GLOBAL FOOD CRISIS AND OUTPUT SUPPLY RESPONSE: Implications for Food Security in Nigeria. M.A. BADMUS (Mrs) NIHORT IBADAN

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1 GLOBAL FOOD CRISIS AND OUTPUT SUPPLY RESPONSE: Implications for Food Security in Nigeria M.A. BADMUS (Mrs) NIHORT IBADAN AND FEMI OGUNDELE NISER IBADAN Abstract The food price shock now roiling world market is destabilizing governments, igniting street riots and threatening to send a new wave of hunger rippling through the world s poorest nations. One major factor accounting for food insecurity is the variability in food production from year to year which often affects mainly the physical availability of food. The current food price inflation in Nigeria cannot be completely isolated from the trend in food supply in the country. This study, thus, adopted a supply response function to examine the impact of the current food price inflation in Nigeria on output supply response in the country. The underlying data for the study was drawn from the household survey conducted by Nigerian Institute of Social and Economic Research (NISER)in 2008 to assess the impact of the global food crisis in Nigeria. The survey was conducted in one state in each of the six geopolitical zones of the country and covered the major staple foods in the country. The output and prices data obtained were fitted into the supply response equation and a regression analysis was carried out using SPSS statistical package. The results are quite revealing with the attendant implication for food security in Nigeria. Price analysis revealed that increase in farm gate price in 2008 was marginal mostly for grains and declined particularly for rice and millet. Consequently, increase in quantity of grains offer for sale by farmers in 2008 was less than 40%. Enterprise profitability as measured by Gross Margin declined for millet and cowpea and recorded only marginal increase for rice and maize in The results of the estimated supply response functions presented four distinct policy variables. These are prices, area cultivated to crops, rainfall pattern and fertilizer use. These variables were found to significantly influence the quantity of food crop output supplied in Their influences were, however, particularly significant for rice.

2 INTRODUCTION Over the years, in Nigeria, there have been occasional food supply shortfalls and high food prices in all or some parts of the country. This was often due to seasonal and cyclical food supply fluctuations, drought and /or poor rainfall in parts of the country. Market imperfections also creates local food supply shortfalls in some parts of the country while there are surpluses in some other parts (NAEE, 2008). However, the current food crisis seems to be different as it cuts across many developing countries. The price of nearly every agricultural commodity increased sharply between 2007 and food prices rose 55 percent form June 2007 to February 2008.Corn prices began their rise in the third quarter of 2006 and soared by some 70 percent within two years wheat and soybean prices also skyrocketed during this time. The cooking oils (mainly form soybean and palm oil)- an essential foodstuff in many poor countries rocketed up as well. Rice prices also more than doubled in the years (TWN, 2009). The price of nearly every agricultural commodity increased sharply by 55 percent between 2007 and (UNDP, 2008). World prices of wheat and maize were three times higher than at the beginning of 2003, while rice was five times higher (ITRD, 2009). African continent with a population of 900 million people now has 315 million living in less than 81 a day (UNDP, 2008). This rapid and simultaneous rise in World prices of all basis food crops is having a devastating effect on poor people all over the world. Almost everybody s standard of living has been reduced; the middle class are spending more on food purchases, the near poor drop into poverty and the poor suffer even more (TWN, 2009). Explanations for these crises in food ranges from global warming through to international trade policies, the emergence of bio-fuels, increasing urbanization and population growth. Also included are poor post-harvest supply management in many developing countries, sharp increase in World-wide demand for food to feed refuges and other displaced people in crisis-ridden countries and drought or poor rainfall in some countries. For example in Nigeria, food production was said to have declined by about 25 percent in 2007 due to drought in the Northern part of the country. (NAEC; Economic & Policy Series, 2008). The level of dependence of a country for a particular food item is a measure of the vitality of the food system and the vulnerability of the people to changes in production of the exporting countries and other external factors such world prices. The current food crisis in Nigeria cannot be completely isolated from the trend in supply in the country. The gap between supply and demand for a particular food item is a measure of the level of food in security with respect to such commodities. One major factor accounting for food insecurity is the variability in food production from year to year which often affects mainly the physical availability of food. In attempt to stem the gap between food supply and demand in Nigeria, the Federal Government designed and implemented a plethora of reform initiatives. The responsiveness of farmers to these economic incentives/policies determines agriculture s contribution to the economy. This study therefore examined the impact of food price increases on output supply response and accesses the implications for food securities.

