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Nick Vink - One of the best experts on this subject based on the ideXlab platform.
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Margins of Fair Trade Wine along the Supply Chain: Evidence from South African Wine in the U.S. Market
Journal of Wine Economics, 2019Co-Authors: Robin M. Back, Xinyang Liu, Britta Niklas, Karl Storchmann, Nick VinkAbstract:In this paper, we analyze profit margins and markups of Fair Trade (FT) wines sold in the United States. We are particularly interested in whether and to what extent the FT cost impulse in production is passed along to the supply chain. We draw on a limited sample of about 470 South African wines sold in Connecticut and New Jersey in the fall of 2016; about 90 of them are certified FT. For these wines we have Free on Board export prices, wholesale prices, and retail prices, which allows us to compute wholesale and retail margins and analyze the FT treatment effect. We run OLS, 2SLS, and propensity score matching models and find evidence of asymmetrical pricing behavior. While wholesalers seem to fully pass-through the FT cost effect, retailers appear to amplify the cost effect. As a result, at the retail level, FT wines yield significantly higher margins than their non-FT counterparts. (JEL Classifications: L11, L31, L43, L81, Q17)
J.m. West - One of the best experts on this subject based on the ideXlab platform.
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Efficient Generation Portfolio Construction Using Time-Varying Correlations
Natural Resources Research, 2014Co-Authors: J.m. WestAbstract:We constructed a procurement portfolio for the Indian power sector using two variants of the dynamic conditional correlation GARCH model to derive time-varying correlations between major coal indices. We used prices and qualities of observed cargos to adjust indices for quality gaps as well as for freight costs and power plant efficiency factors. Using the relative homogeneity of the energy content of imports from Australia, South Africa, and Indonesia, we found that the regional seaborne market is highly correlated during normal economic conditions, while suffering brief departures in correlation during demand and supply shocks. Our results show that the buying behavior of power producers is aligned with the mean-variance efficient portfolio of delivered prices using time-varying correlation estimates, but not Free-on-Board coal index prices. This study challenges the notion that thermal coal importers only source material with a freight price advantage and highlights the importance of coal quality gaps in power production.
Prakash L. Abad - One of the best experts on this subject based on the ideXlab platform.
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Buyer’s response to a temporary price reduction incorporating freight costs
European Journal of Operational Research, 2007Co-Authors: Prakash L. AbadAbstract:Abstract In this paper, we characterize the buyer’s response to a temporary price reduction. Although there have been many studies that have considered the above problem, most of those studies assume that the buyer orders FOB (Free on Board) destination and that the freight charges are included in the supplier’s unit price. Our model thus becomes applicable for a buyer whose strategy is to include transportation costs in their purchase decisions. The buyer may want direct control on his inbound logistics costs. The company may have outsourced its logistics function and as a result is charged for freight as invoiced by the public motor carrier. In some cases, the supplier may only allow for orders that are FOB origin. Our model allows for less-than-truckload as well as truckload rates. Freight cost for a LTL shipment is modeled using tariffs set by public carriers in practice. These tariffs generally involve 6–7 breakpoints in terms of the weight of the shipment. Another complication in practice is that the shipper/buyer has an option to over-declare the weight of the shipment.
S.h. Nieuwoudt - One of the best experts on this subject based on the ideXlab platform.
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Influences of the Free Trade Agreement between South African and the European Union on the South African fresh orange industry
South African Journal of Economic and Management Sciences, 2000Co-Authors: S.h. NieuwoudtAbstract:This paper evaluates the effects of the Free Trade Agreement (FT A) between South Africa and the European Union (EU) on the South African orange industry. Oranges account for ten percent of South African agricultural exports. The aggregate trade simulation model used here is designed on the programme STELLA, and consists of regional production models, a local market model, an export model and an exchange rate model. Results indicate that the FT A is expected to have small positive effects on both South African producers and consumers. This is caused by increasing real Free-on-Board prices and decreasing real local prices of oranges. Total area under oranges will increase more with the FT A, which thus results in a larger orange production too.
Robin M. Back - One of the best experts on this subject based on the ideXlab platform.
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Margins of Fair Trade Wine along the Supply Chain: Evidence from South African Wine in the U.S. Market
Journal of Wine Economics, 2019Co-Authors: Robin M. Back, Xinyang Liu, Britta Niklas, Karl Storchmann, Nick VinkAbstract:In this paper, we analyze profit margins and markups of Fair Trade (FT) wines sold in the United States. We are particularly interested in whether and to what extent the FT cost impulse in production is passed along to the supply chain. We draw on a limited sample of about 470 South African wines sold in Connecticut and New Jersey in the fall of 2016; about 90 of them are certified FT. For these wines we have Free on Board export prices, wholesale prices, and retail prices, which allows us to compute wholesale and retail margins and analyze the FT treatment effect. We run OLS, 2SLS, and propensity score matching models and find evidence of asymmetrical pricing behavior. While wholesalers seem to fully pass-through the FT cost effect, retailers appear to amplify the cost effect. As a result, at the retail level, FT wines yield significantly higher margins than their non-FT counterparts. (JEL Classifications: L11, L31, L43, L81, Q17)
