whether foreign aid donors tend to allocate more aid towards countries that employ a good policy. The same econometric techniques are employed and Burnside & Dollar build on earlier research in order to determine the relevant variables to include. To asses donor countries considerations dummy variables are used including a proxy of the ratio of weapons imports over total imports. Here they find that donor countries do seem to reward countries that employ a good policy.
The final question addressed is on whether aid itself has contributed to good policies. They did not find results that underscored that foreign donation itself also contributes to better policies in the recipient countries, but they did add that in general the policy climate in developing countries seemed to signal a positive trend over time so that foreign aid disbursements and the presence of good policy seemed to coincide more often (Burnside & Dollar, 2000).
Easterly, Levine & Roodman (2004), were amongst many scholars that published a paper in response to the works of Burnside & Dollar. They choose to replicate the study, thus using the same econometric techniques, but to expand the dataset from 1970-1993 to 1970-1997 as more data had become available over time. They found that Burnside & Dollar’s findings where no longer robust with the expansion of the dataset and thereby stated that the original findings must be reconsidered in terms of explanatory power (Easterly et al., 2003). Easterly et al. (2003) stress that they do not argue that aid itself is not effective, but rather that other foreign aid growth mechanisms should be considered and that additional research should be stimulated.
Burnside & Dollar (2004) replied to Easterly et al.’s critiques in another article (published in the same issue of the journal) where they find that it is especially the inclusion of additional countries in the dataset that lead to Easterly et al.’s conclusion that the original results are not robust. Burnside & Dollar’s (2004) claim is preceded by another replication of their own studies with the expanded dataset that Easterly et al. used and ends with countering that Easterly et al.’s conclusion is too negative a conclusion to draw and that even other reasons can be found as to why good policy environments do attribute to economic growth.
Hansen & Tarp have both made numerous contributions to the field of
development economics and they both also pay attention to aid effectiveness research. One regularly cited paper of theirs is ‘Aid and Growth Regressions’ published in 2001. In that paper they examine the relationship between foreign aid and growth in real GDP in a cross-countries studies. They find several meaningful results and implications that will be revisited here.
First Hansen & Tarp (2001) compare cross-country aid effectiveness studies, including that of Burnside & Dollar (2004), that find positive but decreasing marginal returns to aid. For this they construct a model that includes the policy term and a term for aid squared that can capture diminishing marginal returns to aid effects. Amongst the other variables are some political and other institutional indicators with the inclusion of the initial level of GDP, of which the latter Hansen & Tarp (2001) explain to be able to capture convergence effects. The econometric techniques used are OLS and Instrumental Variables (IV) regression. The results show that the preferred model includes a variable for aid squared but without a policy interaction term and that there is a positive effect of foreign aid on GDP growth and also a rather quick decrease in the marginal effects thereof (Hansen & Tarp, 2001). They conclude for that part that they find it to be premature for researchers to attribute great
importance to policy indexes.
Hansen & Tarp (2001) then turn to the question of whether the potential endogeneity of aid can cause bias problems when interpreting results. On this subject Hansen & Tarp find it surprising that most recent cross-country studies seem to find that aid is exogenous and that there is negligible bias. However when they revisit this subject and augment the models to include country specific effects there seems to be strong evidence of the aid bias problem. Hansen & Tarp (2001) then use another OLS model to estimate effects of aid and manage to get consistent results when country specific effects are accounted for. They also point out that different methodological methods across studies can explain the lack of findings on aid bias problems, however that mention that as the literature on aid effectiveness evolves, techniques also evolve and that there seems to be a tendency towards uniformity in results of cross-country studies.
The final area Hansen & Tarp (2001) turn to concerns the classical notion that aid might inspire capital growth through increased investments, or capital
measures for Gross Domestic Investments, Foreign Direct Investments and a measure for human capital to have the most thorough measure of investment over the dataset. Hansen & Tarp (2001) find that when they control for investment and human capital that no positive effect of aid on growth is found, and mention that this may relate to the weight that the most aid-dependent countries have in the dataset. When Hansen & Tarp (2001) then use a Fixed Effects (FE) regression they find that the effect of the investment link is confirmed as aid does seem to impact growth via that channel and that the result is convincing. Hansen & Tarp (2001) close their paper by stressing the importance of laying out a solid theoretical foundation before undertaking any analytical efforts when it comes to cross-country studies. All in all their study seems to fall on the side of those that attribute aid to have its merits when it comes to realizing GDP growth for the recipient countries, however as almost all researchers do, the recognition that aid effectiveness is and will likely still be a highly challenged area of research is stated coupled with the request for more and continued research on the topic.
