This paper explores the determinants of technical efficiency, and the relationship between farm size and efficiency, in the Center‐West of Brazil. This is the region where agricultural production and total factor productivity have grown the fastest since 1970. It is also a region characterised by unusually large farms. Technical efficiency is studied with Data Envelopment Analysis and county level data disaggregated by farm size and type of land tenure. The efficiency measure is regressed on a set of explanatory variables which includes farm size, type of land tenure, composition of output, access to institutions and indicators of technology and input usage. The relationship between farm size and efficiency is found to be non‐linear, with efficiency first falling and then rising with size. Type of land tenure, access to institutions and markets, and modern inputs are found to be important determinants of the differences in efficiency across farms.

This paper explores the determinants of technical efficiency, and the relationship between farm size and efficiency, in the Center-West of Brazil. This is the region where agricultural production and total factor productivity have grown the fastest since 1970. It is also a region characterised by unusually large farms. Technical efficiency is studied with Data Envelopment Analysis and county level data disaggregated by farm size and type of land tenure. The efficiency measure is regressed on a set of explanatory variables which includes farm size, type of land tenure, composition of output, access to institutions and indicators of technology and input usage. The relationship between farm size and efficiency is found to be non-linear, with efficiency first falling and then rising with size. Type of land tenure, access to institutions and markets, and modern inputs are found to be important determinants of the differences in efficiency across farms. 0 2004 Elsevier B.V. All rights reserved. JEL clmsifcation: Q 100. 0 3 0 0

The extent, pattern, and degree of integration are analyzed in a multivariate system with cointegrating restrictions. The extent of the market is found by identifying locations that are linked by trade and where prices share identical long-run information (permanent component). The pattern of integration characterizes interdependence and is analyzed by estimating a vector error correction model. The degree of integration is calculated with persistence profiles of the long run relations. We demonstrate that bivariate models are inadequate for capturing the spatial dynamics of price adjustment. The methodology is applied to the Brazilian rice market and policy implications are discussed. Copyright 2001, Oxford University Press.

The relationship between farm size and productivity is a recurrent topic in development economics, almost as old as the discipline itself. This paper emphasizes the importance of choice of productivity measures in the inverse relationship literature. First, we seek to clarify the common measures, their relationships, and their advantages and limitations in empirical work. Second, we argue that much of the existing literature inappropriately uses partial measures such as land productivity. Third, we discuss the dynamic nature of the farm size -productivity relationship and show that the identification of these dynamics will in part depend upon the choice of productivity measure. Lastly, using a pseudo-panel of Brazilian farms that are aggregated at the municipality and farm size levels over the period 1985-2006, we provide new empirical evidence on the inverse relationship between farm size and both land productivity and total factor productivity. The empirical exercise highlights the importance of choice of measure when testing the inverse relationship. The inverse relationship between size and land productivity is alive and well. The relationship between total factor productivity and size, in contrast, has evolved with modernization during this period, becoming increasingly U-shaped or even positive.

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Bayesian paradigm, Conditional autoregressive priors, Monte Carlo Markov chain, Stochastic frontier models, Spatial econometrics, C01, C11,

This article analyzes the impact of policy reforms and changing macroeconomic conditions on the Brazilian agricultural sector. It stresses four issues: events outside of agriculture were central to the performance of the sector and to the timing and sequence of policy reform; reform involved far more than trade liberalization; the impact of reform on input markets and productivity was key for understanding the period; and policy reform had a highly differentiated impact on the sector. As a result of the reforms, agriculture became the most dynamic sector of the Brazilian economy in the 1990s. Policies still in need of reform are identified. (JEL O13, Q18)

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