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on Insurance Economics |
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Issue of 2011‒05‒24
fifteen papers chosen by Soumitra K Mallick Indian Institute of Social Welfare and Business Management |
| By: | Adhikari, Shyam; Belasco, Eric J.; Knight, Thomas O. |
| Keywords: | Crop Yield Modeling, Crop Insurance, Weather Cycle, Crop Yield Aurocorrelation, Agricultural Finance, Production Economics, Risk and Uncertainty, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea11:103724&r=ias |
| By: | Filonov, Vitaly; Vedenov, Dmitry V. |
| Keywords: | Risk and Uncertainty, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea11:103972&r=ias |
| By: | Makoto Nakajima |
| Abstract: | This paper measures the effect of extensions of unemployment insurance (UI) benefits on the unemployment rate using a calibrated structural model that features job search and consumption-saving decision, skill depreciation, UI eligibility, and UI benefit extensions that capture what has happened during the current downturn. I find that the extensions of UI benefits contributed to an increase in the unemployment rate by 1.2 percentage points, which is about a quarter of an observed increase during the current downturn (a 5.1 percentage point increase from 4.8 percent at the end of 2007 to 9.9 percent in the fall of 2009). Among the remaining 3.9 percentage points, 2.4 percentage points are due to the large increase in the separation rate, while the staggering job-finding probability contributes 1.4 percentage points. The last extension in December 2010 moderately slows down the recovery of the unemployment rate. Specifically, the model indicates that the last extension keeps the unemployment rate higher by up to 0.4 percentage point during 2011. |
| Keywords: | Unemployment Insurance, Extension, Labor Market, Search, Consumption Smoothing |
| JEL: | J64 J65 E24 D83 |
| Date: | 2011–03 |
| URL: | http://d.repec.org/n?u=RePEc:hst:ghsdps:gd10-175&r=ias |
| By: | Belasco, Eric; Chen, Chen; Ponnaluru, Srinivasa Sasdhar; Galinato, Suzette P.; Marsh, Thomas L. |
| Abstract: | Protective covers, such as high tunnels, are being used by specialty crop producers to enhance production quality and yields, expand or growing seasons, and protect crops from some extreme elements. While growing in popularity, one barrier to larger utilization includes the uncertainty regarding their practices and benefits. This paper recognizes that high tunnels can be used as a form of risk management and examines the relationship with crop insurance in order to better define optimal risk management strategies. |
| Keywords: | high tunnels, specialty crop insurance, risk management, Production Economics, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea11:103896&r=ias |
| By: | Liu, Chia-Lan; Richardson, James W.; Leatham, David J. |
| Abstract: | The Dungeness is a popular food and the most commercially important crab in the western states in the U.S. Like all agricultural production, the crab fisherman face yield risks and must manage these risks. In addition to weather risk, crab fisherman may experience low yields if the crabs are over fished in previous years. Farmers for many traditional agricultural crops can purchase crop insurance to insure against low yields. However, crab fishermen at this time do not have this option. The purpose of this paper is to estimate a fair insurance premium based on the historical yields of the Dungeness crab. This information can then be used in risk/return models for crab fishing to determine if it would be optimal for fisherman to purchase crop insurance. An important input into the fair insurance premium estimation is the yield distribution. Sherrick et al. estimated alternative yield distributions to evaluate traditional crop insurance. However, no one has looked at the yield distributions for the Dungeness crab nor explored possible crop insurance. Much of the past literature for the fishing industry has focused on production functions, cost function models, and optimal catching yields for specific fish species. Moreover, most research has focused on the endangered commercial ocean species such as tuna and swordfish. Data and Methodology This research collects the annual landing data including metric tons, pounds, and price per pound from NOAA's National Marine Fisheries Service (NOAA Fisheries Service) to analyze the yield distributions of Dungeness crab in California, Oregon, Washington, and Alaska from 1950 to 2009. Dickey Fuller test is conducted for each state to test if the data is stationary. The Durbin-Watson test was used to make sure the data did not have autocorrelation problems. We find that the detrended data has positive Skewness