3 MATERIALS AND METHODS Conceptual Framework The framework for monitoring the effects of food price increases on food supply can be found in the pioneering work of Olayide and Heady (1982) who advanced the concepts of farm supply function, supply response and of course, the extended crop response function. The concept of farm supply function describes how the quantity and price of a product that is offered for sale, at any given point in time, varies relative to other products prices for a given state of arts or technology. This can be stated functionally in implicit form as: Q = f(po, Pi, T) (1) Where Q is the quantity of the given product supplied, Po is the price of the given product, Pi (for i= 1, 2,, n) is the price of the ith product component of other competing products, and T is the given state of the arts or technology. Implicit in this idea of supply relation are the notions that (a) one or more productive resources may be varied in the production process involved, and (b) the factors are substitutable among the various and competing farm enterprises. This concept is, however, very rigorous and its usefulness lies in the meaningful way in which it facilitates an explanation of market price formation processes in economic analysis. The concept of supply response on the other hands specifies how quantity of any farm commodity that is offered for sale varies with changes in the price of the commodity itself. This concept is more general in structure since it is inclusive of the former concept of a net supply relation. It is basically concerned with output response to a price change, irrespective of by whatever means that response takes place. It is known from theory and practice that such a response may be due to one or combination of the followings. employment of more or less resources, depending upon whether there was a price rise or decrease; modification of scale or farm size; technological advancement under the production influences that obtain with respect to liquidity position, access to credit, market information, price certainty and so on. These conditions help us to describe supply response as what will happen to the quantity of a farm commodity that is offered for sale when we do not hold other things constant. This concept finds the greatest use in a prediction of the change in the quantity that is associated with some particular change in price. The functional form of supply response can be stated as: Q = f(po, Pc, At, Wt, T, Ct, V) (2) Where Q is the quantity of the given farm commodity, Po is the product price, Pc is the average price of competing products, At is the acreage in production, Wt is the

4 weather variable, T is the level of technology, Ct is the capital stock, and V represents other omitted variables. The extended version of the supply response is the crop response function. The crop response function was divided into two types and depends essentially on the nature of the particular crop in terms of crop year, or in terms of the period between planting and harvesting. The first type is the crop response function for arable crop farming. Arable crops are those farm enterprises which are grown and harvested within one calendar year. These include maize, millet, sorghum, rice, wheat, cowpeas, soyabeans, yams, sweet potatoes, cocoyam, cassava, vegetables etc. In this case, the crop response function is specified as: Qt = f(po, Ps, At-1, Po-1, W, T, Ct, Vt, Qt-1) (3) Where Qt is the quantity supplied of the given commodity, Qt-1 is the quantity supplied in the last crop year, Po is the current price of the commodity, Po-1 is the last season s price of the commodity, Ps is the current price of the competing crop, At-1 is the acreage devoted to the commodity during the last season, W is the weather index, T is the current level of technology, Ct is the capital stock, and Vt represents other unspecified variables. This specification is straight-forward in guiding our thinking in designing research for empirical analysis of arable crop response function. The second type is the perennial crops response function which will not be dealt with in this study and will therefore not be expatiated on in this section. The supply response function has been used by several authors and in recent time, by Dharmaratne and Hathurusinghe, (1999) and Weerahewa (2004). These studies have greatly underscored the importance of the function to an economy. According them, the problem of minimizing and/or eliminating the ugly consequences of hunger, famine and soaring food prices can only be successfully solved by a full understanding of the food supply situations. When we add the supply of fiber in the right amounts and quality, as well as fair prices to adequate food supply, then we begin to tackle very seriously the vital societal task of promoting the general welfare of the nation. Aside, analysts, researchers and extension workers need a more basic knowledge that relates product output to factor input. This knowledge will enable them to meaningfully derive a workable framework for the adjustment of production and employment of resources to economic growth or trends. Efficient adjustment procedures and economically efficient utilization of productive resources are twin forces that society has to contend with under economic growth, be it developed or developing countries. Also, improved knowledge of product supply and the associated factor demand in agriculture would make possible more precise forecasts and predictions. These forecasts and predictions are essential in aiding farmers to make better short run and long run decision on investment and planning. Again, increased production of food and fiber under economic growth calls for adequate servicing of farm business. In other words, there are basic off-farm products of manufacturing industries which are primarily required on the farm. Firms