To close the brief overview of studies on aid effectiveness a short reference will be made to the paper of McGillivray ‘Is Aid Effective’ (2004). This paper can be viewed as being a ‘super-synthesis’ as it goes over trends in aid effectiveness
literature since the 1960s up until 2002, with emphasis on the Sub-Saharan African region. It references 36 studies, including the aforementioned of Burnside & Dolalr and Hansen &Tarp, however note that this paper does not contain original empirical research.
McGillivray (2004) evaluated empirical literature on the macro level
effectiveness of aid and names the 19972 work of Burnside and Dollar as one of the papers defining the turning point in the research for aid effectiveness. He states that in the empirical research conducted since then “aid now appears to work in the sense
that per capita economic growth would have been lower in its absence” (McGillivray,
2004, p. 2), whereas in the period up and until then the research on the effects of aid on economic growth seems to have garnered on the majority inconclusive or
contradictory results. He references 36 studies conducted between 1997-2004 of which 34 employed original empirical work and found that 34 papers concluded aid to work. McGillivray theorizes that a possible reason as to why this overturn in findings
2
This references the working paper version of the Burnside & Dollar paper that would go on to be published in the American Economic Review in 2000, also referenced in this thesis.
might have occurred might lie in that it is possible that empirical methods have improved since then. The question of whether good policies in the recipient country matter is also touched upon and corroborated to be indeed a positive factor.
McGillivray (2004) explains that the poor growth records of sub-Saharan Africa should not be attributed to aid ineffectiveness but that one should realize that these numbers would have actually been lower in the absence of aid. He also touches on the subject of diminishing returns to aid and acknowledges the existence thereof, so that having too much aid could eventually lead to negative returns. This has to do with the aid absorptive capacities of the recipient country. From the reviewed papers the amount of aid for this to happen ranges between 15 and 45 percent of the recipient countries GDP.
Concluding this sub-section leaves us with a general idea of the contents of aid effectiveness research, especially in the arena of cross-country studies. Remarking that the publication of one study can inspire the publication of others, leading to a vivid ‘dialogue’ between prominent researchers in the field that all themselves acknowledge the width and depths and complications of aid effectiveness research.
2.3 Foreign aid and Nigeria: Recent Empirical Evidence
Nigeria is the world’s 10th largest oil producer and tops the list as Africa’s largest oil producer with Algeria and Angola closing Africa’s top 3 (OECD, 2015). Even though Nigeria produces an estimated 2.5 million barrels of oils a day, oil production accounted for about 13% of GDP, whereas its services sector accounted for over 50% of GDP in 2013 (OECD, 2015; IMF 2015). It had been predominantly the non-oil producing sectors that lead to the positive average of 6.8% (Appendix A: figure 4) growth in the prior years. However as of today Nigeria is still classified as a developing country and Kolawole (2013) recognizes that the unequal distribution of wealth explains to a large extent why 46% of the population still lives under the poverty line (World Bank, 2015). Kolawole (2013) also names some other reasons for the problem of underdevelopment in Nigeria, which includes a lack of good
infrastructural facilities, wrong policy frameworks, outdated technology and an over-dependence on imported goods. Kolawole and several other authors have investigated the relationship between foreign aid and growth for Nigeria.
Alabi (2012), Fasanya & Onakoya (2012), Kolawole (2013), Tombofa, Edoumiekumo & Obudah (2013) and Mbah & Amassoma (2014) all mention in their
papers that for Nigeria ODA is primarily used as a supplement for short falling domestic savings that is needed to finance investments. The underlying idea here is that in order to achieve any economic growth, investments must increase which in the case for Nigeria could be achieved through an increase in ODA. If channeled properly to the productive sectors of the economy Alabi (2012) believes that ODA may
achieve economic growth if ODA can also supplements for low export earnings and low tax collections. A well-known theory in the field of development economics is that of the ‘Big Push’ in which simultaneous industrialization of different sectors of an economy can be profitable even if otherwise these sectors would not break-even if they were to industrialize by themselves (Murphy, Shleifer & Vishny, 1989). Murphy et al. further explore originator’s Rosenstein-Rodan’s model and recount that the intention is to create economic growth with neither expanding the initial technological endowments nor requiring technological spillovers from occurring. The only thing that is needed in this model is a simultaneous investment in all sectors, using the existing available technology and then reaping the increasing returns from each sector (Murphy et al., 1989). This model is used to explain why large amounts of aid are needed to inspire this necessary ‘big push’ that would then propel developing economies into self-sustainable economic growth. Given that and the upcoming literature, this could be amongst the theories that fall in line with explaining for Nigeria why there is such a large focus on increasing the level of investments.
