Colonialism, Institutional Quality and the Resource Curse. Jubril O. Animashaun 1 Department of Economics, University of Manchester, UK Abstract

Colonialism, Institutional Quality and the Resource Curse Jubril O. Animashaun 1 Department of Economics, University of Manchester, UK Abstract In many resource endowed countries, hydrocarbon endowment is associated with poor socioeconomic performance, a condition often called the Resource Curse. However, there is little consensus on the cause of this paradox. This paper explores an additional channel to explain the income inequality across oil-rich countries. We hypothesise that European-organised mercantilism and resource exploitation during colonialization could have an enduring effect, manifesting in the inherited socio-economic and political institutional structures that moderate the benefits from oil endowment. We test this hypothesis using a dynamic panel 5- year distributed lag model and examine how colonial legacy indirectly influences the unweighted aggregated index of average protection against expropriation, executive constraint and government effectiveness. We also use the log of the depth of oil discoveries to get the unbiased estimate of the log of oil abundance on income per capita five years after the discovery of giant oil field. Our findings show that oil-rich countries that were former colonies during European colonialization have a poor institutional quality index, and institutional quality moderates the adverse effect from oil abundance. In addition, our results also suggest that former European extractive colonies used for natural resource expropriation are unable to positively relate hydrocarbon endowments to income per-capita. We recommend that formulating a benchmark of governance and socio-economic institutional indicators for monitoring petroleum-rich countries adherence to best practises, especially in countries with experience of European colonialism could resolve some of the paradox. Keyword: Colonialism, Post-colonialism, Institutions, Hydrocarbon Resources JEL-Codes: F54, E02, O43, Q35 1 Introduction Why are there differences in income-per capita in oil and gas rich countries such that many endowed countries have been unable to get out of the low income trap by relating rents to socio-economic development (Figure 1)? The literature, broadly, describes this paradox as the Resource Curse (RC), and the divergent perspectives on this question make reaching a 1 Jubril is a PhD student in Environmental and Resource Economics, Department of Economics, University of Manchester, UK. Phone number: 07440077279, email: jubril.animashaun@manchester.ac.uk, and a lecturer in the Department of Agricultural Economics, University of Ilorin, Nigeria. Email: Animashaun.jo@unilorin.edu.ng I thank Ada Wossink and Ron Chan for helpful comments and suggestions. I am also grateful to the Islamic Development Bank for the financial support and scholarship provided. The usual disclaimer applies. 1

-2-1 0 1 2 consensus difficult (Manzano and Rigobon 2001,Van de Ploeg 2011, Havranek et al., 2016) 2. However, a growing literature considers institutional quality as one of the potential determinants (Mehlum et al. 2006, Van de Ploeg 2011). Institutional quality matters because oil windfall in the presence of strong governance and socio-economic institutions could encourage growth by inducing a multi-sector economic growth with positive multiplier effect (Mehlum et al. 2006, Alexeev and Conrad 2009, Kolstad 2009). However, when institutional quality is weak, sudden oil wealth could further raise the incentives of political office holders staying in office and limit the constraints on the power of the political elites. The implication is a clientelistic state that favours a socially inefficient rent-seeking and distributive system, unrewarding for entrepreneurship, and allowing management policies that over-discount future rents, while neglecting investment in the non-oil sectors (Corden and Neary 1982, Robinson et al. 2006, Robinson and Torvik 2005, Van de Ploeg 2011). Log of GDP/capita (Constant US$) and Log Oil and Gas rents/gdp AUT USAAUS GBR CAN NOR QAT ARE BRN KWT IND BRA CHN ARG MEXMYS COL IDN VNM EGY ECU SDN VEN RUS KAZ IRN DZA AZE IRQ NGA TCD GAB LBY YEM SSD OMN SAU GNQ AGO COG -6-4 -2 0 2 Log Oil and Gas Rents Per GDP coef = -.20808887, se =.14040427, t = -1.48 Figure 1: The Partial-regression leverage plot between Log GDP/capita and Log Oil and Gas Rents/ GDP in 40 of the largest Oil and Gas Endowed Countries (2000-2015) However, there are caveats to these explanations that suggest rethinking. First, the simultaneity bias arising from the country-level correlation of oil abundance/rents and institutional quality with national income could bias the estimates and make the relationship difficult to interpret. For instance, it could be that wealthier countries can afford the human 2 Several economics papers have investigated the relevance of natural resource abundance for development. For instance see Brunnschweiler and Bulte (2008) and Cavalcanti et al. (2011), and Havranek et al. (2016) and Van de Ploeg (2011) for a more detailed review. 2

