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Philippine Quarterly National Accounts


									         Strengthening Regional Capacities for Statistical
              Development in Southeast Asia Project
       Sponsored by UNSD, ESCAP and ASEAN Secretariat
                    Bangkok, 6-10 August 2001

              Compilation of Quarterly GDP:
             Methods, Problems, and Solutions
              The Case of the PHILIPPINES


                      Raymundo J. Talento

                          Compilation of Quarterly GDP:
                         Methods, Problems, and Solutions
                          The Case of the PHILIPPINES

                    ACCOUNTS (PSNA)1
                                    Raymundo J. Talento2


        The initial work on the Philippine Quarterly National Accounts started in
1983. It was conceived in response to the needs of planners and policy-makers for a
more timely set of indicators regarding the performance of the economy. The first set
of estimates covered the period 1981 and 1982 and basically follows the 1968 version
of the System of National Accounts (SNA).
        The task of developing the quarterly national accounts was facilitated by the
presence of quarterly data which some agencies have begun collecting as early as the
mid 1970’s. The National Statistics Office (NSO) began their Quarterly Survey of
Establishment (QSE) in 1974. Other agencies particularly, those with monitoring
and/or regulating functions have started to adopt a quarterly reporting system.
However, despite the availability of these quarterly data still, they were not sufficient
to establish a consistent set of accounts. Moreover, the survey design of QSE was
revised in 1981 to be more meaningful for national accounts purposes. From hereon,
the National Statistical Coordination Board (NSCB) has been actively coordinating
the data collection activities of the Philippine Statistical System (PSS), advocating
and strengthening the data support for the quarterly national accounts.                        As the
quarterly database improved, some of the estimation methodologies have to be refined
or modified to reflect these improvements.

 Paper presented in the ASEAN Workshop on the Development of Short-Term Indicators, held at
ESCAP Bangkok, Thailand, 06-10 August 2001.
 Division Chief for the Economic Indicators & Consolidation Division of National Statistical
Coordination Board (NSCB) of the Philippines.

          The publication of the quarterly accounts shows the Gross Domestic Product
(GDP) both by industrial origin and by item of expenditures covering a three-year
series. Subsectoral disaggregations are also presented however, no income and outlay
account, capital reconciliation account or institutional accounts are compiled for the
quarterly accounts. Deseasonalization of the GDP and its major components are also
prepared and included in the publication.
          This paper presents the present compilation system of the Philippine Quarterly
National Accounts following the outline provided by the ASEAN Secretariat. Some
sectors in national accounts are discussed in detail while the other sectors are
presented in a summary table. The deseasonalization of estimates will not be tackled

          Censuses & Special Studies – Since it is difficult to obtain data that is on a
one-to-one correspondence to the national accounts, the quarterly national accounts
still relies on censuses and special studies in developing/deriving parameters that are
part of the estimation methodology. Among others these parameters include gross
value added ratio, undercoverage ratio and unit cost relevant to the sector concerned.
          The censuses essentially provide “complete” coverage of the population while
the special studies cover specific areas or information that cannot be covered in the
censuses considering that the censuses are geared towards providing general-purpose
statistics. Special studies are normally done by the concerned agency in a particular
area of interest or in some cases it is a collaborative effort among agencies that have
also a stake or interest in that topic/area.
          Sample Surveys – Some agencies within the Philippine Statistical System
(PSS) have started quarterly data compilation long before the quarterly account was
initiated. The same is true for some private business associations. Majority of the
sectors under the production side of the accounts rely on the Quarterly Survey of
Philippine Business and Industry (QSPBI) However, these quarterly or even monthly
surveys were in most instances not originally designed for national accounts purposes
hence, the variables gathered served as indicators regarding the performance of a
sector.    In the absence of a census, the Annual Survey of Philippine Business and

Industries (ASPBI) is also utilized to update the various parameters used in the
quarterly estimation.
       Administrative Data – This type of data came about out of a need to address
the mandate of regulating and/or monitoring agencies. In most cases, they have
complete coverage for their area of concern and most of the sectors under the
expenditure side of the accounts utilize administrative-based data for their quarterly
estimates. For monthly or quarterly monitoring, they cover a sample of the population
that represents the performance of the sector. Some of the administrative based data
can be used directly for quarterly accounts while others are used as indicators.

