frontiers and sustainable economic development

Environ Resource Econ (2007) 37:271–295DOI 10.1007/s10640-007-9120-9

Frontiers and sustainable economic development

Edward B. Barbier

Published online: 16 May 2007© Springer Science+Business Media B.V. 2007

Abstract Exploiting new resource “frontiers,” such as agricultural land and mineral re-serves, is a fundamental feature of economic development in poor economies. Yet fron-tier-based development is symptomatic of a pattern of economy-wide resource exploitationin developing economies that: (a) generates little additional economic rents, and (b) whatrents are generated are not being reinvested in other sectors. Such development is inherentlyunsustainable. The following paper explains this phenomenon, and provides evidence thatlong-run expansion of agricultural land and oil and natural gas proved reserves across pooreconomies is associated with lower levels of real income per capita. The paper proposes afrontier expansion hypothesis to explain why the structural economic dependence of theseeconomies on frontier land expansion and resource exploitation is not conducive to sustainedlong-run growth. The key to sustainable economic development in poor economies will beimproving the economic integration between frontier and other sectors of the economy, tar-geting policies to improved resource management in frontier areas and overcoming problemsof corruption and rent-seeking in resource sectors.

Keywords Economic development · Frontier · Natural capital · Natural resources ·Resource-abundant economies · Sustainable development

JEL classification O13 · O41 · Q32 · Q33

1 Introduction: natural capital and sustainable development

One of the many important contributions of David Pearce’s work, particularly through his“Blueprint” series of books, was to clarify the concept of sustainable economic development(Pearce et al. 1989; Pearce and Barbier 2000). As pointed out in these works, economic

E. B. Barbier (B)Department of Economics and Finance, University of Wyoming, Department 3985, Ross Hall 1621000 E. University Ave., Laramie, WY 82071, USAe-mail: [email protected]

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272 Edward B. Barbier

interpretations of sustainability should take as their starting point the consensus reachedby the World Commission on Environment and Development (WCED). The WCED (1987)defined sustainable development as “development that meets the needs of the present withoutcompromising the ability of future generations to meet their own needs.”

Economists are generally comfortable with this broad interpretation of sustainability, asit is easily translatable into economic terms: an increase in well-being today should not haveas its consequences a reduction in well-being tomorrow.1 That is, future generations shouldbe entitled to at least the same level of economic opportunities—and thus at least the samelevel of economic welfare—as currently available to present generations. Consequently, eco-nomic development today must ensure that future generations are left no worse off thanpresent generations. Or, as some economists have succinctly put it, per capita welfare shouldnot be declining over time (Pezzey 1989).

As noted in Fig. 1, it is the total stock of capital employed by the economic system,including natural capital, which determines the full range of economic opportunities, andthus well-being, available to both present and future generations. Society must decide howbest to “use” its total capital stock today to increase current economic activities and welfare,and how much it needs to “save” or even “accumulate” for tomorrow, and ultimately, for thewell-being of future generations.

However, it is not simply the aggregate stock of capital in the economy that may matterbut also its composition, in particular whether present generations are “using up” one formof capital to meet the needs of today. For example, much of the recent interest in sustainabledevelopment has risen out of concern that current economic development may be leading torapid accumulation of physical and human capital, but at the expense of excessive depletionand degradation of natural capital. This concern is especially important for developing coun-tries that are dependent on the exploitation of natural capital for their current developmentefforts. Such dependence of low- and middle-income economies on natural resources is akey “stylized fact” for these economies, and should shape our perspective on the role of effi-cient and sustainable management of natural capital to foster long-run development (Barbier2005b).

From an economic standpoint, the critical issue of debate is not whether natural capitalis being irreversibly depleted, but whether individuals today can compensate future genera-tions for the current loss of natural capital, and if that is possible, how much compensation isrequired for this loss (Mäler 1995). As pointed out by Pearce and colleagues some years ago,economists concerned with this problem appear to be divided into two camps over the specialrole of natural capital in sustainable development (Pearce et al. 1989). The main disagree-ment is whether natural capital has a unique or “essential” role in sustaining human welfare,and thus whether special “compensation rules” are required to ensure that future generationsare not made worse off by natural capital depletion today (see Fig. 1). These two contrastingviews are now generally referred to as weak sustainability versus strong sustainability.

The debate between weak and strong sustainability perspectives is not easy to reconcile.Nevertheless, it is clear that the very minimum criterion for attaining sustainable economicdevelopment is ensuring that an economy satisfies weak sustainability conditions. That is, aslong as the natural capital that is being depleted is replaced with even more valuable physicaland human capital, then the value of the aggregate stock—comprising human, physical and

1 Although as Bishop (1993) has pointed out, the objective of “sustainability” is different from that of thestandard economic objective of “efficiency.” That is, there are potentially an infinite number of developmentpaths for an economy, only some of which are sustainable. Efficiency therefore does not guarantee sustain-ability, as some efficient paths are not sustainable. At the same time, there is no reason why an economy couldnot be both efficient and sustainable.

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Frontiers and sustainable economic development 273

Sustainable Development

Development that meets the needs of the present without compromising the ability of future generations to meet their needs

Welfare does not decline over time

Requires managing and enhancing a portfolio of economic assets

Total Capital Stock

Natural Capital KN

Physical Capital KP

Human Capital KH

"Weak" Sustainability

All KN is non-essential Substitutes for KN

"Strong" Sustainability

Some KN is essential Keep essential KN "intact" because of:

Imperfect substitution

Irreversible losses

Uncertainty over values

Fig. 1 Sustainable economic development. Source: Adapted from Pearce and Barbier (2000)

the remaining natural capital—should be increasing over time. This in turn requires that thedevelopment path of an economy is governed by principles somewhat akin to Hartwick’s rule(Hartwick 1977).2 First, environmental and natural resources must be managed efficiently sothat the welfare losses from environmental damages are minimized and any resource rentsearned after “internalizing” environmental externalities are maximized. Second, the rentsarising from the depletion of natural capital must be invested into other productive economicassets. As we shall show, such principles are important for determining the extent to whichfrontier land expansion and resource expansion in low- and middle-income economies iscontributing to sustainable development in these economies.

A great concern today is that many developing countries are currently not satisfying theabove conditions for efficient and sustainable management of their natural resources for suc-cessful development. The purpose of the following paper is to explore one hypothesis as to

2 This concept is often also referred to as the Hartwick–Solow rule, in recognition that Solow (1974) firstderived the principle that reinvestment of the rents derived from the intertemporally efficient use of exhaustiblenatural resources can be reinvested in reproducible capital in order to ensure a constant stream of consumptionover time. Solow (1993) provides an excellent summary of the implications of Hartwick’s rule for economicsustainability.

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why this is the case, which is referred here and elsewhere as the frontier expansion hypoth-esis.3 In addition, the paper presents new empirical evidence in support of this hypothesis.The overall aim is to explain why the exploitation of “frontiers” is a critical part of thepuzzle of “unsustainable” economic development in many of the poorest nations of theworld.

Since Fredrick Jackson Turner (1986) explored the “significance of the frontier” in Amer-ican history over a century ago, the term “frontier” usually refers to an area of unusuallyabundant natural resources and land relative to labor and capital, and the process of “frontierexpansion” or “frontier-based development” refers to finding and exploiting or convertingthese relative abundant resources for production purposes. This perspective is especiallyimportant, as it suggests that the process of economic development is not just about allocat-ing scare resources but also about obtaining and exploiting more abundant, or “new frontiers,”of natural resources. This is particularly the case if, as noted by Findlay and Lundahl (1999,p. 26), the concept of a “frontier” also extends “vertically downwards” to include mineralresources and extractive activities “rather than be horizontally extensive as in the case of landand agriculture.” When viewed in this way, finding and exploiting new sources, or “frontiers,”of natural resources have clearly been an important aspect of economic development for mostof global history.

However, although historically “frontier expansion” may have been associated with suc-cessful resource-based development, this is less likely in the case of most developing countriestoday (Barbier 2005a, b). The main reason is that the current process of “frontier expansion”in many poor countries has two unique structural features: first, the key “frontier” activityoccurring in these countries is land conversion leading to agricultural expansion, and second,this frontier land expansion is serving mainly as an outlet for the subsistence and near-sub-sistence needs of the rural poor. Such frontier land expansion does not generate substantialrents, and any resulting agricultural output is consumed mainly locally. In the case of frontierresource-extractive activities, such as timber harvesting, mining, ranching and commercialplantations, do yield more significant rents, the rent-seeking behavior associated with theseactivities will mean that these rents will be reinvested into further exploitation of frontierresources. The result is that whether one is talking about exploitation of “horizontal” or “verti-cal” frontiers, and whether the exploitation is the basis for commercial or subsistence activity,the frontier economy will remain an isolated enclave within the larger developing economy,and that the resulting land expansion and resource exploitation becomes symptomatic ofa pattern of economy-wide resource-based development that: (a) generates little additionaleconomic rents, and (b) what rents are generated are not reinvested in more productive anddynamic sectors, such as manufacturing.

