Bank for International Settlements (BIS)

Consumer Prices

Data categorization: year-on-year changes by per cent (ratio)

The consumer price data for the most recent periods correspond to the consumer price index published by national statistical offices. Proxy indicators, such as a consumer price index with limited coverage or a retail price index, were used to extend the series backward as far as possible.

The average length of the monthly series is close to 55 years. Some annual series go back to the middle of the 19th century - or even earlier for several countries. The BIS constructed long consumer price index series by joining the series available for consecutive periods. In undertaking this work, the BIS worked in close coordination with national authorities with the aim of providing the most accurate data possible.

The BIS’s data set for consumer prices contains long monthly and annual time series for 60 countries. The average length of the monthly series is close to 55 years. [you already said this] Some annual series go back to the mid-19th century – or even earlier for several countries. [and this] For each country, the most recent data correspond to the national consumer price index published by the statistical offices. Proxy indicators, such as a consumer price index with limited coverage1 [I am assuming this is a footnote that didn't copy-paste correctly, which means this is copied text from some unreferenced source, or plagiarized. Please do not copy-paste directly unless you quote that text and in either case, cite the source.] [also, this is a direct copy of the second sentence of the first paragraph above] or the retail price index, were used to extend the series back as far as possible.

The BIS constructed the long consumer price index by joining2 [same comment as above] the series available for consecutive periods. In doing so, it has worked closely with national authorities to provide the most accurate data possible.[this is a direct copy of the last sentence of the second paragraph] The long series are rebased and presented on a monthly and annual frequency. The publication contains both the index figures with the reference period 2010 = 100 and the year-on-year percentage changes.

The BIS long series have been used, in particular, for the calculation of the published real effective exchange rate and real residential property price [define both of these] series; they are also a useful support for macroeconomic and financial stability research. Listed below [where?] are the series used to compile the BIS long series, as well as links to websites where the most recent national data can be found. Any use of the long series should be cited as follows: “Sources: National sources; BIS long consumer prices database, www.bis.org/statistics/cp.htm.”

And there is only one series in the excel you've attached - what series is that? It sounds like there are multiple CPIs in the BIS dataset. Which did you pull and why?

Credit to the private nonfinancial sector

Overview

All series on credit to the non-financial sector cover 43 economies, both advanced and emerging. They capture the outstanding amount of credit at the end of the reference quarter. Credit is provided by domestic banks, all other sectors of the economy and non-residents. In terms of financial instruments, credit covers the core debt, defined as loans, debt securities and currency & deposits.

All series are published in local currency, in US dollars and as percentages of nominal GDP.[which did you pull? there is only one series in the excel you sent] The regional aggregates as percentages of GDP are calculated based on conversion to the US dollar at market and at purchasing power parity (PPP) exchange rates.

Long series on total credit and domestic bank credit to the private nonfinancial sector

Documentation The BIS has constructed long series on credit to the private non-financial sector for 43 economies, both advanced and emerging. [repetitive] Credit is provided by domestic banks, all other sectors of the economy and nonresidents. The “private non-financial sector” includes non-financial corporations (both private-owned and public-owned), households and non-profit institutions serving households as defined in the System of National Accounts 2008[what is this? is that a report you are referencing? add a link to it or citation.]. In terms of financial instruments, credit covers loans and debt securities. The series have quarterly frequency and capture the outstanding amount of credit at the end of the reference quarter [copied from above]. Table 1[there is no table 1] below shows the list of financial instruments, borrowers and lenders covered by the series.

The BIS consulted its member central banks in this endeavour, and is very thankful for the assistance received [are you writing as the BIS now?] .1 [looks like an unformatted footnote from a copy-paste again] The BIS has made every reasonable effort to ensure that the long series on credit are accurate, but no guarantees are made.

To encompass as long a period as possible, the construction of the long series required combining data from several sources, such as the financial accounts by institutional sector, the balance sheets of domestic banks, international banking statistics, and the balance sheets of non-bank financial institutions. In turn, some of these statistics were compiled in past periods according to earlier methodological frameworks (eg the System of National Accounts 1968, which was replaced by the System of National Accounts 1993). Where original data were published at annual frequency, the intra-annual observations were interpolated.

