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División de Estadística y Proyecciones Económicas
Producing Environmental Statistics
and Indicators: gaps and
discrepancies challenges in Latin
America and the Caribbean
Rayén Quiroga-Martínez,
UN ECLAC
IAOS Conference
Santiago, Chile, October 20 to 22, 2010
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División de Estadística y Proyecciones Económicas
Contents
1. Env Stats Data Gaps and Discrepancies
2. Contributing factors
3. Towards a regional strategy
for environmental statistics
development in the LAC region
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1. Env Stats in LAC: heterogeneous,
emerging field
In country of LAC region, the production of environmental
statistics, indicators and integrated accounting (ES, from
here on), is emerging within official statistical systems.
They co-exist (co-develop) with globally agreed definitions
and frameworks, as well as user-driven internationally
agreed environmental and sustainability goals and their
respective sets of indicators (i.e. MDG7, ILAC, etc.).
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Envt. data gaps and discrepancies
• Despite the positive evolution of the last decade in the
LAC region as a whole, ES data gaps remain most
relevant problem.
• Official national and global indicators: data point values
of the same environmental variable or indicator can be
quite different making statistical discrepancies is growing
concern.
• Both problems are related to specific factors that will be
addressed in the regional strategy ahead.
Source: Quiroga, Stockins and Azocar, 2010.
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División de Estadística y Proyecciones Económicas
Gaps and discrepancies

Both gaps and discrepancies among national and global sources for all MDG
indicators (comparing only National Reports with the MDG UN database),
describes a problematic and generalized situation by 2006/7:
•
50% data gaps were observed in MDG national reports and
•
90% of reported data point values inconsistent (national and global)

Worse in 10 environmental MDG7 indicators.
•
Significant data gaps exist (very heterogeneous)
•
Data reported by LAC countries is scarce and sporadic.
•
Data point values reported in National MDG Reports generally
inconsistent with those from the UN.
•
Environmental indicators reported by countries showed insufficient
metadata to make a thorough comparison.
•
Expert judgment: most of the reported indicators for MDG7 are essentially
different from those defined internationally, difficult to coincide.
Source: Quiroga, Stockins and Azocar, 2010
Medio Ambiente
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División de Estadística y Proyecciones Económicas
60%
50%
%
40%
I.Nac.
30%
NU
20%
10%
0%
0
1ó2
3ó+
Observaciones Promedio por Indicador
By 2006/2007:
• 50% of potential data points are missing in the NReports, reduced to
10% in the UN Millennium Database.
• 30% of data series report one or two observations in NRs, while this
number increases to 50% in the UN MDatabase.
• Only 20% of observation points present 3 or more observations in the
NRs, 33% in UN MDatabase
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División de Estadística y Proyecciones Económicas
Producing Env Stats: scales and types of sources
For analytical purposes: distinguish between
•
Level of production (or compilation): each serves different users and
purposes, and van follow different conceptions and methodologies.
– Global, regional, national
– Ideally, production fully described and thus conciliated.
Types of sources of ES production;
a) Administrative records (i.e. pesticides use, environmental government
expenditure);
b) environmental quality monitoring systems (i.e. stations that monitor air
emissions, MP concentrations, rainfall, surface water quality at different
points in a river)
c) estimation (through statistical process, i.e CO2 emissions, land degradation)
d) Census (i.e. population, housing and agriculture) and Surveys (i.e.
household, employment, economic and specific environmental surveys);
e) Remote sensing (i.e. satellite images).
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Producing ES: Types of sources and scale
of production-compilation
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División de Estadística y Proyecciones Económicas
Types of environmental statistical sources
1.
Administrative records (i.e: apparent consumption of
agrochemicals, CFC consumption)
2.
Monitoring systems (i.e: urban air quality, coastal pollution)
3.
Estimates (i.e: CO2 emissions, SO2 emissions, degradation
of natural resources )
4.
Censuses (i.e: Drinkable water, basic sanitation)
5.
Surveys (i.e: housing quality, collection of solid waste, etc.)
6.
Remote sensing (i.e: satellite images for forests inventories,
remote imaging of urban sprawl (city core)
7.
