Gaussian Semiparametric Estimation of Long Range Dependence

Robinson, Peter

doi:10.1214/aos/1176324317

Cited by 1,270 publications

(1,432 citation statements)

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“…Under finiteness of the fourth moment and other mild conditions, Robinson (1995) proved that: The results are very consistent with those reported in Table 1 with the parametric methods. Thus, the unit root is almost never rejected, and we only observe a few number of cases of mean reversion (d < 1) for the logged prices in Figure 2.…”

Section: Resultssupporting

confidence: 87%

“…Here we use a "local" Whittle estimate in the frequency domain, based on a band of frequencies that degenerates to zero. This method (Robinson, 1995) is implicitly defined by:…”

Section: Resultsmentioning

confidence: 99%

“…This method has the advantage that it can be implemented even in nonstationary contexts and thus, it does not require preliminary differencing in the case of nonstationary series. A semiparametric "local" Whittle method (Robinson, 1995), widely employed in empirical studies will also be implemented in the empirical section.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Modeling persistence of carbon emission allowance prices

Gil-Alana

Gracia

Gupta

2016

Renewable and Sustainable Energy Reviews

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This study reexamines the issue of persistence in carbon emission allowance spot prices, using daily data, and covering the period from 28/2/2007 to 14/05/2014. For this purpose we use techniques based on the concept of long memory accounting for structural breaks and non-linearities in the data, with both of these aspects potentially affecting the degree of persistence. Our results indicate that, while there is no evidence of non-linearity, when allowing for structural breaks, persistence of shocks to the carbon emission allowance is markedly reduced, with the same being transitory in nature for recent sub-samples.JEL classification: C22, G13, G14, Q50

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Section: Resultssupporting

confidence: 87%

“…Here we use a "local" Whittle estimate in the frequency domain, based on a band of frequencies that degenerates to zero. This method (Robinson, 1995) is implicitly defined by:…”

Section: Resultsmentioning

confidence: 99%

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Modeling persistence of carbon emission allowance prices

Gil-Alana

Gracia

Gupta

2016

Renewable and Sustainable Energy Reviews

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“…But proceeding step-by-step as in the proof of (4.8) in Robinson (1995b), the expectation of the first term of (A.14) is bounded by…”

Section: Appendix Amentioning

confidence: 93%

“…Condition C1 only differs from conditions used in the semiparametric literature that focusses on low frequencies only (see Robinson, 1995a,b) by its requirement that f be everywhere positive, which is a natural one in the present context. The first part of Condition C3 was used in the semiparametric context by Robinson (1995b), for frequencies λ in a neighbourhood of the origin, while the second part is standard in smoothed spectral density estimation.…”

Section: Condition C5mentioning

confidence: 99%

Adapting to Unknown Disturbance Autocorrelation in Regression with Long Memory

Hidalgo

Robinson

2002

Econometrica

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We show that it is possible to adapt to nonparametric disturbance autocorrelation in time series regression in the presence of long memory in both regressors and disturbances by using a smoothed nonparametric spectrum estimate in frequency-domain generalized least squares. When the collective memory in regressors and disturbances is sufficiently strong, ordinary least squares is not only asymptotically inefficient but asymptotically non-normal and has a slow rate of convergence, whereas generalized least squares is asymptotically normal and Gauss-Markov efficient with standard convergence rate. Despite the anomalous behaviour of nonparametric spectrum estimates near a spectral pole, we are able to justify a standard construction of frequency-domain generalized least squares, earlier considered in case of short memory disturbances. A small Monte Carlo study of finite sample performance is included.

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