Technical note: Analysis of price incentives and disincentives for wheat in Kenya for the time period 2005-2013

August 2014

Technical note: Analysis of price incentives and disincentives for wheat in Kenya for the time period 2005-2013

August 2014

This technical note is a product of the Monitoring and Analysing Food and Agricultural Policies (MAFAP) programme. It may be updated as new data becomes available.

MAFAP is implemented by the Food and Agriculture Organization of the United Nations (FAO) in collaboration with the Organisation for Economic Co-operation and Development (OECD) and national partners in participating countries. It is financially supported by the Bill and Melinda Gates Foundation, the United States Agency for International Development (USAID) and FAO.

The analysis presented in this document is the result of partnerships established in the context of the MAFAP programme with Kenya Agricultural Research Institute (KARI).

This technical note was prepared by Mulinge, W.M. and F.M. Murithi of the Kenya Agricultural Research Institute (KARI), with support and contributions from Ahmed, M. of the FAO.

For more information: www.fao.org/in-action/mafap

Recommended citation: FAO. 2015. Analysis of price incentives for Wheat in Kenya. Technical notes series, MAFAP, by Mulinge, W.M., F.M. Murithi and Ahmed M., Rome.

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CONTENTS CONTENTS ............................................................................................................................................... iv

SUMMARY OF THE NOTE .......................................................................................................................... v

COMMODITY CONTEXT ........................................................................................................................ v DRIVING FACTORS ........................................................................................................................... vi

RECOMMENDATIONS ...................................................................................................................... vi

1. PURPOSE OF THE NOTE ................................................................................................................... 1

2. COMMODITY CONTEXT ................................................................................................................... 2

PRODUCTION ....................................................................................................................................... 2 CONSUMPTION/UTILIZATION.............................................................................................................. 4 MARKETING AND TRADE ..................................................................................................................... 5 DESCRIPTION OF THE VALUE CHAIN ................................................................................................... 6 POLICY DECISIONS AND MEASURES .................................................................................................... 8

3. METHODOLOGY ............................................................................................................................. 11

DATA REQUIREMENTS, DESCRIPTION AND CALCULATION OF INDICATORS ......................................... 15

TRADE STATUS OF THE PRODUCTS ................................................................................................... 15 MARKET PATHWAYS ANALYZED ........................................................................................................ 15 BENCHMARK PRICES .......................................................................................................................... 15 DOMESTIC PRICES.............................................................................................................................. 16 EXCHANGE RATES .............................................................................................................................. 17 OBSERVED ACCESS COSTS ................................................................................................................. 17 OBSERVED ACCESS COSTS ................................................................................................................. 19 BUDGET AND OTHER TRANSFERS...................................................................................................... 20 QUALITY AND QUANTITY ADJUSTMENTS .......................................................................................... 20 DATA OVERVIEW ............................................................................................................................... 20 SUMMARY OF INDICATORS ............................................................................................................... 23

4. RESULTS AND INTERPRETATION .................................................................................................... 25

5. CONCLUSIONS AND RECOMMENDATIONS ................................................................................... 28

MAIN MESSAGE ................................................................................................................................. 28 RECOMMENDATIONS ........................................................................................................................ 29 LIMITATIONS ...................................................................................................................................... 29 FURTHER INVESTIGATION AND RESEARCH ....................................................................................... 30

BIBLIOGRAPHY ....................................................................................................................................... 31

ANNEX I: Data and calculations used in the analysis ............................................................................ 33

SUMMARY OF THE NOTE

COMMODITY CONTEXT • Wheat is the second most important agricultural commodity in Kenya from a food security

point of view, both in terms of quantity consumed and calorie intake. • An increasing number of consumers spend more on wheat products than on maize and more

than twice as much as they spend on rice. Although far behind maize, it is twice as important as a source of calories for Kenyans as the third most important cereal, rice.

• Wheat consumption is associated with urbanization and higher incomes and, therefore, has been an increasing component in Kenyans’ diets. Besides its apparent prevalence among higher income consumers, wheat has a convenience factor because bread and other wheat products can be prepared in large-scale establishments and distributed in an easily consumed form with little additional preparation.

• Production and area under production grew by 18.4 percent and 4.6 percent respectively, while yield declined by 2.2 percent between 2005 and 2013. The growth was higher during 2011-13 where production, area under production and yield grew by 19.3 percent, 7.3 percent, and 1.9 percent respectively. The growth in wheat production was mainly due to expansion in area under production instead of increase in productivity.

• Consumption, on the other hand, increased by 11.9 percent for the entire period (2005-2013) while imports grew on average during the same by 10.8 percent.

• Wheat has a different policy context because it is a major import. Kenya now imports about five times as much wheat as it produces. Wheat is imported from world markets at world market prices in contrast to other food security related commodities like maize, beans and rice that may be imported in significant quantities from other East African countries.

Price incentives to wheat producers in Kenya (2005-2013)

• The observed Nominal Rate of Protection (NRP, green line) in the graph above measures the effect of policy distortions and overall market performance on price incentives for producers. These factors result in a general protection for wheat producers in Kenya with farm gate

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prices being 40 percent above the reference price. However, these price incentives tend to vary over time because of the short term adjustment of the tariff imposed on wheat imports.

• The adjusted NRP (blue line) captures the same elements as the observed NRP in addition to any market distortions resulting from inefficiencies in the commodity’s value chain and exchange rate misalignment. Due to the simplicity of the value chain of wheat, market distortions due to value chain inefficiencies are minimal and hence the adjusted NRP is very close to the observed NRP, i.e., the market development gap is small as reflected by the area in red.

DRIVING FACTORS The major driving factor for the producer’s price incentives is the fluctuation in tariff rate imposed on wheat imports. The burden of the tariff is borne by consumers to the benefit of producers and the Government.

RECOMMENDATIONS • Maintain the low tariff on wheat imports announced in 2011. Inability of wheat farmers to be

competitive is strong signal for the need to technological change to improve productivity and, hence, lower unit cost of production. This will benefit consumers and encourage export of processed wheat products. While supplying of the domestic market should apparently be the first priority, Kenya may need to align its tariff policy with its neighbors to avoid disparities in the regional market for wheat products.

• The following are options that can be taken to improve farmer’s competitiveness through higher productivity:

• Development of wheat varieties suitable for different agro ecological zones of Kenya and also resistant to Wheat Stem Rust: Breeding wheat varieties suitable for different agro ecological zones and mega environments would be very challenging for many nations in Sub-Saharan Africa, given the scarcity of funds for agricultural research. Wheat Stem Rust (UG 99) has been causing havoc in Kenya.

• Provision of effective farmer advisory services: Updated farmer advisory services are needed to better serve the needs of wheat farmers and, in particular, to introduce wheat as a new crop to smallholder farmers.

• Improved postharvest management practices: There is a need for strong postharvest management support to reduce quantity and quality losses in wheat value chains. Postharvest management practices have major impacts on the quality of wheat grain for processing and various end uses. Developing or improving storage, handling and processing activities, while taking end-market specifications and quality into account, is critical. These measures help improving the quality of wheat produced and increased profitability of wheat production.

• Create a conducive enabling environment: Domestic wheat production could be made more competitive by improving marketing efficiency and lowering transaction costs. In addition, by designing policies, institutions and infrastructure to reduce the cost of acquiring inputs, marketing wheat, and procuring wheat from international markets, the situation of farmers is likely to improve in particular when domestic demand exceeds production.

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1. PURPOSE OF THE NOTE This technical note is an attempt to measure, analyse and interpret price incentives and disincentives for wheat in Kenya over the period 2005-2013.

For this purpose, yearly averages of domestic farm gate and wholesale prices are compared with reference prices calculated on the basis of the price of the commodity in the international market. The price gaps between reference prices and domestic prices along the commodity’s value chain indicate the extent to which incentives (positive gaps) or disincentives (negative gaps) were present at the farm gate and wholesale level. The price gaps are expressed in relative terms as a percentage of the reference price, referred to as the Nominal Rate of Protection (NRP). These key indicators are used by MAFAP to assess the effects of policy and market performance on prices.

This technical note begins with a review of the commodity’s production, consumption/utilization, marketing and trade, value chain and policy context (Chapter 2). It also provides a detailed description of how key data elements were obtained and indicators were calculated (Chapter 3). The indicators were then interpreted in light of existing policies and market characteristics (Chapter 4), and key policy recommendations were formulated on the basis of this interpretation (Chapter 5). Finally, the note concludes with a few main messages, limitations of the analysis and areas identified for further research to improve the analysis.

The results and recommendations presented in this analysis can be used by stakeholders involved in policy-making for the food and agriculture sector. They can also serve as input for evidence-based policy dialogue at the national, regional or international level.

This technical note should not be interpreted as an in-depth value chain analysis or detailed description of the commodity’s production, consumption/utilization, marketing and trade or policy context. All information related to these areas is presented merely to provide background on the commodity under review, help understand major trends and facilitate the interpretation of the indicators.

All information in this technical note is subject to review and validation.

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2. COMMODITY CONTEXT Wheat has a unique policy context because of its relevance to food security and the role that trade plays in wheat supply. After maize, wheat is the second most important agricultural commodity in Kenya, both in terms of quantity consumed, contribution to GDP (0.2 percent) after maize (3.1 percent) and calorie intake. Muyanga et al. (2005) found that Nairobi consumers in 2003 spent 34 percent more on wheat products than they did on maize and more than twice as much as they spent on rice. Although far behind maize, wheat is twice as important as a source of calories for Kenyans as the third most important cereal, rice. Wheat consumption is associated with urbanization and higher incomes and, therefore, has been an increasing component in Kenyan’s diets. Besides its apparent prevalence among higher income consumers, wheat has a convenience factor because bread and other wheat products can be prepared in large-scale establishments and distributed in a form that is easily consumed with little additional preparation.

