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QUARTERLY MANUFACTURING INDUSTRIAL SURVEY: METHODS, PROBLEMS, AND SOLUTION THE CASE OF INDONESIA. SUB DIRECTORATE SMALL-SCALE AND COTTAGE INDUSTRY STATISTIC S BPS - STATISTICS INDONESIA. 1. QUARTERLY MANUFACTURING INDUSTRIAL SURVEY. BACKGROUND. BPS:. 2.

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Quarterly manufacturing industrial survey methods problems and solution the case of indonesia l.jpg

QUARTERLY MANUFACTURING INDUSTRIAL SURVEY:METHODS, PROBLEMS, AND SOLUTIONTHE CASE OF INDONESIA

SUB DIRECTORATE SMALL-SCALE AND COTTAGE INDUSTRY STATISTIC S

BPS - STATISTICS INDONESIA


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1

QUARTERLY MANUFACTURING INDUSTRIAL SURVEY


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BACKGROUND

BPS:

2

In the beginning PJP I, the Indonesian Economic was still relied on the agricultural sector, which contributed over 50% to the GDP. While contribution manufacturing industrial sector was only less than 9%.

Industrialization process => Economic structure has shifted from agricultural sector to industrial sector. Contribution industrial sector (20.96%) is bigger than agricultural sector (19.66%).

Entering the PJP II (1994) => contribution industrial sector to GDP continued to increase (23.5%), while agricultural sector tended to decline (17.4%).

The industrial sector is a leading sector as a main supporting Indonesian Economy => The existence of Quarterly Production Indices as a prompt indicator which useful for monitoring the economy.

In 2000 BPS introduced a new quarterly system with a monthly sub-system that gives an aggregate monthly index.


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SOURCES OF MANUFACTURING INDUSTRY DATA

Manufacturing industry is categorized into four groups according to the number of employees. Large & Medium establishment cover those  20 persons engaged, Small and cottage establishment cover those  19 persons engaged.

Data on Large & Medium manufacturing industries is collected every year, while Small & Cottage industries could not be collected every year.

Large & Medium Manufacturing Industrial Survey relied on the cencuse basis, while Small & Cottage Industrial Survey relied on sample basis.

Data sources of manufacturing industrial survey => relied on the establishment record. Administrative records from association of several industries => needed just for standard of comparison => check for plausibility.

- Directory of Large & Medium establishments => Updated every year.

- Large & Medium Manufacturing Industrial Survey => Relies on cencus

(covers all establishments).

- Response rate of the annual survey around 84% - 91% from the target.

- Timeliness around 18 months after the reference year.


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PROFILE OF MANUFACTURING INDUSTRY

- Number of manufacturing industries in 1998 amounted to 2.22 million units.

- Absorbing around 9.43 million persons.

- Large & Medium establishments => is a smallest part from the total number

of establishments ( less than 1%).

- Cottage industries => is the biggest part (90.26%)

- Small scale industries => is the second biggest part (8.77%).

- Large & Medium establishments => is a biggest absorber employements (44%)

- Cottage industries absorbs around 40.28%, and

- Small-scale industry absorbs around 16% employments.

- Total value of gross output of the manufacturing industries in 1998 was

around Rp. 474,424 billion.

- Large & Medium establishments => The biggest share total of output of the

manufacturing industry (91%).

- Small-scale and Cottage industries constibuted only 9% to the total output.


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PROFILE OF MANUFACTURING INDUSTRY

- Number of establishments, the Large & Medium Manufacturing Industry

=> was dominated by sub-sector 31, 32 and 33 => Each sub-sector has

share around 25%; 22% and 14% from the total number of establish-

ments.

- Sub-sector 35,38 and 36 has share was around 11.15%, 10.99% and 9%.

- Sub-sector 34: less than 5%, sub-sector 39: less than 3%.

- More over the sub-sector 37 which was only less than 1%.


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METHOD OF MANUFACTURING

INDUSTRY SURVEY

Quarterly Survey

Sampling frame based on the 1996 Annual Large & Medium

Manufacturing Industry Survey.

Methodology of Sample Selection:

- A rough target sample of 992 establishments was choosen whisch should

allow timely processing based on pas experience. Based on this sample, the

level of representation of the sample was determine to be at the 3-digit ISIC,

not at the 5-digit ISIC currently used.

