OECD Standardised BCI, Amplitude adjusted (Long term average=100), sa

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Data Characteristics

Data Characteristics

Unit of measure used

Unit of measure used

Index

Population & Scope

Population & Scope

Geographic coverage

Geographic coverage

The index is calculated for all the OECD countries (excluding Iceland) and for all of the BRIICS countries.

Sector coverage

Sector coverage

The standardised BCI is computed only for the manufacturing sector. Other sectors (construction, retail trade and services) are not included due to poor data availability among non-EU OECD member countries and among the OECD Non-member Economies.

The computation of the standardised indicators is based upon the availability of either the business confidence indicator (using the national definition or computed internally) or the business situation, future or current, which can be used as a proxy.

The computation of the standardised indicators is based upon the availability of either the business confidence indicator (using the national definition or computed internally) or the business situation, future or current, which can be used as a proxy.

Concepts & Classifications

Concepts & Classifications

Key statistical concept

Key statistical concept

A standardisation process entailing a period conversion, a smoothing and an amplitude-adjustment is performed on each confidence indicator in order to achieve comparability across countries and business cycles for both the OECD CLIs and the de-trended GDP. See the OECD Business Cycle Clock (http://stats.oecd.org/mei/bcc/default.html) for a cross-country comparison of these indicators.

Three steps are undertaken to standarise the indicators:

1. Periodicity

Quarterly indicators are first converted to monthly frequency. Such a conversion is achieved through linear interpolation of quarterly series followed by an alignment to the most appropriate month of the quarter. Most series are aligned to the central month of the quarter, though quarterly series based on surveys conducted in a given month of the quarter are aligned to the month itself.

2. Smoothing

In order to remove irregular roughness, seasonal adjusted series are smoothed by applying the Hodrick-Prescott filter. Fluctuations with periodicity below 6 month are cut-off, which corresponds to setting the multiplier lambda to 1. In so doing, we preserve the trend -cycle component of the time series.

3. Amplitude-adjustment

Smoothed series are adjusted to match the amplitudes of the de-trended GDP. To do so we first normalise the series by subtracting the mean of the series and dividing with its mean absolute deviation, and then rescale them by adding 100 to the result. More information on the calculation can be found at http://www.oecd.org/std/leading-indicators/45430429.pdf.

Three steps are undertaken to standarise the indicators:

1. Periodicity

Quarterly indicators are first converted to monthly frequency. Such a conversion is achieved through linear interpolation of quarterly series followed by an alignment to the most appropriate month of the quarter. Most series are aligned to the central month of the quarter, though quarterly series based on surveys conducted in a given month of the quarter are aligned to the month itself.

2. Smoothing

In order to remove irregular roughness, seasonal adjusted series are smoothed by applying the Hodrick-Prescott filter. Fluctuations with periodicity below 6 month are cut-off, which corresponds to setting the multiplier lambda to 1. In so doing, we preserve the trend -cycle component of the time series.

3. Amplitude-adjustment

Smoothed series are adjusted to match the amplitudes of the de-trended GDP. To do so we first normalise the series by subtracting the mean of the series and dividing with its mean absolute deviation, and then rescale them by adding 100 to the result. More information on the calculation can be found at http://www.oecd.org/std/leading-indicators/45430429.pdf.

Aggregation & consolidation

Aggregation & consolidation

While the Euro Area aggregate is provided by the European Commission, the remaining aggregates are computed by the Secretariat.Based on the standardised confidence indicators, zone aggregates for the business and consumer area are calculated as annually chain-linked Laspeyres indices using as weights annual GDP at current prices adjusted for PPPs. A zone aggregate is calculated if the overall weight of the available components is greater than 75%. Country weights for each individual link are the previous year's gross domestic product based on purchasing-power-parity (PPP) valuation of country GDP, in billions of current international dollar.Weights up until 1981 refer to the GDP PPP value in 1980.Country average values are calculated as the average of the country's indicator from the previous year. The linking point is February of each year.