Wheat is Kenya’s major import. The country now imports about five times as much wheat as it produces (Economic Survey, 2013, GoK). Wheat must be imported from world markets at world market prices in contrast to other food security related commodities like maize, beans and rice that may be imported in significant quantities from other East African countries.

PRODUCTION Wheat is also unique in that nearly all production takes place on large- and medium-scale farms, using capital intensive technology. Longmire and Lugogo (1989) report on surveys that found that there were only about 1 700 smallholder wheat producers in the early 1980s. Similarly, Makanda and Oehmke (undated) estimate that, a decade later, smallholders still only accounted for about 15 percent of the area planted with wheat. In 2002, Nyangito, Ikiara and Ronge (2002) report the dominance of large-scale farmers, accounting for 75 percent of the area planted and 83 percent of production. In 2010, Chemonics International reported that there were 2,000 small-scale (<5ha) and only 20 large-scale (>40ha) wheat farmers under the Cereal Growers Association, with the large-scale farmers responsible for 80 percent of the total output.

The small number of wheat farmers in Kenya receives effective tariff protection from imports. The technology used by medium- and large-scale farms is probably not too different from the one used in Western Europe, with a similar complement of tractors, tillage equipment and combines. Operations, such as combine harvesting, are often contracted. Even small-scale farmers may depend on contractors for tillage and harvesting operations, although the machinery may be smaller.

The main growing regions have been the areas above 1 500 meters above sea level in the Nakuru, Uasin Gishu, Trans Nzoia and Laikipia Counties counties (Figure 1). The break-up of some of the large farms in these counties resulted in a switch to maize production or a combination in which wheat is grown as a cash crop and maize is produced for subsistence consumption. However, new wheat growing areas have opened up on land leased from Masai pastoralists in Narok, a county bordering Tanzania. Makanda and Oehmke (undated) report that GOK estimates up to 500 000 ha could be planted to wheat in Narok.

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Figure 1. Wheat growing counties in Kenya

Figure 2 shows long-term trends in wheat production area and yield in Kenya. The area for wheat has increased marginally since independence in 1963 and has remained at an average of 120 000 hectares for the last decade. Yields increased at an annual rate of about 1.5 percent between 1960 and 1985. Since that period, they have trended downward at an average annual rate of about -0.7 percent. Yields also appear to have become more variable since 1985. The regional shift from the large farm area in Western Kenya to Narok and the greater share coming from small-scale farmers likely explain this decline in yields. The shift towards more liberalized markets in the 1990s may also be a factor. Between 2005 and 2013, production increased from 225 000 Tonnes to 390 000 Tones (i. e., by over 70 per cent. During the same period, harvested area increased by 25 per cent. This indicates that the growth in wheat production was partly due to area expansion and partly to improved productivity. A record production and yield of 512 000 Tonnes and 3.2 Tonne per ha, respectively, were recorded in 2009. The cause of this record production and yield is not apparent.

According to FAO’s wheat database, Kenya has nearly a million hectares with medium potential for wheat production compared to the area currently under production. Of all the rainfed wheat producing countries in Africa, Kenya has recorded the largest average yields, at 1.8-3.2 tonnes/ha. It has all the natural resources it needs to achieve self-sufficiency in wheat (FAO, 2014). Nevertheless, wheat competes with other demands for land in Kenya and may well lose out to other more profitable crops. It is not clear whether self-sufficiency is an appropriate goal from an economic perspective.

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Figure 2: Kenya wheat production, area, and yield

Source: http://www.indexmundi.com/agriculture/?country=ke&commodity=wheat

Over the period 2005-2013, wheat production averaged about 348 000 tonnes, of which about 3 percent being retained for seed (Table 1). Exports were negligible, while imports averaged about 668 000 tonnes, contributing to a total average supply of over 1 million tonnes annually. However, the supply is extremely variable during this period; production varied from a low of 219 000 tonnes in 2009 to 512 000 tonnes in 2009. The low level of production in 2010-2011 is likely related to drought in major production districts. Imports appear to have been somewhat pro-cyclical, with the highest levels occurring in the same year of highest production (Table 1).

Table 1: Kenya wheat production and disposition, 2005 - 2013

(‘000 tonnes) 2005 2006 2007 2008 2009 2010 2011 2012 2013

Production 368.9 329.2 322.3 336.7 219.3 512.0 268 442 390

Sales to NCPB 122.6 98.6 107.5 82.1 123.1 190.2 100.9 155 185

Retention for seed 12.0 8.3 10.0 10.0 10.0 10.0 10.0 10.0 10.0

Imports 621.8 650.4 564.3 538.5 781.7 848.1 1002.7 1044.8 1033.1

Supply 990.7 979.6 886.6 875.2 1001.0 1360.1 1832 1582 1790

Apparent consumption 927.2 960.2 994.4 1,029.9 1,066.5 1,104.5 1,575 1,700 1,800

Surplus/shortage 63.5 19.4 -107.8 -154.7 -65.5 255.6 -257.0 118.0 10.0

Sources: FAOSTAT for production and seed retention; Kneya National Burea of Statistics (2008 and 2014).

CONSUMPTION/UTILIZATION Figure 3 shows trends in production, trade and apparent consumption from 1960 to 2013. Apparent (estimated) consumption has been growing steadily at an average of over 4 percent per year. With production largely stagnant, the gap has been met by a continuous increase in imports. Consumption has increased at an average annual growth rate of 11.9 percent for the entire period (2005-2013).

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Figure 3: Kenya wheat supply, Imports, exports and apparent consumption (1960-2013)

Source: Index Mundi (2014).

The average per capita intake over the period 2005-2013 is slightly more than 28 kg/person/year, as compared to 63.1kg/person/year for maize (Economic Survey, 2014). While the fall in production in 2009 may have been related to the drought, the fall in consumption in the same year may have been a response to the higher cost of imported wheat resulting from the 2007-2008 price spike in global markets.

MARKETING AND TRADE As Figure 4 indicated, Kenya meets much of its demand for wheat through imports. From 2010 to 2013, 70% percent of Kenya’s wheat imports came from Russia (34%), Ukraine (25%), andArgentina (11%) while the United States, Pakistan and Australia combined supplied about 14 percent of the imports (Figure 4). The balance of 16 percent is supplied from a number of other countries mostly in South America and Europe.

Kenya exports some flour and products from the bakery industry, mainly to its neighboring countries under the market access terms of Common Market for Eastern and Southern Africa (COMESA) and East Africa Community (EAC). Currently, this market is relatively small, but there is substantial potential for future growth Musyoka (2009). By-products of the milling industry, flour and pollard, are an important input for the animal feed industry. Milling capacity is located in all the major regions of Kenya.

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Figure 4: Average Wheat imports by country of origin, 2006-2013

Source: Global Trade Atlas (2014)

DESCRIPTION OF THE VALUE CHAIN Figure 5 shows a representative wheat value chain in Kenya. The wheat value chain is relatively simple with relatively fewer intermediaries as compared to maize and rice. Government involvement in the value chain currently entails providing support to farmers in the form of research and extension, in regulating and promoting trade through the National Cereals and Produce Board (NCPB), which is responsible for maintaining a food reserve and monitoring prices and markets. The NCPB has occasionally been called upon to directly intervene in the markets to respond to exceptionally high prices.

Russia 34%

Ukraine 25%

Argentina 11%

Australia 5%

Pakistan 5%

United States 4%

Rest of the world 16%

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Figure 5: The wheat value chain in Kenya

Source: Adapted from Gitau, et al. (2009)

Farmers in Kenya sell wheat either to the NCPB or directly to the millers. Small-scale farmers usually sell directly to the NCPB, while large-scale farmers may sell to both. When they sell to millers, they deliver wheat directly to the millers in Nairobi. Kenya National Bureau of Statistics (KNBS) reported wheat sales to NCPB averaged 36 percent of the production over the period 2005-13 (Table 1). Presumably, farmers receive a price that compensates them for the additional costs they must bear in delivering wheat from the farm to Nairobi.

There are 100 medium scale millers and 23 large scale millers in Kenya. The installed capacity of the medium scale millers is between 100-200 MT per day, while for the large scale millers installed capacity is 3,600 MT per day (Gitau et al., 2010). Both medium and large scale millers are located in the major town (Eldoret, Nakuru and Narok). From the millers, the milled wheat either goes to the bakeries which produce wheat by- products such as cakes, bread, and biscuits, amongst others. The milled wheat is also distributed through supermarkets or wholesalers who then sell directly to consumers.

Transport services cuts across the whole value chain. Inefficiencies encountered by the transporters along the value chain were mainly the high cost of operation due to high fuel prices (Gitau et al., 2010). Thus, an increase in the price of fuel will have a significant effect on the total cost of transportation. The domestic fuel prices have continued to increase and this cost is transmitted to the farmers and traders along the chain.

Both farmers and millers organizations play a crucial role in the value chain. Farmers are represented by the Cereal Growers Association (CGA), which is mainly present in the traditional large farm area of Western Kenya, and the Narok Wheat Farmers Association. Millers are represented by the Cereal Millers Association.

