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THE GREAT DIVERGENCE IN SOUTH AFRICA: POPULATION AND
WEALTH DYNAMICS OVER TWO CENTURIES
African economic history working paper series
No. 47/2019
Dieter von Fintel, Stellenbosch University
Johan Fourie, Stellenbosch University
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ISBN 978-91-981477-9-7
AEHN working papers are circulated for discussion and comment purposes. The papers have not been peer reviewed, but published at
the discretion of the AEHN committee.
The African Economic History Network is funded by Riksbankens Jubileumsfond, Sweden
For submissions, contact:
Erik Green
Department of Economic History
Lund University
P. O. Box 7083
The great divergence in South Africa:
Population and wealth dynamics over two
centuries∗
Dieter von Fintel† and Johan Fourie‡
Abstract
Does wealth persist over time, despite the disruptions of historical shockslike colonisation? This paper shows that South Africa experienced a rever-sal of fortunes after the arrival of European settlers in the eastern half ofthe country. Yet this was not, as some have argued was the case elsewherein colonial Africa, because of an institutional reversal. We argue, instead,that black South Africans found themselves at the mercy of two extrac-tive regimes: those in ‘white South Africa and those in the ‘homelands.The political and economic institutions of each of those regimes favoured asmall elite: in white South Africa, whites, and in the homelands, the blackchiefs and headmen. Democracy brought inclusive institutions for blackresidents in white South Africa but not for those in the former home-lands. This is why we see mass migration to the urban areas of SouthAfrica today, and why addressing the institutional weaknesses of the for-mer homelands is key to alleviating the poverty in these regions where athird of South Africans still reside.
Keywords. reversal of fortunes, population persistence, institutional reversal, colo-nial impact, settler economy, African economic history, traditional leaders
∗We thank the editor, three anonymous referees, Kara Dimitruk, Katherine Eriksson,James Fenske, Erik Green, Remi Jedwab, Martine Mariotti, James Robinson, participantsat the ASSA meetings in San Francisco, the WEHC in Kyoto and the ESSA conference inCape Town for valuable comments on an earlier version of the paper.†LEAP, Department of Economics, Stellenbosch University; Institute of Labor Economics
(IZA), Bonn. E-mail: [email protected]‡LEAP, Department of Economics, Stellenbosch University.
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The great divergence in South Africa:
Population and wealth dynamics over two centuries
August 12, 2019
1 IntroductionCountries colonized by European powers during the past five centuries ex-perienced a reversal of fortunes: those that were relatively rich in 1500 arenow relatively poor. In their seminal contribution to African economic his-tory, Acemoglu et al. (2002) show that pre-industrial population density isnegatively correlated with modern-day income per capita. The result holdseven when they include only African countries in their study sample.
The cause of this negative correlation, they argue, is the institutions es-tablished by Europeans in the colonies. Fewer Europeans settled in denselypopulated regions, and instead of introducing ‘good’ institutions (such asprivate property rights), these colonial powers imposed ‘bad’, extractive in-stitutions. They say it was the poor institutional environment, rather thanthe geography, that made these countries poorer today than countries where‘good’ institutions were set up. They note that the ‘reversal in relative in-comes’ occurred mostly during the late eighteenth and early nineteenth cen-turies, and they argue that it ‘resulted from societies with good institutionstaking advantage of the opportunity to industrialise’ (Acemoglu, Johnson,and Robinson 2002, p. 1231).
Not everyone accepts the validity of this hypothesis. More recently,Maloney and Caicedo (2016) have used sub-national pre-colonial populationdensities for eighteen countries in the Western hemisphere to show thatpopulation density has persisted up to today: those countries with highestconcentrations in 1500 remain most densely populated. Importantly, thosecountries also have higher average income levels today, challenging Acemogluet al.s hypothesis and suggesting wealth persistence instead.
We compare the merit of these two conflicting arguments by consideringthe case of South Africa over the past two hundred years. Our resultsshow, firstly, that the settlement of black South Africans has been highlypersistent: those areas that were populated primarily by this group in the1830s and 1911 remain densely populated by their descendants today. Atfirst, this appears to lend support to the argument of Maloney and Caicedo
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(2016): locational advantage determines persistence. But we argue thatthis is a simplistic interpretation of historical processes. The settlementpatterns we observe in the 1830s are related to specific historical events,particularly conflicts within the Bantu-speaking peoples and the movementof European settlers into the interior of the country. As new archaeologicalevidence now shows, indigenous settlement patterns were very different onlyone century earlier. Although we find population persistence in the twocenturies before 2011 (the date of the most recent South African census),it is unlikely that settlement patterns at the beginning of the nineteenthcentury reflected a stable, Malthusian equilibrium. Path dependence maybe a better explanation for the observed trends than persistence.
When we consider measures of welfare, we find that the regions that weremost densely populated early in the nineteenth century have today the high-est unemployment rates and the lowest night lights luminosity. If we assumethat high population density in this era reflects relative wealth – as it wouldhave, given the devastating effects of the Mfecane – this seems to suggest thata reversal of fortunes occurred, of the kind that would support Acemoglu etal.s argument . But it is, again, not that simple. South Africa did not expe-rience an institutional reversal: rather, black South Africans were subjectedto extractive institutions in both ‘white South Africa’ and the homelands,the semi-autonomous polities that were formed around historically denselysettled areas. The extractive institutions in these homelands were the resultof a mixture of precolonial institutions and apartheid-era government in-fluences. Democracy brought new institutional arrangements: black SouthAfricans could now own property and vote in ‘white South Africa, but werestill subject to extractive institutions in the former homelands. The resultwas diverging economic outcomes for black South Africans, mitigated onlyby open borders and large out-migration.
Our paper expands the debate in three ways. First, past populationdensity is often assumed to be correlated with income. At least duringthe pre-colonial era, when populations tended to rise with and offset anyincreases in wealth, this Malthusian argument appeared to be valid. Wequestion this assumption in the case of South Africa. In particular, we ar-gue that the slave trade and internal warfare may have obliged people tosettle (even before colonial displacement) in areas that were not optimal forwealth accumulation following industrialisation – such as areas that wererugged or far from markets. Second, both Acemoglu et al. (2002) and Mal-oney and Caicedo (2016) include descendants of European settlers in theircurrent-day estimates of population density and income. Their estimatesare therefore confounded by other causal mechanisms (in addition to geog-raphy and institutions), such as cultural and genetic diversity. Our focusis only on the descendants of the indigenous, Bantu-speaking inhabitantsof South Africa. The mechanism that explains the persistence or reversalof population density and wealth must be either geography or institutions.
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Third, we argue that the mechanism that Acemoglu et al.(2002) found toexplain reversal of fortune, i.e. a change in institutions, does not explainthe South African case. Black South Africans were generally excluded fromeconomic and political rights in both ‘white South Africa and the formerhomelands. It was only towards the end of apartheid, and emphatically soafter 1994, that these rights began to be shared more equally and the welfareof black South Africans in the former ‘white areas began to improve. Thesame was not true in the former homelands, where the positions of chiefsand headmen became more entrenched, deepening the institutional divide.Migration from the former homelands to the cities has become the primarypoverty alleviation strategy for black South Africans in the twenty-five yearsafter the end of apartheid.
In short, our paper questions the premises of the persistence versus re-versal debate. Black South Africans incomes have diverged enormously, notbecause of an institutional reversal, but because of idiosyncratic historicalshocks that affected the timing and intensity of settler migration, the type ofextractive institutions that were set up in both ‘white South Africa and thehomelands and the inability to move between these, and the institutionaldivergence after the start of democracy. As the case of South Africa shows,history is too complicated to be compressed into binary outcomes at thebookends of historical eras.
2 Geography vs InstitutionsThere is little doubt that both geography – the climate, terrain, diseaseand other environmental conditions – and institutions – the formal andinformal ‘rules of the game’ – determine a region’s development trajectory.The pertinent question is which of these two determinants acts as the corebinding constraint towards further development. The answer would allowpolicy-makers to design policies that address these most urgent needs; ifgeography, then infrastructure investment or anti-malaria campaigns mightbe more appropriate, but if institutions, then the rule of law or protectingprivate property rights would matter more.
A vast literature has made a case for both. Poor geography, such as thepresence of natural resources, a tropical climate or being landlocked, nega-tively predicts income in early cross-country regressions (Sachs and Warner2001; Sachs and Warner 1997b; Sachs and Warner 1997a). Africa has fewnavigable rivers and most Africans live far from the coast (Collier and Gun-ning 1999). Africans are also more likely to live in rugged areas. Nunn andPuga (2012) argue that this is a consequence of the slave trade; in turn,the geographic patterns of the slave trade were influenced by climate shocks(Fenske and Kala 2015). Poor access to waterways and the rugged terraininhibit trade, lowering the profitability of surplus production, providing noincentive for economic growth.