contrary to traditional crop yield data. The positive Skewness indicates that the tail on the right sides is longer than the left side and the mass of the distribution is concentrated on the left. It also has relatively few high values. The candidate distributions used include normal, Gamma, Weibull, logistic, lognormal, and loglogistic distributions. The fitted distributions are compared with formal goodness- of- fit tests including Chi-Square, Anderson-Darling, and Kolmogorov-Smirnov. The loglogistic distribution is best to estimate the yield losses of Alaska, Oregon, and California respectively while the logistic is best for Washington. The Gamma and normal distribution are the worst for the four states. Actual Production History (APH) policies insure crop producers against yield losses due to natural causes. After Just and Weninger found that crop yield losses were nonnormally distributed, many agricultural researchers use parametric (Goodwin and Ker) and nonparametric distributions (Sherrick et al) and the insured price to estimate the insurance premium. The premium refers to the periodic payment made on the insurance policy. When the yields are below the insured level (the predicted level each year), the insurance company has to pay indemnities to the producers to compensate them for their losses. Our study uses different parametric distributions to forecast the crab yields. Along with the yield distributions and yield forecasts, we assume that the crop insurance insures up to 80% of the yield distribution. We also assume that the insured price is the predicted price per pound for 2010 (since the price model are Pth-order autoregressive (AR(p)) processes) to estimate the fair insurance premium. The insured prices per pound of the four states from north to south are $1.88, $2.39, $1.94, and $1.99 respectively. If the random value (that the realized yields fall below the guaranteed yields) generated by the best distributions which may generate different parametric value for the four states falls below zero, it will means that the fisherman suffer yield losses, and that the insurance company has to compensate the fishermenâs revenue. The insurance company pays the fishermen the dollars that the insured price times 80% of the yield that the fishermen suffer from loss. The indemnities will be either zero or positive. Next, we adopt Latin hypercube sampling (LHS) to simulate the indemnities 500 times to calculate the average indemnities. If we donât consider the capital and administration fees of the insurance company, the average indemnities will be the actuarially fair insurance premium. The average indemnity and thus the actuarially fair premiums of the overall crab industry are $1,380,924, $702,344, $2,823,855, and $3,470,998 one year for the all ships in Alaska, Washington, Oregon, and California respectively. Unlike traditional crop insurance that estimates the premium per acre, we use the total premium shared by all fishing vessels in the state and account for the total tons that the fishing vessels load because the crabs and the fishing vessel move everywhere. After simulated, half of the time the insurance company must pay indemnities. To avoid the high risk of yield losses and uncertainty, the existence of insurance is necessary to protect the fishermenâs revenue. Finally, we will try to use non-parametric method to estimate the fair premium and compare the results of the parametric and non-parametric distributions for the rigorous study. We will also estimate the potential welfare gain of fishermen from this insurance policy. |
| Keywords: | Dungeness Crab, Fair Insurance Premium, Simulation, Agricultural and Food Policy, Agricultural Finance, Risk and Uncertainty, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea11:103424&r=ias |
| By: | Ghosh, Somali; Woodard, Joshua D.; Vedenov, Dmitry V. |
| Abstract: | The association between prices and yields are of paramount importance to the crop insurance programs. Proper estimation of the association is highly desirable. Copulas are one such method to measure the dependence structure. Five single parametric copulas, a non- parametric copula and their fifteen different combinations taking a mixture of two different copulas at a time have been used in the crop insurance rating analysis. Using data of corn from 1973-2009 for 602 counties in the Mid-West area two different efficient methods have been proposed to generate the optimal mixtures using the cross validation approach. A resampling technique is used to check for the significance of the expected indemnities. |
| Keywords: | Copulas, Crop Insurance, Cross-Validation, Empirical distribution, GRIP, Indemnities, Out-Of-Sample Log-Likelihood, Agricultural Finance, Q14, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea11:103738&r=ias |
