Economic Importance of Agriculture for Sustainable Development and Poverty Reduction: The Case Study of Ethiopia

Transcription

1 This paper was first presented to the Working Party on Agricultural Policy and Markets, May Reference: TAD/CA/APM/WP(2010)23. Global Forum on Agriculture November 2010 Policies for Agricultural Development, Poverty Reduction and Food Security OECD Headquarters, Paris Economic Importance of Agriculture for Sustainable Development and Poverty Reduction: The Case Study of Ethiopia Xinshen Diao, IFPRI,

2 2

3 TABLE OF CONTENTS ECONOMIC IMPORTANCE OF AGRICULTURE FOR SUSTAINABLE DEVELOPMENT AND POVERTY REDUCTION: THE CASE STUDY OF ETHIOPIA Introduction An overview of Ethiopian agricultural policy Agricultural performance, food security and poverty Cereal production and productivity Agriculture and poverty reduction Agricultural-non-agricultural growth linkages in the Ethiopian economy Why agricultural growth linkages matter? Measuring agricultural growth linkages in Ethiopia a fixed price input-output model Results of an Ethiopia fixed price input-output model Growth linkages in the Ethiopian economy an economy-wide multimarket model Achieving agricultural growth Irrigation Adoption of improved seed Promoting modern technology in livestock production Halving the poverty: markets and non-agriculture matter Conclusions APPENDIX A A1. An illustration of the fixed price input-output models A2. The fixed price, semi-input-output (SIO) models A3. The Ethiopia economy-wide multimarket (EMM) model APPENDIX B: APPENDIX TABLES APPENDIX C: SENSITIVITY TEST OF THE SIO MODEL RESULTS REFERENCES Tables Table 1. Cereal production in 2003/04 and 2007/ Table 2. Cereal growth and growth contribution between 2003/04 and 2007/ Table 3. Share of cereal areas and cereal yields by technology Table 4. Yields in on-farm field trials vs. farmers' yield (tonne/ha) Table 5. Poverty incidence and inequality Table 6. National poverty rate by different daily 2005 USD PPP poverty line Table 7. Poverty rate by sector of employment of household head and livelihood Table 8. Poverty rate by administrative region Table 9. Agricultural and other income sources across four regions for two percentile household groups19 Table 10. Agro-ecological conditions across four regions for two percentile household groups Table 11. Agricultural growth linkages: international evidence

4 Table 12. Impact on Growth due to one unit of increase in selected sectors' output Table 13. Impact on Income due to one unit of increase in sectors' output Table 14. Importance of services in measuring multiplier effect Table 15. Population and poverty rates in the three areas Table 16. Land size and cereal output per household in the three areas Table 17. Cereal yield and input use in the three areas Table 18. Agricultural and non-agricultural growth rate in the simulations Table 19. Agricultural growth is more pro-poor Table A 1. The structure of the 2006/07 Ethiopian Social Accounting Matrix (SAM) Table A 2. Income distribution in SAM Table A 3. Household consumption spending patterns in Ethiopia Table A 4. Composition of demand and supply by sector in SAM Table A 5. Sensitivity test result gains in GDP Table A 6. Sensitivity test result gains in total household income Table A 7. Sensitivity test result - income ratio of rural poor household (rural poor household income in SAM is 1) Table A 8. Sensitivity test result - income ratio of rural non-poor household (rural non-poor household income in SAM is 1) Table A 9. Agricultural commodities included in the economy-wide, multi-market model Figures Figure 1. Agricultural GDP annual growth rate (%)... 9 Figure 2. Agricultural GDP per capita (2000 constant USD) Figure 3. Total cereal area according to the use of modern input (000 hectares) Figure 4. Food deficit, food balanced, and food surplus areas Figure 5. GDP growth multipliers in staple and export agricultural growth scenarios Figure 6. GDP growth multipliers in agriculture-led and non-agricultural-led growth scenarios Figure 7. National poverty rate (%) in agriculture-led and non-agricultural-led growth scenarios Figure 8. Comparison of effect of agricultural subsector growth on poverty reduction in the food deficit and food surplus areas

5 ECONOMIC IMPORTANCE OF AGRICULTURE FOR SUSTAINABLE DEVELOPMENT AND POVERTY REDUCTION: THE CASE STUDY OF ETHIOPIA 1 1. Introduction 1. It has been more than two and half decades since the government of Ethiopia had formally adopted Agriculture Development Led Industrialization (ADLI) as its development strategy in The main goal of this strategy is to attain fast and broad-based development within the agricultural sector and to make this sector's development to power broad economic growth. ADLI had been further rationalized as the basis of the poverty reduction program subsequently adopted by the government in 2002 (MoFED, 2002), a program is officially known as Sustainable Development and Poverty Reduction Program (SDPRP). 2. With 85% of the population living in the rural areas and depending on agriculture for livelihood, there is no doubt for the economic importance of the agricultural sector for sustainable development and poverty reduction in Ethiopia. The agricultural sector accounts for more than 40% of national GDP, 90% of exports, and provides basic needs and income to more than 90% of the poor. A better performed agricultural sector has provided growth to the overall economy, improved the food security and reduced poverty in the recent years. 3. However, debate on the potential for the agricultural sector to lead industrialization and economic transformation has been lasted for many years in the country, though the debate is often more political and not well served by rigorous empirical evidence. As the second largest country in Africa and with extreme high population growth, one of the key questions dominating the policy debate is the doubt for the future development of agriculture given the increasingly small plots which farmers must earn their living. The doubt also relates to the role of agriculture in the poverty reduction. While the majority of population lives in the rural and most poor are the rural poor, there is a question about how much growth in agriculture that can lead further and significant poverty reduction. 4. Even among those who believe the importance of agriculture in development and poverty reduction, the debate exists on what kind agricultural growth should be pursued. Should the government promote large-scale agriculture that is more advantage in adopting modern technology and hence more productive and competitive? Or should the government focus on the growth of smallholder agriculture from which a majority of rural population can get benefit? Among the agricultural subsectors, should considerable specific policy supports or interventions focus on export-led agriculture that may get quick outcome targeting niche markets, or emphasize the staple crop and livestock sectors that can bring a broadbased growth for the country? 1. This report is the first draft of the Ethiopia country case study of an OECD project "The Economic Importance of Agriculture for Sustainable Development and Poverty Reduction." The work should be considered as work in progress. The principal authors accept responsibility for any errors. The authors are: Xinshen Diao, Alemayehu Seyoum Taffesse, Bingxin Yu, and Alejandro Nin Pratt, International Food Policy Research Institute (IFPRI). 5

6 5. Against this policy background, the objective of this report is to contribute to such debates by focusing on the role of agriculture s future growth in economic transformation and poverty reduction. The evaluation of such role will be conducted in a broad economic context, and the linkages of agriculture with the other economic sectors and the possible differential contribution of agricultural growth at sub-sector levels to the poverty reduction are quantitatively measured. In the following section (Section 2), we first provide an overview of the agricultural policy evolutions in the last three decades in Ethiopia. The policy outcome in terms of agricultural growth performance and poverty reduction are assessed in Section 3. In Section 4 we provide a quantitative measure of agricultural linkages in the economy and assess the role of future agricultural growth in further poverty reduction. Section 5 provides an assessment on some key intervention areas that will promote agricultural growth, while the role of the government and policy implications are concluded the report. 2. An overview of Ethiopian agricultural policy 6. While Ethiopia has been witnessed three major political regime changes in the recent history, the importance of agriculture has been recognized by each government in this period. However, different policies pursued by the different regimes have resulted in very different outcomes in agricultural and rural development, particularly between the last two regimes in the past 35 years. In this period, the Derg regime ( ) has been characterized as an agrarian socialist regime with widespread government controls in all economic spheres including agriculture. After overthrowing the imperial regime of Haile Selassie, the Derg announced an agrarian reform program to declare all rural land to be the property of the state, together with the nationalization of almost all other assets in the industrial and services sectors such as manufacturing factories, financial institutions, big hotels and many residential buildings. While the agrarian reform had prohibited all tenancy relations and provided a large number of rural households with equal access to cultivation land according to their needs, the restriction on plot size per family, the prohibition of hired agricultural labour, the intensification of collectivization, the establishment of largescale state farms, and a series of other anti-market and state-controlled economic instruments had not only significantly negatively affected the incentives of farmers but also distorted the market mechanism in guiding land allocation and promoting productivity improvement. While central planning types of development strategies had identified agriculture as an engine of growth and targeted the improvement of food security through agricultural productivity, most growth targets became just a piece of paper and had never been able to achieve. Ethiopia suffered the worst famine on record in 1984 and the country's economy was in the dismal state at the end of Derg Regime. 7. Bad policies and brutal political repression during the Derg period generated disastrous economic outcomes and led to civil conflict. As a consequence the Derg regime collapsed in 1991 and the Ethiopian People s Revolutionary Democratic Front (EPRDF) assumed power. The years that followed witnessed a radical shift in overall government policy. Both the Transitional government ( ) and the EPRDF government that followed initiated extensive economic reforms including significant market liberalization and a structural adjustment program. Tariffs have been cut, quota constraints relaxed, licensing procedures simplified, foreign exchange controls eased, compulsory cooperative membership and grain delivery discontinued, subsidized rationing of manufactured consumer goods and fertilizers have been discontinued, privatization of state-owned enterprises begun, private banks authorized, and interest rates decontrolled and an inter-bank money market introduced. Consequently, the direct role of the state in economic activity has declined. 8. The most important development strategy under the transitional government is the adoption of Agriculture Development Led Industrialization (ADLI), which has been a central plank of the EPRDF government's development program until recent years. The ADLI focuses on productivity growth on small farms as well as labour-intensive industrialization. This strategy has been justified because agriculture is the largest sector in terms of output and, particularly, employment and exports; the bulk of the poor live in 6