and physical capital necessary for both institutional quality and natural resource exploration activities whereas low or middle-income countries could not (Acemoglu et al. 2001, Cotet and Tsui 2013, Cust and Harding 2015, Arezki et al. 2016). In support of treating institutional quality as endogenous, evidence from the literature suggests that certain historical events that have no direct bearing on current GDP/capita, particularly, European-organised mercantilism and resource exploitation during colonialism are significant in explaining the type of institutions that persist today (Acemoglu et al. 2001, Feyrer and Sacerdote 2009). Indeed, there is stronger evidence of Resource Curse in many oil rich countries that were extractive colonies during the era of European colonialism (Figure 1). Contrariwise, oil rich countries without exploitative colonialism, and with a settlement rather than exploitative colonies have been able to emerge from poverty, and accumulate human and physical capital with oil discovery (Figure 1) 3. In this study, we asked if the inherited governance and socio-economic, institutional structures that favoured exploitative practice during the era of European colonialism is an intermediating channel causing Resource Curse 4. An essential feature of European colonial occupation was the consolidation of foreign rule, which often involved the imposition of a political and cultural hegemony that could lead to the restructuring of socio-political, governance and economic institutions 5 (Acemoglu et al. 2001, Dell 2010, Aldrich and McCreery 2016). For instance, to consolidate authority over the colonies and encourage resource exploitation, colonial authorities often deposed or modfied existing apparatuses of governance and designated leadership function to a sub-group, thereby, created a political hegemony that favors an elitist rather than an egalitarian state 6 (Laclau and Mouffe 2001 pp 3 For instance, many oil rich countries in the Gulf regions have been able to relate oil windfall to socio economic growth and infrastructural development. 4 In this study the focus on colonialism is on the settler and exploitative European organised types of colonialism driven in part by geography (Acemoglu et al. 2001). In settler colonialism, European immigrants create settlement colonies after taking over the land of the indigenous people (Wolfe 2006). Whereas in exploitative colonialism, natural and human resources are the main motivation and these are exploited and exported to Europe. 5 Studies on the assessment of the impact of European colonialism show that experience of colonial occupation generates significant variation in the current level of socio-economic inequality (Acemoglu et al. 2001, Dell 2010). Dell (2010), for instance, examines the long-run impacts of the mita, an extensive forced mining labour system in colonial Peru and Bolivia between 1573 and 1812 and Acemoglu et al. (2001) examines how the log of settlers mortality associated with latitude influence colonisation patterns and causes differences in institutional quality. In both studies, the authors found that the residual effect of colonisation via the investment made in growth building institutions 6 The problem with the empowerment of a sub-group with political power is well captured in Acemoglu and Robinson (2012) as: "those who are further empowered politically will use this to gain a greater economic 3

40-59, Igbafe 1979). Post-colonial political restructuring of this status quo ante might be difficult (Acemoglu and Robinson 2012), and inheriting these political cliental-oriented and governance structures could result in creating a leadership features that cause the marked differences in per capita income among oil rich countries. We investigate how the enduring legacies of European-organised mercantilism during colonisation shapes governance and socio-economic institutional quality, creating differing post-colonial growth trajectories and driving disparity in income per capita (Acemoglu et al. 2001, Engerman and Sokoloff 2002, Bruhn and Francisco 2012). We test our hypothesis using a sample of oil-rich countries with at least a discovery of giant oil reserves from 1960-2015. We use a dynamic panel 5-year distributed lag IV-GMM model to examine how colonial legacy indirectly influences the unweighted aggregated index of institutional quality and use the log of the depth of oil discoveries to get the reduced form estimate of oil abundance on income per capita five years after the discovery of giant oil field. Oil and gas endowed countries are of particular interest because of the large potential impacts oil and gas have on national accounts, and together with institutional quality, having broader implications on socio-economic outcomes (Watts 2001, Mehlum et al. 2006, Ross 2012). Furthermore, because large quantities of oil reserves are usually found in countries with weak institutions and limited technical abilities (Manzano and Monaldi 2008), foreign oil firms are usually licenced to carry out the exploration activities. The weak institutional envirorment might favour sharp and corrupt practices that are reminiscent of exploitative colonialism by both the firm and the political elites which could further impede economic growth from a broader socio-political and economic perspective. Our results show that colonial experience and the log of the depth of oil discoveries explain a substantial part of the variation in changes in economic development via institutional quality and oil abundance and their interaction over the period 1960 2015. Our reduced form estimates suggest a negative correlation between the probability of colonisation and current income per capita, and in the first stage, colonised countries have a poorer institutional quality than non-colonised countries. We confirm that the negative causal impact of oil abundance on income per capita is moderated by institutional quality, as increasing the indicators of average protection against expropriation; executive constraint and government advantage by stacking the cards in their favour and increasing economic inequality yet further a quintessential vicious circle. 4

effectiveness reduce the negative impact of oil discoveries on income. Our findings hold even after accounting for prior level of income per capita in the year of oil discovery. We conduct a series of robustness check to test the validity of our results. First, we restrict our sampled oil rich countries only to those with experience of colonialism 7 and instrument institutional quality and a log of oil abundance with the log of settler mortality and the log of the depth of oil fields. Additionally, we restrict our sample to countries with experience of exploitative colonialism by excluding earlier colonised countries with settler colonialism 8. We find that the higher the log of settler mortality, the poorer institutional quality than countries. Second, we consider alternative specification and measurement of natural resource value by accounting for the log of the monetary value of oil discoveries. Third, we considered the disaggregated components of the institutional quality. Our robustness checks, validate our findings on the impact of colonialism and pattern of colonialism on institutional quality and the moderating impact of institutional quality, particularly the constraints on political leaders scope for unilateral action, on resource curse. Our findings relate with previous studies that link good quality institutions to economic development, and we recommend addressing the declining quality of institutions is a right way of improving economic performance and closing the gaps in inequality in income per capita across oil-rich countries. Notably, our study contributes to the economic literature on Resource Curse (RC) in two ways. First, we identify income inequality arising from the moderating effect of institutional quality among oil rich countries with colonial legacy (Sachs and Warner 1995, 1997, Mehlum et al. 2006, Robinson et al. 2006). Also, we expand the understanding of the contribution of European colonialization on institutional quality by allowing for an alternative comparison with non-colonised countries. This contribution allows for a better understanding of the impact of European colonisation on the disparity in current national income per capita. Second, we identify oil and gas abundance with the log of oil depth and treat the magnitude of oil discoveries, which is suggested as being an exogenous measure of oil and gas abundance as endogenous (Arezki et al. 2017). Oil and gas abundance is plausibly 7 We refer to the sample of colonised oil rich countries from the list of colonised countries in Acemoglu et al. (2001) 8 Countries like Canada, USA, Australia and New Zealand are examples of colonised countries with settler colonies (Acemoglu et al. 2001) 5