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A bad disease environment, such as the presence of malaria, also explainsAfricans’ persistently low relative incomes (Gallup and Sachs 2001). Betteridentified empirical strategies have confirmed these earlier correlations, withmany of the diseases that were studied being unique to Africa: river blind-ness (Kazianga, Masters, and McMillan 2014), the tsetse fly (Alsan 2014),and a range of diseases caused by the intensity of UV radiation (Andersen,Dalgaard, and Selaya 2016).
However, geography also matters for Acemoglu, et al. (2002)’s mecha-nisms; their instrumental variable is a spatially determined measure of thedisease environment. Yet the mechanism through which they believe thepast persists into the present is the institutional characteristics that formedsociety. A bad disease environment, Acemoglu, et al. (2002) argue, haslittle effect on the indigenous populations who have had time to build upimmunities. Instead, a bad disease environment severely effects the arrivingEuropean settlers. In areas where tropical diseases decimate the Europeancolonisers, extractive formal institutions are imposed that have detrimentalconsequences for economic development. In areas where Europeans did notsuffer the consequences of a bad disease environment - such as in current-day South Africa - they settled and imposed institutions that are currentlygrowth promoting.
The precise mechanism through which institutions explain Africa’s pooreconomic performance has varied. Acemoglu, et al (2005, p. 397) somewhatvaguely refer to good institutions as those that promote ‘private property’,or which constitute a ‘cluster of good economic institutions, including therule of law and the enforcement of property rights’. Elsewhere, they pinthe mechanism down more explicitly. The ‘process of state formation’ wasdelayed in Africa relative to Eurasia, and ‘state institutions appear to havebeen intensely absolutist and patrimonial’. These pre-colonial institutions:
interacted in a perverse way with a series of shocks that hitAfrica, in particular the slave trade in the early modern period,and colonialism in the 19th and 20th centuries. African countriesemerged at independence with a complex path dependent set ofinstitutions that were probably even worse than those which theyhad at the time of colonization (Acemoglu and Robinson 2010,p. 21).
Some have tried to empirically verify political institutions as the mech-anism through which the African past effects the present (Gennaioli andRainer 2007). Michalopoulos and Papaioannou (2013) compare the spatialdistribution of ethnicities before colonisation with contemporary informationon economic performance at the regional level. Even when controlling for lo-cal geographic features and other observable ethnic-specific characteristics,they find a strong link between pre-colonial ethnic political centralisation
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and regional development. But centralisation, according to Osafo-Kwaakoand Robinson (2013), was not the result of high population density andtrade, as was the case in Eurasia. In fact, higher population density inAfrica was correlated with weaker degrees of centralization, and thus poorerdevelopment outcomes today: thus emerges an African reversal of fortune.
Political centralisation is, however, also correlated with other types ofinstitutions. Colonial powers brought different legal systems (La Porta,Silanes, and Shleifer 2008). Missionaries promoted formal education (Gal-lego and Woodberry 2010; Frankema 2012; Cage and Rueda 2016). Eventhe introduction of new crops affected land property rights; Fenske (2014)shows how the introduction of Brazilian rubber during the colonial periodtransformed land rights and land disputes in the Benin region of Nigeria.Rubber trees raised the value of land relative to labour, increasing farm sizesand creating both sale and rental markets.
The distinction between geographic and institutional explanations hastherefore become blurred. Alsan (2014) shows that ethnic groups locatedin tsetse-suitable areas were less likely to use domesticated animals and theplough. Consequently their settlement patterns were low density. Neverthe-less, the mechanism through which these past effects persist into the presentrelies on pre-colonial political centralisation, as suggested by others. But innew, unpublished work, Michalopoulos, Papaioannou and Weil (2016) arguethat political centralisation may itself be a consequence of geography: theyfind that the descendants of pre-colonial pastoralists are today more likely tobe poorer than the descendants of agriculturalists. The mechanism throughwhich this effect persists is the inferior treatment of women among those ofpastoral ancestry.
Isolating the exact mechanism across a range of countries may not be afruitful exercise: many likely reasons, contingent on the local environmental,political and economic context, explain why geography or institutions persistor not. Comparing distant historical events to present-day outcomes mayalso suffer from a ‘compression of history’, as Austin (2008) warns. Wetherefore investigate one country that has escaped the attention of economichistorians, despite exhibiting many of the features described in the literature.And we do so for several points of observation over time. Did wealth in SouthAfrica persist because of locational advantages (as Maloney and Caicedo(2016) found for most Latin American countries), or did fortunes reverse(much like Acemoglu, et al. (2002) argue for the whole of Africa)? Can weempirically disentangle the complex geographic or institutional mechanismsthat underpin such persistence or reversal?
3 The Great Divergence within South AfricaOne advantage we have in investigating South Africa is that the descendantsof the European settlers have remained, to a large extent, a separate com-
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munity from the indigenous, Bantu-speaking peoples. Integration betweenthe Bantu-speaking Africans and the descendants of Europeans was min-imal during the first two centuries of settlement, and criminalised duringthe twentieth century. Even after legalisation and democracy, inter-ethnicmarriages remain uncommon.
This feature of South African history and society allows us to investigatethe persistence or reversal of wealth within the Bantu-speaking population.As far as we can tell, none of the earlier studies could do this: in LatinAmerica, European settlers mixed with indigenous and slave populations.Any measure of welfare today includes the fortunes of the descendants ofEuropean immigrants. Similarly, the reversal of fortune-hypothesis thatAcemoglu, et al. (2002) advance includes the descendants of European set-tlers. Most ‘neo-Europes’ (such as Australia, New Zealand, Canada and theUnited States) are today populated by descendants of Europeans; whereindigenous populations have remained a separate community, they are apoor minority. The decline in relative and absolute numbers of the indige-nous populations over several centuries is due to a combination of diseasessuch as smallpox that decimated vulnerable populations, the seizing of landand resources and, often, violence and warfare perpetrated by Europeanimmigrants. We take the view that comparing initial indigenous popula-tions with descendants of European immigrants distorts the mechanismsof a reversal or persistence of fortunes. South Africa, where the descen-dants of Bantu-speaking people survive and constitute the majority of thepopulation, we believe, provides a relatively uncontaminated case study ofhow wealth persists or reverses over two centuries of settlement within theindigenous population.
Although European immigrants already settled South Africa in the mid-seventeenth century, they did not immediately confront Bantu-speaking peo-ples. They instead settled at the southwestern tip of the continent, in thequasi-Mediterranean, winter-rainfall climate of the Cape. The region was in-habited by the Khoesan, a heterogenous group of nomadic pastoralists andhunter-gatherers. Under Dutch East India Company rule, the settlementexpanded to cover most of this winter-rainfall region. Settler farmers movedeast until they met, towards the end of the eighteenth century, the agricul-turalist, Bantu-speaking isiXhosa at what became the eastern boundary ofthe Colony (Elphick and Giliomee 2014).
Bantu-speaking peoples had migrated into southern Africa around twomillennia ago, reaching the modern-day northern border – the Limpoporiver – of South Africa around 300 AD. In a slow and haphazard processof group fragmentation and augmentation (often with indigenous hunter-gatherer people), Bantu-speakers settled across modern-day South Africa,except in the semi-arid western half and the quasi-Mediterranean southwest.However, these settlement patterns were in continuous flux, especially dur-ing the first decades of the nineteenth century. Around 1815, a series of
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conflicts erupted within and between the Bantu-speaking communities ofSouth Africa. The cause(s) of the conflicts, now known as the mfecane inZulu or difaqane in Sesotho, remain unsolved (Eldredge 1992); historianshave variously attributed these events to the leadership of Shaka, conflictwith European farmers on the frontier, the slave and gold trades and, inrecent contributions, to the eruption of a volcano on an Indonesian islandwhich caused resource constraints across southern Africa (Garstang, Cole-man, and Therrell 2014). But the reason why the mfecane happened is lessimportant here; we are more concerned, instead, with its consequences.
Starting in modern-day Kwazulu-Natal, or Zululand, the mfecane ledto large-scale resettlements of people across southern Africa. One defectinggroup of Zulu, the AmaNdebele under Mzilikazi, migrated northwest andwest. They finally settled in modern-day Zimbabwe (Matabeleland), caus-ing widespread disruption on their way. Those resisting the Zulu, like theNdwandwe, were forced to flee east into modern-day Mozambique, displacingthe Tsonga (who in turn fled over the Lubombo Mountains into the north-ernmost region of South Africa). Others, like the Makololo, moved north,displacing several Tswana-speaking groups (in modern-day South Africa andBotswana), and settling for three decades amongst the Luyi in Barotseland,part of modern-day Zambia and Angola. From here they would later moveinto modern-day Malawi. And others, dislocated from their former placesof residence by repeated Zulu warfare, moved west, settling between theamaXhosa and becoming known as the Mfengu.
