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on Insurance Economics |
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Issue of 2016‒06‒09
sixteen papers chosen by Soumitra K. Mallick Indian Institute of Social Welfare and Business Management |
| By: | Yi, Jing; Richardson, James; Bryant, Henry |
| Abstract: | This paper uses regional county level data to explore the impacts of crop insurance premium subsidies on the demand for corn crop insurance at each coverage level. Although the demand for corn insurance is price-inelastic, the elasticities of demand with respect to per dollar net premium vary significantly among coverage levels, insurance plans, and regions. The elasticities of demand for corn yield insurance (APH) with respect to per dollar net premium are − 0 .230, −0 .158, and −0 .259 at the 80% coverage level in the Corn Belt, Lake States, and Northern Plains, respectively. The corresponding elasticity at the 75% coverage level in the Southern Plains is −0 .654. The elasticities of demand for corn revenue insurance (CRC) with respect to per dollar net premium are −0 .200, −0 .208 at the 80% coverage level in the Corn Belt and Lake States, respectively, and it is −0 .670 at the 75% coverage level in the Southern Plains. The results show that elasticities of demand for corn insurance tend to be larger in riskier regions at relatively higher coverage levels. This study also estimates the possible changes in producers’ crop insurance purchases if federal crop insurance premium subsidies are reduced by 10 percentage points. The expected change in producers’ purchases of corn revenue insurance at the 75% coverage level in the Southern Plains ( −12 .182%) would be three times greater than it is at the 80% coverage level in the Corn Belt ( −4 .167%) with a 10 percentage point decrease in premium subsidy rates. |
| Keywords: | crop insurance, demand, premium subsidies, Agribusiness, Agricultural and Food Policy, Agricultural Finance, Consumer/Household Economics, Crop Production/Industries, Demand and Price Analysis, Farm Management, Marketing, Risk and Uncertainty, A1, B2, C3, |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:236249&r=ias |
| By: | Kosali Simon; Aparna Soni; John Cawley |
| Abstract: | The U.S. population receives suboptimal levels of preventive care and has a high prevalence of risky health behaviors. One goal of the Affordable Care Act (ACA) was to increase preventive care and improve health behaviors by expanding access to health insurance. This paper estimates how the ACA’s state-level expansions of Medicaid in 2014 affected these outcomes. Using data from the Behavioral Risk Factor Surveillance System, and a difference-in-differences model that compares states that did and did not expand Medicaid, we examine the impact of the expansions on preventive care (e.g. dental visits, immunizations, mammograms, cancer screenings) and risky health behaviors (e.g. smoking, heavy drinking, lack of exercise, obesity). We find evidence consistent with increased use of certain forms of preventive care such as dental visits and cancer screenings but little evidence of changes in health behaviors and in particular no evidence of ex ante moral hazard (i.e., no evidence that risky health behaviors increased in response to health insurance coverage). The Medicaid expansions also resulted in modest improvements in self-assessed health and decreases in the number of work days missed due to poor health. |
| JEL: | I12 I13 I28 |
| Date: | 2016–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:22265&r=ias |
| By: | Weber, Jeremy G.; Key, Nigel; O'Donoghue, Erik |
| Abstract: | Farmers dramatically increased their use of federal crop insurance in the 2000s. From 2000 to 2013, premium subsidies increased seven-fold and acres enrolled increased by 77 percent. Although designed for non-environmental goals, subsidized insurance may affect the use of land, fertilizer, and agrochemicals and therefore environmental externalities from agriculture. Using a novel panel data, we examine farmer responses to changes in coverage with an empirical approach that exploits program limits on coverage that were more binding for some farmers than for others. Estimates indicate that expanded coverage had little effect on the share of farmland harvested, crop specialization, productivity, or fertilizer and chemical use. More broadly, we construct and describe a new nation-wide, farm-level panel data set with nearly 32,500 farms observed at least twice over the 2000-2013 period, a resource that should enrich U.S. agro-environmental research. |
| Keywords: | Crop insurance, agriculture, environmental externalities, fertilizer |
| JEL: | Q12 Q15 Q18 |
| Date: | 2016–05–13 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:71293&r=ias |
| By: | Oñate, Carlos Andrés; Ozaki, Vitor Augusto; Bravo-Ureta, Boris |