| By: | Lisa Jönsson; Mårten Palme; Ingemar Svensson |
| Abstract: | This paper describes the development of population health and disability insurance utilization for older workers in Sweden and analyzes the relation between the two. We use three different measures of population health: (1) the mortality rate (measured between 1950 and 2009); (2) the prevalence of different types of health deficiencies obtained from Statistics Sweden’s Survey on Living Conditions (ULF, 1975-2005); (3) the utilization of health care from the inpatient register (1968–2008). We also study the development of the relative health between disability insurance recipients and non-recipients. Finally, we study the effect of the introduction of less strict eligibility criteria for older workers in 1970 and 1972 as well as the subsequent abolishment of these rules in 1991 and 1997, respectively. |
| JEL: | H51 H55 I18 J26 |
| Date: | 2011–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:17054&r=ias |
| By: | Woodard, Joshua D. |
| Abstract: | An important issue in the agricultural actuarial literature is the extent to which sample period selection affects the accuracy of insurance rating. A conditional Weibull distribution approach is developed which explicitly models the interaction of weather, technology, and other variables on probabilistic yield outcomes to address this issue. Results from an application with an extensive producer-level yield dataset representing commercial-scale Illinois firms suggest that the impact of weather heterogeneity on risk estimation across reasonable samples is likely not as great as is often claimed. The results also suggest that yield risk is decreasing significantly through time, and indicate the presence of trend acceleration. A rating analysis indicates that violations in the risk evolution assumptions of the rating approaches used in the Federal Crop Insurance Programâwhich implicitly assume increasing yield risk through time when yields trendâresult in severely biased rates, with typical overstatements of 200% to 400% for Midwest corn. |
| Keywords: | Conditional Weibull Distribution, Conditional Production Function, Catastrophic Risk Modeling, Sample Selection, Yield Risk, Crop Insurance, Ratemaking, Crop Production/Industries, Risk and Uncertainty, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea11:103929&r=ias |
| By: | Norton, Michael; Holthaus, Eric; Madajewicz, Malgosia; Osgood, Daniel; Peterson, Nicole; Gebremichael, Mengesha; Mullally, Conner; Teh, TseLing |
| Abstract: | There is much interest in weather index insurance as a povertyâmitigating tool, but concerns persist about potential demand for the product among the poorest of the poor. This paper relates the experiences in rural areas of Tigray region, Ethiopia through both commercial signâup data and a series of experimental games conducted to test demand for weather index insurance. Demand was observed to be considerable in both. |
| Keywords: | Risk and Uncertainty, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea11:104022&r=ias |
| By: | Miao, Ruiqing; Feng, Hongli; Hennessy, David A. |
| Abstract: | There have long been concerns that federal crop insurance subsidies may significantly impact land use decisions. It is well known that classical insurance market information asymmetry problems can lead to a social excess of risky land entering crop production. Our conceptual model shows that the problem will arise absent any information failures. This is because the subsidy is i) proportional to acres planted, and ii) greatest for the most production risky land. Using farm-level data, we follow this observation through to establish the implications of subsidies for the extent of crop production, with particular emphasis on U.S. regions where the cropland growth is likely to have marked adverse environmental impacts. Simulation results show that when subsidy rate decreases by 5 percentage points, then about 0.60 percent of insured cropped land will be converted to non-cropped land. When crop price decreases by 5 percent, then about 1.01 percent of insured cropped land will be converted to non-cropped land. |
| Keywords: | crop insurance, land use, crop yields, yield risk measurement, Agricultural and Food Policy, Crop Production/Industries, Land Economics/Use, Q15, Q18, Q24, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea11:103891&r=ias |
| By: | Hennessy, David A.; Miao, Ruiqing; Feng, Hongli |
