Annual Balance Sheets: 2007–2022

General Information On 31 March 2017 Stats NZ published its first annual balance sheet estimates for all sectors of the economy, as at each March. The release was for balance sheets estimates for March 2007 to March 2015. These annual balance sheets are part of a wider project to improve New Zealand’s national accounts. Other stages of the project were producing: - accumulation accounts, first published on 28 June 2018, for the years ended March 2008 to 2016. - quarterly balance sheets and accumulation accounts, released from July 2021. The accumulation accounts explain movements in assets and liabilities from one balance sheet position to the next. The accounts are estimated on an annual basis for each of New Zealand’s institutional sectors, and show the accumulation of physical assets (eg houses), financial assets (eg bank deposits), and financial liabilities (eg loans). Assets and liabilities can accumulate from transactions between parties, price movements, and unintentional and exceptional events causing assets to appear or disappear (eg write off of house values due to catastrophic earthquakes). The accumulation accounts are now an integral part of the annual balance sheets series. Sources and methods for the accumulation accounts (changes in assets and liabilities) has more information. The release of balance sheet and accumulation statistics in December 2023 provided: March 2022 estimates revisions to previously published estimates (2007-2021). Revisions to the previously published estimates are due to either updated data source information or method changes to the way we derive estimates. These balance sheets are produced within the New Zealand System of National Accounts (NZSNA). The NZSNA is based on the internationally agreed standards of the System of National Accounts 2008 (SNA08) which is a statistical framework for compiling measures of economic activity. The national accounts summarise all transactions taking place in the whole economy, using consistent definitions and concepts, and present this information in an agreed structure. Data used in these estimates has been translated to SNA concepts, and then concorded into standard classifications of assets, liabilities and institutional sectors. The Statistical Classification of Financial Assets and Liabilities (SCFAL) and the Statistical Classification of Non-financial Assets (SCNFA) provide the groupings for the balance sheet categories. The Statistical Classification for Institutional Sectors (SCIS) groups units together on the basis of their principle functions, behaviour and objectives such as non-financial and financial business enterprises, general government enterprises, households and the rest of the world. These balance sheets are being developed as part of completing New Zealand’s suite of national accounts. A primary purpose of the balance sheets is to bring together various data sources with partial coverage of the economy into a full coherent picture of the assets and liabilities for the whole economy. This coherence within balance sheets and also with the other national accounts provides a complete picture of the economy. Data quality The balance sheet and accumulation account estimates have been compiled from a number of independent sources of data following internationally accepted methodology. A discussion of the data sources and potential issues can be found in the documentation below. The quality of individual estimates is improved by the process of bringing them into an integrated system which confronts them with other corresponding data. However, in some cases this confrontation raises issues about data quality that cannot be resolved or requires further work to resolve. The balance sheet project is a multi-year project which involves further compilation and analysis of NZ financial data accounts. As the project progresses further analysis of, for example, the flow of funds in the economy we expect will result in further improvements being made, resulting in revisions to the latest published estimates. In particular further work is needed to fully reconcile between the balance sheet (stock measure) and the institutional sector income and outlay accounts (flow measure), which are currently not aligned. In addition, the sum of the accumulation account flows may not reconcile with the change in balance sheet position for given reference periods. This is due to the different data sources and varying quality of data used in the compilation of the accounts, discussed in this section. In the compilation of the balance sheets we have maintained consistency with existing published sector balance sheets for the rest of the world and government sectors. In some cases further work is needed to fully reconcile these currently independent outputs. In a number of transactions the Household sector estimates are a residual. This is due to the paucity of direct data for household estimates. This is a common situation internationally which means that errors/omissions/inconsistencies in underlying data or methods are acknowledged to impact adversely on the Household sector. This is nowhere more evident than in the Household equity estimates which have been footnoted for this reason in the tables. Confrontation of data sources has been completed at the two digit level for assets and liabilities. This means that data at a more detailed level is currently of a lower quality and only some of this can be made available on request. Statistical discrepancy The statistical discrepancy is the difference between the net lending/borrowing of the capital account and the equivalent estimate from the financial account. Net lending in the capital account is an excess of capital finance over requirements for gross fixed capital formation and net purchases of non-produced