- Establishment were then sorted by declining output, and a cut-off point

( Rp. 141.55 million in 1996) was determined above which all establish-

ments are choosen with certainty. The number of such establishments was

236 => given a code “C1”


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METHOD OF MANUFACTURING

INDUSTRY SURVEY

Quarterly Survey

Methodology of Sample Selection:

- The top 1 % establishments group which have extraordinarily high output

per worker, then was choosen and was added to the sample with certainty.

The number of establishments added was 131 => given a code “C2”

(those establishments group have a special behavior => special treatment)

- Remaining establishments were then sorted by 3-digit ISIC, and within each

ISIC by descending output per worker. The remaining number of establish-

ments to be selected (992 - 236 - 131) were then selected with PPS, and they

were given a code of “S”.

- Establishments selected with certainty were then given a sampling weight of

1, and those selected by PPS were given a weight equal to the invers of their

probability of selection.


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METHOD OF MANUFACTURING

INDUSTRY SURVEY

8

Quarterly Survey

Number of establishments has been selected by sub-sector

------------------------------------------------------------------------------------------

Sub-sector Number of establishments Distribution (%)

------------------------------------------------------------------------------------------

31 210 21.17

32 195 19.66

33 97 9.78

34 45 4.54

35 195 19.66

36 43 4.33

37 39 3.93

38 160 16.13

39 8 0.80

-------------------------------------------------------------------------------------------

Total 992 100.00

=====================================================


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METHOD OF MANUFACTURING

INDUSTRY SURVEY

9

Quarterly Survey

Methodology of Sample Selection:

- In line with the sampling design, the unweighted output of establishments in the

sample represents 61.7% of total output in the population.

- Target publication schedule => 3-3.5 months after the end of the reference

quarter for the preliminary version and 6 months for the final figures.

- The methodology of computing Quarterly Production Indices was based on

inter-month commodity growth. Previously was based on estimation of intra

quarterly commodity growht and inter quarterly growth.

- Quarterly Production Indices are calculated by averaging of three monthly indi-

ces of the concerned quarter using the Discrete Divisia procedure.


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METHOD OF MANUFACTURING

INDUSTRY SURVEY

10

Quarterly Survey

Steps are required to compute the Quarterly Production Index based on

the Monthly Index:

- The first step includes calculating commodity growth between the two relevant

months.

- The second step includes calculating an establishment index by aggregating

commodity growth using their relative value weights.

- The third step includes aggregating to the 5-digit ISIC level to measure growth

for that particular ISIC.

- The fourth step includes computing a total index for all establishments.

- Finally, by averaging of three monthly indices on the concerned quarter, then

would be Quarterly Production Index result.


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METHOD OF MANUFACTURING

INDUSTRY SURVEY

11

Monthly survey as a sub-sample of the Quarterly survey

- Using the same selection methodology which used in the Quarterly survey. The

only difference being that while the Annual Survey was the frame for the quar-

terly, the Quarterly itself was the frame for the Monthly Survey.

- Target sample of 195 establishments, is representative for 1-digit ISIC level

monthly production index result, and could be handle for a monthly survey.

- Establishment were then sorted by declining output, and cut-off point (Rp.907.9

billion) was determined above which all establishments are choosen with

certainty. The number of such establishments was 11 =>given a code “C1”.

- Remaining establishments were then sorted by descending output per worker.

The remaining number of establishments to be selected (195-11) were then se-

lected with PPS =>given a code “S”.

- 797 establishments are compiled for a quarterly survey.

- 195 establishments are compiled for a monthly survey.


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12

QUESTIONNAIRES AND MAJOR VARIABLES

Questionnaire format:

- Periodicity => Quarterly

- Quarterly index computation => Inter month commodity growth

=> The questionnaire requires data for every month in the quarter,

=> In addition to the last month of the previous quarter (overlapping months)

=> Cover three main variables:

- Quantity of production => Commodity growth factors

- Value of production => Current weight value

- Number of employees => For editing purpose

The main reasons for adopting those format:

- With information for four consecutive months (including one overlapping

month) in one questionnaire, a quarterly growth rate for an establishment

can be calculated from a single questionnaire rather than having to com-

pare two questionnaires. This has two important advantages:

a. The role of inconsistent nomenclature and classification from quarter

to quarter is eliminated.