| Abstract: | The U.S. Federal Government implements environmental, biofuels and crop insurance programs that influence land use. They are not well-integrated in that cost savings from crop insurance subsidies are not acknowledged when screening land for retirement or when calculating the cost of land retirement programs. We identify and evaluate an optimal benefit index for enrollment in a land retirement program that includes a sub-index to rank land according to insurance subsidy savings. All else equal, land ranked higher in the Lorenz stochastic order should be retired first. Empirical analysis based on field level data will be provided. |
| Keywords: | Agro-environmental policy, Budget, Conservation reserve program, Crop failure, Environmental benefit index, Lorenz order, Land Economics/Use, Risk and Uncertainty, Q18, Q28, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea11:104002&r=ias |
| By: | Chang, Hung-Hao; Meyerhoefer, Chad R.; Just, David |
| Abstract: | Using a unique dataset of 703,287 farm operators from the Taiwanese Census of Agriculture merged to administrative records from the National Farmers' Health Insurance (FHI) program, we examine the effects of the enrollment in the FHI program on farmersâ on- and off-farm labor supply and the amount of land they allocate to Taiwanâs land retirement program. In order to account for non-random self-selection into the FHI we use a matching procedure to estimate the impact of the program on land and labor allocations. Our results indicate that participation in the FHI increases (decrease) on (off) farm labor supply, and decreases the amount of land enrolled in the land retirement program. Our findings have implication for health care reforms that have been initiated in other countries, and the United States in particular. |
| Keywords: | National Farmer's Health Insurance Program, labor supply, land retirement program, Taiwan., Agricultural and Food Policy, Health Economics and Policy, Labor and Human Capital, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea11:103446&r=ias |
| By: | Chen, Shu-Ling |
| Abstract: | 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 contractâs 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. |
| Keywords: | nonlinear quantile, temperature risk, weather index insurance, Agricultural Finance, Financial Economics, Risk and Uncertainty, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea11:104229&r=ias |
| By: | Tsung Yu, Yang |
| Abstract: | Regarding the nature of yield data, there are two basic characteristics that needs to be accommodated while we are about to model a yield distribution. The first one is the nonstationary nature of the yield distribution, which causes the heteroscedasticity related problems. The second one is the left skewness of the yield distribution. A common approach to this problem is based on a two-stage method in which the yields are detrended first and the detrended yields are taken as observed data modeled by various parametric and nonparametric methods. Based on a two-stage estimation structure, a mixed normal distribution seems to better capture the the secondary distribution from catastrophic years than a Beta distribution. The implication to the risk management is the yield risk may be underestimated under the common selection -- Beta distribution. A mixed normal distribution under a time-varying structure, under which the parameters are allowed to vary over time, tends to collapse to a single normal distribution. The time-varying mixed normal model fits the realized yield data in one step that avoids the possible bias caused by sampling variability. Also, the time-varying parameters imply that the premium rates can be adjusted to represent the most recent information and that lifts the efficiency of the insurance market. |
| Keywords: | Time-Varying Distribution, Mixture Distribution, Crop Insurance, Agricultural Finance, Crop Production/Industries, Research Methods/ Statistical Methods, Risk and Uncertainty, |
| Date: | 2011 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea11:103422&r=ias |
| By: | Klaas de Vos; Arie Kapteyn; Adriaan Kalwij |
| Abstract: | This paper presents information on labor market participation of the elderly, mortality and health, pathways to retirement and rates of participation in various earnings replacing programs in the Netherlands. It presents an overview of reforms to Disability Insurance (DI) and other income maintenance and early retirement programs over the past few decades, and examines to what extent these reforms have affected labor market exit routes of older workers. The overall picture that emerges is that DI receipt appears unrelated to the general health of the population and that over the last two decades relatively fewer older workers exit the labor market through DI. This reduction may, arguably, in part be attributed to stricter DI eligibility rules. |
| JEL: | J26 |
| Date: | 2011–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:17053&r=ias |