Giorgia Giovannetti (University of Firenze and European University

Institute)

Elisa Ticci (University of Siena)

AFRICA’S BIOENERGY POTENTIAL: A NEW RESOURCE CURSE?

16th ICABR Conference June 24-27, 2012

Outline of the presentation

Africa’s biofuel energy potentialThe state of biofuel development in the

continentEconometric estimates of drivers of large

scale land FDI for biofuel crops in SSAConclusions

Africa’s biofuel energy potential

Africa accounts for the largest share of the world’s non protected grassland and woodland areas potentially suitable for biofuel feedstocks

Southern Africa has been described as a potential ‘Middle East of biofuels’

National plans to support biofuel sector in Ghana, Angola, Mozambique, Nigeria, South Africa, Tanzania, Zambia, Zimbabwe, Uganda, Benin, Mali, Malawi, Senegal

0

100

200

300

400

500

600

700

800

Sugarcane Maize Cassava Soybean Jatropha

Potentials for currently grassland and woodland (Mha)

North America, Europe and Russia Asia and Pacific LAC Africa

Source: IIASA 2009

The state of biofuel development in SSA

Sources of data and information Case studies Global Biofuel Information Tool of the Center for

International Forestry Research Renewable Fuels Association Land Matrix

The state of biofuel development in SSA/1

Great investors’ interest: SSA accounts for more than half of worldwide farmland area involved in large scale land deals for biofuel crops since 2001

Large land deals for crops than can be used as biofuel feedstocks by region

0

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000

12,000,000

14,000,000

0

50

100

150

200

250

Hectares

Number of deals

Source: authors’ elaborations based on Land Matrix

The state of biofuel development in SSA/2

The role of Africa in the biofuel market is expected to increase, but so far it has been marginal.

Fig: World fuel ethanol production in 2006, million liters

Asia, 6961

Australia, 149

Europe, 4631

North and Central America, 20933

Oceania, 24

South America, 17756

Egypt , 30Kenya , 17

Malawi , 15Mauritius, 9

Nigeria, 30

South Africa , 388

Swaziland , 17

Zimbabwe , 25

Other, 75Africa, 606

Authors' elaboration from F.O. Licht estimates reported in Renewable Fuels Association (2007)

The state of biofuel development in SSA/3

Future trends are very uncertain, problems in the start-up of the production.

Main barriers include: local resistance financial problems unexpected technical difficulties uncertain market and regulatory conditions long lag between investment and production building capacity in proper planting, caring and processing

is crucial but it is expensive and takes time small farmers report low yields, processing difficulties,

problems with pests and in accessing inputs (Mozambique, Swaziland, Kenya)

The state of biofuel development in SSA/4

Only first-generation biofuels

In most cases, biofuel projects are large-scale commercial plantations financed by big corporations

According to data from Global Biofuel Information Tool of the Center for International Forestry Research (CIFOR-GBIT), about nine to ten biofuel investments recorded in 22 Sub-Saharan African countries until 2011 (181 projects) have been planned for cultivation, and only ten percent are under outgrowing schemes.

The state of biofuel development in SSA/5

Foreign based investments are a very important component of biofuel projects in Sub-Saharan Africa

Planned and executed biofuel investments. Area of land accessed (in ha)

Source: Authors’ elaboration from CIFOR - GBIT

0

200000

400000

600000

800000

1000000

1200000

Foreign, non OECD Foreign, OECD National Foreign OECD + non OECD

The drivers of land FDI for biofuel investments in SSA

Focus on land demand for biofuel crops

Dependent variable: number of deals concluded in SSA since 2001 with the purpose to cultivate crops that can be used as biofuel feedstocks (Land Matrix)

Gravity model framework

Zero-Inflated Poisson model: in the first stage a logit regression estimates the probability that land FDI for biofuel projects are not affordable or profitable. The second stage estimates the potential count of land investments for the pairs of countries with a non-zero probability of concluding an international land deal.

Logit component (probability to encounter zero-values)

Poisson regression component

Biofuel producer (-)Regional dummy:

Gulf States (+), High income OECD

countries (-) Emerging economies

(-) Land scarcity (-)

Bilateral variables Distance (-) Past colonial ties (+)

Origin country variables Population (+) Per capita agricultural imports (+)

Destination country variables freshwater resources (+) Agricultural land (+) Land governance (-) Public land (+) General institutional conditions (?)

Independent variables (and expected sign)

Related literature

Arezki, Deininger and Selod (2011): Main findings: negative and hardly significant effect of

conventional governance variables, robust and negative effect of land governance, positive role of land availability.