The combination of different sources and data from various methodological frameworks resulted in breaks in the series. The BIS is therefore, in addition, publishing a second set of series adjusted for breaks, which covers the same time span as the unadjusted series. The break-adjusted series are the result of the BIS’s own calculations, and were obtained by adjusting levels through standard statistical techniques described in the special feature on the long credit series of the March 2013 issue of the BIS Quarterly Review. Since September 2015 data are also available in US dollars and as a percentage of GDP. [is that the data we pulled? the break-adjusted series?]

The data for each country include (i) credit to private non-financial sectors by domestic banks and (ii) total credit to private non-financial sectors. Moreover, for most countries, total credit is broken down into (iii) credit to non-financial corporations and (iv) credit to households and non-profit institutions serving households. [so which did you pull?] Tables 2 and 3 below [where?] contain more information about the methodology followed in the compilation of each time series, as well as links to websites where the most recent national data can be found. For more information, see the above-mentioned article about the long credit series.

Since March 2016, the BIS has added the regional aggregates in the data set. Four aggregates are available: G20, advanced economies, emerging market economies and all reporting economies.2 [same comments as above] The data in billions of US dollars are calculated using market exchange rates and the percentages of GDP are calculated based on conversion to US dollars at market and at purchasing power parity (PPP) exchange rates.

This data set on credit to private non-financial sectors combined with the one on general government debt can provide a useful picture of the aggregated indebtedness of all non-financial sectors.[sounds good, but we only pulled, it looks like, one series, and it's unclear what that series is]

Debt service ratios for the private non-financial sector

General overview

The BIS publishes debt service ratios (DSR) for the household, the non-financial corporate and the total private non-financial sector (PNFS) for 17 countries. [so we pulled the household and the total private non-financial sector data but not the "nonfinancial corporate" series? why?] Total PNFS DSRs are also available for 15 additional countries, using different income and interest rates measures, due to data availability at the national level [what does this mean? there are 32 countries with data for PNFS?]

The DSR reflects the share of income used to service debt and has been found to provide important information about financial-real interactions. For one, the DSR is a reliable early warning indicator for systemic banking crises. Furthermore, a high DSR has a strong negative impact on consumption and investment. The DSRs are constructed based primarily on data from the national accounts.

Data documentation The debt service ratio (DSR) is defined as the ratio of interest payments plus amortisations to income.

As such, the DSR provides a flow-to-flow comparison – the flow of debt service payments divided by the flow of income. To derive the DSR on an internationally consistent basis, the BIS applies a unified methodological approach and uses, as much as possible, input data that are compiled on an internationally consistent basis. The data inputs are reviewed in this note, and country specific details are provided in the [non-existent] tables at the end of the document. Drehmann et al (2015) [there is no citation for this reference] explain the key concepts underlying the compilation of the series, and discuss the economic rationale and the robustness of the series in greater detail.

Methodology The methodology follows the approach used by the Federal Reserve Board to construct DSRs for the household sector (Dynan et al (2003)).2 It starts with the basic assumption that, for a given lending rate, debt service costs – interest and amortisations – on the aggregate debt stock are repaid in equal portions over the maturity of the loan (instalment loans). The justification for this assumption is that the differences between the repayment structures of individual loans will tend to cancel each other out in theaggregate.3 Using a number of simulations, Drehmann et al (2015) show that this indeed seems to be the case. By using the standard formula for calculating the fixed debt service costs of an instalment loan and dividing it by income, the DSR for sector j at time t is calculated as denotes the total stock of debt, Yj,t denotes quarterly income, ij,t denotes the average interest rate on the existing stock of debt per quarter and sj,t denotes the average remaining maturity in quarters. [looks like there's supposed to be an equation here that's referenced, but there is none]

The non-linearities in the instalment loan formula can generate an approximation error when aggregate data are used. However, this approximation error turns out to be relatively independent of average interest rates, debt-to-income ratios or maturities (Drehmann et al (2015). Thus, the methodology should correctly capture how the DSR in a particular country changes over time, even if it does not necessarily accurately measure its level relative to what one could obtain from the correct micro data.

For practical purposes, the difficulties in pinpointing the level imply that it is most meaningful to compare DSRs over time – by, for instance, removing country-specific means.

Sectors DSRs are derived for the household sector, non-financial corporations (NFCs) and the total private non-financial sector (PNFS).

Frequency DSRs are compiled at quarterly frequency.