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An important element of the wheat value chain in Kenya is the port and grain handling facilities. Until 2000, Kenya did not have elevators and other specialized grain handling infrastructure. Grain arriving at the Mombasa Mombasa had to be bagged, and grain handling was both labor intensive and expensive, with port handling costs amounting to about USD 35/tonne. In 2000, the private company Grain Bulk Handlers Ltd. began operating modern bulk grain handling facilities where?. The company has held a monopoly over bulk grain handling for eight years and continues as the sole bulk grain operating facility. This has lowered costs by USD 8-10 per tonne, but it could be argued that increased competition in bulk grain handling at the port would lead to even larger reductions in cost.

POLICY DECISIONS AND MEASURES Before 1993, all aspects of wheat marketing were essentially controlled by a government board. In 1979, this authority was vested in the National Cereals and Produce Board (NCPB), which replaced the Maize and Produce Board and the Wheat Board of Kenya without changing the command and control approach to grain marketing.

The NCPB was given monopoly powers to purchase, store, market and generally manage cereal grains and other produce in Kenya. It was empowered to regulate and control the collection, movement, storage, sale, purchase, transportation, marketing, processing, distribution, import, export, and supply of maize, wheat and other scheduled agricultural produce under a controlled price system.

Prices were set each year at each level in the value chain. The NCPB bought from farmers and sold to millers at administratively determined prices, while wholesale and retail prices for flour and bread were set by the Office of the Price Controller of the Treasury.

In the framework of the Grains Sector Reform Program, the monopoly powers of NCPB were gradually reduced, culminating in a fully liberalized market in 1993. Between 1996 and 1998, the NCPB Commercialization Project sought to transform the NCPB into a commercially viable entity. The NCPB is now a publicly owned commercial agency that purchases grains for strategic reserves and monitors trade in cereals.

With liberalization of wheat marketing, private sector imports and domestic marketing are no longer proscribed. However, large-scale wheat farmers have long influenced pricing and other aspects of wheat marketing as have the millers. In the 1996/1997 harvest season, farmers in former Uasin Gishu District, a major wheat-growing region, rioted over low producer prices offered by millers and NCPB. The Government forced NCPB to buy the wheat at a higher price than the then prevailing market price (Nyangito, Ikiara, and Ronge, 2002)

These authors also suggest that domestic wheat producers are able to force the NCPB to pay them an Australia hard, white wheat import parity price for lower quality Kenya soft wheat. It is not clear whether these costs are passed forward to the millers. It is possible that the system operates somewhat like a bilateral monopoly with prices agreed upon between the Cereal Growers Association and the two wheat farmers organizations.

Most of the measures that currently have a direct impact on the wheat market are related to trade and tariffs. In recent years, Kenya has protected domestic wheat producers with a tariff in the 25 to 35 percent range, although tariffs of 50 percent appear to have been levied in 2000 under a variable

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levy system operating at that time. Under COMESA, Kenya’s tariffs were harmonized with those of other members at 35 percent for wheat and 60 percent for wheat flour. The East African Community (EAC) harmonized these rates in its agreement on a CET in 2004. However, members of COMESA and the EAC have agreed to a process to vary these rates as circumstances require. Thus, Kenya reduced its wheat tariff from 35 to 25 percent in response to the wheat price spike of 2007-2008. Tanzania and Uganda also lowered their tariffs on wheat, which were reduced to 10 percent and zero, respectively, in 2010.

Similar to Tanzania, Kenya’s tariff was reduced further from 25 percent to 10 percent in June 2010. This was done by a duty remission scheme in which importers initially paid the 35 percent tariff and then applied for remission. This approach may have been used as a means of limiting the quantity eligible for the lower tariff. This reduction was implemented despite protests by large-scale farmers in Narok. Finally, in 2011, a continuation of the “tariff-abatement” policy was announced. Under the new scheme registered millers were allowed to import wheat duty free.

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3. METHODOLOGY MAFAP methodology seeks to measure price incentives for producers and other marketing agents in key agricultural value chains. The analysis is based on the comparison between observed domestic prices and constructed reference prices. Reference prices are calculated from the international price of the product at the country’s border, where the product enters the country (if imported) or exits the country (if exported). This price is considered the benchmark price free of influence from domestic policies and markets. MAFAP estimates two types of reference prices – observed and adjusted. Observed reference prices are those that producers and other marketing agents could receive if the effects of distortions from domestic market and trade policies, as well as overall market performance, were removed. Adjusted reference prices are the same as observed reference prices, but also exclude the effects of any additional distortions from domestic exchange rate policies, structural inefficiencies in the commodity’s value chain, and imperfect functioning and non-competitive pricing in international markets.

MAFAP’s price incentives analysis is based on the law of one price, which is the economic theory that there is only one prevailing price for each product in a perfectly competitive market. This law only applies in the case of homogeneous goods, if information is correct and free, and if transaction costs are zero. Thus, this analysis was conducted for goods that are either perfectly homogeneous or perfect substitutes in the local market in terms of quality, or, failing that, are simply comparable goods. Indicators calculated from reference and domestic prices will, therefore, reveal whether domestic prices represent support (incentives) or a tax (disincentives) to various agents in the value chain.

Domestic prices are compared to reference prices at two specific locations along commodity value chains – the farm gate (usually the main production area for the product) and the point of competition (usually the main wholesale market where the domestic product competes with the internationally traded product). The approach for comparing prices at each location is summarized below, using an imported commodity as an example. In this situation, the country is importing a commodity that arrives in the port at the benchmark price (usually the unit value CIF price at the port of entry). In the domestic market, we observe the price of the same commodity at the point of competition, which is in this case the wholesale market, and at the farm gate. We also have information on observed access costs, which are all the costs associated with bringing the commodity to market, such as costs for processing, storage, handling, transport and the different margins applied by marketing agents in the value chain. These include access costs between the border and wholesale, as well as between the farm gate and wholesale.

The benchmark price is made comparable to the domestic price at wholesale by adding the access costs between the border and wholesale, resulting in the observed reference price at wholesale. This takes into account all the costs incurred by importers and other agents to bring the commodity to market, which in effect, raises the price of the commodity. The reference price at wholesale is further made comparable to the domestic price at the farm gate by deducting the access costs between the farm gate and wholesale, resulting in the observed reference price at farm gate. This takes into account all the costs incurred by farmers and other agents to bring the commodity from the farm to the wholesale market. Mathematically, the equations for calculating the observed

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reference prices at wholesale (𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜ℎ) and farm gate �𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜� for an imported commodity are as follows:

𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜ℎ = 𝑅𝑅𝑏𝑏 + 𝐴𝐴𝐴𝐴𝑜𝑜𝑜𝑜ℎ

𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜 = 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜ℎ − 𝐴𝐴𝐴𝐴𝑜𝑜𝑜𝑜𝑜𝑜

where 𝐴𝐴𝐴𝐴𝑜𝑜𝑜𝑜ℎ are the observed access costs from the border to wholesale, including handling costs at the border, transport costs from the border to the wholesale market, profit margins and all observed taxes and levies, except tariffs, and 𝑅𝑅𝑏𝑏 is the benchmark price. 𝐴𝐴𝐴𝐴𝑜𝑜𝑜𝑜𝑜𝑜 are the observed access costs from the farm gate to wholesale, including handling costs at the farm, transport costs from farm to wholesale market, processing, profit margins and all observed taxes and levies.

The same steps described above can be taken a second time using benchmark prices and access costs that have been adjusted to eliminate market distortions due to exchange rate misalignments, structural inefficiencies in the commodity’s value chain 1 and imperfect functioning and non-competitive pricing in international markets, where possible and relevant. The adjusted benchmark prices and access costs are then used to generate a second set of adjusted reference prices, in addition to the first set of observed reference prices calculated.

For exported commodities, a slightly different approach is used. In this case, the border is generally considered the point of competition (wholesale), and the unit value FOB price for the commodity is normally taken as the benchmark price. Furthermore, observed and adjusted reference prices at wholesale are obtained by subtracting, rather than adding, the access costs between the border and wholesale. Mathematically, the equations for calculating the observed reference prices at wholesale (𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜ℎ) and farm gate �𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜� for an exported commodity are as follows:

𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜ℎ = 𝑅𝑅𝑏𝑏 − 𝐴𝐴𝐴𝐴𝑜𝑜𝑜𝑜ℎ

𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜 = 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜ℎ − 𝐴𝐴𝐴𝐴𝑜𝑜𝑜𝑜𝑜𝑜

After observed and adjusted reference prices are calculated for the commodity, they are subtracted from the domestic prices at each point in the value chain to obtain the observed and adjusted price gaps at wholesale and farm gate. Observed price gaps capture the effect of distortions from trade and market policies directly influencing the price of the commodity in domestic markets (e.g. price ceilings and tariffs), as well as overall market performance. Adjusted price gaps capture the same as the observed, in addition to the effect of any distortions from domestic exchange rate policies, structural inefficiencies in the commodity’s value chain, and imperfect functioning and non-competitive pricing in international markets. Mathematically, the equations for calculating the observed price gaps at wholesale (𝑅𝑅𝑃𝑃𝑜𝑜𝑜𝑜ℎ) and farm gate �𝑅𝑅𝑃𝑃𝑜𝑜𝑜𝑜𝑜𝑜� are as follows:

𝑅𝑅𝑃𝑃𝑜𝑜𝑜𝑜ℎ = 𝑅𝑅𝑜𝑜ℎ − 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜ℎ

𝑅𝑅𝑃𝑃𝑜𝑜𝑜𝑜𝑜𝑜 = 𝑅𝑅𝑜𝑜𝑜𝑜 − 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜

1 Structural inefficiencies in commodity value chains may include government taxes and fees (excluding fees for services), high transportation and processing costs, high profit margins captured by various marketing agents, bribes and other non-tariff barriers.

