Kalman Filtering Applied to Statistical Forecasting

Morrison, G.W.; Pike, D.H.

doi:10.1287/mnsc.23.7.768

Cited by 53 publications

(20 citation statements)

References 5 publications

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“…Morisson and Pike (1977) also argue that in the case that the estimated coefficients do not vary over time, the Kalman filter and the least squares approach are expected to produce similar results. However in the presence of parameter instability, the Kalman filter can be proven superior to the least squares model (Morisson and Pike, 1977).…”

Section: General Issuesmentioning

confidence: 97%

The evolution of price elasticity of electricity demand in South Africa: A Kalman filter application

Inglesi‐Lotz

2011

Energy Policy

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a b s t r a c tIn South Africa, the electricity mismatch of supply and demand has been of major concern. Additional to past problems, the 2008 electricity crisis made the solution crucial after its damaging consequences to the economy. The disagreement on the need and consequences of the continuous electricity price hikes worsens the situation.To contribute to the recent electricity debate, this paper proposes a time-varying price elasticity of demand for electricity; the sensitivity of electricity consumption to price fluctuations changes throughout the years. The main purpose of this study is the estimation of the price elasticity of electricity in South Africa during the period 1980-2005 by employing an advanced econometric technique, the Kalman filter.Apart from the decreasing effect of electricity prices to consumption (À 71.8% in the 1990s and À 94.5% in the 2000s in average), our results conclude to an important finding: the higher the prices (for example in the 1980s) the higher the sensitivity of consumers to price fluctuations.Thus, further increases of the electricity prices may lead to changes in the behaviour of electricity consumers, focusing their efforts on improving their efficiency levels by introducing demand-side management techniques or even turning to other sources of -cheaper -energy.

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Section: General Issuesmentioning

confidence: 97%

The evolution of price elasticity of electricity demand in South Africa: A Kalman filter application

Inglesi‐Lotz

2011

Energy Policy

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“…has been suggested by Morrison and Pike (1977) and others (cf. Kendall (1973)) that the KF model provides an appropriate setting within which to parametrize smoothing and forecasting problems.…”

Section: Introductionmentioning

confidence: 52%

Bootstrapping Nonlinear Least Squares Estimates in the Kalman Filter Model.

Stoffer¹

1986

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“…First, this approach is considered an ideal model for estimating regressions with variables whose impact changes over time (Slade, 1989). Second, the Kalman filter is believed to be superior to the least squares models, especially in the presence of parameter instability (Morisson and Pike, 1977). Third, this procedure can be used with non-stationarity data and it is predictive and adaptive (Inglesi-Lotz, 2011).…”

Section: Kalman Filter Estimation Strategymentioning

confidence: 99%