In-sample forecasting: A brief review and new algorithms

Statistical methods often distinguish between in-sample and out-of-sample approaches. In particular this is the case when time is involved. Then often time series methods are proposed that extrapolate past patterns into the future via complicated recursion formulas. Standard statistical inference is on the other hand concerned with estimating parameters within the given sample. This review paper is about a statistical methodology, where all parameters are estimated in-sample while producing a forecast out-of-sample without recursion or extrapolation. A new super-simulation algorithm ensures a faster implementation of the simplest and perhaps most important version of in-sample forecasting

Climate Impacts, Political Institutions, and Leader Survival: Effects of Drought and Flooding Precipitation.

We explore how the political survival of leaders in different political regimes is affected by drought and flooding precipitation, which are the two major anticipated impacts of anthropogenic climate change. Using georeferenced climate data for the entire world and the Archigos dataset for the period of 1950-2010, we find that irregular political exits, such as coups or revolutions, are not significantly affected by climate impacts. Similarly, drought has a positive but insignificant effect on all types of political exits. On the other hand, we find that floods increase political turnover through the regular means such as elections or term limits. Democracies are better able to withstand the pressures arising from the economic and social disruptions associated with high precipitation than other institutional arrangements. Our results further suggest that, in the context of floods, political institutions play a more important role than economic development for the leaders’ political survival