12

where 𝑅𝑅𝑜𝑜𝑜𝑜 is the domestic price at farm gate, 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜 is the observed reference price at farm gate, 𝑅𝑅𝑜𝑜ℎ is the domestic price at wholesale, and 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜ℎ is the observed reference price at wholesale.

A positive price gap, resulting when the domestic price exceeds the reference price, means that the policy environment and market functioning as a whole generate incentives (support) to producers or wholesalers. For an imported commodity this could be due to distortions such as the existence of an import tariff. On the other hand, if the reference price exceeds the domestic price, resulting in a negative price gap, this means that the policy environment and market functioning as a whole generate disincentives (taxes) to producers or wholesalers. For an imported commodity this could be due to distortions such as a price ceiling established by the government to keep domestic prices low.

In general, price gaps provide an absolute measure of the market price incentives (or disincentives) that producers and wholesalers face. Therefore, price gaps at wholesale and farm gate are divided by their corresponding reference price and expressed as a ratio, referred to as the Nominal Rate of Protection (NRP), which can be compared between years, commodities, and countries.

The Observed Nominal Rates of Protection at the farm gate (𝑁𝑁𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜) and wholesale (𝑁𝑁𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜ℎ) are defined by the following equations:

𝑁𝑁𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜 =𝑅𝑅𝑃𝑃𝑜𝑜𝑜𝑜𝑜𝑜𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜

; 𝑁𝑁𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜ℎ =𝑅𝑅𝑃𝑃𝑜𝑜𝑜𝑜ℎ𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜ℎ

where 𝑅𝑅𝑃𝑃𝑜𝑜𝑜𝑜𝑜𝑜 is the observed price gap at farm gate, 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜𝑜𝑜 is the observed reference price at the farm gate, 𝑅𝑅𝑃𝑃𝑜𝑜𝑜𝑜ℎis the observed price gap at wholesale and 𝑅𝑅𝑅𝑅𝑜𝑜𝑜𝑜ℎ is the observed reference price at wholesale.

Similarly, the Adjusted Nominal Rates of Protection at the farm gate (𝑁𝑁𝑅𝑅𝑅𝑅𝑎𝑎𝑜𝑜𝑜𝑜) and wholesale (𝑁𝑁𝑅𝑅𝑅𝑅𝑎𝑎𝑜𝑜ℎ) are defined by the following equations:

𝑁𝑁𝑅𝑅𝑅𝑅𝑎𝑎𝑜𝑜𝑜𝑜 =𝑅𝑅𝑃𝑃𝑎𝑎𝑜𝑜𝑜𝑜𝑅𝑅𝑅𝑅𝑎𝑎𝑜𝑜𝑜𝑜

; 𝑁𝑁𝑅𝑅𝑅𝑅𝑎𝑎𝑜𝑜ℎ =𝑅𝑅𝑃𝑃𝑎𝑎𝑜𝑜ℎ𝑅𝑅𝑅𝑅𝑎𝑎𝑜𝑜ℎ

where 𝑅𝑅𝑃𝑃𝑎𝑎𝑜𝑜𝑜𝑜 is the adjusted price gap at farm gate, 𝑅𝑅𝑅𝑅𝑎𝑎𝑜𝑜𝑜𝑜 is the adjusted reference price at the farm gate, 𝑅𝑅𝑃𝑃𝑎𝑎𝑜𝑜ℎis the adjusted price gap at wholesale and 𝑅𝑅𝑅𝑅𝑎𝑎𝑜𝑜ℎ is the adjusted reference price at wholesale.

If public expenditure allocated to the commodity is added to the price gap at farm gate when calculating the ratios, the Nominal Rate of Assistance (NRA) is generated. This indicator summarizes the incentives (or disincentives) due to policies, market performance and public expenditure.2 Mathematically, the Nominal Rate of Assistance is defined by the following equation:

𝑁𝑁𝑅𝑅𝐴𝐴 =𝑅𝑅𝑃𝑃𝑎𝑎𝑜𝑜𝑜𝑜 + 𝑅𝑅𝑃𝑃𝑐𝑐𝑐𝑐𝑐𝑐

𝑅𝑅𝑅𝑅𝑎𝑎𝑜𝑜𝑜𝑜

2 The NRA indicator was not calculated for any of the commodities analyzed because of insufficient data on public expenditure. However, it will be developed in the forthcoming reports, as the public expenditure analysis is improved and better data are made available.

13

where PEcsp is commodity-specific public expenditure that has been identified and measured as monetary units per tonne.

Finally, MAFAP methodology estimates the Market Development Gap (MDG), which is the portion of the price gap that can be attributed to “excessive” or inefficient access costs within a given value chain, exchange rate misalignments, and imperfect functioning of international markets. “Excessive” access costs may result from factors such as poor infrastructure, high processing costs due to obsolete technology, government taxes and fees (excluding fees for services), high profit margins captured by various marketing agents, bribes and other non-tariff barriers. Therefore, the total MDG at farm gate is comprised of three components – gaps due to “excessive” access costs, the exchange rate policy gap and the international market gap. When added together, these components are equivalent to the difference between the observed and adjusted price gaps at farm gate.

Similar to the price gaps calculated, the MDG is an absolute measure, which is also expressed as a ratio to allow for comparison between years, commodities, and countries. This relative indicator of the total MDG affecting farmers is derived by calculating the ratio between the total MDG at farm gate and the adjusted reference price at farm gate as follows:

𝑀𝑀𝑀𝑀𝑃𝑃𝑜𝑜𝑜𝑜 = (𝐴𝐴𝐴𝐴𝐴𝐴𝑤𝑤ℎ+𝐴𝐴𝐴𝐴𝐴𝐴𝑓𝑓𝑓𝑓+𝐸𝐸𝐸𝐸𝐸𝐸𝐴𝐴+𝐼𝐼𝐼𝐼𝐴𝐴)𝑅𝑅𝐸𝐸𝑎𝑎𝑓𝑓𝑓𝑓

where ACGwh is the access cost gap at wholesale defined as the difference between observed and adjusted access costs at wholesale, ACGfg is the access cost gap at farm gate defined as the difference between observed and adjusted access costs at the farm gate, ERPG is the exchange rate policy gap, and IMG is the international market gap.

A more detailed description of the methodology applied in this analysis is available on MAFAP’s website at www.fao.org/in-action/mafap.

14

DATA REQUIREMENTS, DESCRIPTION AND CALCULATION OF INDICATORS To calculate the indicators needed to estimate incentives or disincentives to production (NRP, NRA), as well as the Market Development Gaps (MDGs), several types of data are needed. They were collected and are presented and explained hereafter.

TRADE STATUS OF THE PRODUCTS Substantial volumes of wheat were imported throughout 2005-13. Kenya, therefore, has long been a net wheat importer with negative trade balance (Figure 6).

Figure 6. Wheat trade balance of Kenya (2005-2013)

Source: Index Mundi (2014) and KNBS, Statistical Abstract (2010) and (2014).

MARKET PATHWAYS ANALYZED Grain wheat is the form of the product analyzed. In Kenya, about 65 per cent of wheat is sold directly to millers with the remainder to NCPB, as it can be seen from Figure 5. Wheat is also imported by mills either directly or through NCPB. After processing into flour, wheat flour moves to bakeries and supermarket through the wholesale market in Nairobi and other cities.

As such, there is no wholesale market for wheat grain. The point of competition in this analysis is the mills which serve as the wholesale buyers of both imported and local wheat grain. Clearly in the wheat value chain, producers receive the difference between the wholesale buying prices paid by millers and the costs of transporting the grain from the farm to the mill. Thus, the price incentives/disincentives at the mills, consequently, mirror those at the farm gate. , The analysis of wheat incentives/disincentives is carried for the period of 2005-2013.

BENCHMARK PRICES The basis for calculating a reference price to determine whether wheat producers receive market incentives or disincentives is to establish a benchmark price, which represents the price for wheat

(1,200)

(1,000)

(800)

(600)

(400)

(200)

-2005 2006 2007 2008 2009 2010 2011 2012 2013

Trad

e Bl

ance

(000

' Ton

ne)

15

free of domestic policy and market distortions. Since Kenya was a net wheat importer during the 2005-13 period, the benchmark price considered is the CIF price for wheat.

The benchmark price is the average Mombasa CIF price for wheat imports from all countries. The CIF prices of wheat were obtained directly from the KNBS, Economic Review (2008), (2010) and (2013), reported in local currency (Table 2). The import price of wheat in Kenya soared in 2007-2008 and declined in 2009 to follow an increasing trend since June 2010, when it began to rise again. During the last three years, the CIF price of wheat in Kenya was as high as its 2008 level.

Table 2: CIF price of wheat of Kenya’s wheat imports (2005-2013) Year 2005 2006 2007 2008 2009 2010 2011 2012 2013

Border Price (USD/ton)

169.36 171.00 255.51 374.14 228.91 259.70 351.46 336.89 339.29

Source: KNBS, Economic Survey (2008), (2010) and (2014)..

Adjusted

The observed CIF prices accurately measure the opportunity cost of wheat imports to Kenya. Therefore, adjustment of the benchmark prices is unnecessary.

