1 SESSION 4: Extrapolation, modelling, econometric and sampling techniques used in the preparation of rapid estimates Review of papers

2 4 papers Economic projection at NESDB – Thailand Monthly estimate of GDP in Peru Canadian Monthly GDP estimates Singapore Advance GDP estimates

3 Economic projection at NESDB – Thailand Through 2 models –Current quarterly model (CQM) Uses data on indicators to estimate GDP from both demand and supply side Short-term projections In a range, progressively reduced to point estimate –Quarterly financial model (QFM) CGE model Used 29 endogenous and 28 exogenous variables For medium and long-term projections of GDP

4 Comments Monthly data is available on a number of indictors, both from supply and demand side – some indicators from VAT Most countries use this data directly to extrapolate benchmark GDP estimates GDP short-term estimates are given in a range, which at most times becomes not readily usable. Long-term projections using CGE model – is it really the mandate of NSOs Most of these models do not pick up abnormal or sudden events

5 Monthly estimate of GDP in Peru Based on indicators –Monthly index of production information provided by public and private agencies 1994 base –Administrative registers –Surveys Value of sales and personnel –Output as an indicator to extrapolate GDP 45 days timeliness

6 Comments Old IP base year –relative price movements are fixed –Output as proxy to GDP

7 Singapore Advance GDP estimates Output based QGDP –2 weeks (advance) Broad 3 industry break-up –8 weeks (preliminary) More detailed industry break-up Advance estimates use –Data on indicators (one month less data) –ARIMA models –Judgement Quality – assessed from next set of QGDP release –Generally unbiased

8 Comments Uses available data at the end of the quarter –For 3 key industry-groups –Generally 2 months data, given that most indicators have a timeliness of one month –Very good advance information, provided nothing drastic happens in the last month

9 Canadian Monthly GDP estimates Since 1919, Industry output in the form of Index of Physical Volume of Business Since 1971, monthly GDP by industry Annual estimates prepared in parallel to benchmark monthly estimates Since 1986, benchmarked to IO accounts Reconciled to income-expenditure accounts Approach –Projector or indicator, rather than econometric, of latest IO accounts –Focus on production in real terms – timeliness of 60 days –Compiled for 240 industries

10 Contd.. Sources –Surveys (output and employment), government accounts, private firms, industry associations Extrapolators –Turnover and inventories (deflated) –Physical indicators –Employment –Use of GST – being explored Releases –Volume terms Constant price Laspeyres Chain volume (focus of dissemination) – closer to chained-Fisher due to integration with QNA Revisions –Monthly, alongwith quarterly, annual, IO tables, rebasing and historical

11 Comments Comprehensive compilation For how many industries, data is released Too many revisions –Can monthly revisions be avoided –Only alongwith QNA and ANA Any plans for monthly GDP expenditures

12 General comments Source data –Administrative sources (Peru) Indicator approach – alternative data –Tax data (as in Thailand) –Companies quarterly accounts –Government expenditures both extrapolation and econometric models –Output as proxy for value added Periodicity –Monthly GDP for all countries within one month, may be difficult in view of the timeliness of data on indicators – should be within one month –Therefore, minimum quarterly – both production and expenditure Timeliness –45 days appears minimum for QNA –Singapore experience of advance estimates based on partial data can be considered for replication Revisions –Can we avoid revisions till the annual national accounts release Dissemination –Providing commentaries alongwith estimates

13 Thanks