7 the agriculture-centred rural areas; considerable gaps exist between rural and urban across key dimensions of human well-being including health, education and income; and there exists substantial potential to raise agricultural productivity. 9. Consistent with the ADLI, in the mid 1990s, the government focus shifted from policy reforms designed to "get the prices right" to public investment in agricultural extension aimed at boosting productivity through the widespread introduction of modern technology (MoFED 2002). An extensive extension program called the Participatory Demonstration and Training Extension System (PADETES) had been implemented, and through this system, the government delivered off-the-shelf packages of fertilizer, improved seed and credit, as well as information on input use and better agricultural practices to vast majority of smallholders in the rural areas. The promotion of the credit-fertilizer package was accompanied by a further liberalization of the fertilizer market. By 1997, fertilizer subsidies were completely removed and retail prices were fully liberalized, which also resulted in higher fertilizer prices. The use of fertilizer increased, though diffusion and adoption rates remained. Disappointing despite strong-handed promotion of the credit-fertilizer packages existed at times. On average, agricultural output continued to fall behind population growth. 10. Acknowledging the limited success of PADETES, the government revisited the program and formulated an integrated rural and agriculture development strategy that was launched in The new development strategy, which is officially known as Sustainable Development and Poverty Reduction Program (SDPRP) (MoFED 2002), has centred on the principal goal of poverty reduction. In line with this program, the government has introduced fiscal decentralization, judicial and civil service reform, and public sector capacity building. After the continuing evidence of widespread food insecurity in the drought of 2002/03, the government also initiated a strong focus on safety nets, programs to build the assets of food insecure households, resettlement, and soil and water conservation (especially water harvesting). 11. The SDPRP, which covered the three years 2002/ /05, was the first full Poverty Reduction Strategy Paper (PRSP) developed and implemented by the Ethiopian government. It was followed by the second PRSP titled Plan for Accelerated and Sustained Development to End Poverty (PASDEP). The Plan formed Ethiopia s guiding strategic framework for the five-year period 2005/ /10 (MoFED 2005). PASDEP aimed to significantly accelerate growth via the commercialization of agricultural and the promotion of private sector development. It further focused on a number of areas/issues in setting targets and designing interventions - a geographically differentiated strategy, addressing the population challenge, unleashing the potential of Ethiopia s women, strengthening the infrastructure backbone, managing risk and volatility, scaling up to reach the MDGs, and creating jobs (particularly in urban areas) (MoFED 2005). 12. The agricultural growth agenda set by PASDEP consisted of the following elements: shift to higher-valued crops; promote niche high-value export crops; a focus on selected high-potential areas; facilitate the commercialization of agriculture; support the development of large-scale commercial agriculture where it is feasible; and better integrating farmers with markets both locally and globally. 13. The instruments to achieve these in the context of PASDEP include (i) constructing farm-tomarket roads; (ii) development of agricultural credit markets; (iii) specialized extension services for differentiated agricultural zones and types of commercial agriculture; (iv) the development of national 7

8 business plans and tailored packages for specialized export crops (such as spices, cut flowers, fruits and vegetables); (v) area irrigation through multi-purpose dams; (vi) measures to improve land tenure security, and to make land available where feasible for large-scale commercial farming; and (vii) reforms to improve the availability of fertilizer and seeds. 14. PASDEP reflected deeper understanding of the role of agriculture in growth, with an acknowledgement that the ADLI strategy needs to be enhanced. Indeed, the acknowledgement is explicit in a draft version of the PASDEP document: The approach remains basically sound... However, the full potential of agricultural growth has not yet been realized, and intensification of the strategy is needed. More broadly, the overall growth performance has not yielded the hoped-for poverty-reduction results over the long-term. The time is now right to mount a major effort to accelerate growth, and this forms the main thrust of the PASDEP. (MoFED 2005). 15. Thus, PASDEP articulates a more comprehensive strategy which focuses on commercialization and intensification of agriculture, emphasizes the importance of intersectoral linkages, favours a geographically differentiated strategy, recognizes the dangers of volatile economic growth and rapid population growth, and highlights the importance of the urban sector. 16. The analytical foundations of PASDEP are broadly consistent with the underlying causes of poverty low productivity symbiotically linked with: limited capital stock (physical, human, infrastructural, natural) compounded by rapid population growth; weak institutions (imperfect or absent markets, weak civil service including agencies of public service delivery, insecure property rights, sparse early-warning and emergency assistance systems); and regular shocks (erratic weather, volatile prices, ill-health episodes, and conflict). 17. Critical concerns relate to implementation and sustainability of achievements include: Implementation - the extent to which priorities are set on the basis of decent diagnostics, the feasibility of some of the ambitious targets in light of resource requirements ( can vs. want ); Sustainability of achievements institution building, the effort towards domestic resource mobilization, industrial policy and incentives to the private sector, business environment The case of the livestock sector particularly in mixed-farming is a specific area yet to be fully incorporated within the economic policy sphere. 19. The overview of Ethiopia's agricultural policy evolution in this section highlights the vision and measures the current government has to promote agricultural growth. In the next section, we focus on agricultural performance in the recent five years and poverty reduction in a relative longer period. 3. Agricultural performance, food security and poverty 20. Ethiopia has been well known for its agricultural development challenge given its large and rapid growing population and limited and deteriorated land resource. These two factors together have caused extreme land shortages in the highland Ethiopia, the area most population lives and most agricultural production occurs. According to World Bank (2005), per capita land area in the highlands has fallen from 8

9 0.5 hectare in the 1960s to only 0.2 hectare by 2005, and a marginal productivity of labour is estimated at close to zero. 21. Population pressure has led to expanded cultivation into forest areas and steep slopes. This creates serious repercussion for the environment, which, together with fluctuation in rainfall, have made agricultural production very vulnerable to weather shock. As indicated by Figure 1, growth in agricultural GDP, which is predominated by crop and livestock production, has been extremely fluctuated. The positive growth unlikely continued for more than two or three years before the next weather shock occurred and resulted in agricultural GDP to decline. In the period of 22 years between 1982 and 2003, there were four years in which agricultural GDP declined by more than or close to 10%, and growth was also negative in the other five years. In fact, agriculture only contributed 0.3 percentage points on average to annual GDP growth over the decade to 2003 (World Bank 2006). The serious drought that lasted for two years in 1984 and 1985, together with the bad policy under the Derg regime, resulted in the worst famine in Ethiopian modern history. Per capita agricultural GDP declined by one-third and many people starved to die. Poor farmers who survived from the drought often lose their livestock, causing permanent shock to their livelihood. Figure 1. Agricultural GDP annual growth rate (%) 19 Agricultural growth Agricultural growth -21 Source: World Development Indicator In the recent years, the policy reforms, agricultural investments and public service provision have provided a boost to agricultural production, primary cereals. After 2003, Ethiopia agriculture has witnessed the most rapid growth in its history. As Figure 1 indicates such growth has already lasted for five years and annual growth rate is also high. Even excluding the highest growth rate of 17% in 2004 that has certain recovery pattern from the drought of 2003 in which agricultural GDP fell by 10.5%, the average annual growth rate of is still as high as 10%. While there is a controversial debate about how realistic such rapid growth is and a systematic, rigorous and comprehensive investigation into the sources of such growth has yet be conducted, cereal production data aggregated from the country's agricultural sample surveys is consistent with the total agricultural GDP growth. The recent growth has reversed the down slop trend of agricultural per capita GDP, a trend had lasted for three decades under the Derg regime and the 1990s. 9

10 Figure 2. Agricultural GDP per capita (2000 constant USD) AgGDP pc Trendline R² = Source: World Development Indicator (2009) Cereal production and productivity 23. Cereals are the dominant staples for the majority of Ethiopians, are the source of 62% of average Ethiopians' daily calorie intake, and account for about 45% of food expenditure for an average household. Thus, cereals, including barley, maize, teff, wheat and sorghum, are the most important crops for Ethiopia's agriculture. While 64% of agricultural value added comes from crops, more than 70% of crop land is devoted to cereal production. More than 11 million smallholders engage in cereal production, and total cereal production was 13.6 million tonnes in 2007/08, an increase of 4.8 million tonnes compared to production in 2003/04 (Table 1). Total area allocated to cereals also expanded by 27% from 6.8 million hectares in 2003/04 to 8.8 million in 2007/08. At the same time, average cereal yield exhibited a 22% growth from 1.3 tonnes/ha in 2003/04 to 1.6 tonnes/ha in 2007/ Teff is the most favourable staple crop for both Ethiopian rural and urban consumers and for all different income levels of households. Thus, teff occupied more land than the other crops. 30% of total cereal land in 2007 was used for teff production. The second important food crop is maize, which occupied 20% of total cereal land, followed by sorghum (18%), wheat (16%), and barley (12%). While most cereal crops are staple foods, barley is also used for local alcohol production. In terms of volume of production in the same year (2007), maize actually ranked first with 3.8 million tonnes of output, and output of teff is 3 million. While teff occupied 30% of cereal land, output of teff is equivalent to 22% of cereal output. This implies that teff is much less productive in land use. Indeed, national average yield of maize is 2.1 tonne per hectare (mt/ha) in 2007, yield of teff is only 1.2 mt/ha, the lowest level of yield among all major cereal crops. Teff is a crop only grown in few countries (mainly in Ethiopia) and its yield response to fertilizer is relatively limited given that the technology to develop high-yield variety of teff is more difficult than to develop other cereal crop varieties broadly grown in the world. On the other hand, teff is more favourable than maize in Ethiopian diet and has higher income elasticity in demand. This combination indicates a potential challenge to Ethiopia food security due to the inconsistency between the technology potential and consumers' preference. 10

