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The Adoption of Energy Efficiency Enhancing Technologies
Verhoef, Erik; Nijkamp, Peter - Tinbergen Institute - 1997
This paper analyses the adoption of energy-efficiency enhancing technologies by heterogeneous firms. The fact that … energy use does not only cause external environmental costs through pollution, but also directly affects the profitability of … energy use. The analysis focuses in particular on the efficiency of the market-led adoption and diffusion process under …
Persistent link: https://www.econbiz.de/10005450770
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Long Memory Dynamics for Multivariate Dependence under Heavy Tails
Janus, Pawel; Koopman, Siem Jan; Lucas, André - Tinbergen Institute - 2011
We develop a new simultaneous time series model for volatility and dependence with long memory (fractionally integrated) dynamics and heavy-tailed densities. Our new multivariate model accounts for typical empirical features in financial time series while being robust to outliers or jumps in the...
Persistent link: https://www.econbiz.de/10009386532
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A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations
Creal, Drew; Koopman, Siem Jan; Lucas, André - Tinbergen Institute - 2010
We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate...
Persistent link: https://www.econbiz.de/10008838568
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A Weak Bifurcation Theory for Discrete Time Stochastic Dynamical Systems
Diks, Cees; Wagener, Florian - Tinbergen Institute - 2006
This article presents a bifurcation theory of smooth stochastic dynamical systems that are governed by everywhere positive transition densities. The local dependence structure of the unique strictly stationary evolution of such a system can be expressed by the ratio of joint and marginal...
Persistent link: https://www.econbiz.de/10005136879
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Likelihood Functions for State Space Models with Diffuse Initial Conditions
Francke, Marc K.; Koopman, Siem Jan; Vos, Aart de - Tinbergen Institute - 2008
State space models with nonstationary processes and fixed regression effects require a state vector with diffuse initial conditions. Different likelihood functions can be adopted for the estimation of parameters in time series models with diffuse initial conditions. In this paper we consider...
Persistent link: https://www.econbiz.de/10005137120
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Spline Smoothing over Difficult Regions
Koopman, Siem Jan; Wong, Soon Yip - Tinbergen Institute - 2008
We consider the problem of smoothing data on two-dimensional grids with holes or gaps. Such grids are often referred to as difficult regions. Since the data is not observed on these locations, the gap is not part of the domain. We cannot apply standard smoothing methods since they smooth over...
Persistent link: https://www.econbiz.de/10005137304
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A General Framework for Observation Driven Time-Varying Parameter Models
Creal, Drew; Koopman, Siem Jan; Lucas, André - Tinbergen Institute - 2008
We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...
Persistent link: https://www.econbiz.de/10005209514
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An Hourly Periodic State Space Model for Modelling French National Electricity Load
Dordonnat, V.; Koopman, S.J.; Ooms, M.; Dessertaine, A.; … - Tinbergen Institute - 2008
We present a model for hourly electricity load forecasting based on stochastically time-varying processes that are designed to account for changes in customer behaviour and in utility production efficiencies. The model is periodic: it consists of different equations and different parameters for...
Persistent link: https://www.econbiz.de/10005144435
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Stock Index Volatility Forecasting with High Frequency Data
Hol, Eugenie; Koopman, Siem Jan - Tinbergen Institute - 2002
The increasing availability of financial market data at intraday frequencies has not only led to the development of improved ex-post volatility measurements but has also inspired research into their potential value as an informa-tion source for longer horizon volatility forecasts. In this paper...
Persistent link: https://www.econbiz.de/10005136957
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Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity
Martens, Martin; Dijk, Dick van; Pooter, Michiel de - Tinbergen Institute - 2004
The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility, which accommodates level shifts, day-of-the-week...
Persistent link: https://www.econbiz.de/10005137234