Comparison of Series – Cumulative Data
səhifə 3/15 tarix 06.03.2018 ölçüsü 521 b. #44921
Comparison of Series – Monthly Data 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 Revisions to the earlier periods cannot be matched to the correct periods of time Time series from cumulative data have incorrect seasonality From Cumulative to Monthly 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.) Currently 10 countries publish time series of more than 24 observations Where is the Economy Going? 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 Development of release practices of SA Standardization of compilation and release practices would enhance quality of SA Conclusions of the Assessment Need for longer time series Historical time series to be build and maintained Backcalculation or linking in base year changes Seasonally adjusted data would enable comparison More comparable information on the service sector Review data collection techniques Introduce sampling (and allow revisions) Use administrative sources Publication policy New release practices (SA, time series, revisions) More detailed metadata Carsten Boldsen Hansen Economic Statistics Section, UNECE Overview General guidelines and quality Sources for methodology guidelines Response burden STS vs. SBS Time series Release Practices Metadata User consultation “The use by statistical agencies in each country of international concepts , classifications and methods promotes the consistency and efficiency of statistical systems at all official levels.” “The use by statistical agencies in each country of international concepts, classifications and methods promotes the consistency and efficiency of statistical systems at all official levels.” The ninth principle of The Fundamental Principles of Official Statistics in the Region of the Economic Commission for Europe , UNECE General Guidelines The Fundamental Principles of Official Statistics (UN) http://unstats.un.org/unsd/dnss/gp/fundprinciples.aspx Quality of Statistics Data Quality Assessment Framework (IMF) http://www.imf.org/external/np/sta/dsbb/2003/eng/dqaf.htm ESS quality framework (EC) http://epp.eurostat.ec.europa.eu/portal/page/portal/quality/introduction OECD quality framework (OECD) http://www.oecd.org/document/43/0,3343,en_2649_33715_21571947_1_1_1_1,00.html Handbook of Statistical Organization, The Operation and Organization of a Statistical Agency , 2003 http://unstats.un.org/unsd/dnss/hb/default.aspx The Fundamental Principles indispensable for a democratic society statistical agencies decide methods and procedures present data according to scientific standards comment on erroneous interpretation statistical agencies choose the data sources with regard to quality, timeliness, costs and burden The Fundamental Principles strictly confidentiality of individual data and use exclusively for statistical purposes statistical laws, regulations and measures to be made public coordination among statistical agencies within countries use of international concepts, classifications and methods Respondent Burden Minimizing respondent burden should be an important objective vs. cut-off sampling Dostları ilə paylaş:
