Long Term Recovery Planning Task Force Report, August 2008

Eighty-five of 99 Iowa counties were declared Presidential Disaster Areas for Public Assistance and/orIndividual Assistance as a result of the tornadoes, storms, and floods over the incident period May 25 through August 13, 2008. Response dominated the state’s attention for weeks, with a transition to recovery as the local situations warranted. The widespread damage and severity of the impact on Iowans and their communities required a statewide effort to continue moving forward despite being surrounded by adversity. By all accounts, it will require years for the state to recover from these disasters. With an eye toward the future, recovery is underway across Iowa. As part of the Rebuild Iowa efforts, the Long Term Recovery Planning Task Force was charged with responsibilities somewhat different from other topical Task Force assignments. Rather than assess damage and report on how the state might address immediate needs, the Long Term Recovery Planning Task Force is directed to discuss and discern the best approach to the lengthy recovery process. Certainly, the Governor and Lieutenant Governor expect the task to be difficult; when planning around so many critical issues and overwhelming needs, it is challenging to think to the future, rather than to rise to the current day’s needs.

Correspondence analysis of two transition tables

The case of two transition tables is considered, that is two squareasymmetric matrices of frequencies where the rows and columns of thematrices are the same objects observed at three different timepoints. Different ways of visualizing the tables, either separatelyor jointly, are examined. We generalize an existing idea where asquare matrix is descomposed into symmetric and skew-symmetric partsto two matrices, leading to a decomposition into four components: (1)average symmetric, (2) average skew-symmetric, (3) symmetricdifference from average, and (4) skew-symmetric difference fromaverage. The method is illustrated with an artificial example and anexample using real data from a study of changing values over threegenerations.

The three horsemen of riches: Plague, war and urbanization in early modern Europe

How did Europe escape the "Iron Law of Wages?" We construct a simple Malthusian model withtwo sectors and multiple steady states, and use it to explain why European per capita incomes andurbanization rates increased during the period 1350-1700. Productivity growth can only explain a smallfraction of the rise in output per capita. Population dynamics changes of the birth and death schedules were far more important determinants of steady states. We show how a major shock to population cantrigger a transition to a new steady state with higher per-capita income. The Black Death was such ashock, raising wages substantially. Because of Engel's Law, demand for urban products increased, andurban centers grew in size. European cities were unhealthy, and rising urbanization pushed up aggregatedeath rates. This effect was reinforced by diseases spread through war, financed by higher tax revenues.In addition, rising trade also spread diseases. In this way higher wages themselves reduced populationpressure. We show in a calibration exercise that our model can account for the sustained rise in Europeanurbanization as well as permanently higher per capita incomes in 1700, without technological change.Wars contributed importantly to the "Rise of Europe", even if they had negative short-run effects. We thustrace Europe s precocious rise to economic riches to interactions of the plague shock with the belligerentpolitical environment and the nature of cities.