UNECE Workshop on Short-Term Statistics (STS) and Seasonal Adjustment 14 – 17 March 2011, Astana, Kazakhstan Challenges & Problems of ShortTerm Statistics (STS) Based.
Download ReportTranscript UNECE Workshop on Short-Term Statistics (STS) and Seasonal Adjustment 14 – 17 March 2011, Astana, Kazakhstan Challenges & Problems of ShortTerm Statistics (STS) Based.
UNECE Workshop on Short-Term Statistics (STS) and Seasonal Adjustment 14 – 17 March 2011, Astana, Kazakhstan Challenges & Problems of ShortTerm Statistics (STS) Based on the UNECE paper on Short-Term Economic Statistics in the CIS and Western Balkans Carsten Boldsen Hansen Economic Statistics Section, UNECE March 2011 UNECE Statistical Division 1 Agenda 1. 2. 3. 4. 5. 6. Introduction Availability of STS Publication policy Data collection and compilation of time series Seasonal adjustment Conclusions March 2011 UNECE Statistical Division 2 Introduction A survey on seasonal adjustment in 2008 Challenges with STS were analyzed in 2007 and 2009 via web sites of NSOs on: Consumer price index Producer price index Producer price index for services Industrial production index Retail trade turnover Turnover of services Volume of services production Wages and salaries March 2011 UNECE Statistical Division 3 Introduction Countries included in the assessment: Albania Armenia Azerbaijan Belarus Bosnia and Herzegovina Georgia Kazakhstan Kyrgyzstan Republic of Moldova March 2011 Montenegro Russian Federation Serbia Tajikistan The former Yugoslav Republic of Macedonia Turkmenistan Uzbekistan Ukraine UNECE Statistical Division 4 Introduction What constitutes international comparability in STS? Coverage Classifications Methodological and computational practices Provision of fixed based and/or discrete time series Provision of long coherent time series Provision of seasonal adjusted series Dissemination of documentation March 2011 UNECE Statistical Division 5 Availability of Time Series Number of countries Availability of time series with more than six observations 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 2007 2009 Consumer Price Index March 2011 Industrial Production Index Producer Price Index Wages and Salaries UNECE Statistical Division Retail Trade Turnover 6 Availability of STS on Services March 2011 UNECE Statistical Division 7 Availability of STS on Services Share of services (incl. trade) in GDP: • Lack of data for services • Problems for estimating GDP 8/17 countries publish wages and salaries Output indicators rarely produced 52% 1996 -> 57% 2008 (in the EECCA countries) 7 countries publish turnover or volume of services Indicators do not cover the whole service sector Indicators limited to transport, hotels and restaurants March 2011 UNECE Statistical Division 8 Availability Number of countries Availability of short-term indicators for services (2009) 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 Wages and Salaries March 2011 Number of Employees Turnover in Services Volume of Services Price Information for Services UNECE Statistical Division 9 Publication Policy Issues Almost all countries publish advance release calendars • A huge step forward in just a few years Most countries archive releases to websites Time series not easily accessible Few countries have a published revision policy Metadata have been improved Timeliness of releases is often very good March 2011 UNECE Statistical Division 10 Timeliness The average timeliness of STS indicators March 2011 UNECE Statistical Division 11 Publication of Metadata 15 of 17 surveyed countries provide some methodological information in English • Countries subscribing to IMF’s SDDS or GDDS have more comprehensive set of metadata For statistics not included in SDDS/GDDS • • Very little data for retail trade and services Many details regarding production methods not available in English March 2011 UNECE Statistical Division 12 Publication Methodology Revisions are a necessary feature of STS Data are rarely published in time series format • • Instead data for a few months is published Seasonally adjusted data can only be published as long time series Only half of the countries publish indices with a fixed reference period Change from previous period should only be calculated from seasonally adjusted data! March 2011 UNECE Statistical Division 13 Methodology and Comparability Number of countries Production of STS according to international standards (2009) 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 fixed base indices for some indicator March 2011 internationally comparable classification seasonally adjusted statistics UNECE Statistical Division value added tax data used for statistics 14 Data Collection Methodology Many have cut-off samples or totals • Over sampling for some countries and indicators? Some use registers to reduce sample sizes and increase efficiency Register data requires substantial IT resources and implementation of new production methods • • NSOs may have difficulties in accessing registers? May