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The Rise of Income Inequality in Guyana.

Imagine a ten-mile race in which contestants have different starting
lines based on parental education, income, and wealth. The economically
privileged athletes start several hundred yards ahead of the
disadvantaged runners. Each contestant begins with ten one-pound leg
weights. The race begins, and the advantaged competitors pull ahead
quickly. At each half-mile mark, according to the rules, the first
twenty runners shed two pounds of weights while those in the last half
of the field take on two additional pounds. After several miles, lead
racers have no weights, while the slower runners carry twenty
additional pounds. By midrace, an alarming gap has opened up in the
field, and by the finish line, the last half of the field finishes more
than two miles behind the winners.
- Chuck Collins 2013, The Wealthy Kids Are All Right


Guyana has undergone a dramatic economic and political transition since the onset of its Economic Recovery Program in 1989. The return of democracy and the end of the socialist experiment present Guyana as an exciting case to study distributional dynamics. Moreover, its history of colonialism and indentureship extend the distributional conflict beyond class into ethnic based contestation. The epigraph above best sums up the evolution of income inequality in Guyana between 1960-2013. Like the ten-mile race, the starting lines of income shares in 1960 were wholly unequal, at midrace (1998), the bottom 50% lost half of their mean income and at the finish line, the top 10% owns 41% of household income, while in 2013 the bottom 50% realizes a mere 12.42%.

Three questions motivate this research. How has income inequality evolved over the period? What are the driving forces that explain the dynamics observed? And finally, what is the ethnic composition of the income distribution?

The first finding is that income inequality has increased over the past decades, particularly during the reform period of the 1990s. Though the article computes Gini coefficients, it explains that these are less sensitive to changes at the tails of the income distribution. Unlike the Gini, the Palma and P90/P10 ratios demonstrate how the richest 10% is diverging from the poorest 40% and 10% respectively. This finding provides empirical support to opinions in the popular press (Gampat 2010) and assertions in academia (Khemraj 2013) about the rise of inequality, in spite of official Gini statistics indicating a decline in income disparities (G.O.G 2011). The decline in the Gini illustrates the second principal finding, that the upper middle class gained the greatest income share during the 1990s. The third central discovery demonstrates the power of entrenched wealth - the income share of the top 10% has remained unchanged over the 1960-2013 period. This is a striking finding given that Guyana has undertaken a socialist experiment, suffered dramatic economic collapse and political and economic changes during the reform period. This is a shining example of how money can purchase influence and insurance against political and economic shocks. The final determination of the article is that the bottom half of the income distribution has fallen behind the top 50%. Guyana is a country divided.

The article uses historical analyses to show that the driving forces behind these inequality dynamics lie in the IMF structural adjustment program that officially started in 1989. The major beneficiaries were the supporters of the newly elected government in 1992. The shock therapy approach to reform led to price inflation for agricultural produce, which disproportionally benefitted Indo-Guyanese, and rapid fire privatization also advantaged government supporters. Further, fiscal retrenchment adversely affected public servants who are primarily Afro-Guyanese. The reform period increased ethnic inequality. Finally, the article finds that a specific form of the colonial construct of ethnic inequality remains unchanged, that is, Portuguese still occupy top income status.

The only other study that is close to this work is Boyd (1989) but there are major limitations with this work. First, it is not a time series analysis; it only calculates income shares for 1988. Second, Boyd's estimates are based on a number of heroic assumptions: 1. He assumes that household income is understated by 50%, 2. Corporate sector appropriates 25% of government outlay, and 3. That the relative income shares in Sri Lanka (1969-70) would be a useful proxy for Guyana. He concludes that the top 20% owns 43.4% of household income in 1989 and, as Thomas (1993) argues, these estimates are speculative at best. While Gafar (2004) attempts to study inequality in Guyana, he depends solely on the Gini coefficient and, unlike this article, he uses consumption inequality as a proxy measure for income inequality.

Gafar's use of consumption inequality as a proxy indicates the paucity of distributional income statistics. This article overcomes this limitation with the use of the Global Income and Consumption Project (GCIP) database that includes consumption and income datasets, which span 133 countries between 1960-2013. The GCIP collects per capita survey data from the World Income Inequality Database, Luxembourg Income Study, country statistical offices, UN agencies, academic studies and the World Bank's Povcalnet database. Since household surveys were irregularly undertaken prior to the 1980s, GCIP constructs synthetic consumption and income profiles and through interpolation and extrapolation generates estimates for non-survey years. This highlights the first limitation with the dataset employed in this study. However, historical analyses broadly support the data's principal findings for the period prior to the 1980s. Moreover, in 1992 and 2006 Guyana had undertaken a Household Income and Expenditure Survey, in 1999 a Living Conditions Survey, and Poverty Surveys in 1992,1999, and 2006. These surveys either collect income or consumption data or both, and are part of the World Bank's Povcalnet database and therefore, form the basis of the estimated income and consumption profiles. For full details on methodology and the dataset see Lahoti, Jayadev and Reddy (2016) and gcip.info respectively.

