Improvement of China QGDP Dong Lihua Dept. of National Accounts, NBS

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Improvement of China QGDP
Dong Lihua
Dept. of National Accounts, NBS
Overview
 QGDP began in 1992, established Experimental
Scheme for Quarterly GDP Estimation
Features:
1. Accumulated accounting
2. By industries
3. Method: Production approach,
Extrapolation
Overview
 1997, Method of Quarterly GDP Estimation of
China
 2000, Method of Quarterly GDP Estimation ;
 2004, Some Complementary Regulation for
Quarterly Regional GDP Estimation
 2006, Method of Quarterly GDP Estimation
(tentative)
Improvement in recent years
Study the method of calculating Chain growth
 1. Develop X-12-ARIMA-NBS
a. NBS and Nankai University jointly organize Technique
Group,Benefit from experiences of OECD and
Statistics Canada
b. Base on X-12-ARIMA
c. Take into account Chinese factors, such as moving
holidays, Effect of change of working days since 1995;
Effect of “Goldenweek” holidays since 2000; Effect of
adjusting working day for “Goldenweek” holidays
Chinese factors
 Effect of Moving Holidays:
 There are Spring Festival, Mid-autumn Festival,
Qingming Festival and Dragon boat Festival. Their
effects are reflected by the relevant variables
Chinese factors
 Effect of Changing Workdays
 Since April 1995, the working time has changed
from 6 days per week to 5 days per week . The
effect reflected by redefined workday effect of X12.
Chinese factors
 Effect of golden week
 Golden week is appeared in Oct. 1999. As the
name implies, golden week is a seven-days holiday
which consists of nation holiday/labor
holiday/spring festival and its adjacent weekend.
This effect is adjusted by relative variables.
Chinese factors
 Effect of working days shift
 In order to make the golden week seven days,
sometimes we need to exchange several working days
with weekend. Obviously, it will change the effect of
working days and trading days. For this reason, we
redefined the relative variables of trading days.
Improvement in recent years
d. Set up X-12-ARIMA-NBS for Chinese seasonal
adjustment
 2. Seasonal Adjustment for 18 selected
indicators
Quarterly Indicators





1.GDP
2.Agriculture
3.Industry
4.Contruction
5.Transport, Postal and
Telecommunication
 6. Wholesale and Retail





7. Hotel and Catering
8.Finance
9.Real Estate
10.Others
11.Wage and Salary
Monthly Indicators
 1.Value-added of
Industrial
Enterprises above
Designated size
 2.Total Retail Sales
of Consumer Goods
 3.Investment in
Fixed Assets
 4.Freight Ton-Kilometers
 5.Electricity Consumption
 6.CPI
 7.PPI
Improvement in recent years
 3. Collect and process the basic data of 18 indicators
 4. Challenges in Practice
a. Accumulate data convert to separate data
b. Statistical coverage changes
c. Statistical period is not complete in practice. for
example, one month usually missed in service sector
survey.
Improvement in recent years
 d. The length of time series is not enough
 e. Master seasonal adjustment technique as soon as
possible
 f. Chain growth and Growth year on year, which
one is dominant?
 g. Whether annualized or not?
Improvement in recent years
 Study the method of quarterly GDP by
Expenditure Approach and implement on trial.
1. Accumulated quarterly accounting
2. The primary method
The primary method
Items of
Expenditure
Household
Consumption
Expenditure
(HCE)
Method of Estimation
Basic Data
Extrapolation
(1) Household sample
Extrapolated indicator:
survey: Per capita
(1) Growth rate of
rural resident HCE in
HCE=Growth rate of
cash, Per capita urban
per capita
resident HCE;
(2) Investment in fixed
HCE×Growth rate
of total population
assets statistical
(2) Growth rate of
survey;
Investment in owner- (3) CPI
occupied dwelling
The primary method
Government
Consumption
Expenditure
Extrapolation,
Extrapolated indicator:
Growth rate of General
government current
expenditure
(1) Financial statistical data
(2) Price index of Investment
in fixed assets and CPI
Gross Fixed
Capital
Formation
Extrapolation,
Extrapolated indicator::
Growth rate of total
investment in fixed assets
in the whole country
(1) Investment in fixed assets
statistical survey,
(2) Price index of Investment
in fixed assets
The primary method
Change in
Inventory
(1))Financial statistical data:
Inventory of state-owned
enterprises
Change in inventory
(2)Industry statistical survey:
=value of end of period Inventory of finished goods of
industrial enterprises above
-value of beginning
of period
designated size
(3)Wholesale and retail trade
statistical survey:Inventory of
enterprises above designated size
(4)PPI
The primary method
Net
Exports
Net Exports=
Exports-Imports
(1) The Customs Statistical
Data
(2) BOP
(3) Price indices of goods
of imports and exports
Improvement in recent years
3. Challenges in practice
 Growth rate of total population is not available
while estimating HCE
 It is difficult to estimate and deduct cost of land
from investment infixed assets while estimating
GFCF
 Inventories other than state-owned units are
missing while estimating change in inventory
 Problems exist in Price indices of exports and
imports
 Choice of accumulated accounting and
separated accounting
 Coordinate the difference between GDP by
industry and GDP by Expenditure approach
Thank you!
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