Costa, Alex

Galter, Jordi

English

Research Papers in Economics

1
DIVERSINESS AND COMPLEMENTARINESS OF STATISTICAL SOURCES
Àlex Costa and Jordi Galter Pareja
Institut d'Estadística de Catalunya
Barcelona, Spain
Address:
Via Laietana, 58
Barcelona 08005
Tel. 934120088
Fax. 9341231452
40
th CONGRESS OF THE EUROPEAN REGIONAL SCIENCE ASSOCIATION
29 august-1 September 2000 in Barcelona
DIVERSINESS AND COMPLEMENTARINESS OF STATISTICAL SOURCES
ÀLEX COSTA/JORDI GALTER
Institut d’Estadística de Catalunya (Idescat)
Introduction
The first part of this paper presents the diverseness and complementariness of statistical
forms of productions and of general statistical sources. The reader will be able to
evaluate that the diversity identified is not useless, instead it reflects the different
capabilities and limitations of each source. Therefore, it's possible to affirm that the
diverseness of the statistical sources is justified by the complementariness between
diverse forms of data production.
In the second part of the paper regional sources are taken into account. The diverseness
and complementariness of sources are once more considered. At this point, the
convergence of the priorities and activities of diverse statistical organizations such as
the central and regional governments is crucial. Complamentariness is analyzed from
two points of view: production process and final statistical products.
Diverseness of general statistical sources
In official statistics diverse methods of information production exist together: census
operations, survey investigations, the use of administrative registers and the estimation
of synthetic accounts. All these different methods of production are useful, however,
and they clearly have different drawbacks and features. We will examine this
diverseness in a simple and empirical way, generating statistics about statistics that are
included in the publication catalogue of Idescat.3
In Idescat's catalogue, we can find summaries such as the Statistics Yearbook of
Catalonia, books about instrumental statistics (methodological or classifications), or
publications on subjects such as: demographics, social statistics, structural economic
statistics or short-term economic statistics. In order to determine the diverseness of the
production methods already mentioned we can elaborate statistics on statistics (Table 1).
Table 1: Statistics about the methods of statistical production.
Results in percentage. Idescat publications.
Census Surveys Ad.
Registers
Synthetical Total
Demography 50,0 -- 33,3 16,6 100
Social 33,3 33,3 16,6 16,6
Economic structure 8,3 58,3 16,6 16,6 100
Short-term economics -- 66,6 16,6 16,6 100
Total 16,6 47,2 19,4 16,6 100
In these results, it can be shown that even if sample surveys are clearly the most
important form of production (they alone represent 50% of the total), the other methods
are not marginal, but instead have an important presence. Therefore, the information
made available confirms the importance of sample surveys but it also illustrates and
confirms the idea of the  diverseness that was mentioned at the beginning of this paper.
Complementariness of general statistical sources: quantity and promptness of the
information.
The largest amount of information and its promptness are natural and legitimate goals.
The amount of information can be expressed as a function of an optimum conceptual
detail and a great territorial distribution. Daily experience shows us that these three
dimensions: promptness, conceptual detail and territorial distribution, are rarely found
in acceptable levels in one statistical product. Generally, a survey with large conceptual
detail (for example, an enterprise survey), will present some delay and will rarely make
an important approximation to the territory. Also, promptness, so important with regard
to short-term indicators, does not provide a satisfactory territorial approximation and
limited conceptual detail. Finally, there are some statistical operations, such as the
population census, that offer a large territorial distribution, but are not conceptualy
detailed and are not satisfactory with respect to their quickness in data availability.4
This does not mean that we must not make an effort to improve the promptness of
enterprise surveys or that they can not be used at the territorial level. Neither is it
pretended that short-term statistics should necessarily be deficient from the conceptual
detail point of view. What has to be pointed out is that, in reality, some trade-off exists
between these three characteristics of a statistic. This argument can best be visualized
by a graphic in form of a triangle with projections at each side. A statistic that is
perfectly centered in the triangular space would have a value of 1/3 at each side, with
axis that measure its value in promptness, conceptual detail, and territorial distribution.
This idea is shown in graphic 1. The rule that this triangle shows can be explained the
following way: for a fixed amount of statistical resources and technology (methodology
and organization), the significant improvement one of the three aspects will result in
some loss in the remaining two. Another way of explaining this idea: each statistical
operation has a place in this space, giving more or less priority to each feature. For
example, as graphic 2 shows, the Industrial Enterprise Survey, the Population Census
and the Large Shopping Centers Sales Index (LSCI) have in each case different
priorities on each side of the triangle.
Graphic 1. Three presentations of a statistic: the rule of the triangle
concepts (1/3)
time (1/3)
territory (1/3)5
Graphic 2. Three primary operations and three features: example of the rule of the
triangle
This complementariness of the features regarding the amount of information and its
promptness is the first of the justifications about the diverseness of sources. Regarding
the forms of productions, we cans see in table 2 the complementariness of primary
forms of production.
Table 2: Features of the primary forms of statistical production
Timely promptness Territorial
information
