In this paper, we give an overview of the state-of-the-art in the econometric literature on the modeling of so-called financial point processes. The latter are associated with the random arrival of specific financial trading events, such as transactions, quote updates, limit orders or price...

This paper explores implications of nominal rigidity characterized by a non-constant hazard function for aggregate dynamics. I derive the NKPC under an arbitrary hazard function and parameterize it with the Weibull duration model. The resulting Phillips curve involves lagged inflation and lagged...

This paper uses the Bayesian approach to solve and estimate a New Keynesian model augmented by a generalized Phillips curve, in which the shape of the price reset hazards can be identified using aggregate data. My empirical result shows that a constant hazard function is easily rejected by the...

Whelan (2007) found that the generalized Calvo-sticky-price model fails to replicate a typical feature of the empirical reduced-form Phillips curve - the positive dependence of inflation on its own lags. In this paper, I show hat it is the 4-period-Taylor-contract hazard function he chose that...

This paper presents an approach to identify aggregate price reset hazards from the joint dynamic behavior of inflation and macroeconomic aggregates. The identification is possible due to the fact that inflation is composed of current and past reset prices and that the composition depends on the...

This paper demonstrates that tractability gained from the Calvo pricing assumption is costly in terms of aggregate dynamics. I derive a generalized New Keynesian Phillips curve featuring a generalized hazard function, non-zero steady state inflation and real rigidity. Analytically, I find that...

The analysis of return series from financial markets is often based on the Peaks-over-threshold (POT) model. This model assumes independent and identically distributed observations and therefore a Poisson process is used to characterize the occurrence of extreme events. However, stylized facts...

We propose a local adaptive multiplicative error model (MEM) accommodating timevarying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time....