Surveys on prices at the Statistical office of the Republic of Slovenia (SURS) Mojca Noč Razinger.

Slides:



Advertisements
Similar presentations
Implementation of the CoP in SLOVENIA Cooperation with data users Genovefa RUŽIĆ Deputy Director-General.
Advertisements

Session 2 : The Downturn & Irish Business Richard McMahon Central Statistics Office.
Challenges in designing mixed mode in business surveys Dr Mojca Noc Razinger, Statistical Office of the Republic of Slovenia.
28-30 April 2014UNECE - Work session on statistical data editing Data editing and scanner data I. Léonard, G. Varlet and P. Sillard Insee.
Sébastien FAIVRE INSEE Workshop on scanner data, Stockholm, /06/2012 Would scanner data improve the French CPI?
Miroslav Jankovic (Statistical Office of Serbia and Montenegro) Dragi Stojiljkovic Tatjana Stanojevic-Miladinovic (Statistical Office of the Republic of.
Fertilizer consumption: main information sources on national level and data quality assurance Prepared by Barbara Kutin Slatnar and Enisa Lojović Hadžihasanović,
Seminar on Developing a Programme on Integrated Statistics in the Caribbean Saint Lucia The Components of an Integrated Business and International Statistics.
Electronic reporting in Poland 27th Voorburg Group Meeting Warsaw, Poland October 1st to October 5th, 2012 Central Statistical Office of Poland.
Usage of new data sources at SORS Boro Nikić, Tomaž Špeh, Zvone Klun Statistical Office of the Republic of Slovenia Washington, 29 April - 1 May 2015.
Rudi Seljak, Metka Zaletel Statistical Office of the Republic of Slovenia TAX DATA AS A MEANS FOR THE ESSENTIAL REDUCTION OF THE SHORT-TERM SURVEYS RESPONSE.
Emerging methodologies for the census in the UNECE region Paolo Valente United Nations Economic Commission for Europe Statistical Division International.
Current practice of Kazakhstan on calculating of price index in the dwelling market December, , Astana Statistics Committee Of Ministry of national.
United Nations Statistics Division/DESA International Recommendations for the Index of Industrial Production (IIP)
Use of Administrative Data Seminar on Developing a Programme on Integrated Statistics in support of the Implementation of the SNA for CARICOM countries.
ECE/ILO Meeting on Consumer Price Indices, May 10-12, 2006, Geneva1 A FAMILY OF INDICES IN THE ISRAELI CPI Yoel Finkel Central Bureau of Statistics, Israel.
The Swedish experience with scanner data From sampling to index calculation Paulina Jonéus.
Renewable Energy Statistics Keep-on-Track! 1 st Policy Workshop 23 January
1 Outline  Introduction  Methodology for compiling CPI  Data Collection and Compilation.
WORKING PARTY ON NATIONAL ACCOUNTS Paris, 3-5 October 2007 The situation of QUARTERLY NATIONAL ACCOUNTS data transmission to the OECD Document STD/CSTAT/WPNA(2007)6.
CPI/HICP price collection Validation of prices Twinning project: Development of new statistical methodologies and indicators in selected areas of statistics.
M O N T E N E G R O Negotiating Team for Accession of Montenegro to the European Union Working Group for Chapter 18 – Statistics Bilateral screening: Chapter.
M O N T E N E G R O Negotiating Team for Accession of Montenegro to the European Union Working Group for Chapter 18 – Statistics Bilateral screening: Chapter.
Armenia Twinning 2011 Component F – Information Society, 2 – 6 May DEVELOPMENT OF INFORMATION SOCIETY STATISTICS IN LITHUANIA Statistics.
Measuring e-commerce - the Eurostat and OECD approach and the Statistics Finland experience Aarno Airaksinen Regional Workshop, Strengthening.
PRESENTATION OF MONTENEGRO
End Use Survey: Manufacturing, Residential and Commercial Sector
Principles and definitions of conducting Agriculture Census in Armenia
WEB SCRAPING FOR JOB STATISTICS
TEST AANKOOP/TEST ACHATS INTERNET SPEEDTEST CAMPAIGN
FUTURE EVOLUTION OF SHORT-TERM ECONOMIC STATISTICS
Marcel van Kints United Nations Statistics Division/DESA
John Loucks St. Edward’s University . SLIDES . BY.
Croatian Statistical System Presented by Robert Knežević
7th Oslo Group Meeting Riitta Pipatti and Kari Grönfors
OECD SHORT-TERM ECONOMIC STATISTICS WORKING PARTY (STESWP) MEETING
Quality Aspects and Approaches in Business Statistics
Profile of Danish enterprises with 0 employees
Recent developments in Israel Foreign Trade Statistics Methodology
Business Register Quality Improvement
Global Assessment on Tendency Surveys
SA Economic Indicators
Changed Data Collection Strategies
Development of production routines for Crime & Criminal justice statistics Arsela Sturc SOGETI.
PRODCOM-Statistics in Austria
Price Indices for External Trade of Goods Eleonora Baghy 26/05/2013
Information Society Statistics
Energy Consumption in Transport
Ag.No Price statistics briefing (a) HICP
Ag.No Price statistics briefing (b) ECP
SES 2014 IN SLOVENIA Miran Žavbi, SURS.
Main lessons learnt from the censuses in Hungary
Presentation to the Committee for Establishment of a Business Register
Data collection including specific goods Lídia Bassó
ANALYSIS OF POSSIBILITY TO USE TAX AUTHORITY DATA IN STS
Challenges in Promoting Data and Data Dissemination Policies
IMPLEMENTATION PROGRAMME OF SNA 2008 (Dominica)
The change of data sources in the Spanish SILC
« LFS series breaks with the adoption of the IESS FR How is Statistics Portugal planning to tackle the issue? 13th Workshop on Labour Force Survey Methodology.
Mapping Data Production Processes to the GSBPM
Chapter 3 INDEX NUMBERS Dr. A. PHILIP AROKIADOSS Assistant Professor
The modules of the EU Labour Force Survey
Quality Reporting in CBS
Agricultural Production Statistics Group
Hanna Gembarzewska, Monika Grabani
Towards Census 2021 in Hungary
2.7 Annex 3 – Quality reports
Karmen Hren Statistical Office of Slovenia
WORKING PARTY ON NATIONAL ACCOUNTS Paris, 4-6 November 2009
Work Session on Statistical Metadata (Geneva, Switzerland May 2013)
Presentation transcript:

Surveys on prices at the Statistical office of the Republic of Slovenia (SURS) Mojca Noč Razinger

Contents Statistical office of the Republic of Slovenia (SURS) Price statistics Consumer prices and calculated inidices and average retail prices Data collection and new data sources Open questions and conclustions

Statistical Office of the Republic of Slovenia (SURS) Publish data on www.stat.si For researchers: Secure room at SURS, Remote access and Subscription for releases Additional detailed data for researchers: methodological explanations, questionnaires All data are available in SI-STAT database http://pxweb.stat.si/pxweb/dialog/statfile1.asp

Price statistics at SURS Data type Current state of data collection Data series Retail prices and indices of goods and services Monthly data collection – price collectors with tablets and special agreements with enterprises. Data have been published monthly since 1997 and annually since 2003. Producer prices of manufactured goods Monthly data collection with self-administered questionnaire. Mix mode type of collection with parallel web and paper mode. Data have been published annually since 1954 and monthly since 2005. Services producer prices Quarterly data collection with self-administered questionnaire. Mix mode type of collection with parallel web and paper mode. Data have been published quarterly since 2006. Real estate prices   Quarterly data collection from registers and SURS data. Data have been published quarterly since 2003. Purchasing power Data from enterprises, administrative data and SURS data. Data have been published since 2007. Agricultural price statistics Monthly surveys with self-administsred paper questionnaire, secondary statistical data and registers. Annualy surveys with self- administsred paper questionnaire or based on administrative data sources. Data have been published monthly, quarterly and annualy since 2000 (for Prices and rents of agricultural land since 2013). Energy sources prices Quarterly administrative sources. Data have been published semi-annually for gas since 1995 and for electricity since 1992. In 2007 due to methodology change there is break in time data series.

Consumer prices and calculated indices and average retail prices Collected monthly for presentation of trends in the prices of goods and services Units are representative products (goods and services) Selected for the survey based on the threshold that determines the number of representative products included in the survey in an individual year. The number of the representative products has been increasing each year since 2012 Year 2010 2011 2012 2013 2014 2015 2016 2017 Nr. of representative products 666 669 663 667 684 706 711 717

Consumer prices and calculated indices and average retail prices cont. Prices are collected by price collectors Four major cities (Koper, Ljubljana, Maribor and Novo mesto) Some in other places in Slovenia, mostly by phone and via the Internet and from other databases of individual traders of goods and services. The total number of collection points is around 1,450. In recent years the variable nonresponse was around 5% and has been slightly increasing. For collecting prices by price collectors in individual months, products are classified into the groups: agricultural products (observed in the 1st and 3rd week of the month) food products (between 16th and 21st of the month) non-food products (between 1st and 15th of the month) services (between 1st and 25th of the month) fuels (between 1st and 25th of the month)

Data collection Data collection shifts towards the use of the internal, administrative or internet sources  administrative data, web scrapping and data files from retail chains are promising data sources Legal basis for the data from retail chains is in EU regulation and the annual programm of SURS statistical surveys SURS negotiates with each data owner and signs the agreements to grant SURS access to their data After the data owner enables access to the data, SURS ceases the collection of prices with price collectors in the shops.

New data sources Shift towards using scanner data and online data as consumer price index sources. SURS intends to start to use scanner data in 2018 for homogeneous products (food and beverages), while for technical products where diversity is greater SURS will use the price data collectors. If we used only data from one trader for price statistics, the dataset would no doubt be interesting to use, but the population would probably be systematically biased. In such a situation price collectors, although costlier and smaller in number, could still be the superior method of data collection.

Open questions What is the quality of the new data source? How will this affect the data series? Are the questions we need to consider different to the way we have approached traditional sources?

Conclusions Scanner data have not only reduced the need to physically collect prices of products in stores but will improve the accuracy of the indices by increasing the frequency of price observations, increasing the product and business coverage, and allowing more frequent updates to the weighting information. Could also open up new statistics in the future Disadvantage of such collection is dependency from retail chains data provision. Omission of the provision could mean setback in the results as well as raising the costs for SURS. With the new data sources the statistical offices are evolving into secondary users. Data owners may not fully understand data for statistical use and therefore we need mutually benefitial arrangements to be able to efficiently use available sources.

Thank you for your attention.