DOMESTIC PRICES Observed farm gate prices and the prices at point of competition

KNBS’s Economic Survey 2010 and 2013 published the farm gate prices of wheat paid at the mills for 2006 – 2013. These prices are consistent and very close to the wholesale prices in Nairobi and Nakuru report by RATIN (2014), where the major mills are located. While these represent the cost of purchase (buying price for millers), farmers pay the cost of delivering the product from the farm gate to the mill, i.e., access costs from the farm gate to the point of competition. These costs must be taken into account in determining the relevant net producer’s price. Therefore, the net producer’s price is the difference between the price paid at the mill (mill buying price) and the access costs. Table 3 compares the mill buying prices (the prices at the point of competition) and the estimated farmgate prices.

The soaring wheat prices observed in Kenya between September 2007 and May 2008 led the government to intervene in Kenyan wheat markets to protect vulnerable consumers. The government reduced the wheat import duty from 35 percent to 10 percent in June 2008 (Global Information and Early Warning System, 2008); other measures followed. The interventions by the Kenyan government likely explain the lack of connection between the world wheat price and the average wheat price in Nakuru between October 2008 and June 2010. The prices continued the upward trend in 2011- 2013.

Table 3: Observed wheat price at the point of competition (mills) and farm gate in Kenya (2006-2014)

Year/ market Wheat prices (KES/Tonne) 2005 2006 2007 2008 2009 2010 2011 2012 2013

Point of competition 18,211 19,496 28,589 31,832 29,368 29,138 30,174 36,223 37,449

Farmgate price 17,422 18,659 27,716 30,828 28,213 27,982 28,857 34,782 35,925

Source: KNBS, Economic Survey (2008), (2010) and (2014).

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EXCHANGE RATES Observed

Average nominal exchange rates between the Kenya Shilling and the US Dollar were used in this analysis to convert the benchmark price (USD per tonne) into local currency (KES per tonne). The average rate for each year under review was calculated from monthly data obtained from the International Monetary Fund (IMF) database on exchange rates. While the Kenyan Shilling appreciated between 2005 and 2008, it has depreciated since 2009 (Figure 7).

Figure 7: Exchange Rate KES/dollar (2005-2013)

Source: IMF (2014)

Adjusted

Kenya is adopting a liberal foreign exchange regime during the period of analysis where the exchange rate is determined freely with no direct intervention from the Central Bank. As such, the observed exchange rate appears to be an accurate measure of the real exchange rate and, therefore, no adjustments were made.

OBSERVED ACCESS COSTS Border to point of competition

Access costs for imported wheat are the sum of port charges and the cost to transport wheat from Mombasa to Nairobi. An estimate of observed access cost from Mombasa port to Nairobi including port charges transport to Nairobi, based on Gitau, et al. (2010) is given in Table 4. Wheat imports are subject to numerous fees and levies but most of them are small. The Cost Insurance and Freight (CIF) in July 2010 for wheat Ex US Gulf was USD 221 per ton and translated to USD 276 per ton after clearance at the port and transport to the store/warehouse in Mombasa. The price of imported wheat without duty landing in Nairobi is USD 290.62 per tonne.

0

10

20

30

40

50

60

70

80

90

100

2005 2006 2007 2008 2009 2010 2011 2012 2013

Exch

nage

Rat

e (K

ES/U

SD)

17

Table 4. Estimated cost of wheat importation in Kenya (2010)

Cost item USD/Tonne KES/Tonne Import documents fee (2.25 percent of CIF) 4.97 408.00 Port Charges (1 percent of CIF) 2.00 164.00

Levy (0.0275 percent of CIF) 0.06 5.00

Discharge (3.375 percent of CIF) 8.50 697.00 Terminal handling 7.50 615.00

Health inspection (0.06 percent of CIF) 0.13 10.50 SGS certificate (KEBS 0.475 percent) 1.05 86.00 Handling charges 1.35 111.00 Polyethyline plastic bags 4.34 356.00 Freight port to warehouse 2.74 225.00 Miscellaneous 0.24 20.00 GBHL loss (0.05 percent) 0.14 11.31 Transport cost to Nairobi 36.40 2,985.00 Total 69.48 5682.50

Note. The costs above refer to 2010. Source: Gitau, et al. (2010)

The costs in Table 4 were used to extrapolate the access costs from the border to the point of competition for years before and after 2010. First, the import documents fees, port charges, the port levy, the discharge fees, the storage losses and the levy charged by the Ministry of Health which were charged as a percentage of the CIF price were computed given the CIF price of wheat in each year and then converted into local currency using the observed exchange rate. Second, the remaining costs were deflated/inflated using the general Consumer Price Index (CPI) (with base year of 2010). This procedure is thought to result in more accurate estimates of the access costs since some of the charges are fixed percentages of the CIF price of imported rice. The resulting costs are categorized into major categories (e.g., transportation, handling and taxes) and presented in Table 5.

Table 5: Observed access Cost from the border to Point of Competition for wheat in Kenya (2005-2013)

Cost item 2005 2006 2007 2008 2009 2010 2011 2012 2013

KES/tonne

Transport 2,192 2,325 2,424 2,790 3,084 3,210 3,660 4,004 4,232 Handling 933 926 1,167 1,563 1,272 1,423 2,034 1,949 2,018 Taxes and fees 711 724 851 1,084 1,006 1,068 1,414 1,415 1,476 Others 82 80 106 146 82 117 82 82 82 Total Observed Access Costs

3,919 4,055 4,547 5,583 5,166 5,818 6,770 7,078 7,135

Source: Extrapolated from estimates presented in Table 3.

Farmgate to point of competition

Due to the simplicity of wheat value chain from the farm gate to the point of competition, the observed access costs from the farm to the point of competition are quite simple and include only local council CESS, storage, loading and unloading and transportation from the farm to the mill. Gitau et al. (2010) provided estimates of these costs. These costs are shown in Table 6 for 2010.

18

The costs provided by Gitau et al. (2010) were used to extrapolate the costs for the years before/after 2010 by deflating/inflating available data using the Consumer Price Index with 2010 as the base year. The resulting access costs series is presented in Table 6.

Table 6. Observed access costs between the farmgate and the point of competition for wheat in Kenya (2005-2013)

Cost item 2005 2006 2007 2008 2009 2010 2011 2012 2013

KES/tonne

Council cess 304 322 336 386 444 444 507 554 586

Storage 106 113 117 135 156 156 177 194 205

Loading/unloading 152 161 168 193 222 222 253 277 293

Transport charges 228 241 252 290 333 333 380 416 439

Total 789 837 873 1,004 1,156 1,156 1,318 1,441 1,524

Source: Aurthors’ imputation from Gitau et al. (2010) shown for 2010.

OBSERVED ACCESS COSTS Border to point of competition

Adjusted access costs from border to the point of competition were derived directly from the observed access costs for this market segment. This is done by eliminating import documents fee (2.25 percent of CIF), levy (0.0275 percent of CIF) and the terminal handling charges, which were treated as taxes on imports. These reduce the access costs from the border to the mill significantly. The estimated adjusted access cost for this segment is shown in Table 7.

Table 7. Adjusted access costs from the border to the point of competition for wheat in Kenya (2005-2013)

Cost item 2005 2006 2007 2008 2009 2010 2011 2012 2013

KES/tonne

Transport 2,192 2,325 2,424 2,790 3,084 3,210 3,660 4,004 4,232 Handling 933 926 1,167 1,563 1,272 1,423 2,034 1,949 2,018 Others 82 80 106 146 82 117 82 82 82 Total Observed Access Costs

3,209 3,333 3,696 4,498 4,474 4,751 5,795 6,093 6,404

Source: Authors’ extrapolation from estimates presented in Table 5.

Farmgate to point of competition

Similar to the adjusted access costs from the border to the point of competition, the adjusted access costs from the farm gate to the point of competition (mills) were derived directly from the observed access costs for this segment reported in Table 5. This is done by eliminating the local CESS which is the only tax levied on wheat. The resulting costs are presented in Table 8.

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Table 8. Adjusted access costs from the farmgate to the point of competition for wheat in Kenya (2005-2013)

Cost item 2005 2006 2007 2008 2009 2010 2011 2012 2013

KES/tonne

Storage 106 113 117 135 156 156 177 194 205

Loading/unloading 152 161 168 193 222 222 253 277 293

Transport charges 228 241 252 290 333 333 380 416 439

Total 789 837 873 1,004 1,867 1,156 1318 1441 1524

Source: Extrapolated from Table 5.

BUDGET AND OTHER TRANSFERS The PE database does not indicate any specific support to wheat and the attribution of expenditure allocated to group of commodities that may include wheat (specifically research) cannot be made. These estimates, when available, represent the direct and indirect budget transfer to wheat. Therefore, nominal rate of assistance cannot be estimated for unavailability of this data.

QUALITY AND QUANTITY ADJUSTMENTS This analysis focuses on trade and marketing of grain wheat which has the same quality of imported wheat. As such, adjustment for quantity and quality difference is unnecessary.

DATA OVERVIEW Following the discussions above, the table 9 summarizes the main data sources used and methodological decisions taken for the analysis. The data used in estimation of the price incentives indicators are summarized in Table 10.

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Table 9: Data sources and methodological decisions

Description Concept Observed Adjusted

Benchmark price Average unit cost of imported wheat (CIF) at Mombasa port obtained from KNBS, Economic Review (2008), (2010) and (2013). See Table 2.

Not Applicable (N.A.)

Domestic price at point of competition

Price paid by millers to wheat producers for wheat delivered to the mill as reported KNBS, Economic Review (2008), (2010) and (2013). See Table 3

N.A.

Domestic price at farm gate Price paid by millers to wheat producers for wheat delivered to the mill as reported KNBS, Economic Review (2008), (2010) and (2013)adjusted for the costs to the mills. See Table 3

N.A.

