Price Fluctuation and Market Integration of Selected Cereal in North-Eastern Nigeria, 2001-2010

ABSTRACT

Prices contain information crucial to maximizing the returns to production and marketing investments. At planting time, a farmer's planting decision depends on expected profits, which invariably hinge on the anticipated prices of the crop or mix of crops that would prevail in the market at the time of sale and on the farmer's interpretation of those prices. A trader, in search of profitable arbitrage, reads and translates price signals in deciding on what crops to buy, where to buy, and when to sell. Apart from guiding production and marketing decisions, prices govern the optimal allocation of resources among competing uses. The accuracy, reliability, and promptness of market information are therefore critical in attaining pricing efficiency. Broadly, the study attempted to analyze the price fluctuation and market integration of selected cereal grains in North-eastern Nigeria. The specific objectives of the study were to: (i) estimate the extent of the various components of price; (ii) derive the probability distribution of cereal grain price in the long-run; (iii) determine the existence and level of inter-market price dependency; (iv) examine the speed of price adjustment to long-run equilibrium and (v) examine the Granger Causality among rural and urban cereal grain markets. The study was conducted in North-eastern Nigeria. Purposive sampling technique was used to select two states, of Adamawa and Taraba, from the six states that made up the North-east geopolitical zone. Only secondary data were used in the study. Secondary data on monthly bases for the prices of 100kg of three cereal grains, maize, rice and sorghum in both rural and urban markets in the study area were obtained from Adamawa and Taraba States Agricultural Development Program offices for a period of 10 years (2001-2010). Data were analyzed using descriptive statistics such as price decomposition technique, and inferential statistics such as Markov Chain, Vector Autoregressive and Error Correction Models. The results revealed that, the trend component showed an upward movement for all the three commodities. The seasonal variation had indexes ranged from 198.15 to 52.61, 142.83 to 61.88, and 141.44 to 66.25 for maize, rice and sorghum, respectively. The random and cyclical variations had negligible and insignificant indices with the former having 0.01 all through and the later ranging from 0.93 to 1.26. Probability distribution matrices of the three cereal grains were 0.18, 0.48 and 0.34 for maize, 0.27, 0.68 and 0.05 for rice and 0.48, 0.25 and 0.27 for sorghum. The Augmented Dickey-Fuller unit roots test indicated I(0), I(1) and I(1) for maize, rice and sorghum, respectively. Null hypothesis of β = 1 was rejected against β = 0. Trace statistics for rural and urban markets were not significant ( Rural and urban prices of maize responded to shocks within and between each market. The speed with which the system adjusted to shocks and restored equilibrium between the short and the long-run were -0.170725 and -0.29517 for urban and 0.592237 and 0.38034 for rural prices of rice and sorghum, respectively. Granger Causality showed that a bi-directional flow of price signals existed between rural and urban prices of maize, while rural prices of rice and sorghum did not GrangerCause urban prices of rice and sorghum. Also, urban prices of both rice and sorghum did not Granger-cause rural prices of both rice and sorghum. Findings of the study showed an imperfect market integration for North-eastern Nigeria cereal grain markets, this indicate that there may be substantial benefits in developing better infrastructure facilities to effectively link production centers to market centers and in improving market knowledge by providing more relevant, accurate, and timely public market information.

TABLE OF CONTENTS

Contents Pages

Title i

Certification ii

Dedication iii

Acknowledgements iv

Table of Contents v

List of Tables ix

List of Figures x

Abstract xi

CHAPTER ONE: INTRODUCTION

1.0 Background of the Study 1

1.2 Problem Statement 7

1.3 Objectives of the Study 11

1.4 Research Hypotheses 11

1.5 Justification of the Study 11

1.6 Limitations of the Study 13

CHAPTER TWO: LITERATURE REVIEW

2.1 Spatial Competition 14

2.1.1 Estimating Spatial Price Relationship 17

2.2 Theoretical Framework 20

2.3 Time Series 21

2.3.1 Stationary and Nonstationary Time Series 22

2.3.2 Stationarity 22

2.3.3 Non-stationarity 23

2.4 Unit Roots 24

2.5 Conceptual Framework 25

2.5.1 Measure of Integration 26

2.6 Markov Chain 30

2.6.1 Markov Processes and Random Walk Hypotheses 31

2.7 Analytical Framework 33

2.7.1 Studies on Market Integration around the World 33

2.7.2 Empirical Evidence from Market Integration in Nigeria 45

2.8 Analysis of Time Series 47

2.9 Markov Processes 54

2.9.1 Markov Chains 55

2.10 Price Forecasting Models 59

2.11 Estimation of Transitional and Initial Probability Matrix 62

CHAPTER THREE: METHODOLOGY

3.1 The Study Area 66

3.2 Sampling Procedure 67

3.3 Data Collection 67

3.4 Data Analysis 67

3.4.1 Components of Time Series 68

3.4.2 Isolation of Time Series Components 69

3.4.3 Transition Probability 72

3.4.4 Using Markov Chain 72

3.4.5 Limitations of Markov Chain 72

3.4.6 Error Correction of Cointegration Equation or System 76

CHAPTER FOUR: RESULTS AND DISCUSSION

4.1 Components of Time Series 87

4.2 Probability Distribution of Cereal Price in the Long-run 87

4.2.1 Maize 87

4.2.1.1 Interpretation of Maize Transition Matrix 88

4.2.2 Rice 89

4.2.3 Sorghum 90

4.3 Existence and Level of Inter-Market Price Dependency 92

4.3.1 Unit roots test 92

4.3.2 Impulse Response Function 92

4.3.3 Johansen Cointegration test 92

4.4 Speed of Price Adjustment to Long-run Equilibrium 92

4.4.1 Rice 92

4.4.2 Sorghum 102

4.5 Granger-Causality among Rural and Urban Markets 105

4.5.1 Maize 105

4.5.2 Rice 105

4.5.3 Sorghum 106

CHAPTER FIVE: SUMMARY, CONCLUSION AND

RECOMMENDATIONS

5.1 Summary 107

5.2 Conclusion 107

5.3 Recommendations 109

5.4 Major Contributions of the Study to knowledge 110

5.5 Suggestions for Further Studies 110

References 111

Appendix 128