11 Table 1. Cereal production in 2003/04 and 2007/ / /08 Area Output Yield In total cereal areas Area Output Yield In total cereal areas 000 ha 000 mt mt/ha % 000 ha 000 mt mt/ha % Barley Maize Teff Wheat Millet Sorghum Total With any modern inputs Barley Maize Teff Wheat Total Without modern input Barley Maize Teff Wheat Total Source: Authors calculation using CSA data. 25. Under ADLI, the government emphasized intensification to increase agricultural productivity, especially a centralized extension push focusing on technological packages combining credit, fertilizers, improved seeds and better management practices to raise productivity. Under this program, fertilizer use almost doubled between 1990 and 2000 to tonnes (World Bank 2007). However, the intensity of fertilizer nutrient use per hectare stagnated in the latter half of 1990s and into this decades. According to World Bank (2007), only 37% of farmers use inorganic fertilizer and application rates remain low at 16 kg/ha of nutrients (about 33 ka/ha for commercial products). 26. Following the drought of 2002/03, a large-scale food security program was rapidly scaled up in poor and vulnerable areas, amounting to a significant part of total public spending. More recently, weaknesses in the marketing system have been recognized and a new marketing strategy is being developed based on scaling-up cooperatives, and establishing a commodity exchange and its associated institutions. As a result of these various programs, public spending on agriculture, natural resources and food security has risen from 5% of the total government budget in 1997/98 to over 10% in 2003/04, above the CAADP's target for Sub-Saharan Africa. 27. Strong push on intensification seems to show certain results in the recent years. Consistent with growth in total agricultural GDP, the period 2003/04 to 2007/08 has registered a recorded cereal production growth in Ethiopian history. Total cereal production increased by 54.9% in four years, with a more than 10% of annual average growth rate. Against the historical trend in which almost all increased production can be explained by area expansion, only half of the recent growth is the result of area expansion while the rest half is due to yield increase (Table 2). Table 2 also displays the growth by individual crops, and growth contribution of area expansion and yield increase in each crop s production 11

12 growth. As Table 2 indicates, among the four main crops, there are two crops, teff and sorghum, for which the growth in production is dominantly a result of yield increase, which contributes to, respectively, 63% and 58.7% of teff and sorghum output growth. While for maize and wheat, area expansion is the main source of their growth, increases in yield still contribute to 32% and 29% of their output growth, respectively. 2 Table 2. Cereal growth and growth contribution between 2003/04 and 2007/08 Total growth (%) Growth contribution (Increased individual crop output = 100) (Increased total cereal output = 100) Area Output Yield Due to growth in Areas Yield Output Areas Yield Output Barley Maize Teff Wheat Millet Sorghum Total Source: Authors calculation using CSA data. 28. The last three columns of Table 2 display growth contribution of each individual crop to total cereal production growth. As the last column of Table 2 indicates, 27.6% cereal output increase is the result of maize production growth, followed by teff, which contributes to 22% of cereal growth. Considering the contribution of area expansion to the cereal production growth, increased harvest area in maize production results in 18.8% of total cereal production growth, followed by wheat, of which area expansion contributes to 12.1% of total cereal production increase. Considering the contribution of yield increase to cereal production growth, 13.9% of such growth is the result of yield increase in teff, followed by sorghum, of which yield increase contributes to 11.5% of total cereal production growth. 29. It has to point out that cereal cultivation is highly concentrated geographically. Almost 80% of total area under cereals is in the Amhara and Oromia regions to the northwest, west, southwest and south of Addis Ababa. This area includes a diverse set of conditions for agricultural production. Spatial conditions for production and market access have been discussed elsewhere (see Diao and Nin Pratt, 2005; Taffesse, 2006). 30. Table 1 also disaggregates production of the four main cereals by the use or without use of modern input. Ethiopia has witnessed rapid increases in modern input use, particularly the use of fertilizer in the result years. As Figure 3 indicates, fertilizer combined with local seed was applied to 2.5 million hectares in 1995, reached to 3 million hectares in 2003/04, and jumped to 4 million hectares in 2007/08, a level similar as the areas without use of any modern input. 2. It should notice that level of maize yield in Ethiopia is higher than that in many other African countries in East Africa even in the early 2000s. According to World Bank, over the period of 1986 to 2000, the average yield of maize increased from 1 mt/ha to 1.8 mt/ha as the result of National Maize Research Programs. 12

13 Figure 3. Total cereal area according to the use of modern input (000 hectares) Local seed & no fertilizer Fertilizer & local seed Fertilizer & improved seed / / / / / / / / / /08 Source: Author s calculation using CSA data (various years). 31. The government s fertilizer promotion policy focuses on the four main cereal crops, which are relatively more responsive to fertilizer and have higher producer prices. By focusing on these four crops in Table 1, it indicates that, 55% of the four crops areas were applied by modern inputs, primarily fertilizer, in 2003/04, while the per cent has increase to 65% in 2007/08. In these four years, total harvest areas of these four crops increased by 28%. In the meantime, the areas without use of modern input did not change and stabilize around 2.3 million hectares. 32. However, the yield difference between with and without modern input use is modest for all the four crops. Except for wheat, the average yield for the areas with modern input use is less than 15% higher than the average yield for the areas without any modern input. In the case of wheat, the yield gap is 30% in 2003/04, while it falls to 19% in 2007/08. Many factors affect fertilizer efficiency and in their 2007 study, Byerlee et al. (2007) concluded the following major factors that affect the results of the intensification program that the government has been promoted: Low technical efficiency in the use of fertilizer due to the application of standard packages to very diverse and risky environments, and the timeliness and quality of input supply. Poor performance of the extension service resulting from limited human capital, competing responsibilities, and entrenched routines and behaviours among extension agents. Shortcomings in seed quality and timeliness of seed delivery. Promotion of regionally inefficient allocation of fertilizer as promotion of fertilizer use tied to credit programs is fed by government targets for fertilizer consumption at the local, regional and national levels. Input distribution tied to credit that limits the opportunity for the emergence of private sector retailers. Generation of an unlevel playing field in the rural finance sector by the guaranteed loan program with below-market interest rates, undermining efforts to set up alternative institutions, branches of commercial banks, or independent financial cooperatives. 13

14 Table 3. Share of cereal areas and cereal yields by technology Share in each crop's total areas Average yield (tonnes/hectare) Maize Fertilizer with local seed Fertilizer with improved seed Improved seed without fertilizer Without fertilizer & improved seed Average Teff Fertilizer with local seed Fertilizer with improved seed Improved seed without fertilizer Without fertilizer & improved seed Average Wheat Fertilizer with local seed Fertilizer with improved seed Improved seed without fertilizer Without fertilizer & improved seed Average Barley Fertilizer with local seed Fertilizer with improved seed Improved seed without fertilizer Without fertilizer & improved seed Average Source: Author s calculation using part of CSA data (various years). 33. While all these factors have resulted in the low response of cereal yield to the use of fertilizer, increased use of fertilizer without use of high-yield seed varieties seems to be the most important factor. Table 3 shows cereal area allocation for the different technologies and the yield for the four cereal crops under different technologies. Except for maize, the combined use of fertilizer and improved seed is applied to 0.3% - 0.6% of harvested teff areas and % of wheat area. Only in the case of maize, the share is 18% - 23% high. Moreover, when a rapid increase in fertilizer use occurred in the last four years, growth in the areas with the combination of fertilizer and improved seed has become stagnant. While the low yield response to the combined use of fertilizer and improved seed in the case of teff and wheat seems to indicate that the so-called improved seed is not really high yield varieties, a further assessment is necessary for fully understanding farmer s behaviour as well as the constraints for promoting such combined technology in Ethiopia. To show the potential of doubling Ethiopia cereal production by improving yields, we draw from the World Bank (2006) to display what are the reachable yields for cereal crops in Table 4. 14

15 Table 4. Yields in on-farm field trials vs. farmers' yield (tonne/ha) NAEIP * ( ) SG2000 ** ( ) Current farm improved traditional improved traditional yield Maize Teff Wheat Barley Sorghum * NAEIP is the National Agricultural Extension Intervention Program. ** SG2000 is Sasakawa Global 2000 Program. Source: World Bank Agricultural sector performance over the recent five years is also indicative of the new direction of the country's development strategy (i.e. PASDEP), which indicates an evolution of strategy toward market-driven diversification and commercialization, and increasing exports with a greater focus on private sector investment. Following the opening of incentives for private investment in flower industry, a total of over 100 investors have invested in the industry and flower exports increased to nearly USD 13 million in Other investments in high value products and supply chains are emerging, including the export of green beans to Europe, the emergence of a contractual supply chain for the UK based bean industry, and the supply of quality milk and poultry to urban centres. Several of these emerging industries involve outgrower and/or contract arrangements with small farmers, often linked with an emerging indigenous entrepreneurial class of farmers and agribusiness. Exports of oilseeds and pulses, two traditional cash crops grown by many farmers, have also experienced impressive growth, increasing their value by a factor of ten between 1997 and 2006 and demonstrating the increasing competitiveness of these sectors through area specialization and the uptake of new technologies. While coffee is still the most important export crop in Ethiopia, the combined exports of other crops and leather has passed the coffee in export value in the recent years Agriculture and poverty reduction 35. Given that 85% of Ethiopians live in the rural area and more than 90% of the poor are in the rural, agricultural growth direct transfers into poverty reduction if the growth is significant. While income generation role of agricultural growth is important for poverty reduction, as many poor in rural Ethiopia either mainly produce for own consumption need or are the net buyers of cereals, the direct consumption effect of agricultural growth is equally important in poverty reduction in the country. While the country has conducted agricultural production sample survey almost in each year, the national representative household surveys in income, consumption and expenditure (HICES), which can provide a poverty measure, have been conducted only in each five years in the recent 15 years. Moreover, the HICES is only available publicly for the two runs of 1995/96 and 1999/2000, which have been widely used in poverty assessment in the literature. The most recent HICES was conducted in 2004/05, but the survey data is not available for analysis, besides the poverty rate reported by the government. 36. Table 5 first reports the government's official poverty assessment based on the three runs of HICES and the poverty measure is based on the country's own standard, which is not necessary to be the same as international standard measured by daily income. Instead, the country's own poverty measure standard considers the minimum consumption level to meet the basic need of food and other spending and also considers the different consumption expenditure needs (e.g., for housing) between the rural and urban. For comparison, we also present the national poverty rate measured according to the World Bank's 15