Exchange rate Average market (observed) exchange rate reported by IMF (2014). See Figure 9

N.A.

Access cost from the point of competition to the border

Extrapolated based on costs reported by Gitau et al. (2010). These include cost of handling at the port, fees and levies, storage and transport. See Table 5

Extrapolated from the observed access costs by eliminating the taxes and levies. See Table 7

Access costs from the point of competition to farm gate

Extrapolated from the data in Gitau et al. (2010) including local CESS, loading and unloading, storage and transport to the mill. See Table 6

Extrapolated from the observed access costs by eliminating the local tax. See Table 8.

QT adjustment

Bor-PoC N.A. N.A. PoC -FG N.A. N.A.

QL adjustment

Bor- PoC N.A. N.A. PoC -FG N.A. N.A.

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Table 10: Data Used in the Analysis

Year 2005 2006 2007 2008 2009 2010 2011 2012 2013DATA Unit Symbolrade status m m m m m m m m m

Benchmark PriceObservedUSD/TONNE Pb(int$) 169 170 252 349 222 251 351 337 339 AdjustedUSD/TONNE Pba

Exchange RateObserved KES/USD ERo 76 72 67 69 77 79 89 85 86

Adjusted KES/USD ERa Access costs border - point of competition

ObservedKES/TONNE ACowh 3,919 4,055 4,547 5,583 3,919 5,818 3,919 3,919 3,919

AdjustedKES/TONNE ACawh 3,208 3,331 3,696 4,500 3,208 4,750 3,208 3,208 3,208

Domestic price at point of competition KES/TONNE Pdwh 18,211 19,496 28,589 31,832 29,368 29,138 30,174 36,223 37,449 Access costs point of competition - farm gate

ObservedKES/TONNE ACof g 789 837 873 1,004 1,156 1,156 1,318 1,441 1,524 AdjustedKES/TONNE ACaf g 486 515 537 618 711 711 811 887 938

Farm gate price KES/TONNE Pdf g 17,422 18,659 27,716 30,828 28,213 27,982 28,857 34,782 35,925 Externalities associated with production KES/TONNE E - - - - - - - - - Budget and other product related transfers KES/TONNE BOT - - - - - - - - - Quantity conversion factor (border - point of competition) Fraction QTwh Quality conversion factor (border - point of competition) Fraction QLwh Quantity conversion factor (point of competition - farm gate) Fraction QTf g Quality conversion factor (point of competition - farm gate) Fraction QLf g

Notes

CIF

KNBS, Economic Survey (2008, 2010 and 2014)

KNBS, Economic Survey (2008, 2010 and 2014)

From PE Analysis

22

SUMMARY OF INDICATORS Table 11. Observed and adjusted MAFAP Price Gaps for wheat in Kenya (KES/tonne), 2005-2013

2005 2006 2007 2008 2009 2010 2011 2012 2013

Trade status m m m m m m m m Observed price gap at point of competition

1496.0 3105.8 6823.5 232.9 7742.3 2694.7 -5024.8 3837.1 4306.5

Adjusted price gap at point of competition

2207.5 3832.0 7679.7 1356.9 8453.8 3778.4 -4313.3 4548.6 5018.0

Observed price gap at farm gate

1496.0 3105.8 6823.5 232.9 7742.3 2694.7 -5024.8 3837.1 4306.5

Adjusted price gap at farm gate

1903.9 3510.1 7344.1 970.6 8009.3 3333.9 -4820.1 3994.3 4432.0

Source: Authors’ own calculations using data as described above.

Table 12: MAFAP Observed and Adjusted Nominal Rates of Protection (Percent) for wheat in Kenya, 2005-2013

2005 2006 2007 2008 2009 2010 2011 2012 2013

Trade status m m m m m m m m m

Observed NRP at point of competition

9.0% 18.9% 31.4% 0.7% 35.8% 10.2% -14.3% 11.8% 13.0%

Adjusted NRP at point of competition

13.8% 24.5% 36.7% 4.5% 40.4% 14.9% -12.5% 14.4% 15.5%

Observed NRP at farm gate

9.4% 20.0% 32.7% 0.8% 37.8% 10.7% -14.8% 12.4% 13.6%

Adjusted NRP at farm gate

12.3% 23.2% 36.0% 3.3% 39.6% 13.5% -14.3% 13.0% 14.1%

Observed NRA at farm gate

9.4% 20.0% 32.7% 0.8% 37.8% 10.7% -14.8% 12.4% 13.6%

Adjusted NRA at farm gate

12.3% 23.2% 36.0% 3.3% 39.6% 13.5% -14.3% 13.0% 14.1%

Source: Authors’ own calculations using data as described above.

Table 13: MAFAP Market Development Gaps for wheat in Kenya, 2005-2013 2005 2006 2007 2008 2009 2010 2011 2012 2013

Trade status m m m m m m m m m Access costs gap to competition point (ACGwh)

711.4 726.2 856.1 1,124.0 711.4 1,083.6 711.4 711.4 711.4

Access costs gap to farm gate (ACGfg)

(303.5) (321.9) (335.6) (386.3) (444.4) (444.4) (506.8) (554.3) (586.0)

Total gap (KES/Tonne) 407.91 404.30 520.52 737.68 267.00 639.20 204.68 157.13 125.46 Total Gap ( percent of reference price)

2.63% 2.67% 2.56% 2.47% 1.32% 2.59% 0.61% 0.51% 0.40%

Source: Authors’ own calculations using data as described above.

23

4. RESULTS AND INTERPRETATION The estimated observed and adjusted price gaps and the associated nominal rates of protection at the point of competition (mills) and at the farm level are presented in Tables 11-12 and Figures 8-9. Due to absence of intermediaries between the farm gate and the mills, the observed price gaps at the point of competition (mills) mirror the indicators at the farm gate very closely3. However, the adjusted indicators differ slightly due to the local taxes levied at the producer level (Figure 8, 9).

The price gaps at both millers’ and producers’ levels are positive throughout the period of analysis except in 2011 when it has shown a sharp negative spiral. The observed price gap were as high as KES 7 732 per tonne as in 2009 and was as low as KES 234 per tonne as in 2008. In 2011, the observed price gap plummeted to a negative level of over KES 5,000 per tonne at the farmgate and mills. Despite an increase in world market price of about 40 percent, domestic prices of wheat in Kenya in this year were stagnant. Besides, the tariff on wheat was abolished in June 2011 and massive quantities of wheat of almost a million tonnes were imported. In this year, domestic prices of wheat were significantly below the reference price due to the lower tariff and increased supply.

The nominal rate of protection follows the same trends of the price gap. With the exception of 2011, the observed NRP at the point of competition was positive and ranging from less than 1.0 percent to 35.8 percent. The observed NRP at the farm gate is slightly higher ranging from 0.8 percent (2008) to 37.8 percent (Table 12; Figure 9). In 2011, the observed nominal rate of protection at the point of competition was -14.3 percent compared to -14.8 percent at the farm gate (almost equal).

Figure 8: Observed and adjusted Price gaps at the farm gate and the point of competition for wheat in Kenya (2005-2013)

Source: Authors’ own calculations using data as described above.

3 As explained earlier, the price at the point of competition (milling) is the price paid to farmers for wheat delivered at the mill. Therefore, the net producer price is the price at the point of competition less the cost of delivering wheat at the mill. In the wheat value chain, there are no intermediaries to alter the producer price.

-6,000

-4,000

-2,000

0

2,000

4,000

6,000

8,000

10,000

2005 2006 2007 2008 2009 2010 2011 2012 2013Pric

e G

ap (K

ES/t

onne

)

Observed price gap at point of competition Adjusted price gap at point of competition

Observed price gap at farm gate Adjusted price gap at farm gate

25

The adjusted nominal rate of protection at both levels is generally higher than the observed NRP while the adjusted NRP at the farm gate is slightly higher than that at the point of competition (Table 10) due to local tax levied at the farm gate. With the exception of 2011, where the indicator is negative, the adjusted NRP ranges from 4.5 to 40.4 percent. In contrast, the adjusted the NRP at the farm gate ranges from 3.3 to 39.6 percent in the same years. The negative NRP in 2011 is partly due to the elimination of the tariff on wheat.

The incentives/disincentives for wheat producers and millers in Kenya are quite variable over time and largely driven by the changing policy for wheat imports over time. The import duty on wheat has seen the most frequent adjustments since the inception of the EAC common external tariff (CET). The CET on grain wheat was set at 35 per cent of CIF price at the port of entry in the region. However, applied tariff on wheat has tended to be lower than the 35 per cent for most of the years in most EAC members (Vitale, et. al. 2013). This is partly due to the spikes in the world wheat prices but also for reasons related to imbalances in cereal demand-supply in the region. The decision by Kenya to lower wheat import duty to 10 percent from the applied rate of 25 percent, announced in the Budget Speech of June 2010, provoked a fierce reaction among stakeholders. The government decision was a response to the soaring price in the world market. Farmers and millers reacted differently. The price trend led the Kenyan wheat farmers, mostly large producers, to ration their deliveries to mills in anticipation of higher prices. On the other hand, importers were not willing to empty their cargos at the port in order to avoid the 35 percent duty, which they expected to be reduced. (Vitale et al., 2013). The tariff on wheat was eliminated since June 2011.

Figure 9: Observed and adjusted Nominal Rates of Protection (NRPs) at farm gate and at the point of competition for wheat in Kenya (2006-2013)

Source: Authors’ own calculations using data as described above.

