Development of construction statistics

Crook, Tony; Sharp, G. R.

doi:10.1057/elmr.2010.37

Cited by 2 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Crook and Sharp (2010) and Office for National Statistics (2010a, 2010b) provide an excellent summary of the new methodology and process. Some of the important changes are as follows:…”

Section: Introductionmentioning

confidence: 99%

Orders and output in UK construction statistics: new methodology and old problems

Ive

2011

Construction Management and Economics

View full text Add to dashboard Cite

The Office for National Statistics in the UK has developed and adopted a new method for collecting and publishing construction statistics. The analysis of the revised construction new orders series and the associated new UK Department for Business, Innovation and Skills (BIS) output price index for all new construction leads to three conclusions: (1) the new indices have corrected two significant methodological errors, namely the underestimation of the number of main contractors and the underestimation of inflation by BIS output price indices for new construction; (2) the new indices addressed a concern, the orders-output 'credibility gap', in the construction output forecasting literature; and (3) care should be taken when using the revised orders series and new output price index for historic research because a 'credibility gap' exists between the two back series prior to 1990.

show abstract

“…Crook and Sharp (2010) and Office for National Statistics (2010a, 2010b) provide an excellent summary of the new methodology and process. Some of the important changes are as follows:…”

Section: Introductionmentioning

confidence: 99%

Orders and output in UK construction statistics: new methodology and old problems

Ive

2011

Construction Management and Economics

View full text Add to dashboard Cite

show abstract

“…It is unusual for a survey design to be carried forward wholesale for implementation at a faster rate; usually a design change is involved, often a change to the sample size, which affects the quality of the new series. For example, the construction output statistics produced by the Office for National Statistics changed from a sample of 12000 businesses per quarter to 8000 businesses per month in 2010 as described by Crook and Sharp (). This change would be expected to make the sampling variance of the high frequency (monthly) series higher than that of the low frequency series.…”

Section: Discussionmentioning

confidence: 99%

“…Setting Δ is important because it impacts the degree to which aliasing can adversely alter potentially interesting portions of the spectrum. How to fix Δ is covered in classic works such as Blackman and Tukey () and Brillinger () and presumes some knowledge (from physical theory, previous analyses or a pilot study) about the spectrum for different Δ. This interesting paper questions the assumption of fixing Δ.…”

Section: Discussion On the Paper By Nason Powell Elliott And Smithmentioning

confidence: 99%

Should we Sample a time Series more Frequently?: Decision Support via Multirate Spectrum Estimation

Nason

Powell

Elliott

et al. 2016

Journal of the Royal Statistical Society Series A: Statistics in Society

View full text Add to dashboard Cite

Summary. Suppose that we have a historical time series with samples taken at a slow rate, e.g. quarterly. The paper proposes a new method to answer the question: is it worth sampling the series at a faster rate, e.g. monthly? Our contention is that classical time series methods are designed to analyse a series at a single and given sampling rate with the consequence that analysts are not often encouraged to think carefully about what an appropriate sampling rate might be. To answer the sampling rate question we propose a novel Bayesian method that incorporates the historical series, cost information and small amounts of pilot data sampled at the faster rate. The heart of our method is a new Bayesian spectral estimation technique that is capable of coherently using data sampled at multiple rates and is demonstrated to have superior practical performance compared with alternatives. Additionally, we introduce a method for hindcasting historical data at the faster rate. A freeware R package, regspec, is available that implements our methods. We illustrate our work by using official statistics time series including the UK consumer price index and counts of UK residents travelling abroad, but our methods are general and apply to any situation where time series data are collected.

show abstract

Development of construction statistics

Cited by 2 publications

References 0 publications

Orders and output in UK construction statistics: new methodology and old problems

Orders and output in UK construction statistics: new methodology and old problems

Should we Sample a time Series more Frequently?: Decision Support via Multirate Spectrum Estimation

Contact Info

Product

Resources

About