Alabi (2012) researched the effect of ODA per sector of the Nigerian economy for the period 1981-2010. Under consideration is the percentage of aid used for a specific destination such as e.g. debt servicing (66.5%), health & population (13.8%), education (0%) and others and the percentage of aid received per sector such as the public administration (26.9%), health & social services (17.3%), agricultural sector (5.4%) and others. Using the Vector Auto Regression (VAR) model Alabi found that there is between a non-conclusive and negative relationship between GDP and ODA. He then seeks an explanation in stating that policy makers should strongly consider the policies that are in place in Nigeria before administering aid to certain sectors in order to gain better results. Alabi (2012) underlined this throughout his theoretical framework by pointing out that there is institutional weakness at both the federal and state level, weak capacity of aid coordination and infrastructural deficiencies in the country.
Fasanya & Onakoya (2012) researched in their work the relationship between foreign aid and economic growth for Nigeria in the period 1970-2010 using a model based on the neoclassical growth model. Their attention was also primarily on the level of domestic investments, with the addition of also mentioning the aid-policy growth hypothesis for which they reference the works of Burrnside & Dollar. As mentioned earlier Burnside & Dollar (2000) constructed a policy index in their paper and found that aid seems to have a positive impact in good policy environments. The model used by Fasanya & Onakoya however only includes the variables that allowed for inferences to be drawn on the importance of the short falling domestic savings. Fasanya & Onakoya (2012) used the OLS estimator method accompanied by econometric techniques to assess that the data could be used as it concerned a time series set. They found a significant and positive impact on economic growth adding that domestic investments rose due to the aid, thereby confirming the theory that closing the low-savings gap increases domestic investments and that it ultimately leads to increased economic growth. In their conclusion they hypothesize, referring back to their theoretical framework, that the inclusion of a policy-index may have had an adverse effect on economic growth for Nigeria and that policy makers should take this into account.
Kolawole (2013) used the Two-Gap model3 to examine the impact of ODA and Foreign Direct Investment (FDI) on real GDP growth in Nigeria over the period 1980-2011. The macroeconomic Two-Gap model (an extension of the Harrod-Domar model) can be used to study the effectiveness of foreign aid and does so by examining to what extent the two gaps, namely the savings gap (income minus expenditures) and the trade gap (current account) can be filled (Wijnbegen, van., 1984). The rationale behind the theory is that in order for an economy to grow at some desired rate these two gaps need to be additionally supplemented when there is a short falling. For lesser developed countries (LDCs) there tends to be an excess of imports over exports and an excess of investing over saving, leading to respectively a balance of payment deficit and pressure on the economy’s resources (Kolawole, 2013). As previously
3 E – Y National expenditure minus national output I – S Investment minus savings (savings gap) M – X Imports minus exports (trade gap) F Net capital inflow
Conditionality of the two gaps E – Y ≡ I – S ≡ M – X ≡ F Kolawole (2013).
stated the issue of short falling domestic savings is relevant for Nigeria. Kolawole (2013) examined the Two-Gap model using the Error Correction Model (ECM), combined with other econometric techniques and found Granger no-causality between any pair of the variables, a negative relationship between FDI and real growth and ODA having no impact on real growth. He therefore concludes that the level of foreign assistance (both ODA and FDI) does not have enough effect on the level of investments in Nigeria.
Tombofa, Edoumiekumo & Obudah (2013) examined the role that the level of external debt had on economic growth in Nigeria for the period 1981-2010, with the level of ODA also being a variable under investigation. Their overview reveal that during the 1970s and 1980s (during the oil/debt crisis) huge levels of debt were accumulated in Nigeria, 11 billion dollars in 1981 and 19 billion dollars by 1985, leading to high fractions of debt/total exports and debt/GNP levels. Nigeria’s debt increased steadily until in 2005 the Paris Club (an informal organization of creditor countries with observers from the IMF/World Bank/OECD) agreed on rescheduling some of Nigeria’s debt and allowed part of it to be relieved, such that external debt came down to 8 billion dollars in 2005 (Tombofa et al., 2013). Since then domestic debt has been increasingly incurred in favor of external debt and Tombofa et al. found a negative relationship between external debt and GDP growth, whereas they found a positive relationship between both domestic debt and foreign aid and economic growth using co-integration techniques and the ECM model in order to be able to establish whether there is a long-run relationship between all included variables.
Mbah & Omassoma (2014) studied the period 1981-2012 for Nigeria to
determine whether there is a relationship between the level of foreign aid (here: ODA) and economic growth (here: GDP growth). In their theoretical framework the Two-Gap model is also attributed a big role with a similar focus on the needed levels of investments. And also in this paper there is a discussion on the aid-policy growth theory, but there is no inclusion of such a proxy in the analysis part. Mbah & Omassoma (2014) find a negative, yet non-significant relationship between foreign aid and GDP using the Ordinary Least Squares (OLS) method with considerations on the usage of time series data. Suggestions are made towards political, institutional and economic reforms.
It is seen from these studies, all of them covering at least the period 1981-2010, that there is no one conclusive result to be drawn on aid effectiveness in
Nigeria. The full spectrum of observations is covered as we find negative, positive and inconclusive results on the impact of ODA on economic growth. It is however noteworthy to see that there seems to be a uniformity in stressing the importance of good-governance policies in most concluding parts of the papers done for Nigeria. However the mentioned studies did not actively researched the effects of policies that are in place. It is also important to note here that different econometric techniques were used between studies and that some studies included more variables into the analysis, such that ODA was not necessarily the main focus. It is therefore important to explain which model is being used to measure the relationship and be aware of possible limitations before analysing and discussing the results and basing policy implications on them. Nonetheless, with that in mind any new addition to the studies of aid effectiveness on the micro level remains very valuable.
3. Methodology
3.1 Description of Data and Variables
For Nigeria the period 1981-2013 will be investigated on the relationship between foreign aid and economic growth. The type of aid that will be at the heart of the focus is that of systematic government-to-government aid that is either bilateral or multilateral in nature. In particular for Nigeria we will use the Net ODA flows as a proxy for foreign aid. This means that for ODA the repayments by Nigeria for the concessional loan parts are netted out. As a proxy for economic growth we will use annual GDP numbers, as it remains the broadest indicator of economic output and growth. Both the chosen proxies and the period under investigation are in line with earlier done studies such that comparisons on results can be facilitated.
The following other variables will be included: Exports are defined as exports of all goods and services and exclude compensation of employees and investment income and transfer payments, which prevents for double accounting in GDP. Imports are defined as imports of all goods and services and also exclude compensation of employees and investment income and transfer payments for the same reason. Gross Fixed Capital Formation is used as a proxy for the level of investments and consists of additions to the fixed assets of Nigeria’s economy. The World Bank lists fixed assets to include amongst other things the following: land improvements, plant, machinery, equipment purchases and the construction of roads, railways and other real estate
including real estate for commercial purposes. Therefore Gross Fixed Capital Formation is deemed an appropriate proxy for the level of Nigerian investments. Gross Domestic Savings are a function of Gross Fixed Capital Formation and will therefore be omitted as a variable in favor of a proxy for the level of investments to prevent multicollinearity issues.
All data concern time-series data and are defined in current US dollars meaning that prices for each year are defined in the dollar value of that year (e.g. the value of 1981 ODA is in 1981 prices, the value of 1982 ODA is in 1982 prices … etc.). In total the dataset at the start of the analysis contains 5 variables with a total of 165 observations with no missing values in the series. All of the data used is
downloaded from the World Bank Database for development indicators, updated for the last time on April 14th 2014.
3.2 Model specification
With the background from the theoretical framework a function can be composed that is deemed appropriate for the examination of aid effectiveness in Nigeria. An OLS approach will be employed accompanied by appropriate measures to account for the usage of time-series data. It is established that foreign aid plays a strong role in supplementing for short falling domestic savings in Nigeria and that the intuition behind the Two-Gap model is one appropriate way of investigating this relationship. Therefore it is considered fitting to include those variables that relate to that model.
