Calibrating spatial models of trade

Paris, Quirino; Drogué, Sophie; Anania, Giovanni

doi:10.1016/j.econmod.2011.07.008

Cited by 30 publications

(15 citation statements)

References 9 publications

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“…For the present study, when the variables production, consumption and prices were evaluated, the maximum difference found between the estimated and observed values is 9%. According to Paris, Drogué and Anania, (2011), there are several reasons why the results may not be identical to those observed. These include: the existence of unobservable costs, the occurrence of measurement errors when estimating demand and supply functions and differences in terms of marketed products.…”

Section: Base Scenario and Model Calibrationmentioning

confidence: 89%

The Impacts of Soy-Based Biodiesel on the Main Soy Producers in the International Market

Alvim

Fochezatto

2020

JAS

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This study analyzes the impacts of soy-based biodiesel consumption on the main soybean-producing countries. To achieve this goal, a partial equilibrium model formulated as a Mixed Complementarity Problem (PCM) is used, which allows the inclusion of trade barriers and the construction of alternative scenarios. Four scenarios are analyzed. The first simulates a demand shock for soybean meal and soybean oil, considering the observed growth in demand over the last ten years. The second evaluates the effects of an increase in the demand for meal, oil and biodiesel. The third considers the elimination of the demand for soy-based biodiesel. The last scenario assesses the effects of the elimination of tariffs and subsidies on the grain and food markets. In general terms, the results show that: in the second scenario, Brazil is the only exporting country that shows a greater increase in consumption than in production, reflecting the country's smaller share in the world soybean trade; in the fourth scenario the gains are relatively smaller than the potential gains in the first scenario; in the third scenario, soybean prices are about 8% higher because of the use of soybeans for biodiesel production, demonstrating the relevance of mandatory policies in this market.

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Section: Base Scenario and Model Calibrationmentioning

confidence: 89%

The Impacts of Soy-Based Biodiesel on the Main Soy Producers in the International Market

Alvim

Fochezatto

2020

JAS

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“…Positive mathematical programming is now the preferred approach for calibrating farm management models. PMP was first developed by Howitt (1995) to address land-use allocation problems in agriculture (e.g., Röhm and Dabbert 2003), but has increasingly been adapted for use in trade modeling and other resource management settings (Weintraub et al 2007;Paris et al 2011;Heckelei et al 2012;Mérel and Howitt 2014). PMP can be used to estimate crop-specific marginal cost functions and, thereby, replicate farmers" observed crop allocation decisions (Mérel and Bucaram 2010;Mérel et al 2011).…”

Section: Calibrating Agricultural Business Risk Management Models: Bamentioning

confidence: 99%

Calibration of agricultural risk programming models using positive mathematical programming

Kooten

Duan

2020

Aus J Agri & Res Econ

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Beginning in the 1960s, agricultural economists used mathematical programming methods to examine producers' responses to policy changes. Today, positive mathematical programming (PMP) employs observed average costs and crop allocations to calibrate a nonlinear cost function, thereby modifying a linear objective function to a nonlinear one to replicate observed allocations. The standard PMP approach takes into account producers' risk aversion, which is not a very satisfying outcome because it intricately entangles the cost parameters and the producer's attitudes -biophysical aspects of production and human behavior are intertwined so that one cannot study the impact of policy on one in the absence of the other. Several approaches that calibrate both the risk coefficient and cost function parameters have been proposed. In this paper, we discuss two methods mentioned in literature -one based on constant absolute risk aversion (exponential utility function) and the other on decreasing absolute risk aversion (logarithmic utility function). We compare these methods to an approach that employs maximum entropy method. Then we use historical data from a region in Alberta's southern grain belt to compare the different outcomes to which the three approaches lead. We find that the latter approach is robust and easier to employ.Abstract: Beginning in the 1960s, agricultural economists used mathematical programming (MP) methods to examine producer responses to policy changes. Today, positive mathematical programming (PMP) employs observed average costs and crop allocations to calibrate the parameters of an assumed nonlinear cost function, thereby modifying a linear objective function to a nonlinear one to replicate observed crop allocations exactly. The standard PMP approach takes into account producers" risk aversion, which is not a very satisfying outcome because it intricately entangles the cost parameters and the decision maker"s attitudesbiophysical aspects of agricultural production and human behavior are intertwined so that one cannot study the impact of policy on one in the absence of the other. Several approaches that calibrate both the risk coefficient and cost function parameters have been proposed by different researchers. In this paper, we discuss two methods mentioned in literatureone based on assumed constant absolute risk aversion (and exponential utility function) and the other on decreasing absolute risk aversion (logarithmic utility function). We compare these methods to a more standard approach that employs maximum entropy (ME) method. Then we use crop insurance and historical data from a region in Alberta"s southern grain belt to compare the different outcomes to which the three approaches lead. We find that the latter approach is robust and easier to employ.

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“…ocorrem nas transações comerciais de forma agregada e servem para fazer a calibração do modelo (PARIS et al, 2011). O objetivo da etapa de calibração é corrigir possíveis distorções ocorridas entre os dados observados e estimados.…”

Section: Calibração Do Modelo E Custos Das Transações Comerciaisunclassified

Mercado Internacional Da Soja: Modelando Os Efeitos Dos Custos Das Transações E Das Barreiras Comerciais

Caetani

Alvim

2020

RAE

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Este estudo analisa os impactos dos custos das transações e das barreiras comerciais no mercado internacional da soja. Para atingir tal objetivo, utiliza-se um modelo de equilíbrio parcial formulado como um Problema de Complementaridade Mista (PCM) o qual permite a construção de cenários alternativos. São definidos três cenários: no primeiro eliminam-se os custos das transações comerciais; no segundo, retiram-se as barreiras tarifárias e os subsídios; e no terceiro é simulado um choque de demanda de 20%. Os resultados mostram que a eliminação dos custos das transações comerciais resulta em um aumento na produção de soja no Brasil, na Argentina e na China e um maior consumo nos Estados Unidos e na UE. No cenário de livre comércio observa-se que as mudanças em termos de produção e consumo são reduzidas, o que reflete as características das políticas adotadas pelos principais países produtores e consumidores. A simulação do choque de demanda, definido com base nas expectativas de incremento no consumo de farelo, óleo e biodiesel, mostra que o Brasil é o único país exportador que apresenta um maior incremento no consumo do que na produção, refletindo em uma menor participação no comércio mundial de soja.

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Calibrating spatial models of trade

Cited by 30 publications

References 9 publications

The Impacts of Soy-Based Biodiesel on the Main Soy Producers in the International Market

The Impacts of Soy-Based Biodiesel on the Main Soy Producers in the International Market

Calibration of agricultural risk programming models using positive mathematical programming

Mercado Internacional Da Soja: Modelando Os Efeitos Dos Custos Das Transações E Das Barreiras Comerciais

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