       The estimation methods among sectors in the quarterly PSNA vary depending
on the available data for the quarterly accounts and to what extent they are applicable
in addressing the national accounts concepts.
       For the production side of the accounts there are two main techniques used in
the quarterly estimation of the gross value added (GVA), namely:

       Direct Estimates –
       Some sectors in the PSNA utilize this approach as their estimation method
since the data available correspond to the national accounts requirements. For some
sectors, quarterly production estimates are available as in the case of agriculture,
fishery and forestry; mining and quarrying; and the utilities sector. However, for
some sectors production estimates need further elaboration to incorporate the
undercoverage of the indicators used for the quarterly estimates. This is done by
applying an undercoverage ratio (UCR) suitable to the sector.
       For lack of information on a quarterly basis, the GVA for most of the sectors
are derived by using Gross Value Added Ratio (GVAR) appropriate to each sector.
These GVAR’s and UCR’s are computed from the latest Census of Philippine
Business and Industries (CPBI) or ASPBI.

       Derived Estimates (Extrapolation) –
       Estimates for the manufacturing sector and sectors under Services are derived
based on quarterly indicators. These sectors rely on the trend of the quarterly survey

of NSO to extrapolate either the output of the sector or its GVA. If the output of the
sector is extrapolated, an appropriate GVAR is applied to derive its GVA.

       The quarterly PSNA compiles the GDP both by kind of activity and by
expenditure items. GDP by kind of activity (production side) is the summation of the
gross value added of the different industry groups namely: a) agriculture, fishery and
forestry; b) industry; and c) services. Under these main aggregates are the specific
sectors so that, the first aggregate includes agricultural crops, livestock and poultry,
fishery and forestry.       Industry includes mining and quarrying, manufacturing,
construction and utilities. Services cover wholesale and retail trade, transportation,
communication and storage, finance, housing, and other private and government
services. Each sectors has specified sub-sectors that are deemed useful for the users
of the national accounts.
       The expenditure side of the quarterly PSNA is independently estimated and
includes the following expenditure items: 1) personal consumption expenditure of
households and private non-profit institution, 2) general government consumption
expenditure, 3) gross domestic capital formation and, 4) exports and imports from the
rest of the world.
       All estimates are expressed both at current and constant prices. The PSNA
still uses the fixed base year method in arriving at the constant price estimates. The
GDP level is determined on the production side of the accounts as data support on
production is more reliable than on the expenditure side.          Hence, a statistical
discrepancy is a residual item of the expenditure on GDP.

       Data Sources:
       Quarterly estimates for the agriculture sector rely heavily on both surveys,
censuses, administrative-based data and special studies as well. Based on surveys, the
Bureau of Agricultural Statistics (BAS) provides quarterly data on volume of
production agricultural crops; inventory of livestock and poultry; number of
slaughtered animals; milk and egg production; agricultural prices received by farmers;

and volume and value of commercial and municipal fishing, aquaculture, and other
fishery products. The Philippine Coconut Authority (PCA) provides data on the
volume of production of copra and other coconut products including its prices. The
Sugar Regulatory Authority, on the other hand, is the source of data for the
production, consumption, inventory, and prices of centrifugal sugar and molasses.
Data on the production, sales and prices of fiber are sourced from the Fiber
Development Authority (FDA). All of the above agencies conduct their respective
cost of production studies, which are the sources of information in deriving the gross
value added ratio (GVAR) for the different agricultural commodities.

       Estimation Method:
       Gross value added (GVA) estimates for agriculture, fishery and forestry are
computed similarly both for current and constant price estimates by subsector. Values
of production at current prices by subsector are determined based on the reports of
respective data-source agencies.     The respective GVARs by subsector are then
multiplied to the production estimates to arrive at the current price estimates
       Estimates of GVA at constant prices follow the above approach however,
value of production is expressed at base year price using base year unit price of
corresponding commodities.

       Data Sources:
       Aside from the censuses and annual surveys, which serve as the basis for the
benchmark estimates, the manufacturing sector also utilizes the NSO Quarterly
Survey of Philippine Business and Industry (QSPBI), complemented by the Monthly
Integrated Survey of Selected Industries (MISSI) and the Wholesale Price Index
(WPI). The Integrated Survey of households (ISH) conducted by NSO provides data
on employment.