endogenous to national income because exploration activities require substantial technical and financial expertise that could make wealthier countries more able to afford more discoveries ahead of poorer countries. The log of the depth of oil discoveries is more likely to be exogenous to the magnitude of oil abundance because abundant oil and gas are formed mostly from the rapid burial of dead microorganisms in environments where oxygen is scarce, and pressure is high which makes log of depth to correlate with the log of oil and gas abundance (Tissot 1971, Tissot et al. 1974). We utilise this empirical strategy to advance the understanding of the fundamental causes of the substantial differences in income per capita across all oil rich countries. We conclude by suggesting the devising of a benchmark for institutional quality that constrains political leaders scope for unilateral action. Particularly, we suggest that ensuring broader accountability and transparency of governments in oil-rich countries with experience of European colonialism could reduce the gap in economic benefits from oil endowments across oil rich countries. Following this introduction, the remainder of the paper is organized as follows. Section 2 presents the estimation strategy and the data. The gap in income per capita across oil rich countries depending on whether colonised is estimated in Section 3.1. The effect of colonial legacy on institutional quality and economic development is discussed in Section 3.2. Section 3.3 provides robustness checks, and Section 4 concludes. 6

2. Estimation Strategy and Data Description 2.1. Institutional Quality and the gap in income per capita of oil rich countries Following Mehlum et al. (2006), we motivate our thesis of the moderating effect of institutional quality and oil abundance on the log of income per capita five years after the discovery of giant oil reserves in oil rich countries in equation (1). LogY i,t+5 = α + β 1 IQ i + β 2 Log Disc it + β 3 (Log Disc it IQ i ) + δ(year t ) + µ it (1) In eqn. (1), Y i,t+5 stands for the log of GDP per capita in country i five years after the discovery of giant oil and gas fields. We specifically expect the effect of giant oil discovery not to be immediate but to materialise after a time period given that it takes time for oil production and processing to take pace after discovery (Arezki et al. 2017). A typical lag between oil discovery and oil production of five years is discussed in Arezki et al. (2017). A giant oil or gas discovery is defined as a discovery of an oil and/or gas field that contains at least 500 million barrels of ultimately recoverable oil equivalent (Arezki et al. (2017). IQ i is the unweighted institutional quality index which is the unweighted averages of Executive Constraints (1960-2000), Expropriation Risk (1982-1997) and Government Effectiveness (1998-2000) for each country. Log Disc it measures the size and magnitude of oil and gas discovery in country i time t. Log Disc it IQ i captures the interaction term which is the moderating effect of institutional quality on oil abundance or the deteriorating influence of oil discovery on institutional quality in country i period t. Year captures the effect of time such as changes in technology or regulation that could cause income per capita to be different. Conceptually, estimate of the interaction term, Log Disc it IQ i, has important implication. It represents the influence of institutional and governance quality on sudden oil discovery. If the features of governance and socio-economic institutional quality are weak, sudden oil discovery could make leaders more likely to stay put in power, encourage dictatorships and favours a cliental-oriented and socially inefficient rent-seeking system that seek to exchange rents benefits for political patronage. Therefore, given the same amount of oil discoveries; countries with better institutional quality and political accountability could have an improvement in income per capita by spurring investment decision with a wide multiplier effect on the economy. 7

-4-2 0 2 4 Correlation of Log GDP/Capita and Institutional Quality Index GNQ TKM UZB KAZ IRQAZE TJK QAT ARE NOR KWT BRN DNK FRA SAU ESP ISR ITAAUS CAN NZL DEU USA NLD GBR OMN VEN LBY GAB HUN ARG BRA RUS TTO MEX IRN NAM DZA PER ECU COL MYS UKR AGO COG ALB TUN THA NGACIV MAR BOL IDN EGY PHL SDN GHA YEM PNG VNM PAK CHN IND BGD SLE MMR ETH MOZ -1 -.5 0.5 Institutional Quality Index coef = 2.8699896, se =.51834024, t = 5.54 Figure 2: Partial-regression leverage Plot of Institutional quality index on Log GDP/Capita for Oil and gas-rich countries However, countries could perform better just because they already have economic structures and are highly industrialised before the oil discoveries which would be evident in their income per capita. Besides, it is possible for other factors to account for the difference in the gap in the impact of giant oil discoveries. Countries could be worse off because of the difference in institutional quality, and differences in the physical environment could be driving the economic results. Several accounts in the literature suggest that political and economic institutions are as fundamental to explaining whether a country is developed or under-developed (Glaeser 2004, Knack and Keefer, 1995). Another school of thought accounts for the role of the physical environment like latitude, climate, and land composition that predisposes countries towards particular development trajectories (Mellinger et al., 2000, Nunn and Puga, 2012). Indeed, as noted by Gallup et al. (1999) and Easterly and Levine (2003), as latitude increases relative to the equator, levels of real GDP per capita also increases 9. Because of the omission of essential variables in equation (1), we include additional variables in equation (2). 9 The inverse relationship between closeness to the latitude and economic performance could be due to the correlation areas closer to the latitudes has with productivity and ecological conditions that favour infectious diseases and food security. 8