The following relationship between foreign aid inflows and economic growth will be the starting point:
𝑮𝑮𝑮𝑮𝑮𝑮 = 𝒇𝒇( 𝑶𝑶𝑮𝑮𝑶𝑶, 𝑰𝑰𝑰𝑰𝑮𝑮, 𝑬𝑬𝑬𝑬𝑮𝑮, 𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮) (1)
GDP Gross Domestic Product
ODA Official Development Assistance (as a proxy for foreign aid) IMP Imports
EXP Exports
The next step is to express this relationship in a linear form with, ODA being expressed as a fraction of GDP and the inclusion of a an error term to capture all other variations in GDP:
𝑮𝑮𝑮𝑮𝑮𝑮𝒕𝒕 = 𝜷𝜷𝟎𝟎+ (𝑶𝑶𝑮𝑮𝑶𝑶/𝑮𝑮𝑮𝑮𝑮𝑮)𝒕𝒕𝜷𝜷𝟏𝟏+ 𝑰𝑰𝑰𝑰𝑮𝑮𝒕𝒕𝜷𝜷𝟐𝟐+ 𝑬𝑬𝑬𝑬𝑮𝑮𝒕𝒕𝜷𝜷𝟑𝟑+ 𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝒕𝒕𝜷𝜷𝟒𝟒+ 𝑼𝑼𝒕𝒕 (2)
Most economic time series are estimated in logarithmic form as over the long run they tend to grow by a certain percentage per year and the transformation also facilitates the interpreting of the output results (Stock & Watson, 2011). Therefore (2) will be transformed to a log-log specification:
𝒍𝒍𝒍𝒍𝑮𝑮𝑮𝑮𝑮𝑮𝒕𝒕 = 𝜷𝜷𝟎𝟎+ 𝒍𝒍𝒍𝒍(𝑶𝑶𝑮𝑮𝑶𝑶/𝑮𝑮𝑮𝑮𝑮𝑮)𝒕𝒕𝜷𝜷𝟏𝟏+ 𝒍𝒍𝒍𝒍𝑰𝑰𝑰𝑰𝑮𝑮𝒕𝒕𝜷𝜷𝟐𝟐+ 𝒍𝒍𝒍𝒍𝑬𝑬𝑬𝑬𝑮𝑮𝒕𝒕𝜷𝜷𝟑𝟑+ 𝒍𝒍𝒍𝒍𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝒕𝒕𝜷𝜷𝟒𝟒+
𝑼𝑼𝒕𝒕 (3)
Before any analysis can be done with time-series data, it needs to be
established first that the data is suitable for analysis. If not, first proper measures need to be taken in order to ensure the quality of the output. For time-series data it is important to establish whether the variables (both dependent and independent) are stationary or non-stationary. If a time series is stationary this means that the probability distribution of the included variables do not change over time and the output can generate significant results (Stock & Watson, 2011). Stock & Watson (2011) explain that if there is non-stationarity the series contains an unit root. The consequence is that the regressors from the OLS regression will then have
nonstandard distributions for the t-statistic and lead to so-called spurious regression results. If however non-stationarity is established then it could still be possible to use the data for research if proper additional measures are undertaken. The Augmented Dickey-Fuller (ADF) test is employed to determine the presence of any unit roots in the time series. Stock & Watson (2011) explain that this test takes the null hypothesis to be that the series contains a unit root and the alternative hypothesis to be that there is no unit root. Or in other words this means that the null hypothesis implies a non-stationary series that may deliver significant results and the alternative hypothesis indicating that this might be a stationary series that could lead to problematic regression results. Table 1. shows the result of the first ADF test:
Table 1. ADF test outcome (1)
Augmented Dickey-Fuller test (ADF)
Variables #Obs Test Statistic
lnGDP 32 1.053 ln(ODA/GDP) 32 -2.549 lnIMP 32 -0.305 lnEXP 32 -0.531 lnGFCF 32 0.178 * 1% critical value -3.702 ** 5% critical value – 2.980 *** 10% critical value – 2.622
It is clear from table 2 that there are unit roots present as none of the null hypotheses were rejected at any significance level meaning that the series is very likely non-stationary. First we will have to solve this problem. Stock & Watson (2011) explain that integrating a series in order d can lead to a time series absent of unit roots, so that it can be considered as a stationary series. All variables would then be differenced with respect to themselves so that e.g. lgdpt when differenced in order 1 would become ∆1
lgdpt = lgdpt - lgdpt-1. Differencing in second order would be denoted ∆2
lgdpt = lgdpt - lgdpt-1 and so on. First all variables will be differenced in order 1, which will result dropping one observation, and then the ADF test will be run again. If that still results in a non-stationary series the process of differencing can continue. Table 2 shows the result of the second ADF test:
Table 2. ADF test outcomes (1) and (2)
Augmented Dickey-Fuller test (ADF)
Variables # Obs Test
Statistic
Variables #Obs Test Statistic
lnGDP 32 1.053 lnGDPD1 31 -5.207*** ln(ODA/GDP) 32 -2.549 ln(ODA/GDP)D1 31 -4.912*** lnIMP 32 -0.305 lnIMPD1 31 -4.537*** lnEXP 32 -0.531 lnEXPD1 31 -6.552*** lnGFCF 32 0.192 lnGFCFD1 31 -3.902*** * 1% critical value -3.702 ** 5% critical value – 2.980 *** 10% critical value – 2.622 * 1% critical value -3.709 ** 5% critical value -2.983 *** 10% critical value -2.623
At the first order differencing all variables reject the null hypothesis in favor of the alternative at a significance level of 1%. It is now possible to proceed with the analysis.