       Estimation Method:
       The manufacturing sector has twenty subsectors. The estimation procedure
for manufacturing consists of two components, the organized and unorganized
sectors.   The organized component refers to the large and small establishments
covered by the NSO establishment surveys. Benchmark estimate of the gross output

of this component is based on the CPBI/ASPBI. GVA at current prices is derived
using the production approach.
       The unorganized component, on the other hand, refers to manufacturing units,
which do not possess the attributes of establishment hence, are not covered in the
establishment inquiries of NSO. Benchmark GVA estimate is computed using the
employment approach.      The difference between the employment report from the
CPBI/annual establishment survey and the ISH total employment for manufacturing is
the estimated employment for the unorganized sector. GVA is estimated by applying
the GVA per worker of small establishments based on the results of the latest
       The total GVA at current prices is simply the total of the GVA of the
organized and unorganized sectors.      The benchmark annual GVA estimates are
disaggregated into quarters by applying the index of production derived from the
       Preliminary current price quarterly estimates are derived by extrapolation
based on production trends of the QSPBI and MISSI. Deflating GVA at current
prices by the corresponding WPI derives GVA at constant prices.

       Data Sources:
       The primary data source for the trade sector is the NSO. The CPBI and
ASPBI provide information on receipts, employment, compensation, costs,
inventories and fixed assets of trade establishments. The ISH provides information on
employment while the WPI and the Retail Price Index (RPI) serve as the deflators.

       Estimation Method:
       Estimation of GVA at current prices utilizes the production approach and
similarly follows the method used in the manufacturing sector wherein the organized
and unorganized sectors are estimated separately. Preliminary quarterly estimates at
current prices are derived by applying the trend of gross revenues from the quarterly
survey to the previous quarter’s GVA level.
         To arrive at the GVA at constant prices, current price estimates are deflated
using as the deflator the implicit price index (IPIN) of the sector, which is updated

based on the corresponding price indices. The IPIN is simply equal to the GVA at
current prices divided by the GVA at constant prices multiplied by one hundred.

       Data Sources:
       The real estate sector relies on the results of the CPBI, ASPBI, QSPBI and the
CPI as provided by the NSO. The financial reports of the Commission on Audit
(COA) provide information on the rental activities of government corporations.
       Ownership of dwellings, on the other hand, utilizes the Census of Population
and Housing (CPH), Family Income and Expenditure Survey (FIES), Building
Permits and the CPI as compiled by NSO and likewise the reports on damages by the
National Disaster Coordinating Council (NDCC).

       Estimation Method:
       For real estate, annual benchmark estimate for output at current prices is based
on the results of the CPBI/ASPBI and rental income of households is based on the
FIES. The production approach is utilized to derive the GVA at current prices.
Benchmark GVA is disaggregated into quarters using the gross revenue index
computed from the QSPBI. Preliminary GVA estimates is derived by extrapolation
using the trend of the QSPBI.
       For ownership of dwellings, benchmark quarterly GVA at current prices is
estimated by multiplying the gross output, which is the imputed rent, by the GVAR
for owner-occupied dwellings. Imputed rent of owner-occupied dwellings are derived
by applying the average rental expenditure per dwelling unit to the estimated number
of existing dwellings adjusted by the quarterly price index (CPI). The FIES provides
the benchmark estimates of average rental expenditure of families and the GVAR,
while the CPH provides the benchmark estimates of owner-occupied dwellings.
       For preliminary current price estimates, quarterly GVA for real estate is
derived by extrapolation based on the trends of gross revenue from the quarterly
survey. For ownership of dwellings, preliminary current price GVA is extrapolated
based on the trend of the stock of residential structures. Stock data is updated using
the trend of the Building Permits and reports on damages.
       In estimating GVA in real terms for both the real estate and ownership of
dwellings, the current values are deflated using the CPI as deflator

          The estimation methods for the other sectors of the production accounts are
summarized in a table as part of the attachment.

          Most of the expenditure items on GDP rely on administrative data for the
quarterly estimates.      General government consumption expenditure and capital
formation on public construction depend on government statistics from the
Department of Budget and Management. Merchandise exports and imports employ
the direct estimation method based on the tabulation of the NSO Foreign Trade
Statistics whose basic data come from the Bureau of Customs. Likewise, non-factor
exports and imports use the Balance of Payment (BOP) data except for travel.

          Data Sources:
          Data for PCE comes from a variety of sources since there is no quarterly
household expenditure survey. Data for production comes from the quarterly survey
of NSO and likewise from the surveys and administrative reports of data source
agencies for the production side of the accounts. Other data from the NSO includes
the Foreign Trade Statistics (FTS) and the Family Income and Expenditure Survey

          Estimation Method:
          The Philippine national income accounts series presents personal consumption
expenditure by purpose such as food; beverages; tobacco; clothing and footwear; fuel,
light and water; household furnishings; household operations; transportation and
communication; and miscellaneous expenditures.
          Generally, personal consumption expenditures are recorded using the
commodity flow approach, where the disposition of the produced goods and services
to intermediate consumption and other final users are subtracted and PCE then is
derived as a residual. Exports, which include declared purchases made by tourists are
likewise considered in the use flow. This is of course undervalued by the amount of
undeclared purchases made. On direct purchases made by Filipino residents abroad,

necessary adjustments on final expenditures are not being made for lack of
information. Benchmark estimates and expenditure patterns are derived on based on
the FIES.
       Constant price estimates are derived by deflating the current expenditures by
the appropriate CPI component.