The next section provides a brief explanation as to why agricultural land expansion, andnatural resource exploitation by “frontier” primary sector activities more generally, is a fun-damental feature of “unsuccessful” economic development in poor economies. Subsequentsections present empirical evidence that appears to support the frontier expansion hypothesis,and in light of this evidence, discusses the hypothesis in more detail. Finally, the paper ends byproposing policy recommendations and reforms that could lead to better economic integra-tion of frontier and other sectors in developing economies, that target improvements in ruralresource management in frontier areas, and that might ameliorate problems of corruption andrent-seeking in resource sectors.

3 For further elaboration of this hypothesis beyond what is possible in this paper, see Barbier (2005a, b).

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2 Why is frontier expansion linked to unsustainable development?

As indicated in the introduction, a critical contribution of David Pearce’s writings has been toemphasize how management of environmental and natural resources, i.e., the natural capitalstock, of a country is important for achieving sustainable economic development (Pearceet al. 1989, 1990; Pearce and Barbier 2000). A key point emphasized in this paper is that,instead of “managing” their existing natural resource stocks, most developing countries havein fact sought to augment their natural resources through finding and exploiting new resource“reserves.”

This latter fact in itself is not startling. Finding “new frontiers,” or “reserves,” of nat-ural resources to exploit has been the basis of much of global economic development forthe past 500 years (Cipolla 1976; di Tella 1982; Findaly 1995; Findlay and Lundahl 1994;Webb 1964). Such frontier-based economic development is characterized by a pattern of cap-ital investment, technological innovation and social and economic institutions dependent on“opening up” new frontiers of natural resources once existing ones have been “closed” andexhausted (di Tella 1982; Findlay and Lundahl 1994). Over the years there has also emergeda general consensus over both the definition of a “frontier” and its significance in terms ofeconomic development: a frontier area is assumed to be “a geographic region adjacent to theunsettled portions of the continent in which a low man–land ratio and unusually abundant,unexploited, natural resources provide an exceptional opportunity for social and economicbetterment to the small-propertied individual” (Billington 1966, p. 25). Or, as di Tella (1982,p. 212) has put it more succinctly, throughout history “processes” of frontier-based develop-ment “were characterized by the initial existence of abundant land, mostly unoccupied, andby a substantial migration of capital and people.”

However, perhaps because frontier expansion and economic development has gone hand-in-hand for so many centuries, economists have overlooked the possible importance of thisrelationship, especially for today’s developing economies.

As Findlay and Lundahl (1994, p. 70) note, the analysis of frontier-based development“has been used extensively by historians and geographers for a wide variety of times andplaces, but has been neglected by economists.”4 The exceptions are the “staples thesis,” whichhas argued that the development of many countries and regions has been led by the expan-sion of export sectors, and in particular, natural resource exports, and the “vent for surplus”theory, which suggested that trade was the means by which idle resources, and in particularnatural resources in poor countries, were brought into productive use (Chambers and Gordon1966; Myint 1958; Smith 1976; Southey 1978; Watkins 1963). Both theories are relevant tothe economic analysis of frontier-based development, because they focus on the existence ofexcess resources—“land” and “natural resources”—that are not being fully exploited by aclosed economy. The function of international trade is to allow these new sources of naturalresources that previously had no economic value to be exploited, for increased exports andgrowth.

More recent theories have focused on characterizing the “endogenous” or “moving”frontier as the basis for attracting inflows of labor and capital into a region or economy

4 One of the few exceptions in the environmental and resource economics literature is Howe (1979), whoprovides a simple model of a frontier resource-using economy. The concept of a frontier economy as devel-oped by Howe (1979, pp. 62–64) shares many common features with both the non-economic definitions of a“frontier” and also with the “endogenous” frontier literature in economics: “A frontier economy is defined asone with very plentiful supplies of natural resources relative to capital and labor. . ..The GNP level is limitedat any time not by a natural resource shortage in any physical sense but because some of the labor-capital inputmust be used to gather or otherwise prepare the resources for use in producing final goods and services.”

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(di Tella 1982; Findlay 1995; Findlay and Lundahl 1994; Hansen 1979). Such “surplusland” models essentially postulate a Ricardian land frontier, whereby additional land can bebrought into cultivation through investment of labor and/or capital, provided that the resultingrents earned are competitive with the returns from alternative assets. Thus frontier expan-sion becomes an “endogenous” process within a general equilibrium system of an economy,sometimes incorporating trade and international capital flows, with the supply and price ofland determined along with the supplies and prices of all other goods and factors. As a conse-quence, changes in relative commodity and factor prices, as well as exogenous factors suchas technological change and “transport revolutions”, induce adjustments in the supplies ofthe specific factors including expansion of the land frontier. As in the case of the staplesand vent-for-surplus theories, these “endogenous frontier” models have been used mainly toexplain economic expansion in the temperate “regions of recent settlement”, e.g. Canada,the United States, Argentina and Australia, and export-led colonial agricultural developmentin certain tropical countries during the “Golden Age” of resource-based development from1870 to 1914.5

In comparison, very little economic analysis has been devoted to present-day processesof frontier resource expansion in poor economies and the implications for their sustainabledevelopment. Yet, in direct contrast to the “Golden Age” of resource-based development from1870 to 1914, the process of frontier expansion in today’s developing countries is clearly notassociated with substantial economy-wide benefits. The critical question is what is differentin the relationship between natural capital, growth and development for present-day low andmiddle-income countries in Africa, Asia and Latin America?

As emphasized by Barbier (2005b) the key to understanding why frontier expansion isnot leading to sustainable economic development in today’s poor economies can be found infour “stylized” facts of natural resource use in these economies:

1. The majority of low- and middle-income countries (LMICs) are highly dependent onprimary product exports.

2. Resource dependency—usually measured as primary product exports as a share of totalexports—in LMICs is associated with poor economic performance.

3. Development in LMICs is associated with increased land conversion.4. A significant share of the population in LMICs is concentrated on “fragile” lands.

The first stylized fact confirms that natural capital (KN ) is a vital input into the productionprocess of developing economies (see Fig. 1). That is, efficient and sustainable managementof the natural capital stock is essential for the long-run development prospects of many pooreconomies, because natural resources form the basis of the important export-earning activi-ties of these economies. The resource rents earned from these activities in turn are the mainsource of investment in physical and human capital, and the export revenues finance thenecessary imports of capital goods, services and technology that are critical for long-termdevelopment efforts.

5 Hansen (1979) suggests that his Ricardian land surplus model is mainly applicable to the agricultural devel-opment “under old-style imperialism” (i.e., colonialism) whereby “subsistence agriculture by illiterate anduneducated native farmers takes place exclusively on vast expanses of marginal land, whereas intra-marginalland is occupied by colons—knowledgeable Europeans capable of picking up and applying technical pro-gress.” Findlay and Lundahl (1994) show how their basic “endogenous frontier” model can be modified closerto the “vent-for-surplus” theory to explain the process of rapid export expansion in key plantation and peasantexport economies, such as smallholder rubber in Malaya and bananas and coffee in Costa Rica in the late 19thand early 20th century, cocoa in Ghana in the early 20th century and rice in Burma in the second half of the19th century.