4. Analysis and discussion
Given now that the necessary augmentations on the data have occurred it will be the following model on which an OLS regression will be ran:
𝒍𝒍𝒍𝒍𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝟏𝟏𝒕𝒕 = 𝜷𝜷𝟎𝟎+ 𝒍𝒍𝒍𝒍(𝑶𝑶𝑮𝑮𝑶𝑶/𝑮𝑮𝑮𝑮𝑮𝑮)𝑮𝑮𝟏𝟏𝒕𝒕𝜷𝜷𝟏𝟏+ 𝒍𝒍𝒍𝒍𝑰𝑰𝑰𝑰𝑮𝑮𝑮𝑮𝟏𝟏𝒕𝒕𝜷𝜷𝟐𝟐+ 𝒍𝒍𝒍𝒍𝑬𝑬𝑬𝑬𝑮𝑮𝑮𝑮𝟏𝟏𝒕𝒕𝜷𝜷𝟑𝟑+ 𝒍𝒍𝒍𝒍𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝟏𝟏𝒕𝒕𝜷𝜷𝟒𝟒+ 𝑼𝑼𝒕𝒕 (4) The log-log model relating GDP growth to the first difference of all the included variables. From the literary background and economic theory the following expectations can be expressed upfront: ambiguity on the sign for β1, a negative expectation on the sign β2 and a positive one on both β3 and β4. The result are the following:
Table 3. OLS output
Variables Coefficient Standard Error P value
ln(ODA/GDP)D1 -0.0424333 0.0377025 0.27
lnIMPD1 -0.0901855 0.0889254 0.32
lnEXPD1 0.3116003 0.0718329 0
lnGFCFD1 0.4103196 0.091944 0
_cons 0.0388182 0.023977 0.117
This output has an R2 = 0.7712, adjusted R2 = 0.7373 and a Root MSE = 0.1382 (full output in Appendix B). At first glance we see a negative sign on the coefficient including ODA. However the p-value on ln(ODA/GDP)D1 is 0.27 which is not particularly small, but also not so large that there is strong evidence that there would be no relationship between the variable and GDP at all. The suggestion seems to be that if the fraction of GDP/ODA where to increase with 1%, this would have a negative effect on GDP of about -0.04%. Given that the impact is not very big in the absolute sense it is then safe to conclude that given the small negative and weakly significant result that ODA seems to not affect any real impact on Nigerian GDP. Thus for this model concerning the period 1981-2013 ODA seems to have no real impact on GDP for the Nigerian economy.
Looking at the other coefficient tells us that the coefficient on imports has the expected negative sign and seems to imply that a 1% increase in imports leads to an approximate -0.09% decrease in GDP. It is noted however that the p-value on this coefficient is also net very low with a value of 0.32, but also not so high that the lack of any relationship between the two variables can be strongly denied. Both exports and the proxy for investments show the expected positive sign and are both significant at the 1% level. It tells us that a 1% increase in exports and investments would lead to respectively a 0.31% and 0.41% increase in GDP, which is quite a strong effect yet understandable in relation to the fact that it was predominantly the services that contributed to the high growth numbers for Nigeria. These effects also corroborate the assumption that ODA would most likely have no effect on Nigeria’s GDP, rather than having a negative effect seeming as there seems to be no distortion in exports and investments.
