Acreage Abandonment, Moral Hazard and Crop Insurance

Empirical evidence for the existence of moral hazard in the U.S. crop insurance program has been inconclusive. Here we use a nested-dynamic programming framework to estimate an intra-seasonal dynamic model that explicitly incorporates a farmer's crop abandonment decision. The estimation is implemented for selected Texas counties where actuarial performances of the crop insurance program are poor and high incidences of acreage abandonment are frequently observed.Farm Management,

Actuarial Implication of Structural Changes in El Niño-Southern Oscillation Index Dynamics

The influence of climate variability on agricultural production and financial risks faced by an individual or an institution has been the center of the public discussion in the recent years. The changing weather patterns and environmental conditions could cause substantial unpredicted economic loss. Failure to capture the changing climate would underestimate the insurance contract’s expected indemnity and further create a major obstacle for insurance sectors. In this paper, we undertake a case study of El Niño-Southern Oscillation Index insurance for coastal Peru proposed by Skees. We examined the behavior of El Niño dynamics and found El Niño indices are changing over time. A class of generalized autoregressive conditional heteroskedasticity (GARCH) - family process that allows the disturbance variance to vary over time is used to design and rate the El Niño-Southern Oscillation Index insurance contract.actuarial rating, climate variability, El Niño, fractional integration ARCH, FIGARCH, index insurance, structural change, Agricultural Finance, Financial Economics, Risk and Uncertainty, G21, G22, Q10, Q14,

Modeling Temperature Dynamics for Aquaculture Index Insurance In Taiwan: A Nonlinear Quantile Approach

According to the Taiwan Council of Agriculture, frost was responsible for approximately 30 percent of aquaculture losses in Taiwan during the period 1999-2008. Farmed milkfish, the most important aquaculture crop in Taiwan, is particularly sensitive to temperature variations, and can experience widespread kills whenever temperatures fall below 14°C for sustained periods of time. Temperatures below this critical minimum, however, are not uncommon during the January-March winter months. The purpose of our study is to analyze the possible benefits and the actuarial properties of temperature-based index insurance for the farmed milkfish industry in Kaohsiung County, Taiwan. Weather-based index insurance has been promoted as a cost-effective means of managing risk associated with catastrophic weather events, examples of which include risk transfer products as varied as rainfall insurance in Mali and El Nino-Southern Oscillation insurance in Peru. Of special interest here will be performing accurate assessments of the actuarial properties of a temperature index contract that would indemnify Kaohsiung County farmed milkfish producers based on the value of lower-quadrant daily temperature, which has been shown to be highly correlated with extreme production losses. To assess the actuarial properties of such a contract, we will develop a time series model of daily temperatures lows in Kaohsiung County. Daily temperatures exhibit some special features that must be observed by any reasonable time series model. For example, daily temperatures exhibit strong seasonality with small perturbations. Moreover, seasonal variations exist not only with the mean daily temperatures, but also their variance. Specifically, daily low temperatures are more volatile in winter than in summer. To capture the special features of daily temperatures, we estimate a nonlinear nonstructural time series model of the quantiles of the conditional distribution of daily temperature lows given the observed covariates based on Campbell and Diebold (2005). A simple low-ordered polynomial function is used to capture the deterministic trend and autoregressive lags are used to capture cyclical dynamics of the daily temperature. Also, a Fourier series is applied to model the seasonal components in daily temperature and its variance. However, in contrast to Campbell and Diebold (2005), we model and forecast the lower quantile rather than mean of the daily temperature. We also introduce a phase angle in the low-order Fourier series to allow the peak of daily average temperature to occur at any point in time within a year. The algorithm for computing the nonlinear quantile regression estimates is based on an interior point method described in Koenker and Park (1996). Once the estimates are computed, we invoke bootstrap methods to compute confidence intervals for the contract’s fair premium rate. Our research employs 1974-2008 daily surface temperature data, which is collected and published by Central Bureau, Taiwan, for a weather station located in Kaohsiung County. The farmed milkfish production data in Kaohsiung County also obtained from Council of Agriculture, Executive Yuan, is used to examine the risk-reduction effectiveness of the temperature contracts with different trigger and stop-loss points. The contribution of our paper is not only to provide an alternative method in modeling temperature risk, but also to provide an empirical basis for further, more general discussion regarding the potential benefits of weather index insurance contracts in Taiwan.nonlinear quantile, temperature risk, weather index insurance, Agricultural Finance, Financial Economics, Risk and Uncertainty,

Nonlinear Mean Reversion across National Stock Markets: Evidence from Emerging Asian Markets

This paper seeks empirical evidence of nonlinear mean-reversion in relative national stock price indices for Emerging Asian countries. It is well known that conventional linear unit root tests suffer from low power against the stationary nonlinear alternative. Implementing the nonlinear unit root tests proposed by Kapetanios, et al. (2003) and Cerrato, et al. (2009) for the relative stock prices of Emerging Asian markets, we find strong evidence of nonlinear mean reversion, whereas linear tests fail to reject the unit root null for most cases. We also report some evidence that stock markets in China and Taiwan are highly localized.Linear Unit Root Test; Nonlinear Unit Root Test; Nonlinear Panel Unit Root Test; International Relative Stock Prices

Effects of Insurance on Farmer Crop Abandonment

Empirical evidence for the existence of moral hazard in the U.S. crop insurance program has been inconclusive. Here, we seek empirical evidence of moral hazard in the U.S. crop insurance program, departing from the established empirical literature in two significant respects. First, we attempt to uncover evidence of moral hazard by examining the effects of crop insurance on post-planting crop abandonment decisions. Second, we expand to the scope of existing empirical studies by including regions and crops that have historically experienced high loss ratios under the Federal crop insurance program. Our results provide strong evidence that insurance participation encourages producers to abandon their crops during the growing season for corn in Central Plains and Southern Plains regions and for upland cotton in Southeast, Delta States and Southern Plains regions.Farm Management, Risk and Uncertainty,

MODELING MULTIVARIATE CROP YIELD DENSITIES WITH FREQUENT EXTREME EVENTS

Measuring the lower tail of a crop yield distribution is important for managing agricultural production risk and rating crop insurance. Common parametric techniques encounter difficulties when attempting to model extreme yield events. We evaluate and compare alternative models based on our candidate distributions for high risk counties.Research Methods/ Statistical Methods,