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Given the importance of natural capital to sustainable development especially of LMICs,one might conclude reasonably that greater resource abundance and exploitation shouldimprove economic performance. That is, LMIC economies that have a greater endowment ofnatural resources to exploit must surely have a much better chance of attaining higher eco-nomic growth rates and prosperity than relatively resource-poor economies. Yet, as stylizedfact two suggests, recent evidence suggests that low and middle-income economies that aremore resource-dependent, in terms of primary product export share of total exports, tend tohave lower levels of real GDP per capita, lower growth rates, higher poverty levels and ahigher proportion of their populations living in poverty (Rodríguez and Sachs 1999; Sachsand Warner 1997, 2001).6

As stylized fact three indicates, in all LMICs, expansion of this agricultural land baseis occurring rapidly through conversion of forests, wetlands and other natural habitat (FAO1995, 2001; Fischer and Helig 1997; López 1998). This trend for greater land use appearsto be occurring in all low- and middle-income countries, regardless of their resource depen-dency or economic performance. This is a persistent, long-term trend that is unlikely toabate in coming decades. Over 1970–1990 increased harvested area accounted for 31% ofthe additional crop production in these countries, and over 1990–2010 this contribution isexpected to rise to 34% (FAO 1995). Throughout the developing world, cultivated land areais expected to increase by over 47% by 2050, with about 66% of the new land coming fromdeforestation and wetland conversion (Fischer and Helig 1997).7

Stylized fact four is the outcome of two important trends in rural population growth indeveloping countries. First, in the coming decades rural population growth will be muchhigher for those low- and middle-income economies that are more resource dependent, andsecond a large share of the rural populations in these economies are concentrated on poor,or “fragile,” lands (World Bank 2003). The World Bank defines “fragile lands” as “areasthat present significant constraints for intensive agriculture and where the people’s links tothe land are critical for the sustainability of communities, pastures, forests, and other naturalresources” (Word Bank 2003, p. 59). Currently one quarter of the people in developing coun-tries—almost 1.3 billion—survive on fragile lands, which include 518 million living in aridregions with no access to irrigation systems, 430 million on soils unsuitable for agriculture,216 million on land with steep slopes and more than 130 million in fragile forest systems.Barbier (2005b) has shown that resource-dependent LMICs contain large concentrations oftheir populations on fragile lands. Moreover, greater resource dependency is associated witha large percentage of population on fragile land. For example, as the concentration of pop-ulations on fragile lands in low and middle-income economies increases from 20–30% to

6 It has been difficult to determine from the empirical evidence whether greater resource abundance, in theterms of a larger natural resource endowment or stocks, is associated with lower long-run growth in devel-oping economies. Instead, most studies provide evidence that resource dependency, as defined here in termsof primary product share of total exports, is associated with poorer economic performance. Strictly speak-ing, the latter cannot be a true indicator of “resource abundance” per se, as it is not a measure of the totalresource endowment or stocks of a country. Hence, the second stylized fact is stated in terms of the correlationbetween resource dependency, and not abundance, with poor economic performance in low and middle-incomecountries.7 Increasing land conversion in developing countries may be symptomatic of a more general correlationbetween environmental deterioration and growth in these economies. For example, a World Bank study founda statistically significant negative correlation (r = −0.27) between an environmental quality change index(EQI) and GDP growth rates over 1981–1998 for 56 developing countries, where the EQI was constructed byattaching equal weights to changes in indicators of water quality, air quality and deforestation (Thomas et al.2000).

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30–50% to 50–70% to over 70%, the average share of primary products in exports rises from62.9% to 72.8% to 87.6% to 98.3%, respectively.

Each of the four stylized facts on its own has important development implications. How-ever, taken together, these facts also suggest some key underlying relationships betweenexploiting new land and resource frontiers and unsustainable economic development inLMICs.

For example, the first three stylized facts suggest that developing countries today areembarking on a pattern of resource-dependent development that culminates in frontierresource exploitation, particularly in the form of agricultural land expansion and commer-cial raw material exploitation, but the end results do not yield much in the way of sustainedeconomic progress. Stylized fact four indicates an additional “symptom” of malaise asso-ciated with frontier-based development today: In many developing economies a significantproportion of extremely poor households are concentrated on fragile lands, and both ruralpopulation growth and the share of population on fragile lands seem to increase with thedegree of resource dependency of a developing economy. That is, frontier land expansionappears to be serving mainly as an outlet for the rural poor in many developing countries.

In fact, a closer look at the four “stylized facts” suggests that most low- and middle-income economies fall into a persistent pattern of resource use that is very much relevant tothe problem of resource degradation, poverty and chronic underdevelopment. Table 1 revealsthis pattern by grouping low- and middle-income economies by three types of indicators: Thefirst indicator is the degree of resource dependency of an economy, as measured by the shareof primary commodities in total exports. For instance, an economy with a primary productexport share of 50% or more would be considered highly resource dependent. As stylizedfacts one and two imply, if a developing country is highly resource dependent, then its “takeoff” into sustained and structurally balanced economic growth and development is still sometime away, and thus the dependence of the overall economy on natural resources will persistover the medium and long-term. The second and third indicators depicted in Table 1 illustratethe extent to which both a high degree of rural poverty and a high concentration of the ruralpoor in marginal land areas occur in low- and middle-income economies. The former indica-tor is the share of the rural population living under conditions of absolute poverty, whereasthe latter indicator is the share of the total population concentrated on fragile lands, as definedby the World Bank (2003, p. 59) and discussed above in connection with stylized fact four.Combining these two indicators gives us an approximate benchmark, or “20–20 rule,” forthe degree of rural poverty-resource degradation linkage within a developing economy: acountry with 20% or more of its population concentrated on fragile land and 20% or moreof its rural population living in poverty shows evidence that poverty, frontier land expansionand resource degradation are persistent problems in rural areas.

Table 1 combines the above two sets of indicators for 72 low- and middle-income econo-mies. The countries are grouped in terms of their degree of resource dependency, as measuredby the share of primary products in total exports, and the extent to which their populationsare concentrated on fragile land. The figure in the parentheses by each country also indicatesthe percentage of the rural population below the national poverty line.

According to the table, 56 out of the 72 economies have a primary product export share of50% or more, and therefore display evidence of high resource dependency. All 72 economieshave 20% or more of their population on fragile land and all but seven also have 20% ormore of the rural population living in absolute poverty. Thus by the “20–20 rule,” virtuallyall the economies listed in Table 1 show signs of a high incidence of rural poverty-resourcedegradation linkage within the economy. What is more striking is that, with the exceptionof the Yemen Arab Republic and Indonesia, all 56 highly resource-dependent countries also

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Table 1 Low-and middle-income countries and patterns of resource use

Share of population onfragile land ≥ 50%

Share of population onfragile land 30–50%

Share of population onfragile land 20–30%

Primary productexport share ≥ 90%

Burkina Faso (61.2) Algeria (30.3) Ecuador (47.0)

Chad (67.0) Angola (NA) Congo, Rep. (NA)Congo Dem. Rep. (NA) Benin (33.0) Liberia (NA)Laos (53.0) Botswana (NA) Zambia (88.0)Mali (72.8) Cameroon (32.4)Niger (66.0) Comoros (NA)Papua New Guinea (NA) Eq. Guinea (NA)Somalia (NA) Ethiopia (31.3)Sudan (NA) Gambia (64.0)Yemen A.R. (19.2) Guyana (NA)

Iran (NA)Mauritania (57.0)Nigeria (36.4)Rwanda (51.2)Uganda (55.0)

Primary productexport share 50–90%

Egypt (23.3) Central Af. Rep. (66.6) Bolivia (79.1)

Zimbabwe (31.0) Chad (67.0) Burundi (36.2)Guatemala (71.9) Côte d’Ivoire (32.3)Guinea (40.0) El Salvador (55.7)Kenya (46.4) Ghana (34.3)Morocco (27.2) Guinea-Bissau (48.7)Senegal (40.4) Honduras (51.0)Sierra Leone (76.0) Indonesia (15.7)Syria (NA) Madagascar (77.0)Tanzania (51.1) Mozambique (37.9)

Myanmar (NA)Panama (64.9)Peru (64.7)Togo (32.3)Trinidad & Tobago (20.0)

Primary productexport share< 50%

Costa Rica (25.5) China (4.6)

Haiti (66.0) Dominican Rep. (29.8)Lesotho (53.9) India (36.7)Nepal (44.0) Jamaica (33.9)Pakistan (36.9) Jordan (15.0)South Africa (11.5) Malaysia (15.5)Tunisia (21.6) Mexico (10.1)

Sri Lanka (20.0)Vietnam (57.2)

Notes: Primary commodity export share is the average export share 1990/1999 for low- and middle-incomecountries in Appendix 1. Share of population on fragile land is from World Bank, World Development Report2003, Table 4.3. Figure in parenthesis is the percentage of the rural population below the national poverty line,from World Bank, 2002 World Development Indicators.

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satisfy the “20–20 rule.”8 That is, three-quarters of the countries listed in Table 1 show con-siderable evidence of a high degree of resource dependency as well as a high incidence ofrural poverty-resource degradation linkage.

Of the 16 countries that are not highly resource dependent, i.e., they have a primary prod-uct export share of less than 50%, many of the countries nevertheless display evidence thatpoverty, frontier land expansion and resource degradation may be chronic in rural areas.For example, Haiti, Lesotho, Nepal and Pakistan have 30–50% of their populations on frag-ile land and display an incidence of rural poverty of 30–70%. The Dominican Republic,India, Jamaica and Vietnam have 20–30% of their populations living in fragile areas andaround 30–60% of their rural populations in poverty. Only China and Mexico, and to a lesserextent Jordan and Malaysia, do not conform very strongly to the “20–20 rule” for populationconcentrated on fragile land and the degree of rural poverty.