16 standards in Table 6, in which the poverty line of USD 1.25 in 2005 PPP dollar per day is commonly used as an international standard for poverty measure across countries. 37. While the level of national poverty rate for the same year differs between national and the international measures, the trends of change in the poverty rate are similar. Poverty has declined over time, and it declines more according to the measure using the international standard. Moreover, the poverty declined more in both absolute level and per cent change between 1999/2000 and 2004/05, and this is true for both measures. The third observation is that while poverty is falling, the country seems to be unlikely to achieve the MDG1 of halving its 1990's poverty rate by 2015, if the poverty reduction trend, which is calculated according to the country's own poverty measure, will be similar in the next 10 years after 2004/05 as that in the previous years between 1995 and Table 5. Poverty incidence and inequality Poverty rate (%) % Change in incidences 1995/ / / /00 over 1995/ /05 over 1995/ /05 over 1999/00 Headcount index National Rural Urban Gini coefficient (consumption) National Rural Urban Source: MOFED Table 6. National poverty rate by different daily 2005 USD PPP poverty line Poverty rate (%) Gini USD 1.00 USD 1.25 USD / / / / Source: World Bank PovCal Net. 38. Table 5 also reports the poverty rate for the rural and urban households separately. After considering different expenditure patterns between the rural and urban households caused by location factors, the rural poverty rate is still higher than the urban poverty rate in each survey year reported in Table 5. However, the reduction in poverty rate is more rapidly in the rural than in the urban, indicating the direct effect of agricultural growth on the poverty reduction. The urban poverty has in fact risen in the period between the first and third survey years, although it fells slightly between the second and third surveys. Because of this, the rural and urban poverty rate has converged in the recent years. 39. Gini coefficient that is used to measure inequality is included in both Tables 5 and 6. While Gini coefficient has slightly increased in Table 5 according the country's own consumption-based assessment, this coefficient fells significantly in Table 6 between 1995/00 and 2004/05 using the income measured by the international standard. The slight increase in inequality reported in Table 5 is the result of significant 16

17 increase in the value of urban Gini coefficient. The urban Gini, which starts with a value higher than the rural Gini in 1995/96, has increased from 0.34 to 0.44, a 10 percentage points increase, in the period of 10 years. In the same period, the rural Gini has actually fallen slightly, and has been at a low level of 0.27 to Significant declines in the rural poverty rate and low and relatively stable rural Gini coefficients in Ethiopia seem to indicate that agricultural growth in the recent years has benefited the poor and growth outcome has been shared by a majority of the rural population. Moreover, such growth outcome on poverty and income distribution seems to be stronger in the first five years of the 21th century than in the previous years. However, as the data of the recent HICES survey of 2004/05 is not available for our study, we have to draw from the exiting analysis on the previous HICES surveys to further understand the relationship between agriculture and poverty reduction in the rest of this section. In 2005, the World Bank published a detail assessment on the role of agriculture in the well-being and poverty in Ethiopia (World Bank, 2005). The relevant findings of this report are synthesized here to conclude this section. Table 7. Poverty rate by sector of employment of household head and livelihood Poverty rate (%) Consumption per adult equivalent Population share 1995/ / / / / /00 By sector of employment of household head Agriculture Industry Services By type of livelihood Mainly agriculture Mainly cash crop producers Coffee producers Chat producers Tea producers Source: Tables 1.9 and 1.10 in the World Bank (2005). 41. Authors of the World Bank Report (2005) calculate the poverty incidence by sector of employment of household head and by rural livelihood. As indicated in Table 7, poverty incidence among households employed in non-agriculture is substantially lower than those employed in the agricultural sector in the first run of HICES survey (1995/96). The poverty gap became significantly smaller between these two types of employment and the poverty rate of a group of households whose heads are employed in the industrial sector is actually higher than the poverty rate for agriculturally employed households. While the poverty rate of the group households whose heads were employed in the service sector is still lower than the poverty rate of agriculturally employed households in the second run of the survey, the gap has become much smaller than that in the first run. Moreover, poverty rate increases in the non-agriculturally employed household groups and it increases more in the industrially employed household group. This finding is consistent with the change in the poverty rate by rural and urban household groups, which further confirms the positive role of agricultural growth to rural poverty reduction. 42. In the second panel of Table 7, the poverty distribution is displayed by different types of rural livelihood. The poverty rate for the group of households whose main livelihood activity is the engagement of agriculture is similar as the poverty rate for the group of households whose heads employed in the nonagricultural sector. However, if we only focus on the rural households whose main livelihood activities are 17

18 cash crop production, the poverty rate is significantly lower than the whole agricultural group in both runs of the surveys. Among the cash crop producers, the households mainly involving in the production of coffee, the most important export crop of Ethiopia, actually are similar poor as the agricultural household group as a whole. The poverty rate for coffee growers is actually higher than for the agricultural producers as a group in the second run of the survey (1999/00) due to the declined world coffee price. However, the poverty rate for coffee growers has to be read in caution as coffee production areas are quite concentrated in Ethiopia and the comparison between coffee and non-coffee households should make more sense considering these areas only. 43. Geographically, poverty is widespread in Ethiopia, while the majority of the poor live in the four large regions (Tigray, Amhara, Oromiya and SNNP) and Addis Ababa. Together, these regions account for 85% of population of the country (World Bank, 2005). The World Bank Report shows that the highest rates of poverty among the major regions are found in Tigray and SNNP. Authors of the report calculate their own regional poverty rate and two poverty lines are considered in the calculation. The two large regions with the high poverty rate are characterized by lower than average arable land per capita, which underscores the role of land scarcity in determining poverty. Table 8. Poverty rate by administrative region Lower poverty rate Upper poverty rate 1995/ / / /00 Tigray Afar Amhara Oromiya Somali Benishangul-Gumuz SNNP Gambela Harari Addis Ababa Dire Dawa National Source: Table 1.12 in the World Bank (2005) and national poverty rate is from Table 1.2 in the World Bank (2005). 44. Regional disaggregation in poverty also shows that poverty rose between the two runs of surveys in 9 of 10 regions and declined only in Amhara under the lower poverty rate assessment and slightly declined in additions in the other two regions under the upper poverty rate assessment. It has to point out that the poverty rate in Table 8 is from the World Bank report's authors own calculation based the same data of HICES from which the official poverty rate is derived. According to them, both lower and upper poverty rates for the country as a whole did not change between the two runs of HICES, which explains why poverty rate rose in most regions and declined in few. 45. Focusing on the four large regions that account for 85% of total population in Ethiopia, the World Bank report further assesses the relationship between livelihood and level of income. Table 9 is drawn from the findings of the report. By considering only two percentile groups of population in each of the four regions, it shows that for the poor one-percent of population (the 25th percentile), the level of real expenditure is only equivalent to 63% of regional average for the three regions and only 48% for Amhara. On the other hand, for the non-poor one-percent of population (the 75 th percentile), the level of real 18

19 expenditure is times of the expenditure level for the 25 th percentile of population in the three regions and 2.53 times in Amhara. Table 9. Agricultural and other income sources across four regions for two percentile household groups Tigray Amhara Oromiya SNNP Real expenditure per adult equivalent in Addis 1995 price Mean th percentile th percentile Share of income from agriculture (%) Mean th percentile th percentile Share of income from other sources (%) Mean th percentile th percentile Source: Drawn from Table 4.7 in the World Bank (2005). 46. While there are many factors that associate to the income gaps between the poor and non-poor, we focus only on the sources of income in Table 9. As indicated in the table, for the poor percentile group, share of agricultural income is consistently lower than that for the regions as a whole and for the rich percentile group across the four regions. It shows that for the rich percentile group, share of income from agriculture is more than 95% for the three regions and 92% for SNNP. On the other hand, for the poor percentile group, the share is below 60% for the two regions, and 63% and 71%, respectively, for Oromiya and Amhara. The poor not only have lower share of agricultural income, but also few income generation opportunities from other livelihood sources. This seems to indicate that many poor Ethiopian households, particularly the extremely poor ones, could not earn enough income to meet their basic expenditures, and supports of food and other types of aids are important component of their basic consumption. This finding also indicates the positive relationship between agriculture as the main source of income and rural households position in income distribution ranking, and hence, the important role of agriculture even for the relative non-poor rural households. 47. Similar as most African countries, Ethiopia is characterized as rainfall-dominated agriculture and irrigation covers less than three per cent of agricultural crop areas. Understanding the relationship between agro-ecological conditions and household income is helpful for identifying a group of policies that are more location specific and targeted. Table 10 reports three important agro-ecological condition factors for the four large regions and these factors are defined at the woreda level. As indicated in the table, the poor group of households (25 th percentile) lives in relatively low altitude areas, while the non-poor group (75 th percentile) lives in highland in all the four regions. While long run average rainfall varies across the four regions, the poor seem to live in the areas with less rain than the areas where the non-poor live. On the other hand, the variation of rain is larger in the areas the non-poor live than in the areas the poor live. Agro-ecological condition information compiled in Table 10 indicates that the absolute disadvantage in agricultural natural production condition partially characterizes the areas where the poor live, which is at least the case for the one per cent of the poor (25 th percentile) population considered in Table 9. While agricultural potential in such areas is not necessary high and hence these areas can only pay limited role in national wide agricultural growth, to promote the technology that aims at improving such disadvantage 19