According to INCSR (2014) Guyana is considered a cocaine transit country and drug traffickers can easily rise to top income status and are unlikely to be represented in household surveys. But the under sampling of top incomes, whether these come from legal or illegal sources are known shortcomings of all household surveys (Milanovic 2016 and Piketty 2014). At best, estimates of top incomes based on survey data are lower bound estimates. The standard approach to overcome this limitation is to integrate tax data on top incomes with survey data, but in Guyana income tax data for the very top is likely to be even more under reported, given the large size of its underground economy (Thomas, Jourdain, and Pasha 2011). It follows that the top 10%'s income share of 41% in 2013 underestimates top incomes that come from legitimate entrepreneurs, informal economic activities and drug traffickers. Notwithstanding this limitation, it is striking that the average income of the richest 10% is 4.1 times larger than the average income of the entire population--comparable to Russia and the USA today (Novokmet, Piketty, and Zucman 2017).

This article is part of a broader project that attempts to reintroduce the study of income inequality into the wider Caribbean scholarship. This line of research was commonplace in the older tradition of Caribbean political economy associated with the New World Group, but has fallen out of fashion since the late 1970s. New data and the global interest in the distribution of income present a re-opening for this critical tradition. This work builds on Constantine (2015) who attempts to overcome the limitations in Gafar (2004) by focusing exclusively on the rate of change of the functional income distribution--unlike Gafar, Constantine concludes that inequality has increased in Guyana since 1976. With new data, this work adds power to Constantine's claim. Two noteworthy pieces on income inequality in Jamaica are Handa and King (1997) and King and Handa (2001). They are empirically driven and both demonstrate the role of structural adjustments in determining the overall income distribution. This type of work has already been extended to other Caribbean countries with a focus on top incomes (Constantine 2017a) and theoretical work has been undertaken to determine the economic implications of redistribution (Constantine 2017b). Finally, ongoing research is fast apace to identify the role(s) of remittances in determining the functional income distribution in small open economies in the Caribbean.

The remainder of the article is organized as follows. Section 2 empirically demonstrates the evolution ot inequality and section 3 provides historical analyses to account for the patterns observed. Finally, section 4 concludes.

EVOLUTION OF INEQUALITY IN GUYANA

Patterns of Change in Mean Income by Decile

Figure 1 illustrates the evolution of mean income in D1-D10 between 1960-2013. To provide a useful discussion I divide this period into five parts: Period A (1960-76), Period B (1977-88), Period C (1989-97), Period D (1998-2000) and Period E (2001-present). Also, I divide the ten deciles into three groups: the bottom 50% (D1-D5), the middle class (D6-D9) (this definition follows Cornia 2012) and the top 10% (D10). At first glance, there appears to be remarkable similarity in the pattern of change across all groups. For instance, in Period A, all income groups experienced marked improvements in mean income that peaked in 1976. Also, the middle class and the top 10% appear fairly homogenous in terms of pattern of growth in mean income. But there are also important heterogeneities--in the bottom 50%, mean income in D1 and D2 or the poorest 20% grew slower than the remainder of the bottom 50%. In a cruel twist of fate, the gains recorded in Period A were reversed for all groups in the following period; thus, we label Period B as the great deterioration. In the bottom 50%, the deterioration in mean income was particularly pronounced for D3-D5, with only mild reductions for the bottom 20%. The top 10% and the middle class, with the exception of D6, fared better than the bottom 50% during the great deterioration, but the decline in their mean incomes is unmistakable. Given the growth in mean income and the great deterioration, one can argue without referring to aggregate measures of inequality that the income share in each decile remained fairly stable over Periods A and B. In other words, a preliminary conclusion can be that the level of inequality has remained unchanged over Periods A and B.

Now consider Period C, which records growth in mean income for all groups. Unlike the middle class, the bottom 50%, especially D3-D5, recorded strong growth in mean income. Interestingly, the top 10% and the bottom 20% of the income distribution perform similarly, with only meagre growth in mean incomes. Though Period D is a short period, it is as significant as the period of the great deterioration. The bottom 50% lost half of their mean income since 1998, with D2 and D3 recording the largest losses. Unlike the middle class, the top 10% also suffered major losses in mean income. In fact, the middle class actually recorded growth in mean income in some cases. Collectively, Periods C and D mark the reshuffling of the income distribution in Guyana. But not on account of robust growth and a fairer distribution of income, rather, due to the collapse in mean income for the bottom 50%.

The last period considers the post 2001 years, and the first thing to note is that the mean income for the bottom 50% in 2013 is still below its 1976 peak. In contrast, the middle class and the top 10% have fully recovered and their mean incomes in 2013 are well above their peak level. Thus far, the story about the top 10% has not been very exciting, especially since the great deterioration, but post 2001 they have returned with a vengeance. In short, Period E entrenches the reshuffled income shares in Periods C and D.

The unique patterns of change in each decile give rise to a number of important questions. First, what explains the massive decline in mean incomes for the bottom 50%? Second, what accounts for the rapid rise of the middle class and the top 10% post 2001? Third, what explains the initial distribution of income in 1960? Finally, since Guyana is a plural society with Afro and Indo-Guyanese as the two major ethnic groups and Chinese, Amerindians and Portuguese as minorities--it is of great political interest to determine what is the ethnic distribution across the income groups. The article now moves on from the patterns of change in mean incomes to discuss the evolution of income shares held by the middle class and the top decile.