-20%

-10%

0%

10%

20%

30%

40%

50%

2005 2006 2007 2008 2009 2010 2011 2012 2013Nom

inal

rate

of p

rote

ctio

n (%

)

Observed nominal rate of protection at point of competitionAdjusted nominal rate of protection at point of competitionObserved nominal rate of protection at farm gateAdjusted nominal rate of protection at farm gate

26

The estimated indicators for wheat appear to follow the above adjustment of the tariff in Kenya. As shown in Figure 8, the adjusted nominal rate of protection at both the farm gate and the point of competition declined from close to 40 percent in 2007 to around 10 percent when the tariff rate was reduced to 10 percent. The same indicators soared to over 40 percent after a tariff of 25 percent was imposed on wheat imports in June 2009 to decline again in the following year to the level of 17-18 percent. The nominal rate of protection became negative in 2011 when the tariff was abolished on wheat but domestic prices seems to adjust slightly above the world prices since 2012 by 13-15 percent. Gitau et al. (2010) find that with import duties rate of 10 percent for wheat, both efficient and average producers remain competitive, but if tariffs are eliminated, only the efficient producers stay competitive, with average wheat producers barely remaining competitive.

Wheat is predominantly a cash crop and large scale farmers tend to provide most of the marketed output in Kenya, which still remains relatively uncompetitive without adequate tariff protection (Gitau, Mathenge and Mburu, 2010). The debate over tariffs on wheat products is mainly driven by farmers’ and millers’ concerns, with respective views largely diverging (Vitale et al., 2013). Farmers typically strongly oppose tariff cuts on wheat grains; but accepted cuts when prices soared in the world market during 2010/11. Millers have usually advocated for lower tariffs on grains for two reasons – large deficits and quality concerns for processing local wheat4. They were also concerned with duty-free imports of flour from COMESA area (e.g. Egypt, Mauritius). According to the view of the Kenyan Association of Manufacturers (KAM), cited by Vitale et al. (2013), as a result of the disparities in the duty structures between the EA countries, there have been increasingly large quantities of flour and its by-products being imported into Kenya from neighboring countries resulting in disinvestments in the wheat milling Industry in Kenya. This led to the loss of major export markets such as Rwanda, Burundi and Eastern Democratic Republic of Congo, which have traditionally been the major destinations for Kenya’s wheat flour exports. The aforementioned conflict in trade policy arrangements within EAC and COMESA, have negatively affected Kenyan Millers (Vitale, et al., 2013).

According to Vitale et al. (2013), two prominent issues are related to wheat policies in Kenya and East Africa in general:

• Setting appropriate Common External Tariff (CET) rates for staple food products continues to be a relevant policy issue to be addressed, in view of the lack of consensus on the distribution of gains and losses across the member countries and among various stakeholders. There is also the issue of the impacts over time and in periods of high and low world market prices.

• A more contentious issue is the way in which trade policy formulation is managed at the national levels, and how effectively the CET is implemented across the region.

Figure 10 and Table 13 present summary of Market Development Gaps. Market development gap at both the farm gate and point of competition are relatively small, less than 2.7 percent of the reference price at the farmgate. The gap at the farm gate is the result of the local taxes on wheat producers that tend to lower producer prices (negative impact on producers prices). On the other

4 The validity of these concerns cannot be ascertained. However, the large deficit requires substantial capital outlays from the mills while the high tariff adds an additional burden and cost.

27

hand, the numerous fees and levies paid at the port of entry tend to raise the cost of imports and represent an additional protection to wheat producers (positive impact). The net effect is a higher price at the farm gate. However, the market development gap appears to be small and declining since 2010. This is primarily because the wheat value chain in Kenya is quite simple with minimum number of intermediaries. For instance, mills buy wheat directly from farmers and import directly from abroad. This tends to reduce the access costs and leads to relatively efficient transactions along the value chain.

Figure 10: Market Development Gaps (MDGs)

5. CONCLUSIONS AND RECOMMENDATIONS

MAIN MESSAGE For over 50 years, Kenya has long provided protection to wheat farmers even though many of them are large-scale commercial farms. Overall, the number of large-scale farmers involved in wheat production is relatively small, while the number of small-scale farmers continues to grow.

Government support to wheat farmers could perhaps have been justified at one time because most of the wheat was consumed by relatively rich Kenyans and the hotel and restaurant industries serving the needs of relatively wealthy Kenyans. However, in the recent rebasing of the consumer price index, the income share spent on wheat and wheat products by low income Kenyans in Nairobi is 10.68 percent of their total expenditure on food, compared to 11.46 percent for maize. Even in other urban areas, Kenyans are spending nearly as large a share of their food budget on wheat and wheat products as they do on maize and maize products – 9.69 percent versus 13.48 percent. A tariff on wheat is a tariff on poor consumers and, as MAFAP analysis has shown, it affects prices.

Kenya’s policy of explicit protection seems to be coming to an end with the reduction in the tariff to 10 percent in 2010 and the further reduction to zero announced in the July 2011 budget. However, farm gate prices in recent years have been even higher than justified by the tariffs in effect. Other policy measures that have produced this result could also be reformed so that Kenyan wheat farmers’ prices in the future are based upon the full opportunity costs to the Kenyan economy.

-2.00%

-1.50%

-1.00%

-0.50%

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

(800)

(600)

(400)

(200)

-

200

400

600

800

1,000

1,200

2005 2006 2007 2008 2009 2010 2011 2012 2013

MDG

( pe

rcen

t of r

efer

ence

pric

e at

farm

gat

e)

Mar

ket d

evel

opm

ent g

ap (K

ES/t

onne

)

Access costs gap to point of competition Access costs gap to farm gate

Market Development Gap MDG as % of Reference Price at Farm Gate

28

RECOMMENDATIONS Import duties are short-term policy instruments. Use of tariff to protect farmers penalizes consumers while artificially maintaining the competiveness of a group of producers. Besdes, it leads to distortion of resource allocation and limits the competitiveness of Kenyan wheat products such as flour in the regional markets. This policy instruments may not be available in the near feature as Kenya is a member of several trade blocs. The trend in most of the trade blocs is to move towards a free movement of goods within member states. The government needs to address the inefficiencies along the value chain for the locally produced wheat to be competitive. The following measures are recommended:

• Maintain the low tariff on wheat imports announced in 2011. Inability of wheat farmers to be competitive is strong signal for the need to technological change to improve productivity and, hence, lower unit cost of production. This will benefit consumers and encourage export of processed wheat products. While supplying of the domestic market should apparently be the first priority, Kenya may need to align its tariff policy with its neighbors to avoid disparities in the regional market for wheat products.

• The following are options that can be taken to improve farmer’s competitiveness through higher productivity:

• Development of wheat varieties suitable for different agro ecological zones of Kenya and also resistant to Wheat Stem Rust: Breeding wheat varieties suitable for different agro ecological zones and mega environments would be very challenging for many nations in Sub-Saharan Africa, given the scarcity of funds for agricultural research. Wheat Stem Rust (UG 99) has been causing havoc in Kenya.

• Provision of effective farmer advisory services: Updated farmer advisory services are needed to better serve the needs of wheat farmers and, in particular, to introduce wheat as a new crop to smallholder farmers.

• Improved postharvest management practices: There is a need for strong postharvest management support to reduce quantity and quality losses in wheat value chains. Postharvest management practices have major impacts on the quality of wheat grain for processing and various end uses. Developing or improving storage, handling and processing activities, while taking end-market specifications and quality into account, is critical. These measures help improving the quality of wheat produced and increased profitability of wheat production.

• Create conducive enabling environment: Domestic wheat production could be made more competitive by improving marketing efficiency and lowering transaction costs. In addition, by designing policies, institutions and infrastructure to reduce the cost of acquiring inputs, marketing wheat, and procuring wheat from international markets, the situation of farmers is likely to improve in particular when domestic demand exceeds production.

LIMITATIONS All conclusions provided are contingent on the quality of the data. Price data for 2005 is unavailable limiting the analysis to 2006-2013. The access costs estimated are based on a single year data (2010). Marketing costs need to be updated. However, despite these limitations, the results are consistent with the economic realities of wheat markets in Kenya.

Though wheat is receiving public support in terms of expenditure for research and other services, the specific public expenditure in support of wheat in Kenya cannot be determined due to

29

attribution problem. This limit the analysis only to the price gap and the nominal rate of protection as the nominal rate of assistance cannot be estimated. However, since the nominal rate of protection is positive for almost all years, it follows that the nominal rate of assistance for wheat in Kenya is at least as high as the nominal rate of protection.

FURTHER INVESTIGATION AND RESEARCH Due to the growing demand for wheat in Kenya, it would also be useful to carry the analysis forward by examining the effect on consumers and comparing these results with those for other staple foods in Kenya and other countries in the region. There is also a need to carry out an in-depth study on wheat value chains and detailed study on access costs.

In addition, it will be useful to extend this analysis to compute effective rates of protection to further investigate the combined effect for farmers and consumers of policies on input and output markets.

30

BIBLIOGRAPHY Chemonics International Inc. (2010) “Staple Foods Value Chain Analysis Country Report – Kenya,”

January 2010.

FAO Wheat Database. (2014). “Kenya production potential,” Source: http://www.fao.org/ag/AGP/AGPC/doc/ field/Wheat/africa/Kenya/kenyaagec.htm July. 23, 2014

Gitau, R., Mathenge, M., & Mburu, S. (2010). Trade and Agricultural Competitiveness for Growth, Food Security and Poverty Reduction: A Case of Wheat and Rice Production in Kenya. Draft Report. Nairobi, Kenya: Tegemeo Institute- Egerton University.