20 condition in these areas such as land management and other farming practice is important for poverty reduction. This policy issue will be further discussed in the following sections. Table 10. Agro-ecological conditions across four regions for two percentile household groups Tigray Amhara Oromiya SNNP Mean altitude (m) Mean th percentile th percentile Long-run average rainfall (mm) Mean th percentile th percentile Long-run coefficient of variation of rain Mean th percentile th percentile Source: Drawn from Table 4.8 in the World Bank (2005). 4. Agricultural-non-agricultural growth linkages in the Ethiopian economy 4.1. Why agricultural growth linkages matter? The economic importance of agriculture for development has been quantitatively measured in the literature and the linkage effect is often used in such measure. As agriculture grows, it stimulates series of economic linkages with the rest of the economy. The resulting demand linkages fall into two broad categories: production linkages, and consumption linkages Production linkages include backward linkages the input demands by farmers for farm equipment, pumps, fuel, fertilizer and repair services as well as forward linkages from agriculture to nonfarm processors of agricultural raw materials. In prosperous agricultural zones, these linkages prove substantial as pump suppliers, input dealers, grain traders, processing industries and transporters emerge to supply agricultural inputs and process and distribute farm output. Empirical work on these relationships has focused on measurement of input-output coefficients to establish the strength of the forward and backward supply linkages. 50. Consumption linkages include spending by farm families on locally produced consumer goods and services. Early work in Green Revolution India indicated that higher-income small farmers spent about half of their incremental farm income on non-farm goods and services as well as another third on perishable agricultural commodities such as milk, fruit and vegetables (Mellor and Lele 1971). Thus, consumption linkages from growing farm income can induce sizable second rounds of rural growth via 3. Although the discussion below focuses explicitly on agricultural growth and linkages thereof, the approach and concepts therein apply to growth in other sectors as well. 4. It is important to emphasise that this study, and almost all studies of its kind, focus on demand linkages described in the following paragraphs. Aside from demand linkages, there are other inter-sectoral linkages in an economy. Briefly, these operate via saving and investment (private and public), labour flows, and transfers including taxes. 20

21 increased consumer demand for non-agricultural goods and services as well as perishable, high value farm commodities such as milk, meat and vegetables. In places like India, where many non-farm goods and services are produced by labour-intensive methods, the spending multipliers not only accelerate growth but also enhance the equity of agriculture led growth. 51. Following an initial spurt in farm productivity and incomes, production and consumption linkages together induce second rounds of demand-led growth. Empirical evidence from around the developing world suggests that a USD 1 increase in agricultural income will generate an additional USD 0.30 to USD 0.80 income in rural non-farm economy. Linkages are even higher when consumption of urban-produced products is included. In Africa and Asia, consumption linkages typically account for over 80% total spending linkages. 52. This evidence contrasts with Hirschman s claim of feeble agricultural growth linkages (Hirschman, 1958). Where did Hirschman go wrong? He underestimated agricultural growth linkages in two very fundamental ways. As Johnston and Kilby (1975) originally pointed out, agricultural technology changed during the green revolution. The new high yielding varieties demanded pumps, sprayers, fertilizer, cement, construction labour, and repair facilities from non-agricultural firms, thus generating substantial backward linkages. Furthermore, considerable milling, processing and distribution of agricultural produce took place in rural areas, thus generating important forward production linkages as well. The new agricultural technology fundamentally altered input-output relationships. 53. Still more important were the consumption linkages that Hirschman had ignored altogether. As Mellor and Lele (1971) originally pointed out, consumption linkages from growing farm income induce sizable second rounds of rural growth via increased consumer demand. Where new technology or investment in agriculture leads to increased income, farm families spend large increments of additional earnings on high-value processed foods and on consumer goods and services such as transport, education, health, construction and personal services. 54. Available evidence indicates, however, that demand linkages vary considerably across locations and farm technologies. As Table 11 indicates, they typically prove highest in Asia and lowest in Africa because of higher input linkages with Green Revolution Asian agriculture and because of higher income levels which lead to more rapid diversification of consumer spending into non-foods. 55. The accumulating evidence briefly noted in the previous paragraphs induced a shift in the policy prescriptions concerning sectoral and overall growth. Reversing the industry-first orthodoxy of the 1950's, the results of Adelman s (1984) classic study suggest that agricultural demand-led industrialization can generate superior growth and equity when contrasted with the alternative of export promoting industrialization strategies. Better identified and measured growth linkages thus led to the recognition of agriculture as a potentially powerful engine of economic growth. 5 The same evidence also revealed that this potential is neither present nor equally realizable everywhere. 6 Consequently, it became vital to consider two sets of policy relevant questions. Globally, it is necessary to answer, under what conditions agriculture can become a leading sector to induce faster growth, how does agriculture grow, and do government policies matter a lot to agricultural growth. Specific to each economy, it is indispensable to establish the size of potential agricultural growth linkages and the extent to which it is possible to realize them. 5. Prominent writers such as Irma Adelman, Peter Hazell, Peter Kilby, Bruce Johnston, Uma Lele, Michael Lipton and John Mellor highlight the potential power of agriculture-led growth strategies, particularly in the early stages of economic development. 6. A good summary of the relevant issues and evidence can be found in Sarris (January 2001). 21

22 Table 11. Agricultural growth linkages: international evidence Additional Income Growth Source of Linkages (%) Initial Agricultural Income Growth Other Agriculture Non-farm Activities Total Consumption Production Asia Africa Latin America Source: Haggblade and Hazell (1989) Measuring agricultural growth linkages in Ethiopia a fixed price input-output model 56. A variety of economic models are available for measuring agricultural growth linkages. We first introduce a fixed-price, semi-input-output (SIO) model as it is a rather simple and spreadsheet operated model and can be easily used by the analysts in the government. Fixed price input-output models 57. Early studies of growth linkages most commonly apply some variant of the linear inputoutput (IO) model. In its most basic form, the input-output model uses fixed IO coefficients and assumes fixed prices and perfectly elastic supply in all sectors. In such models, production sectors are linked by input-output technical relationship as any sector's output can be employed as intermediate inputs in production of other sectors' output. Second part of the linkages in this kind of model occurs between consumer's final demand and sector's output. When consumers purchase any good, e.g., a shirt, it is equivalent to purchase those products such as fibre and yarns used as intermediate inputs in shirt production. The third part of the linkages is the relationship between income generated from factor endowments employed in production process and received by consumers as owners of the endowments. This occurs when a social accounting matrix (SAM) is used in the model and primary inputs (labour, land and capital) are captured in sectoral production. When more primary inputs are employed by a sector's production, without constraint on the supply of such inputs, there are income gains to consumers who own such factor endowments. 58. Without investigating into the functional forms for each product's supply and demand, a linear input-output relationship is assumed in an IO based model. This implicitly implies a Leontief technology in production and non-substitution relationship in consumer's demand. While it is a rather strong (but not unacceptable) assumption in the microeconomic theory, it avoids the arbitrary choice of elasticity either in production or utility (welfare) function, i.e. there is no any substitution between inputs in a production function nor substitution in consumption in a utility function. Given that an IO model often composes disaggregate economic activities with many sectors and multiple consumers, it seems impossible to econometrically estimate elasticity for all these sectors' supply and consumers' demand functions. Thus, to assume a fixed relationship between input and output seems to be acceptable. 59. With the non-substitution assumption in both production and consumption, assuming that supply of any good is not constrained by its inputs, any increase in demand (which can be export demand) leads to more output with no change in price. From this point of view, a fixed price IO model is 'partial equilibrium' in its factor market, while it is 'general equilibrium' in the commodity market. In Appendix A, to help readers understand how the fixed price IO model works, we present a simple model to illustrate it. 60. Unconstrained supply in all sectors is, of course, an unrealistic assumption in any country, particularly for some sectors. Bigsten and Collier (1995) and Haggblade, Hammer and Hazell (1991), for example, note that the existence of a real multiplier hinges on the existence of slack resources which can be pulled into productive activity. In a developing country, given high rates of seasonal labour underemployment, typically low capital requirements and substantial rates of reported excess capacity in 22

23 many rural non-farm businesses, a highly elastic supply of rural non-farm goods and services is frequently an appropriate assumption. 7 In contrast, shortages of skilled labour, foreign exchange, and fixed capital frequently constrain output in the formal industrial sector. Likewise in agriculture, seasonal labour bottlenecks, land availability, soil fertility, input supply, marketing infrastructure and agro-climate constraints frequently limit supply responses. 61. Even so, some analysts suggest that agricultural supply elasticities may be high, at least over a certain range (Delgado et al. 1998; Thorbecke 1994). Anecdotal reports of piles of rotting fruit, unable to find their way to market, and excess bags of grain unevacuated from specific remote regions bolster these claims in some, limited circumstance. Yet apart from these episodic special cases, the overwhelming bulk of empirical evidence points to a low aggregate supply response in agriculture (Binswanger 1989). If farmers in the developing world could, in fact, increase crop output in unlimited amounts, agriculture would indeed represent a powerful engine of economic growth, for both malnutrition and poverty would vanish overnight as hungry farmers availed themselves of this perfectly elastic cornucopia. 62. By ignoring supply constraints altogether, unconstrained input-output multiplier models exaggerate the size of the inter-sectoral linkages. Given that over half of the reported indirect effects in these unconstrained models come from demand-induced growth in food grains and other allegedly elastically supplied agricultural commodities, this questionable assumption biases anticipated indirect income gains substantially upwards. Side-by-side comparison with alternative formulations suggests that the unconstrained input-output models overstate agricultural growth multipliers by a factor of two to ten (Haggblade, Hammer and Hazell 1991). Fixed price, Semi-Input-Output (SIO) models 63. To better simulate real-world supply rigidities, semi-input-output (SIO) models classify sectors into two groups, those that are perfectly elastic in supply and those with supply-constrained. The SIO model permits output responses only in the supply responsive sectors, in which perfectly elastic supply ensures fixed prices for their output. In the other group, i.e., the group of supply-constrained products, perfect substitutability between domestic goods and imports guarantees that world prices will ensure fixed prices for these goods as well. For these models to produce a reasonable approximation of reality, the supply-constrained sectors often correspond to tradable goods whose domestic supply remains fixed at the prevailing output price. In these supply-constrained sectors, increases in domestic demand merely reduce net exports, which then become endogenous to the system and determined by the matrix of semi-inputoutput multipliers. 64. As social accounting matrices (SAMs) have grown in popularity, SAM-based multiplier estimates have emerged to complement and extend the early linkages work. In spite of such improvement, given that SAM-based multiplier analysis does not capture price effect (and other imperfect substitution relationship in production and consumption and imperfect elastic in supply, as a CGE model does), the SAM-based multipliers are formally identical to the IO and SIO models. All require an input-output table to calculate the production linkages; all adopt fixed prices, fixed input-output coefficients and fixed marginal budget shares; and all come in unconstrained and constrained versions. The SAMs themselves become convenient tools for summarizing the raw data and results. They also provide a basis for incorporating investment, balance of payment, and government accounts. Frequently, given their origin in poverty and income distribution analyses, the SAMs offer great detail on factor allocation and distribution of income across household groups. What many in the literature call unconstrained SAM-based multipliers are formally identical to the unconstrained IO models. Similarly, the constrained SAM-based 7. Bagachwa (1981), Liedholm and Chuta (1976) and Steel (1977) report rates of excess capacity between 33% and 60% for the countries of Tanzania, Sierra Leone and Ghana. See Bagachwa and Stewart (1992) for a detailed summary. 23

