Driving Forces for Changes in Land Use

Brons, J.E.; Ruben, Ruerd; Toure, Mohammed; Ouedraogo, B.S.

doi:10.1007/1-4020-2158-5_9

Cited by 3 publications

(7 citation statements)

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“…This result supports evidence that maize, sorghum, and millet are competing crops to cotton (Mittal and Reimer, 2008). Likewise, Brons et al (2004) reported strong negative cross‐price elasticity between cotton and sorghum on cotton yields in Mali. In contrast, Vitale et al (2009) found a weak positive cross‐price of sorghum and cotton on cotton acreage, which was, however, cancelled out by the negative millet‐cotton cross‐price estimates.…”

Section: Resultsmentioning

confidence: 97%

“…In general, fewer estimated price coefficients remain significant when their absolute values are included. Similarly, in their estimated supply responses for cotton and cereals (maize, sorghum, and millet) in Mali and Burkina Faso, Brons et al (2004) found that the coefficients of crops’ own prices were not statistically significant. This finding supports the argument that cotton farming decisions are mostly based on relative prices rather than on farm‐gate cotton prices alone, and thus, have important implications in terms of pricing policy.…”

Section: Resultsmentioning

confidence: 98%

“…Estimated adjustment coefficients from previous cotton supply response studies vary considerably, ranging from less than 0.10 in China (Yu et al, 2011) to over 0.80 in Australia (Agbola and Evans, 2012). Based on national level data, Brons et al (2004) estimated an adjustment coefficient of 0.69 in Mali and of 0.63 in Burkina Faso for the time period 1965–1990.…”

Section: Resultsmentioning

confidence: 99%

“…Nerlove's seminal work (1956), based on the hypotheses that farmers’ production decisions are a function of their price expectations and partial supply adjustment, has been extensively used to investigate the responsiveness of cotton supply to changes in prices in developing countries. Cotton supply responses, based on a Nerlovian model, have been previously estimated using data at the farm (Douya, 2008; Vitale et al, 2009), regional (Yu et al, 2011), and national (Brons et al, 2004; Mittal and Reimer, 2008; Onal, 2012) levels. Regional data sets have also been used to analyze acreage response of other commodities, such as sugarcane and soybean (Hausman, 2011) and wheat (Albayrak, 1998).…”

Section: Theoretical Modelmentioning

confidence: 99%

“…This variable is lagged by one period in order to take into account the lapse of time before return to extension services become tangible (Poulton and Tschirley, 2009). Land‐use and resource allocations are affected by agro‐climatic factors influencing regional and farm‐household options in terms of crop choice and input use (Brons et al, 2004, p. 83). As such, it is assumed that farmers make land allocation decisions based, in part, on their expectation concerning weather conditions.…”

Section: Theoretical Modelmentioning

confidence: 99%

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Prices, institutions, and determinants of supply in the Malian cotton sector

Thériault

Serra

Sterns

2013

Agricultural Economics

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Cotton, both a source of livelihood for millions of poor rural households and a major source of export revenues, is a vital commodity for the economic and social development of Mali. Inefficiencies in the Malian cotton system at the ginnery and producers' cooperative levels (e.g., late payment to farmers and poorly functioning credit schemes) have recently led to an important decline in supply, threatening the sustainability of the sector. Using regional data from 1998/1999 to 2008/2009, this study aims to quantitatively assess the contribution of key determinants, such as cotton prices and timely payment, toward the downward trend in cotton area. A dynamic supply model, based on adaptive expectations and partial adjustment, is employed to estimate the effects of prices and institutional factors, such as credit recovery rates and date of payment to farmers, on the Malian cotton supply. Results show that supply responds significantly to cotton prices relative to cereal and fertilizer prices. Date of payment varies across agricultural cycles and late payment negatively influences land devoted to cotton. Low credit repayment rates create disincentives to grow cotton. Therefore, the revitalization of the Malian cotton sector depends upon getting both prices and institutions right. JEL classifications: O17, Q11, Q13, Q18

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Section: Resultsmentioning

confidence: 97%

Section: Resultsmentioning

confidence: 98%

Section: Resultsmentioning

confidence: 99%

Section: Theoretical Modelmentioning

confidence: 99%

Section: Theoretical Modelmentioning

confidence: 99%

See 3 more Smart Citations

Prices, institutions, and determinants of supply in the Malian cotton sector

Thériault

Serra

Sterns

2013

Agricultural Economics

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Evaluating the impact of an agricultural land‐use change adaptation strategy on household crop production in semi‐arid Ghana

Badmos

Villamor

Agodzo

et al. 2020

Singap J Trop Geogr

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In this study, the Land Use Dynamic Simulator model was applied to investigate the impact of farm credit as an adaptation strategy to cope with effects of climate variability on agricultural land‐use change and crop production in the Vea watershed in Ghana. The authors identified the determinants of crop choices within the landscape (e.g., farm household and biophysical characteristics of farm plot). The crop choice sub‐model was then linked to the crop yield sub‐model to determine the yields of selected crops. In adapting to the impacts of climate variability, the maize credit adoption sub‐model under the maize cultivation credit scenario was integrated into decision‐making. This was simulated for a 20‐year period, and compared with the business‐as‐usual scenario. Under the simulated maize credit scenario, maize adopters increased from about 20 per cent to about 50 per cent and the area allocated for maize cultivation significantly increased by about 266 per cent. Consequently, the average annual aggregated household crop yield increased by 6.3 per cent higher than in the business‐as‐usual scenario. This simulation study shows that access to maize credit can significantly influence agricultural land‐use change and food availability in the study area. However, although access to farm credit may translate into food availability, the sustainability of this strategy is questionable.

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Food crop supply in sub-Saharan Africa and climate change

Blanc¹

2013

J. Dev. Agric. Econ.

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This study estimates the impact of climate change on supply for the four most common crops (millet, maize, sorghum and cassava) in sub-Saharan Africa (SSA). The analysis relates crop supply, measured as cropped area, to weather, climate and prices. Crop supply functions are estimated using an error correction model (ECM) built on panel data. Crop supply through 2100 is predicted by combining estimates from the panel data analysis with climate change predictions from 20 general circulation models (GCMs). Results indicate climate change impacts on crop supplies ranging from-20 to +133% compared to a scenario of no climate change.

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Driving Forces for Changes in Land Use

Cited by 3 publications

References 0 publications

Prices, institutions, and determinants of supply in the Malian cotton sector

Prices, institutions, and determinants of supply in the Malian cotton sector

Evaluating the impact of an agricultural land‐use change adaptation strategy on household crop production in semi‐arid Ghana

Food crop supply in sub-Saharan Africa and climate change

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