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13

QUESTIONAIRE AND MAJOR VARIABLES

b. More data are used in calculating the index, since calculations need

not be limited to establishments that respond in both quarters.

- Comparing data for overlapping months in various quarters provides an

indication or response reliability.

- The questionnaire has additional fields for calculating the implicit unit price

of various commodities reported => an easy way to detect implausibility or

inconsistency in reported data.

- Many establishments may find it easier to report monthly rather than quarter-

ly because their books are arranged that way.


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QUESTIONAIRE AND MAJOR VARIABLES


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DATA COLLECTION METHOD

15

Periodicity:

Data on Quarterly Survey are collected in two ways :

- First, 797 establishments are compiled every quarter.

- Second, the remaining establishments (195) are compiled every months.

Notes: After three months then the data which collected every month could

be consolidated with data which are collected every quarter for com-

putting the Quarterly Production Index.

System data collection:

- Quarterly Survey => Direct enumeration.

- Monthly Survey => Combination of the mailling, facsimile, and email

system.

System of directory updating:

Directory of the Quarterly and Monthly Sample are maintained and kept updated, for cases in which some sample establishments has died or is non- active.


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DATA COLLECTION METHOD

Purposes of sample directory:

- Useful for monitoring of document reponses for each establishment.

- Measuring of response rate of documents survey from the target sample in

each Province.

Improving the response rate :

Based on the response rate, policy actions could be taken for improving the response rate:

- To inform the BPS Province to handle or troubleshoot the problem, espicially

for lack of response and non-response cases.

ponse.

- To visit some establishments in order to improve their cooperation and data

integrity.

- To contact establishments (via contact person), to ask about progress and

problems in filling up the questionnaire.

- To ensure establishments, that their report is important for to computing

production index, industrial policy decisions, for itself, and so on.


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ADJUSTMENT FOR NON-RESPONSE

Adjustment methodology:

The response rate of the Quarterly Survey is always under from the target sample. Usually after 3 to 4 months of the reference quarter, the response rate was still around 40% to 50%. Therefore, in order to maintain reliability and representativeness, then the adjustment for non-response was needed. Adjustment for non-response distinguishes between establishments selected with certainty and those selected with PPS.

- Establishment with code of “C1”, sampling weights of respondents in a parti-

cular quarter are adjusted by multiplying them by a ratio of total output of

all establishments has code of “C1” in a particular ISIC to total output of

actual respondents in that quarter in that ISIC.

- Establishments with code of “S”, sampling weights of respondents are multi-

plied by the invers of the response rate in that quarter in a particular ISIC.


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ADJUSTMENT FOR NON-RESPONSE

Therefore, it’s more better for always be maintain of the res-

ponse rate than must be done adjustment for non-response.

There are the informal approach which need to be done:

=> To develop and improve better relationships with contact

persons.

- Indirect communication with establishments (by phone).

- Direct communication with establishments (visited).

=> Give and take principal must be taken.

- BPS giving the relevant publications which useful for

establishments, while the establishments giving the data

report to BPS.


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DATA PROCESSING AND DISSEMINATION

Data preparation:

Data consistency and plausibility are detected following these two steps:

- First, manually system => Before the entry.

- Second, computerized system => After the entry (data processing).

Before the entry, data consistency and plausibility must be evaluated mannu-

aly to ensure that the data have been toleraby consistence:

- Calculate average price per unit of every commodities in every month

within one quarter, then comparing one to the others.

- Compare the productivity per worker between months within one qua-

ter, to ensure that production per month is plausible.

- Examine the onsistency possibility of quantity and value of production

for every commodity by comparing them with the previous quarter, and

make the necessary correction if they are inconsistent.


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DATA PROCESSING AND DISSEMINATION

20

If data are suspected as being inconsistent:

-BPS comes back and asks the contact person to ensure that the correction

can be made appropriately.

- Indicators of the previous quarter usually are used for correction.

- Moreover, to ensure that the data is plausible, data are crosschecked againts

administrative records of a limited number of industry associations.

