Spatial Retail Price Integration of Maize Markets in Ogun State


Master's Thesis, 2007

96 Pages, Grade: A


Excerpt

TABLE OF CONTENTS

ABSTRACT

DEDICATION

ACKNOWLEDGEMENT

TABLE OF CONTENTS

LIST OF TABLES

CHAPTER ONE
1.0 INTRODUCTION
1.1 Background Information of Nigeria
1.2 Importance of Agriculture to Nigeria’s Economy
1.3 Economic Role of Maize in Nigeria
1.3.1 Trends in maize production and area harvested
1.4 Statement of Research Problem
1.5 The Basic Research Questions Include:
1.6 Research Objectives
1.7 Hypotheses of the Study
1.8 Justification of the Study
1.9 Scope of Research

CHAPTER TWO
2.0 LITERATURE REVIEW
2.1 Previous Studies on Market Integration
2.2 Theoretical Frame Work
2.2.1 Concept of market integration
2.2.2 Concept of price transmission
2.2.3 Price transmission notions and components
2.2.4 Distinguishing the concept of Market Integration (MI), the law of one price (LOP) and market segmentation (MS) by definition;
2.2.5 Concept of structure, conduct and performance
2.2.6 Concept of non-stationarity and cointegration
2.3 Characteristics of Agricultural Commodity Retail Markets
2.4 Agricultural Marketing
2.5 Benefits of Market Development to Agricultural Commodity Marketing

CHAPTER 3
3.0 RESEARCH METHODOLOGY
3.1 Study Area
3.2 Data Sources and Method of Collection
3.3 Sampling Procedure
3.3.1 Abeokuta zone
3.3.2 Ikenne zone
3.3.3 Ijebu ode zone
3.4 Analytical Techniques
3.4.1 Descriptive statistic
3.4.2 Test of Series Stationarity and Equation Cointegration
3.4.3 Dynamic price relations
3.4.4 Granger-causality test
3.5 Limitations of the study

CHAPTER FOUR
4.0 RESULT PRESENTATION AND DISCUSSION
4.1 Marketing Characteristics of Maize Traders in Ogun state
4.1.1 Profile of Sample Maize Traders.
4.1.2 Access to Infrastructural Facilities
4.1.3 Marketing characteristics of sample maize traders.
4.1.4 Associated Cost with Maize Trading
4.1.5 Cost and Returns of Maize Retailing
4.1.6 Sources of Market information and Strategies for Price Fixing
4.2 Integration of Maize Markets
4.2.1 Unit root tests of Maize Price Series
4.2.2 Cointegration Test of Maize Price Series
4.3 Results of the normalized cointegration coefficients between Markets
4.3.1 Abeokuta zone
4.3.2 Ikenne zone
4.4 Granger Causality Test

CHAPTER FIVE
5.0 SUMMARY, CONCLUSION AND POLICY IMPLICATION
5.1 Summary
5.2 Conclusions
5.3 Policy Implication

REFERENCES

APPENDIX

M. AGRIC RESEARCH INTERVIEW GUIDE

ABSTRACT

The study examined the dynamism of price movement between markets and its implication on pricing efficiency in maize markets. Primary data were collected using interview guides. A total of 240 respondents were selected using stratified random sampling technique in 6 rural and 6 urban markets in Ogun State. Weekly retail prices of yellow and white maize for five years (January 1999-December 2003) were analysed using the Bivariate Cointegration test and the Granger causality test to detect the presence and level of price integration. Results of the study revealed that markets in Abeokuta zone were the most integrated (α0.05). The Granger causality test (α0.05) complemented the cointegration test (α0.05), revealing that market price of maize move together at appropriate lag. Consequently, prices in Osiele market could predict price in Odeda and Lafenwa markets. Also prices in Arigbajo market cointegrated and could predict price in Lafenwa and Odeda markets. The cointegrating parameters for maize prices (β), were 0.5953 and 0.9661 for white maize for market pairs Osiele – Odeda and Osiele – Lafenwa respectively and 0.7237, 0.6781 and 1.4646 for yellow maize, for market pairs Osiele – Odeda, Osiele – Lafenwa and Arigbajo – Lafenwa respectively. At (α0.01), t statistics was significant; invariably the price series was subject to little or no shock. In Ikenne zone, the causality test (α0.05) revealed predictable relationship between sampled markets, which the cointegration test did not reveal. Prices in Kajola market cointegrated with prices in Ikenne ans Shagamu markets. However, prices in Akala market cointegrated imperfectly with prices in Ikenne and Shagamu markets thus the predictability of relationships became unstable. Although there were cointegrating equations, the t statistic for β values, -7.0341 and -8.1167 for white maize, for market pairs Kajola – Ikenne and Kajola – Shagamu respectively and -6.3330, -4.1853, -2.6383 and -2.2962, for yellow maize, for market pairs, Kajola – Ikenne, Kajola – Shagamu, Akala – Ikenne and Akala – Shagamu respectively were not significant at (α0.01) level. Invariably, the price series are exposed to enormous amount of shock. In Ijebu- Ode, the null hypothesis of no cointegration was accepted for all market pairs, thus suggesting perfect market segmentation. Results further revealed that there were large numbers of suppliers and consumers in the market, indicating that maize markets in the study area were competitive. Entry and exit from the market was frequent and there was free flow of market information. There are market associations, which provide some sort of legal redress structures for the effectiveness of the market. Potential constraints that hampered perfect maize market integration in Ogun State were observed. Prices distortion was a major constraint since price information was transmitted from one market agent to another verbally. Other problems included; poor transportation, inadequate and costly post harvest services (storage) and the inefficiency of the existing associations. It is recommended that government and private agencies involved in marketing information be strengthened to enhance their efficiency. Provision of market infrastructure such as shelter store and post harvest storage facilities will help reduce transaction cost in maize marketing.