5. Conclusion
As stated at the beginning of this thesis and throughout, the emergence of foreign aid was virtually accompanied by the emergence of aid-effectiveness research. The past 50 years saw the publication of numerous studies on both the micro level and on the macro level, with the latter consisting of mostly cross-country study analyses with very large samples (sometimes nearing a hundred countries) (Hansen & Tarp, 2001). It is safe to say that there is no one consensus on aid effectiveness as any next investigation can garner different results than a previous similar one. There do however seem to be trends towards convergence over time when it comes to the findings of aid effectiveness studies, that coincide with the usage of similar types of econometric techniques and models (McGillivray, 2004).
Regarding the studies reviewed in this thesis and the results found in this thesis on aid effectiveness as it relates to Nigeria a few conclusions can be made. It is advocated that for Nigeria that the investment channel is a strong instrument to improve growth numbers. The results from the conducted regression underscore this showing a significant effect on the investment coefficient. Examining the trade balance also shows us that the effects of exports are stronger than those of import, such that investing in the export-competing sector is advisable. Alabi (2012) also believed that channeling aid to the productive sectors of the economy could inspire
economic growth. The task at hand would then be to identify these sectors such that a favorable distribution can be made. Alabi (2012) found at the end of his sectoral analysis of ODA effects on GDP that there is between a non-conclusive and negative effect of ODA on GDP for the period 1981-2010, which coincides with the period investigated and conclusion of this thesis. Kolawole (2013) investigated the similar period 1980-2011 and found no relationship between ODA and economic growth. And finally Mbah & Omassoma (2014) looked at the period 1981-2012 and found a negative yet non-significant relationship between ODA and growth also making use of the OLS method. Fasanya & Onakoya (2012) and Tombofa et al. (2013) on the other hand both found positive relationships between ODA and economic growth in Nigeria, using similar econometric techniques. They respectively looked at the periods 1970-2010 and 1981-2010. It should be noted that the Fasanya & Onakoya’s range of dates start 10 years earlier and that Tombofa et al.’s range stops three years earlier, in which GDP growth for Nigeria started to decline again. These results cover the full range of possibilities with two papers finding positive effects and the other three either weakly significant negative or no conclusive results. The findings in this thesis thus finds itself amongst those finding no strong results of aid effectiveness in Nigeria.
All researchers however advocate the implementation of better policies, which strongly implies that there is a lack in ability to utilize aid to its most effective potential. It seems that a possible next topic of investigation for Nigeria could be the construction of a policy index to quantify the level in which policies prevent aid from having a positive effect on growth. Once quantified, it would become easier to make more case-related suggestions in improving policies there were they are implemented inefficiently. The studies on policy indexes already lends itself to be extended to the case of Nigeria, but as always laying out a solid theoretical foundation should be the starting point in order to determine the inclusion of which variables are best to construct Nigeria’s policy index.
To conclude it suffices to say that the jury might still be out on whether foreign aid has any impact on Nigeria’s economic growth at all, the results seems to suggest there is none. What has become evident is that case study analysis are also an important part of aid-effectiveness studies and that these can give strong direction towards next studies so that future disbursements of foreign aid can realize its maximum potential, a potential that definitely cannot be disregarded just yet.
6. References
Alabi, R.A. (2012). Sectoral Analysis of Impact of Foreign Aid in Nigeria: A
Dynamic Specification. Department of Agricultural Economics, Ambrose Alli university, Ekpoma, Nigeria.
Burnside, C. & Dollar, D (2000). Aid, Policies and Growth. American Economic
Review, Vol 90, No. 4, pp. 847-868.
Burnside, C. & Dollar, D (2004). Aid, Policies and Growth: Reply. American
Economic Review, Vol 94, No. 3, pp. 781-784.
Easterly, W., Levine, R. & Roodman, D (2004). Aid, Policies and Growth: Comment.
American Economic Review, Vol 94, No 3, pp. 774-780.
Fasanya, I. & Onakoya, A (2012). Does Foreign Aid Accelerate Economic Growth? An Empirical Analysis for Nigeria. International Journal of Economics and
Financial Issues, Vol. 2, No. 4, pp. 423-431.
Hansen, H. & Tarp, F (2001). Aid and Growth Regressions. Journal of Development
Economics. Vol. 64, No. 2, pp. 547-570.
Hjertholm, P. & White, H (2000). Survey of Foreign Aid: History, Trends and Allocation. Discussion Papers. Department of Economics, University of Copenhagen.
IMF (2015). IMF Country Report no. 15/85. Selected Issues Paper: Nigeria.
Kolawole, B. (2013). Foreign Assistance and Economic Growth in Nigeria: The Two-Gap Model Framework. American International Journal of Contemporary
Research, Vol. 3, No. 10, pp. 153-159.
