Dokumentation og international benchmarking af bygge - Danmarks ...

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detached houses. Also in Sweden, the building price index for dwellings ispublished quarterly.Development in thecountryDevelopment of output price index new detached houses in Norway(2000 = 100)Development of output price index building price index for dwellings inSweden (1968=100)Sources of errors and uncertaintyHow many variables toinclude in the modelTwo important questions arise with regard to calculating hedonic pricefunctions. Which characteristics should the function possess, and whichform of function should be chosen. Choosing the type of function is alsoan empirical question. Statistics Norway tries to limit the number of variablesto those that <strong>af</strong>fect the estimation in order to avoid autocorrelation.95
They use the t-value as a guideline whether to use the variables in themodel or not. The t-value should not be less than ±2. Another guideline isto look at the sign of the variable: The sign must be in accordance to theexpected sign. In addition, Sweden states that they try to limit the numberof explanatory variables.Weaknesses with themodelThe main weakness with the hedonic method is that it does not capture allquality improvements. Hence, the hedonic method will, to some extent,tend to overestimate the increase in prices when construction quality isimproving.One weakness with the estimation is the relatively low r-square value(which provides a measure of how well outcomes are likely to bepredicted by the model). In Norway, the r-square value of the estimationis only 0.3 = 30%, which is not considered very high. In Sweden the r-square has varied over time, it has varied within the range 0,20-0,73.Generally, the r-square has been higher for multi-dwelling buildings,compared to one and two-dwelling buildings.Statistics Norway has also commented that it is a challenge to follow upon changes in the building industry e.g. introducing new concepts forwarming up houses etc. If the quality changes are not fully incorporated inthe model, part of the price variation may be explained by quality improvementsand hence the index gets misleading.Sweden, on the other hand, has experienced a rising concern since thenumber of new dwellings has gone down to very low levels in recentyears. This may disturb the stability in the estimations and thus randomfluctuations may occur more easily. It is important that the estimations arerather stable and volatile random fluctuations question the model’s reliability.Measurement andprocessing errorsFor Norway, because of registration delays in GAB, not all detachedhouses registered as completed during the quarter in question are actuallycompleted during this quarter. Average delay measured in 2005 was 1.2months.Concerning the Swedish index the calculation of the multi-dwellingbuildings index (which is included in the Building price index for dwellings)for 1995-2006 is uncertain because of the small number of projects.Further, the number of building permits vary greatly between the years,which contribute to variations of the Building price index for dwellings.In Sweden, the reported cost is the price the investor has to pay for amulti-dwelling building or a collectively built one-or-two-dwelling buildingbased on the tender/contract amount, when available. When this isnot available, the price is based on estimate and this is a potential problemsince it might be hard for the investor to compute an accurate estimate.96
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Dokumentation og internationalbench
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1. Indledning1.1. Baggrund og form
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2. Sammenfatning2.1. Baggrund og fo
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stedet at anvende regnskabsstatisti
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ATP-oplysningerne er korrelerede me
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øget fokus og straf på kommuner,
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3.1.3.2. Byggeomkostningsindeks 2Ud
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Den centraleproblemstillingDet cent
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3.2. Outputprisindeks for bygge- og
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PriserHvad er udfordringen?De prise
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elle byggemetode. For det andet ska
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Hovedpunkterne i tilbagemeldingen v
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Løbende og faste priserDer er foku
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ner af variable og erhverv (bl.a. o
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underentrepriser udelades (da de ik
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Faste priserDet bedst mulige estima
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4. BilagBilag 3.1.1.Beskæftigede v
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4) Andet bygnings- og anlægsarbejd
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DataVægtgrundlaget erbaseret på f
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Figur 1Påbegyndte boliger, første
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Bilag 3.1.4.Dokumentation af beregn
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slutningen for tidsperioden med byg
Page 45 and 46: Tabel 3. Reparation og vedligeholde
Page 47 and 48: A.III. Sort bygningsreparation [H45
Page 49 and 50: Tabel 5: Deflatorer til produktions
Page 51 and 52: Optimal bestemmelse af alle variabl
Page 53 and 54: erne for udvælgelsen (demografisk,
Page 55 and 56: systemer. Der bruges nu særdeles r
Page 57 and 58: Bilag 3.1.7.Byggevirksomhed, intern
Page 59 and 60: Holland: Der gennemføres en eller
Page 61 and 62: Andre initiativerOffentliggørelses
Page 63 and 64: Bilag 3.1.8.International benchmark
Page 65 and 66: samlede investeringsomfang på erhv
Page 67 and 68: Ud over ovennævnte hovedtyper find
Page 69 and 70: Germany:• The German National Ban
Page 71 and 72: Construction totalOutput price inde
Page 73 and 74: • VAT and other sales taxes shoul
Page 75 and 76: It is very difficult to make one ge
Page 77 and 78: nents. In Germany, reporting of the
Page 79 and 80: Germany:There are three cases to be
Page 81 and 82: Office building 11% 26,4%Dwellings
Page 83 and 84: Itfbrtpfbr= × 100t 0pfbrIndex of c
Page 85 and 86: ConstructionType cRegionaleweights
Page 87 and 88: PlasteringPlastering work (internal
Page 89 and 90: Bilag 3.2.2.International experienc
Page 91 and 92: Bilag 3.2.3.International experienc
Page 93 and 94: In order to calculate the price lin
Page 95: the usual definition of an output p
Page 99 and 100: Bilag 3.2.4.Output price index for
Page 101 and 102: Figure 1.Conceptual frame: Construc
Page 103 and 104: The representativity of the constru
Page 105 and 106: Matched model methodHedonics method
Page 107 and 108: Bilag 3.2.5.Fra: Finn Bo FrandsenTi
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