Income Share by Decile

Figure 2 depicts the evolution of income shares held by D7-D10 between 1960-2013 and the income share of each decile in 2013. The focus on the top 10% and the upper middle class is deliberate--the latter and the former have demonstrated clear gains in their mean incomes in Figure 1. Consistent with the patterns of change in Periods A and B, income shares in D7-D10 have remained the same between 1960-89--this confirms that inequality has remained unchanged over this period. Figure 2 also demonstrates that the major beneficiary from the reshuffling of the income distribution in Periods C and D is the upper middle class--D7-D9. During this period the top 10% lost income share that was appropriated by the upper middle class. Curiously, post 2001 the reshuffling of the income distribution has stabilized and the top 10% has recovered its income share.

Though the middle class now own more income share than in any other time since 1960, they are still far below the top 10%. In 2013, the latter owned 41% of household income, while D9 owned a mere 18%! However, the middle class as a collective owns 46% of household income but this is only a few percentage points more than the top 10%. Consider the other extreme--the poorest 10% or D1 owned a meagre 0.4% of household income in 2013, while, as a whole, the bottom 50% owned only 12.42%.

The income share held by deciles best depict the stark inequality that exists between the top 10% and the rest of the income distribution. It also leads to additional questions. What is the ethnic composition of the top 10% and how were they able to defend their income share over five decades, even as Guyana had undertaken radical changes in its political system? Also, what can explain the rapid gain in income share for the upper middle class?

Patterns of Change in Mean Income and Consumption by Decile

The article imposes the evolution of mean consumption on Figure 1 to analyse savings pattern by decile and interrogate the nexus between poverty (as measured by consumption) and inequality. This is now represented in Figure 3, which illustrates that the middle class and the top 10% are savers since 1960. The same holds for the bottom 50% but only up to 1998, after which the bottom 40% becomes dissavers. It is important to emphasize here that dissavings emerge, not on account of irresponsible consumption or spending, but largely because of the collapse in mean income in Period D. Decile 5 manages to avoid becoming a dissaver and only consumes all of its income since 1998. The obvious question is what supports household consumption for the bottom 40% of the income distribution?

Unlike income, mean consumption across all income groups has a homogenous pattern of evolution over the entire time period. The persistent growth in mean consumption for the poorest 50% is consistent with the reduction in extreme and moderate poverty in Guyana (G.O.G 2011). This positive image caused Gafar (2004) to declare that income inequality has declined since 1992. He used the consumption Gini as a proxy measure for income inequality, noting that income data is either unavailable or unreliable in Guyana. But Figure 3 demonstrates the major limitation with using consumption inequality as a proxy measure for income inequality. Also, Guyana is an important remittance recipient country and remittance inflows are likely to support consumption for the bottom 40% (Roberts 2009; Orozco 2004; Singh 2008), which produce lower estimates of consumption inequality but mask the collapse in mean income for the bottom half of the income distribution.

What does rising inequality and reductions in poverty indicate about the nexus between poverty and inequality in Guyana? On one hand, Dollar and Kraay (2002) argue that growth rather than lower inequality is the most important factor for poverty reduction. They claim that income of the bottom quintile increases as average income increases - this supports the trickle down view of reducing poverty. But they failed to identify the key mechanisms than ensure income trickles down to the lowest quintile. On the other hand, Dagdeviran, Hoeven, and Weeks (2001) contend that redistribution, either of current income or the growth increment of income, is more effective in reducing poverty for a majority of countries than growth alone.

At first glance, the evidence in Guyana (higher inequality and lower poverty) supports Dollar and Kraay (2002). But a careful examination begs the question: what supports the growth in consumption for the bottom 40% since their mean consumption exceeds their mean income? If the answer lies in remittance inflow, and this is likely in the Guyana case, then in the absence of the generosity of others, lower inequality might be necessary for poverty reduction. Further, if remittance inflow indeed supports consumption for the poorest 40%, then government poverty reduction strategies have been ineffective and this is a serious indictment against both government and the World Bank, since poverty reduction falls under their portfolio. Also, the fact that mean incomes are rising for the middle class and the top 10%, while the bottom 40% cannot support their consumption pattern from their own income, pokes a hole in the trickle-down argument. This article takes the view that growth is an essential ingredient in the fight against poverty. But distribution is also key for the growth process itself (Ostry, Berg, and Tsangarides (2014) and Cingano (2014); therefore, distribution and poverty reduction go hand in hand.