3 Conditions and caveats for successful resource-based development

In sum, agricultural land expansion, and natural resource exploitation by primary sectoractivities more generally, appears to be a fundamental feature of economic development inmany of today’s poorer economies. Yet, as we have seen, many developing economies havea large concentration of their populations on fragile land and high incidence of rural poverty.Also, developing countries that are highly dependent on exploiting their natural resourceendowments tend to exhibit a relatively poor growth performance. This poses an intriguingparadox. Why should economic dependence on natural resource exploitation and frontier landexpansion be associated with “unsustainable” resource-based development in many low- andmiddle-income countries today, especially as historically this has not always been the case?

For example, it has been argued that the origins of rapid industrial and economic expansionin the US over 1879–1940 were strongly linked to the exploitation of abundant non-reproduc-ible natural resources, particularly energy and mineral resources (Romer 1996; Wright 1990).Other examples of successful mineral-based development have been cited for today’s econo-mies (Davis 1995; Wright and Czelusta 2002). In the developing world, most prominent havebeen the mineral-led booms in the 1990s in Peru, Brazil and Chile, although Davis (1995)identifies up to 22 mineral-based developing economies who appear to have fared compar-atively well compared to other developing countries. In his review of 85 “resource-rich”developing economies, Gylfasson (2001) found only four to have performed successfully:Botswana, Indonesia, Malaysia and Thailand. Whereas the three Asian countries achievedthis success by diversifying their economies and by industrializing, Botswana still remainsfundamentally mineral-dependent.9

Recent reviews of successful resource-based development, both past and present, havepointed to a number of key features critical to that success (David and Wright 1997; Wrightand Czelusta 2002).

First, the given natural resource endowment of a country must be continuously expandedthrough a process of country-specific knowledge in the resource extraction sector. As argued

8 In fact, with over 50% of its population in fragile areas and with a rural poverty incidence of 19.2%, Yemenshows distinct signs of a rural poverty-resource degradation linkage. Indonesia is also not far off from satis-fying the “20–20 rule,” given that the country has over 20% of its population on fragile land and 15.7% of itsrural population in absolute poverty.9 However, Gylfason (2001, p. 566, n. 12) suggests that Indonesia should at best be considered only a qualifiedsuccess, given the widespread corruption in the country and because Indonesia has recovered much less wellfrom the 1997–1998 Asian crisis compared to Malaysia and Thailand.

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by Wright and Czelusta (2002, pp. 29 and 31): “From the standpoint of development policy,a crucial aspect of the process is the role of country-specific knowledge. Although the deepscientific bases for progress are undoubtedly global, it is in the nature of geology that loca-tion-specific knowledge continues to be important. . .the experience of the 1970s stands inmarked contrast to the 1990s, when mineral production steadily expanded primarily as a resultof purposeful exploration and ongoing advances in the technologies of search, extraction,refining, and utilization; in other words by a process of learning.”

Second, there must be strong linkages between the resource and other, more dynamiceconomic sectors (i.e., manufacturing). “Not only was the USA the world’s leading mineraleconomy in the very historical period during which the country became the world leaderin manufacturing (roughly from 1890 to 1910); but linkages and complementarities to theresource sector were vital in the broader story of American economic success. . .Nearly allmajor US manufactured goods were closely linked to the resource economy in one way oranother: petroleum products, primary copper, meat packing and poultry, steel works androlling mills, coal mining, vegetable oils, grain mill products, sawmill products, and so on”(Wright and Czelusta 2002, pp. 3–5). Similarly, Findlay and Lundahl (1999, pp. 31–32) notethe importance of such linkages in promoting successful “staples-based” development dur-ing the 1870–1914 era: “not all resource-rich countries succeeded in spreading the growthimpulses from their primary sectors. . .in a number of instances the staples sector turnedout to be an enclave with little contact with the rest of the economy. . .The staples theoryof growth stresses the development of linkages between the export sector and an incipientmanufacturing sector.”

Third, there must be substantial knowledge spillovers arising from the extraction andindustrial use of resources in the economy. For example, David and Wright (1997) suggestthat the rise of the American minerals economy can be attributed to the infrastructure ofpublic scientific knowledge, mining education and the “ethos of exploration.” This in turncreated knowledge spillovers across firms and “the components of successful modern-regimesof knowledge-based economic growth. In essential respects, the minerals economy was anintegral part of the emerging knowledge-based economy of the twentieth century. . .increas-ing returns were manifest at the national level, with important consequences for Americanindustrialization and world economic leadership” (David and Wright 1997, pp. 240–241).10

However, there are three important caveats attached to the above conditions for successfulresource-based development.

First, all of the past and present examples of development with the above three features areclearly based largely on minerals-based development (David and Wright 1997; Davis 1995;Wright and Czelusta 2002). A small open economy dependent on frontier agricultural landexpansion may find it more difficult to foster such conditions for successful resource-baseddevelopment. However, as we shall see in the next section, empirical evidence suggests thatLMICs that have expanding agricultural land frontiers and also increasing oil and naturalgas proved reserves appear to have performed less well than those economies where suchresource expansion has not occurred. It appears that a large number of today’s LMICs depen-dent on exploiting new land and resource “frontiers” are failing to meet the above conditionsfor resource-based development.

10 Wright and Czelusta (2002, p. 17) cite the specific example of the development of the US petrochemicalindustry to illustrate the economic importance of knowledge spillovers: “Progress in petrochemicals is anexample of new technology built on resource-based heritage. It may also be considered a return to scale atthe industry level, because the search for by-products was an outgrowth of the vast American enterprise ofpetroleum refining.”

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Second, the existence of policy and market failures in the resource sector, such as rent-seeking behavior and corruption or open-access resource exploitation, will mitigate againstsuccessful resource-based development. Unfortunately, it is well documented that resourcesectors in many developing countries are prone to problems of rent-seeking and corruption,thus ensuring that natural resource assets, including land, are not being managed efficientlyor sustainably (Ascher 1999; Barbier et al. 2005; Mehlum et al. 2006; Tornell and Lane2001; Torvik 2002).11 Several studies have noted the rent-dissipation effect of poorly definedproperty rights, including the breakdown of traditional common property rights regimes, indeveloping countries (Alston et al. 1999; Baland and Plateau 1996; Bromley 1989, 1991;Deacon 1999; Ostrom 1990). Recent empirical evidence confirms that greater dependencyon agricultural and raw material exports in developing countries as well as increased corrup-tion is directly associated with land conversion (Barbier 2004; Barbier et al. 2005). Mehlumet al. (2006) also show that resource abundance is inimical to growth with the presence of“grabber friendly” institutions that encourage rent-seeking behavior.

Third, there is also increasing evidence in developing countries that more powerful andwealthier groups use their social and economic power to secure greater access to valu-able environmental resources, including land, minerals, energy, gems, water and even fuel-wood, (Alston et al. 1999; Ascher 1999; Binswanger and Deininger 1997; Fairhead 2001;Homer-Dixon 1999; Lonegran 1999; Swain 2001). Such problems are exacerbated by gov-ernment policies that favor rent-seeking opportunities for the wealthy in markets for these keynatural resources, including land.12 For example, “rural elites” in developing countries areoften “able to steer policies and programs meant to increase rural productivity into capital-intensive investment programs for large farms, thus perpetuating inequality and inefficiency”(Binswanger and Deininger 1997, p. 1996). Similarly, Ascher (1999, p. 249) notes that “inthe oil and mining sectors, six policy failures predominate: very low accountability, unwiseinvestments within the sector, failure to minimize costs by state entities, inappropriate use ofproceeds outside of the sector, underexploitation by state entities due to their overcapitaliza-tion, and. . .underpricing of outputs when the product has significant domestic sales.”