| Abstract: | This research evaluates the impact of a public risk management tool that provides insurance to small-scale farmers. In particular, we analyze the “Farm Activity Guarantee Program for Smallholders” or Proagro Mais, which is one of the largest Brazilian public programs that uses crop insurance indemnity mechanisms. This program covers financial debts incurred by smallholders related to rural credit operations, and which payment was hampered by the occurrence of pests, diseases or climatological effects. The relevance of this research relies on the considerable size of the program, both in terms of number of operations and money invested to cover crop losses. We use a sample of small-scale corn producers from the State of Paraná, which included Proagro Mais beneficiaries and nonbeneficiaries. One should note that all growers in the sample contracted credits associated with their corn crop, but not all subscribed to the insurance Program. We use 2003 as the baseline since it is the year prior to the launch of Proagro Mais and then used 2005 as the endline considering the indemnity mechanism of the Program. The database used in this study was provided by the Federal Accounting Court of Brazil (TCU), and includes 25,877 corn growers that contracted with Proagro Mais between 2003 and 2005 (treatment group), and 68,312 growers who were not beneficiaries of that program in this same period (control group). The relevant variables include crop and growers characteristics such as area financed, complementary economic activities for additional income (dummy), education, and expected yield. We also added meteorological and regional variables from other public sources to control farm location. Our main objective is to evaluate the impact of Proagro Mais on the amount of credit per hectare granted to the beneficiaries of the Program. The methodology includes Propensity Score Matching (PSM) along with Difference-in-Difference (DID). We use longitudinal data and apply the conditional DID estimator proposed by Heckman et al. (1997), and the conditional DID estimator with repeated cross-sections, proposed by Blundell and Costa Dias (2000).The econometric estimates with both methods described above, show that the effect of the treatment on the tread was not positive. This suggests that after the yield loss period, the control group got a higher average amount of credit per hectare than Proagro Mais beneficiaries. Thus, the question that arises is whether there may be other agricultural risk management mechanisms more suited for smallholders than Proagro Mais, or whether the evaluated program could not achieve its main goal because it does not cover all risks faced by its beneficiaries. Therefore, this study could serve to promote discussions about the economic performance and efficiency of agricultural policy in Brazil. |
| Keywords: | Brazil, impact evaluation, agricultural risk management policy, Agricultural and Food Policy, Research Methods/ Statistical Methods, Risk and Uncertainty, Q18, C54, Q12, G22, |
| Date: | 2016–05–25 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:236096&r=ias |
| By: | Yu, Jisang; Smith, Aaron; Sumner, Daniel A. |
| Abstract: | The U.S. federal crop insurance program experienced periodic policy changes over the past three decades that increased premium subsidies. These premium subsidies encourage changes in crop acreage for two reasons. First, holding insurance coverage constant, premium subsidies directly increase the expected return, which may encourage more acreage of the insured crop (profit effect). Second, premium subsidies encourage farms to increase crop insurance coverage. With more insurance coverage, farm revenue, which includes crop revenues and expected crop insurance indemnity payments, becomes less variable and therefore, acreage of the insured crop may increase (coverage effect). By exploiting exogenous policy changes, this study estimates the sum of these two distinct effects of premium subsidies on crop acreage. Using about 180,000 county-crop-year observations for seven major crops over 26 years, we estimate that a 10% increase in the premium subsidy causes a 0.39% increase in crop acreage. Taking account of the small share of crop insurance premium subsidies in expected crop revenue, this estimate is analogous to an analogue to the own-price elasticity is about 1.10. This estimate exceeds supply elasticity estimates in the literature because crop insurance premium subsidies has a coverage effect in addition to a profit effect. |
| Keywords: | Agricultural Policy, Crop Insurance, Acreage Response, Agricultural and Food Policy, Production Economics, Risk and Uncertainty, |
| Date: | 2016–08–01 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:236022&r=ias |
| By: | Li, Xiaofei; Tack, Jesse B.; Coble, Keith H.; Barnett, Barry J. |