DEDICATION

This dissertation is dedicated to God Almighty for sparing my life and for granting me wisdom and patience. Also to my parents, Mr. and Mrs. Felix Imonikhe Itoandon and my beloved brothers and sisters for their patience and support.

ACKNOWLEDGEMENT

The completion of this study marked another level in my life. I learnt a lot of new and very interesting things about knowledge and getting knowledge. I am grateful to my supervisors, Dr. S. Momoh for his encouragement and constructive criticism through out the conduct of this research and Dr (Mrs.) B.B. Philip for her interest in this study and believing in me. My special thanks goes to my lecturers, who during the course work played the role of true mentors. I am deeply indebted and grateful to my beloved parents for the moral, advisory and financial support given to me in pursuit of another academic dream. I pray that God Almighty will grant them long live so that they can reap the fruit of their labour.

My special thanks goes to my loving brothers and sisters; Engr, Rotor, Emoliela, Efe, Odegua and Izegbua for their efforts in praying for my success and speaking prophetically during difficult times.

LIST OF TABLES

Table 1: Ogun State Maize Production; Area Cultivated, Output and Yield (1990-2001)

Table 2: Type of Business Ownership

Table 3: Frequency of Sample Maize Traders who sell other Commodities

Table 4: Reasons for joining the Business

Table 5: Years in trading activity of sample Maize Traders

Table 6: Sources of Traders Commodity

Table 7: Cost Associated with Sample Maize Marketing

Table 8: Association distribution as revealed by Survey

Table 9: Strategies for Price fixing

Table 10: Measuring the Profitability of Maize retailing on a 50kg bag

Table 11: Source of Market Information

Table 12: Ease of Price Transmission

Table 13:Result of Augmented Dickey-Fuller Unit Root Test of Price Series in Abeokuta zone

Table 14: Result of Augmented Dickey-Fuller Unit Root Test of Price Series in Ikenne zone

Table 15: Result of Augmented Dickey-Fuller Unit Root Test of Price Series in Ijebu ode zone

Table 16: Results of Johansen Cointegration Test of Price Series in Abeokuta zone

Table 17: Results of Johansen Cointegration Test of Price Series in Ikenne zone

Table 18: Results of Johansen Cointegration Test of Price Series in Ijebu ode zone

Table 19: Summary of Results of cointegration Test of Price Series in Abeokuta zone

Table 20: Summary of Results of cointegration Test of Price Series in Ikenne zone

Table 21: Pairwise Granger Causality Tests (Abeokuta Zone) At No Lag

Table 22: Pairwise Granger Causality Tests (Ikenne Zone) At No Lag

Table 23: Pairwise Granger Causality Tests (Abeokuta Zone) At Lag 4

Table 24: Pairwise Granger Causality Tests (Ikenne Zone) At Lag 4

CHAPTER ONE

1.0 INTRODUCTION

1.1 Background Information of Nigeria

Nigeria has a population of about 120 million people, of which 65% are rural-based, and is growing at 2.83% per annum. Average population density is about 100 person/km2, ranging from 40/km2 in the middle belt and Northern States to about 400/km2 in some Southern States (FOS, 2000).

According to Adubi (1996), prior to the discovery of oil in the 1970s, agriculture was the main stay of the Nigerian economy, accounting for about two-thirds of the Gross Domestic Product (GDP), with the oil boom, agriculture’s contribution to GDP declined to 25% by 1980, and Nigeria moved from being a large exporter to a major importer of agricultural products. Since the mid-1980s, as a result of a decline in oil revenue and policy measures implemented under the structural adjustment programme (SAP) agriculture’s contribution to GDP has risen to about 40% in 1989. By 1996, agriculture had taken a sizeable share of the non-oil sector contributing over seventy percent (70%) to the GDP and three quarter of the non-oil exports and employment (Adubi, 1996).

Of the total land area, 71 million ha, (77%) are considered cultivable; about 32 million ha (45% of the total cultivable land area) is cultivated. Annual rainfall ranges between 2500mm in the coastal area to about 500mm in the far north. Nigeria is undoubtedly blessed with abundant arable and fertile land for cultivation. The wide agro-ecological conditions allow for very diverse crop production (both food and cash crops) to be grown in large and commercial quantities. The northern part of the country is suitable for sorghum, millet, maize, cowpea, groundnut and cotton. The main food crops in the middle belt and the south are cassava, yam, plantain, rice and maize. Low lying and seasonally flooded areas are increasingly being used for rice production. CBN (1981), observed that the factors militating against agriculture in Nigeria, which still exist after four decades include among others Infrastructure deficiencies e.g. lack of rural electrification, few access roads, high cost of labour due to more attractive remuneration in other occupations like industry and commerce; institutional constraints, such as weak agricultural extension and research services that have widened communication gaps between peasant farmers and policy makers and government agents; marketing problems embracing the lack of processing, storage; and transportation facilities, as well as the ineffective market research and information system; ineffective pricing policy, which have not generated adequate farmer’s response. Broadly speaking, maize growing belts fall within three agro-ecological zones of the southeast, southwest and the central areas. The first two zones fall within the humid tropics. The predominant soil types are the ferralitic soil, which are rich in free iron but low in mineral reserves and are consequently low in fertility. The central zone lies between the southern and the drier northern agro-ecological zones. The soils are poor, due to leaching from heavy and intense rainfall and so limited fertility is a constraint to agricultural production in Nigeria.