non-financial assets. Net borrowing implies the existence of a borrowing requirement to finance capital acquisitions. Changes in net/lending borrowing in the capital account should be reflected in the changes in the financial assets and liabilities in the financial account. Technically the estimates should be equal. However, due to the different data sources used across the accounts a statistical discrepancy arises. Net lending/borrowing in the capital account is derived as a balancing item from the production and expenditure components of GDP, as well as saving from the income and outlay account. The financial account also derives net lending/borrowing as the balancing item and is the difference between the acquisition of financial assets and the incurrence of liabilities. However, it is derived from totally independent data sources. Data sources: Annual Enterprise Survey (AES) RBNZ central bank balance sheet RBNZ Standard Statistical Return – registered banks RBNZ Standard Statistical Return – other financial organisations (Non-bank lending institutions)) RBNZ Managed Funds Survey Crown Financial Information System (CFIS) Local Authority Census (LAC) RBNZ household balance sheet International Investment Position (IIP). 1. Annual Enterprise Survey The Annual Enterprise Survey (AES) is New Zealand’s most comprehensive source of financial statistics. It provides annual information on the financial performance and financial position of businesses operating in New Zealand. It covers around 80 percent of New Zealand’s gross domestic product (GDP). AES is a combination of sampled units for larger businesses with tax administrative data used for medium to smaller businesses. The target population is all economically significant enterprises that operate within New Zealand. The sample population is sourced from the Statistics New Zealand (Stats NZ) Business Register (BR). The BR is a database of all businesses and is organised by enterprise, kind-of-activity unit, and geographic location. The register also identifies which businesses are economically significant, and therefore available for selection in AES. The BR is structured at an enterprise level, which can have numerous subdivisions – called kind-of-activity units (KAU) – operating in different industries. KAUs are engaged in predominately one activity and have separate accounting records available. The AES population is sourced at the KAU level. Therefore in theory, data obtained is at a deconsolidated level as opposed to a consolidated level. Data obtained at this deconsolidated level is used as much as possible in order to identify counterparty information relating to financial assets and liabilities. Data compilation/processing Compilation of AES data is used at the linecode level, the lowest level of detail possible. Where possible, linecodes are translated to System of National Accounts (SNA) transaction codes. Some linecodes can be matched one-to-one with SNA codes; however, some translate to multiple codes. There are four main linecodes from AES that cannot be directly translated into SNA codes and are classed as ‘not elsewhere classified’. These are: other current assets other non-current assets other current liabilities other non-current liabilities For each sector these linecodes are allocated to an SNA code based on respondent comments in the ‘free text field’ if available, and annual reports. Thus each sector allocation may be different. Currently, the predominant instrument class allocation is to short and long term loans. In some sectors the values of these ‘not elsewhere classified’ linecodes are substantial in relation to the total assets and liabilities of the sector. Out-of-scope of AES data (IR10) As already noted above, AES only sources economically significant businesses from the BR, where economic significance relates to measures including production, sales, expenditure, and employment for GDP purposes. AES also excludes some industries due to difficulty in collecting data from respondents, of which residential property operators L671100 is the most prevalent. These significance rules, however, may not correspond to the financial position of businesses in terms of materiality. To include those industries that AES does not cover and those excluded because they are deemed economically insignificant, a supplementary data source is used. Administrative data (mainly from IR10 balance sheet information) is matched with all identified economically insignificant businesses and out-of-scope industries, and aggregated with AES data for each sector. Only two sectors, 111 Corporate business enterprises and 121 Non-corporate business enterprises, are affected. Other sectors published by AES have good coverage of all businesses. While some IR10 data is at a broad level the same methodology has been used for AES to classify to SNA08 codes. Items such as other current assets and other assets are initially coded as not elsewhere classified, before being split and allocated to SNA08 codes using other information and assumptions. Sectors using AES as the principal data source: Sector 111 Corporate business enterprises. AES is used for economically significant businesses, plus IR10 is used for units identified from the BR as economically insignificant and any out-of-scope industries. Sector 121 Non-corporate business enterprises. AES is used for economically significant businesses, plus IR10 is used for units identified from the BR as economically insignificant and any out-of-scope industries. Units within this sector are predominately sole traders, partnerships, and trusts. IR7 and IR6 data has been used to match with BR for any missing businesses. Those identified are matched with IR10 to derive assets and liabilities. For all of the following sectors AES is the principal data source: Sector 