5 producing such inputs used by agriculture require improved knowledge of product supply and factor demand situations as necessary and sufficient data for their investment planning exercises. Finally, an interregional and/ or interstate framework, improved knowledge of product supply and factor demand phenomena will provide a better basis for programme projection by extension services. It will also be invaluable to regional and / or community bodies in farm planning exercises. Since farming is regionalized as a result of locational, ecological, and edaphic factors, a regional approach to farm planning is an unavoidable process of overall national development and economic growth. Regional supply and demand information can lead to a meaningful analysis of spatial equilibrium in food and fiber for a given economy or country. This study, therefore, will adopt the crop response function to carry out regional analysis of the effects of food price increases on food supply in the country by way of analyzing the data by geo-political zones in order to identify zonal differences. Data Sources This study was done using mainly primary data. The data was obtained from the survey of farming households across the six geo-political zones in the country. A random sample of 200 farming households was selected from one state in each of geopolitical zones. Thus, a total representative sample of 1200 farming households was covered during the field survey. Well structured questionnaires was designed and administered on the selected households. Apart from information on socio-economic and household characteristics, critical information collected include; output of various food crops during last crop year and in recent year, proportion of output meant for household consumption, proportion for gift, proportion set aside for new planting season and proportion sold or set aside for sale. Others include; last season prices of commodities, current prices of commodities and competing crops, area cultivated for crops during last season, rainfall pattern during last season, the use of fertilizer and amount spent on other farm inputs or the use of credit. The crop coverage was done on the basis of the common staples available in each geo-political zone. Method of Data Analysis The data analysis involved both descriptive statistics and a regression analysis. The descriptive statistics was used to calibrate the socio-economic and other household characteristics while the regression analysis involved an econometric estimation of the crop response equation for all the identified crops. The analysis was carried out with the use of either SPSS package. Estimation Methods Deriving from the implicit model of crop supply response function therefore, the empirical model that was estimated is stated as follows: Qsi = b o + b 1 Po + b 2 Ps + b 3 At-1 + b 4 Po-1 + b 5 W + b 6 T+ b 7 Ct + b 8 Qs-1 + E t ) (4) Where Qsi = the quantity supplied of the given commodity (kg) Qsi-1 = quantity supplied in the last crop year (kg)

6 Po = current price of the commodity (N/kg) Po-1 = last season s price of the commodity (N/kg) Ps = current price of the competing crops (N/kg) Asi-1 = acreage devoted to the commodity during the last season (ha) W = weather index (dummy proxy by rainfall 1 for normal and zero otherwise) T = current level of technology (proxy by fertilizer use in kg/ha) Ct = capital stock (proxy by credit use N/ha) Et = error term b o is the intercept while b 1 - b 8 are coefficients and (i=1, 2,n) for crops The a priori expectations are that Po, Po-1, W, T and Ct are expected to have positive influence on Qsi while Qsi-1, Ps and Asi-1 will exert negative impact on Qsi. RESULTS AND DISCUSSION Supply is the quantity of a product that is offered for sale at a given price and at a particular point in time. Most food crops are sold by farmers immediately after harvest as a result of lack of reliable farm level storage facilities. In estimating quantity supplied by the various farming households under investigation in the various geo-political zones in the country in 2008, the quantity of output consumed or meant for home consumption, quantities set aside for the following planting season and quantity given out as gifts were taken away from output of the various crops. What is left is considered as quantity of crop output that was offered for sale. Thus, the average quantity of crop output offered for sale in 2007 and 2008 is as presented in Tables 1 and 2 while the change in output sold between the two years is shown in Figure 3. It is obvious from these Tables and Figure that the quantity of output offered for sale in 2008 did not show any significant increase. In fact growth rate in output sold showed a significant decline for cassava and cowpea while it only recorded a marginal and insignificant increase for yam and maize. The growth rate for rice was less than 30%. In terms of variation across the six geo-political zones, yam sold declined by 20% in the South-East, cassava declined by 45% in the South-South and by 2% in the South-West and rice by 53% in the North-Central. Similarly, maize sold declined by 47% in the South-South and 7% in the South-West while cowpea offer for sale declined by 800% in the North-East, 7% in the North-West and South-West respectively. Table 1: Average Quantity of Output Sold by Geo-Political Zones in 2007 Crop NC NE NW SE SS SW National Yam Cassava Rice Sorghum Maize Millet Cowpea Cocoyam Source: Field Survey, 2008 Table 2: Average Quantity of Output Sold by Geo-Political Zones in 2008