LogY i,t+5 = α + β 1 IQ i + β 2 Log Disc it + β 3 (Log Disc it IQ i ) + β 4 LogGDP i,t + β 5 log pop it + β 6 SSA i + β 7 SAsia i + β 8 Latin i + β 9 MENA i + β 10 Latt i + δ(year t ) + µ it Where Log Y i,t+5 stands for the log of GDP per capita in country i five years after the discovery of giant oil and gas fields, IQ i is the unweighted institutional quality index and og Disc it IQ i captures the moderating effect of institutional quality on oil abundance or the deteriorating influence of oil discovery on institutional quality in country i period t. The additional variable LogGDP i,t denotes the log of GDP per-capita for country i in the year t (year of oil discovery), and it tests how the prior income level of oil rich country shapes the current realisation. log pop it is the log of population growth. Variables SSA, South Asia Latin and MENA are dummy variables indicating whether sample country belong to regions in the Sub-Sahara, South Asia, Latin America or the Middle East and North Africa geographical regions based on World bank classification. Latt i is the absolute value for the latitude in each country. We estimate eqns (1) and (2) for all oil rich countries and exclude oil rich countries in Europe and central Asia. 2.2 Indirect impact of colonialism on economic performance in oil rich countries Suppose, for instance, that an equilibrium relation exists in equations (1) and (2) implying a bi-directional relationship between the dependent and the independent variables; then this could render our estimates biased. It is possible for oil-endowed countries to be able to afford better institutions and/or have the financial and technical capacity to engage in oil prospecting which would lead to more and early discoveries than less rich ones. In essence, equations (1) and (2) can yield a set of structural equations since it has, ceteris paribus, causal interpretations from the equilibrium relationship. Log Disc i,t = α + β 1 Log GDP/capita it + δ(year t ) + µ it (3) IQ i = α + β 1 Log GDP/capita it + δ(year t ) + µ it (4) Log Disc it IQ i = α + β 1 Log GDP/capita it + δ(year t ) + µ it (5) Where Log Disc it measures the size and magnitude of oil and gas discovery in country i time t. IQ i is the unweighted institutional quality index which is the index of the unweighted averages of Executive Constraints (1960-2000), Expropriation Risk (1982-1997) and (2) 9

Government Effectiveness (1998-2000) for each country and Log Disc it IQ i captures the moderating effect of institutional quality on oil abundance or the deteriorating influence of oil discovery on institutional quality in country i period t. Therefore performing the regression with just equations (1) and (2) would lead to a biased OLS estimator arising from simultaenity bias. In addition to this bias, equations (1) and (2) cannot verify our hypothesis of the enduring impact of the legacy of European colonialism on the economic performance in oil rich countries since we hypothesis that the effect of colonial instruments over a hundred years ago do not have a direct influence on current income except through the indirect impact on institutional quality. In this study, we correct this bias by employing the Instrumental variable (IV) method which allows for the consistent estimation of our variables. Using the 2SLS estimator, it is possible to recover unbiased estimates of the variables of interests. To consistently use the 2SLS, we need new variable(s) that satisfies properties of non-correlation with under-development and not that is not directly correlated with economic performance (Wooldridge 2001, pp. 101-2, Nichols 2006). In support of treating institutional quality as endogenous, evidence from the literature suggests that specific historical events helped in shaping the current level and quality of institutions. In Acemoglu et al. (2001), the authors employ OLS to identify institutional quality using log of settlers mortality associated with latitude influence on colonialism patterns. Feyrer and Sacerdote (2009) instrument the length of colonialism using variation in prevailing wind patterns and argue that wind speed and direction had a significant effect on the historical colonial rule but does not have a direct effect on GDP today. Finally, La Porta et al. (1997, 1998) suspect the legal origins and Bertocchi and Canova (2002) suggest that origins of colonisers are significant in explaining the type of institutions that persist today. In all these studies, the authors justified the exclusion restriction of their instruments by suggesting that it was unlikely for the instruments used for colonialization of European settlers more than 100 years ago to have any effect on current GDP except through the effect they had on institutional quality. Although strict exogeneity of the instruments implies that the causal effect in the conditional model should operate entirely through the endogenous regressors (Engle et al. 1983), however, an underlying background knowledge on the relationship between the instruments and the dependent variable is required in order to construct new causal facts (Cartwright 10

-3-2 -1 Log GDP/capita 0 1 2 1989, Pearl 2000, Bazinas and Nielsen 2015). We test for the underlying reduced relationship, independent of the endogenous variables, between colonisation and income per capita in equation 6. Log Y i,t+5 = α + β 1 Coly i + β 2 LogGDP i,t 1 + β 3 LogGDP i,t 2 + β 4 logdepth it + β 5 Latt i + β 6 log pop i + β 7 SSA i + β 8 SAsia i+ + β 9 Latin i + β 10 Mena i + δ(year t ) + µ it (6) Equation (6) as a reduced form equation is essential in its right as it helps to demonstrate if designating a country as a colony of European colonisation resulted in post-colonial substantial changes in income per capita compared to non-colonised countries and countries without exploitative colonialism. Particularly, this is important in explaining the apparent differences in oil-rich countries of settler colonialism with fewer settler mortality and colonies with exploitative colonialism with higher European mortality (Figure 3). Correlation of Log of Settler Mortality and Log GDP/capita AUS NZL USA CAN VEN TTO ARG BRA MEX GAB MYS COL ECU PER DZA TUN EGY BOL MAR IDN COG AGO CIV NGA PAK IND SDN BGD VNM SLE GHA ETH -2-1 0 1 2 3 Log of European Settler Mortality coef = -.48883013, se =.1754063, t = -2.79 Figure 3: Plot of Regression Log of Settler Mortality on Log GDP/Capita for Oil and gas-rich countries that were former European colonies. Also, because abundant oil and gas are formed mostly from the rapid burial of dead microorganisms in environments where oxygen is so scarce that they do not decompose (Tissot 1971, Tissot et al. 1974). This lack of oxygen corresponds with depth creating 11