Aggregate Measures of Inequality

Palma (2011) and Palma (2014) explain that the Gini coefficient is more sensitive to changes in the middle of the income distribution (D6-D9) and less so to the tails--the top 10% and the bottom 40%. Further, Palma empirically demonstrates that the middle and upper middle classes across space and time tend to maintain their income share. He explains that the middle class manages to acquire and defend their property rights and, by extension, their position in the income distribution. Given this empirical regularity, Palma argues that our interest in inequality must focus on what happens at the tail of the income distribution--this necessarily means that researchers and policymakers must move beyond Gini coefficients. Palma (2011) proposes a new measure of inequality, which has become known as the Palma ratio. Unlike the Gini coefficient, the Palma ratio measures the changes in the top 10% as a ratio of the bottom 40%. An intuitively similar measure of inequality is known as the P90/P10 ratio, it measures the changes in the top 10% as a ratio of the bottom 10%. In the analysis that follows I employ all three summary measures of inequality.

Following Palma (2011) and Palma (2014) I argue that the reduction of inequality as measured by the Gini coefficient in Figure 4, does not capture what really matters--the income share of the rich. Figure 4 depicts a dramatic decline in the Gini coefficient during Period D, which coincides with the reshuffling of the income distribution in favour of the middle class. Curiously, the Gini coefficient escalated almost immediately after it declined and having since stabilized, it indicates only a marginal decline in inequality. But this is consistent with the evidence shown in Figure 2, which depicts only marginal gains in the income share of the upper middle class.

Given Palma's thesis of a strong middle class and stable income shares in the middle of the income distribution, it is tempting to conclude that Guyana's middle class successfully defended their property rights and negotiated for a bigger share of the pie--indicating an increase in their political power. But the rise of the middle was short lived, and unlikely to be the result of strong middle class negotiation. The rise of Guyana's middle in the short space of Period D has to be explained by other factors than the traditional thesis of strong middle class power. Nonetheless, the article definitively concludes that the upper middle class has managed to appropriate a bigger share of the national pie since the early 1990s. But this fact hardly gets us closer to understanding inequality in Guyana.

Considering the ratio of the richest 10% in relation to the bottom 40%, a clear divergence is observed and thus, a dramatic rise of income inequality. This is summarized in the Palma ratio in Figure 4, which illustrates the enormous growth of inequality in Periods C and D--a far less optimistic image when compared to the Gini coefficient. The Palma ratio demonstrates that the top 10% of the income distribution in Guyana manages to appropriate greater income share at the expense of the bottom 40%--this is how the rich devours the poor. The rise of inequality is even more intense when one considers the top 10% in relation to the poorest of the poor--D1. This relationship is summarized in the P90/P10 ratio shown in

Figure 4. Based on this measure, the rise of inequality far exceeds that illustrated in the Palma ratio and it indicates that the richest 10% increase their income share even at the expense of the poor and the powerless. This story is diametrically opposed to the optimistic image summarized in the Gini coefficient and Gafar (2004). I conclude that income inequality has increased appreciably in Guyana.

Figure 4 also presents Palma and P90/P10 ratios for consumption. Based on the Palma ratio consumption inequality has declined, but there is a marked increase based on the P90/P10 ratio. This is in stark contrast to the consumption Gini calculated in Gafar (2004), where he argues that consumption inequality has declined.

For completeness, I compare Guyana's summary measures of inequality with Jamaica, Barbados, and Trinidad and Tobago, but on consideration of space I do not reproduce the graphs. Based on the Palma ratio, Jamaica has the highest level of income inequality in the group and Guyana has the dubious honor of being number two. However, the P90/P10 ratio indicates that Guyana has the highest level of income inequality. This means that Guyana's top 10% manages to squeeze its bottom 10% the hardest as compared to the top 10% in Jamaica, Barbados and Trinidad and Tobago. Using the Gini coefficient, Barbados and Jamaica have the most unequally distributed income within the group, this means that Guyana's middle class is performing relatively (albeit marginally) better.

What Determines the Evolution of Inequality?

External Shocks and Policy Failures

What are the key facts to be explained? First, how do we explain the reversal of fortune during the great deterioration? Second, what can explain the dramatic decline in mean incomes for the bottom 50% and third, the rise of the upper middle class? Finally, what is the ethnic composition of the income distribution?

Prior to the great deterioration (Period A), Guyana was governed by a coalition government that was staunchly pro-capitalist and opened to foreign investment (Premdas 1982) and Gafar (1996). The right wing coalition had an official policy of industrialization by invitation (tax concessions). Further, Premdas (1982) notes that Guyana benefitted from substantial foreign aid since the government was supported by the USA. These coupled with an external boom in the price of rice, bauxite, and sugar led to the growth in per capita income that peaked in 1976 (Gafar 2004), Gafar (1996) and Gafar (1998)). I argue that collectively these can explain why mean income grew for all income groups during Period A.

But how do we explain the reversal of fortune during the great deterioration? In 1968 the Finance Minister was ousted from government and the country soon took a socialist turn (Premdas 1982). Premdas notes that, between 1969-77 there was extensive capital flight, reduction in private and foreign investment, decline in US aid, nationalization of all major foreign owned firms, and migration. As noted in Gafar (1996), the Prime Minister declares the following (see Burnham 1974):
[...] We socialists hold that property is for the use and benefit of
the society and nation, and not for hoarding, profiteering, and
manipulation by private individuals for their own ends and benefits (p.
17) ... As we move to control land in the interest of the nation, we
will take control over all foreign trade-import and export... Our other
exports--bauxite, rice, and forestry products--are already handed by
public agencies. This pattern will be extended to all other products
(p. 19). ... There will be certain sub-sectors like public transport
and communications which must and will be owned and controlled
exclusively by the Government (p. 22). ... Notice was given since 1970
of our intention to miniaturize foreign owned banks and during 1975 to
bring an end to foreign banks (p. 25).