1.2 Importance of Agriculture to Nigeria’s Economy

A wide range of climatic and soil conditions allow for the production of different crops by both traditional and modern methods. The dry Savannah of the north is suitable for sorghum, millet, maize, groundnuts and cotton. The main food crops of the middle belt and the south of the country, which have up to five months of rainy season, are cassava, yam, plantain and maize. The swampy river basin areas produce rice. Cocoa is cultivated in the southwest, and oil palms in the southeast. The Northern part of the country support substantial livestock production owing to the availability of grazing feed. Reports such as Gilbert, (1969); Oludimu, (1982); Adubi, (1996); show that the Nigerian economy was largely agrarian at independence in 1960 with agriculture providing employment for about 70 per cent of the country’s labour force. Agriculture also contributed about 70 per cent of Gross Domestic Product (GDP). Much of the domestic savings of the early 1960s were equally generated by the sector. According to Adegeye et. al., (2000), the principal products were cocoa, palm kernel, palm oil and groundnuts. Nigeria was the world's second largest exporter of cocoa in 1960 controlling almost 20 per cent of world cocoa trade, however, a gradual decline of the contribution of agriculture to GDP, employment and foreign revenue was reported. The evident implication is the decline in relative importance of agriculture in terms of contribution to GDP as well as export earning. From about 70 percent in 1960, the contribution of the sector to GDP declined to 55 per cent in 1966. The contribution stood at 53 per cent and 23.4 per cent in 1968 and 1975 respectively. According to the CBN,(1995) the figure was 31.6 per cent in 1990. The fall in agricultural production recorded in the 1970s coincided with the rapid growth in urban population, the production of crude petroleum and expansion of the construction sector, which drew young and able-bodied men from the farms to the cities to pick up white collar jobs.

Successive attempts have been made to promote food production over the years, with little or no success. For example, in the 1970s there was “Operation Feed the Nation”, “Green Revolution” and River Basin Developments in the 1980s followed this. In spite of these highly publicized efforts, the reality is that there has been little practical support provided to farmers. The result is that Nigeria has moved, since independence, from being a large exporter of major agricultural products to a net importer. The sector seemed to have strengthened in the late 1980s. This trend was more encouraging in the last few years as a result of some of the measures implemented under the Structural Adjustment Programme (SAP), especially the abolition of the produce marketing boards in 1986. But this was short-lived owing to frequent changes in official policies, which failed to raise farmers’ confidence enough to stimulate cultivation of major commodities. Until recently, cocoa, one of the country’s agricultural export crop with production averaged well over 200,000 tons in the 1970s suffered subsequently from low prices, drift of labour and insufficient replanting as well as shortages of inputs due to foreign exchange constraints experienced decline in volume of it’s export tones. The liberalisation of cocoa marketing in 1986 along with the devaluation of the Naira increased cocoa farmers’ earnings and thus reversed the decline in cultivation. About 256,000 tons was produced in 1989 but this slowed down to 167,000 and 140,000 tons in 1992 and 1995 respectively (CBN Annual Report and Statement of Accounts, 1995).

Nigeria also exported large amounts of groundnuts and groundnut oil, palm kernels and palm oil, rubber, cotton and timber in the 1960s. However, by 1980 the country has become a large importer of foodstuffs such as rice, maize, wheat and sugar. Today, cassava, cocoa and rubber and some small quantities of other commodities are exported. Some former cash crop exports such as cotton and groundnuts are currently being imported to supplement the requirements of local processing industries. In 1992, food and live animal imports amounted to N12.6 billion, 8.8% of total imports compared to N802 million or 13.4% of total imports in 1986. Agricultural exports earned N3.1 billion or 1.5% of total exports in 1992, down from 8.2% in 1988 (Aigbokhan, 2000).

1.3 Economic Role of Maize in Nigeria

Nigerian arable crop production’s earning is heavily dependent on the production of four crops, cassava, yam, sorghum and maize, which account for approximately 80.0 percent of total output of staples in 1999. Of these major crops, sorghum and maize are the chief cereal grains, with cassava constituting the country’s arable crop export of the agricultural commodities grown in Nigeria. Maize is the second most important grain crop after sorghum (FOS, 2000).

1.3.1 Trends in maize production and area harvested

Output of maize has been expanding since the 1970’s; it increased at an average annual rate of 3.45 percent over the 1970–1999 crop years (Durojaye and Aihonsu, 1988). Although total maize area continued to increase during that period, the size of maize farms in Nigeria remained relatively small, accounting for about 2.6 hectares on average but the total area under maize was put at 6million hectares (FOS, 2000). Yellow and white maize are the two varieties of maize popularly grown in Nigeria. The growth in maize area, however, came largely from yellow maize, which grew at an average rate of 8.83 percent yearly over 1974 – 1989 (FAO, 1995). Due to the sustained growth in yellow maize, the relative share of harvested area of yellow maize rose from 10 percent in 1974 to 27 percent in 1991 (FAO, 1995). White maize area showed a meagre increase of 0.05 percent per year during 1974 – 1989.

In Ogun State, domestic production of maize increased by 9 percent a year between 1990 – 2001 (Table I) Although the growth in maize production may be attributed to cultivating more crop area and/or the adoption of improved open pollinated and hybrid maize varieties which provide the major stimulus for increased yield on the average. Annual growth rate of maize yields was 9.08 percent during 1990 - 2001. Most of the growth came from yellow maize, which increased at 8.92 percent annually, compared with 3.57 percent for white maize. In comparison with other states in South-West however, the Ogun state average yield of 1.41 metric tons per hectare is the lowest (OGADEP, 2002).

Table 1: Ogun State Maize Production; Area Cultivated, Output, and Yield (1990-2001)

illustration not visible in this excerpt

Source: OGADEP STATISTICS, 2002

Maize has two major uses: human food and animal feed. It is a cheaper source of Calories than rice. In Nigeria, a recent available statistics reveal that rural settlers consumed nearly 10 kilograms of maize per person in 1987, more than twice the 4.30 kilograms eaten by urban settlers (FAO, 1995). Maize purchases account for only 0.01 percent of the food budget in urban household and 0.24 in rural households. Maize is an excellent energy source in the production of poultry feed because of its high metabolizable energy content and crude protein content. Maize accounts for 30 percent, of the total poultry feed mix (Mendoza and Rosegrant, 1991).

FAO, (1995), asserted that the demand for maize as food and feed has undergone some major transformations. Over the years, more and more maize has been used in feed manufacturing, displacing its primary use as human food. The relative share of maize used in the manufacturing of poultry and livestock feed increased to 67 percent in 1997 from 60 percent in 1988 (FOS, 2000). Maize consumed as food accounted for almost 27 percent of domestically available corn supply in 1997, down from 33 percent in 1988. The relative share of non-food corn uses, excluding wastage and seeds, remained relatively stable at 5.0 percent in 1988 and 4.5 percent in 1997 in Nigeria.

The major impetus in growth of yellow corn production stems from the development in Nigeria’s poultry and livestock sectors during the 1970s. Between 1971 and 1989, total production of poultry meat rose at 4.99 percent per year during 1971 – 89 and 11 percent per year between 1990-1997. The boost in poultry production also came from substantial growth in commercial sector, which displayed a remarkable 14.11 percent yearly increase during this period. Backyard poultry production rose at 2.85 percent per year.

1.4 Statement of Research Problem

Poor market knowledge and other structural imperfections have been asserted to cause inefficiency in agricultural commodity markets, Gilbert, 1969; Durojaye and Aihonsu, 1988; but the role of information in pricing, the dynamic process of information transmission between markets in price discovery and its implications for marketing efficiency is very important (Mendoza and Rosegrant 1995).

The study of market integration has usually tried to characterize the degree of co-movement of prices across spatially separated markets. Since prices are the most readily available and often the most reliable information in developing countries marketing system (Wyeth, 1992).

In Nigeria in general and Ogun state in particular, researches ( Oludimu, 1982; Durojaye and Aihonsu, 1988;) have shown at different levels that markets are characterised by problems that greatly distort pricing efficiency, for example transportation constraints, communication constraints to mention a few. However, Agricultural commodity markets have been said to be some worth highly competitive (OGADEP, 2000).

The research problem of this study is built on two salient issues. First, the assumption that Nigerian foodstuff markets are perfectly competitive as submitted by OGADEP, (2000), Orubu (1991), Durojaiye, and Aihonsu, (1988), Hay and McCoy, (1977), Jones, (1972), and Gilbert, (1969). Their conclusions based on the data and information available to them may not just be suitable enough to draw inference that is void of errors in this present day. The second issue is the methodology. The assumption that economic variables (e.g. price) are steady over time i.e. they have a steady mean and variance over time brings up another submission that cannot be void of inferential errors, however, efforts are been made to correct this notion. This study is another of such efforts that will try and establish the relevance of previous criticism using maize market information in Ogun State.

Using the concepts of Structure, Conduct and Performance (SCP) to assess if the market systems are competitive or not, this study is to attempt by the application of measure of cointegration model developed by Ravallion (1986) with refinement, by Engle and Granger (1987), Mendoza and Rosegrant (1995), Goletti et al (1995) to investigate the existence of a stable relation among price series across maize markets, measuring long run shocks and investigating market pairs causality that exist across integrated maize markets in Ogun State.

1.5 The Basic Research Questions Include:

i. How integrated are the maize markets in the study area?
ii. Are there evidences of lead-lag relationship among spatial maize markets in Ogun State?
iii. Are there evidences of communication of information to integrate spatial markets?
iv. How long does it take information to become common knowledge across spatially dispersed markets (temporal effect)?
v. Are the market systems competitive or not?

1.6 Research Objectives

Broad Objectives

To determine the efficiency of price movement between maize markets in Ogun State.

The Specific Objectives are to:

i. Assess the marketing characteristics of maize traders in the study area.
ii. Determine the presence and level of long run integration in spatial maize markets in the study area.
iii. Investigate the lead-lag relationship among spatial maize markets in the study area.
iv. Make recommendation(s) based on the findings of the study.

1.7 Hypotheses of the Study

The study will test the following null hypotheses

(1) Ho: that the markets are independent
(2) Ho: that there is no influenced adjustment to price change
(3) Ho: that there is no perfect price matching without delayed response to Price changes.

Note: the rejection of these hypotheses suggests that the market or pricing systems are integrated, perfectly competitive and efficient.

1.8 Justification of the Study

Most previous studies Gilbert, 1969; Durojaiye and Aihonsu, 1988; Orubu, 1991 of food market integration select just a single technique, which the researchers feel, is suitable to the data set to be analysed on a prior ground. The results from most of such studies are likely to be misleading due to lack of a thorough knowledge of the workings of the markets from which the price data are gathered (Mafimisebi, 2001).

Past research OGADEP, (2000), Durojaiye, and Aihonsu, (1988), Jones, (1972), Gilbert, (1969), Hay and McCoy, (1977) and Orubu (1991). on foodstuff and grain markets employed the marketing margin analysis and the traditional methodology of bivariate correlation of price series of spatially-dispersed market, They reported low correlation coefficients, which were contrary to expectations. Others employed static linear function for analysis of price behaviour in spatially dispersed market in many other studies. These methods have been criticized on the grounds of auto-correlation, serial dependence, measurement errors, model misspecification (that would result in imprecise estimates) and non-stationarity. These introduce bias in the estimates leading eventually to inferential errors. Also, these methods have been found to be unreliable when trade is discontinuous or bi-directional (Barret, 1996, Barret et. al., 1999).