131 Non-profit business enterprises Sector 241 Other financial intermediaries excluding insurance and pension funds Sector 251 Insurance corporations Sector 271 Corporate financial auxiliaries Sector 272 Non-corporate financial auxiliaries Sector 281 Captive financial institutions Sector 4 Non-profit institutions serving households. Special note: Sector 251 Insurance corporations. The data covers assets and liabilities of both life and non-life companies. Like all other sectors and industries, the AES data is based on the balance sheets of enterprises. The insurance corporations sector is no different. In the balance sheet, the asset and liability values for Insurance, pension and standardised guarantee scheme has been conceptually adjusted to take account of the impacts of the Canterbury Earthquakes. In macroeconomic statistics, non-life insurance recoveries (arising from reinsurance) and outstanding claim liabilities of insurance companies is recorded in the period the catastrophic events (earthquakes) take place. The financial accounts of insurance companies record these positions in the periods the transaction takes place that give rise to outstanding assets and liability positions. A similar conceptual adjustment has also been made to those sectors that had an insurance exposure relating to Canterbury Earthquakes. 2. RBNZ central bank balance sheet Central bank (sector 211) data is sourced directly from table R2 Reserve Bank statistical balance sheet. While data can also be sourced through AES, AES data has a June balance date, whereas Reserve Bank data is quarterly and the March quarter is used to compile the March year annual. Items from the Reserve Bank’s central bank balance sheet have been specifically derived to conform to SNA08 concepts. In addition, we have adjusted the balance sheet item AFL05 equity and investment fund shares, to more closely reflect SNA concepts. This replaces some accounting values with values reflecting economic concepts. As a result total assets and total liabilities for sector 211 may not match the central bank R2 balance sheet totals. 3. RBNZ Standard Statistical Return - registered banks sector 221 Data from the Reserve Bank’s Standard Statistical return (SSR) for registered banks is used for this sectors assets and liabilities for the periods 2007 to 2016. From December 2016, data from the RBNZ’s new Bank Balance Sheets (BBS) became available. In the annual balance sheets, the BBS replaced the SSR as the data source for the registered banks sector from the March 2017 reference period. The BBS data concords well with the SCFAL. Debt security liabilities New Zealand banks source some of their funding from offshore via their offshore funding entities. This funding is reported in the IIP as a mix of debt securities and loans. In the national balance sheets, all this funding is classified as debt securities over the series 2007 – 16. In the IIP, this classification is applied only from March 2015. This difference in instrument classification affects the classification to instrument types of a portion of New Zealand bank’s offshore liabilities; it does not affect totals. Equity. The national balance sheets value equity at market values, which can be quite different to the net assets (assets less liabilities) concept in business accounts. The difference between market values and net assets value is allocated to the Net Worth item. This is the value of assets less liabilities less the market value of equity ‘liabilities’. Because market values are often higher than net asset values, reflecting investor confidence in future income streams for example, the Net Worth value is often negative. Hence Net Worth should not be considered equivalent to ‘net wealth’ for corporations. This differs to sectors like households, where Net Worth is an estimate of net wealth. 4. RBNZ Standard Statistical Return for other depository institutions Other financial organisations include all of the non-bank lending institutions as published by RBNZ: deposit-taking finance companies (DTFC) savings institutions non-deposit taking finance companies (NDTFC). Deposit-taking finance companies Deposit-taking finance companies are non-bank lending institutions (excluding savings institutions) with a prospectus on issue, enabling them to take deposits from the public. Data is sourced from the published RBNZ table T21 For recording purposes DTFC are included in the SCIS subsector 222 Other depository institutions (NZISC96 - 2221 Private other broad money (M3) depository organisations). Savings institutions Savings institutions are non-bank lending institutions with a prospectus on issue, enabling them to take deposits from the public. They include registered building societies and credit unions. Data is sourced from published RBNZ table T11. For recording purposes savings institutions are also included in the SCIS subsector 222 Other depository institutions (NZISC96 - 2221 private other broad money (M3) depository organisations). Non-deposit taking finance companies Non-deposit-taking finance companies are non-bank lending institutions that do not issue a prospectus or take deposits from the public. Funding for these institutions generally comes from 'wholesale' financial markets or from parent companies. Data is sourced from the published RBNZ table T31. For recording purposes NDTFC are included in the SCIS subsector 222 Other depository institutions (NZISC96 - 2311 Private other financial organisations (except insurance and pension funds)). Data compilation All three data sources are published by RBNZ as an aggregation in table T1. Thus all transactions for each data source are translated to the same System of National Accounts (SNA08) concepts. 