Australian Bureau of Statistics
5609.0 - Housing Finance, Australia, Dec 2008 Quality Declaration
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 11/02/2009
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3 All lending commitments are classified to the lender type which is (or will be) the legal lender on the corresponding loan contract. Commitments are published for two broad groupings of lender type: Banks and Non-Banks; the Non-Bank grouping also has the components Permanent Building Societies and Wholesale Lenders n.e.c. published.
4 Housing loan outstandings are classified to the following lender types: Banks; Permanent Building societies; Credit unions/cooperative credit societies; Securitisation vehicles; and Other lenders n.e.c.. The first three of these types are components of the grouping Authorised Deposit-taking Institutions (ADIs). Loan outstandings for the ADI lender types are published monthly, and are classified by purpose (owner occupied housing or investment housing). All other institutions, including securitisation vehicles, are only available on a quarterly basis. The release of loan outstandings data for those lenders reporting on a quarterly basis will be lagged by one month - for example March outstandings for securitisation vehicles and other lenders n.e.c. will be released from the April publication onwards.
5 The statistics of housing finance commitments cover all banks and permanent building societies. The largest of the remaining lenders of secured housing finance for owner occupation are included so that, together with banks and building societies, at least 95% of the Australian total of finance commitments is covered, and at least 90% of each state total is covered. While many smaller contributors to the Non-Banks series are excluded under these coverage criteria, at least 70% of finance commitments by wholesale contributors are covered.
6 An annual collection is conducted to maintain and update the survey coverage of housing finance commitments. New lenders are included as their lending for housing becomes sufficiently large.
7 From June 2001, the collection of housing finance commitments covers all commitments by banks and permanent building societies, all other lenders providing funds of more than $50m in 2000, and some additional smaller other lenders where necessary to maintain collection coverage (as specified in paragraph 5).
8 The statistics of housing loan outstandings cover all lenders included in the scope of paragraph 2 that have been identified as holding residential loan assets on their balance sheet as at the end of a particular reference month.
9 For banks, credit cooperatives, building societies and RFCs, the statistics in this publication are currently derived from returns submitted to the Australian Prudential Regulation Authority (APRA). The Financial Sector (Collection of Data) Act 2001 facilitates the collection of statistical data from the financial sector, with APRA established as the central point for collection of both prudential and statistical data. In October 2001, APRA implemented new reporting forms for building societies and credit cooperatives. New reporting forms were implemented for banks in March 2002, and for RFCs in March 2003. APRA commenced collecting loan commitments data from banks, credit cooperatives, building societies in July 2002 and from RFCs in March 2003.
10 Housing finance commitments for owner occupied housing from banks, building societies and credit cooperatives are derived from form ARF 392.0 Housing Finance collected by APRA. Housing finance commitments for investor housing from these lenders are sourced from the ARF 394.0 Personal Finance. Housing finance commitments for RFCs are collected on the RRF 392.0 Housing Finance and RRF 394.0 Personal Finance for owner occupied housing and investor housing respectively.
11 Statistics on loan outstandings in table 12 are sourced from banks on form ARF 320.0 Statement of Financial Position (Domestic Books), with lending by building societies and credit cooperatives derived from form ARF 323.0: Statement of Financial Position (Licensed ADI). While building societies and credit cooperatives with total assets greater than or equal to $50 million are required to report this APRA return on a monthly basis, those institutions with total assets less than this threshold are only required to submit this return on a quarterly basis. An undercoverage adjustment is made in deriving table 12 in the two months between the last month in the quarter to derive estimates for the complete population on a monthly basis.
12 Electronic versions of the forms and instructions for ADIs are available on the APRA web site at <http://www.apra.gov.au/Statistics/Basel-II-reporting-forms-and-instructions-for-all-ADIs.cfm>. For RFCs, these are available at: <http://www.apra.gov.au/rfc/>.
13 All other institutions, including securitisation vehicles, are collected directly by the ABS. Data on loan outstandings of households for housing purposes for these lender types are only available on a quarterly basis. The data for Other lenders n.e.c. is compiled from a range of other data sources collected by the Australian Bureau of Statistics.