Weights

Weights

The source of the weights data, updated twice a year in October and April, is the International Monetary Fund’s World Economic Outlook (WEO) database. The Purchasing Power Parity (PPP) estimates are produced by the International Comparisons Program (ICP). The PPP exchange rate estimates, maintained and published by the World Bank, the OECD, and other international organizations, are used by WEO to calculate its own PPP weight time series.

The index is calculated for all the OECD countries (excluding Iceland) and for all of the BRIICS countries.

The standardised BCI is computed only for the manufacturing sector. Other sectors (construction, retail trade and services) are not included due to poor data availability among non-EU OECD member countries and among the OECD Non-member Economies.

The computation of the standardised indicators is based upon the availability of either the business confidence indicator (using the national definition or computed internally) or the business situation, future or current, which can be used as a proxy.

The computation of the standardised indicators is based upon the availability of either the business confidence indicator (using the national definition or computed internally) or the business situation, future or current, which can be used as a proxy.

A standardisation process entailing a period conversion, a smoothing and an amplitude-adjustment is performed on each confidence indicator in order to achieve comparability across countries and business cycles for both the OECD CLIs and the de-trended GDP. See the OECD Business Cycle Clock (http://stats.oecd.org/mei/bcc/default.html) for a cross-country comparison of these indicators.

Three steps are undertaken to standarise the indicators:

1. Periodicity

Quarterly indicators are first converted to monthly frequency. Such a conversion is achieved through linear interpolation of quarterly series followed by an alignment to the most appropriate month of the quarter. Most series are aligned to the central month of the quarter, though quarterly series based on surveys conducted in a given month of the quarter are aligned to the month itself.

2. Smoothing

In order to remove irregular roughness, seasonal adjusted series are smoothed by applying the Hodrick-Prescott filter. Fluctuations with periodicity below 6 month are cut-off, which corresponds to setting the multiplier lambda to 1. In so doing, we preserve the trend -cycle component of the time series.

3. Amplitude-adjustment

Smoothed series are adjusted to match the amplitudes of the de-trended GDP. To do so we first normalise the series by subtracting the mean of the series and dividing with its mean absolute deviation, and then rescale them by adding 100 to the result. More information on the calculation can be found at http://www.oecd.org/std/leading-indicators/45430429.pdf.

Three steps are undertaken to standarise the indicators:

1. Periodicity

Quarterly indicators are first converted to monthly frequency. Such a conversion is achieved through linear interpolation of quarterly series followed by an alignment to the most appropriate month of the quarter. Most series are aligned to the central month of the quarter, though quarterly series based on surveys conducted in a given month of the quarter are aligned to the month itself.

2. Smoothing

In order to remove irregular roughness, seasonal adjusted series are smoothed by applying the Hodrick-Prescott filter. Fluctuations with periodicity below 6 month are cut-off, which corresponds to setting the multiplier lambda to 1. In so doing, we preserve the trend -cycle component of the time series.

3. Amplitude-adjustment

Smoothed series are adjusted to match the amplitudes of the de-trended GDP. To do so we first normalise the series by subtracting the mean of the series and dividing with its mean absolute deviation, and then rescale them by adding 100 to the result. More information on the calculation can be found at http://www.oecd.org/std/leading-indicators/45430429.pdf.

While the Euro Area aggregate is provided by the European Commission, the remaining aggregates are computed by the Secretariat.Based on the standardised confidence indicators, zone aggregates for the business and consumer area are calculated as annually chain-linked Laspeyres indices using as weights annual GDP at current prices adjusted for PPPs. A zone aggregate is calculated if the overall weight of the available components is greater than 75%. Country weights for each individual link are the previous year's gross domestic product based on purchasing-power-parity (PPP) valuation of country GDP, in billions of current international dollar.Weights up until 1981 refer to the GDP PPP value in 1980.Country average values are calculated as the average of the country's indicator from the previous year. The linking point is February of each year.

The source of the weights data, updated twice a year in October and April, is the International Monetary Fund’s World Economic Outlook (WEO) database. The Purchasing Power Parity (PPP) estimates are produced by the International Comparisons Program (ICP). The PPP exchange rate estimates, maintained and published by the World Bank, the OECD, and other international organizations, are used by WEO to calculate its own PPP weight time series.