Some moved pre-emptively. The Ngwane, hoping to escape Zulu attacks,moved to higher elevations and established the Swazi kingdom in what isnow Eswatini. Moshoeshoe I also moved to the rugged mountains of theDrakensberg to create an alliance of Sotho groups against the Zulu, whichlater became known as Basutoland, and still later, the Kingdom of Lesotho.
As a consequence of the need to secure access to food and other re-sources and to provide protection against the Zulu, several political entitieswere born throughout southern Africa, most notably the Swazi and Basutokingdoms. But protection necessitated not just more centralised states; therefugees consolidated their new kingdoms in rugged areas that provideddefence against outsiders. This concentration in rugged areas is found else-where in Africa too. The Atlantic slave trade pushed Africans into ruggedand less accessible regions to reduce the risk of being enslaved (Nunn andPuga 2012).
When the mfecane dissipated by the 1830s, the spatial distribution ofBantu-speakers had been irrevocably changed. Figure 1 (a) shows regionsthat were not affected by the mfecane or colonial rule by the 1830s. Thesewere the most densely populated regions, concentrated in the high-rainfall,rugged areas of the east coast of South Africa, and inhabited by a collectionof amaXhosa clans like the Pondo, the Thembu and the immigrant Mfengu,and further up along the coast, the Zulu of Zululand and the Swazi of Swazi-
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land. The open, flat interior of the country, formerly home to mostly Sothoand Tswana, had been devastated by conflict. Survivors moved either northinto modern-day Botswana or found refuge in the Drakensberg mountains(the Basotho).
Recent archaeological evidence supports the contention that indigenoussettlement patterns were not static before European arrival. Sadr andRodier (2012) use Google Earth satellite imagery to identify dispersed pre-colonial homesteads and nucleated towns in the Suikerbosrand Nature Re-serve close to Johannesburg. Inhabited during the fifteenth to the seven-teenth century, the settlement disappeared because of ‘climate change, con-flict and other factors’ (Sadr and Rodier 2012, p. 1034). The Suikerbosrandsettlement also ‘echo[es] similar patterns reported in the neighboring NorthWest Province, where they have been interpreted as a sequence of evolu-tion in social, political and economic complexity’ (Sadr and Rodier 2012,p. 1034).
The wars and dispersal at the beginning of the nineteenth century hadconsequences that were different from earlier periods of turmoil. The mfe-cane had left much of the South African interior uninhabited by the 1830s.This quasi-desertification allowed bands of European settlers of Dutch de-scent to move deeper into the interior of the country, at low risk. Figure1(a) shows the routes that these settlers followed into the interior. There isstill little agreement on the reasons these Voortrekkers left the Cape Colony:the ongoing frontier conflicts with the amaXhosa (Africa’s Hundred YearsWar, from 1789 to 1889), the arrival of large numbers of British settlers (in1820), a hostile British government (which had taken control of the Cape in1806 and introduced new policies, in the late 1820s, that affected access toland and labour), and the emancipation of slaves (in 1834) are just severalreasons touted for the migration. Beginning in 1836, several thousand fron-tier farmers moved deeper into the South African interior. Although there isno doubt that these push-factors could have been important, the pull-factorof abundant land obtained at relatively low risk must have been appeal-ing too, especially for highly indebted land speculators in the Colony. TheVoortrekkers were not welcomed everywhere they arrived. Several skirmishesensued, most notably when they arrived in Zululand. As a consequence, theVoortrekkers avoided those areas that were densely populated by Bantu-speaking groups and settled instead in those areas left largely vacant by themfecane (Etherington 2004b).
These Voortrekkers quickly brought the political and economic institu-tions they had left behind to the new regions of settlement. The SouthAfrican Republic (which was formally recognised by Britain under the SandRiver Convention treaty in 1852) protected the right of farmers across theVaal River to govern themselves. A second Boer republic – the Orange FreeState – gained independence in 1854. The new states provided full rights toall citizens who had resided in the territory for at least six months. These
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rights included property ownership and the vote for the legislative authority(the Volksraad or People’s Council), every five years. Of course, there wasone notable exception: only white immigrants and their descendants couldbe citizens.
These whites would benefit most from the discovery, in 1867, of vastquantities of diamonds on the Orange Free State and Cape Colony border(Cilliers and Fourie 2018). The discovery of diamonds, and of gold twentyyears later, reorientated the economic power of the region from the coastto the interior (Feinstein 2005). Thousands of immigrants arrived from Eu-rope and elsewhere, pulled by the promises of quick fortunes; as a result,many profited. Some original inhabitants of the region benefited too; forinstance, some Basuto farmers suddenly had a ready market for their pro-duce (Bundy 1979). But the construction of the railways to Kimberley andJohannesburg to supply the mines with equipment, and the surroundingtowns with foodstuffs and manufactures, dragged down the Basuto econ-omy (Herranz-Loncan and Fourie 2017). The mines, of course, demandedlabour. Although many Bantu-speakers flocked to (or were sent to the minesby their chiefs), their living conditions and bargaining power soon declined,making mining less attractive to them. The colonial governments respondedby instituting head and other taxes to forcibly increase the supply of labour.Mines also offered only temporary accommodation for these migrating blackmine workers, adopting a system of migrant labour (Wilson 2001).
The political and economic institutions that favoured growth – a la Ace-moglu, et al. (2002) – were thus embedded in the new Boer republics tothe benefit of the white community. Attempts were made to extend prop-erty rights to the Bantu-speaking groups. The Glen Grey Act of 1894, forinstance, extended individual land holdings to areas in the Cape Colonythat were then under communal ownership. However, these policies weremostly sinister attempts at racial segregation, hoping to increase the supplyof labour on the mines or boost fiscal revenue. They seldom had the benefitof boosting Bantu-speaking participation in the market economy. Although‘coloured’ (descendants of slave, Khoesan, black and European liaisons) andBantu-speaking (black) property owners could vote in the Cape Colony, theunification of the two British colonies (Cape and Natal) with the two for-mer Boer republics into the Union of South Africa in 1910 abolished manyof these rights. The two British protectorates, Basutoland and Swaziland,remained separate political entities, becoming independent countries in 1966and 1968 respectively.
Over the course of the twentieth century, coloured and black inhabitantsincreasingly lost political and economic rights in ‘white South Africa’. TheBantu Land Act of 1913 was the first policy of the Union to formally reg-ulate the acquisition of land by blacks. It created black ‘reserves’ in thoseareas where black settlement was most dense, an area less than 10% of theUnion, and introduced certain restrictions on blacks owning land outside
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the reserves. The reserve boundaries are shown in figure 1(b). The purposewas ostensibly to reduce the status of black sharecroppers to tenant farmers,increasing black tenant labourers on white farms, and to limit the possibilitythat blacks could repurchase white-owned land. The law was amended in1936, increasing the proportion of reserve land to 13%. Mpeta et al. (2018)use data on individual heights to show that black living standards declinedsignificantly during the first three decades of the twentieth century.
After the National Party victory of 1948, apartheid policies were intro-duced that not only segregated whites from other races within towns andcities, but, through the Grand Apartheid policies of ‘separate development’introduced in the 1950s and 1960s, created homelands – or Bantustans –for the different black ethnic groups residing in South Africa. These home-lands often matched the borders of the reserves established earlier, but nowwith the intent of establishing self-governing, semi-independent states. Theultimate aim was to make blacks living within the borders of South Africanationals of the homelands instead of the newly formed Republic of SouthAfrica, a policy which was eventually made concrete by the Black Home-lands Citizenship Act of 1970. Four of the homelands - Transkei (Xhosa),Bophuthatswana (Tswana), Venda, and Ciskei (Xhosa) - were declared inde-pendent states, while three others, KwaZulu (Zulu), Lebowa (North Sotho)and Qwaqwa (South Sotho) received partial independence. Independencewas never recognized outside South Africa. Separate development also af-fected the spatial distribution of people: to adhere to the ethnic restrictionsplaced on settlement, large numbers of blacks were relocated - up to 3.5 mil-lion people (Abel 2015). Almost all resettlements were from ‘white SouthAfrica’ to the homelands.