Fourth, there may be important interactions between the “Dutch disease” effects of expand-ing export-based resource sectors, the counter-cyclical expansion of non-traded sectors, suchas food-based agriculture, and policy failures in resource sectors. According to Wunder(2003), this phenomenon is particularly relevant for oil producing tropical countries. Forexample, when a tropical country experiences an oil-price boom or discovers new oil reserves,there is a real appreciation of the booming country’s currency. This is also equivalent to aprice shift in favor of non-traded goods. The result is a “Dutch disease” effect, in that theoil and non-traded sectors of the economy expand at the expense of those facing declining

11 There is also an obvious link between rent-seeking activities in frontier areas and the lack of governmentenforcement of efficient regulation of these activities. For example, Ascher (1999, p.268) points out: “The weakcapacity of the government to enforce natural-resource regulations and guard against illegal exploitation is anobvious factor in many of the cases reviewed. In every case of land and forest use, illegal extraction and failureto abide by conservation regulations reduce the costs to the resource exploiter and induce overexploitation,while failing to make the exploiter internalize the costs of resource depletion and pollution.”12 Ascher (1999, p. 258) succinctly summarizes the incentive problem as follows: “The creation of rent-seeking opportunities at the expense of sound natural-resource exploitation arises for at least three reasons.First, government officials may offer rent-seeking opportunities in order to enlist the cooperation of state orextra-governmental actors in pursuit of ulterior objectives. In exchange for actions that help the policymakersaccomplish programmatic goals, the extra-governmental actors receive benefits as rewards and incentives.Second, the financial flows with which the state or extra-government actors are involved may give them theopportunity to capture some of the surplus. . .Third, programmatic distribution often drifts into rent-seeking.Even if subsidies or other special treatments are designed for a broad segment of potential beneficiaries, thebest-connected actors often end up with the bulk of the benefits.”

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competitiveness. In most tropical developing countries, the latter non-oil trade sectors aretypically agriculture, fisheries, forestry and non-oil mining, which are also the sectors mostassociated with forest conversion. As a consequence, a country with a large non-oil primaryproduct export sector is likely to experience a greater slow down in forest land conversionas a result of the rising terms of trade from an oil price boom. Wunder finds evidence of thisphenomenon in a study of eight tropical oil producing countries, all of which faced fewerpressures for conversion or degradation of their forests than non-oil producing countriesand experienced less forest loss during periods of oil booms.13 Wunder also suggests thatincreased corruption, rent-seeking behavior and policy failures may exacerbate this effectfor some oil-producing tropical countries. For example, if the terms of trade appreciationis due to an oil boom, then one consequence is higher rents in the oil and non-trade goodsectors. Corruptible officials will therefore be able to enrich themselves by diverting moreresources away from non-oil primary product sectors, including agriculture, that are mainlyresponsible for deforestation. The result is again a slowing down of cumulative agriculturalland expansion and forest conversion. There is some statistical evidence across all tropicalLMICs that countries with higher terms of trade may reduce the resource dependency effectson land expansion (Barbier 2004; Barbier et al. 2005). Moreover, the impact of a rise in theterms of trade in reducing cumulative land conversion is dissipated if the country is morecorrupt and amplified if there is less corruption.

The above conditions and caveats concerning successful resource-based development arecrucial factors in understanding why frontier resource extraction and land expansion in manypoor economies are symptomatic of a pattern and structure of economic activity that is notgenerating sustained growth. Below, we refer to this explanation as the frontier expansionhypothesis. Before elaborating on this hypothesis in more detail, let us first examine someempirical evidence linking land and energy reserve expansion and economic performance indeveloping countries.

4 Frontier resource expansion and economic performance: empirical evidence

So far, we have seen that frontier expansion in today’s developing countries is generally asso-ciated with land conversion, and much of this conversion is serving to absorb the rural poor.Moreover, unlike historical cases where exploitation of “new’ resources led to increasedeconomic development and growth, the economic benefits of frontier land and resourceexpansion today are largely short-lived, as such expansion reflects an economy-wide patternof resource-based development that is largely “unsustainable.” This would suggest that low-and middle-income countries that have experienced persistent expansion of agricultural landand other natural resource “reserves” over the long term are likely to have performed lesswell than countries that have been less reliant on land conversion.

A fairly straightforward way of empirically verifying whether frontier-based developmentis associated with poor economic performance is to estimate a relationship between grossdomestic product (GDP) per capita and some measure of long-run resource supply expansion.For example, if an indicator of long-run resource or “reserve” expansion is represented bysome index, αi t , then one could estimate a cubic relationship between per capita income, Yit ,and this indicator:

Yit = b0 + b1αi t + b2α2i t + b3α

3i t . (1)

13 The eight countries studied by Wunder (2003) were Cameroon, Ecuador, Gabon, Indonesia, Mexico,Nigeria, Papua New Guinea and Venezuela.

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Note that b0 > 0, b1 < 0, b2 > 0, b3 < 0 and |b1| > b2 would imply that (i) countries withlong-run increased land or resource reserves would have lower levels of per capita incomethan countries with decreased reserves and (ii) per capita income may fluctuate with long-runreserve expansion, but any such increase in income is short-lived.

Barbier (2003, 2005b) estimated the above relationship (1) through employing a panelanalysis of 78 tropical low- and middle-income countries (LMICs) over 1961–1994. In theanalysis, per capita income, Yit , was represented by GDP per capita in constant purchasingpower parity (1987 $), and the indicator αi t represented an agricultural land long-run changeindex. This indicator was created by dividing the current agricultural land area of a country(i.e., in year t) by its land area in the base year 1961. The results of the analysis for all78 tropical LMICs and for a sub-set of poorer countries (i.e., real per capita GDP less than$3,500 over 1961–1994) confirmed that all the estimated coefficients for equation (1) had theexpected signs and the relative magnitudes. That is, an increase in agriculture land expansionin the long run for these countries is clearly associated with a lower level of per capita income,and although after certain turning points in long-run agricultural land expansion (αi t = 1.2for all tropical LMICs and αi t = 1.3 for poorer tropical LMICs) there is a slight increase inreal GDP per capita, this impact is short-lived. For all tropical countries, per capita incomefalls again once the land area index reaches 2.3; for poorer countries this occurs sooner atan index of 1.9. In fact, for the poor tropical LMICs, GDP per capita remains fairly constantover the 1.3 to 1.9 range of αi t .

In this section, the empirical analysis of frontier expansion and economic performance inLMICs is extended and improved in the following three ways.

First, the previous analysis by Barbier (2003, 2005b) of applying (1) to long-run agricul-tural land expansion is updated to 1961–2001 and broadened to include not just tropical lowand middle-income countries but all LMICs in Africa, Asia and Latin America.

Second, following Findlay and Lundahl (1999, p. 26), in addition to applying (1) to a“horizontal” frontier, such as land and agriculture, the relationship should also be applied toan important “vertical” frontier in many LMICs, such as proved reserves of oil and naturalgas.

Finally, because estimating Eq. 1 may encounter problems of endogeneity and omittedvariable bias, the estimation should include procedures for testing and correcting for theseproblems. For a single-equation panel analysis model such as (1), the standard Hausman–Tay-lor procedure for testing and correcting problems of endogeneity and omitted variable biaswas employed (Hausman and Taylor 1981; Baltagi and Khanti-Akom 1990; Baltagi 2001;Metcalf 1996). The appendix to the paper explains this procedure in the case of estimatingrelationship (1) for both agricultural land expansion and oil and natural gas proved reserveexpansion. The results of these two estimations are discussed in turn.

4.1 Long-Run Agricultural Land Expansion in LMICs

Equation 1 was applied to long-run agricultural land expansion through employing a panelanalysis of 105 low- and middle-income countries from Africa, Asia and Latin America over1961–2000. In this analysis, per capita income, Yit , is represented by real gross domesticproduct (GDP) per capita (1995 $). The indicator αi t is an agricultural land long run changeindex, created by dividing the current (i.e., in year t) agricultural land area of a country byits land area in 1961.14

14 The data used in this analysis are from the World Bank’s World Development Indicators.

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The appendix to this paper describes the Hausman–Taylor procedure for testing and cor-recting for possible endogeneity and omitted variable effects in this estimation (See alsoBaltagi 2001, pp. 118–124). To conduct this procedure, three additional variables were in-cluded in the regression of (1); these were: rural population as a percentage of total population,a measure of trade openness and the distance of each country from the equator. As discussedin the appendix, the Hausman–Taylor procedure involves comparing the fixed and random ef-fects versions of the panel analysis of the full model with the additional exogenous variables,as well as using the exogenous variables as instruments in a Hausman–Taylor model. Theresults of the panel analysis are shown in Table 2.15 For the three regressions, the estimatedcoefficients of b1, b2 and b3 in Eq. 1 are highly significant, and also display the expectedsigns and relative magnitudes. In addition, as the magnitude of these estimated parametersvary only slightly across the three regressions, these estimates are extremely robust. Thus,the results of the panel analysis imply that one cannot reject the hypothesis that developingcountries that have experienced agricultural land expansion since 1961 display lower levelsof real GDP per capita compared to countries whose agricultural land areas have contracted.