Conceptual detail
Census -- ++ +-
Structural surveys +- -- ++
Short-term surveys ++ -- +-
Administration
registers (i)
+- ++ --
Administration
registers (ii)
++ +- --
The rule of the triangle is not a fixed rule without exceptions. International trade data
from customs are punctual and also have a great detail in their nomenclatures. The
Labour Force Survey is quite good regarding its conceptual detail as well as its
concepts
time
territory
census,
adminis. files
economic
surveys to
enterprises
short-term
surveys6
promptness, although its territorial distribution is affected by the rule of the triangle.
Despite the exceptions that can be found, the rule of the triangle is sufficiently valid in
general and it also is useful in a didactful manner for statistics users to establish marked
priorities as is the case of regional statistics.
In the area of synthetical accounts the rule regarding the contraposition between
promptness, conceptual detail and territorial distribution also applies as can be expected
if we consider that the synthesis feeds itself from statistical information. In graphic 3,
this situation regarding accounting statistics is shown.
The rule of the triangle is the first expression that allows us to affirm that the
diverseness of sources and of statistical production processes, if it translates in
complementary information, is a positive diversity. This diversity allows us to have
strategies that approximate the reality adapted to the preferences of our investigation.
This is important since punctual information at the concept and territory level is difficult
to obtain.
Graphic 3. Three account operations and three features: a sample of the rule of the
triangle
concepts
time
territory
regional
accounts
national
accounts and
IOT
quarterly
accounts7
Diverseness of regional statistics sources.
All that has been said up to now about the diverseness of statistics sources and about
their complementariness can be applied to all statistical systems. However, in a
statistical system such as ours, where regional statistics is the subject of interest and of
responsibility of central statistical organizations, such as INE in Spain, as well as of
regional organization of the autonomic communities, a new diverse and complementary
axis is added related to the plurality of production organizations. At this point, we must
ask ourselves what is the nature of the diverseness found in regional statistics sources
produced by the convergence of statistical administrations and we must also ask
ourselves about their complementariness.
One first basic element is the legal framework. This framework determines the
exclusive competence of statistics regarded as those of state interest at the central
administration and those regarded to be of exclusive competence at the regional level.
However, official statistics is not a free investigation field but rather is determined by an
international consent (in our case basically European) that defines a rather closed
catalogue about which statistic that are useful for the following of the demographic and
economic reality. This creates a general coincidence of interests between the central and
regional administration, with some differences regarding the emphasis and focus. In
front of this situation and considering the fact that the central statistics was already at
work at the moment of developing the official statistics at the autonomous community
level, we can identify three basic strategies: 1) minimize production  activities in favor
of dissemination, 2) duplicate operations, 3) complementary operations.
Most of the autonomic communities have opted basically for the first or third strategy
and only in specific cases has the second option to duplicate been considered. This
second option is possible, although it's expensive and complex, and from the
cost/benefit point of view it's difficult to justify. In the case of Idescat, we have given
priority to the first and third options.8
Complementariness of regional statistics sources: process collaboration and
making the most of each activity
One first line of complementariness appears in the activity field, in the production of
large statistical operations that, as a survey or as a census, are carried out by the central
administration's statistical organization, INE. It's clear that these operations are of most
interest to regional statistics. For example, the population census, agriculture census, the
annual survey to industrial enterprises, and the surveys to service enterprises. Idescat's
strategy was from the beginning one of collaboration and support to INE's operations
and, at the same time, to make most use of them. This strategy of collaboration and
making the most of existing statistics generates an important and diverse number of
performance formulas. Table 3 summarizes different possibilities of intervention and
making most of data.
Table 3. Idescat's areas of activities in relation to INE's programs.
Questionnaire Edition of Spanish/Catalan
questionnaires with INE/Idescat
anagram
Addition of a module with
questions that are of interest to
Idescat
Directory Exhaustive Directory Inspection Continuos  updatting  of  the
directories
Sample Without participation (within the limits of general interest, a general
interest for Idescat could be defined)
Field work Questionnaire  presentation  with
INE/Idescat anagram and
signatures
Idescat's field work execution
Purge, imputation and validation
of microdata
Purge, imputation and validation of microdata of Idescat
Elevation and estimation of sample
data
Idescat elevation is complementary
to INE's elevation
Idescat elevation is autonomous to
INE's elevation
Tabulation from microdata Idescat's  tabulation  is
complementary to INE's elevation
Idescat's tabulation is autonomous
to INE's elevation
At the last table, five of Idescat's activities have been identified that are associated to
INE's procedures, some of which can be considered as: 1) coproductions with process
collaboration (with or without fieldwork), 2) dissemination from microdata and 3)
