REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat Direct vs. Indirect Approach in Seasonal Adjustment: Proposal for a new tool Necmettin Alpay KOÇAK Akın ÖZTÜRK Economic Indicators and Price Statistics Department Information and Communication Technologies Department 2012 Workshop on recent advances in Seasonal Adjustment 6 March 2012, Luxembourg

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat Outline of the Presentation Introduction Motivation New Tool : DISAT –Hierarchy Tree –Aggregation –Analysis –Outputs Application and results (preliminary) Conclusion and further steps

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat Introduction When considering a single economic time series, which method to be used has importance in seasonal adjustment, But, when a group of time series (i.e. balance of payments, national accounts, industrial production and sub-items) is of interest, the situation is slightly more complicated than previous. In this case, the discussion is on which approach (aggregated or disaggregated data) is to be used in seasonal adjustment.

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat Introduction 1.Direct approach 2.Indirect approach Since the choice between direct and indirect approach directly affects the information that is given to policy makers (Koçak, Mazzi and Moauro, 2010) the decision must be taken efficiently by agencies and organizations.

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat Introduction Extensive literature –Geweke (1978) –Ghysels, Granger and Siklos (1996) –Ghysels and Osborn (2001) –Hood and Findley (2001) –Astolfi, et al. (2001) –Maravall (2006)

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat Motivation Considering the statistical classifications (i.e. NACE, ISIC, etc.) used in production of data, it is a difficult task to compare direct and indirect approaches for each aggregated series (for each level of classification). The motivation of this study is the lack of an aggregation module to provide the series according to indirect approach and lack of a tool to easily calculate the criteria proposed in literature to compare of these two approaches. Another objective of this study is to extend the criteria previously explained by the literature. In detail, the diagnostics are extended by taking account not only final series but also preliminary series, the forecast functions of derived components.

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat New Tool : DISAT Direct & Indirect Seasonal Adjustment Tool (DISAT) DISAT performs aggregation of the series using by the outputs of individually seasonally adjusted series. During the aggregation process, it uses a classification structure defined by user and weights used in the classification to obtain indirectly seasonal adjusted series. Then, it provides to users both graphical views and statistical criteria to compare the directly and indirectly adjusted series.

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat New Tool : DISAT This tool is designed to analyze the Excel outputs obtained from TRAMO&SEATS for Windows, hereafter TSW (Caporello and Maravall, 2004), and Demetra+ seasonal adjustment softwares. DISAT needs three basic pieces of information as well as output files of TSW or Demetra+. –frequency of group of the time series (monthly and quarterly) –the number of forecasts that are in the output files –classification system (hierarchy tree)

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat DISAT : Hierarchy tree The user must identify a hierarchical relationship between the series so that DISAT can perform aggregation process. Such classifications, NACE, MIGS, national accounts by production method, may be examples of this relationship

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat DISAT : Hierarchy tree The series which is hierarchically at the top of the group will be at the top of the hierarchy tree. During the creation process of that tree, the most important issue is weighting and it is possible to give weight by the user for each series in the process. NACE Rev.2 → hard process Once the user created hierarchy tree, it is possible to save this tree as an XML file and to use in other applications, subsequently. Using original series → no seasonality

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat DISAT : Aggregation i = 1,2,...,n shows the number of the series K in the group, “O” means that original series, A is aggregated one; Discripancies of below components will be tested for; –Linearized series –Trend-Cycle component –Irregular component (just to test residual seasonality) –Seasonal and calendar adjusted series –Seasonal adjusted series –Calendar adjusted series

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat DISAT : Aggregation The components here are obtained as level value of the series in case of additive decomposition, but in case of multiplicative decomposition, the components are obtained as factors. x = S, C, I

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat DISAT : Analysis Astolfi et al. (2001)Concordance ratio (ECB, 2010) 0 < Concordance ≤ 0.6 → No concordance 0.6 < Concordance ≤ 0.7 → Poor 0.7 < Concordance ≤ 0.8 →Acceptable (Fair) 0.8 < Concordance ≤ 0.9 → Excellent (Good) 0.9 < Concordance ≤ 1 → Outstanding

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat DISAT : Analysis Difference between final estimator and preliminary estimators  Last three years  Full sample  Forecasts Dagum (1979) Residual seasonality → Friedman Test on Irregular Maravall (2007)

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat DISAT : Output Group of the series and growth rates of them –Linearized –Trend-Cycle –Seasonal adjusted –Calendar adjusted –Seasonal and calendar adjusted Their graphics And diagnostics ; –Astolfi et al. (2001) –Concordance ratio –Last three years, full sample and forecasts –Dagum (1979) –Residual seasonality test

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat Application and results (preliminary) GDP and sub-items according to production methods 21 time series 1988-Q1 and 2009-Q4 Seasonally adjusted with RSA=3 and IREG=1 by TSW Gross Domestic Product () A.Sectoral total 1.Agriculture, hunting and forestry 2.Fishing 3.Mining and quarrying 4.Manufacturing 5.Electricity, gas and water supply 6.Construction 7.Wholesale and retail trade 8.Hotels and Restaurants 9.Transport, storage and communication 10.Financial intermediation 11.Ownership and dwelling 12.Real estate, renting and business activities 13.Public administration and defense; compulsory social security 14.Education 15.Health and social work 16.Other community, social and personal service activities 17.Private household with employed persons B. Financial intermediation services indirectly measured (-) (FISIM) C. Taxes-Subsidies

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat Application and results (preliminary)

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat Application and results (preliminary) Sectoral Total GDP

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat Residual Seasonality DirectIndirect A. Sectoral total1.14 (0.999)1.90 (0.996) GDP1.58 (0.998)

REPUBLIC OF TURKEY TURKISH STATISTICAL INSTITUTE TurkStat Conclusion and further steps Development stage of DISAT will continue … DISAT tool will be a more effective tool when it contains other benchmarking criteria (revisions, sliding spans etc.) explained in the literature. This version has written in C#, next step is to transform it to Java and to provide possible implementation to JDemetra