-4-2 0 2 4 6 pressure cooker in more deeper zones where the dead organic matter matures slowly enabling them to maintain their hydrogen-carbon bonds, a necessary ingredient for the production of oil and gas. However, well drilling is the major cost components of any geothermal project (Petty et al., 1992; Pierce and Livesay, 1994) and it is directly influenced by the depth of oil fields. Given that more oil reserves are located in countries with weak institutional quality (Cust and Harding 2016), then, the log of depth could be useful for identification of oil abundance and institutional quality (Figure 4). In addition, we utilise the positive correlation of the log of the depth of discoveries with oil abundance and its negative correlation with institutional quality to instrument the endogenous regressor of the interaction effect of oil abundance and institutional quality. More importantly, to satisfy our exclusion restriction criteria, log of depth of oil fields is exogenously generated depending on geography and events that occurred millions of years ago and are not expected to be correlated with the causes of underdevelopment in oil rich countries and other plausible channel like human capital or technology shock that might affect income per capita. Correlation of Log of depth and the Interaction term GNQ TKM KAZ UZB AZE IRQ LBY RUS QAT DZA ARE KWT TJK GAB UKRARG AGO SDN TUN COG MEX MAR VEN OMNEGY NAMCIV PER CAN MMR BOLGHA NOR ALB BGD BRNPAK ECU PHL SLE VNM ETH HUN TTO COL NZL MOZ GBR MYS FRA ESP THAYEM DNK ITA DEU ISR NLD PNG IND BRA NGA USA IDN CHN AUS SAU IRN -.5 0.5 1 1.5 Log of Depth of Oil fields (Km) coef = 3.1460188, se =.70617948, t = 4.45 Figure 4: Plot of Regression Log of Depth on the Interaction of Oil Discoveries and Institutional quality in Oil and gas-rich countries 12

Subsequently, we re-estimate equation (2) after accounting for the endogeneity of our regressors in the first stage regression in eqn. (7) The first stage reduced form equation for the endogenous regressors in equation (2) is presented in Eqn (7). X i,t = σ + λ 1 logdepth it + λ 2 Coly i + λ 3 LogGDP i,t 1 + λ 4 LogGDP i,t 2 + β 1 Latt i + β 2 log pop i + β 3 SSA i + β 4 SAsia i + β 5 Latin i + β 6 Mena i + δ(year t ) + ε it (7) Here, X it stands for the endogenous regressors of unweighted index of institutional quality, log of income percapita in the year of oil discovery and log of amount of oil discovery in country i. logdepth is the Log of depth of oil reserves and it is, used as an instrument for oil abudance and the interaction of oil abundance with institutional quality. Coly is a dummy variable and it measures if a country has experience of colonial occupation. Coly is used as instrumental variable for a measure of institutional quality and to identify the indirect efect of the heritage of European colonialism relative to non-colonised countries. We also restrict our sample countries to only the colonised to test how the geography-induced the settlement patterns across colonies such that colonies that were geographically unsuitable for colonial settlement had higher mortality rates (Figure 5) and a higher tendency for abuse and current poor quality in institutional quality in equation (8). Xc i,t = σ + λ c1 logdepth it + λ c2 Log SettlerMort i + λ c3 British i + λ c4 LogGDP i,t 1 + λ c5 LogGDP i,t 2 + β c1 Latt i + β c2 log pop i + β c3 SSA i + β c4 SAsia i + βc 5 Latin i + β c6 Mena i + δ(year t ) + ε it (8) Here, Xc it stands for the endogenous regressors of unweighted index of institutional quality, log of income percapita in the year of oil discovery and log a of amount of oil discovery for colonised country i. Log SettlerMort is represent the log of recorded mortality in colonies and British i is the dummy for the country of origin. Bertocchi and Canova (2002) suggest that colonial origins, particularly, British colonies are known to have an enduring legal origin compared to non-british origins and these with log of settler mortality a could explain the 13

-.2 0.2.4 type of institutions that persist (Acemoglu et al. 2001, La Porta et al. 1997, 1998, Du 2010) 10. Correlation of Log of Settler Mortality on Institutional Quality Index IND MYS NZL COL TTO ETH AUS ECU USA VNM PAK BGD BOLIDN PER VEN EGY CAN SLE GHA CIV SDN BRA MEX MAR COG TUN GAB ARG AGO NGA DZA -2-1 0 1 2 3 Log Settler Mortality coef = -.0857516, se =.02311127, t = -3.71 Figure 5: Plot of Regression of Log of Settler Mortality on Institutional quality in Oil and gas-rich countries that were former European colonies. A further econometric issue is that because the log of GDP/capita in the year of oil discovery, which is correlated to indicators of under development, has a finite-dimensional distribution, then using a 2SLS estimator would be insufficient. In such a situation, the Generalised Method of Moments (GMM), instead of the 2SLS would be a better estimator (Hansen, 1982; 10 A primary criterion for the validity of our instrument for institutional quality (settler mortality and british colony dummy) is its non-correlation with any other channel that can affect economic performance except through institutional quality. For instance, Margolis (2017) argue that it is possible for areas with low settlers mortality to have a higher capital investment and transfer of technology from the motherland than in areas with high settlers mortality. Therefore, it is likely that historical endowments and early investments received in these areas are the additional channels through which growth occurs and not necessarily through improvement in institutional quality. These two regions are located in regions closer to the equator, and if we are to go about the settler mortality as an indicator of colonial pattern, then these two regions would most likely have the higher incidence of expropriation colonialism. Controlling for these two regions removes the correlation between settlers mortality and underlying causes of under-development associated with colonialism in our sample countries. In addition, using a dummy for the country origin of colonial rulers as instruments for institutional quality is because countries whose legal system is based on the common law (British) created more effective checks on executive power than did countries that use civil law (La Porta et al., 1998; Beck et al. 2003, Du, 2010). 14

