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Benchmarking

Benchmarking. Workshop on the Methodological Review of Benchmarking, Rebasing and Chain-linking of Economic Indicators 24-26 August 2011, Vientiane, Lao People’s Democratic Republic Vu Quang Viet. Why benchmarking?.

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Benchmarking

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  1. Benchmarking Workshop on the Methodological Review of Benchmarking, Rebasing and Chain-linking of Economic Indicators 24-26 August 2011, Vientiane, Lao People’s Democratic Republic Vu Quang Viet

  2. Why benchmarking? • Economic statistics and national accounts are estimates that are extrapolated from a base year using short-term indicators. • Data from a base year is considered the most reliable as they are based on economic census that covers the complete population. • Short-tem indicators are based on survey (or administrative report) of a limited number of units in an activity that deems to signify the full activity. • When a new base year is compiled, the estimates must be benchmarked to the data of the new base year.

  3. What are normally benchmarked? • Quarterly values are benchmarked so that the sum of quarterly values is the same of the annual value. • Annual estimates should be benchmarked so that the last annual estimate should match the benchmark value. • These benchmarking applies to an individual statistics or a composite statistics such as quarterly GDP and annual GDP. • Preferred approach: benchmark each individual statistic series.

  4. Indicators • Economic performance indicators are mostly drawn from annual or quarterly accounts and therefore are fully consistent with one another and provide useful overview of the economy, its strength as well as weakness. • However, they need to be supplemented by other important indicators that are prepared from specialized statistics such as monetary and government budget statistics. • All indicators would be more meaningful in the context of changes over time, therefore, time series of statistics are required.

  5. National accounts aggregates as indicators • Indicators based solely on national account aggregates. • Familiar indicators are: rate of growth in GDP, final consumption, investment in fixed assets, saving rate (saving/GDP), investment rate, effective individual and corporate tax rates, etc. • These indicators can be derived directly from national account data. They allow to compare not only the performance of the economy over time but also to other countries of the same level of development. • Consumer prices indexes. • Producer price indexes (or wholesale price indexes).

  6. Indicators that relate national accounts with other indicators • Government budget balance / GDP. • Current external account balance / GDP. • Foreign debt payment / export (which includes both interest payment and payment principal). • Etc.

  7. Indicators that are used to national accounts aggregates • Industrial production indexes. • Crop yield indexes. • Employment indexes, based on: • Establishment survey that captures only employment in formal activities that are covered by updated census frame • Household survey that captures employment in informal activities. • Retail sale indexes. • Investment (GCF) indexes.

  8. Use of indicators for extrapolation • Base year: 2000. • It-1,t : Volume index indicating growth from t-1 to t. • Q: Value in constant prices. Q2000,t = Q2000,t-1*It-1,t

  9. Other specialized indicators • Non-performing loan ratio. • Foreign exchange reserves (reserve over average monthly imports). • Short-term liability denominated in foreign currencies. • Leading, coincident and lagging indicators to track the economy: • Inventory over sale (leading indicator) • GDP (coincident indicator) • Employment (lagging indicator)

  10. Comments on indicators • To be useful, indicators must be timely. • Quarterly accounts are extremely useful. • For quarterly accounts, other indicators must be available monthly, particularly important: • CPI, PPI • Industrial production indexes • Employment • Retail sales

  11. UN recommenations on short-term indicators • To be distributed.

  12. Topics to be discussed • Benchmarking a series of values of annual estimates to match the new annual value of the benchmark year. • Benchmarking growth rate approach • Benchmarking the sum of the quarterly GDP to the annual value of GDP. • Pro rate distribution of discrepancy method • The Bassie method • The Denton method • Linking seasonally unadjusted quarterly data

  13. Scheme for growth and value benchmarking of annual data Benchmarkyear 2 =13 Conditions: • New rates of growth are close to the old rates of growth • The new rates of growth should permit the obtaining of the new benchmark value at the new benchmark period. Benchmark year 1 =10 Annual Estimates

  14. Example for benchmarking annual values

  15. Method for benchmarking • Find the percentage growth difference between the estimate and the new benchmark for the same benchmark year. • = 13/12=1.083 • Distribute that percentage difference to the n-years in the old series. • = (1.083)^(1/3) = 1.027 • New rate of growth = old rate * ig

  16. A benchmarking is linking • This will be discussed by Benson Sim.

  17. Benchmark quarterly data to annual data – pro rata method

  18. Step problem Problems of pro-rata method

  19. Other methods • Bassie method aims at allocating the values so as to reduce the reduction in the first year and increase the value in the second year to reduce the step problem. • Denton method aims at minimizing the difference in the rates of growth of the old and the new series, while maintaining the annual value equal the sum of the quarters. This requires software. STATA IS THE SOFTWARE THAT CAN DO THE JOB. • Observations: All methods are mechanical. It is thus important to review the indicators and see if they are good indicators or if they should be replaced.

  20. Index linking seasonally unadjusted data: method • Convert quarterly data of the two consecutive years to constant values • Calculate seasonal index of T (of the current year) as compared to T-4 (of the previous year), SIT . SIT = VT / VT-4 • Link by seasonal indexes to the previous index series by multiplying the seasonal index to the index of the same quarter. IT = SIT * IT-4 • (See Exel-file).

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