Gafar (1996) explains that a number of domestic policy failures were responsible for the great deterioration, in particular, a bloated public sector that reduced government efficiency. Thomas (1988) and Thomas (1982) highlight these domestic failures as follows: excessive money creation that led to monetary disequilibrium, excessive spending that built up domestic and external indebtedness, over valued exchange rates and import substitution industrialization strategies led to external deficits. In later work, Gafar (1998) argues that depressed commodity prices and declining terms of trade were also important explanatory factors for the great deterioration.

In summary, the great deterioration in mean incomes across the income distribution is due to adverse terms of trade and domestic policy failures that led to a dramatic economic downturn. This reversal of fortune negated the gains in Period A and explains why the overall income distribution as measured by income share has not changed over these decades (see Figure 2). This is a striking finding in light of the declaration of socialism.

Socialism-State Capitalism

How did socialism affect the overall income distribution? Thomas (1988) contends that, in practice, the socialist government can be better characterized as a capitalist state that sought to create its own domestic capitalist class. Thomas (1988) and Ishmael (1993) explain that the policy of nationalization led to a bureaucratic bourgeoisie that reinforced domestic capitalist relations. Moreover, nationalization was targeted at foreign rather than domestic capital per se (Thomas 1988). Thus, the Guyana socialist experiment was more an exercise in politics than re-distributional policy.

Thomas explains that, while co-operatives were a key pillar of the socialist agenda, many private enterprises were changed only in name to benefit from tax concessions and to acquire property. He notes that private enterprise even flourished during economic crises. Balance of payment crises led to import restrictions and acute shortages of key goods; this in turn increased prices and provided a lucrative pool of economic rents for the domestic entrepreneurial class (Gafar 1996). But Thomas and Gafar are not alone in their controversial claim; Chandisingh (1983) explains that some members of the bureaucratic bourgeoisie used state resources to transform themselves into traditional capitalists and even protected the interests of the local capitalist class.

Besides the evidence that the overall income distribution has not changed during the socialist period, there is other empirical support to the claim that Guyana was more state capitalist than socialist. Bishop, Davenport, and Flamm(1982) show that, since the late 1970s, the fishing industry was overwhelmingly a private sector venture, with only one state owned company--Guyana Fisheries Limited. The report demonstrates that in 1977 almost two-thirds of employment directly involved in agricultural production (excluding processing) was in the private sector and the remainder in publicly owned sugar estates. As it relates to forest products, the four largest private producers accounted for 75% of official exports in 1976, 78% in 1980 and 74% in 1981. Bishop, Davenport, and Flamm (1982) also highlighted the considerable importance of the private sector in areas such as professional services, commerce, retailing, transportation, hotels and other services. The central conclusion is that Guyana's experiment with socialism failed to alter the colonial origins of its income distribution. For further evidence on the distributional failures of the socialist period see Hintzen and Premdas (1982), these scholars contend that socialism failed to transfer resources to Afro-Guyanese--the political base of the socialist government.

IMF Austerity and Privatization

The reshuffling of the income distribution--the dramatic decline in mean incomes for the bottom 50% and the rise of the upper middle class--occurred during Guyana's Economic Recovery Program (ERP) that started in 1989 with the support of the IMF and World Bank Group. This article argues that the social degradation of high unemployment and inflation tax--consequences of the ERP--were the first attack on the bottom 50%.

The ERP entailed the following: a downsizing of the public service, elimination of all forms of price controls, 70% devaluation of the Guyana currency (Ely 1990) with a full pass through to retail prices (Syfox 1992), reductions in budget deficits, trade liberalization, privatizations, contractionary monetary policy, wage restraint, removal of subsidies and all the other key features of IMF structural adjustment programs (Gafar 1996; Gafar 1998; Gafar 2003; Gafar 2004; Syfox 1992; Bank 1993;Thomas 1993). There were caps on health and education expenditure (Rampersaud 1992), the elimination of price controls led to inflation of 101.5% in 1989, 61% in 1990 and 80%-90% in 1991, and the elimination of interest rate suppression increased lending rates to a remarkable 40% (Syfox 1992).

The principal effects are losses in real savings and earnings that disproportionally affected the bottom half of the income distribution. Novokmet, Piketty, and Zucman (2017) come to a similar conclusion fr; a sinilar finding--that Russia's big bang-shock therapy approach to reform led to hyper inflation, which wiped out the savings of the poor and can explain the massive collapse in the income share of its bottom 50%. The Guyana and Russia cases are consistent with EBRD's (2016) findings on the inequality dynamics in transition economies. The report finds that, for transition economies, income inequality increased during the early years of reform (the 1990s) primarily due to the shock therapy approach.