Market integration, an important aspect of marketing research is essential to the maintenance of household and regional food security (Delgado, 1986). It is necessary to study price movement in spatial markets because they reflect or represent the movement of equilibrium paths of demand and supply for a particular commodity or a group of commodities. The co movement, speed and accuracy of diffusion of price information are prerequisite for achieving efficient allocation of resources across space and time (Jayara, 1992). Also, the knowledge of the state of integration in the domestic market system will help market intermediaries to identify the substitution possibilities between markets and between commodities, above all insight to the marketing system to corroborate government policy on poverty alleviation programme will be gained.

With specific reference to the study area this study will advice the government, non governmental organisation (NGO) and private staple food marketing firms on the rules of price movement across the selected maize markets, thus avoiding vast price irregularities. Furthermore, knowledge of price spread across local markets will help the Ogun state government and all the marketing agents to understand the operations in local markets and indirectly, to influence maize supply and availability so as to ensure the balance in maize supply across the state.

1.9 Scope of Research

The study considered 6 urban and 6 rural markets specifically known for grain business in the high consumption areas (Abeokuta, ijebu Ode and Ikenne) of Ogun State as recommended by Ogun State Development Project (OGADEP). From Ikenne zone; Kajola and Akala markets are rural markets while Ikenne and Shagamu markets are urban markets. From Ijebu Ode zone; Atan and Isiwo markets are rural while Isonyin and Odogbolu markets are urban markets. And for Abeokuta zone; Arigbajo and Osiele markets are rural while Odeda and Lafenwa markets are urban markets. Weekly retail prices were collected for the commodity (white maize and yellow maize), for the period of five years (Jan 1999 – Dec 2003). The time series data was collected from OGADEP. Also field survey was carried out to help describe the socio-economic and marketing characteristic of the traders.

CHAPTER TWO

2.0 LITERATURE REVIEW

2.1 Previous Studies on Market Integration

Market integration is a concept with application in spatial, temporal and product form market interrelatedness; it is often used as a proxy for the efficiency with which a marketing system operates (Dittoh, 1994, Ashad, 1990) and the level of competitiveness in the market (Jones, 1972, Anthonio, 1968, Hays and McCoy, 1977, Delgado, 1986). Spatial market integration by definition refers to co-movements of prices, and more generally, to the smooth transmission of price signals and information across spatially separated markets (Goletti et al 1995).

Reasons for studying market integration, includes the ability to determine the possibility of obtaining some gains by trading across commodity markets; exploiting movement in one market (urban) for the prediction of price movements in another market (rural) and to identify groups of integrated markets, so as to avoid duplication of intervention. If locations A, B and C are well integrated, then the government may think of withdrawing from, or at least stop or reduce, its efforts to influence the price process in these locations. Since a scarcity in A will be quickly transmitted to B and C, making it redundant to duplicate the same program in the three locations. To give a more detailed picture of the process of transmission of incentives across the marketing chain, knowledge of market integration is relevant to the success of policies such as market liberalization or price stabilization. Market integration ensures that a regional balance occurs among food deficit and food surplus regions, and regions producing non-food cash crops (Delgado 1986).

In this respect a well-integrated marketing system is essential for.

i. Both agricultural and industrial development, in the sense that the integrated marketing system facilitates optimum allocation of goods and resources.
ii. Ensure household food security;
iii. Boosting the Gross Domestic Product (GDP) as place, time and form utility of goods is enhanced;
iv. Inter-regional policy formulation since it indicates the level of mutual interdependence between markets (regions).
v. Enhance efficient use of available resources.

Integrated markets are markets between which a stable price differential exists for a commodity or for which relative price for the commodity remains constant or for which price of the commodity do not behave independently and differ by no more than the cost of commodity arbitrage. A number of factors may, however, cause the prices of the same commodity to differ in a non-proportional manner between markets (Durojaiye and Aihonsu, 1988). The study of market integration has tried to characterize the degree of co-movement of prices across spatially separated markets. Most specifically, market integration is restricted to the interdependence of price changes across spatially separated market locations (Wyeth, 1992).

Markets are complex institutions, encompassing hierarchies and interlinked transactions that may involve the simultaneous consideration of various commodities (Palaskas and Harris, 1991). Systematic efforts to relate the available measures of market integration based on price and structural factors cannot be over emphasized, as they try to transmit information, which are conveyed as price signals (Goletti et al, 1995).

Traditionally, the static price correlation or regression approach has been the basic approach employed for testing the presence and level of integration in pairs of spatially dispersed markets. Correlation coefficient directly measure how closely prices of a commodity move together in spatially dispersed markets. The closer the correlation or regression coefficient is to unity, the more integrated and efficient the markets are said to be and the closer they are to zero the less integrated and less efficient they are. Price correlations are the easiest way to measure this co-movement. However, the traditional tests of market integration focused on correlation co-efficient of spatial prices (Lele, 1972, Farruk, 1970, Jones 1972). This approach though masks the presence of other synchronous factors, such as general price inflation, transfer cost, seasonality, procurement policy etc. Early criticism of this approach has been advanced by Blyn (1973), Harris (1972) and Timmer (1974). They suggested the correlation of differenced prices on the grounds that it has the attractive property of interpreting market integration as interdependence of price changes in different markets. Moreover, price change would eliminate common trends that introduce spurious correlation. Besides the problem of spurious correlation, there are other serious problems related to the often non-stationary nature of the price series involved.