24 multipliers are formally identical to the SIO models (Haggblade, Hammer and Hazell, 1991; Lewis and Thorbecke, 1992). While we use a recently developed SAM for Ethiopia in the following SIO modelling analysis, we consider only the linkages effect through production and consumption, and ignore the government and investment that are included in the SAM as two individual institution accounts, given that the fixed-coefficient method is not a proper tool to analyze investment behaviour and government decision. 65. What does a SIO model reveal? When researchers apply a SIO model for growth linkage analysis, they need first to assume which sectors in the studied economy are supply-constrained and which are supply-unconstrained. The analysis then focuses on those sectors that are supply constrained to discuss their multiplier or linkage effect in the economy by assuming their supply curves shifted outward. For instance, maize and sorghum, together with other agricultural subsectors, are assumed to be supplyconstrained in the Ethiopian economy in the given time, while trade and some other services, together with selected manufacturing sectors, are supply-unconstrained. These assumptions imply that, without an outward shift in maize's supply curve (which should be a vertical line with the assumption of supplyconstrained), output of maize (as well as output for other agricultural production) is fixed in the SIO model for Ethiopia. Now, assuming that a new technology is adopted by maize producers such that maize supply curve is shift rightward at the given prices for inputs and output. Then the linkages between such supply shift in maize production and the rest of the economy are captured by the coefficient values in the column of the matrix presented on the right side of Equation (4') in Appendix A corresponding to the maize sector in this matrix. These coefficients indicate the additional demand on the other sectors' output and on the primary factors with a one unit increase in maize production. Moreover, these input demand coefficients capture both the direct demand on intermediate and primary inputs employed in the maize production and indirect demand induced by the input-output linkages across all the sectors and consumer's demand. Such second, third or more round effects (the cycle continues until all related growth possibilities are exhausted) are typically focus of growth multiplier analysis. In this particular case, linkages or multiplier effects are induced by supply shift in maize production curve given that there are sectors which are supplyunconstrained and they are possible to have a local supply response to a shift in maize supply curve. However, there will not have supply response for those sectors of which supply is constrained (e.g. sorghum). For the supply-constrained sectors, increased demand for their products is met by reduced exports or increased imports (which is often called a leakage effect to the rest of the world). In the present case, when maize's supply curve shifts outward in Ethiopian economy, the supply response did not occur in the other agricultural sectors and only occurred in the non-agricultural sectors (e.g. trade and other service sectors). 66. Obviously, the assumption about which sectors to be supply-constrained and which are supplyunconstrained affects the model results. In practice, tradability, technological and/or resource constraints, and capacity utilization condition the extent of the rigidities of supply response. In the present case, given that Ethiopia is a land-scarce economy, all agricultural production, including crop and livestock, is assumed to be supply-constrained while most private services are assumed to be supply-unconstrained. In the case of the manufacturing and other industrial sectors, the domestic manufacturing with less importdependency such as meat and dairy processing, grain milling, thread, yarns, fibre, lint and clothing, together with the construction, and public administration subsectors, are deemed supply-constrained. In contrast, the reported considerable unused capacity in some manufacturing suggests the possibility of expanding supply without significant incremental costs. 8 Therefore, the manufacturing other than list above, mining, and utility, (together with most private services), are identified as supply-unconstrained. 8. For instance, CSA survey data (2003a) reveals that capacity utilisation within large/medium-scale manufacturing averaged just above 50% during 1997/ /04. More tellingly, this rate of capacity utilization varies very little across years. 24

25 67. While the choice of which manufacturing sector as supply-constrained is rather arbitrary, it can be used to capture different types of constraints in supply response across sectors if the local knowledge for such constraints is available. However, it is common and must to be noted that a SIO model analysis does not explain why or how the initial increase in a sector s output occurs or why certain sectors respond to this trigger while others do not. For example, in the following section we will discuss the multiplier effect of selected agricultural and non-agricultural subsectors, assuming their supply curves can be shifted outward by adoption of any new technology. If such shift is unlikely to occur in reality, of course, the corresponding linkage effect will not happen too. Moreover, we also conducted a series of sensitivity tests in which different manufacturing and other industrial sectors are assumed to be supply constrained or unconstrained. These sensitivity tests are used to evaluate the robustness of the model results. 68. The impacts of growth in the output of four staple crops (teff, barley, maize and sorghum), a crop fully served as material inputs in textile manufacture(cotton), an export crop (coffee), two livestock sectors (cattle and poultry), and two agriculture-related manufactures (grain milling and thread/yarns), and the construction are examined under the conditions specified above. The aim is to provide a contrasting analysis that can inform the dialogue on investment strategies in Ethiopia. More specifically, the results allow a comparison across three broad investment strategies for the country: growth in staple crops (cereals), growth in high value or export crops (cotton and coffee) and growth in manufacturing Results of an Ethiopia fixed price input-output model Impact on growth 69. Under the assumptions summarized above, we first discuss the growth effect of a given sector by assuming that this sector's supply curve can be shifted outward with adoption of any new technology. To do it, we focus on the impact on GDP. Given the economic structure of Ethiopia, the fixed price SIO model results show that a 1 Birr increase in teff domestic supply generates 1.42 Birr rise in total GDP. The analogous change in GDP are Birr for the other three grain crops, 1.56 and 1.54 Birr for cotton and coffee, respectively, 1.56 and 1.55 Birr for cattle and poultry, respectively, 0.61 Birr for grain milling, 1.01 Birr for thread/yarns, and 1.08 Birr for construction (see Table 12) The contrast in the rise in total GDP due to growth in the agricultural sectors or in manufactures and other industrial sector (construction in this case) is marked. This difference arises primarily because of smaller value-added generated by the direct increase in manufacturing and other industrial output. As a fraction of the gross value of output, material inputs used in manufacturing and other industrial range from 51% in thread/yarns to 74% in grain milling. Value added, thus, comprises on 25 to 49% of output only in these three non-agricultural sectors. By comparison, the value added in total output is much higher in the agricultural sub-sectors, ranging between 77 and 98%. Consequently, a 1 Birr increase in agricultural output produces a bigger direct impact on GDP, i.e. GDP produced directed from the targeted sectors. In the case of cereal production, such direct gains in GDP range between 0.75 and 0.87 Birr; 0.82 and 0.94 Birr for coffee and cotton production; and 0.93 and 0.94 Birr for poultry and cattle production, respectively. On the other hand, an identical expansion in the three non-agricultural outputs can only generate 0.20 to 0.43 Birr direct increase in GDP. 9. It is a misunderstanding that the linkage effect presented here tries to pick up a 'driving' sector and define others as 'following' sectors (see, for example, Dercon and Zeitlin, 2009, for such kind of explanation). In contrast, it is impossible for a SIO model to identify which sector is or should be a driver for the economywide growth. Linkages can only occur when many sectors grow simultaneously. Rather, the linkage analysis emphasizes second and third round demand side effects in stimulating growth. Such indirect or general equilibrium effect of any sector's growth is unlikely to be observed in a typical partial equilibrium analysis focusing on a particular sector. 25

26 71. We are more interested in the linkage effect between growth in the targeted subsector and the gains in the rest of the economy, and such linkage effect is captured by the gap between the direct increase in GDP and the total change in GDP (i.e. the difference between the first and second lows in Table 12). Such indirect effect on total GDP is originated from the second, third, and more round linkages between targeted subsector and the rest of the economy. The analysis shows that, when the SAM can be developed with highly disaggregated production sectors, which is the case of the current Ethiopian SAM 10 used in this study, more indirect production linkages have been captured, particularly within manufacturing sectors. For example, the SAM includes six textile subsectors along the textile production process. Some subsectors are downstream activities of others in this process (e.g. fibre and lint are inputs of thread and yarns, which, in return, are inputs of textile and clothing). With such details in manufacturing sectors, we can further decompose production linkages into two parts: direct and indirect. We treat the direct impact on GDP, the sector's value added as the direct production linkages, while the rest of production linkages that generate through multiple rounds of intermediate demand as indirect linkages. 72. Given that Ethiopia's agricultural production is dominated by the use of primary inputs, indirect production linkages induced by agricultural growth are quite small. As shown in Table 12, such linkage effect accounts for 7.3% to 12.2% of total gains in GDP. On the other hand, indirect production linkages as shares of total GDP gains are much larger for the non-agricultural growth, counting for 33.7% % in the three non-agricultural sectors. The strong linkages in the manufacturing production process are the main reasons for Hirschman to emphasize the importance of industrialization in the development process, as "the superiority of manufacturing in this respect is crushing" (Hirschman 1958, p110). Focusing typically on such production linkages the governments of many developing countries emphasized the importance of industrialization and have adopted an import substitution development strategy in the 1960s and 1970s. 73. As some development economists pointed out (see, for example, Mellor, 1995), Hirschman theory emphasizes only the linkages within production process, while consumption linkages have been ignored. Consumption linkages can only be captured in a general equilibrium setup in which both consumption and production are endogenous. Agricultural economists emphasize more such linkages, and believe that they are particularly important in the early development stage, when food and other basic need dominate consumers' consumption bundle, and when most such products are produced locally where a majority of population resides in (Mellor 1995, p13). 74. To assess whether and how important consumption linkages are for Ethiopia's economy today, the SIO model is used to further decompose the consumption linkages from the production ones. What SIO model captures is constrained by the structure of the SAM, which represents the country's current economic structure. Comparing the third and first rows in Table 12 it shows that consumption linkages account for one-third total GDP gains created via growth either in agriculture or non-agriculture, though the absolute level of income effect due to the consumption linkages is quite different between agriculture and non-agriculture. However, when the indirect effect is considered, consumption linkages account for 85% to 93% of indirect effect of agricultural subsector growth on total GDP, except for coffee, in which such linkages account for 78.9% of total indirect effect on GDP. In contrast, consumption linkages are relatively weak in the non-agricultural growth, ranging between 47% and 66% in the three non-agricultural sectors selected (Table 12, last row). Such results are consistent with findings in the literature using similar method but focusing on other low income developing countries. 10. The current Ethiopian SAM includes 24 agricultural subsectors, 29 industrial and 11 service sectors. 26