The latter outcome is seen more clearly when the regressions are used to project respectiverelationships between long run agricultural land expansion and GDP per capita, which aredisplayed in Fig. 2. As indicated in the figure, an increase in agricultural land expansion inthe long-run is clearly associated with a lower level of per capita income than decreasingagricultural land area. For all developing countries that have experienced an increase in landarea over 1961 levels (index level 1), GDP per income per capita is lower as expansionincreases, until the turning point in the long run agricultural change index of 2.3 is reached.Although continued agricultural land expansion beyond this point is associated with a slightincrease in GDP per capita, this impact is short-lived. Per capita income starts to fall againonce the land area index reaches 3.8.

It is revealing to compare the projections in Fig. 2 with the actual land use situation in 2000for all 105 LMICs from Africa, Asia and Latin America. For all countries in 2000, the averageland expansion index was 1.96, and the median was 1.61. Moreover, 36 of the 105 low- andmiddle-income countries had a long run land expansion index of 2 or higher, and 10 coun-tries had a land expansion index of 4 or higher. In comparison, 10 countries had a long-runagricultural land expansion index less than one, suggesting a decline in agricultural land over1961–2000. Thus, it is fair to say that for the majority of today’s developing countries long-runagricultural land conversion appears to be associated with lower GDP per capita levels.

15 As explained in the appendix, the first step in this procedure is to estimate Eq. 1 for the analysis of long-runagricultural land expansion using both fixed and random effects panel analysis. The Hausman test based onthe difference between the fixed and random effects estimation yields a value of 11.93, which for a chi-squaredistribution with three degrees of freedom is significant at the 95% confidence level. Although this test rejectsthe hypothesis of no correlation between the individual effects and the explanatory variables, one cannotdistinguish whether correlation may arise through the possible endogeneity of the αi t terms in (1) or throughomitted variables. Thus the next step is to estimate and compare three regressions: a random effects estimationof the full model of (1) including the additional explanatory variables (rural population share, trade opennessand distance from equator); a fixed effects estimation of the full model and a Hausman–Taylor random effectsestimation with the additional explanatory variables used as instruments for the suspected endogenous αi tterms in (1). The results of these three estimations of the full model are shown in Table 2. The Hausman testbased on the difference between the fixed and random effects estimation of the full model yields a value of 1.28,which is not significant. Thus the hypothesis of no correlation of the αi t terms or the additional explanatoryvariables with the individual effects cannot be rejected. The Hausman test based on the difference betweenthe Hausman–Taylor instrumental variable random effects estimation and the fixed effects estimation yieldsa value of 9.8, which is also not significant. Moreover, the parameter estimates for the random effects, fixedeffects and Hausman–Taylor regressions of the full model of (1) do not vary significantly, which suggests thatthese estimates are highly robust.

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Table 2 Panel analysis of per capita income and long run agricultural expansion in low and middle-incomecountries, 1961–2000

Explanatory variables Dependent variable: GDP per capita (constant 1995 $)a

Parameter Estimates:b

Random effectsmodel (N = 3, 319)

Fixed effects model(N = 3, 319)

Hausman–Taylormodel (N = 3, 319)

Constant 5532.40 – 5531.53(17.66)∗∗ – (16.36)∗∗

Long run agricultural landarea change index (αi t )

c−2211.21 −2237.98 −2208.06

(−11.93)∗∗ (−11.32)∗∗ (−11.38)∗∗α2

i t 775.90 786.99 774.60(10.66)∗∗ (10.18)∗∗ (10.15)∗∗

α3i t −85.01 −86.28 −84.86

(−9.86)∗∗ (−9.45)∗∗ (−9.39)∗∗Rural population −43.82 −43.56 −43.85(% of total population) (−27.79)∗∗ (−25.44)∗∗ (−26.61)∗∗Trade Openness 5.01 4.90 5.02(Exports + imports %GDP)

(9.53)∗∗ (8.78)∗∗ (9.12)∗∗

Distance from equator 7.81 – 7.80(measured in absolute de-grees)

(0.63) (0.64)

F-test for pooled model – 176.10∗∗ –Breusch–Pagan (LM) test 39588.22∗∗ – –Hausman test 1.28 – 9.80Adjusted R2 – 0.916 –

Notes: a The mean for all countries over 1961–2000 is $1,558; the median is $822b t-ratios are indicated in parentheses.c Mean for all countries over 1961–2000 is 1.42; the median is 1.20.∗∗Significant at 99% level, ∗significant at 95% level.

0

500

1,000

1,500

2,000

2,500

3,000

3,500

0 1 2 3 4 5 6

Agricultural land long-run change index

GD

P p

er c

apit

a ($

199

5)

1.961.61

Fig. 2 Agricultural land expansion and GDP per capita in low and middle-income countries, 1961–2000

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4.2 Long-Run Proved Oil and Natural Gas Reserve Expansion in LMICs

Equation 1 was also applied to oil and natural gas proved reserve expansion by employinga panel analysis of 41 low- and middle-income countries from all regions of the world over1980–2001. In this analysis, per capita income, Yit , is again represented by real gross domes-tic product (GDP) per capita (1995 $). The indicator αi t is an oil and natural gas provedreserve long run change index, created by dividing the current (i.e., in year t) oil and naturalgas proved reserves of a country by its reserves in 1980.16

Once again, the Hausman–Taylor procedure for testing and correcting for possible endo-geneity and omitted variable effects in this estimation was employed (see the Appendix), withrural population share, trade openness and distance from equator as the exogenous variablesused as instruments. However, in this case, fixed effects estimation was always preferredto random effects and Hausman–Taylor estimation of (1). In addition, the restricted modelwith the coefficients b2 = b3 = 0 is always the preferred specification of the fixed effects.17

Table 3 displays the results for the unrestricted fixed effects full model, the restricted fixedeffects full model and the Hausman–Taylor instrumental variable estimation. The preferredmodel is the two-way restricted fixed effects model, which confirms that b1 < 0 and that thisrelationship between income per capita and long-run changes in oil and natural gas reservesappears to be linear. Thus, one cannot reject the hypothesis that LMICs that have experiencedan increase in their proved reserves of oil and natural gas display lower levels of real GDPper capita compared to countries whose reserves have declined.

Figure 3 displays the projections of the estimated relationship between long run oil natu-ral gas reserve expansion and GDP per capita. As indicated in the figure, across LMICs realincome per capita falls as proved oil and natural gas reserves increase. For all developingcountries that have experienced an increase in reserves over 1980 levels (index level 1), realGDP per capita is lower.

16 The data used in this analysis are from the World Bank’s World Development Indicators, except for thedata on proved oil and natural gas reserves, which are from the BP Statistical Review of World Energy. Provedoil reserves are generally taken to be those quantities that geological and engineering information indicateswith reasonable certainty can be recovered in the future from known reservoirs under existing economic andoperating conditions. Both oil and natural gas proved reserves are measured in terms of 1,000 million barrelsof oil equivalent.17 The Hausman test of the fixed and random effects estimation of (1) applied to proved oil and natural gasreserves across LMICs over 1980–2001 was 58.05, which is significant at the 99% confidence level. This leadsto rejection of the hypothesis of no correlation between the individual effects and the explanatory variables.However, for the fixed effects model of (1) the F-test of the null hypothesis that b1 = b2 = b3 = 0 wassignificant, suggesting that the null cannot be rejected. Once again, three regressions of the full model of (1)including additional explanatory variables were compared: a random effects estimation including the addi-tional explanatory variables (rural population share, trade openness and distance from equator); a fixed effectsestimation of the full model and a Hausman–Taylor random effects estimation with the additional explanatoryvariables used as instruments for the suspected endogenous αi t terms in (1). Both Hausman tests based onthe difference between the fixed and random effects estimation of the full model yields a value of 38.8, whichis significant. Thus the hypothesis of no correlation of the αi t terms or the additional explanatory variableswith the individual effects can be rejected. As indicated in Table 3, the Hausman test based on the differencebetween the Hausman–Taylor instrumental variable random effects estimation and the fixed effects estimationalso yields a value of 38.8, which is also significant. This suggest that fixed effects of the full model is boththe most consistent and efficient estimator. As indicated in Table 3, the likelihood ratio test for the restrictedmodel with b2 = b3 = 0 cannot be rejected, indicating the two-way fixed effects linear model specification of(1) shown in Table 3 is the preferred model. Finally, the Granger causality Hausman test of the null hypothesisthat αi t is exogenous yields a value of 0.379, which is not significant, indicating that the null hypothesis cannotbe rejected.