Data The ratio uses input data from the national accounts, as detailed below (...). If these data are not available, alternative sources are used. Stock of debt: [<= Is that a definition?] Debt is defined as credit (in terms of loans and debt securities4) from all sources to the PNFS, as compiled by the BIS. This includes information for the household and NFC sectors.

Average interest rate on the existing stock of debt: To accurately measure aggregate debt servicing costs, the interest rate has to reflect average interest rate conditions on the stock of debt, which contains a mix of new and old loans with different fixed and floating nominal interest rates attached to them.

The average interest rate on the stock of debt is computed by dividing gross interest payments plus financial intermediation services indirectly measured (FISIM) by the stock of debt. FISIM is an estimate of the value of financial intermediation services provided by financial institutions. When national account compilers derive the sectoral accounts, parts of interest payments are reclassified as payments for services and allocated as output of the financial intermediation sector. In turn, this output is recorded as consumption by households and NFCs. As the aim is to identify the total burden of interest payments on borrowers regardless of their economic function, FISIM is added back to interest payments reported in the national accounts to derive effective interest payments.

Income: Income in this context corresponds to the amount of money available to economic agents to pay debt service costs. Gross disposable income (GDI) is a close approximation. GDI measures the income available to households and NFCs after interest payments and, in the case of NFCs, dividends. Hence, to accurately reflect the amount of money available to service debt, GDI has to be augmented by interest payments (and dividends for the NFCs). 4 Excluding SDR allocations, deposits and other accounts receivable, which include trade credits.3 GDI complemented with these other items is called “augmented GDI”. Below is the definition of augmented GDI for each sector.

Household sector: Augmented GDI is equal to GDI plus interest payments excluding FISIM (item D41) [what does "item D41" mean? and is this the definition of the "household sector" or the way "augmented GDI" is calculated for the household sector?]. FISIM is not added to augmented GDI for the household sector because it is not considered an element of intermediary consumption and is therefore not deducted from the various types of income households earn to get GDI. FISIM is a service that is included in final consumption.

NFC sector: Augmented GDI is equal to GDI plus interest payments including FISIM(item D41g) [and same comment as above] and distributed income (dividends). FISIM is an element of intermediate consumption, which is deducted from the various types of income NFCs earn and has to be added to GDI to reflect the income available to NFCs.

Total PNFS: The sum of the two income measures from the household and NFC sectors comprises the income of the total PNFS.5

Average remaining maturity: For the household and NFC sectors, 18 and 13 years are assumed, respectively, which is fixed across time and countries. The maturity of the total PNFS is the average of the remaining maturities of the two subsectors, weighted by the stock of debt of each sector. Data adjustments [looks like we're missing something here...]

Smoothing of some components of income: Four-quarter moving averages are applied to GDI and dividends paid.

Interpolation and extrapolation: Some data in a number of countries are originally compiled at an annual frequency. In these cases, quarterly series are derived by interpolating the annual data with the Chow-Lin method (Chow and Lin (1971)),6 using nominal GDP for GDI as well as dividends, and average bank lending rates for the average interest rate on the stock of debt.

To derive the most recent quarters following the last available annual data point, series are extrapolated using the growth rate of nominal GDP for both GDI and dividends, and the change in average bank lending rates for the average interest rate on the stock of debt.

Series used when national accounts sectoral data are not available For data from 15 countries, there is only information to construct the DSR for the total PNFS. For many of these countries, information on sectors from the national accounts is limited, and data are not available to derive average interest rates and income as detailed above. In these cases, the series are proxied as follows:

Average interest rate on the existing stock of debt [this is already above. Is this a different definition?]: The average interest rate on the stock of debt is proxied by the average lending rates on loans from depository corporations (or monetary and financial institutions (MFIs)) to the PNFS. Most of the time, these lending rates are available for the household and NFC sectors separately, and a weighted average is calculated for the total PNFS, using the stock of debt in each sector as weights.

For a few countries, no lending rates on outstanding MFI loans are available. In these cases, the average lending rate on the stock of debt is proxied by the short-term money market rate plus 2.18 percentage points – the average markup between lending rates and the money market rates across countries. In addition, a smoothing factor calibrated on a cross-country data set is applied.7 Income: The income measure for the total PNFS is proxied by the nominal quarterly GDP series. Four-quarter moving averages are applied to the raw GDP data