Maize is the staple food and principal cash crop in Mozambique. Production is dominated by small-holders who sell their surpluses to generate income. Southern Mozambique is a maize deficit region while the North is in surplus, therefore trade between these two areas has implications for food security in the country and is expected to accelerate economic development. This study attempts to measure the extent of market integration between major maize markets in Mozambique. }The study is organised into six chapters. Chapter One presents findings of the investigation into the dynamics and operation of informal maize markets in Mozambique. Chapter Two presents a brief overview of the methods used in the analysis of market integration and gives a review of international studies and studies specific to Mozambique on market integration. Chapter Three reviews agricultural policies in Mozambique and provides an overview of the maize markets in Mozambique. The methodology applied in the study in discussed in Chapter Four while Chapter Five presents a discussion of results from the econometric analysis. In conclusion, Chapter six provides a summary of the results of the market survey and on the basis of the econometric analysis forwards recommendations.

The issue of market integration lies at the heart of many contemporary debates concerning market liberalization, price policy, and government agency reforms in developing country food markets, Mozambique being one of the poorest. Without spatial integration of markets, price signals will not be transmitted from deficit to surplus areas, prices will be more volatile, agricultural producers will fail to specialize according to long-term comparative advantage, and the gains from trade will not be realized. The objective of this article is to indicate the extent of market integration between major Mozambican maize markets. Recognizing the statistical dangers and inaccuracies of using measures of price correlation to test for market integration, a new methodology for testing the state of food market integration is employed in this study, namely the parity bounds model, (PBM) as developed by Baulch (1997). This method provides a more reliable procedure for testing violations of spatial arbitrage conditions than conventional methods, because it compares time series of observed price differentials with transfer costs and explicitly recognizes that spatial arbitrage conditions are represented by inequality constraints. The results point to a failure of spatial arbitrage conditions between the Maputo and Chimoio markets about 23% of the time over the period.

This report presents the data from a midline data collection effort as part of the impact evaluation of Phase II of the Innovation for Agribusiness (INOVAGRO II) intervention in northern Mozambique. INOVAGRO II is a development program intended to decrease rural poverty by improving the connectedness of farmers to market systems. The midline data were collected during the intervention phase, in two districts in Zambézia province - Alto Molócue and Molumbo - during the months of late October to December of 2017. The questionnaire focused on agricultural production and market access for all crops, and particularly for the INOVAGRO value chain crops - soybean, pigeon pea, and maize. The purpose of the report is to describe the data, focusing on key variables.

This report presents the data from a baseline data collection effort as part of the impact evaluation of Phase II of the Innovation for Agribusiness (INOVAGRO II) intervention in northern Mozambique. INOVAGRO II is a development program intended to decrease rural poverty by improving the connectedness of farmers to market systems. The baseline data were collected before the intervention began in two districts in Zambezia province – Alto Molócue and Molumbo – during the months of August and September 2015. The questionnaire focused on agricultural production and market access, in particular on the INOVAGRO value chain crops – soybean, pigeon pea, and maize. The purpose of the report is to describe the data, focusing on key variables.