| Abstract: | This study explores whether the soil information contributes additional explanatory power beyond the base premium rate to crop insurance loss. By examining a panel of 697 counties from the Corn Belt states in the U.S. over the period of 2005—2015, we find the loss costs are systematically associated with the National Commodity Crop Productivity Index (NCCPI) conditioning on the county base premium rates, weather conditions, and year fixed effects. The loss cost rises first with NCCPI in lower NCCPI quartiles and then decreases in higher NCCPI quartile. In general, counties with medium NCCPI values are expected to have higher relative loss cost comparing with low and high NCCPI counties. The pattern of NCCPI’s effects is robust to different model specifications, heteroskedasticity and spatial correlation of data, as well as subsamples by insured acreage thresholds. The finding of this study presents empirical evidence that there is additional information embodied in soil and spatial variables not captured by the current base premium rates that is correlated with loss experiences. It suggests the potential to incorporate soil and spatial information to improve the crop insurance ratemaking. |
| Keywords: | Crop insurance, loss cost, base premium rate, soil productivity index (NCCPI), risk, Agricultural and Food Policy, Agricultural Finance, Crop Production/Industries, Environmental Economics and Policy, Production Economics, Risk and Uncertainty, |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:235750&r=ias |
| By: | Adriano A. Rampini; S. Viswanathan |
| Abstract: | Households' insurance against shocks to income, health and other non-discretionary expenditures, and asset values (that is, household risk management) is limited, especially for poor households. We argue that a trade-off between intertemporal financing needs and insurance across states explains this basic insurance pattern. In a model with limited enforcement, we show that household risk management is increasing in household net worth and income, incomplete, and precautionary. These results hold in economies with income risk, durable goods and collateral constraints, and durable goods price risk, under quite general conditions and, remarkably, risk aversion is sufficient and prudence is not required. In equilibrium, collateral scarcity results in a lower interest rate, reduced insurance, and increased inequality. |
| JEL: | D14 D91 E21 G22 I13 |
| Date: | 2016–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:22293&r=ias |
| By: | François Le Grand (EMLyon Business School); Xavier Ragot (OFCE) |
| Abstract: | We analyze derivative asset trading in an economy in which agents face both aggregate and uninsurable idiosyncratic risks. Insurance markets are incomplete for idiosyncratic risk and, possibly, for aggregate risk as well. However, agents can exchange insurance against aggregate risk through derivative assets such as options. We present a tractable framework, which allows us to characterize the extent of risk sharing in this environment. We show that incomplete insurance markets can explain some properties of the volume of traded derivative assets, which are difficult to explain in complete market economies. |
| Keywords: | Incomplete markets; Heterogeneous agent models; Imperfect risk sharing; Derivative assets |
| JEL: | G1 G12 E44 |
| Date: | 2015–09 |
| URL: | http://d.repec.org/n?u=RePEc:spo:wpmain:info:hdl:2441/1p7ctioc2n80gp0icks5dssdsa&r=ias |
| By: | ODonoghue, Erik; Tulman, Sarah |
| Keywords: | Agricultural and Food Policy, Risk and Uncertainty, |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:235623&r=ias |
| By: | Xiaoqing Liang; Zbigniew Palmowski |
| Abstract: | In this paper, we consider the problem of maximizing the expected discounted utility of dividend payments for an insurance company that controls risk exposure by purchasing proportional reinsurance. We assume the preference of the insurer is of CRRA form. By solving the corresponding Hamilton-Jacobi-Bellman equation, we identify the value function and the corresponding optimal strategy. We also analyze the asymptotics of the value function for large initial reserves. |
| Date: | 2016–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1605.06849&r=ias |
| By: | Rajkamal Iyer (MIT Sloan, Cambridge); Thais Jensen,; Niels Johannesen; Adam Sheridan (Department of Economics, University of Copenhagen) |
| Abstract: | We study a run on uninsured deposits in Danish banks triggered by a reform that limited deposit insurance coverage. Using a unique dataset with information about all individual accounts in Danish banks, we show that the reform caused a 50% decrease in deposits above the insurance limit in non-systemic banks, but a much smaller decrease in systemic banks which experienced less withdrawals from uninsured accounts, but also more openings of new uninsured accounts. Our results highlight the significant risks from a differential reallocation of uninsured deposits across banks and, in turn, the need for high insurance limits during a crisis. |
| Date: | 2016–05–18 |
| URL: | http://d.repec.org/n?u=RePEc:kud:epruwp:1602&r=ias |
| By: | Kim, Youngjune; Pendell, Dustin |
| Keywords: | Agricultural and Food Policy, Farm Management, |
| Date: | 2016–05–25 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:235828&r=ias |
| By: | Liran Einav; Amy Finkelstein; Maria Polyakova |
