About the Northern Ireland Annual Business Inquiry
The Northern Ireland Annual Business Inquiry (NIABI) collects both financial and employment information from businesses and other establishments and covers about two thirds of the economy. This includes the production, construction, distribution and service industries in Northern Ireland but excludes public sector activity for the most part.
The NIABI provides a number of high level indicators of economic activity such as the total value of sales and work completed by businesses (Turnover), the value of the purchase of goods, materials and services and total employment costs. The contribution of different industries to the overall value of economic activity can be assessed and because estimates of employment are collected at the same time it is also possible to get a measure of value added and costs per head to allow better comparison between different sized industrial sectors.
The NIABI is designed to provide the best estimates for Northern Ireland as well as providing information that is used at a later stage to inform UK National and Regional Accounts estimates.
Recent Methodological Improvements
Review of the ABI - Quality Improvement Fund Project
A number of methodological improvements were initially introduced in the production of Annual Business Inquiry results for 2008 and 2009. In order to take due account of user feedback in terms of ongoing development these statistics have therefore been described as "experimental", although they are considered to meet National Statistics standards. Also, DFP has moved to producing results using Statistics Canada’s Generalized Estimation System. This has allowed DFP to continue to produce estimates, with an associated measure of their quality.
Integration of the Annual Business Inquiry and Manufacturing Sales and Exports
Users should note that Annual Business Inquiry 2011 and Manufacturing Sales and Exports 2011/12 information will now be collected from businesses using one unified form. The below notice to users explains the rationale behind this, as well as the expected benefits:
Quinquennial Review
The Northern Ireland Statistics and Research Agency (NISRA) is required to regularly review each of its statistical surveys, with the main objective of each review being to determine the efficiency and effectiveness of all of our procedures, and to identify where improvements can be made.
Please note that a review of the Annual Business Inquiry was conducted in early 2012, with an emphasis especially on the need for the information (evaluating the reason for conducting the survey), the conduct of the survey, costs, respondent's views, users' views and options for change.
Comparability with statistics from other sources
Office for National Statistics
The NIABI is conducted by the Northern Ireland Statistics & Research Agency and while the survey process is similar to that for Great Britain, it is not identical. ONS receive data from NISRA in September and February of each survey year. These data are processed with the Great Britain data to produce UK-wide estimates as well as producing regional estimates. NISRA separately process the Northern Ireland data to produce their own regional estimates. further information on these differences can be found in the ONS ABS Technical Report at the below link.
Northern Ireland Statistics and Research Agency (NISRA)
The NIABI provides estimates of employment to enable per head calculations to be made. Preferred estimates of the changes in employment and employee jobs are provided by the Labour Force Survey (LFS) and Quarterly Employment Survey (QES). As dedicated employment surveys, the LFS and QES provide more frequent and accurate measures of the change in employment. By utilising internationally recognised definitions the LFS provides employment figures consistent with international standards.
Within the relevant sectors the turnover figures provided by the NIABI are the most up to date available from ELMSB statistical publications, and ultimately contribute to updating the Inter-Departmental Business Register (IDBR). However for a more comprehensive measure of turnover within the NI economy users are recommended to refer to the IDBR. The IDBR contains information on all businesses in the UK which are VAT registered or operate a PAYE scheme; consequently the IDBR provides a more complete picture of the Northern Ireland business population.
Definitions
Approximate Gross Value Added at Basic prices represents the income generated by businesses, out of which is paid wages and salaries, the cost of capital investment and financial charges before arriving at a figure for profit. It includes taxes on production (e.g. business rates), net of subsidies but excludes subsidies and taxes on products (e.g. VAT and excise duty). This is an output-based measure of GVA. All published GVA is given at basic prices. Please find below calculation applied to derive GVA.
The calculations used in the NIABI are:
- GVA AT BASIC PRICES: GVA at factor cost + business rates + vehicle excise duty
- GVA AT MARKET PRICES: Total turnover + insurance claims + change in stocks + own account capital expenditure – total purchases
- GVA AT FACTOR COST: GVA at market prices + subsidies – total taxes + customs & excise drawback
Turnover is defined as total sales and work done. This is calculated by adding to the value of sales of goods produced, goods purchased and resold without further processing, work done and industrial and non-industrial services rendered.
Purchases represent the value of all goods, materials and services purchased during the year.
Coefficient of Variation (CV) measures the variability of the estimates by expressing the standard error as a percentage of the parameter estimate. Unlike confidence intervals, which measure variability by providing the range of values between which the mean value for a predetermined percentage of all possible samples would fall, the coefficient of variation expresses variability as an easily comparable percentage. As the coefficient of variation is not measured in any specific unit, it facilitates comparison between surveys measuring different underlying variables. A larger coefficient of variation implies a larger variability.