Hall, 2005). The IV-GMM is a particular case when the variable has a finite-dimensional distribution. This approach allows the introduction of more instruments that can dramatically improve estimation efficiency (Arellano and Bond, 1991; Arellano and Bover, 1995; Blundell and Bond, 1998). 2.3. Data description Log GDP/capita 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 depletion and degradation of natural resources. Data are in constant 2010 U.S. dollars, and it is sourced from the World Bank national accounts data, and OECD National Accounts data files. Log Adjusted net national income per capita (current US$) between 1960-2015 Adjusted net national income (anni) is GNI minus consumption of fixed capital and natural resources depletion. Estimated Ultimate Recovery of Oil Equivalence in MMBOE (EUR) is the sum of the proven reserves at a specific time. Data on oil reserves discoveries include a column for depth of oil fields. Data covers the period from 1960-2010, and it is sourced from Horn (2014), Giant Oil and Gas Fields of the World. As an alternative specification, we use the value of the oil discoveries in USD. Information on oil prices was sourced from British petroleum (USD 2015), and we multiplied oil price with the magnitude of oil discoveries between 1960 and 2010 to get the oil wealth. Institutional quality is a measure of the quality of institutions which is the index of an unweighted aggregate of Executive Constraints (1960-2000), average protection against Expropriation Risk (1982-1997) and Government Effectiveness (1998-2000). It takes the value of zero to one with 1 being the maximum value and 0 being the country with the lowest protection against expropriation risk, government effectiveness and of constraint on the absoluteness of the authority of the executives. Institutional Quality i = ((X i) Min (X i )) (Max(X i ) Min(X i ) 15

Where X i is the average of the scores of Protection against risk of expropriation, executive constraint and government effectiveness for each country, Min (X i ) is the value for the country with the lowest aggregate score and Max(X i ) is for the country with the highest aggregate score. The executive constraint is the extent of institutionalised constraints on the decision-making powers of chief executives. It ranges from one to seven where higher values equalled a greater extent of institutionalised constraints on the power of chief executives and calculated as the average from 1960 through 2000, or for specific years (Jaggers and Marshall 2000). Protection against Expropriation Risk is defined as the protection against outright confiscation and forced nationalisation" of property. This variable ranges from zero to ten where higher values equal a lower probability of expropriation. This variable is calculated as the average from 1982 through 1997, or for specific years as needed in the tables. The source is from the International Country Risk Guide at http://www.countrydata.com/datasets/. Government effectiveness is defined as the measure of the quality of public service provision, the quality of the bureaucracy, the competence of civil servants, the independence of the civil service from political pressures, and the credibility of the government s commitment to policies. The primary focus of this index is on inputs required for the government to be able to produce and implement good policies and deliver public goods. This variable ranges from -2.5 to 2.5 where higher values equal higher government effectiveness. This variable is measured as the average from 1998 through 2000 (Kaufman et al. 2003). Because of the difference in the years of availability of these data, we consider a robustness analysis where the institutional quality is disaggregated. Colonial data Data on countries colonial origins, log settler mortality, the origin of the colonial legal system is all from the updated replication data of Acemoglu et al. (2001 2005). Countries categorisation into regions is form the World Bank classification sourced from the World Bank database. Log Annual Population Growth Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage. The population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship and the data from the from the World Bank database. The description and summary statistics of variables are described in Table I in the Appendix section. 16

3. Results and discussion 3.1 Colonisation and Income Gap across Oil-Rich Countries using OLS Table 1 reports ordinary least-squares (OLS) regressions of the gap in the log income per capita between colonised and non-colonised oil rich countries. The dependent variable is the log of income per capita. Table I shows that including a measure of the underlying economic performance of oil rich countries significantly improves the overall prediction of the model by increasing the adjusted R-squared by more than 100% (an increase from 0.41 to 0.98). In Models I and II, we show that institutional quality index and the log of oil discoveries positively correlates with log of economic performance, however, these two no longer gets significant in Model III and IV with the introduction of the lag of GDP per capita in the year of oil discovery which measures the historical economic performance. Models III and IV indicate that a significant driver of income inequality five years after the discovery of giant oil reserves is the level of recorded prior economic performance. Countries with the legacy of economic growth are likely to continue on that path even with the discovery of oil. The result is repeated in Model IV when oil rich countries in Europe and Central Asia and the USA, Canada, Australia and New Zealand are excluded. In models I and II, institutional quality is a determinant of income per capita. The literature suggests that political and economic institutions are fundamental to explaining the economic performance of a country. Essentially, institutional quality and economic development reinforce each other over the longer term (North 1990, Hall and Jones, 1999; Knack and Keefer, 1995; Glaeser 2004). Improving the institutional quality unlocks growth potential, and this does not intrinsically suffer from diminishing returns. 17