14 Revisions to previously published statistics are included in the publication as they occur.
15 Changes in the classification of lenders (e.g. the conversion of a permanent building society to a bank) are reflected in the Lender series from the month of such change. Data for earlier periods for such lenders are not reclassified. Details of the establishment of new banks are published in the Reserve Bank of Australia’s monthly Bulletin in the section on Technical Notes to Tables.
16 A wholesale lender provides funds to borrowers through a retail intermediary which may then also be responsible for the ongoing relationship with the borrower.
17 The Wholesale Lenders n.e.c. series almost exclusively comprises securitisation vehicles (typically special purpose trusts), established to issue mortgage backed securities. It excludes commitments where a bank or permanent building society, acting as a wholesale provider of funds, is the lender on the loan contract. Those commitments are published as bank or permanent building society commitments.
18 From July 1995 to July 2000, mortgage managers reported housing finance commitments on behalf of wholesale lenders. The introduction of wholesale lenders as the reporting unit does not change the scope of the collection, but has increased its coverage. This, along with the reclassification of some lending activity, increased the level of the Wholesale Lenders n.e.c. series for owner occupied housing by $249m in July 2000.
19 Wholesale lenders contribute to the Non-Banks series for owner occupied housing, which is seasonally adjusted in table 3. A trend break was added to the Non-Banks series, shifting the trend up by 1,579 commitments and $178m in July 2000. Revisions related to the introduction of wholesale lenders also resulted in a downward shift in the Banks' trend for owner occupied housing of 1,256 commitments and $167m. Consequential breaks in the finance purpose trend series for owner occupied housing at July 2000 were:
20 Because of difficulties experienced by Wholesale Lenders n.e.c. in accurately identifying first home buyers in their commitments, these data are not used in estimating first home buyer commitments (table 9). Instead, from July 2000, the percentage of first home buyer commitments made by all banks and permanent building societies is applied to total Wholesale Lenders n.e.c. commitments to calculate their contribution to the First Home Buyers series. As a result, first home buyer commitments were revised upwards by 0.8 percentage points in July 2000.
21 An article on the introduction of the Wholesale Lenders n.e.c. series (including implications for the First Home Buyers series) featured in the October 2000 issue of this publication. A copy of the article is available from the contact person listed on the front of the publication.
22 Seasonal adjustment is a means of removing the estimated effects of normal seasonal variation and ‘trading day effects’. A ‘trading day effect’ reflects the varying amounts of activity on different days of the week and the different number of days of the week in any month (i.e. the number of Sundays, Mondays, etc.). This effect may be partly caused by the reporting practices of the lenders. Adjustment is also made for Easter which may affect the March and April estimates differently. Trading day effects are removed from the original estimates prior to the seasonal adjustment process. Seasonal adjustment does not remove the effect of irregular or non-seasonal influences (e.g. a change in interest rates) from the series.
23 Over the period from early 1990 to April 1995, four of the major banks changed from reporting for the four or five weeks ending on the last Wednesday of each month to reporting on a calendar month basis. The published seasonally adjusted data take account of this change in pattern.
24 Rapid change in the financial sector, and particularly developments in the provision of housing finance, may cause changes in the seasonal and trading day patterns of the housing finance data. Examples include changes in the classification of financial institutions (particularly the reclassification of non-bank financial institutions to banks) and the increased use of mortgage securitisation.
25 Estimation of seasonal adjustment and trading day factors that reflect the full effect of recent developments is not possible until a sufficient number of years of data have been collected. When changes are occurring in the seasonal patterns, larger revisions to the seasonally adjusted series can be expected at the time of the annual seasonal re-analysis. Accordingly, the trend estimate data provide a more reliable indicator of underlying movement in housing finance commitments. (See paragraphs 30 and 31 for further information on trend estimates).
26 State component series have been seasonally adjusted independently of the Australian series. The sum of the state components is therefore unlikely to equal the corresponding Australian total. State component series are also affected by the changes mentioned in paragraphs 22 to 25.
27 The housing finance series uses a concurrent seasonal adjustment methodology to derive the seasonal adjustment factors. This means that original estimates available at the current reference month are used to estimate seasonal factors for the current and previous months. As a result of this methodology, the seasonally adjusted and trend estimates for earlier periods can be revised each month. However, in most instances, the only noticeable revisions will be to the previous month and the same month a year ago.