7 Crop NC NE NW SE SS SW National Yam Cassava Rice Sorghum Maize Millet Cowpea Cocoyam Source: Field Survey, 2008 Changes in Crop Sold Growth rate (% ) Yam 0.7 Cassava Rice Sorghum Maize 33 Millet Cowpea Cocoyam Crops Figure 3: Percentage Change in Output of Crop Sold, Estimated Supply Response Functions Food crops cultivation varies across the various geo-political zones as shown in Tables 1 and 2. For example, root and tuber crops like yam and cassava were cultivated in four of the six geo-political zones (NC, SW, SE and SS) while rice; sorghum and millet were cultivated only in the northern zones (NC, NE and NW). The fact that cultivation of rice was not recorded for the SW and SE does not mean that the crop was not grown in these geo-political zones, it only shows that the selection of samples for this study in these zones was probably biased against areas where the crop is cultivated in these zones. This perhaps underscored one of the limitations of this study. Meanwhile, maize recorded wide cultivation across all the six geo-political zones. Consequently, the result of the estimated supply response functions for these crops were only presented for those zones with significant number of respondents. Thus, results of the estimated supply response for yam and cassava were presented for South-West where the models showed some relative level of fitness. Similarly, the results of the estimated supply response function for rice and sorghum were presented for North-Central while that of millet was presented for North-East. Since cultivation of maize cut across all the six geo-political zones, the result of the estimated supply response function was presented for the aggregate national data as shown in Table 3. The Table presented mixed results. For example, while some variables were found to comply with a priori expectations in some equations, some deviated from a priori expectations in other equations. Nevertheless,

8 all the equations showed some significant level of fitness as depicted by the Adjusted R-Square. In other words, the adjusted R-Squares were significantly high except for the estimated supply response function for rice. This is an indication that the explanatory variables in the various equations explained more than 50% variations observed in the dependent variable (Output supply). In terms of the behaviour of the included variables in the models, the supply of output in last season was found to be correctly signed (positive) for all the crop enterprise. It was equally significant for rice, sorghum, maize and millet but not significant for cassava and yam. Similarly, output price during last season was found to have positive influence on output supply in 2008 for all crops and was significant for yam cassava and sorghum while the variable was excluded for the supply response function for rice due to problem of spurious regression. It was, however, not significant for maize and millet. The price of substitute only carried the appropriate sign for yam, cassava and sorghum but the effect was highly significant for almost all the crop enterprises except for millet. This result might be affected by the type of substitute used for the various crops. For example, yam was used for cassava, sorghum for rice, while cassava was use as substitute for maize and sorghum for millet. The area cultivated to crop last season carries appropriate sign as it was found to impact negative influence on all crop except for maize. The variable was also significant for rice, sorghum and millet. It was, however, not significant for yam, cassava and maize. Similarly, rainfall pattern was found to influence positively output supply response for virtually all the crops in 2008 except for rice. The influence was particularly significant for yam, cassava and rice while the variable was excluded from the supply response function for sorghum also due to the problem of spurious regression. The influence of fertilizer on output supply in 2008 was found to be positive for most of the crops except for rice and sorghum. The influence was highly significant for yam, cassava, rice, sorghum and maize while the variable was excluded from supply response function for millet. Table 3: Results of the Estimated Supply response Functions for Crops in 2008 Crops Constant Last season supply Yam (SW) ** (3.16) Cassava (SW) (2.71)** Rice (NC) (5.45)** Sorghum (NC) Maize (National) (5.24)** (1.27) Millet (NE) (1.56) 0.03 (0.37) 0.02 (0.19) 1.84 (2.56)** 1.82 (2.41)** 0.60 (18.95)** 1.72 (4.56)** Crop price last season 80.23** (4.25) (4.95)** Current price of substitute ** (4.17) (4.92)** (5.77)** 5.38 (5.56)** 0.20 (1.50) 0.06 (1.06) (5.24)** 0.21 (2.09)** 0.04 (1.02) Crop area last season (1.67) (0.95) (5.44)** (3.01)** (0.32) (5.24)** Rainfall pattern ** (3.03) ** (2.97) (3.12)** Fertiliz er use 30.19* * (5.04) (3.99)* * (2.91)* * (2.63)* * (1.23) Source; Computed from Field Survey Data, 2008 Figures in parentheses are t-values ** Significant at 10% alpha value 8.25 (2.46)* * Current price of crops 39.51** (4.17) 40.69** (4.92) 4.36 (5.77)** 6.25 (5.24)** 0.21 (2.09)** (1.02) Adjusted R-square

