RURAL-URBAN PRICE TRANSMISSION AND MARKET INTEGRATION OF SELECTED HORTICULTURAL CROPS IN OYO STATE, NIGERIA

The majority of agricultural markets in African countries are inefficient and poorly integrated. This study therefore assessed the level of market integration and the trend analysis of selected vegetable crops in Oyo State. It also identified the leading market between rural and urban markets in Oyo state. Secondary data on the prices of fresh tomato, onion, chilli pepper, sweet pepper, and fresh pepper (2003–2011) were obtained from Oyo State Agricultural Development Programme and were analysed using trend analyses, Augmented Dickey-Fuller (ADF) test, Granger causality test and index of market concentration. Results showed that the prices of onion, chilli pepper and fresh pepper were non-stationary in their various level forms but stationary at first difference; while prices of fresh tomato and sweet pepper in urban markets were stationary at their level form at probability of 5% respectively. The indices of market concentration for onion, sweet pepper, fresh pepper, chilli pepper were less than one suggesting high short-run market integration, whereas fresh tomato achieved low short-run market integration. Further, urban markets were the leading markets for onion, chilli pepper and sweet pepper, while rural markets were the leading markets for fresh tomato and fresh pepper.


Introduction
Efficient food marketing system and its role in food security in Nigeria is pivotal to a reduction in post harvest losses; ensuring adequate returns to farmer's investment and stimulating an expansion in food production thereby enhancing the level of food security in Nigeria through adequate information about prices of agricultural produce (Ladele and Ayoola, 1997).Prices are a measure of availability because they tend to rise as the supply of food falls in relation to demand (e.g.poor production, constrained imports of food), and they tend to fall when supply expands in relation to demand (e.g. a bumper harvest).Agricultural prices contribute significantly to the pace and direction of agricultural development.They serve as market signals of the relative scarcity or abundance of a given product (Akintunde et al., 2012).Prices also serve as a stimulus to direct the allocation of economic resources and to a large extent they decide the structure and rate of economic growth.Prices vary almost throughout the year and understanding the trend of such variations was therefore essential for good planning by the producers, consumers and policy makers.
Agricultural commodity prices unprecedentedly fluctuated and continuously increased from 2002 to mid 2008.This resulted in price volatility, food inflation, poverty and hunger, coupled with inadequate market price transmission.High food prices increased the levels of food deprivation, food insecurity, worsening conditions for many who were already food insecure and thus threatening global long-term food security (Abbott, 2009).This has placed a tremendous pressure on achieving the millennium development goal (MDG) on hunger by the year 2015 (FAO, 2008).The price volatility of agricultural commodities in Nigeria is attributable to various factors including variances in bargaining power among consumers, cyclical income fluctuations among sellers and consumers, natural shocks and inappropriate response by farmers to price signals (Adebusuyi, 2004;Udoh and Sunday, 2007).However, short-run fluctuations in agricultural commodity prices take place between production seasons.During the harvesting period farmers offer to the market the minimum price for their products while prices become high during the drought or off-season owing to reduced production and seasonal changes (Cashin and Pattillo, 2000;Akpan, 2002).The issue of market integration (co-movement of prices and smooth transmission of price signals and information across spatially separated markets) is fundamental to many contemporary debates on market liberation, price policy and parastatal reform in food market of developing countries.The integration of agricultural commodity market is therefore a necessity for the effectiveness of agricultural marketing reform programmes.It ensures the transmission of price signals from food deficit to food surplus areas and help farmers to increase specialization and harness comparative advantages and gains from trade (Baulch, 1997).The aim of market integration analyses therefore is to find the possibility of achieving some gains by trading across commodity markets, exploiting price movements in one market (urban) for the prediction of price movements in another market (rural) (Okoh and Egbon, 2005).
The majority of agricultural markets in African countries are inefficiently and poorly integrated and agricultural marketing efficiency in Nigeria is dismally low (Onyuma et al., 2006;Phillip et al., 2008).A major characteristic of agricultural markets in Oyo State is the inter-and intra-pricing variations among its urban and rural retail markets due to the forces of demand and supply (Adenegan and Adeoye, 2011).The majority of farmers and retailers have poor access to credit which may reduce their ability to respond to price changes (Okoh and Egbon, 2005).Consequent to these factors, market service areas covered by traders may overlap with several sellers operating within the same market or village.Therefore, there exists a possibility that a price change in one market would result in a series of price responses that spread throughout contiguous market areas in this case such price changes may not have discernible effects on more distant markets making the attainment of an integrated foodstuff market system a mirage (Akintunde et al., 2012).
Vegetable marketing is often characterized mainly by the problem of seasonality and perishability.The quality and nutritional value of fresh produce like tomato, fresh pepper, sweet pepper, chilli pepper and onion are affected by post harvest handling and storage conditions (Sablani et al., 2006).Many consumers do not have price information on the selected vegetables in various retail markets which might lead to exploitation due to insufficient price statistics and a familiar problem is the inter and intra-pricing variations among urban and rural retail markets due to the forces of demand and supply.There are arrays of competitive prices on tomato, onion, sweet pepper, fresh pepper, and chilli pepper within and across the rural and urban markets in the state.This study therefore evaluates the market integration of the selected vegetables between rural and urban markets in Oyo state.

Material and Methods
The secondary time series data prices on the selected vegetables were obtained from Oyo State agricultural development programme.The secondary time series price data contain monthly retail price per kilogramme of fresh tomato from the selected rural and urban retail markets of the state from 2003-2011.The choice of fresh tomato, fresh pepper, sweet pepper, chilli pepper and onion is due to their importance in the diet and the daily variation in prices.