provide a solution for developing new statistics? March 2011 UNECE Statistical Division 15 Compilation Methodology Good knowledge of international standards exists Significant methodological differences exist: • Some incoherences in definitions • • • price indices, retail trade turnover, wages and salaries Definitions of turnover, wages and salaries Treatment of VAT, subsidies and delivery costs Need to standardize definitions also in the EU Almost all countries use internationally comparable classifications for economic activities (ISIC/NACE) March 2011 UNECE Statistical Division 16 Time Series Methodology Production of cumulative data Suitable for national use only Summarizes development during the current year • • When data are available for April -> information is provided from January to April Length of the reference period changes with each release (Jan-Feb > Jan-Mar > Jan-Apr…) Cumulative data are usually only additional information, not the only type of data • A huge step forward: done by a majority of countries March 2011 UNECE Statistical Division 17 Comparison of Series – Cumulative Data Industrial Production and Production of Electricity in Belarus 115 110 105 100 95 90 85 Jan-Dec Jan-Nov Jan-Oct Jan-Sep Jan-Aug Jan-Jul Jan-Jun Jan-May Jan-Apr Jan-Mar Jan-Feb 2008 2009 industry March 2011 Jan Jan-Dec Jan-Nov Jan-Oct Jan-Sep Jan-Aug Jan-Jul Jan-Jun Jan-May Jan-Apr Jan-Mar Jan-Feb 80 Jan cumulative index from the corresponding period of the previous year 120 electricity Not easy to say which industry is doing better – UNECE Statistical Division year visible only the change from previous 18 Comparison of Series – Monthly Data Industrial Production and Production of Electricity in Belarus 130 120 index 2008=100 110 100 90 80 70 60 50 industry March 2011 Dec-09 Nov-09 Oct-09 Sep-09 Aug-09 Jul-09 Jun-09 May-09 Apr-09 Mar-09 Feb-09 Jan-09 Dec-08 Nov-08 Oct-08 Sep-08 Aug-08 Jul-08 Jun-08 May-08 Apr-08 Mar-08 Feb-08 Jan-08 40 electricity Seasonality interferes in comparing monthly data – Statistical Division seasonalUNECE adjustment needed 19 Time Series Methodology Problems with cumulative data International comparison and analysis not possible Slow identification of turning points • Change from the previous period in seasonally adjusted data provides faster indications of turning points User cannot derive a correct monthly time series • • Revisions to the earlier periods cannot be matched to the correct periods of time Time series from cumulative data have incorrect seasonality March 2011 UNECE Statistical Division 20 From Cumulative to Monthly Cumulative Industrial Production Data (estimates of monthly values) 104 104 1000 104 800 103 103 600 103 103 400 102 102 200 102 102 0 101 101 Jan Jan JanJanFeb Feb JanJanMar Mar JanApr JanMay Jan- Jan-Jul JanJan- JanJun Aug Aug Jul JanJanSep Sep JanOct JanNov cumulative change from the corresponding period of the previous year cumulative changemonthly from thevalue corresponding period of the previous year 104 1200 JanDec CalculatedCalculated from cumulative from cumulative valuesCumulative values Realchange monthly value with revisions Cumulative Cumulative change change March 2011 UNECE Statistical Division 21 Time Series Methodology Fixed base indices and/or absolute values for discrete periods are recommended Time series to be linked or calculated back when base year is changed • Not to shorten the series or to leave breaks (the series should not start from its b.y.) Previous periods need to be revised to come up with reliable time series • Currently 10 countries publish time series of more than 24 observations March 2011 UNECE Statistical Division 22 Where is the Economy Going? Frequent changes of base year without links or backcalculation 130 previous year = 100 120 110 100 2005=100 2006=100 90 2007=100 2008=100 80 2009=100 70 March 2011 UNECE Statistical Division 2010m10 2010m07 2010m04 2010m01 2009m10 2009m07 2009m04 2009m01 2008m10 2008m07 2008m04 2008m01 2007m10 2007m07 2007m04 2007m01 2006m10 2006m07 2006m04 2006m01 60 23 Seasonal Adjustment SA data calculated by 11/17 countries Need for training, materials/guidelines and support on methodological and practical issues Expansion of number and length of seasonally adjusted series More metadata on SA needed for the users Development of release practices of SA Standardization of compilation and release practices would enhance quality of SA March 2011 UNECE Statistical Division 24 Conclusions of the Assessment 1. Need for longer time series • • Historical time series to be build and maintained Backcalculation or linking in base year changes 2. Improve international comparability • • Seasonally adjusted data would enable comparison More comparable information on the service sector 3. Review data collection techniques • • Introduce sampling (and allow revisions) Use administrative sources 4. Publication policy • • March 2011 New release practices (SA, time series, revisions) More detailed metadata UNECE Statistical Division 25