Editing and Imputing Administrative Tax Return Data. Charlotte Gaughan Office for National Statistics UK

Transcription

1 Edtng and Imputng Admnstratve Tax Return Data Charlotte Gaughan Offce for Natonal Statstcs UK

2 Overvew Introducton Lmtatons Data Lnkng Data Cleanng Imputaton Methods Concluson and Future Work

3 Introducton An assessment of the feasblty of edtng and mputng admnstratve tax return data to provde a substtute for survey data Current duplcaton of collecton of key varables by The Offce for Natonal Statstcs (ONS) and the Natonal Tax Offce (HMRC) The ntal study focuses on turnover for the calendar year Turnover was chosen because of ts mportance to ONS, and 2012 for qualty reasons

4 Lmtatons Taggng system used by companes to submt data. Only data whch are tagged are avalable to use. Data are nether consstently nor relably tagged Varables poorly populated e.g. number of employees has a tag rate of around 1%. Legal ssues surroundng the tax data lmts our access to the data stored n London. Unable to query suspcous data wth busnesses The nature of the data.e. data submtted for tax purposes may mpact on the accuracy of the data compared to survey data.

5 Data Lnkng Companes submt tax data accordng to ther own accountng perod, the company returns were assgned to a calendar year based on the md-pont of ther perod of accounts. Data were then summed by company reference number (CRN) and by calendar year Data are submtted usng a company reference number - n order to compare the data to ONS survey data, the HMRC data needed to be translated to RU level

6 Data Lnkng

7 Data Cleanng For the year 2012 around 0.66% of returns had all varables mssng. Turnover had 8 % of values mssng Estmated around 350,000 scalng errors 99.74% of the total turnover n the HMRC data attrbuted to the company wth the largest turnover.

8 Data Cleanng Prevous perod data unedted, thus no prevous perod valdaton performed ONS data could be utlsed at RU level whch enables scalng error checks to be conducted usng followng formula: 650<(TaxTurnover /ONSTurnover)<1350

9 Data Cleanng The taggng system utlsed meant that some data are submtted by companes that s not tagged these data are not accessble to us Companes returned fgures n currences other than GBP, n % of the companes dd so - removed from the dataset Negatve values were also removed from the dataset Foregn currences and negatve values were mputed

10 Imputaton Imputaton study requred ) to provde a complete dataset to allow comparsons to ONS survey data ) to ascertan whether the mssng data n the HMRC dataset could be accurately mputed The dataset needed to be complete at the RU level; mssngness at the CRN level dd not n tself present a problem.

11 Data Lnkng

12 Imputaton All CRN Turnovers are present at the ENT level; the CRN Turnover values are summed to create ENT turnover. The ENT value s then apportoned by RU employment to create RU Turnover. Some CRN Turnovers are present at the ENT level; the mssng CRN Turnover s mputed usng a medan mputaton and then summed wth the CRN Turnovers whch are present to create ENT turnover. The ENT value s then apportoned by RU employment to create RU Turnover. None of the CRN Turnovers are present; Turnover s mputed drectly at the RU level.

13 Imputaton Strata In scenaro 2, CRN level strata were created by summng number of CRN s per ENT level for sze. Combned wth a 2 dgt SIC at ENT level for ndustry. In scenaro 3, mputaton strata were created based on employment and SIC; employment level data were avalable va ONS data

14 Imputaton Medan mputaton Trm mean mputaton (top and bottom 5% and top and bottom 10%) Rato of means mputaton * y Rx R 1 n 1 n class class y x class class y x

15 Imputaton A smulaton study was conducted, whereby a smple random sample of 10% was taken and mputed wth each of the methods above. Tested for Bas and Accuracy class (y * y ) class y class (y * y ) class y 2

16 Concluson and Future work The results are currently beng fnalsed, and should be publshed by wnter Lmtatons to study potentally reduce the beneft of utlsng admnstratve data The study also has the scope to evaluate other varables such as sales revenue and purchases. Recommended before the dataset s used for natonal statstcs.