Past research, however, has identified various measures of market integration including correlation coefficient (Farruk, 1970, Lele, 1972, Jones, 1972, Blyn, 1973), short and long term tests of integration (Ravallion, 1986) Long-term multipliers and time of adjustment (Boyd and Brossen, 1986, Mendoza and Rosegrant, 1995), Cointegration coefficient (Ardeni, 1989, Goodwin and Schroeder, 1991, Wyeth, 1992, Palaskas and Harris, 1991), causality and centrality tests (Mendoza and Farris, 1992; Mendoza and Rosegrant, 1995). However, a comparison of various measures as well as analysis of the structural factors affecting their measures of market integration has not been given much attention.

The studies of Jones (1972), Gilbert (1969) Thodey (1986), Hays and McCoy, (1977) and Orubu (1991), which adopted correlation and regression coefficient, generally concluded that apart from gari other staple foodstuff markets are poorly integrated and hence inefficient. The major sources of inefficiency as identified by the authors include the poor price information transmission channel, too many intermediaries, high cost of transportation as well as the sources and validity of price data. An important observation is that while markets have characteristics of perfect competition, the price correlation results show that they are not integrated and inefficient. The bivariate correlation coefficient method adopted is however beclouded by the problems of overwhelming seasonal and secular trends, with possibility of autocorrelation from a static model calibrated to non-stationary time series leading to inferential errors (Granger and Newbold, 1974, Harriss, (1979), Blyn, (1973), Delgado, (1986), Ravallion, (1986), Heytens (1986) and Palaskas and Harris (1991). Other approaches were applied to study foodstuff market behaviour (Delgado, 1986 and Oludimu 1982) but they yielded results similar to those of bivariate correlation coefficient method.

Ravallion (1986) proposed an autoregressive lag (ADL) model for testing “short-run” and “Long-run” integration involving the correlation of price series in a rural market with lagged own prices of reference (urban) markets, as well as non-price determinants of demand and supply. The method attempts to measure the extent to which the rural (peripheral) market price is determined by the reference (urban) market price. It is a one-way approach to market integration. It has helped to avoid many of the problems of the correlation coefficient method. Dittoh, (1994) applied the Ravallion model to the study of marketing efficiency in vegetable markets in Nigeria, and obtained results, which showed that the marketing system was generally poorly integrated.

The Ravallion approach has been faulted on the grounds of simultaneous equation bias, requiring the use of instrumental variables, failure to measure the level of integration where the flow between rural and urban areas reverses with the season, problem of co linearity among explanatory variables, which are likely to yield inefficient estimates and hence spurious conclusions and, the problems associated with the use of non-stationary price data. Despite these problems, the Ravallion approach remains the pivotal model for analysis of dynamics in market behaviour and market integration in contemporary market performance research. As a result, a number of extensions of the model have been developed, (Heytens 1986; Faminow and Benson 1990; and Dahlgram and Blank 1992).

The notion of Cointegration has been applied to studies of market integration and spatial market analysis (Taylor and Tonks, 1989, Palaskas and Harris, 1991, Alexander and Whyte, 1994, Dercon, 1995). Barrett (1996) presented a hierarchical classification of markets analysis method based on the nature of the data used. Level I methods used only price data and are most susceptible to specification error. Level II methods combine price and transactions cost data. Level II methods are said to be relatively recent innovations and represent the current frontier. Level III methods, combining price, transactions cost and trade flows data, were predicted to offer greater flexibility and influence. However, the Cointegration test has been said to be neither a necessary nor a sufficient condition for market integration (Barrett, 1996, Barrett et al., 1999 and Li and Barrett, 1999). Baulch’s (1997) parity bounds models (PBM) employs exogenous transaction cost data to estimate the probability (using maximum likelihood estimator) of attaining inter-market arbitrage conditions, it is said to be well suited to situations of trade discontinuities, and complex and time-varying transaction costs (Barrett, 1996, Li and Barrett, 1999). The PBM approach has been adapted by the Li-Barrett method (LBM) (Li and Barrett, 1999) to distinguish between market integration and market equilibrium. This method however is most suited to international trade. The dearth of trade flow data between rural and urban markets in Nigeria makes it impracticable to apply the PBM technique to a study of this nature.

A recent study by Mendoza and Rosegrant (1995) that applied a bivariate autoregressive model developed a simplified version of the Ravallion model to circumvent the problems of simultaneity as well as those of auto-correlation, by differencing the price series once before employing it for analysis. The method will solve the problem of non-stationarity, if and only if, the series are of order one [I(1)]. Okoh (1999) however adopted the model after testing the class of unit roots to ascertain the status of the price data. In her study of the oligopolistic pricing and market integration of cassava and its products in Delta and Edo States of Nigeria, it was found that the time series data were non-stationary or are of order [I(1)].

In order to identify the implications of using the original data or differenced data for the analysis, the two sets of data were used to compute bivariate correlation coefficients. The original data resulted in high coefficients for gari, which corroborate the results of previous studies, (Jones, 1972, Thodey, 1986). The result of the differenced series showed the contrary. This result is more akin to the market situation as revealed by the questionnaire survey. The general conclusion from the study was that cassava markets in the study area were weakly associated.

2.2 Theoretical Frame Work

2.2.1 Concept of market integration

Market integration (MI) can be understood from two aspects. First, it refers to vertical integration and horizontal integration. The former is in fact the industry integration, which reflects the nature of agribusiness, while the latter mainly is spatial market integration. Second, the integration includes spatial market integration, temporal market Integration, integration across price form and integration across product form.