autonomous production while taking advantage of INE's microdata.9
All these formula relationships with INE are related to the survey and census fields.
Specifically, the five formulas are found in the surveys while census represent only two
formulas: strong production collaboration and dissemination.
By their nature, administrative registers are an activity that is attained in collaboration,
since it's an activity that takes into account the use of external organization data
(customs, commercial registers, etc.). In any case, we can differentiate between simple
and direct procedures or more complex procedures. Finally, the secondary production or
synthesis of accounts, is carried out at the moment without collaboration in the process,
although there is some counseling relationship.
Considering all that has already been explained, if we want to evaluate the diverse
forms of production (and also the dissemination from microdata), we must add new
forms of production to those that are already known.
The last recount allows us to renovate the statistics of table 1 about production methods
in Idescat's case, as a regional statistic organization. We can see how the different forms
of cooperation and making use of existing data on official regional statistics, does not
create a negative panorama but instead produces more diverse forms of procedures, in a
way that diverse general sources are multiplied by regional sources according to
complementariness strategy in the production process.
The complementariness of regional statistics sources in final products: quantity,
promptness and comparison of results
The second type of complementariness refers to the field of results. This
complementariness derives from the acceptance of the regional information provided by
the central administration's statistical office, normally the INE. This way, the best
operative activity and most justifiable socially tries to compliment this body of data in
those points where the data available does no cover our fields of interests. Following
this line of work, the next step would be to analyze those general type of products that
include regional information, detect deficiencies and consider improving them. From
this point of view, and considering the three viewpoints presented in the first part of this
work, we can identify a series of statistical results that complete the information on10
Catalunya and that emphasize more conceptual detail, a better knowledge of the
territory, or some statistical products more specific or necessary to follow short-term
indicators. In the field of primary production (with all diverse forms of production that
we have shown) and of the synthesis of accounts, examples of these different statistical
results are shown in graphic 4 and 5.
Graphic 4. Idescat's primary statistical products
Graphic 5. Idescat's accounts statistical products
concepts
time
territory
EPA.
Industry accounts and statistics
Catalan trips
Spanish trips to Catalunya
IPI
IPRI
Census: daily mobility for
work or study
Make use of IAE
Hotel ocupation according to
tourist zones
concepts
time
territory
GNP
Real evolution
(deflactors)
Demand and supply
Quarterly
GNP of
Catalunya
Municipal GNP
County GNP
Municipal family income
County family income11
Each one of the products of these two graphics has a clear justification since they
improve the information offered by INE.
These statistics are produced following different strategies: sometimes with autonomic
surveys, as is the case of the LSCI, of the tourist trips of Catalans, or the trips made by
residents in other communities from the rest of Spain or Catalonia. In other cases, it's
necessary to obtain a specific module of interest to Catalonia's government as is the case
of imposed mobility in case of work or study. Sometimes, it's very useful to exploit
INE's files as is the case of the Industrial Production Index or the Industrial Price
Production Index. Finally, in operations so important as the Labour Force Survey , the
Industry Survey, or the Agriculture Census, an additional complementary tabulation is
carried out. This tabulation can be accompanied (or not) by field work cooperation in
the production process. These are the cases of the industrial survey and of the
agriculture census, respectively.
The possibility to adopt the central administration's results and complement them is
clearly effective in the case of macromagnituds. From the first moment, Idescat studied
the suitability to adopt the final results of INE's Regional Accounts. It must be pointed
out that once these results were adopted, it became necessary to extend them
conceptually offering annual GDP  results not only from the supply side but also from
the demand side as well as the need to deflate all the macromagnituds in order to
determine the annual evolution of the Catalan economy in real terms.
In the territorial field, it was necessary to supply data from the family home income
accounts  and GDP at the county and municipality level. Finally, regarding time series,
it was an important goal to arrive to Catalonia's quarterly accounts, obtained at the same
time and comparable to Spain's quarterly accounts. At the moment, these results, all
compatible with the final estimations of INE's Gross value added and family income
estimations for Catalonia, are greatly appreciated by our users who by this method find
in Idescat's activities a source of enrichment and complentariness with INE's
information, and it does not create a contradiction of choosing between available data.
The key to this planning consists, as has already been mentioned, in assuming INE's
results as interesting and available to be extended and complemented. To make this12
possible, as has been explained before, there are institutional and legal reasons. There
are also efficiency reasons when it is clear that official statistics are considered to be a
public service.

DIVERSENESS AND COMPLEMENTARINESS OF STATISTICAL SOURCES

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DIVERSENESS AND COMPLEMENTARINESS OF STATISTICAL SOURCES

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