These homelands often had little economic security to offer. Land waslimited and ownership communal; land use rights depended largely on thegoodwill of the chief or headman. Moreover, chiefs were often not elected butappointed by the apartheid government. According to Burger (2018, p. 222),‘[T]he apartheid government used the tribal system to maintain control overthe black population in traditional areas, appointing and dismissing chiefson the basis of their cooperation with the apartheid government and itsvarious structures. If a chief was not cooperating to the satisfaction of thegovernment he was deposed and replaced’. He explains how councillors in thehomelands were appointed by (white) commissioners and black taxpayers,but that commissioner could overrule anyone elected by taxpayers. ‘Thisrigged the system and ensured that resistance from within the governancestructures to apartheid rule was minimised’ (Burger 2018, p. 222).
The policy of segregation and, later, separate development was an at-tempt by the apartheid government to push back against the large-scaleurbanization of blacks that had followed the high economic growth rates ofSouth Africa from the mid-1930s until the early 1970s. Although apartheidpolicies prevented blacks from benefiting directly from political and eco-
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nomic institutions, rapid growth in urban areas created economic opportu-nities on a scale much bigger than those on offer in the homelands. Attemptsat industrial policy were largely ineffective at relocating industry to the pe-ripheries of the homeland borders (Lowenberg 1997).
The apartheid government and its skewed institutions of ownership wereonly replaced by democracy in the early 1990s. Only then did all SouthAfricans enjoy the right to acquire and own property, and move withoutrestrictions. While changes in property rights did occur in former ‘whiteSouth Africa’, the economic institutions of the former homelands remainedlargely the same, with communal ownership dominating. One of the featuresof post-apartheid South Africa is the large rates of internal migration of bothmen and women from the former homelands (von Fintel and Moses 2017).
This changing institutional landscape provides one reason for complicat-ing the binary long-run outcomes proposed by Acemoglu, et al. (2002) andMaloney and Caicedo (2016). Whether the transitory institutional arrange-ments of the nineteenth century would have the same effect on black livingstandards as the increasingly repressive and discriminatory institutions oftwentieth century ‘white South Africa’ is unclear. Nor is it clear whetherthe institutions of the native reserves and later Bantustans, or of the inde-pendent nations of Lesotho and Swaziland, would result in similar outcomesbefore and after democracy in South Africa. By considering only the in-digenous population and by splitting the period of analysis into three parts,we investigate how settlement and fortune persisted or reversed over nearlytwo centuries. A less compressed history may offer better insights into howgeography and institutions interact to explain contemporary settlement pat-terns and living standards, and which mechanisms may be responsible forthis persistence or reversal.
4 DataTo measure the persistence of population density across two centuries, wemake use of two new datasets. Firstly, we infer 19th century (post-mfecane)black settlement patterns from digitised historical maps (Walker 1922). Be-cause no figures for population density of Bantu-speaking peoples and theirspatial distribution exist in this period, we only infer their approximate lo-cations. Areas that were not devastated by the mfecane and which werelocated outside British colonial territories are assumed to have been settledby indigenous populations. Critics believe that Walker’s maps were moreaccurate than those previously drawn, but may not have indicated the fullextent of black settlement (Etherington 2004a). However, we argue thatsettler migrant routes partially verify these patterns.
The bands of Voortrekker migrants moved somewhat arbitrarily into theinterior, attempting to circumvent densely-populated areas to avoid conflict,with no obvious end destination in mind. They could do this because of the
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devastation caused by the mfecane which had consolidated Bantu-speakingtribes into defensible areas and left large tracts of land in the interior onlysporadically inhabited by Bantu-speaking people at the time of their mi-gration. As Etherington (2001, p. 323) remarks: ‘Powerful chiefs and kingsstill held the best well-watered defensible positions where agriculture couldbe practised alongside pastoralism’. Our evidence below is consistent withthis view, as white settlers did not migrate to the best agricultural land,which was also densely populated by Bantu-speaking groups in later years(for which figures are available).
Figure 1 (a) provides (inter alia) a map of the routes that these migrantsfollowed. The routes departed from the British colonial frontier, and mostlytraversed areas that were unaffected by the mfecane to reach areas thatwere indicated as abandoned. In some instances, the settlers circumventedareas of black settlement. In the case of the Zulu Kingdom, the settlersfirst ventured into the territory, before turning around. All indications sug-gest that the routes were followed to find land that was not occupied byBantu speakers after the mfecane. Because these trekker routes started onthe eastern border of the then Cape Colony, our analysis excludes most ofthe western parts of what would become the unified South Africa. Histor-ical sources suggest that almost no Bantu-speaking people inhabited thissparsely-populated and semi-arid region.
Secondly we use the population estimates for the 1911 census districts.This census was the first to cover the full territory that encompasses modern-day South Africa. Again we exclude the semi-arid western half of SouthAfrica. Finally, we obtain population estimates for similar regions from the1996 and the 2011 South African censuses.1
We are interested in the correlations between population locations anddensity at the start of the nineteenth century, at the start of the twentiethcentury and the start of the twenty-first century. Does the spatial distri-bution of the black population and its density persist over two centuries ofremarkable societal change in South Africa? Further, does early populationdensity also predict better modern-day labour market outcomes and localeconomic conditions? Our empirical analysis attempts to distinguish be-tween geographic and institutional explanations for the observed patterns.To this end, we collate multiple data sources, matching them with the geo-graphic units of analysis of the 1911 census.
Firstly, we obtain district-level geographic and environmental indica-tors. We incorporate long-run rainfall data made available by climatologists(Willmott and Matsuura 2012). These data are gridded at 0.5 x 0.5 degreepoints for all terrestrial areas across the globe. Their long-run rainfall es-timates provide spatial variation in usual precipitation patterns, indicating
1Many boundary changes emerge across time, so that we apply areal weighting tomatch later figures to 1911 boundaries.
12
the potential of the land to be fruitful. We aggregate these grids onto 1911census demarcations to incorporate into our empirical models. Similarly, wedraw in crop suitability indices to understand whether populations movedto regions that could potentially offer food security in the long run. In par-ticular, we follow Galor and Ozak (2016), who develop a 0.5 x 0.5 degreecaloric suitability index, which adjusts potential crop yields to reflect thenutritional value that could be produced from land in gridded regions.
Following Nunn and Puga (2012), we study district-level indicators ofterrain ruggedness. This particular feature does not measure the benefitsof location for food security, but for physical security in the context ofearly political conflicts. This indicator therefore represents the interactionof geography with institutional upheaval.
More direct institutional shocks are also spatially defined. In particular,we study the legacy of the 1913 Land Act. These areas were designatedby the new Union government as reserves for blacks. Within the confines ofthese areas, blacks could own property subject to the communal law systemsof traditional chiefs. More importantly, these regions laid the foundation forthe apartheid -era Bantustans. The long-run welfare and social effects of cre-ating separate homelands persist to this day (Pienaar and Von Fintel 2014),and would likely have been areas of agglomeration had these institutions notbeen implemented (Von Fintel 2018). The homelands or Bantustans, cre-ated in 1959, were designed to facilitate the ‘separate development’ of SouthAfrica’s different ethnicities. We trace the borders of these homelands andthen consider the proportion of the area of each of the 1911 districts thateventually became an apartheid homeland. This serves as an indicator of20th century institutional shocks that affected the black population in dif-ferent locations.
We use two outcomes to represent modern welfare. The first is district-specific unemployment rates sourced from the 1996 and 2011 censuses. Un-employment is a strong correlate of chronic poverty in democratic SouthAfrica (Aliber 2003) and can be directly measured at the local level in cen-sus records.2 Secondly, we use night lights luminosity in 1996 and 2011, acommonly used measure to represent local economic development (Hender-son, Storeygard, and Weil 2012; Von Fintel and Moses 2017).3
This paper uses standard econometric techniques – Ordinary Least Squaresregressions – to illustrate three propositions.4 Firstly, we show that early
2On the other hand, the incomes recorded in South African census data are poorlyreported; welfare estimates are sensitive to assumptions regarding imputations of bracketsand implausible reports of zero incomes (Ardington et al. 2006). We therefore do not relyon incomes in analysing the reversal of fortunes.
3While we use the broad unemployment rate of black South Africans, we can, of course,not differentiate night lights luminosity by race.
4In the online supplementary materials, we repeat the analysis using spatially clusteredstandard errors, developed by Conley (1999) and coded by Hsiang (2010). Various distancecut-offs are used, ranging from 50km to 1000km. Except where we explicitly state the
13
19th century black settlement patterns were driven in part by the nutritionalpotential of the land and the security of rugged terrain. Even if these pat-terns were prompted by migrations related to the mfecane, the Great Trek,the frontier wars and the internal conflicts that led to the formation of aUnion, settlement was focused in areas with suitable conditions for estab-lishing fortune in future. Secondly, we illustrate that the settlement patternpersists into the 21st century, partially facilitated by geographic fundamen-tals; however, due to institutional shocks, the persistence in population isnot equivalent to persistence in fortunes. Instead, regions that provided highpotential for food security in the pre-industrial area became high unemploy-ment regions with relatively low night lights luminosity in modern times.Despite two decades of unrestricted movement in democratic South Africa,the persistence of settlement but reversal of fortune remains a feature of theSouth African landscape.
5 Evidence of persistence and reversal5.1 Population persistence
Figure 1 (a) shows the distribution of the indigenous population in 1830.Shaded districts overlap with the areas which Walker (1922) indicated asbeing unaffected by the Mfecane. These areas continued to be densely pop-ulated in 1911 and 2011. Figures 1 (b) and (c) illustrate the locationalpersistence of the black population distribution in South Africa between1911 and 2011, a finding similar to that of Krugell (2014). The Xhosa pop-ulation remains concentrated between the Fish and the Kei rivers and theZulu population are located largely around Shaka’s early-nineteenth cen-tury centroid of power in the east of the country. Figure 1(a) indicates thatVoortrekker migration routes tended to avoid or circumvent regions thatwere unaffected by the Mfecane; these areas would eventually be denselypopulated by indigenous inhabitants in later years. This indicates that 20thand 21st century settlement patterns were already in place by the beginningof the 19th century. These highly populated regions also correspond to theLand Act and homelands borders that were imposed by the early and middleof the 20th century respectively (see Figure 1 (b) and (c)).
Were these initial settlement patterns chosen based on favourable geo-graphic conditions? Figure 2 (a) shows that the regions which were denselyinhabited by black South Africans in 1911 were also highly suitable for en-suring potential food security (as represented by the caloric suitability ofthe land). Most of the Voortrekker settler routes did not navigate to re-gions with the same potential, except for the isolated parties that venturedinto the Zulu kingdom after concluding a treaty with Dingane in 1838. In-digenous populations therefore claimed the best land with the most suitable
contrary, our results are robust to the mode of inference.
14
Fig
ure
1:
(a)
Bla
ckse
ttle
men
tin
1830
.R
epre
sente
das
the
regi
ons
bey
ond
the
Cap
eC
olon
yb
ord
eran
dth
ere
gion
sth
atw
ere
mos
tly
un
aff
ecte
dby
the
mfe
can
e(a
tle
ast
70%
ofd
istr
ict
was
not
mar
ked
as”a
ban
don
ed”
by
Wal
ker
’s(1
922)
map
.(b
)19
11P
opu
lati
onD
ensi
typ
ersq
uar
ekm
,m
easu
red
inlo
gs.
Sou
rced
from
the
1911
cen
sus.
(c)
2011
Pop
ula
tion
den
sity
per
squ
are
km
,m
easu
red
inlo
gs.
Sou
rced
from
the
201
1ce
nsu
s.A
llfi
gure
sm
app
edon
1911
dis
tric
tb
oun
dar
ies
usi
ng
aere
alw
eigh
ting.
15
Fig
ure
2:(a
)C
alo
ric
Su
itab
ilit
yIn
dex
.(b
)T
erra
inR
ugg
edn
ess
Ind
ex.
(c)
Lon
g-ru
nra
infa
llin
mm
.A
llfi
gure
sm
app
edon
191
1d
istr
ict
bou
nd
arie
s.
16
agricultural potential, while settlers followed afterwards and occupied thenext best territories, avoiding existing settlements. These patterns are alsoreflected in long-run rainfall patterns that are depicted in Figure 2(b).
Pre-industrial food security was, however, not the only determinant ofblack settlement patterns. Conflict did not only motivate the choice of whitesettler routes, but also the proximate migration patterns of black groups.Figure 2(c) shows that populations settled - partially, at least - in placesthat were the most rugged in the region. These regions are also known tobe adjacent to the locus of the mfecane in the 19th century. They providedsecurity from the ensuing instability in much the same way that Nunn andPuga (2012) attribute the concentration of African populations in ruggedterrain to the violence of the slave trade. Putting these factors together,early black settlement patterns were motivated by a combination of thepotential for food security and safety from conflict.
Table 1 presents a set of correlation coefficients, and confirms many ofthe relationships between these factors. While our proxy for early 19th cen-tury black population density (Settle1830, or being unaffected by colonialrule or the mfecane) is positively correlated with terain ruggedness (Rugged)and caloric suitability (Soil), a weak negative correlation with rainfall arises.The latter finding is somewhat surprising, but arises due to large settlementsin the current-day Free State and North-West provinces, which are typicallydrier than the eastern part of the country. Zululand and the area that wasknown as the Transkei during apartheid, both enjoy high rainfall and soilsuitability. Black Africans therefore tended to settle in agriculturally suit-able regions; the ‘bad geography’ of these same regions was also favourableat the time that the mfecane was winding down. Settlement in regions withhigh food potential persisted into later years, except that by 1911 blackSouth Africans were located in more rugged regions, seeking security in thepost-mfecane period. On balance, however, population distributions remainstrongly correlated over a period of more than 150 years. High density inall historical periods are correlated with high unemployment today.
Table 2 presents Ordinary Least Squares (OLS) regressions to illustratepartial correlations. In the first column, our proxy for early 19th centuryblack settlement patterns is positively correlated with population density in1911, though its magnitude reduces once we control for rainfall and rugged-ness in column two.5 The latter are both positively correlated with popu-lation density in the early 20th century. This supports our hypothesis thatblack settlement patterns by 1911 were partially determined by climate and
5They are only significant at a 10% level. In the online supplementary material, weshow results using Conley (1999) standard errors. Allowing for spatial correlations overshort distances reduces the correlations to insignificance at standard levels; once we allowfor spatial relationships reaching as far as 1000km, they become highly significant. We in-terpret this as evidence for a positive relationship, though measurement error in our proxyvariable for 1830 settlement patterns inflates standard errors and reduces significance.
17
Set
tle1
830
Pop
1911
Pop
1996
Pop
2011
Un
em19
96U
nem
2011
Lig
ht1
996
Lig
ht2
011
Rai
nR
ugg
edS
oil
Set
tle1
830
1.0
000.1
460.0
460.
134
0.30
30.
283
-0.3
48-0
.394
-0.0
040.
223
0.04
1P
op191
10.1
461.0
000.8
550.
830
0.58
30.
518
0.37
80.
131
0.65
60.
503
0.64
3P
op199
60.0
460.8
551.0
000.
883
0.62
50.
496
0.50
80.
248
0.75
50.
405
0.63
7P
op201
10.1
340.8
300.8
831.
000
0.49
30.
371
0.52
30.
322
0.65
80.
385
0.55
7U
nem
199
60.3
030.5
830.6
250.
493
1.00
00.
791
-0.1
25-0
.378
0.37
00.
503
0.40
8U
nem
201
10.2
830.5
180.4
960.
371
0.79
11.
000
-0.2
11-0
.434
0.40
30.
497
0.43
3L
ight1
996
-0.3
48
0.3
780.
508
0.52
3-0
.125
-0.2
111.
000
0.91
20.
442
-0.1
510.
231
Lig
ht2
011
-0.3
94
0.1
310.
248
0.32
2-0
.378
-0.4
340.
912
1.00
00.
214
-0.2
970.
062
Rai
n-0
.004
0.6
560.
755
0.65
80.
370
0.40
30.
442
0.21
41.
000
0.47
70.
742
Ru
gged
0.2
230.5
030.4
050.
385
0.50
30.
497
-0.1
51-0
.297
0.47
71.
000
0.69
5S
oil
0.0
410.6
430.6
370.
557
0.40
80.
433
0.23
10.
062
0.74
20.
695
1.00
0
Tab
le1:
Cor
rela
tion
matr
ix.
(1)Settle1
830
rep
rese
nts
ab
inar
yva
riab
lere
pre
senti
ng
dom
inan
tb
lack
sett
lem
ent;
itis
der
ived
from
figu
re1(a
)u
sin
gW
alke
r(1
922)
;(2
)Pop
1911
,Pop
1996
andPop
2011
are
logg
edb
lack
pop
ula
tion
den
siti
esfr
omth
ere
spec
tive
cen
sus
data
sets
;(3
)Unem
199
6an
dUnem
2011
are
the
logg
edb
road
un
emp
loym
ent
rate
s(i
ncl
ud
ing
dis
cou
rage
dw
ork
ers)
der
ived
from
cen
sus
data
;(4
)Light1
996
and
Light2
011
are
logg
edligh
tslu
min
osit
yfigu
res
from
the
Nat
ion
alO
cean
ican
dA
tmosp
her
icA
dm
inis
trat
ion
;(5
)Rain
rep
rese
nts
lon
g-ru
np
reci
pit
atio
nle
vels
(Wil
lmot
tan
dM
atsu
ura
2012
);(6
)Rugged
isth
ein
dex
ofte
rrai
nfr
om
Nu
nn
&P
uga
(201
2);
(7)Soil
isa
calo
ric
suit
abil
ity
ind
ex(G
alor
and
Oza
ka20
16).
