With the advances in the Internet-of-Things technology, electric vehicles (EVs) have become
easier to schedule in daily life, which is resha** the electric load curve. It is important to …

The development of wind power plants is an economical solution to provide energy to
remote communities. For these isolated systems, the cogeneration of diesel generators and …

Approximating stochastic processes by finite‐state Markov chains is useful for reducing
computational complexity when solving dynamic economic models. We provide a new …

Foreign currency sovereign bond spreads tend to be higher than historical sovereign credit
losses, and cross-country spread correlations are larger than their macro-economic …

These notes describe tools for solving microeconomic dynamic stochastic optimization
problems, and show how to use those tools for efficiently estimating a standard life cycle …

We consider the problem of approximating a continuous random variable, characterized by
a cumulative distribution function (cdf) F (x), by means of k points, x 1< x 2<⋯< xk, with …

Existing methods for estimating nonlinear dynamic models are either highly computationally
costly or rely on local approximations which often fail adequately to capture the nonlinear …

It is well-known that returns of financial assets exhibit heavy tail property and there has been
no distribution which can reliably capture this characteristic so far. To contribute to the …

Tensor-grid discretization of VARs is inefficient. In particular, when there are just a few
variables or the VAR components are correlated, this approach creates large inefficiencies …

We present a novel approach to Bayesian inference and general Bayesian computation that
is defined through a sequential decision loop. Our method defines a recursive partitioning of …