Data entry:

- Data of every establishment are entered twice by independent data entry

operators, and result are then compared one to another.

- Any discrepancies are then checked and corrected by the computerized

system which has been developed in the data entry module.


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DATA PROCESSING AND DISSEMINATION

21

Data entry module has three main feature:

- It validates quantity and value totals per commodity. That allows

detection of inconsistencies between individual commodity entries

and commodity totals in the questionnaire.

- As quantity and value data per commodity are entered, the pro-

gram flashes the implicit unit prices. Inconsistencies can then be

detected and corrected.

- It is interactive, i.e. entry erros can be corrected on the spot.


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DATA PROCESSING AND DISSEMINATION

22

Data Processing:

- Data processing uses the same manner and software as the ones previously

used.

- The previous growth computation uses inter quarter growth and intra

quarter growth =>Then to be change base on commodity growth factors

between two consecutive months in the reference qua-

ter.

Step of computation:

- Commodity growth factors are computed for every establishments.

- An establishments index is then calculated, aggregating commodity

growth factors using theDiscrete Divisia procedure.

- Establishments indices are then aggegated using the same procedure to pro-

duce a 3-digit index, these are in turn aggregated using the same procedure

to produce a 2-digit then a 1-digit index.


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DATA PROCESSING AND DISSEMINATION

23

Program data processing has an three modules:

- First, response module it produces two tables:

- Provides response rates by province, to measure the relevant perfor-

mance of various provincial office.

- Produces table of share of respondents in industry output are broken

down by selection criteria (ISIC and category “C1” or other).

Therefore, the response module useful for BPS to monitor the progress of the

survey (progress of the response rate).

- Second, data entry module:

- Allows detection and correction of inconsistent commodity entries

and unit prices.

- Thirt, growth computation module:

- Produces inter month measures of monthly growth quantities, unit

value indices and employment indices.


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DATA PROCESSING AND DISSEMINATION

24

Limits on various variables

> Caused of outlying observations:

- Unsustainable movements in production in a paticular quarter

- Strong seasonality in production (cases of sugar)

- Data error

- If production was zero in certain month in within one quarter

> Reducing the influence of outlying observations:

- For reducing of these cases affected, then in the system data processing

places limits on three types of variables:

- Growth rates of commodities => -2.50 to 2.50 (is still the same)

- Establishment growth rates => 0.25 to 4.00 (is still the same)

- Establishment weight => 0.05 to 4.00 ( previously 0.1 - 4.00)


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DATA PROCESSING AND DISSEMINATION

25

- Appropriate with the sample design, the Quarterly Production Index was

published at the most, in 3-digit ISIC. While the Monthly Production Index

was published was the most, in 1-digit ISIC.

- Those index would be release every quarter/month.

- After 3-4 months of the reference quarter, these indices are still considered

preliminary figures and become the final figures after 6-7 months.

- After the quarterly production indices turn to final figures, then the month-

ly production indices of the following quarter are revised, and become the

final figures (Monthly Survey as sub-sample Quarterly Survey).

- Data are release simultaneously to all users in the publication of Monthly

Economic Indicator, Monthly Statistical Bulletin, and can be accessed thro-

ugh Internet on BPS website: (http://www.bps.go.id).


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PROBLEMS AND SOLUTION

26

The main problems :

- Lower of awareness entrepreneur side

- Non-response

- Late or lack of response.

- Inconsistency and plausibility’s data reported.

Solutions for handling those cases:

- Take special efforts for visit establishments, to improve the relation-

ships and cooperativeness.

- Improve the monitoring activities of the document receiving, and

keep contacts with establishments by phone or email to remind their

duties to report.

- Improve the monitoring of the data quality to detect and evaluate

data plausibility and consistency.

- In the futures, BPS need to take special efforts to intensively improve

statistics awareness of respondent (including establishments).

- Ideally, a special telephone number and a toll-free telephone number

facilities should be avaliable in BPS central office, to accelarate com-

munication with establishments and to be used by establishment that

have chosen to use facsimile to send the questionnaire.


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Thankyou for your attentions

SUB DIRECTORATE SMALL-SCALE AND COTTAGE INDUSTRY STATISTICS

BPS - STATISTICS INDONESIA


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