9 IMPLICATIONS OF THE RESULTS The results of the various analyses on the impact of food price increase on agricultural production and profitability of enterprises presented in section four of this report posed a number of policy issues and challenges. There was significant increase in labour use across various farming activities in This also underscores the inefficient use of resources with its attendant consequent for labour productivity. In the use of other variable inputs, increase in fertilizer use in 2008 was very marginal while the use of herbicide declined an indication of low level of technology adoption. Consequently, increase in output of fertilizer demanding crops in such as rice, maize and millet in 2008 was very insignificant. Price analysis revealed that increase in farm gate price in 2008 was marginal mostly for grains and declined particularly for rice and millet. Consequently, increase in quantity of grains offer for sale by farmers in 2008 was less than 40%. Enterprise profitability as measured by Gross Margin declined for millet and cowpea and recorded only marginal increase for rice and maize in The results of the estimated supply response functions presented four distinct policy variables. These are prices, area cultivated to crops, rainfall pattern and fertilizer use. These variables were found to significantly influence the quantity of food crop output supplied in Their influences were particularly significant for rice. Policy Recommendations To address the price problem, government at state and Federal level will need to improve on their price stabilization measures. The strategic grain reserve policy of Federal Government needs to be made operational and efficient while the buffer stock policy at the State level needs to be reinforced. This is to guarantee remunerative prices for crop output by farmers every year. There is no doubt that for Nigerian farmers to gradually move towards commercial agriculture that can guaranteed constant food supply, there is the need to expedite actions on the agricultural land development policy of the Federal Government. The tractor hiring scheme of the State Governments should also be reinforced. Our food crop production is still mainly rain fed. Thus, a judicious implementation of FADAMA III project across the country will reduce the risk faced by farmers as a result of the vagaries of whether. In the case of fertilizer, the 25 per cent subsidy on fertilizer by Federal Government is adequate and should be retained. Since agriculture is on the concurrent list however, both state and local governments can still offer their own subsidy. Meanwhile, the bottlenecks that are often encountered in terms of procurement and distribution can be solved by licensing more companies to import and discourage political patronage as a

10 condition for marketing and distribution. As a matter of fact, marketing of fertilizer should be prohibited while farmer associations and cooperatives should form the platform for the distribution of the commodity. However, domestic production of fertilizer is very important and governments efforts should be directed towards establishment of small scale fertilizer plants across the country. Management of such plants should either by a public private partnership or leasehold arrangement. Credit facilities targeted specifically at food crop farmers will enhance the capacity of the farmers to increase production. Thus, 80 per cent of special fund for agricultural development should be set aside as loan to rice, maize, yam and sorghum producing farmers while 20 per cent should be allocated between livestock and fisheries farmers. Finally, other measures that could be adopted include: Boosting agricultural science and technology. Current agricultural yields are insufficient to feed the growing populations. Eventually, rising agricultural productivity will drive economic growth, and; Securing property right and access to finance REFERENCES Dharmaratne, T.A and C.P. Hathrurusinghe (1999): Paddy/Rice marketing: Perspectives and Prospects in 90 s. Economic Review (January-March):6-11 Olayide S.O. and E.O. Heady (1982): Introduction to Agricultural production Economics. Ibadan University Press, University of Ibadan, Nigeria. Weerahewa J. (2004): Impact of Trade Liberalization and market Reforms on the Paddy / Rice Sector in Sri Lanka. MTID Discussion Paper No. 70. International Food Policy Research Institute. Washington, D.C. U.S.A. UN Department of Public Information, News and Media Division, New York. April Press Conference by World Food Programme Executive Director on Food Price Crisis. NAEE: Nigerian Association of Agricultural Economists Economic and Policy series Vol 1, Oct 2008 No1. TWN: Third World Network. accessed 28/03/2009.