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Table 3 Panel analysis of per capita income and long-run oil and natural gas proved reserve expansion in lowand middle income countries, 1980–2001

Explanatory Variables Dependent variable: GDP per capita (constant 1995 $)a

parameter Estimates:b

Unrestricted fixedeffects modelc(N =699)

Restricted fixed ef-fects modelc(N =699)

Hausman–Taylormodel (N = 699)

Constant 1053.57 1040.23 1798.27(3.69)∗∗ (3.68)∗∗ (4.25)∗∗

Long run oil and naturalgas proved reserve changeindex (αi t )

d

−8.72(−0.80)

−3.68(−2.13)∗

−8.56(−0.82)

α2i t 0.06 – 0.09

(0.34) (0.48)α3

i t −0.0002 – −0.0003(−0.24) (−0.40)

Rural population 12.69 12.69 −7.73(% of total population) (2.26)∗ (2.26)∗ (−2.44)∗Trade Openness 7.21 7.22 8.03(Exports + imports %GDP)

(7.94)∗∗ (7.96)∗∗ (9.56)∗∗

Distance from equator(measured in absolutedegrees)

– – –0.94(−0.07)

F-test for pooled model 143.82∗∗ 144.24∗∗ –LR-test for restrictedmodele

– 0.006 –

Breusch–Pagan (LM) test – – 5067.00∗∗Hausman test – – 38.834∗∗Exogeneity test for αf

i t – 0.379 –Adjusted R2 0.965 0.965 –

Notes: a The mean for all countries over 1980–2001 is $2,003; the median is $1,380.b t-ratios are indicated in parentheses.c Two-way model with individual and time effects.d The mean for all countries over 1980–2001 is 5.27; the median is 1.50.e Likelihood ratio test of the null hypothesis that α2

i t = α3i t = 0.

f Hausman test of the null hypothesis that αi t is exogenous.∗∗ Significant at 99% level, ∗ significant at 95% level.

For 44 LMICs in 2004, the average oil and natural gas proved reserve expansion indexwas 11.33 and the median was 2.44.18 In addition, in 2004 16 out of the 44 countries hada long-run reserve expansion index of 3 or higher, and nine had an index of 5 or higher. Incontrast four countries had a long run reserve expansion index of less than one, suggesting adecline in reserves. Thus the vast majority of developing countries with proved oil and naturalgas reserves experienced expansion of those reserves over 1980–2004, and the expansion inthis “vertical” frontier appears to be associated with lower GDP per capita levels.

18 Iran, Iraq and Myanmar could not be included in the cross-country panel analysis because of data gaps forother economic variables in the estimation, even though these countries do have data on proved oil and naturalgas reserves over 1980–2004.

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2,030

2,040

2,050

2,060

2,070

2,080

2,090

2,100

2,110

2,120

0 5 10 15 20 25

Proved oil and gas reserves long-run change index

GD

P p

er c

apit

a (1

995

$)

11.332.44

Fig. 3 Oil and natural gas proved reserve expansion and GDP per capita in low and middle-income countries,1980–2004

5 The frontier expansion hypothesis

Having provided “stylized facts” as well as some empirical evidence that frontier land expan-sion is symptomatic of a pattern of resource-based development that is not sustainable in manypoor economies, we now must try to explain why. Here, we can only sketch out the main fea-tures of this frontier expansion hypothesis. This hypothesis is based on four key observations(Barbier 2003, 2005b).

First, frontier land expansion and resource exploitation may be associated with poor eco-nomic performance in resource-dependent developing countries but not necessarily a cause ofit. That is, frontier expansion is symptomatic of a pattern of economy-wide resource exploi-tation that: (a) generates little additional economic rents, and (b) what rents are generatedare not being reinvested in more productive and dynamic sectors, such as manufacturing.

Second, one important reason that frontier land expansion is unlikely to generate muchrents is that, as such expansion results largely from conversion of forest, wetlands and othernatural habitat, it is likely to yield mainly “marginal” or “fragile” land exhibiting low pro-ductivity as well as significant constraints for intensive agriculture (World Bank 2003). Thisin turn implies that very little effort is invested, either by poor farmers working this landor government agricultural research and extension activities, in developing country-specificknowledge in improving the productivity and sustainable exploitation of frontier land andresources.

Third, in contrast to past and present examples of successful minerals-based development,there are unlikely to be strong linkages between more dynamic economic sectors (i.e., man-ufacturing) and the economic activities responsible for frontier land and resource expansion(Wright and Czelusta 2002). This in turn limits the opportunities for substantial knowledgespillovers arising from the exploitation and conversion of frontier resources, including land.Thus frontier-based economic activities are unlikely to be integrated with the rest of theeconomy. There are several reasons for this. First, as noted above, frontier land expansionappears to be serving mainly as an outlet for the rural poor in many developing countries,which suggests that much of the output is either for subsistence or local markets. Second, bydefinition, frontier areas are likely to be located far away from urban and industrial centers.

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Third, large concentrations of “frontier” extractive mineral and energy reserves are oftenappropriated as “export enclaves” separate from the rest of the economy.

Fourth, as discussed previously, the resource sectors of many developing economies are rifewith widespread policy and market failures, such as distorted markets, rent-seeking behavior,corruptionandopen-accessexploitation.Manyoftheseconditionsarecumulativeandself-rein-forcing.Forexample,manylarge-scaleresource-extractiveactivitiessuchastimberharvesting,mining,ranchingandcommercialplantations,areoftenresponsiblefor initiallyopeninguppre-viously inaccessible frontier areas (Barbier 2005b). Investors in these activities are attracted tofrontier areas because of the lack of government controls and property rights in these remoteareas mean that resource rents are easily captured, and thus frontier resource-extractive activi-ties are particularly prone to rent-seeking behavior (Ascher 1999). Small-scale farmers usuallyfollow because forest and other land is now readily available for conversion, and open accessconditions facilitate the conversion (Alston et al. 1999; López 1998).

All of these factors combine to ensure that frontier-based economic development is un-likely to lead to high rates of sustained economic growth. In essence, all frontier resources,including land in forests and wetlands, are “reserves” that can be exploited potentially foreconomic rents. However, as we have seen, conversion of frontier land “reserves” producesmainly fragile agricultural land that is largely an outlet for absorbing poor households. Suchfrontier land expansion does not generate substantial rents, and any resulting agriculturaloutput will increase mainly consumption of non-tradable goods (food for subsistence orlocal markets). Frontier resource-extractive activities may yield more significant rents, butthe rent-seeking behavior associated with these activities will mean that these rents will bereinvested into further exploitation of frontier resources. This process will continue until theeconomically accessible frontier resource “reserves” are exhausted and all rents are dissi-pated. Finally, the lack of integration of frontier-based economic activities with the rest ofthe economy also decreases the likelihood that any rents generated by these activities will bereinvested in more productive and dynamic sectors, such as manufacturing.

In essence, the frontier sector operates as a separate “enclave” in the developing econ-omy.19 Increased land expansion and extractive mineral and other reserves may lead to highercurrent rents and income levels, at least for the wealthiest individuals, but not to increasedsaving and investment for long-term economic development. Where substantial rents areearned, especially in the case of mineral and energy reserves, they are often dissipated throughrent-seeking, corruption, political lobbying and other “unproductive” activities. In most lowand middle-income countries, frontier expansion appears to be a symptom of unsustainableresource-based development, not a solution.

6 Final Remarks

Ever since “sustainable development” became a popular policy “buzzword,” economistshave tended to disagree over how natural capital should be managed to achieve this goal

19 Barbier (2005a) develops a formal model that includes several (but not all) of the key features of frontierland expansion and resource exploitation described above. These features are: (i) frontier activities are notintegrated with other sectors of the economy; (ii) frontier activities serve mainly to absorb labor; i.e., theonly inputs are converted resources and labor, and the latter is increasing over time; (iii) frontier resourcesare freely available; the only limitations on their conversion are institutional, economic and geographicalconstraints (e.g., distance to markets) that limit the maximum amount of conversion; (iv) if no profits aremade, then frontier households consume all their factor income, and no rents are available to re-invest in thefrontier activities; and (v) capital accumulation will occur in the economy if aggregate output, including fromthe frontier sector, exceeds domestic consumption and exports.

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(see Fig. 1). An important legacy left by David Pearce is to point out that, regardless ofwhether one adheres to the “weak” or “strong” view of sustainability, the starting point mustbe efficient management of natural capital to maximize the rents that it yields and investingthese rents in other productive assets of the economy (Pearce et al. 1989, 1990; Pearce andBarbier 2000). This principle must hold true for all economies, regardless of their level of eco-nomic development, but especially for low- and middle-income countries that are dependenton exploiting their available land and resource endowments to accelerate economic growth,poverty alleviation and enhanced social welfare.