5. RBNZ Managed Funds Survey The Managed Funds Survey (MFS) is the preferred data source for the sectors Investment funds and Pension funds and is also one of multiple sources for compiling the New Zealand international investment position (IIP) statistics. Coverage The MFS is a quarterly survey of large fund managers in New Zealand. There is also an annual survey of smaller managers. The MFS collects data based on product types managed by the managers. The product types and the relevant institutional sector that they belong to are as follows: life office funds (insurance sector, 251) KiwiSaver, and other superannuation funds (pension funds, 261) retail unit trusts, wholesale unit trusts, and cash management funds (investment funds, 231). Most of the above product types are managed as pooled investments funds. The pooled investment funds can also buy units in wholesale trusts. Some investments are managed as Individually Managed Funds (IMP), where client’s funds are not pooled but investments are individually managed. The sources of these IMP’s can be from any institutional sector. Survey Redesign In 2014 the MFS was comprehensively redesigned. The redesigned MFS captured for the first time data on the liabilities of each product type, the counterpart sector to resident assets and liabilities, data on equity and the institutional units holding the equity across the product types. In the balance sheet, the KiwiSaver and other superannuation fund data from MFS make up a significant proportion of the total estimates for the pension sector while data for the investment fund sector is made up entirely of MFS data for retail unit trusts, cash management trusts and wholesale trusts. The fund representing life offices (sector 251) in MFS is not directly used in the balance sheet. Instead, the insurance sector data is sourced from the Annual Enterprise Survey (AES). The AES insurance sector data captures both financial and non-financial assets, liabilities and equity of life insurance companies. Included within the financial assets are the investments that are managed via fund managers. 6. Crown Financial Information System (CFIS) For balance sheet statistics, central government has been split into subsectors. They are: Central government institutions excluding funded social insurance schemes (sector 311) Funded social insurance schemes (sector 312). Data source The central government institutions and funded social insurance scheme’s data is sourced from the Treasury’s CFISnet system. This is supplemented with information obtained from the annual accounts of entities that are outside CFISnet. The Government Finance Statistics (GFS) estimates produced by Stats NZ also use the same sources. Conceptual framework of balance sheet and the GFS The conceptual framework for compiling government and funded social insurance scheme sector data in the balance sheets is the System of National Accounts (SNA). The Government Finance Statistics Manual is used for compiling Government Finance Statistics (GFS). The classification of assets and liabilities in the two frameworks are fully consistent. However, the positions in financial assets and liabilities can differ due to different approaches to consolidation. To conceptually align with macroeconomic statistics and international best practice, the outstanding claims liability of ACC (sector 312) has been excluded from the balance sheet. These claims are considered contingent in nature and can be subject to change by the government. Coverage of central government institutions (sector 311) The central government institutional sector includes all core crown departments and most crown entities. Some crown entities (such as Housing New Zealand Corporation) are excluded because they operate as market entities and therefore do not fall within the scope of this sector within SNA. A market entity provides goods or services at prices that are economically significant. State-owned enterprises are public non-financial corporations and are therefore not included in the scope of the government institutions sector. They belong to the corporate business enterprises sector. The value of the equity of the market-operating crown entities and the state-owned enterprises is included as assets of central government. Funded social security scheme (sector 312) In New Zealand, the funded social security scheme subsector includes the Accident Compensation Corporation (ACC) and the Earthquake Commission (EQC). Data compilation process The data for both subsectors is compiled using a bottom-up approach using transactions for individual units. Consolidation The data for all units that fall within the central government institution subsector has been consolidated. However, transactions between subsectors is presented on a deconsolidated basis. As an example, funded social security scheme’s holdings of New Zealand government debt securities in the national balance sheet is presented as an asset of funded social security schemes and a liability of central government institutions. Whereas, in government’s accounts and in the GFS, these positions are netted out. Therefore, a direct comparison of balance sheet data for central government institutions with the government financial statement produced by the New Zealand Treasury and GFS will show differences. Reporting period The reference period for both subsectors in the balance sheet publication is at March. Note that the GFS and the financial statements of the government are on a June basis. Financial Instrument classification - The raw data for both subsectors have been aligned to SCFAL and the SCFNA to the extent possible for this release. This means that there will be differences in values for asset and liability instrument classes between the balance sheet data for these subsectors and other published data. Some of the differences are: The GFS and the government financial statement record the unfunded