Chebyshev polynomial approximation to approximate partial differential equations

This paper suggests a simple method based on Chebyshev approximation at Chebyshev nodes to approximate partial differential equations. The methodology simply consists in determining the value function by using a set of nodes and basis functions. We provide two examples. Pricing an European option and determining the best policy for chatting down a machinery. The suggested method is flexible, easy to program and efficient. It is also applicable in other fields, providing efficient solutions to complex systems of partial differential equations.

The effects of the generalized use of iodized salt on occupational patterns in Switzerland.

This paper examines the impact of salt iodization in Switzerland in the 1920s and 1930s on occupational patterns of cohorts born after the intervention. The generalized use of iodized salt successfully combatted iodine deficiency disorders, which were previously endemic in some areas of Switzerland. The most important effect of universal prophylaxis by means of iodized salt was the eradication of mental retardation inflicted in utero by lack of iodine. This paper looks for evidence of increased cognitive ability of those treated with iodine in utero by examining the occupational choice and characteristics of occupations chosen by cohorts born after the intervention. By exploiting variation in pre-existing conditions and in the timing of the intervention, I find that cohorts born in previously highly-deficient areas after the introduction of iodized salt self-selected into higher-paying occupations. I also find that the characteristics of occupations in those areas changed, and that cohorts born after the intervention engaged to a higher degree in occupations with higher cognitive demands, whereas they opted out of physical-labor-intensive occupations.

Computing Markov-Perfect Optimal Policies in Business-Cycle Models

Time-inconsistency is an essential feature of many policy problems (Kydland and Prescott, 1977). This paper presents and compares three methods for computing Markov-perfect optimal policies in stochastic nonlinear business cycle models. The methods considered include value function iteration, generalized Euler-equations, and parameterized shadow prices. In the context of a business cycle model in which a scal authority chooses government spending and income taxation optimally, while lacking the ability to commit, we show that the solutions obtained using value function iteration and generalized Euler equations are somewhat more accurate than that obtained using parameterized shadow prices. Among these three methods, we show that value function iteration can be applied easily, even to environments that include a risk-sensitive scal authority and/or inequality constraints on government spending. We show that the risk-sensitive scal authority lowers government spending and income-taxation, reducing the disincentive households face to accumulate wealth.