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A Monte Carlo study into time-aggregation in continuous and discrete- time hazard models

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Author Info
Frenkel ter Hofstede () (Universities of Groningen and Wageningen Department of Marketing and Marketing Research)
Michel Wedel University of Groningen
Abstract

The purpose of this study is to investigate the effect of time- aggregation in discrete and continuous-time hazard models. A Monte Carlo study is conducted in which data are generated according to underlying continuous and discrete-time processes, which data are aggregated into daily, weekly and monthly intervals. Under each of these conditions 400 datasets are generated, that vary in the parameters of the baseline hazard. These datasets are analyzed with flexible continuous-time and discrete-time proportional hazard models. The estimates of the structural parameter and of the baseline hazard, as well as the baseline hazard predicted by those estimates, seem robust to the form of the distribution of the data generation process when the time-aggregation window is small. Both estimates of continuous-time models and of discrete-time models suffer from time-aggregation, but the estimates of the discrete-time model are more sensitive to aggregation.

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Paper provided by Wageningen Agricultural University, Faculty of Economics in its series Economics Papers with number 03-96.

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Handle: RePEc:wop:wafeep:0396

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Related research
Keywords: Monte Carlo simulation Continuous-time Discrete-time Proportional hazard model Time-aggregation.

Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models
C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis
C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation

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This page was last updated on 2008-7-16.

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