28 Autoregressive integrated moving average (ARIMA) modelling can improve the revision properties of the seasonally adjusted and trend estimates. ARIMA modelling relies on the characteristics of the series being analysed to project future period data.The projected values are temporary, intermediate values, that are only used internally to improve the estimation of the seasonal factors. The projected data do not affect the original estimates and are discarded at the end of the seasonal adjustment process. The housing finance collection uses an individual ARIMA model for 96% of the series in this publication.The ARIMA model is assessed as part of the annual reanalysis. For more information on ARIMA modelling see Feature article: Use of ARIMA modelling to reduce revisions in the October 2004 issue of Australian Economic Indicators (cat. no. 1350.0).
29 The best seasonally adjusted estimates are achieved only some years after corresponding original estimates have been released. However, this does not satisfy the demand for timely seasonally adjusted estimates. The ABS advises users that while every effort is made to achieve the highest possible quality of seasonally adjusted estimates, given the available original estimates and preset publication deadlines, revisions to these seasonally adjusted estimates are inevitable and generally indicate improvements to those estimates. The use of the concurrent seasonal adjustment approach means that revisions, and therefore quality improvements, are identified earlier than under the previously used forward factor method. Under the concurrent approach, revisions are made up to one year earlier than under the forward factor approach.
30 Smoothing seasonally adjusted series reduces the impact of the irregular component of the seasonally adjusted series and creates trend estimates. These trend estimates are derived by applying a 13-term Henderson-weighted moving average to all but the last six months of the respective seasonally adjusted series. Trend series are created for the last six months by applying surrogates of the Henderson moving average to the seasonally adjusted series. For further information, refer to Information Paper: A Guide to Interpreting Time Series - Monitoring Trends: An Overview (cat. no. 1349.0) or contact the Assistant Director, Time Series Analysis on Canberra (02) 6252 6345 or by email at <email@example.com>.
31 While the smoothing technique described in paragraph 30 enables trend estimates to be produced for the latest few months, it does result in revisions to the trend estimates as new data become available. Generally, revisions become smaller over time and, after three months, usually have a negligible impact on the series. Changes in the original data and re-estimation of seasonal factors may also lead to revisions to the trend.
EFFECTS OF ROUNDING
32 Where figures have been rounded, discrepancies may occur between sums of the component items and totals. Percentage changes and averages presented in the commentary are based on unrounded data and may differ slightly from percentage changes and averages calculated from the rounded data presented in the tables in this publication.
ABS DATA AVAILABLE ON REQUEST
33 Estimates for months prior to those shown in this publication and more detailed series are available in spreadsheet format from the ABS web site - see listing on pages 3 and 4. For more information, contact the ABS National Information and Referral Service on 1300 135 070.
34 Other ABS publications which may be of interest are outlined below. Please note, older publications may no longer be available through ABS bookshops but are available through ABS libraries. All publications released from 1998 onwards are available on the ABS web site <http://www.abs.gov.au>:
35 Quarterly data prior to the March 2002 for housing loan outstandings by type of lending institution are available as a priced special data report related to the Australian National Accounts: Financial Accounts (cat. no. 5232.0). Inquiries regarding this special data report should be made to the contact on the front cover of this publication.
36 In addition, the Reserve Bank of Australia produces the monthly Reserve Bank of Australia Bulletin as well as data on its web site. Bulletin tables D1 & D2 contain statistics on lending and credit aggregates (including the housing credit aggregate), which contain lending and credit to the private non-financial sector. Table D5 Bank Lending Classified by Sector contains statistics on lending to persons for the purpose of housing, also classified by owner occupiers and investors with statistics available from January 1990.
37 Residential lending by building societies and credit cooperatives is also published in Bulletin tables B7 and B8. These statistics are also sourced from APRA collected data, although this will differ to statistics in table 12 of this publication since the Bulletin tables only include data for building societies and credit cooperatives with total assets greater than or equal to $50 million. Bulletin table B.19 Securitisation Vehicles contains outstandings information for mortgages held, which includes both residential and non-residential mortgages.
38 Current publications produced by the ABS are listed in the Catalogue of Publications and Products, Australia (cat. no. 1101.0). The Catalogue is available from any ABS office or the ABS web site <http://www.abs.gov.au>. The ABS also issues a daily Release Advice on the web site which details products to be released in the week ahead.
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This page last updated 10 March 2009