Grain Bulk Handlers Ltd. (2008). “Grain Bulk Handlers Profile,” Grain Bulk Handlers Ltd. Nairobi, Kenya.

Grain Bulk Handlers Ltd. (2011). “GBHL Tariff Sheet effective 1st January 2011,” December 2011. Grain Bulk Handlers Ltd. Nairobi, Kenya.

Kenya National Bureau of Statistics. (2008). Economic Survey 2008. Government of Kenya. Kenya National Bureau of Statistics (KNBS), Nairobi.

Kenya National Bureau of Statistics. (2010). Economic Survey 2010. Government of Kenya. Kenya National Bureau of Statistics (KNBS), Nairobi.

Kenya National Bureau of Statistics. (2014). Economic Survey 2014. Government of Kenya. Kenya National Bureau of Statistics (KNBS), Nairobi.

Laibuni N, Njenga M., Kiriga B., Omiti J, and M. Ikiara. (2012). IS THERE NEED FOR AN EAST AFRICAN COMMODITY EXCHANGE? Nairobi: Kenya Institute for Public Policy Research and Analysis (KIPPRA).

Longmire, J. and Juma Lugogo. (1989). “The Economics of Small-Scale Wheat Production Technologies for Kenya,” CIMMYT Economics Working Paper 89/01.

Makanda, D. and James F, Oehmke. Undated. “Promise and Problem in the Development of, Kenya's Wheat Agriculture,” mimeo, Department of Agricultural Economics, Michigan State University, East Lansing.

Ministry of Agriculture. (2009). Economic Review of Agriculture 2009-14. Kenya. Government of Kenya, Ministry of Agriculture, Nairobi.

Ministry of Agriculture. (2010). Economic Review of Agriculture 2009-14. Kenya. Government of Kenya, Ministry of Agriculture, Nairobi.

Ministry of Agriculture. (2011). Economic Review of Agriculture 2009-14. Kenya. Government of Kenya, Ministry of Agriculture, Nairobi.

Ministry of Agriculture. (2012). Economic Review of Agriculture 2009-14. Kenya. Government of Kenya, Ministry of Agriculture, Nairobi.

Ministry of Agriculture. (2014). Economic Review of Agriculture 2009-14. Kenya. Government of Kenya, Ministry of Agriculture, Nairobi.

Musyoka, Philip M. (2009) “Wheat Import Demand and Welfare Effects of Import Controls in Kenya,” KIPPRA Discussion Paper No. 100, 2009

Muyanga, M., T.S. Jayne, G. Argwings-Kodhek and Joshua Ariga. (2005). Staple Food Consumption Patterns in Urban Kenya: Trends and Policy Implications. Tegemeo Working Paper No. 19. Nairobi: Egerton University, Tegemeo Institute of Agricultural Policy and Development.

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Nyangito, H., Ikiara, M.M. and Ronge, E.E. (2002). Performance of Kenya’s Wheat Industry and Prospects forRegional Trade in Wheat Products. Discussion Paper No 17. Nairobi: Kenya Institute for Public Policy Research and Analysis (KIPPRA).

Nyoro, J.K. Ayieko, M. and Muyanga, M. (2007). The Compatibility of Trade Policy with Domestic Policy Interventions Affecting the Grains Sector in Kenya. Paper presented at the FAO Workshop on Trade and Policy for Food Products Conducive to Development in Eastern Africa, 1-2 March 2007. Rome, Italy. Web. Accessed in February 2009.

PKF Consulting Ltd. (2005). “Grain Production in Kenya,”, the Export Processing Zones Authority, 2005.

Vitale, A., Morrison, J. and R. Sharma. (2013). The East African Community Common External Tariff on Cereals: An Analysis of Stakeholder Perception. Research Working Paper No. 36. FAO Commodity and Trade Policy. Rome, Italy.

32

ANNEX I: Data and calculations used in the analysis

Year 2005 2006 2007 2008 2009 2010 2011 2012 2013DATA Unit Symbolrade status m m m m m m m m m

Benchmark PriceObservedUSD/TONNE Pb(int$) 169 170 252 349 222 251 351 337 339 AdjustedUSD/TONNE Pba

Exchange RateObserved KES/USD ERo 76 72 67 69 77 79 89 85 86

Adjusted KES/USD ERa Access costs border - point of competition

ObservedKES/TONNE ACowh 3,919 4,055 4,547 5,583 3,919 5,818 3,919 3,919 3,919

AdjustedKES/TONNE ACawh 3,208 3,331 3,696 4,500 3,208 4,750 3,208 3,208 3,208

Domestic price at point of competition KES/TONNE Pdwh 18,211 19,496 28,589 31,832 29,368 29,138 30,174 36,223 37,449 Access costs point of competition - farm gate

ObservedKES/TONNE ACof g 789 837 873 1,004 1,156 1,156 1,318 1,441 1,524 AdjustedKES/TONNE ACaf g 486 515 537 618 711 711 811 887 938

Farm gate price KES/TONNE Pdf g 17,422 18,659 27,716 30,828 28,213 27,982 28,857 34,782 35,925 Externalities associated with production KES/TONNE E - - - - - - - - - Budget and other product related transfers KES/TONNE BOT - - - - - - - - - Quantity conversion factor (border - point of competition) Fraction QTwh Quality conversion factor (border - point of competition) Fraction QLwh Quantity conversion factor (point of competition - farm gate) Fraction QTf g Quality conversion factor (point of competition - farm gate) Fraction QLf g

CALCULATED PRICES Unit Symbol 2005 2006 2007 2008 2009 2010 2011 2012 2013Benchmark price in local currency

ObservedKES/TONNE Pb(loc$) 12,796 12,249 16,957 24,112 17,160 19,889 31,280 28,467 29,223 AdjustedKES/TONNE Pb(loc$)a 12,796 12,249 16,957 24,112 17,160 19,889 31,280 28,467 29,223

Reference Price at point of competitionObservedKES/TONNE RPowh 16,715 16,305 21,505 29,695 21,079 25,706 35,199 32,386 33,142 AdjustedKES/TONNE RPawh 16,004 15,580 20,654 28,612 20,367 24,638 34,488 31,675 32,431

Reference Price at Farm Gate ObservedKES/TONNE RPof g 15,926 15,468 20,632 28,691 19,923 24,551 33,881 30,945 31,618 AdjustedKES/TONNE RPaf g 15,518 15,065 20,117 27,993 19,656 23,927 33,677 30,788 31,493

INDICATORS Unit Symbol 2005 2006 2007 2008 2009 2010 2011 2012 2013Price gap at point of competition

ObservedKES/TONNE PGowh 1,496 3,191 7,084 2,137 8,290 3,431 (5,025) 3,837 4,307 AdjustedKES/TONNE PGawh 2,207 3,916 7,935 3,220 9,001 4,499 (4,313) 4,549 5,018

Price gap at farm gateObservedKES/TONNE PGof g 1,496 3,191 7,084 2,137 8,290 3,431 (5,025) 3,837 4,307 AdjustedKES/TONNE PGaf g 1,904 3,594 7,599 2,834 8,557 4,055 (4,820) 3,994 4,432

Nominal rate of protection at point of competitionObserved % NRPowh 8.95% 19.57% 32.94% 7.20% 39.33% 13.35% -14.28% 11.85% 12.99%Adjusted % NRPawh 13.79% 25.13% 38.42% 11.26% 44.19% 18.26% -12.51% 14.36% 15.47%

Nominal rate of protection at farm gateObserved % NRPof g 9.39% 20.63% 34.34% 7.45% 41.61% 13.98% -14.83% 12.40% 13.62%Adjusted % NRPaf g 12.27% 23.86% 37.78% 10.12% 43.53% 16.95% -14.31% 12.97% 14.07%

Nominal rate of assistanceObserved % NRAo 9.39% 20.63% 34.34% 7.45% 41.61% 13.98% -14.83% 12.40% 13.62%Adjusted % NRAa 12.27% 23.86% 37.78% 10.12% 43.53% 16.95% -14.31% 12.97% 14.07%

Decomposition of PWAfg Unit Symbol 2005 2006 2007 2008 2009 2010 2011 2012 2013International markets gap KES/TONNE IRG - - - - - - - - - Exchange policy gap KES/TONNE ERPG - - - - - - - - - Access costs gap to point of competition KES/TONNE ACGwh 711.44 724.34 850.61 ###### 711.44 ###### 711.44 711.44 711.44 [3]-[3b] Access costs gap to farm gate KES/TONNE ACGf g (303.53) (321.85) (335.61) (386.31) (444.44) (444.44) (506.77) (554.32) (585.98) [5b]-[5]Externality gap KES/TONNE EG - - - - - - - - - -[7]Market Development Gap KES/TONNE MDG 407.91 402.49 515.00 697.39 267.00 623.52 204.68 157.13 125.46 [25]+[26]+[27]+[28]+[29]Market Development Gap % MDG 2.63% 2.67% 2.56% 2.49% 1.36% 2.61% 0.61% 0.51% 0.40% MDG/RPafg

Notes

CIF

KNBS, Economic Survey (2008, 2010 and 2014)

KNBS, Economic Survey (2008, 2010 and 2014)

From PE Analysis

Formula

[1]*[2][1]*[2]

[9]+[3][10]+[3b]

[11]-[5][12]-[5b]

Formula

[4]-[11][4]-[12]

[6]-[13][6]-[14]

([17]+[8])/[13]([18]+[8])/[14]

Formula

[15]/[11][16]/[12]

[17]/[13][18]/[14]

33

I4534E/1/04.15