| Abstract: | Standard theory suggests that optimal consumer cost-sharing in health insurance increases with the price elasticity of demand, yet publicly-provided drug coverage typically involves uniform cost-sharing across drugs. We investigate how private drug plans set cost-sharing in the context of Medicare Part D. We document substantial heterogeneity in the price elasticities of demand across more than 150 drugs and across more than 100 therapeutic classes, as well as substantial heterogeneity in the cost-sharing for different drugs within privately-provided plans. We find that private plans set higher consumer cost-sharing for drugs or classes with more elastic demand. Our findings suggest that benefit design may be more efficient in privately rather than publicly provided insurance. |
| JEL: | D12 G22 H51 I13 |
| Date: | 2016–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:22277&r=ias |
| By: | Stoeffler, Quentin; Wouter, Gelade; Catherine, Guirkinger; Michael, Carter |
| Abstract: | While risk is known to harm farmers’ production investments, there is still limited evidence of index-insurance impact on household ex-ante behavior. This paper studies a pilot area-yield index insurance project sold to cotton farmer groups in Burkina Faso. Insurance sales were randomized, and in the treatment area, an encouragement design was generated by providing premium subsidies (between 25% and 75%) randomly distributed to farmer groups. No impact was found on cotton production, most likely in reason of the late sale period (during the sowing period). However, substantial and significant impacts were found on several activities and assets such as field investments, sesame cultivation and livestock herding. The mechanisms behind these indirect effects are discussed. Overall, the findings suggest a promising role of index insurance for stimulating ex-ante investments, but also draws attention on implementation gaps which currently threaten this type of intervention. |
| Keywords: | Index insurance, cotton, Burkina Faso, risk, indirect impact, productive investments, Agricultural Finance, Crop Production/Industries, Food Security and Poverty, International Development, Research and Development/Tech Change/Emerging Technologies, Risk and Uncertainty, D91, G22, I38, O12, O13, O22, O33, Q12, |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:235980&r=ias |
| By: | Park, Eunchun; Brorsen, B. Wade; Harri, Ardian |
| Abstract: | Rating of insurance premiums depends on the probability of events in the tail of the distribution. Extreme value theory provides a promising way to assess tail risk. We assume that crop yield follows a Generalized Pareto Distribution (GPD), which is a family of extreme value distributions that has advantages for modeling rare events. GPD parameters are fitted using county-level historical winter wheat yield (1970-2014). Spatial smoothing with Kriging parameters is used within a Bayesian hierarchical framework that helps overcome a lack of data due to the rarity of extreme events. We assume that the spatial correlation of crop yield is embedded in the parameters of the GPD. To obtain the posterior distribution, we use Metropolis-Hastings (MH) steps within a Gibbs sampler. Maximum likelihood estimates of the GPD parameters are used for candidate density in the MH step. In the process, MCMC chains are run for 100,000 iterations and burn-in for the first 20,000 observations. We use Deviance Information Criterion (DIC) and out of sample performance to evaluate the quality of the model. From the estimated results, we verify spatial correlation in crop yield, which substantially affects estimates of posterior distributions of GPD parameters. We further simulate spatial random effect based on posterior values of Kriging parameters (range and sill) to visualize and verify the form of spatial correlation. Estimated premiums from an existing method from which current premiums are based, tend to underestimate premium rates compared to our new proposed method. |
| Keywords: | Rating crop insurance contract, Bayesian spatial smoothing, Spatial correlation, Bayesian hierarchical model, Extreme value theory, Agricultural and Food Policy, Crop Production/Industries, Research Methods/ Statistical Methods, Resource /Energy Economics and Policy, |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:235754&r=ias |
| By: | Woodard, Joshua |
| Abstract: | Government subsidized insurance is ubiquitous, yet estimation of demand in such markets remains challenging. Premium charged for a given deductible is determined by actuarial construction, thus observed choice-pairs are endogenous leading to biased estimation under standard econometric approaches. A theoretical model and simulation study are developed, and a new identification strategy proposed. An empirical application using Federal Crop Insurance Program--a $100 billion/year program--data reveals that demand is quite elastic after accounting for this endogeneity. Mistreatment of such endogeneity is likely partly responsible for pervasive faulty findings of inelastic insurance demand in related applications. Policy implications are discussed. |
| Keywords: | crop insurance, risk management, Agribusiness, Agricultural and Food Policy, Agricultural Finance, |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea16:236151&r=ias |