       Data Sources:
       GGCE relies heavily on administrative data with reports coming from the
Department of Budget and Management, the Commission on Audit, the Government
Service Insurance System and the Social Security System.

       Estimation Method:
       General Government Consumption Expenditure on goods and services is
equivalent to the value of the goods and services, which they produce. It includes
compensation of employees and purchases of goods and services less their sales to
households and industries.
       Compensation of employees accounts for the remuneration of general
government employees including social security contributions of the government
funds (or in lieu, the pensions actually paid). The remuneration of members of the
armed forces, besides their regular salaries, includes allowances for food and standard
clothing and housing.
       Purchases by general government comprise: (a) purchases for military
purposes, which include expenditures on arms, ammunitions, aircraft, road vehicles,
ships, new buildings for military use and military service, and (b) purchases for civil
administration, for governing purposes. The latter includes the cost of operating
services such as schools, hospitals, social service, police forces, roads and other
transport installations including gross rent of buildings for government use. Rental
expenditures are also imputed on buildings owned and occupied by government.
Imputed rent is only estimated in respect of buildings such as office premises, schools
and hospitals but not in respect of historical buildings, museums, etc. Provisions for
the depreciation of government buildings are included in the imputed gross rents. No
imputed interest or depreciation is charged in respect of other government
construction such as roads and traffic installations because of practical difficulties.

        In determining the scope of general government consumption expenditure, it is
necessary to decide which purchases are to be treated as consumption expenditure as
distinct from capital formation. In this connection, expenditure for defense purposes,
excluding civil defense is treated as consumption expenditure, whereas all
expenditure on capital formation for civil defense is included in gross domestic capital
        For constant price estimates, compensation of employees is deflated using an
average quarterly compensation index derived from the data of the DBM.              The
maintenance and other operating expenses use the implicit price index (IPIN) of
construction, private services and freight and transportation services. The IPIN is
simply derived by dividing the current price estimates by the constant price estimates.

        Data Sources:
        Data for merchandise exports and imports come from the Foreign Trade
Statistics being compiled by NSO. For non-factor exports and imports the primary
data source is the Balance of Payments being compiled by the Bangko Sentral ng
Pilipinas (Central Bank of the Philippines) and the travel data from the Department of
Tourism (DOT). The compilation of the Philippine BOP has adopted the Balance of
Payment Manual 5 (BPM5) starting CY2000. However, there are still some items in
our BOP that can not be readily use for national accounting due to the limitations of
its source of data.

        Estimation Methods:
        Exports and imports of goods and services consist mainly of transactions
between the residents of a given country and the rest of the world. These transactions
are categorized into the following:
            Commodity Export/Import consists of shipment of goods plus the
             monetization or demonetization of gold; and
            Non-factor services, which include:
             o transport, communication and insurance services;
             o direct purchases of foreign government and extra-territorial bodies
                such as foreign embassies, international organizations or foreign armed

               forces in the domestic market of a country are included in its exports of
           o travel items consisting of direct purchases in the domestic market by
               non-resident households and direct purchases abroad by resident
               households (i.e. tourist expenditures); and
           o miscellaneous expenditures including (1) reimbursement of the cost of
               home office services of parent company from foreign branches and
               subsidies; (2) other services such those related to construction; (3)
               subscription and cable charges; and (4) film and real estate rentals.
       Estimates for non-factor exports and imports are based on the BOP except for
travel, which is based on the travel data of DOT.
       In principle, all transactions should be recorded at the moment when
ownership of, or legal title to, the goods passed between buyer and seller. However,
for purposes of estimation, exports and imports of merchandise are based on Foreign
Trade Statistics (FTS), which record the physical movement of goods across
boundaries.   Adjustment is made to exclude special transactions (gifts, samples,
returned goods, leased equipment) from FTS to conform with the national accounting
       Merchandise exports and imports are expressed in real terms using the base
year unit prices of commodities. Non-factor exports are deflated by applying the
appropriate domestic price index (WPI or CPI). On the other hand non-factor imports
are deflated using the weighted average CPI of selected trading partners of the
Philippines adjusted for exchange rates.

