Markov chain theory is proving to be a powerful approach to bootstrap highly nonlinear time series. In this work we provide a method to estimate the memory of a Markov chain (i.e. its order) and to identify its relevant states. In particular the choice of memory lags and the aggregation of...

Many IT service platforms (e.g., cloud computing platforms) are built as closed systems. They do not allow their customers to interoperate with other platforms or port their data to other platforms. As switching to different system is costly, customer of a closed IT system can be considered...

We develop a model of household demand for frequently purchased consumer goods that are branded, storable and subject to stochastic price fluctuations. Our framework accounts for how inventories and expectations of future prices affect current period purchase decisions. We estimate our model...

In a one-state one-control variable Quadratic Linear Problem, I examine the effect of an increase in the multiplicative uncertainty on the use of the control variable. In contrast with previous studies, this model considers a stochastic constant term in the transition equation. I found that the...

In this essay, it is shown that in the Hoel and Karp (2001) model of global warming, the optimal response of taxes for a stock pollutant with mutiplicative uncertainty is opposite when the control variable is pollution taxes instead of emissions. In this case, the election of control variable...

This article analyzes the trade-off between ÏcautionÓ and ÏintensityÓ in the use of the control variable in a one-state one-control dynamic stochastic quadratic linear optimization problem with discount factor. It studies the effects that changes in uncertainty of the control parameter have...