Co-integration technique
Co-integration can be regarded as the empirical counterpart of the theoretical notion of long-run equilibrium relationship.Firstly, variables have to be pre-tested for stationarity.Stationarity means that the marginal distribution of the process does not change with time.
(1) A series is said to be integrated of order 'd', I(d), if it has to be differenced 'd' times to produce a stationary series.Once stationarity is obtained, variables are then tested for co-integration or long-run relationship.Two series are co-integrated of order (1,1), if the individual series are I(1) and a linear combination of them called the co-integrating regression is I(0).After getting co-integrated relationship, the residuals from the equilibrium regression can be used to estimate the error correction model.Two or more variables are said to be co-integrated if each is individually non-stationary (i.e. has one or more unit roots), but there exists a linear combination of the variables that is stationary.After the stationarity test, we tested for co-integration between market price series that exhibited stationarity of the same order (Johansen, 1988).The Johansen test allows for the existence of more than one co-integrating relationship (vector) and the speed of modification towards the long-term equilibrium is easily determined (Bakucs and Ferto, 2005).The two variable systems were modelled as a vector auto-regression (VAR) as follows: (2) where = an n x 1 vector containing the series of interest (tomato spatial price series), τ and π = matrices of parameters, k = number of lags, and should be adequately large enough both to capture the short-run dynamics of the underlying VAR and to produce normally distributed white noise residuals.

Test for causality
Granger-causal relationship exists in a group of co-integrated series (Chirwa, 2000).The causality test is represented by the error correction equation as follows: where m and n are numbers of lags determined by Akaike information criterion.Rejection of the null hypothesis (by a suitable F-test) that αh = 0 for h = 1, 2,...n and = 0 indicates that Granger causality runs in both markets and, then prices are determined by a simultaneous field-back mechanism (SFM).This is the phenomenon of bi-directional causality.If the Granger causality runs one way, it is called unidirectional Granger causality and the market which leads the other is tagged as the exogenous market.

Index of market connection (IMC)
The index of market concentration was used to measure price relationship between integrated markets.Following Oladapo and Momoh (2007) approach, the actual rural price is given by the equation below.
= urban or reference price = rural price = lagged price for urban markets = difference between urban price and its lag = error term or unexplained term    Rural-urban pri epper were maximum ru rural market ket price wa ce was N68.7 er was the hi ber 2006, w 06 and the m fluctuation in was a high d (Figure 5).

Trend in urban
Trend in urban

Stationarity tests of the selected vegetables
The findings revealed that the acceptance of the null hypothesis of nonstationarity could be achieved at the probability of one percent level of significance (Table 1).Although the null hypotheses of non-stationarity were accepted for the prices of onion, chilli pepper and fresh pepper in their level form for rural markets, they were rejected at first difference.This conforms with the findings of Chirwa (2001), Yusuf et al. (2006) and Adeoye et al. (2011) that commodity prices could be stationary at first difference.However, urban market prices of fresh tomato and sweet pepper were stationary in their level form.Therefore, the test of cointegration was applied to fresh tomato and sweet pepper price series data which were integrated in the same order I(1) and did not have a unit root.

Co-integration test for the prices of the selected vegetables
The co-integration tests for market integration are to test whether there is a statistical significant linear relationship between different series data.The maximum Eigen values revealed that all five market pairs investigated were co-integrated at five percent level of significance.The null hypotheses of co-integration relationships were rejected at five percent significance level for all the selected vegetables in their various market pairs but sweet pepper (p<0.01)(Table 2).The trace test showed that the market pairs for all the selected vegetables were co-integrated in order (1,1) at five percent level of significance.This suggests that there is a linear long-run relationship between the rural and urban price series.RMPFT -Rural market price of fresh tomato, UMPPFT -Urban market price of fresh tomato; RMPO -Rural market price of onion, UMPO -Urban market price of onion; RMPCP -Rural market price of chilli pepper, UMPCP -Urban market price of chilli pepper; RMPSP -Rural market price of sweet pepper, UMPSP -Urban market price of sweet pepper; RMPFP -Rural market price of fresh pepper, UMPFP -Urban market price of fresh pepper.

Granger causality test for the selected vegetables
Five market links accepted their respective null hypothesis of no Granger causality while five other market links exhibited bi-directional Granger causality or a simultaneous feedback relationship (Table 3).Urban markets for onions, chilli pepper and sweet pepper had strong exogeneity over their respective rural markets.On the other hand, rural markets for fresh tomatoes and fresh pepper had strong exogeneity over urban markets for fresh tomatoes and fresh pepper.Thus, the markets were spatially linked by trade with urban markets being the leading markets for onion, chilli pepper and sweet pepper, while rural markets were the leading markets for fresh tomato and fresh pepper.Therefore, there was market integration between rural and urban market of the selected vegetables suggesting that price changes in one market exhibit identical price response in the other market.There was also an adequate free flow of goods between the rural and urban markets and they are linked by efficient arbitrage.

Indices of market concentration (IMC) for the selected vegetables
Results revealed that the indices of market concentration (IMC) for onion, chilli pepper, sweet pepper and fresh pepper were less than one indicating high short-run market integration (Table 4).Therefore, changes in rural market price caused immediate changes in urban market price for all the selected items except for fresh tomato (IMC = 1.37).The low short-run market integration of tomato markets suggests that rural market prices of fresh tomato did not account for immediate changes in urban market price of fresh tomato.(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011).

Figure
Figure 2. T The m December while the m minimum u

Figure
Figure 4. T

Table 1 .
Results of the Augmented Dickey-Fuller (ADF) test for the selected vegetables in Oyo State.

Table 2 .
Results of Johansen maximum likelihood test for the rural and urban markets of the selected vegetables in Oyo State.Represents the rejection of null hypothesis at 5% significance level. *

Table 3 .
Granger causality test for the selected vegetable prices in Oyo state.