Levy, V (1988). Aid and Growth in Sub-Saharan Africa: the Recent Experience.
European Economic Review, Vol. 32, Issue 9, pp. 1777-1795.
Mbah, S. & Amassoma, D (2014). The Linkage between Foreign Aid and Economic Growth in Nigeria. International Journal of Economic Practices and Theories,
Vol 4, No. 6, pp. 1007-1017.
McGillivray, M (2004). Is Aid Effective? WIDER, Helsinki, Finland.
Moyo, D. (2010). Dead Aid: why aid is not working and how there is another way for
Africa. London, LDN: Penguin Group.
Murphy, K.M., Shleifer, A. & Vishny, R.W (1989). Industrialization and the Big Push. The Journal of Political Economy, Vol. 97, Issue 5, pp. 1003-1026. OECD (2003). Papers on Official Development Assistance. OECD Journal on
OECD (2015). OECD Investment Policy Reviews: Nigeria 2015. OECD Publishing, Paris.
Stock, J.H. & Watson, M.M (2011). Introduction to Econometrics. Pearson Education Limited, 3rd edition, Harlow, England.
Tombofa, S., Edoumiekumo, S. & Obudah, B (2013). Foreign Aid, Debt and Growth Nexus in Nigeria. Research Journal of Economics, Business and ICT, Vol 8,
Issue 2, pp. 18-24.
Wijnbergen, S. van (1984). Macroeconomic Aspects of the Effectiveness of Foreign Aid: on the Two-Gap Model, Home Goods Disequilibrium and Real Exchange Rate Misalignment. Journal of International Economics, Vol 21, Issue 1-2, pp.
123-136.
Appendix A: Figures (*)
Figure 1. Figure 2.
Figure 3. Figure 4.
Appendix B: Additional output
Table 4. Summary statistics of included variables
Variable Obs Mean Std. Dev. Min Max
GDP 33 1.05E+11 1.37E+11 1.58E+10 5.22E+11
(ODA/GDP) 33 0.0097025 0.0157227 0.0006426 0.0785809
IMP 33 2.10E+10 2.35E+10 2.16E+09 8.84E+10
EXP 33 3.13E+10 3.77E+10 2.76E+09 1.46E+11
GFCF 33 1.40E+10 2.11E+10 2.02E+09 7.55E+10
lnGDP 33 24.78951 1.009879 23.48258 26.98056 ln(ODA/GDP) 33 -5.229776 1.039231 -7.349931 -2.543627 lnIMP 33 23.17693 1.116256 21.49114 25.20489 lnEXP 33 23.56889 1.091561 21.73824 25.70382 lnGFCF 33 22.62031 1.114366 21.42491 25.04755 lnGDPD1 32 0.0670364 0.2591629 -0.6183052 0.778223 ln(ODA/GDP)D1 32 0.0631454 0.6673657 -1.90004 2.162559 lnIMPD1 32 0.0452114 0.3824417 -0.8370686 0.7444115 lnEXPD1 32 0.0605719 0.4262751 -0.7215519 0.8554707 lnGFCFD1 32 0.0392398 0.3529948 -0.6999207 1.11867
Table 5. Correlation matrix for the regressed variables
Correlations lnGDPD1 ln(ODA/GDP)D1 lnIMPD1 lnEXPD1 lnGFCFD1
lnGDPD1 1
ln(ODA/GDP)D1 -0.3393 1
lnIMPD1 0.554 -0.2135 1
lnEXPD1 0.7352 -0.1583 0.6044 1
lnGFCFD1 0.7713 -0.3173 0.6334 0.5114 1
Table 6. Full regression output
Source SS df MS Number of obs 32
Model 1.60579451 4 0.401448627 Prob > F 0
Residual 0.47633288 27 0.017641959 R-squared 0.7712
Total 2.08212739 31 0.0671654 Root MSE 0.13282
lnGDPD1 Coef. Std. Err. t P>t [95% Conf. Interval]
ln(ODA/GDP)D1 -0.0424333 .0377025 -1.13 0.27 -0.1197923 0.0349258
lnIMPD1 -0.0901855 .0889254 -1.01 0.32 -0.2726453 0.0922743
lnEXPD1 0.3116003 .0718329 4.34 0 0.1642114 0.4589893
lnGFCFD1 0.4103196 .091944 4.46 0 0.2216661 0.5989731
