GDP nowcasting with ragged-edge data: a semi-parametric modeling

Nowcasting Gdp in the Euro Area

This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MFVAR) approaches to model speci…cation in the presence of mixed-frequency data, e.g., monthly and quarterly series. MIDAS leads to parsimonious models based on exponential lag polynomials for the coe¢ cients, whereas MF-VAR does not restrict the dynamics and therefore can su¤er from the curse of dimensionality. But if...

Bayesian Semi-Parametric Modeling of Time-to-Event Data

Date The final copy of this thesis has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline. The multiresolution estimator, originally a wavelet-based method for density estimation, was recently extended for estimation of hazard functions. The multiresolution hazard (MRH) metho...

Semi-parametric inferences for association with semi-competing risks data.

In many biomedical studies, it is of interest to assess dependence between bivariate failure time data. We focus here on a special type of such data, referred to as semi-competing risks data. In this article, we develop methods for making inferences regarding dependence of semi-competing risks data across strata of a discrete covariate Z. A class of rank statistics for testing constancy of asso...

Estimation of Reliability with Semi-parametric Frailty Modeling of Degradation

Modeling and forecasting China's GDP data with time series models

The gross domestic product (GDP), a basic measure of an economy's economic performance, is the market value of all final goods and services produced within the borders of a nation in a year. In this paper, the features of quarterly data of China’s GDP obtained from aggregated annual data of the National Bureau of Statistics of China starting from 1962 to 2008 are studied. Testing for existing a...