18
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
Pop
191
1P
op
1911
Hom
elan
dP
op19
96P
op19
96P
op20
11P
op20
11P
op20
11P
op20
11
Set
tle1
830
0.3
33*
0.2
55*
(0.1
93)
(0.1
45)
Pop
191
10.1
55**
*0.
952*
**0.
726*
**0.
950*
**0.
823*
**0.
355*
**0.
359*
**(0
.029
)(0
.070
)(0
.072
)(0
.072
)(0
.082
)(0
.088
)(0
.090
)H
om
elan
d0.
552*
*0.
448*
*0.
066
0.02
0-0
.278
-0.2
67(0
.217
)(0
.197
)(0
.223
)(0
.223
)(0
.182
)(0
.189
)P
op199
60.
624*
**0.
640*
**(0
.070
)(0
.081
)R
ugg
ed0.0
16**
*0.0
06**
*-0
.005
-0.0
04-0
.001
(0.0
06)
(0.0
02)
(0.0
05)
(0.0
05)
(0.0
04)
Rai
n0.0
05**
*0.0
000.
003*
**0.
002*
**-0
.000
(0.0
01)
(0.0
00)
(0.0
01)
(0.0
01)
(0.0
01)
Con
stan
t1.7
79**
*-1
.696*
**-0
.270
**1.
194*
**-0
.452
2.04
5***
1.11
8***
1.30
0***
1.40
7***
(0.1
26)
(0.3
47)
(0.1
23)
(0.1
22)
(0.2
85)
(0.1
25)
(0.3
23)
(0.1
30)
(0.2
71)
R-s
qu
are
d0.0
210.4
790.
435
0.74
30.
805
0.68
90.
713
0.80
40.
804
N138
.000
138
.000
138.
000
138.
000
138.
000
138.
000
138.
000
138.
000
138.
000
F2.9
6941.
108
34.4
2619
4.87
213
7.48
714
9.23
682
.433
182.
977
108.
382
Tab
le2:
Pop
ula
tion
per
sist
ence
:19
thto
earl
y20
thce
ntu
ry
NO
TE
S:
*p<
0.1
,**
p<
0.05
,***
p<
0.01
.O
LS
regr
essi
ons
usi
ng
vari
ous
inte
grat
edd
ata
sou
rces
.(1
)Settle1
830
rep
rese
nts
ab
inary
vari
able
rep
rese
nti
ng
dom
inan
tb
lack
sett
lem
ent;
itis
der
ived
from
figu
re1(
a)u
sing
Wal
ker
(192
2);(2
)Pop
191
1,Pop
1996
an
dPop
201
1ar
elo
gged
bla
ckp
opu
lati
ond
ensi
ties
from
the
resp
ecti
vece
nsu
sd
atas
ets;
(3)Unem
1996
andUnem
2011
are
the
logge
db
road
un
emp
loym
ent
rate
s(i
ncl
ud
ing
dis
cou
rage
dw
orke
rs)
der
ived
from
cen
sus
data
;(4
)Light1
996
andLight2
011
are
logg
edli
ghts
lum
inos
ity
figu
res
from
the
Nat
ion
alO
cean
ican
dA
tmosp
her
icA
dm
inis
trati
on
;(5
)Rain
rep
rese
nts
lon
g-ru
np
reci
pit
atio
nle
vel
s(W
illm
ott
and
Mat
suu
ra20
12);
(6)
Rugged
isth
ein
dex
ofte
rrai
n(N
un
nan
dP
uga
2012
);(7
)Soil
isa
calo
ric
suit
abil
ity
ind
ex(G
alor
and
Oza
ka20
16)
(8)Hom
eland
isth
ep
rop
ort
ion
ofth
ed
istr
ict
that
was
loca
ted
inan
apa
rthei
dh
omel
and
.
19
geography of the post-mfecane period, and not only settler movements.Because our proxy for 1830 black settlement does not measure population
density, we continue to use the log of 1911 population density as a predictorfor the location of apartheid homelands (column 3), population density in1996 (columns 4 and 5) and population density in 2011 (columns 6 through9). In all of these specifications, the population density of 1911 has a positiveand statistically significant correlation with later population densities, evenwhen controlling for geographic (ruggedness and rainfall6) or institutionalfactors – such as being located in the homelands. And when we regress the2011 population density on the 1996 population density, while including allcontrols, 1911 population density still matters independently (albeit with asmaller coefficient). Populations clearly persisted over very long periods.
In 1996, population densities are still strongly determined by whetherdistricts overlapped with the areas that were (at that point) former apartheidhomelands (see columns 4 and 5). What is striking, however, is the economicand statistical insignificance of the homeland coefficient by 2011 (columns 6to 9). While the homeland border still helps to explain settlement in 1996 –only 10 years after restrictions on movement were lifted in 1986 – the rela-tionship disappears another 15 years later, as migration away from formerhomelands accelerated. With new institutions and freedom of movement wenotice that the relatively recent past – apartheid -era policies – exerts lessinfluence on current settlement decisions than earlier determinants. Thissuggests one mechanism to mitigate the effects institutional shocks. We willreturn to a discussion of migration below. By contrast, patterns from themore distant past (1911) still continue to reflect in settlement patterns, sothat agglomeration leads to long-run persistence in populations.
5.2 Reversal of fortunes
Given the persistence of populations, one might expect a historical persis-tence of local welfare, in much the same way that Maloney and Caicedo(2016) do for Latin America. Our results complicate this assertion. We as-sume that densely populated areas before the imposition of the 1913 LandAct were wealthy regions, and show that these are areas of high unemploy-ment today, and – in the case of former homelands – areas where night lightsluminosity is lower than the rest of the country. The conflation of historicalpopulation densities with initial wealth is an assumption made by both Ace-moglu, et al. (2002) and Maloney and Caicedo (2016). Our evidence doessupport this assumption before white settlement (but after the mfecane):densely populated areas were also regions that were highly suitable to sus-tain food security and provide physical protection for populations. Someof these early densely-populated regions have been postulated to emerge as
6We do not control for soil suitability, since the variable is highly correlated with rainfalland terrain ruggedness, and introduces substantial multicollinearity. See table 1
20
communities with vibrant subsistence agricultural sectors by the end of thenineteenth century (Bundy 1979).
Yet population density may be a poor proxy for wealth in moderneconomies. Figure 3 (a) shows the spatial distribution of the 2011 broadunemployment rate by 1911 district demarcations. The geographic spreadof modern day unemployment corresponds remarkably closely to populationdensity in the early 19th and 20th centuries, indicating that former wealthyregions have become enclaves of poverty. These regions overlap strongly withthe former apartheid homelands, so that an institutional explanation maybe responsible for this reversal. Furthermore, figure 3 (b) shows that theseareas – especially in the south – remain largely under-electrified. Instead,economic well-being, as represented by night lights luminosity, is more pro-nounced in urban regions that agglomerated around mineral deposits andports in ‘white South Africa’. Night lights are therefore negatively relatedto early population density in former homelands, and positively in areasbeyond that.
Table 3 presents our regression results. While 1911 settlement patternscorrelate strongly with 1996 and 2011 unemployment and night lights, fullerspecifications (columns 8 and 12) show that more recent changes can ac-count for this persistence. We therefore focus primarily on the role of thehomelands in determining modern fortunes. In contrast to the insignificanceof the coefficient on homelands when measuring population persistence (inTable 2), it is large and statistically significant in all 10 specifications intable 3. Its sign also follows expectations: unemployment remains higherin the former homelands compared to the rest of the country (columns 1,2and 6-8), and lights are less bright (columns 3-4 and 9-12). Controlling forgeography does not change the core results, so that the fundamentals thatwere important for welfare in the distant past do not matter for the core ar-gument. Instead, the institutional changes brought about by apartheid haveplayed a defining role in reversing fortunes. Black South Africans living informer homeland areas are poorer today than black South Africans livingoutside those regions because of an institutional shock.
Twentieth-century institutions, rather than geography, therefore explainmost of the reversal of fortune we find, supporting the findings of Acemoglu,et al. (2002). The challenge, of course, is to identify which factors were re-sponsible for this reversal. This is no easy task. Acemoglu, et al. (2002,p. 1262) distinguish between institutions of private property (also called in-clusive institutions) and extractive institutions. The former are institutionsthat ‘provide secure property rights, so that those with productive opportu-nities expect to receive returns from their investments, and are encouragedto undertake such investments’. One condition of such property rights isthat they cover a broad cross section of society: ‘A society in which a verysmall fraction of the population, for example, a class of landowners, holdsall the wealth and political power may not be the ideal environment for
21
Fig
ure
3:
(a)
2011
Bro
adU
nem
plo
ym
ent
Rate
(in
clu
din
gd
isco
ura
ged
wor
kers
).S
ourc
edfr
om20
11ce
nsu
sd
ata.