27 Table 12. Impact on Growth due to one unit of increase in selected sectors' output Cereals Industrial materials/exportable Livestock Manufacturing Other industry Teff Barley Maize Sorghum Cotton Coffee Cattle Poultry Grain milling Thread & yarns Construction Change in GDP Production linkages Direct (sector's own value-added) Indirect (others) Consumption linkages Value-added multiplier Share in total indirect impact on GDP (%) Indirect production linkages Consumption linkages Source: Ethiopia SIO model results. 27

28 75. In short, almost all sectors generate large linkages. But those induced by agricultural activities are larger, primarily because of larger initial value added (income). While the second round linkages across sectors through increased intermediate demand are stronger in the industrial sectors than in the agricultural sectors, given that current agriculture is dominated by the use of primary inputs, the third round linkages through consumers' spending on local agricultural and non-agricultural goods and services dominate the overall indirect effect of sector growth on total GDP gains. Moreover, consumption linkages are much stronger in the agricultural growth than that in the growth led by the industrial sectors and such linkages are often ignored in designing a country's development strategy. Obviously, for a low-income country with large size of population (as in the case of Ethiopia), consumption linkages may play much larger role in growth and development. Because this, a development strategy that can stimulate income growth to a majority of population will definitely generate a large impact on the long term growth and development. Impact on the level and distribution of incomes 76. Impact on the level of household income can also be analyzed using the SIO model results. In the Ethiopian SAM, households are classified into four aggregated groups, rural poor households, rural nonpoor, urban poor households, and urban non-poor. The income levels used to define the country's poverty rate in the rural and urban areas are the thresholds to distinguish the poor from not poor in both rural and urban areas in the SAM. While income sources differ for the rural and urban households and between the poor and not poor, consumption patterns are also different. In general, the rural households spend more income on food, given the income level is lower for an average rural household than for an urban household. In the same area (i.e. in rural or urban), the poor households spend more income on food than the non-poor households. In order to capture the marginal propensity to consume, we apply marginal budget shares (MBS), instead of average budget shares, in the SIO model, such that increases in consumption due to income growth are not necessary the same as their current consumption patterns for both poor and non-poor households in rural or urban areas. The MBS has to be econometrically estimated using household survey data. We adapt the method developed by King (reference) and the estimate results are in Appendix. 77. Table 13 first reports the change in income induced by growth among the four household groups. The results show that, in general, rural households benefit more from agricultural growth as most income gains go to the two rural household groups, while urban households benefit more from manufacturing and other industrial growth. A 1 Birr increase in any of agricultural sector's output will generate 1.23 to 1.51 Birr rise in total household income, while an equivalent change in any of the three non-agricultural sectors' output has much lower positive impact on household incomes. 78. To investigate the distributional effect of growth, we calculate the share of income gains across the four household groups in the second panel of Table 13. We also calculate the ratio of this share over corresponding household's income share in the SAM in the third panel of Table 13. When the ratio is greater than 1 for a particular household, it indicates that this household gains disproportionally more than what its income current shares in the economy. The second part of Table 13 shows that more than 50% of additional income generated by agricultural growth goes to the rural non-poor household group, while the rural poor household group gets about 13% to 33%. The share of additional income going to urban poor household group is extremely low, between 2.7% and 3.3%. In total rural households receive 80% - 85% of total gains in income when such income is generated from agriculture-led growth. On the other hand, the income share of urban non-poor household group in total income gain more than doubles when growth is driven by the non-agricultural sectors (the three sections reported in the table). In total about 40% of such income goes to the urban households, while these households account for 15% - 20% of population in the country. 28

29 79. The other way to assess income distribution effect of growth is to analyze income change for each individual household group. We do it by a ratio of income share in the additional income generated from growth over the share of this household's income in total income currently (in the SAM). The ratio of one for a household indicates that this household is not affected by the change in income distribution, while the ratio being greater (less) than one for a household tells that the new income distribution as an outcome of growth is in favourable (against) this household. As shown in the third panel of Table 13, when growth is led by staple agricultural subsectors, including staple crops and livestock products, the distribution of additional income gain is in favourable of the rural poor household group, as ratio for this group is consistently higher than 1 in the growth led by all the six staple subsectors (ranging from 1.01 in the case of sorghum to 1.35 for cattle led growth). While income distribution led by staple crop growth also favours rural nonpoor household group, this group disproportionally benefits more from export agricultural growth such as coffee and cotton. When growth is led by the non-agricultural sectors, the new income distribution moves to the direction benefiting the urban households, while benefits going to the rural households are proportionally smaller than the size of these households' income in the economy in the initial situation. While such different income distribution effects of growth are the outcome in which price effect is ignored, it still provides us meaningful message in terms of a complicated relationship between growth and income distribution. With the rural households forming the bulk of the poor, the potential impact on the poverty, through income distribution effect, is thus greatest with growth in staple crops and livestock production. A more direct measurement of the pro-poorness of different growth options will be analyzed in the following section using an economy-wide model with endogenized prices. 29

30 Table 13. Impact on Income due to one unit of increase in sectors' output Cereals Industrial materials/exportable Livestock Manufacturing Other industry Teff Barley Maize Sorghum Cotton Coffee Cattle Poultry Grain milling Thread & yarns Construction Rural poor Rural nonpoor Urban poor Urban nonpoor Total Share in total income gains (%) Rural poor Rural nonpoor Urban poor Urban nonpoor Ratio to income share in SAM Rural poor Rural nonpoor Urban poor Urban nonpoor Source: Ethiopia SIO model results. 30

31 Important role of service sector in determining the linkages effect 80. When a SIO model is used to measure the economic linkages or the multiplier effect, the model does it by evaluating selected sector by sector. Because this, it seems to generate certain misunderstanding in explaining the model results and some papers criticized that such analysis is 'too narrow and focused on single-sector growth' (see, for example, Dercon and Zeiline, 2009). To clarify such misunderstanding, it is necessary to further assess how the ability of supply response in the other sectors affects the direction and extent of linkages effect of the studied sectors. In the above analysis, we assume that all private service sectors are supply-unconstrained and they positively respond to the supply shift of studied agricultural and manufacturing sectors. To assess how important service sectors in determining multiplier effect of growth in the agricultural and manufacturing sectors, we conduct an additional scenario in which supply of the four subsectors in the services, trade, transport, financial services, and the other business service, becomes constrained while the assumptions on the other sectors are the same as those in the previous analysis. Such constraints can be justified by lack of infrastructure in road, market and information such that market accessibility of agricultural and non-agricultural producers is limited, or due to institutional and policy barriers such that the difficulties to do business in the service sectors limit the possible response of the private sector to increased supply and demand. In Table 14 we compare the model results with such constrained services with those without such constraints reported in Table As expected, constraints in the supply in the services lower the gains in GDP induced by a one unit increase in selected sectors' output. However, such constraints do not change the relative extent of total GDP gains between growth in the agricultural and in the non-agricultural sectors. While lack of supply response in the service sectors limits the economic linkage effect of growth in the production sector, the constraint on the growth in the manufacturing and other industrial subsectors is more than on the growth in the agricultural sectors. As shown in last panel of Table 14, the constraint in service supply lowers total GDP gains by 13% - 24% when such gain is due to growth in the agricultural sectors, while it lowers total GDP gains by 33% - 43% when the gain is due to growth in the non-agricultural sectors. When GDP gains are decomposed into the two parts, i.e., due to production or due to consumption linkages, Table 14 shows that lowered consumption linkages effect is the main channel for the service sectors to constrain the linkages in the economy when agriculture is the trigger for such linkages, while both production and consumption linkages are equally important channels through which the service sectors constrain the linkages effect when the non-agricultural subsectors are the trigger for such linkages. 31

32 Table 14. Importance of services in measuring multiplier effect Teff Barley Maize Sorghum Cotton Coffee Cattle Poultry Grain milling Thread & yarns Construction Total gains in GDP Supply-unconstrained services Supply-constrained services Production linkages Supply-unconstrained services Supply-constrained services Consumption linkages Supply-unconstrained services Supply-constrained services Value-added multiplier Supply-unconstrained services Supply-constrained services Ratio between constrained and unconstrained services Total gains in GDP Production linkages Consumption linkages Value-added multipliers Source: Ethiopia SIO model results. 32