Spatial market integration reflects the effects of price change in one market on another market. Theoretically, under the assumption of full competition, when two regions trade, the product price in the importing region equals to the price in the exporting region plus transportation cost. Therefore, the price change in the export region will induce a price change in the import region in the same direction and of the same degree. If this is the case, the two markets are completely integrated (Wu Laping, 1997).

Spatial market integration includes long-run market integration and short-run market integration. The former refers to such cases in which there exists a long run and stable price relationship between two markets. Even if this long-run relationship “balance” is broken in the short run, eventually the balance will be renewed. Short-run integration shows that the price change in one market in some period will bring “in the next period” (i.e., immediately) the price change in another market. This reflects the sensitivity of the spread of product prices between markets.

Integration across marketing stages reflects the effects of price change in one marketing stage on the price change in next stage. If the prices in different marketing stages meet the condition of “next stage price = this stage price + market charge”, there exists integration between market stages. The integration between wholesale and retail markets is one example of integration across marketing stages (Wu Laping, 1997).

Temporal market integration reflects the effect of present price change on future prices. When prices meet the condition of “future price = present price + storage cost”, it is called temporal market integration (Wu Laping, 1997)

Integration across product form reflects the effect of price change of one product on price change of other related product, which usually refers to the price relationship between a primary product and a processed product. If the condition that “processed product price = primary product price + processing cost” is met, the markets are integrated. The research on the integration of related product markets is very important. Its result can indicate whether the price relations between two products are reasonable and whether these related product markets could coordinate effectively (Wu Laping, 1997). For example, the research on the integration of corn and poultry markets will reflect much more than just the price comparison between them.

This study only analysed the spatial market integration, though the other three types are also very important.

2.2.2 Concept of price transmission

Studies on the transmission of price signals are founded on concepts related to competitive pricing behavior (Fackler and Goodwin, 2002). In spatial terms, the classical paradigm of the law of one price, as well as the predictions on market integration provided by the standard spatial price determination models (Enke, 1951; Samuelson, 1952; Takayama and Judge, 1971) postulate that price transmission is complete with equilibrium price of a commodity sold on competitive foreign and or domestic markets differing only by transfer costs, when converted to common currency. These models predict that changes in supply and demand conditions in one market will affect trade and therefore prices in other markets as equilibrium is restored through spatial arbitrage.

The absence of market integration or of complete pass-through of price changes from one market to another has important implication on economic welfare (Barret, 2001; and Barret and Li, 2002). Incomplete price transmission arising either due to trade or other policies, or due to transaction cost such as poor transportation and communication infrastructure which results in a reduction in the price information available to economic agents and consequently may lead to decision that contribute to inefficient outcomes.

The large body of research on market integration and price transmission, both spatially and vertically, has applied different quantitative techniques and has highlighted several factors that impede the pass through of price signals. Distortions introduced by governments in the form of policies weaken the link between the international and or domestic markets. Agricultural policy instruments such as import tariffs, tariff rate quotas, and export subsidies or taxes, intervention mechanisms as well as exchange rate policies insulate the domestic markets and hinder full transmission of international price signals by affecting the excess demand or supply schedules of domestic commodity markets (Gardner, 1975; Mundlak and Larson, 1992; Quiroz and Soto, 1996; Baffes and Ajwad, 2001; Abdulai, 2000; Sharma, 2002).

Apart from policies, domestic markets can also be partly insulated by large marketing margins that arise due to high transfer cost. Especially in developing countries, poor infrastructure, transport and communication services give rise to large marketing margins due to high costs of delivering the locally produced commodity to the border for export or the imported commodity to the domestic market for consumption. High transfer cost and market margins hinder the transmission of price signals, as they may prohibit arbitrage (Sexton et. al., 1991; Badiane and Shively, 1998).

Non-competitive behavior such as that considered in pricing –to- market models (Dornbush, 1987; Foot and Klempeter, 1989; Krugman, 1986) can hinder market integration. Price – to – market postulate that firms may absorb part of exchange rate movements by altering export prices measured in-home currency in order to retain their market share. Alternatively, Oligopolistic behaviour and collusion among domestic traders may retain price differences between international and domestic prices in levels higher than those determined by transfer costs.

2.2.3 Price transmission notions and components

Given prices for a commodity in two spatially separated markets P1t and P2t, the law of one price and the Enke – Samuelson – Takayama – Judge model postulate that at all points of time, allowing for transfer cost (C), for transporting the commodity from markets 1 to market 2, the relationship between the prices is as follows:

illustration not visible in this excerpt

If a relationship between two prices, such as (1) holds, the markets can be said to be integrated. However, this extreme case may be unlikely to occur, especially in the short run. At the other end of the spectrum, if the joint distribution of two prices were found to be completely independent, then one might feel comfortable saying that there is no market integration and no price transmission. In general, spatial arbitrage is expected to ensure that prices of a commodity will differ by an amount that in at most equal to the transfer cost with the relationship between the prices being identified as the following inequality:

illustration not visible in this excerpt

The spatial arbitrage condition encompasses price relationships that lie between the two extreme cases of the strong form of the law of one price and the absence of market integration. Depending on the market characteristics, or the distortions to which markets are subject, the two price series may behave in a plethora of ways having quite complete relationships with prices adjusting less than completely or slowly rather than instantaneously and according to various dynamic structures are related in a non linear manner. Given the wide range of ways prices may be related, the concept of price transmission can be thought of as being based on three notions or components (Prakash, 1998; Balcombe and Morisson, 2002).

