The impact of multiple structural changes on mortality predictions

Most mortality models proposed in recent literature rely on the standard ARIMA framework (in particular: a random walk with drift) to project mortality rates. As a result the projections are highly sensitive to the calibration period. We therefore analyse the impact of allowing for multiple structural changes on a large collection of mortality models. We find that this may lead to more robust projections for the period effect but that there is only a limited effect on the ranking of the models based on backtesting criteria, since there is often not yet sufficient statistical evidence for structural changes. However, there are cases for which we do find improvements in estimates and we therefore conclude that one should not exclude on beforehand that structural changes may have occurred.     

Education Subsidies, Social Security and Growth: The Implications of a Demographic Shock

We develop a three-period overlapping-generations model in which individual decisions about education are the engine of growth. In this setting, we investigate the normative role of education subsidies and old age pensions. Calibrating this model on empirical data, it is shown that the case for positive pension benefits is rather weak on the optimal path. An important part of education subsidies should be financed by lump-sum taxes on retirees. We also examine how these transfers should be adjusted in the presence of a baby boom-baby bust demographic shock. It turns out that an appropriate policy could be to increase education when the baby-boom generation is at work. Labor productivity will then be higher when aging peaks so that the pension bill can be financed without reducing welfare for the baby-bust generations.
JEL classification : O 41; J 24; E 62     

Come Rain or Shine: Evidence on Flood Insurance Purchases in Florida

This article provides a detailed analysis of the operation of the National Flood Insurance Program (NFIP) in Florida, which accounts for 40 percent of the NFIP portfolio. We study the demand for flood insurance with a data set of more than 7.5 million NFIP policies‐in‐force (the largest ever studied) for the years 2000–2005, as well as all NFIP claims filed in Florida. We answer four questions: What are the characteristics of the buyers of flood insurance? What types of contracts (deductibles and coverage levels) are purchased? What are the determinants of claims payments? How are prices determined and how much does NFIP insurance cost?     

Number of Accidents or Number of Claims? An Approach with Zero‐Inflated Poisson Models for Panel Data

The  hunger for bonus  is a well-known phenomenon in insurance, meaning that the insured does not report all of his accidents to save bonus on his next year's premium. In this article, we assume that the number of accidents is based on a Poisson distribution but that the number of claims is generated by censorship of this Poisson distribution. Then, we present new models for panel count data based on the zero-inflated Poisson distribution. From the claims distributions, we propose an approximation of the accident distribution, which can provide insight into the behavior of insureds. A numerical illustration based on the reported claims of a Spanish insurance company is included to support this discussion.     

Land Allocation between Food and Energy

Many countries are promoting biofuels as a substitute for scarce oil. This paper develops a dynamic model of land allocation between food and energy and shows how the model can be calibrated using standard optimization techniques. Some possible implications of the trade-offs between food and energy are discussed. Specifically, we show that the effect of mandates is mainly felt through increased land conversion, which increases indirect carbon emissions Crude oil prices do not decrease significantly because of leakages.