Exploring the Dynamics of USA-Brazil Commodity Trade
People are always worried that biofuels, which are made from agricultural products, will hurt food supply, which will raise food prices and lead to hunger around the world. This argument in particular assumes that the price of farm goods will go up because biofuel prices are going up. A common theme in recent active research in well-known academic journals about biofuels (Hochman et al., 2014; Kristoufek et al., 2014), agriculture (Myers et al., 2014), and energy (Bastianin et al., 2014a) is the need to rigorously explain this intuitive argument. Using a new way of looking at things, this study looks at how prices have changed recently in the most developed biofuels markets, adding to the conversation. If a country's net exports are going down, it can either devalue its currency or let it devalue. However, the trade balance may keep going down because of adjustment lags in things like production, supply, recognition, and so on. Things may get better later.
Only two studies have tried to figure out the S-curve for developing countries, but Brazil has used it before. Senhadji (1998) uses aggregate trade data to test the curve for 36 developing countries, but he doesn't include Brazil. Parikh and Shibata (2004), on the other hand, test the curve for 64 developing countries and include Brazil. They find weak support for the S-curve there. These studies use the same method as Backus et al. (1994), who test the curve for 11 OECD countries by adding up all the trade flows between each country and the rest of the world. Bahmani-Oskooee and Ratha (2007a) separate trade flows by trading partners to get rid of aggregation bias. They also give the S-surve in trade between the U.S. and each of its big trading partners more support. Brazil is not listed as a partner, which is a shame. We only look at trade between the U.S. and Brazil in this study and try to find stronger support for the S-curve using trade flows between the two countries. To make our results even stronger, we break down the flows of trade between the two countries and estimate the curve for each of the 95 businesses that trade between them. In 52 of these cases, we find support for the S-curve. In Section 2, we talk about how the S-curve was made to show how we came to our conclusions.
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