These are:

co–movement and completeness of adjustment which implies that changes in prices in one market are fully transmitted to the other at all points of time. dynamics and speed of adjustment which implies the process by, and rate at which, changes in prices in one market are filtered to the other market or levels; and asymmetry of response, which implies that upwards and downward movements in the price in on market are symmetrically or asymmetrically transmitted to the other.

Both the extent of completeness and speed of the adjustment can be asymmetric.

Within this context, complete price transmission between two spatially separated markets is defined as a situation where a change in one price is completely and instantaneously transmitted to the other price. In addition, this definition implies that if changes are not passed through instantaneously but after sometime, price transmission is incomplete in the short run, but complete in the long run, as implied by the spatial arbitrage condition.

The distinction between short run and long run price transmission is important and the speed by which price adjust to their long run relationship is essential in understanding the extent to which markets are integrated in the short run. Changes in the price at one market may need some time to be transmitted to other markets for various reasons, such as policies, the number of stages in marketing and the corresponding contractual arrangements between economic agents storage and inventory holding, delays caused in transportation or processing or “price – leveling” practices.

2.2.4 Distinguishing the concept of Market Integration (MI), the law of one price (LOP) and market segmentation (MS) by definition;

The issues culminating into this research is revolving around the concepts of market integration, law of one price and market segmentation. The understanding of these concepts is therefore needful for better follow up of discussion of the study. According to Gertrude and Donald, (1997):

Market integration (MI): If trade takes place at all between two or more spatially separated markets, then prices in one market are related or correlated with the price(s) in the other market(s), i.e., a price change in one market is partially or totally reflected in the price(s) in the other market(s) either in the short run and/or in the long run.

Law of one price (LOP): LOP holds between two spatially separated markets if any price changes in one market are perfectly transmitted in the short run and/or long run after adjusting for transaction costs and any other exogenous factors.

Market segmentation (MS): Two or more spatially separated markets are segmented if price changes in one market are not transmitted partially or in total to the price(s) in the other market(s) either in the short run or the long run.

Adherence to the LOP is a sufficient condition for spatial price efficiency, implying that markets are integrated, and completely ruling out arbitrage opportunities. Imperfect transmission of price shocks implies MI but not LOP, i.e., MI is a necessary, but not a sufficient condition for LOP. The perfect transmission of shocks is referred to as “perfect market integration” (PMI). Hence, PMI will necessarily imply LOP and forms the sufficient condition for efficiency between spatial markets (Gertrude and Donald, 1997).

2.2.5 Concept of structure, conduct and performance

One important approach to the study of market performance is the study of market organization or market structure analysis, suggesting that relationships exist between structural characteristics of a market and the competitive behavior of market participants and that their behavior in turn influences the performance of the market (Scarborough and Kydd, 1992; Scott, 1995; Gebremeskel et. al., 1998). Among the major structural characteristics of a market is the degree of concentration, which is the number of market participants and their size distribution; and the relative ease or difficulty for market participants to secure an entry into the market. Market conduct refers to the behavior of firms or the strategy they use with respect to, for example pricing, buying, selling, etc., which may take the form of informal cooperation or collusion.

Typically Structure-Conduct-Performance (SCP) analyses tend to assess market performance largely in terms of:

Whether marketing margins charged by various actors in the marketing system are consistent with cost; and Whether the degree of market concentration is low enough (and the number of firms operating in a market is large enough) to ensure competition, which in turn assumed to drive down costs to their lowest level.

The SCP approach postulate that as market structure deviates away from the paradigm of perfect competition as characterized, the extent of competitiveness of the market will decrease; and consequently a decline in market efficiency will take place (Scarborough and Kydd, 1992; Scott, 1995 Gebremeskel et. al., 1998)

However, there are several shortcomings with these criteria for assessing market performance. First, the criterion that observed marketing margin should be consistent with costs does in no way indicate that the marketing system is performing adequately. Therefore, assessment of market performance based on whether costs approximates marketing margins must be viewed as very static assessments, and fails to incorporate the long-run dynamic issue of how incentives can be structured within the rules of economic exchange to reduce costs at the various stages of the production/marketing system (Jayne, 1997)

The second criteria (establishing competition through number of firms in the market) are also problematic in the presence of scale economies. Therefore, the existence of few traders (high market concentration among grain buyers) would not necessarily point to lack of competition or artificial barriers to entry, nor would a large number of traders each handling very small volumes indicates that per unit marketing costs are being minimized.

Thirdly, the ability to capturing the gains from specialization and commercialization is limited by the size of the market, that the size of the market is in turn influenced by transaction cost. Therefore, market performance should also be assessed based on the range of activities that do not exist in addition to assessing the efficiency of existing exchange arrangements.

Structure, Conduct and Performance Indicators of Market Performance

There is a problem of practically observing whether any market is more or less competitive. The SCP framework provides a number of indicators, but they are only indicators.

[...]

Excerpt out of 96 pages

Details

Title
Spatial Retail Price Integration of Maize Markets in Ogun State
Course
Agric Economics
Grade
A
Author
Year
2007
Pages
96
Catalog Number
V182670
ISBN (eBook)
9783668235946
ISBN (Book)
9783668235953
File size
977 KB
Language
English
Tags
spatial, retail, price, integration, maize, markets, ogun, state
Quote paper
Iruansi Itoandon (Author), 2007, Spatial Retail Price Integration of Maize Markets in Ogun State, Munich, GRIN Verlag, https://www.grin.com/document/182670

Comments

  • No comments yet.
Read the ebook
Title: Spatial Retail Price Integration of Maize Markets in Ogun State



Upload papers

Your term paper / thesis:

- Publication as eBook and book
- High royalties for the sales
- Completely free - with ISBN
- It only takes five minutes
- Every paper finds readers

Publish now - it's free