THE VALUE OF ENSO INFORMATION TO AGRICULTURE: CONSIDERATION OF EVENT STRENGTH AND TRADE

The agricultural value of El Nino-Southern Oscillation (ENSO) phase knowledge is measured in a value-of-information framework using economic models. We examine the value of considering the full distribution of ENSO phase strength effects as opposed to average ENSO phase strength effects, as well as the implications of considering ENSO impacts on the rest of the world (ROW). A stochastic U.S. agricultural sector model linked with a global trade model is used to assess the value of ENSO phase information. When the full distribution of ENSO phase strength is considered, the value of phase information increases twofold with respect to the average ENSO effects.Agribusiness,

Climate Change and Crop Yield Distribution: Some New Evidence From Panel Data Models

This study examines the impact of climate on the yields of seven major crops in Taiwan based on pooled panel data for 15 prefectures over the 1977-1996 period. Unit-root tests and maximum likelihood methods involving a panel data model are explored to obtain reliable estimates. The results suggest that climate has different impacts on different crops and a gradual increase in crop yield variation is expected as global warming prevails. Policy measures to counteract yield variability should therefore be carefully evaluated to protect farmers from exposure to these long-lasting and increasingly climate-related risks.Yield response, Climate change, Panel data, Unit-root test

AN ANALYSIS ON POTENTIAL ECONOMIC IMPACTS OF GREENHOUSE GAS MITIGATION THROUGH PLANTING ENERGY CROPS IN TAIWAN

The purpose of this study is to evaluate the economic and environmental impacts of planting energy crop on set-aside acreages in Taiwan. To do so, a Taiwan Agricultural Sector Model (TASM) was built and the data parameters of energy crop were incorporated into this model in order to simulate the economic and environmental impacts. Simulation results show that GHGE mitigation depends on the planting acreage of energy crops in which the optimal planting acreage of energy is determined by the profit of other agricultural products as well as government subsidy on energy crop. Therefore, the mitigation of GHGE depends on the government subsidy on energy crop per hectare. Such subsidy is also suitable for the green box by the regulation of WTO.Resource /Energy Economics and Policy,

Economic Growth and Government Size in OECD Countries: New Evidence from the Quantile Regression Approach

The purpose of this paper is to employ the quantile regression methodology to investigate the relationship between government size and economic growth using a panel data set for 24 OECD countries. We find that the magnitude of the effect of government size on economic growth varies through the quantiles. When the economic growth is low, increasing the size of the government may have a positive effect and stimulate economic growth. However, as the economic growth rate increases, such an effect declines and has a negative effect on economic growth.Economic growth; Government size; Quantile regression

Hurricanes and Possible Intensity Increases: Effects on and Reactions from U.S. Agriculture

Hurricanes have caused substantial damage in parts of the U.S. Damages are increasing, perhaps as part of a natural cycle or perhaps in part related to global warming. This paper examines the economic damages that hurricanes cause to U.S. agriculture, estimates the increased damage from an increase in hurricane frequency/intensity, and examines the way that sectoral reactions reduce damages. The simulation results show that hurricanes and associated adjustments cause widespread damage and redistribute agricultural welfare. We find that crop mix shifts of vulnerable crops from stricken to nonstricken regions significantly mitigate hurricane damages.crop mix, hurricane intensity, stochastic agricultural sector model, Agribusiness, Crop Production/Industries, Production Economics, Q24, Q54, R14,

How Volatile is ENSO?

The El Niños Southern Oscillations (ENSO) is a periodical phenomenon of climatic interannual variability, which could be measured through either the Southern Oscillation Index (SOI) or the Sea Surface Temperature (SST) Index. The main purpose of this paper is to analyze these two indexes in order to capture the volatility inherent in ENSO. The empirical results show that both the ARMA(1,1)-GARCH(1,1) and ARMA(3,2)-GJR(1,1) models are suitable for modelling ENSO volatility accurately. The empirical results show that 1998 is a turning point, which indicates that the ENSO strength has increased since 1998. Moreover, the increasing ENSO strength is due to the increase in greenhouse gas emissions. The ENSO strengths for SST are predicted for the year 2030 to increase from 29.62% to 81.5% if global CO2 emissions increase by 40% to 110%, respectively. This indicates that we will be faced with an even stronger El Nino or La Nina in the future if global greenhouse gas emissions continue to increase unabated.ENSO; SOI; SOT; Greenhouse Gas Emissions; Volatility; GARCH; GJR; EGARCH