An Econometric Analysis of Some Models for Constructed Binary Time Series
نویسندگان
چکیده
Macroeconometric and nancial researchers often use binary data constructed in a way that creates serial dependence. We show that this dependence can be allowed for if the binary states are treated as Markov processes. In addition, the methods of construction ensure that certain sequences are never observed in the constructed data. Together these features make it di¢ cult to utilize static and dynamic Probit models. We develop modelling methods that respects the Markov process nature of constructed binary data and explicitly deals with censoring constraints. An application is provided that investigates the relation between the business cycle and the yield spread.
منابع مشابه
Forecasting Residential Burglary*
Following the recent work of Dhiri et al(1999) at the Home Office predicting recorded burglary and theft for England and W ales to the year 2001, econometric and time series models have been constructed for predicting recorded residential burglary to the same date. A comparison between the Home Office econometric predictions and the less alarming econometric predictions made in this paper ident...
متن کاملFunctional-Coefficient Autoregressive Model and its Application for Prediction of the Iranian Heavy Crude Oil Price
Time series and their methods of analysis are important subjects in statistics. Most of time series have a linear behavior and can be modelled by linear ARIMA models. However, some of realized time series have a nonlinear behavior and for modelling them one needs nonlinear models. For this, many good parametric nonlinear models such as bilinear model, exponential autoregressive model, threshold...
متن کاملCombination of Transformed-means Clustering and Neural Networks for Short-Term Solar Radiation Forecasting
In order to provide an efficient conversion and utilization of solar power, solar radiation datashould be measured continuously and accurately over the long-term period. However, the measurement ofsolar radiation is not available to all countries in the world due to some technical and fiscal limitations. Hence,several studies were proposed in the literature to find mathematical and physical mod...
متن کاملTime series forecasting of Bitcoin price based on ARIMA and machine learning approaches
Bitcoin as the current leader in cryptocurrencies is a new asset class receiving significant attention in the financial and investment community and presents an interesting time series prediction problem. In this paper, some forecasting models based on classical like ARIMA and machine learning approaches including Kriging, Artificial Neural Network (ANN), Bayesian method, Support Vector Machine...
متن کاملA new approach to detect Life threatening cardiac arrhythmias using Sequential spectrum of Electrocardiogram signals
This study evaluates the discriminative power of sequential spectrum analysis of the short-term electrocardiogram (ECG) time series in separating normal and subjects with life threatening arrhythmias like, ventricular tachycardia/fibrillation (VT/VF). The raw ECG time series is transformed into a series of binary symbols and the binary occupancy or relative distribution of mono-sequences (i.e. ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009