The second attack on Guyana's bottom 50% is associated with the dramatic decline in export performance for the period under consideration. Mining served as a temporary employer for laid off public servants and Ganga (2002) shows that (mining) exports declined at an annual rate of 4.8% between 1998 and 2001 and Constantine (2015) illustrates that profit rates were negative in the mining sector over the same period. I argue that this quick and dramatic downturn in economic performance is an important contributory factor to the enormous loss in mean income for the bottom 50%. The bottom half of Guyana's income distribution lost decades of employment security in the public sector since the ERP and their source of refuge--mining employment--was only short lived.

How did Guyana's upper middle class manage to gain income share in spite of massive social collapse? This article posits that privatization is the primary explanation for the rapid rise of the middle class and the stabilization of their income share since 2001. While privatization may produce higher income share for its beneficiaries, this process can only be undertaken once, which explains why the distribution of income has stabilized so quickly.

Syfox (1992) argues, quite controversially, that privatization began in 1982 though the government denied it--years before the ERP and while the government had its official policy of socialism. This point emphasizes the lack of transparency in the first phase of the privatization process and foreshadows the Privatization Policy Framework Paper-1993 (G.O.G 1993), which states that, prior to 1992, state assets were sold at giveaway prices with rampant racketeering. Between the short period of 1989 and 1992, G.O.G (1993) shows that 15 state owned enterprises were privatized and, given the depressed state of the social economy at the time, only the richest Guyanese and foreign investors were likely to benefit from the privatization process.

A careful assessment of the second phase of the privatization scheme between 1993-2011, shows that the beneficiaries are known entrepreneurs of today. Brassington (2012, 22-25, 30-36) shows the names of both companies and individuals that acquired public companies and/or government-owned real estate or leases to publicly owned land. Prominent companies include Roraima Airways, Queens Atlantic, BK International LTD, John Fernandes LTD and other well-known enterprises. Khemraj (2013) refers to these as the favoured enterprises that are closely connected to former President Bharrat Jagdeo, in particular, Queens Atlantic. This second wave of privatization led to what is commonly referred to as the Newly Emerging Private Sector (Khemraj 2013), but the first wave of privatization and the review of Guyana's socialist experiment demonstrate that there was an older tradition of private enterprise. This is central to understanding the ethnic composition of Guyana's upper middle class and economic elites (top 10%).

The article concludes that the reshuffling of the income distribution in Periods C and D is due to the IMF's structural adjustment program. This finding is consistent with the Russian case--Novokmet, Piketty, and Zucman (2017) conclude that the privatization of public assets is the principal explanation for the growth of the Russian Oligarchs--the income share of the top 10% has increased from 20-25% during the Soviet period to 45-50% today. These scholars and EBRD (2016) contend that privatization is key to explain the rise of income inequality in China and ex-communist-socialist countries. I argue that the Guyana case is no exception, save for one modification--privatization was more instrumental to the rise of the upper middle class than for top incomes (see Figure 2). Why? Unlike the Russian case (Novokmet, Piketty, and Zucman 2017), no stock market boom or housing bubble during the 1990s facilitated the rise in top incomes.

Ethnic Composition of the Income Distribution

To fully appreciate the ethnic component of the changes in the income distribution post 1988, I present a brief description of Guyana's social hierarchy at the end of this period. Danns (2014) notes that Guyana's socialist state deliberately transformed British Guiana's social hiorarchy where the bureaucratic bourgeoisie (predominantly Afro-Guyanese) now occupy the top level followed by a relatively smaller private sector elite. The professional middle class and working class occupied the third and fourth levels respectively. Hintzen (1985) takes a contrarian view and places the Portuguese (albeit a much smaller group) at the top level and the bureaucratic bourgeoisie at the second level. He explains that the middle class is primarily composed of coloured Guyanese and that Indo-Guyanese and Aboriginals occupied the fourth and fifth levels of the social hierarchy respectively. Further, Gafar (2004) notes that, at the end of this period, Indo-Guyanese occupied the agricultural, industrial and private sectors, while Afro-Guyanese were predominant in the teaching and police professions and the public service generally. This article sides with Gafar and Hintzen's description, but this does not imply that the top elites were only Portuguese, though I argue they were important players--more on this below.

France (2005) posits that, by 1997, Afro-Guyanese lost 40% of public sector employment during the ERP, and that they would have the least opportunity of mobility. In plain terms, the ERP demolished the bureaucratic bourgeoisie (predominantly Afro-Guyanese). Indo-Guyanese were better placed to benefit from the ERP, since the elimination of price controls increased producer prices for key agricultural produce and, as Gafar (2004) notes, Indo-Guyanese largely occupied the agricultural sector. Thomas (1997) explains that since the ERP, the fastest growing sectors were rice, sugar, and distribution, which were all dominated by Indo-Guyanese. Danns (2014) takes a similar position and argues that the ERP reduced the influence of the Afro-Guyanese ruling class and led to an upswing in the class position of Indo-Guyanese. It follows that the dramatic decline in the bottom 50% is largely a diminution in income share for Afro-Guyanese.