Main differences with respect to our estimates: Data source for the number of land deals Different focus: biofuel crops and SSA Slightly different econometric technique: ZIP vs standard

Poisson Closer attention to the role of land governance and

water-seeking behavior

Logit regression

A B C D E F G

High income OECD countries

-1.646** -1.717** -1.680** -1.649** -1.656** -1.636* -1.626**

(0.672) (0.668) (0.687) (0.670) (0.667) (0.848) (0.667)

Emerging countries -2.635*** -2.663*** -2.658*** -2.643*** -2.644*** -2.654*** -2.631***(0.646) (0.651) (0.654) (0.641) (0.648) (0.766) (0.645)

Gulf countries -0.464 -0.568 -0.521 -0.455 -0.485 -0.464 -0.416(1.151) (1.159) (1.162) (1.146) (1.156) (1.195) (1.151)

Land scarcity (dummy) -1.720*** -1.731*** -1.721*** -1.711*** -1.720*** -1.695*** -1.722***(0.500) (0.499) (0.502) (0.498) (0.502) (0.498) (0.504)

Biofuel producer -19.37*** -38.96*** -17.41*** -22.43*** -34.52*** -9.852 -19.20***(1.305) (0.882) (4.264) (1.875) (1.359) (66.22) (1.268)

Constant 5.555*** 5.665*** 5.492*** 5.546*** 5.453*** 5.576*** 5.355***(0.786) (0.813) (0.813) (0.760) (0.774) (0.823) (0.766)

Observations 4622 4622 4622 4468 4468 4468 4468Log pseudo-likelihood -233.3 -233.3 -226.7 -233.1 -229.4 -235.5 -227.7

Notes: Independent variables with negative coefficient estimates are associated with an increase in the probability of biofuel land deals Robust standard errors. * p < 0.10, ** p < 0.05, *** p < 0.01.

Poisson regression component – bilateral variables and country-of-origin variables

A B C D E F G

Bilateral variables Colonial relationship

0.428 0.494 0.573* 0.397 0.560* 0.462 0.521*

(0.327) (0.343) (0.316) (0.314) (0.338) (0.349) (0.313)

Distance -0.603** -0.440 -0.475* -0.633*** -0.515** -0.629*** -0.642***(0.256) (0.290) (0.245) (0.237) (0.262) (0.239) (0.227)

Origin country variables Population 0.303** 0.268* 0.290** 0.309** 0.300** 0.302* 0.333**

(0.146) (0.147) (0.144) (0.142) (0.143) (0.183) (0.138)

Per capita agriculture imports

0.402*** 0.341** 0.381*** 0.418*** 0.398*** 0.427** 0.441***

(0.147) (0.139) (0.138) (0.147) (0.138) (0.191) (0.136)

Poisson regression component –destination country variablesA B C D E F G

Agricultural land (ha) 0.398** 0.414** 0.269*

Potential non forest land 0.323** 0.466*** 0.419*** 0.302**

Freshwater resources 0.103 0.179* 0.283**

Rural population density 1.001*** 0.900*** 1.246*** 0.938*** 1.634*** 0.993***

Investor protection index 0.288* 0.240* 0.488*** 0.308*

Enforcing contract rank 0.00262 -0.00309

Security of land rights -0.798** -0.865** -0.789** -0.528* -0.710*

Importance rural public property land

0.432* 0.532** 0.476*

Index of land tenure policy -0.465**

Rule of Law 0.0272***

Control of Corruption 0.0116* 0.0304*** 0.0208***

Government Effectiveness 0.0607***

Political Stability 0.0182***

Notes: Variables in logs. Refer to the main text for robust standard errors, constant included but not reported

Comments of econometric results

Our evidence is consistent with the notion that biofuel producers and land-scarce countries see transnational land investments as a possible strategy to integrate and expand their access to biofuel feedstocks for domestic energy

Actual or “perceived” agricultural biocapacity of Sub-Saharan African countries appears to act as a pull force

Water abundance is another driving force of biofuel land demand

Better institutional conditions increase Africa’s attractiveness

Countries with weaker protection of land rights and higher share of rural public property land are more likely to host a greater number of land FDI for biofuel crops

Directions for future research

Comparing the current results with alternative methods of dealing with zero values (Eaton–Tamura Tobit model and Heckman sample selection model)

Estimating the number of projects for biofuel crops in a destination country.

Comparing drivers of biofuel and other agricultural projects.

Conclusions

Preliminary stage of development, promising signals but also many barriers

Some features of biofuel development in SSA raise concerns on its equity and sustainability: Specialization in first-generation biofuels Prevalence of large plantations and of export-oriented foreign

corporations Strict link between biofuel investment and large scale farmland

acquisitions.

Biofuel-oriented land FDI seem mainly resource-seeking. Land governance weaknesses may be regarded as a way to access land and water resources at very favorable conditions.