pension liability as item ‘retirement plan liabilities’ whereas in the balance sheet they appear within the item ‘insurance, pension and standardised guarantee scheme’. In the balance sheet, the SDR position of New Zealand equals that reported by the Reserve Bank. This differs from the value currently reported in the GFS. In GFS and in government accounts, government’s overdraft position with its bank is netted against cash and cash equivalent (assets), however, in the balance sheet, the overdraft is included as a loan liability. There is some reclassification between equity and debt securities of New Zealand Superannuation Fund’s investments in the balance sheet. Valuation A number of valuation methods are used in valuing assets and liabilities of government and funded social insurance schemes. The value of non-financial assets of central government units is based on their latest valuation or available benchmark valuations. Some large fixed assets are revalued at irregular intervals. There are some instances where the values recorded in the balance sheet differ from those in the GFS and governments financial statement. These include: Student loans – in the balance sheet student loan assets are recorded at nominal value. In the GFS and in government accounts they appear at amortised cost. Unfunded liability of the Government Superannuation Fund (GSF) – this item in the balance sheet is based on estimation that aligns with GSF’s actuarial valuation instead of the Treasury reported values in CFIS. 7. Local Authority Census (LAC) This is the preferred data source for local government sector 321. Data coverage The Local Authority Census covers the non-trading activities of local authorities. The LAC is a census of all 12 regional councils and 74 territorial authorities and includes seven museum trust boards, Auckland Transport, and Auckland Tourism, Events, and Economic Development. The LAC is available at the individual council (unit-record) level on a deconsolidated basis. The LAC aligns relatively well with the Statistical Classification for Financial Asset and Liabilities (SCFAL) and, at the total level, is consistent with the government financial statistics (GFS) outputs currently produced with the National Accounts. Data compilation process The local government sector balance sheet data is compiled using a bottom-up approach from data on individual transactions of local government units. Reporting period The LAC uses a June reference period. These values have been adjusted to a March reference period. Most commonly this is done by adding ¾ of the subsequent June annual plus ¼ of the previous June annual value. Future development of quarterly balance sheets will improve the methodology used to make this adjustment. Instrument classification The LAC uses published financial statements disclosed in annual reports of councils for financial asset and liability validation. Non-financial assets are captured in the expenditure section of the questionnaire. Improvements in the instrument classification in the balance sheets is the result of more detailed use of financial statements and alignment to the SCFAL classification. LAC data is largely limited to the level of disclosure in annual reports. The quality of reporting across local authorities is varied due to different reporting practices. Work on the instrument classification is ongoing and we expect some variations in totals across instruments. Data issues The liabilities total in the balance sheets for debt securities has been estimated using information from publicly listed debt on the NZX Debt Market (NZDX), International Investment Position (IIP) statistics, disclosure in annual reports, and information from the RBNZ. We expect this total to change as we refine the classification using the ROS database. Transactions between the Local Government Funding Agency (LGFA) and local authorities, which constitute a large portion of local government funding, are considered to be in the form of loans. This is due to the lack of tradability, the ‘pooled’ nature of the funding, and LGFA being an institutional unit in its own right. The LGFA issues debt securities in the market and these liabilities are recorded against this entity in sector 241. In the balance sheets of other sectors (sectors excluding government and households), total assets less total liabilities equals equity or shareholders’ funds. However, local government does not issue shares and does not have shareholders, so total assets less total liabilities is referred to as local government net worth. 8. Reserve Bank of New Zealand household balance sheet A household is defined as a group of persons who share the same living accommodation, who pool some, or all, of their income and wealth, and who consume certain types of goods and services collectively (refer System of National Accounts 2008, para 24.12). The household sector is sourced from the RBNZ quarterly statistics and uses the March quarter data for year-ended values from table C22. The release of the annual balance sheets by Stats NZ means that both the Reserve Bank of New Zealand and Stats NZ use the same estimates for the household sector (511). In order to maintain consistency between both organisations’ data, any revisions are introduced into their respective publications at the earliest opportunity. Up until 2015 the RBNZ household estimates were missing some items from the balance sheet. In 2015 Statistics NZ provided estimates of the following items, which have been included in subsequent publications: equity in unincorporated businesses equity in unlisted NZ businesses housing and land value housing loans. By far the most significant of these inclusions were equity in unincorporated businesses, and equity in unlisted businesses. These added considerably to the existing totals and to