Chapter 17 Spatial price analysis

Fackler, Paul L.; Goodwin, Barry K.

doi:10.1016/s1574-0072(01)10025-3

Cited by 183 publications

(207 citation statements)

References 90 publications

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“…The literature on agricultural marketing, market integration testing and spatial price analysis pays considerable attention to transport costs and intermarket price differences, commonly known as ''basis'' (Ravallion, 1986;Barrett, 1996;Fackler and Goodwin, 2001). The intuition for this goes back at least to the seminal work on spatial markets equilibrium by Enke (1951), Samuelson (1952) and Takayama and Judge (1971).…”

Section: A Producer Price Risk Decomposition Methodsmentioning

confidence: 99%

Decomposing producer price risk: a policy analysis tool with an application to northern Kenyan livestock markets

Barrett

Luseno

2004

Food Policy

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Section: A Producer Price Risk Decomposition Methodsmentioning

confidence: 99%

Decomposing producer price risk: a policy analysis tool with an application to northern Kenyan livestock markets

Barrett

Luseno

2004

Food Policy

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“…Literature addressing the institutional constraints to market development exist (see for example Fafchamps 2004and Platteau 2000a, 2000b. Moreover there is empirical evidence of commodity price variability across space and seasons in many developing countries, with significant unexploited arbitrage opportunities underscoring the low level of market integration (Abdulai 2007 andFackler andGoodwin, 2001). …”

Section: Introductionmentioning

confidence: 99%

Determinants of Domestic Food Price Differentials: Constraints for Intra-Uganda Trade

Shinyekwa¹,

Ijjo²

2016

JSD

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The paper estimates the determinants of price differentials across 79 districts in Uganda. In the framework of the law of one price, we examine the hypothesis that the spatial price differentials are at least partly influenced by transportation and other transaction costs, infrastructural constraints, productivity and commodity output shocks and the purchasing power of households. The study notes the wide range of price differences across the country, which to a large extent can be attributed to the interaction between remoteness and the quality of physical infrastructure. The effect of income per capita on price differentials is relatively uniform across commodities. The findings point towards the importance of strengthening the capacities of farmers and their productivity as a means to improve their livelihoods and foster more efficient markets with faster supply responses to changes in prices. The findings further emphasize the significance of spatial dimension and infrastructure conditions in Uganda, suggesting that infrastructural development must be a core area to reduce price differences in the country.

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“…Indeed, the answer to the central question how long an initially localised scarcity can be expected to persist depends entirely on how well the region is connected by arbitrage to other regions (Ravallion, 1986). Finally, the extent of market integration also has consequences for designing successful agricultural price stabilisation policies (Fackler and Goodwin, 2001).…”

Section: Introductionmentioning

confidence: 99%

Modelling trends in food market integration: Method and an application to Tanzanian maize markets

Campenhout

2007

Food Policy

105

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Pushed by increasing availability of price data and extensive market liberalisation efforts in many developing countries, research on food market integration has evolved rapidly over the last two decades. Empirical methods to measure market integration diverged in two directions: on the one hand, there is the parity bounds model (PBM) using a switching regressions technique, while on the other hand the use of threshold autoregressive (TAR) models has been proposed. This article provides a discussion on the two methods and argues that TAR models are better able to capture the dynamics of the arbitrage process underlying interconnected markets. Furthermore, we extend the standard TAR model to include a time trend in both the threshold and the adjustment parameter. Using weekly maize price data on seven selected markets in Tanzania, we illustrate how both transaction cost and the speed of adjustment have changed during the nineties.

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Chapter 17 Spatial price analysis

Cited by 183 publications

References 90 publications

Decomposing producer price risk: a policy analysis tool with an application to northern Kenyan livestock markets

Decomposing producer price risk: a policy analysis tool with an application to northern Kenyan livestock markets

Determinants of Domestic Food Price Differentials: Constraints for Intra-Uganda Trade

Modelling trends in food market integration: Method and an application to Tanzanian maize markets

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