DEVELOPMENT OF IMPUTATION MODEL FOR SMALL ENTERPRISES Eurostat project “The implementation of a more efficient way of collecting data” DEVELOPMENT OF IMPUTATION MODEL FOR SMALL ENTERPRISES Inga Malasenko Sandris Matisins 2019.02.22.

OBJECTIVE AND TASKS OF THE ACTION The main objective of the action is to lessen the statistical burden for enterprises by wider use of administrative data. To reach the objective following tasks were put forward: To analyze existing administrative data, its availability and possibilities to use them for imputations in annual business survey; To analyze variables and carry out different testing calculations to determine optimal model for imputation of enterprises; To improve imputation algorithm for small enterprises for annual business survey 2007. 2019.02.22.

SURVEY STRATEGY 2007 All enterprises are divided into three groups: Exhaustive survey (10 539 enterprises): average number of persons employed 50; Turnover is higher than threshold defined for the corresponding NACE group. Sample survey (7 678 enterprises) - enterprises with the average number of employees between 10 and 49 and not fulfilling previous conditions are surveyed by sample. Use of administrative data (45 992 enterprises and 14 502 natural persons) - enterprises below thresholds (small units) and self employed physical persons are calculated using administrative sources. 2019.02.22.

Development of imputation algorithm for expenditures ACTIONS OF PROJECT 2 main actions Development of imputation algorithm for expenditures Development of imputation algorithm for investments 2019.02.22.

ADMINISTRATIVE DATA SOURCES FOR CALCULATION OF EXPENDITURES For calculation of expenditures the data from The State Revenue Service (on the basis of official agreement) were used: Annual financial statement of enterprises (enterprises with turnover higher than 200 000 Ls): - balance sheet; - profit and loss account; Declaration on income from economic activity (enterprises with turnover of less than 200 000 Ls and self employed natural persons); Report on mandatory state social insurance contribution. 2019.02.22.

ACTIONS TO IMPROVE IMPUTATION ALGORITHM FOR EXPENDITURES For analysis data from year 2005 were used, as then both statistical survey data for small enterprises and data from administrative sources were available. Actions: Calculation of expenditure structure of large and small enterprises. Comparison and evaluation of the structure – are the large and small enterprises similar by NACE groups. 2019.02.22.

ACTIONS TO IMPROVE IMPUTATION ALGORITHM FOR EXPENDITURES To realize the above mentioned actions following tasks were put forward : Development of an optimal NACE grouping Optimally chosen NACE groups and comparison of expenditure structures of small and large enterprises in each group to evaluate their (dis)similarities on a dataset where there is information on both small and large enterprises; Elimination of outliers Choice of the measure of distance between sets of expenditure structures and elimination of the outlier effect on those measures. 2019.02.22.

RESULT OF THE ACTIONS TO IMPROVE IMPUTATION ALGORITHM FOR EXPENDITURES Consequently, it was established that expenditure structure between large and small enterprises in most cases is similar but not always. 2019.02.22.

“DONOR METHOD” – THE WAY TO IMPROVE IMPUTATION ALGORITHM FOR EXPENDITURES Development of new method taking into account accessible administrative data – donor data imputation. Actions of “The Donor method”: Calculation of total expenditures from administrative data and calculation of wage ratios in total expenditures; Calculation of expenditure ratios at micro level from survey data; Comparison of wage ratios from administrative data and survey data and finding the closest appropriate value in particular NACE groupings; Estimation of achieved result – is it enough close, and correction of coefficients; Use of average coefficients from expenditure structure, which are calculated by definite NACE groups, if the achieved result is not enough close. 2019.02.22.

New data were imported in data processing system. FINAL ACTIONS AFTER DEVELOPMENT OF NEW IMPUTATION ALGORITHM FOR EXPENDITURES New data were imported in data processing system. Preparation of the final SBS data for year 2007 with new imputation model and transmission to Eurostat. 2019.02.22.

INFLUENCE OF RESULTS ON SBS VARIABLES Value added at factor cost Total purchases of goods and service Imputed small enterprises Other enterprises 2019.02.22.

COMPARISON OF NEW AND OLD METHOD NACE Rev.1.1 Value added at factor cost Total purchases of goods and service Industry - C, D, E -21 9 Construction - F -10 5 Trade - G -33 12 Services - H, I, K -1 10 2019.02.22.

CONCLUSIONS AND FUTURE ACTIONS Reduction of response burden for small enterprises. A lot of imputation work has to be done within the statistical office. Timeliness of administrative data is quite late. Very tight timetable for production of SBS preliminary results: 30 September - administrative data available to CSB 31 October – SBS preliminary results transmitted to Eurostat Future actions: Further improvement of imputation algorithm. Adjustment of imputation algorithm to NACE Rev.2. 2019.02.22.

MAIN TASK FOR CALCULATION OF INVESTMENTS Development of imputation model for the part of annual enterprise survey “Movement of long-term intangible and fixed assets”. It was done for the small enterprises below thresholds, which are not directly surveyed by statistical surveys . 2019.02.22.

DATA SOURCES AND VARIABLES FOR CALCULATION OF INVESTMENTS Annual enterprise survey; Quarterly survey on investments; Administrative data of the State Revenue Service (residual value of long-term intangible and fixed assets at the beginning and end of balance). Main variables: Amortization; Increase of the kind of long-term intangible assets and fixed assets. 2019.02.22.

CALCULATION OF AMORTIZATION Calculation of amortization ratios by the kind of long-term intangible assets and fixed assets for large enterprises in 2005. Calculation of amortization ratios by the kind of long-term intangible assets and fixed assets for small enterprises in 2005. Adequacy of amortization ratios between small and large enterprises was observed. Calculation of amortization ratios by the kind of long-term intangible assets and fixed assets for large enterprises in 2007. Average Residual value x Amortization ratio = Amortization 2019.02.22.

CALCULATION OF INCREASE OF LONG-TERM INTANGIBLE ASSETS AND FIXED ASSETS Residual value at the end - Residual value at the beginning + Amortization = Increase Calculation of increase for large enterprises in 2007 taking into account administrative data and Quarterly survey on investments and comparison with the Annual enterprise survey’s results. Result: not feasible Calculation of increase for small enterprises in 2005 taking into account administrative data and Quarterly survey on investments and comparison with the Annual enterprise survey’s results. Result: is feasible (long-term intangible assets were 100% and fixed assets (equipment, machinery, transport vehicles, other fixed assets and inventory) – 104%). 2019.02.22.

FINAL RESULTS OF CALCULATION OF INVESTMENTS Preparation of imputation model for the part of annual enterprise survey “Movement of long-term intangible and fixed assets” for the reference year 2007. Development of calculation and verification of data by description of imputation. 2019.02.22.

INFLUENCE OF RESULTS ON SBS VARIABLES Gross investment in tangible goods Gross investment in land Gross investment in existing buildings and structures Gross investment in construction and alteration of buildings Gross investment in machinery and equipment Imputed small enterprises Other enterprises 2019.02.22.

CONCLUSIONS Amortization ratios can be used for the calculation of small enterprises. Prepared model can be used for small enterprises in 2007 for the part of annual enterprise survey “Movement of long-term intangible and fixed assets”. 2019.02.22.

Thank you for attention! 2019.02.22.