It is important to note for political economy reasons that, in 1992, a new government was elected--a government largely supported by Indo-Guyanese. It follows that this new government managed the privatization process and Khemraj (2013), Canterbury (2016) and Danns (2014) claim that they did so in favour of their ethnic group--Indo-Guyanese. Canterbury argues that the government micromanages investment processes to enrich state elites and Danns claim that ministers of government and top regime officials became rich overnight. Khemraj calls this government an elected oligarchy. It follows that the second phase of the privatization scheme led to the upswing of Indo-Guyanese--largely the upper middle class. It is important to emphasize here that this ethnic economic mobility had little to do with skills and education, but is largely the outcome of good fortune (in the case of Indo-Guyanese) and misfortune (in the case of Afro-Guyanese).

Undoubtedly, some privatization projects were successful enough to enable the beneficiaries to climb into the economic elite status of the top 10%. But as the evidence shows, it was the upper middle class, rather than the top 10%, that gained the greatest income share during the second phase of the privatization scheme. Ergo, Indo-Guyanese enjoy upper middle class status and, unlike popular perception, this article demonstrates that they are not the elite of the elites. In plain terms, they can be viewed as new money that engage in the typical behaviour of conspicuous consumption and investment that propel them into the popular press as the staple example of wealth and power. It is commonplace that the newly rich are viewed as the standard of wealth and power. The Rihanna's and Beyonce's of the world consume goods and services to demonstrate their newly acquired wealth, but the grave concern with inequality is inheritance or old money. This is not to downplay the legitimate concerns with a particular (ethnic) group becoming rich overnight because of the fire sale of public assets. My only objective here is to use the best available evidence in conjunction with historical analyses to determine the ethnic composition of the income distribution.

Colonial Origins

What of the ethnic composition of the top 10%? To answer this question one must turn to history. Consider Figure 5 that illustrates the absolute control the Portuguese had over retail commerce between 1840-1890 in a key commercial space in British Guiana--Georgetown. It shows that by 1880, Portuguese held 100% of retail spirit licenses. This absolute monopoly allowed the Portuguese to effectively fix prices and increase profits (Moore 1975) and Pierre (2007)). Wager (1975) demonstrates that, by 1870, Portuguese owned 11 of the 23 largest enterprises in Georgetown. Hintzen (1977), Danns (2014) and Conway (1993) note that, at the turn of the 20th Century, the planter class were on top of the social hierarchy with the Portuguese, or entrepreneurial class, just below them.

Now consider Table 1, which illustrates the Gini coefficient for land distribution in Guyana by geographic area in 1952 and 1968. The first thing to note is that land becomes more unequally distributed by 1968. Second, Guyana gains its independence in 1966 under a coalition government with the minority coalition partner, or political party, being led by a Portuguese--Hintzen and Premdas (1982), Premdas (1978), Premdas (1994), Hendrickson (1971) and Griffith (1991), who's key objective was to protect Portuguese business interest-Jagan (1997), Greene (1972), Premdas (1982), Premdas (1979), Premdas (1994) and Singh (1996). As noted earlier, a rising Gini coefficient means that the middle class is less resilient in protecting its income share. Therefore, the author interprets the rise of land inequality as the new economic elites (Portuguese) squeezing the small and nascent middle class. Since the GCIP data starts from 1960, I argue that the top 10% was a combination of traditional European elites and new elites of Portuguese ancestry. Now consider Table 2, which depicts the size of land leased in 1964. The table demonstrates that individuals of Portuguese descent held the largest land leases and supports the claim that the top 10% of the income distribution since 1960 were primarily of Portuguese origin.

I argue that, through inheritance and Guyana's socialist experiment that wasn't, the Portuguese remain at the top of the economic hierarchy. Even during the recent ERP former President Hoyte complained about the Portuguese mafia--a term he used to describe the group of Portuguese elites attempting to stymie his economic reforms (StabroekNews 2007). Since the data illustrates that the top 10% were able to defend their income share over the past five decades, this article concludes that Portuguese remain important players in the top 10% at the end of the period.

Conclusion

This article surveys the evolution of income inequality in Guyana between 1960-2013 with the aid of new data and historical analyses. It is the first comprehensive empirical study on the distribution of income, but the limitations of the data must be noted immediately. Missing survey years data are estimated, and top income share must be interpreted as only lower bound estimates, since top incomes are usually under-declared in household surveys. Notwithstanding these limitations, the finding that the richest 10% is a resilient group, as measured by the stability in their income share, is consistent with the historical evidence that the Portuguese had long been established and unchallenged as economic oligarchs since the 19th century. This stability suggests that the super rich of today are well-off because of inheritance, rather than education, skills and thrift. Inheritance is of some concern, because it is inconsistent with widely held notions of economic justice and, in the Guyana case becomes alarming due to the absence of any estate or inheritance tax. This suggests an obvious area for urgent tax reform.