This paper has argued that, just as in past decades, most poor countries today appear to relyon finding new “frontiers” or “reserves” of natural resources and land to exploit as the basisof their long-term development efforts. Unfortunately, such resource-based development hasproven to be largely unsustainable. This paper has sought to explain why this is the casefirstly, by examining the conditions for “successful” resource-based development and whythey have proven so difficult to achieve in many low- and middle-income countries (LMICs)today; secondly, by providing empirical evidence that long-run agricultural land and oil andnatural gas proved reserve expansion is associated with lower levels of real GDP per capitain LMICs; and finally, by articulating a “frontier expansion hypothesis” as to why frontierexpansion in LMICs is not generating long-term economy-wide benefits.

One should be cautious in interpreting the empirical evidence presented in this paper,however. First, the purpose of the econometric analysis is not to explain differences in percapita income across LMICs but to test for a possible negative association between levels ofGDP per capita and some long-run index of agricultural and reserve expansion across thesecountries. With the latter aim in mind, Eq. 1 is the correctly specified model to estimate,and equally important, the Hausman–Taylor procedure outlined in the appendix is crucial totesting for possible endogeneity effects and omitted variables, as well as for examining therobustness of the specification of the underlying model. Nevertheless, based on the simpleempirical relationship (1) tested in this paper, one should refrain from drawing strong con-clusion concerning the causes of frontier expansion and resource exploitation in developingeconomies.

For instance, one might be tempted to argue that, if agricultural land expansion is mainlyby the rural poor, then the empirical results for long-run agricultural land expansion simplyconfirm that more poverty in developing economies tends to be associated with lower percapita income. Such an interpretation is not correct, however. It is true that I have arguedthat frontier land expansion often serves as an “outlet for the rural poor” in many LMICs.However, one should not infer from this observation that a higher incidence of poverty is anunderlying cause of such land expansion. The rural poor may be displaced to frontier areasand marginal lands because they cannot compete with wealthier households for existing,more fertile agricultural land. Specific government policies such as “opening up” inaccessi-ble forest areas and planned settlements may also encourage the migration of the rural poorto frontier areas. Thus, it is misleading to conclude that frontier land expansion is alwayscaused by rising rural poverty, let alone rising incidences of general poverty, in developingcountries, and to draw such a conclusion from this paper is clearly a misinterpretation of itsempirical analysis.

Equally, I have been careful in this paper first to present the empirical evidence linkingfrontier land and resource expansion with lower levels of income per capita in developingcountries, and then to outline the “frontier expansion hypothesis” as a possible explanationof this relationship. The empirical analysis may be one way of testing whether frontier-baseddevelopment is associated with poor economic performance in today’s LMICs, but the analy-sis falls well short of testing the frontier expansion hypothesis itself. Verifying (or falsifying)

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the four key observations underlying this hypothesis will require more in-depth empiricalanalysis that is beyond the scope of the present paper.

Finally, if resource-dependent development in poor economies is associated with frontierland expansion and resource exploitation, then the critical issue for these economies is howto make such development more sustainable. As this paper has made clear, the key stepswill be improving the economic integration between frontier and other sectors of the econ-omy, targeting policies to improved resource management in frontier areas, economy-widereforms that benefit poorer rural households and overcoming problems of corruption and rent-seeking in resource sectors. Although the vast majority of resource-dependent LMICs haveyet to achieve success in these areas, elsewhere I have identified three modern success sto-ries—Botswana, Malaysia and Thailand—that have made substantial progress toward moresustainable resource-based development (Barbier 2005b). Malaysia and Thailand appear tohave harnessed their respective natural resource endowments to diversify their economiessuccessfully. Botswana has utilized its mineral wealth for high rates of sustained economicgrowth through a consistent policy of capturing and reinvesting resource rents. Interestingly,all three “resource-rich” LMICs have achieved their success through exploiting very differentnatural endowments. In Malaysia, the main source of resource rents has come from petro-leum and timber, and more recently, plantation crops; for Thailand, it has been exports offood, plantation crops and fisheries; and for Botswana diamonds and other minerals. Theseexamples suggest that neither the abundance of natural resource wealth nor the type of endow-ment—“horizontal” or “vertical” frontiers—need be an obstacle to constructing policies forsustainable economic development.

In examining the unique historical success of resource-based development in the UnitedStates, Wright (1990, p. 666) suggests that “there is no iron law associating natural resourceabundance with national industrial strength.” Although this paper has attempted to explainwhy so many resource-dependent LMICs continue to perform relatively poorly, the examplesof Botswana, Malaysia and Thailand illustrate that there is also no “iron law” associatingnatural resource abundance, or even a particular type of resource endowment or “frontier” toexploit, with poor economic performance.

Acknowledgements I am grateful for the comments of David Aadland, Ian Bateman, Dan Bromley, MitchKunce, Ramón López, Chuck Mason, Joe Stiglitz, Michael Toman and an anonymous reviewer, as well asfor the research assistance of Tessa Leonce. An earlier version of this paper was presented as the BenjaminH. Hibbard Memorial Lecture, Department of Agricultural & Applied Economics, University of Wisconsin-Madison, April 4, 2003. I am indebted to the Department of Agricultural & Applied Economics, Universityof Wisconsin, Madison for inviting me to present the Hibbard Lecture.

Appendix

The Hausman–Taylor procedure for testing and correcting for possible endogeneity and omit-ted variable effects in a panel analysis is summarized in Baltagi (2001, pp. 118–124). Thisapproach was followed to estimate (1) in the two applications of this paper, where indicator∀i t is an agricultural land long run change index and where it is a long run oil and naturalgas proved reserve index. The purpose of this appendix is to outline the general steps of theHausman–Taylor procedure used in both of these estimations.

The first step in this procedure is to estimate Eq. 1 using both fixed and random effectspanel analysis. The random effects model does not account for the possible correlation of theexplanatory variables with the individual effects that might arise through the endogeneity ofthe αi t terms in (1) or the possibility of omitted variables that might also be correlated with

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individual effects. However, the fixed effects specification is still a consistent estimator of (1)even if such correlation occurs because the within transformation eliminates the individualeffects from the model. Consequently, a Hausman test based on the difference between thefixed and random effects estimation of (1) tests for the null hypothesis of no correlationbetween the individual effects and the explanatory variables, i.e., the αi t terms in (1).

The second step in the Hausman–Taylor procedure is to include additional explanatoryvariables in the panel analysis regression of (1), which could also be used as possible instru-mental variables if the αi t terms are endogenous. These include an additional set of exoge-nous time-varying explanatory variables and an additional set of exogenous time-invariantexplanatory variables. Three regessions are then estimated and compared: a random effectsestimation of the full model of (1) including the additional explanatory variables; a fixedeffects estimation of the full model and a Hausman–Taylor random effects estimation withthe additional explanatory variables used as instruments for the suspected endogenous αi t

terms in (1). The Hausman test based on the difference between the fixed and random effectsestimation of the full model of (1) again tests for the null hypothesis of no correlation betweenthe individual effects and the explanatory variables. The Hausman test based on the differencebetween the Hausman–Taylor instrumental variable random effects estimation and the fixedeffects estimation is a test of whether the set of exogenous variables used as instruments islegitimate.

Choosing the appropriate number and type of additional exogenous variables that couldalso serve as possible instruments is critical. The order condition for identification requiresthat at least one time-varying exogenous variable must be included; the Hausman–Taylorprocedure also requires including at least one time-invariant exogenous variable. However,Metcalf (1996) has shown that, although including more instruments leads to more efficientestimators, the asymptotic bias of the less efficient estimator will also be greater as the nullhypothesis of no correlation is violated. This implies that adding more instruments couldreduce unnecessarily the power of the Hausman specification test of this null hypothesis.Thus, it was decided in both estimations of (1) to limit the number of instruments to twotime-varying and one time-invariant exogenous variables. As to the choice of these variables,Rodrik et al. (2004) review the empirical growth literature and identify international tradeand geography as two important broad determinants of differences in average income levels.The authors suggest that a common explanatory variable for the former is a measure of tradeopenness of a country, and for the latter, distance of a country from the equator. For thesecond, time-varying exogenous variable it seemed appropriate to choose another structuralindicator unrelated to international trade, such as the degree to which “labor surplus” con-ditions prevail in a developing economy. The variable chosen was the share of the rural intotal population. Hence, as the results in Tables 2 and 3 indicate, the Hausman–Taylor esti-mations of (1) include two exogenous time-varying explanatory variables (rural populationas a percentage of total population and a measure of trade openness) and one exogenoustime-invariant explanatory variable (the distance of each country from the equator).

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