net worth. For housing and land and associated loans, we revised current estimates based on a narrower definition of households. To comply with SNA08 standards, we identified all business-related activity (which included rental property operation) and separated it from households. It was reclassified to the appropriate corporate or unincorporated sector. The resulting net equity was then allocated back to the household sector. The methodology in particular affected the compilation of the equity in unincorporated sector and the final housing and land and associated loan values. For the latter, the treatment of rental properties and associated loans by households were seen as separate entities from the household for compilation purposes. In effect, the household balance sheet now records only the assets and liabilities for non-rental (owner-occupied) dwellings. Rental property equity is allocated back to the household sector and is implicit in the equity in unincorporated sector. The initial publication of sector balance sheets included a new methodology for estimating the market value of unlisted corporations. This caused a large increase in the value of equity assets owned by households, compared to the RBNZ’s published household balance sheet. Bank improves household wealth statistics has more information on the methodology of these estimates. In May 2017 the Reserve Bank introduced revisions to household balance sheet statistics. Data translation As the RBNZ household balance sheet is in most part compliant with SNA08 translation, coding of items for the balance sheet is a simple one-to-one match. Missing items As acknowledged by RBNZ, some asset and liability items are still missing from the household balance sheet. These include: household assets held overseas (deposits, superannuation, property) unfunded equity in superannuation (for private sector schemes) consumer durables. Other household data sources The RBNZ household estimates are provided mostly from a macro perspective – however, the Household Economic Survey estimates household net worth (HNW) data is from a micro perspective. This is a sample survey of household financial position, conducted every three years. It provides distributional splits of HNW by income and wealth quintiles, and by demographic groupings. Some confrontation between this data and RBNZ estimates can be completed. The HNW survey has some limitations, but it has the potential to provide either another data source for validation, or for missing items. We have been particularly interested in the data relating to trusts and the value of mortgages for both owner-occupied and rental properties. HNW data also provides some insights into other items missing from the current household balance sheet. Potential items to be analysed include: valuables land consumer durables non-residential real estate (equity to flow back to household sector). HNW values have not been used directly in the household balance sheet, though there is potential to increase its use in the future. As the HNW survey is produced every three years, an indicator for annual values would need to be identified for any data sourced. However, the HNW survey provides considerable demographic and distributional information that could be used to further understand the characteristics underlying sector balance sheets. 9. International Investment Position The data source for the Rest of the World sector is the International Investment Position (IIP) statistics. These statistics are produced quarterly by Statistics NZ. Coverage and collection of IIP data The IIP data is compiled using multiple sources of data. The key source is the Quarterly International Investment Survey, covering full population units of resident banks and sample units from non-bank sectors. Data from the New Zealand Treasury and the Reserve Bank of New Zealand is also included. The data from these units cover New Zealand government debt securities held by non-residents, and New Zealand’s official reserve assets and special drawing rights with the International Monetary Fund. The Reserve Bank’s Managed Funds Survey also provides data on overseas held assets of New Zealand’s pension and investment funds. The above surveys have been designed to comply with the requirements of the latest standard classification of financial assets and liabilities (SCFAL). Data coverage issues The IIP data lacks coverage of trusts and resident household’s holding of overseas financial assets in their own custody and borrowings directly from offshore. Where a resident household’s overseas financial assets are purchased or held via a resident financial intermediary (such as a fund manager), then such investments are likely to be captured in the IIP. The IIP also lacks coverage of land and real estate investments of resident individuals abroad and non-resident individuals in New Zealand where the ownership of these assets are held in non-corporate type structures. Where a non-resident purchases real estate, they are conceptually considered to own a notional resident real estate entity. The value of the ownership in the entity equals the value of the asset purchase. The equity ownership is updated to reflect the market value of the asset over time. In the IIP the ownership of land and real estate is recorded as direct investment. Currently no estimates are made for the direct ownership of land by New Zealanders overseas and non-residents in New Zealand in the IIP. Reserve Bank’s Repository of Securities (ROS) In future, we expect to use the ROS database to validate the coverage, classification, and valuation of debt securities issued in New Zealand against data reported in the IIP. The use of this database we expect will assist reconciling data from security issuing sectors with data from security holding sectors. en-NZ