A reassuring finding is that the Guyana reform experience in the 1990s is broadly consistent with the experiences of ex-communist countries that have undertaken a similar transition over the same period. Rapid privatization in Guyana, as in many former communist states, increased income inequality--the upper middle class in the Guyana case. Further, the elimination of price controls led to the inflation in prices of key agricultural produce that disproportionally benefitted Indo-Guyanese. A downsizing of the state is standard IMF adjustment policy and given the initial ethnic occupational distribution in Guyana, this fiscal consolidation adversely affected Afro-Guyanese. These were widely held assertions in academia and the public discourse and one contribution of this article is to provide empirical support to these claims. More specifically, the data shows that IMF structural adjustment policies reduced mean income of the bottom 50% by half in the early 90s. More strikingly, unlike the top 50%, the mean income of the bottom half of the income distribution has not recovered from its 1976 peak. It follows that the top ends of the income distribution are leaving half of Guyana behind--creating a have and have not dichotomy.

Since Guyana has a history of ethnic conflict and a deeply entrenched ethnic voting pattern (Khemraj 2016), the ethnic composition of the income distribution is of great political import. The rise of Indo-Guyanese at the expense of Afro-Guyanese in terms of income share, pose a significant obstacle to social cohesion. Thus, redistribution is key for social cohesion. On matters of poverty, the article demonstrates that the bottom 40% are dissavers, and perhaps are supported by remittance inflow and government aid. Effective poverty reduction must increase both mean income and the income share of the bottom 40%.

An important implication of this article relates to the measurement of income inequality. Based on the Gini coefficient, the article finds that income inequality has declined in the 1990s and has since stabilized. But it is difficult to reconcile this optimistic and arcane finding with the richer analytical insights provided with the use of measures like the Palma ratio and income shares. I conclude that income inequality has increased using the Palma ratio --the richest 10% of Guyanese as a ratio of the poorest 40%--as the principal indicator. This measure is more meaningful in terms of policy--it suggests that policy must focus on the bottom 40% to reduce the disparity between the rich and the poor. When we think of income inequality we should be principally concerned with what occurs at the tails (rich and poor) of the income distribution and the Gini coefficient, as compared to others, places less weight on these. More research is needed to better understand the distributional dynamics in Guyana and this becomes especially urgent with the impending oil economy. First, how much better off are Indo-Guyanese as compared to Afro-Guyanese? Alternatively, what is the income distribution across all ethnic groups? These are important questions to answer if oil revenues are to be used to reduce gross ethnic inequality. More detailed household data are needed and can only be gathered through primary data collection. This research hopes to highlight the necessity in developing national distributional statistics in addition to other national income data. Second, wealth data are needed to study wealth inequality and how this affects the evolution of income inequality. Third, research on redistributive taxation within the context of dualism and openness is useful to guide policy. Finally, this article hopes to inspire other country profile studies in the Caribbean to bring to bear the nature of the growth models in the respective countries.

ACKNOWLEDGMENTS

I thank two anonymous referees and seminar participants at the Shocks and Reconstructions: Histories of Long-Term Inequalities Conference, in Tampere, Finland, 24th October 2016 for useful comments and suggestions.

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Table 1: Gini Coefficients for Land Distribution in Guyana by
Geographic Area

1952 District               1968 District               Gini   Gini for
                                                        for    1968
                                                        1952

 1-4                        Corentyne-East Berbice      .39    .46
 5-6                        West Berbice                .39    .46
Berbice                     Berbice                     .39    .39
 7-9                        East Coast-Georgetown       .47    .53
10 East Bank-Demerara         .47                       .51
11 Demerara River             .46                       .52
 7-11                        7-11                       .47    .53
12-13                       West Demerara               .46    .44
Demerara                    Demerara                    .47    .51
14-15                       Essequibo Islands           .38    .46
16-18                       Essequibo Coast             .43    .40
14-18                       14-18                       .41    .43
19 Northwest                  .26                       .39
20 Mazaruni-Potaro            .35                       .35
Essequibo (less Rupununi)   Essequibo (less Rupununi)   .42    .43
Guyana (less Rupununi)      Guyana (less Rupununi)      .44    .47

Source: Nathan and Associates (1974) as cited in Jameson (1978).

Table 2: Size of Land Leases in Guyana (1964)

Holder of Permission                Size of Permission
B. L. Hart Co. (*)                    242.5 sq. miles
Inc. Trustees Church Guyana            50 sq. miles
E. McTurk                             142 sq. miles
T. Runo                                50 sq. miles
C. Melville (*)                        32 sq. miles
M. Orella                              50 sq. miles
H. Melville (*)                        50 sq. miles
L. D' Aguiar                          100 sq. miles
E. E. Melville (*)                     30 sq. miles
V. Davis                               12 sq. miles
McDonald                               50 sq. miles
C. Gorinsky                            50 sq. miles
R. C. Ward                             30 sq. miles
H. A. Hart                             25 sq. miles
Rupununi Development Co.            2,000 sq. miles (approx)
Nappi Amerindian Reservation          100 sq. miles
Wapishana Reservation                 400 sq. miles (est)
Potarinau and Kacushi Reservation     200 sq. miles (est)
Achiwiib Reservation                  200 sq. miles (est)

Source: Jameson (1978). Notes: (*) Indicates that lands were taken over
by the Government of Guyana in 1969 and all lands are leased with the
exception of C. Gorinsky.
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