Table 1: Regression of Oil Abundance and Institutional quality on Income/capita OLS Estimates of the Effect of Log of Oil discoveries (mmboe) and Institutional Quality on Log GDP/capita Dependent variable: Log of Income per capita five years after Oil Discovery (1960-2015) Model I Model II Model III Model IV Log Oil Discovery (mmboe) 0.03** 0.06** 0.01** 0.01 (0.01) (0.03) (0.003) (0.01) Institutional Quality (IQ) 3.39*** 2.86*** -0.05-0.2 (0.43) (0.5) (0.09) (0.18) Interaction Term (Log Oil*IQ) -0.05-0.01-0.01 (0.04) (0.01) (0.01) Lag of Log of GDP/Capita (Year of Oil Discovery) 0.96*** 0.97*** (0.02) (0.01) Absolute Latitude -0.04 0.05 (0.09) (0.2) Log Population Growth -0.04** -0.06** (0.02) (0.03) Sub-Sahara Africa -0.05-0.1** (0.04) (0.05) South Asia -0.07-0.9 (0.04) (0.06) Latin America -0.05-0.07* (0.03) (0.04) MENA -0.01-0.06 (0.04) (0.06) Constant 6.34*** 6.60*** 0.60*** 0.62*** (0.32) (0.35) (0.09) (0.09) Europe and Outlier Countries Included? Yes Yes Yes No Observations 2993 2993 2664 1994 Number of countries 68 68 67 47 Time Dummies Yes Yes Yes Yes Adjusted R-sq 0.41 0.41 0.98 0.98 F-stat 33.97 55.1 17224 Notes: Data covers countries with the discovery of at least a giant oil field during 1960-2015. Model I represents the regression results using the log of oil abundance measured in the amount of discoveries of oil and gas equivalence (mmboe) in year t and the Institutional quality index alone. The institutional index is from the unweighted averages of average protection against expropriation, government effectiveness and executive constraints. Models I to IV use the GDP/capita five years after discoveries of giant oil fields as the dependent variable. Model II includes the Interaction term of the Log of oil discovery and institutional quality. Model III adds additional controls of the GDP/capita in the year of discoveries of giant oil fields and regional dummies. Model IV excludes Oil rich countries in Europe and central Asia, and outlier colonised countries of USA, Canada, Australia and New Zealand. The regional classification used is the World Bank classification of countries based on geographical location. All models report robust standard errors in parenthesis and are clustered at the country level. *, ** and *** represent significance level of estimates at p-values of <0.1, 0.05 and 0.01 respectively. 18

However, our first concern with the results in Table 1 is endogeneity. First, oil prospecting is capital intensive, and it is possible that developing countries might not have the human and financial capital to embark on oil prospecting which might reduce their chances of oil discoveries (Cust and Harding 2017). Second, it is also possible for institutional quality to be bi-directionally correlated with our measure of economic prosperity (income/capita) (Acemoglu et al. 2001). In addition, we cannot rule out the possibility of omission of variables that could likely be correlated with some measure of underdevelopment not included in our analysis. For instance, underdevelopment could be associated with the poor institutional quality and the income per capita in the base year of oil discovery which is included in our model. It could be possible that the empirical results are driven in part as a consequence of these confounding factors. Consequently, we extend our regression and conduct a 2-stage Instrumental Variable regression in section 3.2. 19

3.2 Instrumental variable regression We present our estimate using a dynamic panel 5- year distributed IV-GMM model in this section. In the first stage of our revised regression, we treat oil discovery, institutional quality and income at the base year of oil discovery as endogenous and estimate causal impact using a 2-stage GMM. Firstly, we present the reduced form model of the direct causal impact of our instruments; colonisation, a log of oil depth, British origin of a legal rule, and one and twoyear lag GDP/capita before the discovery of oil and gas on income per capita in Table 2. Table 2: Reduced Form relations Reduced Form Relations V VI VII VIII Dependent Variable: Log GDP/Capita t+5 Coly -0.001-0.06** (0.03) (0.03) Log Settlers' Mortality -0.02** -0.02** 0.01 0.01 British -0.01-0.003 0.02 0.02 Log depth 0.01** 0.01* 0.004 0.007 (0.01) (0.01) (0.004) (0.01) Log GDP/capita t-1 1.96*** 1.74*** 1.25*** 1.21*** (0.31) (0.38) (0.1) (0.1) Log GDP/capita t-2-0.99*** -0.79** -0.28** -0.25** (0.3) (0.4) (0.11) (0.1) Region Dummies Yes Yes yes Yes Time Dummies Yes yes Yes Yes Number of countries 67 47 32 28 Observations 2493 1868 1401 1239 Adj R-Squared 0.98 0.98 0.99 0.98 Notes: Data covers countries with the discovery of at least a giant oil field during 1960-2015 and the dependent variable is the log of GDP per capita five years after the discovery of giant oil. Model V includes all sample oil rich countries and Model VI exclude countries in Europe and central Asia. Model VII and VIII include just colonised oil rich countries taken from the sample of colonised countries in Acemoglu et al. 2001, and it includes as instruments for institutional quality, a log of settlers mortality and British colony dummy. Model VIII exclude colonised countries of USA, Canada, New Zealand and Australia (Outlier countries). All models include dummies to control for sub-sahara Africa, south-east Asia Latin America and MENA following the regional classification used in the World Bank classification of countries. In addition, all Models include additional controls of log population growth, and absolute latitude Robust standard errors are in parenthesis and are clustered at the country level. *, ** and *** represent significance level of estimates at p- values of <0.1, 0.05 and 0.01 respectively. 20