Combination of sources (Degradation of soils, for example,
integrating land monitoring systems, remote sensing and
expert estimates)
ES: Levels of Production
Producers
(collectors)
Comparability adjusment
Pros and Cons
Directed to this
users:
Analytical
purposes:
Global
Source
- Adjustments to ensure
Maximum
coverage/
agregation,
imputation and
estimation as
needed
UN GSec
Global Scale
analysis and
assesment
(international
agencies)
global comparability
(global metadata and
statatistical standards)
- Inputation and estimation
(missing national data)
Regional
Source
(regional
agencies)
National
Source
(NSOs, Env
Ministries,
other)
- Adjustment to ensure
regional comparability
(PPAs, geográfico,
territorial, definición
regional-internacional)
- According to national
definitions and stats
norms
-Closer to national
analytical and user
demand
Medium coverage
/ increasing quality
/ regional
metadata
compatible with
global
Lesser coverage
(time and territory)
International
Environmental
Conventions
UNEP (GEO)
UN ECLAC
Regional UNEP
ILAC, regional
GEO
Regional scale
analysis and
assesment
Environmental
Ministries Forum
Environmental
Ministries
Development
and other
ministries
General Public
National scale
analysis and
assesment for
policies and
public
information
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División de Estadística y Proyecciones Económicas
Data gaps and discrepancies: contributing
factors
At the national level:
a) Environmental statistics is an emerging field and institutional
arrangements are recent, (institutional development (existence
of ES unit, staff, resources) still a challenge
b) Insufficient inter-institutional coordination (legal framework,
overlapping, lack of inter-institutional platform)
c) Conceptual and methodological differences
d) Different periodicity of collection and updates for dissemination
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3. Towards a Regional Env Stats Development
Strategy
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Env Stats Development: key components
Enhance and increase quality, quantity and international
comparability of ES within official national systems:
a) statistical and methodological capacity building,
b) institutional strengthening (i.e. environmental
statistical production within the official national
statistics) and
c) inter-institutional coordination (among different
national entities in various scales, where the
participation and leadership of the NSOs).
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Institutional dimension of ES
Inter-institutional coordination key factor of conciliation process, critical in cross
cutting ES domain. Should be constructed at all levels and interfaces.
Three levels: national, regional and global,
and three interfaces:
a)
national-regional,
b)
national-global and
c)
amongst national institutions
Institutional strengthening means sustainable institutionalization of the ES within the
NSOs and within environmental authorities structures and budgets,
•
Allows practitioners and institutions to capitalize the resources, know how, networks
and methodologies available.
•
Requires methodological and statistical capacities, but also implies that both NSOs and
Environmental authorities provide the necessary infrastructure, resources and stability
to work
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División de Estadística y Proyecciones Económicas
Working together in the LAC region...
• Regional Strategy and Program for
Environmental Statistics Development
(SCA - WGES)
• Regional MDG indicator conciliation
strategy (module MDG7), ECLAC’s MDG Statistics
Program with member countries.
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Conciliation strategy
Statistical conciliation: process that allows for
differences in data point values produced by
different sources, clearly accounted for, and
described in metadata.
1st Stage: identification and explanation of statistical gaps and
discrepancies among national and international sources,
relying strongly on the production of national metadata.
2nd Stage: working with existing regional expert and
practitioner’s groups. To produce indicator-specific
recommendations aimed at enhancing production and
incorporating international standards and definitions.
Levels and interfaces for inter-institutional collaboration
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División de Estadística y Proyecciones Económicas
Regional
Level 1: National
Level 2:
Facilitators: NSO,
Env Ministry
Facilitators: ECLAC, SCA
Level 3: Global
Facilitators: ISWG
Env Stats, IAEGM
MDG, UNCEEA,
• NSO
• Environmental Ministries
• Sectoral Ministries
Interface
B:
Interface A:
nationalregional
regionalglobal
Interface C:
nationalglobal
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División de Estadística y Proyecciones Económicas
Statistical Conference of the Americas
•
•
•
Subsidiary body of the Economic Commission for Latin America and the
Caribbean promoting the development and improvement of official national
statistics in the region.
Consists of Directors or Presidents of National Statistical Offices.
Has a 10 year Strategic Plan (2005-2015) that includes thematic
cooperation programs carried out by working groups.
Working Group Env Stats
•
•
•
Established in 2009, the Group consists of the following countries and
agencies: Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican
Republic, Mexico, Panama and Venezuela, UNEP LAC
Represented by both National Statistical Offices and Ministries of
Environment and in some cases Central Banks
Mexico is the coordinator (INEGI) and ECLAC the Technical Secretary
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Gracias por la atención!