Map
ped
on191
1d
istr
ict
bou
nd
ari
esu
sin
gae
real
wei
ghti
ng.
(b)
log(
2011
Nig
ht
Lig
hts
Lu
min
osit
y)
sou
rced
from
the
Nat
ion
alO
cean
ican
dA
tmosp
her
icA
dm
inis
trat
ion
.
22
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
Un1996
Un1996
Lig
hts
96
Lig
hts
96
Un2011
Un2011
Un2011
Un2011
Lig
hts
2011
Lig
hts
2011
Lig
hts
2011
Lig
hts
2011
Pop1911
0.0
63***
0.0
65***
0.6
78***
0.5
11***
0.0
30**
0.0
18
0.0
42**
0.0
25
0.6
59***
0.5
35***
-0.0
24
0.0
63
(0.0
21)
(0.0
24)
(0.1
15)
(0.1
12)
(0.0
13)
(0.0
15)
(0.0
20)
(0.0
17)
(0.1
30)
(0.1
29)
(0.1
56)
(0.1
49)
Hom
eland
0.5
22***
0.4
66***
-1.1
73***
-0.8
81***
0.2
69***
0.2
27***
0.2
28***
0.1
38***
-2.4
02***
-2.0
25***
-2.0
39***
-1.5
63***
(0.0
67)
(0.0
65)
(0.3
58)
(0.3
05)
(0.0
42)
(0.0
41)
(0.0
41)
(0.0
38)
(0.4
04)
(0.3
54)
(0.3
21)
(0.3
27)
Pop2011
-0.0
29*
-0.0
06
0.6
78***
0.5
59***
(0.0
16)
(0.0
14)
(0.1
25)
(0.1
22)
Net
Mig
11
-0.0
09***
0.0
50***
(0.0
01)
(0.0
13)
Rugged
0.0
07***
-0.0
49***
0.0
04***
0.0
04***
0.0
03***
-0.0
56***
-0.0
53***
-0.0
45***
(0.0
02)
(0.0
07)
(0.0
01)
(0.0
01)
(0.0
01)
(0.0
09)
(0.0
08)
(0.0
08)
Rain
-0.0
00**
0.0
05***
-0.0
00
0.0
00
0.0
00
0.0
04***
0.0
03***
0.0
03***
(0.0
00)
(0.0
01)
(0.0
00)
(0.0
00)
(0.0
00)
(0.0
01)
(0.0
01)
(0.0
01)
Const
ant
-0.9
72***
-0.9
19***
-0.7
11***
-2.2
11***
-0.8
37***
-0.8
97***
-0.8
64***
-0.8
89***
-0.8
37***
-2.0
81***
-2.8
40***
-2.7
07***
(0.0
37)
(0.0
94)
(0.2
01)
(0.4
42)
(0.0
24)
(0.0
59)
(0.0
61)
(0.0
54)
(0.2
27)
(0.5
12)
(0.4
85)
(0.4
61)
R-s
quare
d0.5
48
0.6
11
0.2
06
0.4
69
0.4
41
0.5
08
0.5
20
0.6
35
0.2
21
0.4
52
0.5
52
0.6
00
N138.0
00
138.0
00
138.0
00
138.0
00
138.0
00
138.0
00
138.0
00
138.0
00
138.0
00
138.0
00
138.0
00
138.0
00
F81.6
83
52.1
45
17.4
89
29.3
96
53.1
48
34.2
96
28.6
06
38.0
51
19.1
28
27.3
88
32.5
43
32.8
06
Tab
le3:
Rev
ersa
lsof
fort
un
e:19
thto
earl
y20
thce
ntu
ry
NO
TE
S:
*p<
0.1
,**
p<
0.0
5,
***
p<
0.0
1.
OL
Sre
gre
ssio
ns
usi
ng
vari
ous
inte
gra
ted
data
sourc
es.
(1)Pop
1911,Pop
1996
andPop
2011
are
logged
bla
ckp
opula
tion
den
siti
esfr
om
the
resp
ecti
ve
censu
sdata
sets
;(2
)NetM
ig11
isin
ver
sehyp
erb
olic
sin
transf
orm
ati
on
of
the
num
ber
of
net
mig
rants
into
the
dis
tric
tin
the
10
yea
rspri
or
toth
e2011
censu
s;(3
)Unem
1996
andUnem
2011
are
the
logged
bro
ad
unem
plo
ym
ent
rate
s(i
ncl
udin
gdis
coura
ged
work
ers)
der
ived
from
censu
sdata
;(4
)Light1
996
and
Light2
011
are
logged
lights
lum
inosi
tyfigure
sfr
om
the
Nati
onal
Oce
anic
and
Atm
osp
her
icA
dm
inis
trati
on;
(5)Rain
repre
sents
long-r
un
pre
cipit
ati
on
level
s(W
illm
ott
and
Mats
uura
2012);
(6)Rugged
isth
ein
dex
of
terr
ain
(Nunn
and
Puga
2012);
(7)Soil
isa
calo
ric
suit
abilit
yin
dex
(Galo
rand
Oza
ka2016)
(8)Hom
eland
isth
epro
port
ion
of
the
dis
tric
tth
at
was
loca
ted
inanapartheid
hom
eland.
23
investment, even if the property rights of this elite are secure’ (Acemoglu,Johnson, and Robinson 2002, p. 1262). This is an example of extractiveinstitutions.
Such extractive institutions are what black South Africans residing in‘white areas’ were subjected to. Several repressive and discriminatory poli-cies against blacks were imposed in ‘white South Africa’: already by 1911,on the eve of the enactment of the 1913 Land Act, the seeds of racial dis-crimination had been sown. A battery of legislation was in place to regulatethe labour market, with the largest effects targeted at black inhabitants indensely populated regions (including the 1911 Mines and Works Act whichenforced the colour bar and job reservation, as well as the 1908 hut taxesthat intended to force rural inhabitants into the mainstream labour market).
As the South African economy expanded during the mid-twentieth cen-tury, growing at roughly 4% per year between 1935 and 1970, black wages in‘white South Africa’ – despite the many discriminatory apartheid policies –began to increase (Mariotti 2012). By the 1970s and 80s, with rising politicaltension and a domestic and international economic crisis, repressive labourlaws were relaxed or abolished. Rapid increases in black wages followed, cou-pled with rising unemployment. Mechanisation, especially on farms and inmanufacturing, set in to contribute to poor labour market conditions. Blackmigration to the cities increased rapidly, notably after the abolition of influxcontrols in 1986, forcing the apartheid government to review and ultimatelywithdraw the system of separate development. When South Africa held itsfirst democratic elections in 1994, black South Africans could live and ownproperty anywhere within the borders of the former ‘white South Africa’.
These extractive institutions of twentieth-century ‘white South Africa’should, however, be compared to the institutions that evolved in the regionsthat would become the homelands. The 1913 Land Act, while limiting landownership to blacks in white areas, also secured the system of traditionalrule in what was known as the ‘native areas’. The extensions to the LandAct and the more extensive homelands policies established the system oftraditional land rights and chiefly power (Delius 2008). Much as they haddone before European arrival, chiefs held the prerogative over organisingland occupation. There was thus no institutional reversal after Europeanarrival, as Acemoglu, et al. (2002) predicts:
European colonialism led to an institutional reversal, in the sensethat regions that were relatively prosperous before the arrival orEuropeans were more likely to end up with extractive institutionsunder European rule than previously poor areas.
No significant institutional reversal – represented by changes in propertyrights – occurred in South Africa’s former homelands after the onset ofdemocracy. Instead, what caused a reversal in fortunes was an institutional
24
setting with differential extractive institutions: the large majority of blackSouth Africans were endowed with poor economic and political rights in both‘white South Africa’ and the homelands. The Land Acts and homelandspolicies locked-in the pre-colonial institutions of collective ownership andundemocratic rule, much like the pre-colonial institutions of Basutoland(now Lesotho) and Swaziland (now eSwatini) were locked in at cessationand independence.