Table II shows that experience of colonialism is negatively correlated with income per capita in oil rich countries. Specifically, Model V and VI show that relative to non-colonised countries, countries with experience of European colonialism have lesser GDP per capita. The result gets significant after removing countries from Europe and central Asia from the sample. In addition, prior level of income before oil discovery influences income five years after oil discovery and the log of the depth of oil discoveries positively correlates with income, per capita. In Models VII and VII where we restrict our samples to colonised countries, we find a similar negative correlation between the log of settlers mortality and current income. Models VII and VIII, by contrast, show that the effect of depth of oil field on income per capita is not statistically indistinguishable from zero. A plausible implication of these findings is that experience of colonialism is associated with negative income inequality in oil rich countries. These findings are important to their right as they are suggestive of how the legacy of colonialism relates to income. In particular, it could explain the apparent improvement in the income of oil rich countries of the Gulf region who despite having poor institutional quality are growth winners from oil endowment when compared with oil rich countries with colonial experience in Africa and Latin America. Instrumental Variable Estimation According to our hypothesis, colonisation involved the restructuring of the economic and political capacity necessary for institutional quality. Colonialism could improve or deteriorate countries institutional quality relative to non-colonised countries either by affording the colonising European settlers to extend the institutional structure available in Europe or by distorting the institutional and political capacity that would encourage foreign consolidation of imperial rule. We present the reduced first stage of our model in Table III. 21

Table III: Reduced First stage model 1X X XI XII Panel A: First Stage for All Oil-Rich Countries Log Oil (mmboe) Institutional Quality Interaction term Log GDP/Capita l Coly -0.09** -0.15*** -1.19*** -0.02 (0.04) (0.01) (0.13) (0.4) Log depth 3.27*** -0.01** 1.84*** 0.001 (0.03) (0.003) (0.05) (0.001) Log GDP/Capita t-1-0.04-0.05 0.92 1.32*** (0.18) (0.09) (1.01) (0.08) Log GDP/Capita t-2 0.001 0.16* -2.07* -0.33*** (0.18) (0.09) (1.01) (0.08) Number of countries 67 67 67 67 Observations 2493 2493 2493 2493 F-stat 342 88 93.19 72714 Adjusted R-Squared 0.97 0.64 0.67 0.99 Panel B: First Stage for Colonised Oil rich Countries Log Settlers' Mortality 0.02-0.04*** 0.21*** -0.002 (0.02) (0.003) (0.05) (0.002) British -0.03 0.1*** -1.14*** 0.002 (0.03) (0.01) (0.05) (0.004) Log depth 3.3*** 0.002 1.92*** -0.009 (0.04) (0.002) (0.06) (0.1) Log GDP/ Capita t-1 0.13 0.06 0.15 1.2*** (0.23) (0.05) (0.69) (0.06) Log GDP/ Capita t-2 0.09 0.005-0.77-0.21*** (0.23) (0.05) (0.69) (0.06) Number of countries 32 32 32 32 Observations 1401 1401 1401 1401 F-stat 267.37 278.98 75.07 39289 Adjusted R-Squared 0.97 0.83 0.8 0.99 Notes: Data covers countries with the discovery of at least a giant oil field during 1960-2015 and the dependent variables are the endogenous regressors of Log Oil, Institutional Quality, the Interaction term of Institutional Quality and Log of oil abundance and are the log of GDP per capita in the year of discovery of giant oil. Variables in the left column are the instruments used. In Panel A, all oil rich countries in the sample are used while in panel B, only colonised oil rich countries are used. All models include dummies to control for sub-sahara Africa, south-east Asia Latin America and MENA following the regional classification used in the World Bank classification of countries. In addition, all Models include additional controls of log population growth, and absolute latitude Robust standard errors are in parenthesis and are clustered at the country level. *, ** and *** represent significance level of estimates at p-values of <0.1, 0.05 and 0.01 respectively. 22

Table III contains the instrumental variable estimates of the endogenous regressors of Log of Oil Discoveries, Institutional Quality, the Interaction term of Institutional Quality and Log of oil abundance and are the log of GDP per capita in the year of discovery of giant oil. Specifically, panel A is the first stage for all countries and the instrument for institutional quality is the experience of colonialism, which is a dummy variable taking the value of 1 if oil rich country experienced European colonialism and zero if not. In panel B, sample countries are oil rich countries with experience of colonialism and the instruments for institutional quality are the log of settlers mortality and a dummy variable of if the colony was under the British empire or not. The other instruments of the log of oil depth and lag values of log GDP per capita prior to oil discovery control the other endogenous regressors in both panels A and B. In both panels, the legacy of colonialism negatively influences institutional quality. In panel A, relative to non-colonised countries, countries with experience of European colonialism have poorer institutional quality and in panel B, the higher the log of mortality of early settlers, the poorer the institutional quality in such colonies in the current year. The resulting support previous studies that show that evidence of colonialism is related to the enduring poor institutional quality in several colonised countries (Acemoglu et al. 2001, Engerman and Sokoloff 2002, Dell 2010). Specifically, Acemoglu et al. (2001; 2005; 2012) suggest that log of mortality of early colonist in a colony is strongly correlated with average protection expropriation risk. In addition, our findings of the correlation of the identity of the colonial heritage with economic and socio-political variables that determines growth are supported by Bertocchi and Canova (2002). Also, prior level of income before oil discovery influences income five years after oil discovery and the log of the depth of oil discoveries positively correlates with a log of oil abundance and with the interaction term of institutional quality and Log of oil discovery. The first stage results confirm our hypothesis suggesting that colonisation matters for these countries and likely to affect the institutional quality and how it moderates resource endowment and likely to influence how these countries build capacity for the management of factor endowments. The endowment of these regions with rich agricultural and industrial raw materials could have attracted colonialization and which could have been exported for to Europe during the period of colonialization. To facilitate rapid extraction of such resources, it is plausible for the early colonialist to re-structure the political and economic to encourage 23