       The estimation methods for the other sectors of the expenditure accounts are
summarized in table as part of the attachment.

V. Reconciliation of the Quarterly and Annual National Accounts
       Quarterly estimates are always made consistent with the annual estimates. For
the preliminary estimates no adjustments are made since the annual estimates are
simply the summation of the four quarters. However, separate annual estimates are

prepared once a more reliable data set is available. The quarterly estimates are always
reconciled if every time the latter is revised.
        Two methods are adopted in reconciling the two sets of accounts based on the
availability of data: a) quarterly estimates are adjusted based on the quarterly
revisions of the basic data and; b) applying a simple pro rata adjustment based on the
quarterly distribution of output or the quarterly distribution is based on the quarterly
indicators.   Other methods were also explored like the Bassie Method however,
considering the revisions in the data and the relevance of the quarterly accounts the
above two methods were deemed practical.

VI. Revision of the Quarterly National Accounts
        The updating or revision of the quarterly national accounts depend on the
availability of data requiring a large set of information from various sources, covering
data generated from surveys as well as those compiled from administrative records.
These sources of data have varying degrees of timeliness and follow different revision
schedules.    As such NSCB Resolution No. 8-97 approved the updating of the
quarterly accounts for each quarterly estimation round to be limited to the
immediately preceding quarter, and for the rest of the past quarters to be done only
during the May round of estimates.

VII. Dissemination of the quarterly accounts
        NSCB has adopted the policy of releasing in advance (before the year ends)
the schedule of press release of the national accounts for the succeeding year. NSCB
Resolution No. 9-97 stipulates that the quarterly national accounts be released 60 days
after the reference period however, the advance annual and fourth quarter national
accounts estimates shall be released 30 days after the reference period. Hence, prior
to the start of the year, there are already specific dates for the release of the quarterly
national accounts and data source agencies are made aware of these.
        To enhance the transparency of the quarterly national accounts, a press
conference is held at the NSCB every time the quarterly accounts are released.
Likewise, on this date the accounts are also made available through the NSCB
website. Hard copies of the accounts are given free for those attending the press
conference and NSCB also keeps a mailing list for the distribution of the accounts.

Copies for the accounts can be secured through our National Statistics Information
Center (NSIC), a one-stop center for statistical information developed and maintained
by NSCB.

VIII. Problems/Issues in the Compilation of the quarterly accounts
       The quarterly national account has its own peculiar problems/issues some of
which are briefly discussed below:
       Timeliness of data – Despite the coordinative effort of NSCB in ensuring the
availability of quarterly data for the quarterly national accounts, the timeliness of
some data still posed a problem from time to time. There are instances wherein
response rate is low; there is incomplete quarterly data (one or two months of the
quarter is not available) or in some cases, voluminous administrative based data are
not compiled in time for the estimation period.
       The NSCB is presently strengthening its institutional linkages with the data
source agency through memoranda of agreement or formal institutional letters. The
NSO, on the other hand, has recently embarked on a project to improve its annual
       Parameters/Coefficients used – The parameters /coefficients used in the
quarterly national accounts were based or derived from the results of annual surveys,
censuses or special studies. As such, these parameters/coefficients need to be updated
frequently to be more relevant. However, results of annual surveys and censuses are
available some years from the reference year and special studies are not readily
       Given this situation, there is a need to review the sectoral methodologies vis-à-
vis the present availability of data. Other data sources will be tapped for the updating
of the parameters.
       Allocation of outputs to quarters – For some sectors, output is easily
defined. However, in the case of agriculture and construction these sectors have a
long production cycle such that it is quite difficult to allocate their outputs into

IX. Future Directions:
       With the advent of the 1993 SNA, NSCB faces the challenge of carrying on
the adoption of the new SNA to its quarterly accounts. Last year (CY 2000), NSCB
has drawn up its Revision Program for the PSNA. This program of revision is
comprehensive since it involves the improvements in the estimation methods and at
the same time will incorporate the recommendations of the 1993 SNA to the extent
possible. Phase one of the program is scheduled to start this September 2001. This
involves revision of the 1991-1998 series of the national accounts and likewise the
preparation of a set of volume measures using the Chain Volume Measure approach.
With this revision, we also plan to develop a computerized compilation system for the
quarterly PSNA that will make the accounts more transparent and will minimize if not
eliminate estimation errors.     We look forward to a Revised PSNA that is more
relevant to the changing times



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