THE USE OF CLIMATE FORECASTS IN AGRICULTURE: EXPERIENCE IN THE AMERICAS

Resource /Energy Economics and Policy,

CHINA'S AGRICULTURAL WATER SCARCITY : EFFECTS ON INTERNATIONAL MARKETS

Water shortages in important grain-producing regions of China may significantly affect China's agricultural production potential and international markets. This paper provides an overview of how water scarcity could affect China's agricultural production and trade. The paper identifies the areas where available water resources are most overexploited and the crops most vulnerable to reductions in irrigation. We present preliminary results from modeling a decline in irrigated land in water scarce areas in China and the effect this would have on China's production and trade. Wheat and cotton are most vulnerable to a decrease in irrigated area in water scarce regions, and production for these crops could fall by 7-10 percent under a severe cutback in irrigation. The effect this will have on international markets will depend largely on the openness of China's border to imports. In addition, we describe recent conservation policies and how these may affect crop production in China.Resource /Energy Economics and Policy,

Interactions between Resource Scarcity and Trade Policy: The Potential Effects of Water Scarcity on China’s Agricultural Economy under the Current TRQ Regime

International Relations/Trade, Resource /Energy Economics and Policy,

Testing the significance of calendar effects

This paper studies tests of calendar effects in equity returns. It is necessary to control for all possible calendar effects to avoid spurious results. The authors contribute to the calendar effects literature and its significance with a test for calendar-specific anomalies that conditions on the nuisance of possible calendar effects. Thus, their approach to test for calendar effects produces robust data-mining results. Unfortunately, attempts to control for a large number of possible calendar effects have the downside of diminishing the power of the test, making it more difficult to detect actual anomalies. The authors show that our test achieves good power properties because it exploits the correlation structure of (excess) returns specific to the calendar effect being studied. We implement the test with bootstrap methods and apply it to stock indices from Denmark, France, Germany, Hong Kong, Italy, Japan, Norway, Sweden, the United Kingdom, and the United States. Bootstrap p-values reveal that calendar effects are significant for returns in most of these equity markets, but end-of-the-year effects are predominant. It also appears that, beginning in the late 1980s, calendar effects have diminished except in small-cap stock indices.

Assessing the Impact of Climate Change on China's Grain Sector and International Trade

This study analyzes the potential impact of climate change on China's corn, wheat, and rice, domestic agricultural markets, and the international markets out to the year 2050. The study provides a brief background and reviews research literature of climate change effects on China's crop yields. The paper presents the potential impact of climate change on China's yields and attempts to quantify the domestic and global market impacts. The analysis has four scenarios, which assumes two future levels of greenhouse gas emissions with the effects of CO2 fertilization and no CO2 fertilization. A 27-country commodity partial equilibrium simulation mathematical programming model (PEATSim) is used for this analysis. Results indicate under CO2 fertilization, which increases yields, China's grain imports may decrease leading to a decrease in international prices. Under no CO2 fertilization, yields decrease, China's grain imports may increase leading to increased international prices.China, trade, climate change, GHG, CO2 fertilization, rice, wheat, corn, dynamic partial equilibrium simulation mathematical model., Environmental Economics and Policy, International Relations/Trade,

Decomposing Trade Flows: the Case of China in Global Markets

Agribusiness,

Model confidence sets for forecasting models

The paper introduces the model confidence set (MCS) and applies it to the selection of forecasting models. An MCS is a set of models that is constructed so that it will contain the “best” forecasting model, given a level of confidence. Thus, an MCS is analogous to a confidence interval for a parameter. The MCS acknowledges the limitations of the data so that uninformative data yield an MCS with many models, whereas informative data yield an MCS with only a few models. We revisit the empirical application in Stock and Watson (1999) and apply the MCS procedure to their set of inflation forecasts. In the first pre-1984 subsample we obtain an MCS that contains only a few models, notably versions of the Solow-Gordon Phillips curve. On the other hand, the second post-1984 subsample contains little information and results in a large MCS. Yet, the random walk forecast is not contained in the MCS for either of the samples. This outcome shows that the random walk forecast is inferior to inflation forecasts based on Phillips curve-like relationships.

The effect of the range of interaction on the phase diagram of a globular protein

Thermodynamic perturbation theory is applied to the model of globular proteins studied by ten Wolde and Frenkel (Science 277, pg. 1976) using computer simulation. It is found that the reported phase diagrams are accurately reproduced. The calculations show how the phase diagram can be tuned as a function of the lengthscale of the potential.Comment: 20 pages, 5 figure

Interpretation of Long-term Trade Projections: China's Role in Forecast Discrepancies and its Impact on Expectations for World Agricultural Trade

Agricultural and Food Policy, International Relations/Trade,