These homelands (and Lesotho and eSwatini) were some of the mostdeprived regions of southern Africa at the coming of democracy. Today,25 years later, they remain the most poor.7 As Noble and Wright (2013,p. 197) show, the ‘former homelands experienced high levels of poverty in theimmediate post-apartheid era, and ... this continued to be the case at thetime of the Census in 2001, and again 6 years later at the time of the 2007Community Survey’. This is because many of the extractive institutionshave remained in one form or another. In fact, Burger (2018, p. 220) arguesthat in many cases, these institutions have become even more extractive:‘legislation passed by the ANC-government [has] strengthened the powers oftraditional chiefs and continue to undermine the tenure rights of the popu-lation’. While there are many historical reasons for the low level of develop-ment in these regions and countries, including overpopulation, erosion andaccess to markets, the extractive institutions that persist, an amalgamationof the pre-colonial institutions and apartheid -era interventions, must be animportant root cause.
More than a third of black South Africans still live in the former home-lands - a remarkable persistence over more than two centuries. These SouthAfricans today, in contrast to their ancestors two centuries ago, are thepoorest and most destitute. Geography explains why they inhabited thoseregions two centuries ago; institutions (and their persistence into the demo-cratic era) why their fortunes have reversed.
5.3 The mitigating effect of migration
Because the extractive institutions of insecure private property and undemo-cratic political processes have remained in the former homelands regions, it issomewhat of a surprise to find that the regional disadvantage declined in thedemocratic era. As table 3 shows, the institutions of apartheid ’s homelandsexhibit a declining influence on unemployment – the negative coefficients aresmaller in 2011 specifications (columns 5 and 6) compared to those in 1996(columns 1 and 2). Early settlement patterns and institutions created duringthe 20th century are becoming less important in explaining unemployment.
The reason for this is the abolition of influx controls in 1986 that al-lowed black South Africans to settle permanently outside the homelands.
7The 2018 World Development Indicators ranks eSwatini 104th of 178 countries ongross domestic product per capita. Lesotho ranks 149th.
25
Migration from areas of extractive to inclusive institutions is one way forindividuals to escape their historical legacies. In fact, one of the constraintsof Acemoglu, et al. (2002) is that it neglects to address the limits to interna-tional migration that prevent the inhabitants of those now living in regionswith extractive institutions to migrate to regions with inclusive institutions.These limitations indeed held true for South Africa before democracy, wheninflux control and other restrictions prevented black migrants from settlingpermanently in ‘white South Africa’. When these restrictions were relaxedor abolished, black South Africans, as Tiebout (1956) so eloquently phrasedit, ‘voted with their feet’.
Figure 3 (c) maps the most recent net migration numbers for the districtsunder consideration.8 Even though significant numbers of South Africansmove from urban to other urban areas (von Fintel and Moses 2017), out-migration to other regions is concentrated in the former homelands regions.The exceptions are the homelands located close to urban agglomerationsnear Gauteng. Regions with relatively low unemployment and high nightlights luminosity have positive net migration numbers. These flows reflectthe movement from former homelands to areas with more inclusive institu-tions and better economic opportunities.
Our results confirm that migration mitigates the effect of past insti-tutions. The ‘homeland effect’ diminishes if we control for net migration(in columns 8 and 12 of table 3). Institutional barriers to migration wereremoved, while institutions of communal land rights remained in place informer homelands. The result has been large rates of urbanisation andmigration. Unemployment was partially transferred from sending regions(mainly in the former homelands) to receiving regions (mainly in metropoli-tan areas), reducing the influence of past institutions on this outcome9; thesame institutional changes and migration resulted in relative reductions inluminosity in the former compared to the latter areas.
Although migration alleviates some of the unemployment in the formerhomelands (and, of course, improves the lives of the migrants themselves), itcould deepen the disparity between the regions with extractive institutionsand those with inclusive institutions, in other words, those within and thoseoutside the former homelands. This is exactly what has happened. Night
8The number of respondents in the 2011 census who report leaving a particular districtfor another in the preceding decade, is subtracted from the number of respondents thatmove into that district from elsewhere. Figures are transformed by the inverse hyperbolicsine function – this approach is similar to a usual log transformation, but accommodatesnegative net migration values. The variable correlates strongly with reported lifetimemovement from respondents’ province of birth to another.
9The negative sign of the coefficient on net migration in column 8 shows that individualsmigrate to areas with low unemployment. The line of causality reflected here is thereforenot from migration to unemployment. However, the intention is to factor out the largerole of out-migration from the coefficient on homelands. For night lights in column 11 theresult is more intuitive – in-migrants may contribute to growing luminosity.
26
lights in the former homelands areas are becoming dimmer, while remainingbright in other areas that were densely settled in 1911 (compare columns 3-4and 9-10, showing homelands disadvantages in 1996 and 2011 respectively).This suggests that while individual outcomes – such as unemployment –are becoming increasingly de-linked from past geographies and institutions,agglomerations in overall economic activity tend to persist.
6 ConclusionIn this paper we empirically investigate this persistence versus reversal de-bate using the case of South Africa, a country, we argue, that offers anexceptional opportunity to test the role of institutions without the con-founding effects of cultural and genetic diversity. Our results allow us tomake the following conclusions.
Pre-colonial settlement was not, in the case of South Africa, in a sta-ble Malthusian equilibrium. Disrupted by resource constraints at the be-ginning of the nineteenth century, perhaps the result of sudden climaticchanges, the country entered a period of intense indigenous warfare and mi-gration by European settlers into areas formerly inhabited by indigenouspeople. Subsequently, Bantu-speaking peoples were locked into the highrainfall, but rugged, inhospitable regions of the country. The newly settledareas, later to be known as ‘white areas’, developed rapidly as a result ofthe institutions that were established to benefit whites. Natural resourceslike diamonds and gold helped, as did access to temporary migrant labourfrom across southern Africa – the descendants of those affected most by theearly nineteenth-century wars. For the few black inhabitants who were al-lowed to work and reside in ‘white South Africa’ on a temporary basis underapartheid, the institutions designed for whites would ultimately give thema chance to reverse their fortunes vis-a-vis their black counterparts in thehomelands. This divergence in wealth could only happen because limits onthe freedom of movement of black inhabitants restricting most of them tothe homelands where pre-colonial indigenous land tenure and undemocraticpolitical institutions persisted, often with support of the apartheid-era gov-ernments. After the mid-1980s, when the legislative restrictions on blackmigration were lifted, migration to the urban centres of Gauteng and theWestern Cape became the most successful poverty alleviation strategy forresidents of the former homelands. Migration has enabled some to crossthe divide between the still extractive (and in some cases even more so)institutions of the former homelands and the now inclusive institutions ofdemocratic South Africa, thus to some extent undoing the great divergencethat has happened as a consequence.
What do these findings tell us about the debate over the roles of geogra-phy and institutions? Geography may indeed be important in determininghistorical settlement patterns: in agrarian societies, populations tend to set-
27
tle in regions with suitable soils, topographical security and high rainfall.But even here one must be cautious in assuming a stable Malthusian equi-librium in pre-colonial times: a sudden climate shock could shift the spatialequilibrium, with long-term consequences. In short: geography is not de-terministic. As the history of South Africa demonstrates, settlement wasnot static in the 1000 years before Europeans arrived in the South Africaninterior; the choice of start-date matters when identifying the degree of per-sistence of settlement patterns. Neither do institutions inevitably result ina permanent reversal of fortune. The colonial technologies and institutionsdid indeed help to impoverish black South Africans, but the effects was con-tingent on the type of institutions in both the ‘white areas’ and the home-lands. Put another way, had institutions been different, the colonisation ofthe eastern half of South Africa during the nineteenth century might nothave resulted in either a persistence of settlement or a reversal of fortunefor black South Africans. If the 1910 unification had included provisionsthat allowed black residents to vote, as was the case in the Cape Colony be-fore, or if it had allowed free movement of all people, South Africa’s spatialgeography and wealth distribution might be very different today.
The wealth of black South Africans within the borders of the former‘white South Africa’ and that of their counterparts in the former homelandshave diverged since the start of democracy. Again, there is nothing deter-ministic about this outcome: had the political processes that created thevarious acts pertaining to traditional land – notably the Ingonyama TrustAct of 1994 that vested ownership of 2.8 million hectares of KwaZulu-Natalin a sole trustee, the Zulu King Goodwill Zwelethini – been different, it islikely that these regions would have developed much more rapidly. Instead,open borders now allow those who live in regions with extractive institutionsto vote with their feet.
Our case study of South Africa made it clear that geography and insti-tutions interact in unpredictable ways. We argue that previous studies havebeen too inclined to emphasise one of these mechanisms at the expense ofthe other. Our study showed that historical accidents (like climate shocksor institutional idiosyncrasies) can cause suboptimal equilibria to persist fora long time. The good news of this study is that future South Africa is notnecessarily a prisoner to these past equilibria. Addressing the institutionalweaknesses of the former homelands is key to alleviating the poverty in thoseregions where a third of South Africans still reside.
28
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