33 Summary of agricultural linkage effect assessed by a SIO model 82. While the application of a SIO model cannot explicitly assess the source of growth, given the constraints in land and other resources faced by the Ethiopian economy, it is obvious that technological change and hence productivity must be the main source of sustainable growth. Alternative growth options have significant differences in the direction and extent of growth linkages. Growth in agriculture produces stronger linkages with the rest of economy than growth in non-agriculture. The potential benefits of stimulating growth in agricultural production (albeit differentiated by products) are thus substantial. Nevertheless, the size of this potential as well as the extent of its realization depends on a parallel expansion in non-agricultural sectors (particularly in those associated with growing input or consumption demand). Stronger linkage effect of agricultural growth is not only due to its use of primary input, but also consumption linkages. The study shows that at Ethiopia's current development stage, consumption linkages are more important than the second-run production linkages, which are high among the manufacturing sectors. Consumption linkages are particularly high for growth led by the agricultural sectors, indicating that the importance of agriculture to the overall economic growth is not only due to its size in the economy, but also due the stage of development in which, at current, a majority of population in Ethiopia is poor who consume most goods and services (including non-agricultural goods and services) produced locally. 83. When households can be disaggregated according to different income levels and rural and urban location in a SAM, the SIO model can be used to assess income distribution effect of growth. While ignoring price effect is a critical shortcoming of a SIO model, the analysis does provide us meaningful message about the complicated relationship between growth and income distribution. Staples led growth has shown to benefit more the rural households, particularly the rural poor households, while export crop led growth seems to benefit rural non-poor households disproportionally. When growth is led by the manufacturing sectors, urban households are major beneficial. Income distribution is worse and income gap between the rural and urban households increases under such growth options. While the SIO model cannot explicitly measure the poverty impact of alternative growth options, it implicitly indicates the most effectiveness of staple led growth in poverty reduction. 84. It should note that the SIO model results depend on the assumption of constrained or unconstrained supply elasticity among various non-agricultural sectors. By varying the set of nonagricultural sectors assumed to be supply unconstrained show different results. In order to realize the important role of services in measuring linkages effect, we altered the assumption about unconstrained service supply in an additional scenario and assumed that trade, transport, financial and other business services are constrained in their response to the growth in the studied agricultural and non-agricultural subsectors. To do it we find that while the extent of linkages effect is lowered in all cases, growth induced by the non-agricultural sector is constrained more by the service sectors. Barriers to growth due to constraints faced by the service sector should be paid more attention in a development strategy in which either agriculture or manufacturing is emphasized. 85. It has to point out that with globalization, growth linkages seem to be weakening in the manufacturing sector, as export-oriented manufacturing does not need to depend on domestic markets for input supply and output demand (reference for this argument). While it is true that many developing countries want to pursue such growth path, following the success in China and other Asian countries' experience, the current Ethiopian economy actually shows unutilized capacity among many manufacturing sectors, even at the development level where manufacturing accounts for a small share of the economy. The industrial survey shows that the main reason for unutilized factory capacity is due to domestic demand constraint. When such firms cannot produce goods that are for domestic market, can they produce for exports which often requires much better quality and more competitive in price? Moreover, globalization is a two-way thing. When domestic firms have opportunities to export their products using imported goods as input materials, they are also facing stronger competitions from imported goods they produce in their own 33

34 country's market. We observe that in many African countries' domestic markets have become increasingly dependent on imported manufacturing goods and de-industrialization has occurred among some manufacturing sectors. Obviously, competitiveness in export and domestic markets has become more or less as a same thing. Without increasing domestic market demand and improving competition in domestic market, it is unlikely to expect Ethiopia to jump into international market for manufacturing exports. Production linkages effect analyzed in this study, thus, is still highly relevant to the current Ethiopian economy. 86. While the SIO model is a useful tool for linkage analysis, its rigidity in prices is obvious an improper assumption given that linkages are primarily through the interactions between supply and demand in the domestic market. In order to overcome such shortcomings as well as the arbitrary assumptions of constrained and unconstrained supply elasticity, an economy-wide model is developed and applied to further assess the growth linkages and their impact on income and poverty reduction. In this economy-wide model, not only domestic prices are endogenous and all economic sectors can respond to changes in prices with different levels of elasticity, the economy is further disaggregated geographically. Results from both models are compared and the complementary roles of the two models are also discussed at the end of this section Growth linkages in the Ethiopian economy an economy-wide multimarket model 87. Ethiopia is an open economy. However, as a land-locked country with high transportation and other marketing costs, partly explained by considerable geographic distances and an inadequate road network, prevent world market prices from automatically translating into domestic prices. As a consequence, many commodity prices, especially those of agricultural products, are actually determined by supply and demand conditions in the domestic market. For these reasons, it is necessary to take into account for the interaction of prices and growth (the price effect) in analyzing agriculture-non-agriculture linkages. Accordingly, in this sub-section we develop an economy-wide multimarket (EMM) model in which prices of most agricultural and some non-agricultural products are endogenous variables. We apply this EMM model to Ethiopian economy to further assess the importance of the agricultural sector in growth and poverty reduction. Why an EMM model? 88. It is possible to develop a CGE model based on the same SAM used in the SIO model analysis discussed in the previous chapter. Indeed, the CGE approach is more preferable for economy wide analysis and more comparable with above SIO analysis when the same SAM is used for both models. However, as shown in the above analysis, the current SAM is for the national economy and there are only four aggregate households at the national level. Given the current Ethiopian economy is still dominated by agriculture and more than 80% of population live in the rural areas, special attention must be paid to the structure of agriculture in the linkage analysis. It is well known that agricultural production systems are typically characterized by the interactions between human behaviours and natural environment. With heterogeneity in agro-ecological, social and economic conditions, agriculture in Ethiopia is highly diversified. To analyze the economic linkages in the country, it is necessary to understand the role of different agricultural subsectors at different locations of the country. Moreover, agricultural development is constrained by market opportunities and conditions of market access provide different such opportunities to different locations in the country. 89. To take into consideration of geographic factors such as agro-ecological conditions, population distribution, production and market locations and connections and in order to better present the agricultural sector and rural economy in the linkage analysis, we have developed a highly disaggregated EMM model for Ethiopia. Most multimarket models focus on particular subsectors of agriculture or segments of 34

35 economies. The model developed for this study focuses on agriculture but puts the agricultural sector in an economy-wide context, such that the model can be used for the economy-wide linkage analysis. The original EMM model was developed and applied for the food security analysis in Ethiopia (Diao and Nin Pratt, 2007). This model is extended and modified for this study in order to be consistent with the nonagricultural economy described by the SAM discussed above, while detail agricultural sectors are still kept as before. 90. Specifically, there are 32 agricultural commodities or commodity groups (see Table B1 in the Appendix B for a list of agricultural commodities/sectors included in the model) in the EMM model. In contrast with the SAM that represents the national economy, both agricultural production and consumption in the EMM model are further disaggregated into sub-national regions in order to capture the geographic heterogeneity of sectors and households. Limited by the data, the model captures totally 56 administrative zones and all agricultural supply and demand functions are defined at the zonal level. Detail description of the EMM model can be found in Appendix A, while a number of key results concerning impact on growth and poverty are reported as following. Three Ethiopias - areas of food deficit, food balanced, and food surplus 91. With highly spatially disaggregated information, Ethiopia can be examined according to sources of domestic food availability, resulting in a division of Ethiopia into three categories: areas of food deficit, food balanced, and food surplus (Figure 4). Based on data from Ethiopia s 2001/02 Agricultural Census, woredas in which the average cereal equivalent output per rural household is 20% below the national average fall into the food deficit area, those with output between 80% and 120% of the national average form the food balanced area, and those with output 20% or more above than national average constitute the food surplus area The study includes 460 woredas. Cereal output equivalents were used to represent food availability. Equivalents include cereals, pulses, oil crops, and root crops, and account for over 60% of household food consumption in the urban and 70% in rural area. The conversion ratio for crops other than cereals was based on their calorie content (see the FAOSTAT web site). 35

36 Figure 4. Food deficit, food balanced, and food surplus areas The three areas are based on woreda-level ratios of cereal equivalent output per household to the national average: Food deficit area ratio of less than 0.8 Food balanced area ratio of between 0.8 and 1.2 Food surplus area ratio of greater than 1.2 Source: Constructed by authors based on Democratic Republic of Ethiopia (2002). 92. Almost 30 million of Ethiopians live in the food deficit area, where the annual food availability averages only about 530 kilograms per household, even in a good year. 12 This represents half the national average (Table 15). In contrast, food availability per household in the food surplus averages kilograms, which is 70% above the national average. The high proportion of cereals and other staple crops in the food availability calculation (more than 70% of rural household food consumption) is indicative of extremely low food availability and alarming food insecurity, in turn a reflection of very low income levels per capita and a very high rate of poverty. Compared with the rural poverty rate of 46% nationwide, 13 the poverty rate in the food deficit area is 60%; in the food surplus area it is less than 40%. Fifty per cent of the rural poor now live in the food deficit area; that area, however, only accounts for 37% of the total rural population. 93. A major constraint to meeting food demand for the majority of rural households in the food deficit area is extremely small farmland area. National farm size, including permanent and temporal crops, averages about one hectare. In the food deficit area, however, farm size averages only 0.57 hectare compared with 1.38 hectares in the food surplus area (Table 15). Of the 184 woredas constituting the food deficit area, per household farmland is less than 0.4 hectares in half of them, and less than 0.3 hectares in one-third of them. Cereal production yields are also lower than the national average, further eroding food security in these areas. The average cereal yield in the food deficit area is about one metric tonne per hectare, 20% below the national average and 30% below yields in the food surplus area (Table 16). Even taking other staple crops into account, a significant yield gap in staple crop production still exists between the food deficit and food surplus areas. 12. The calculation is based on the data for 2001/02, which is a good harvest year for most areas in the country. 13. The poverty rate used in this study is consistent with data from HICES 1999/2000 (CSA 2000a). 36