Assessment of Latin America transport data availability and quality

Summary of a IDB study conducted in eight countries in

the Region

José Barbero and Luis UechiJanuary 27th, 2011Washington, DC

http://www.iadb.org

The Inter-American Development Bank Discussion Papers and Presentations are documents prepared by both Bank and non-Bank personnel as supporting materials for events and are often produced on an expedited publication schedule without formal editing or review. The information and opinions presented in these publications are entirely those of the author(s), and no endorsement by the Inter-American Development Bank, its Board of Executive Directors, or the countries they represent is expressed or implied.

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Presentation Contents

Report objectives and organization– Motivation and scope– Survey organization

Survey results– Data applicability and availability– Data quality assessment

Conclusions and recommendations– Main findings– Proposed actions

Report objectives and organization

Survey results

Conclusions and recommendations

The relevance of transport data

The importance of transport sector in developing countries can be weighted in many ways– The share of the sector in the economy, in household expenditures, in

the public and private investment plans, in the energy the sector consumes or in the emission its generates

Therefore, the availability and quality of transport data have important implications in decision-making in the public sector– Transportation planning models– Models for infrastructure maintenance and expansion– Models for service regulation– Models for estimating emissions of greenhouse gases

Transport data in the private sector is also a prerequisite for decisions – strategic and operational – made by the firms, particularly those participating in the logistics chains

Survey motivation and organization This work is the result of an initiative taken by the ADB and

shared with the IDB, aimed at the assessment of the transport data availability and quality as regards the estimate of GHG emissions at the national level

The initiative is shared with other institutions through SLOCAT (Sustainable Low Carbon Transport) – Asian Development Bank is carrying out a similar task, looking at getting

joint conclusions that reflect the situation in developing countries The yardstick utilized in the assessment is a detailed GHG

emission model: its demands were the base for the estimation of data availability and quality– The basic model was developed in Australia; it provides a level of detail

considerably higher than those used by developing countries to prepare its National Communications

The IDB is starting a more comprehensive analysis of transport data needs, beyond climate change specific models

Tables structure

The requested data were organized in set of spreadsheets (Workbook)

Data are not restricted to the transportation sector; they also include factors that influence transport activity and emissions

The workbook was completed in eight Latin American countries by local experts fully familiar with their national transport sector and data sources– Argentina, Brazil, Colombia, Costa Rica, Mexico, Panama, Paraguay,

Peru: different size and income level– The task required the harmonization - as much as possible – of the

criteria for assessing the data availability and quality, in order to compare and process the results

The assignment was carried on during the first months of 2010

Report objectives and organization

Survey results

Conclusions and recommendations

Data applicability and availability

The proportion of attributes that effectively «apply» reflects the complexity of each country transport system: the existing transport modes, the diversity of fuels they utilize, the variety of vehicles in the fleets, the existence of waterways, etc.

The proportion of data actually “applying” depends on the data universe defined in the spreadsheet taken as the basis

The proportion of data available (in some form) out of the applicable ones is a more relevant indicator, reflecting the effective existence of basic information– Most countries are in the range of 80% to 90%; the two ones with

the lowest income per capita depict lower values

Data availability by group of attributes

Very high availability (more than 95%):

– Data related to international trade, energy end use, national accounts, emission types, transport vehicles

Intermediate availability (80% to 95%):

– Type of fuel utilized by the transport modes, vehicles property, type of trailer in freight transport, spatial scope of the transport activity (urban, inter-urban, etc.)

Low availability (50% to 80%):

– Transport commercial arrangements, pack type, trip purpose for passenger and freight

Data availability by mode and data type

Three fourth of the attributes are mode-specific: analysis can be made on data availability by mode

Non-motorized transport modes shows very little data availability (in the range of 30% to 40%)

Within motorized modes, road, water-domestic and conveyor transport show the weakest data availability (around 80%)

Rail, pipelines, air transport (domestic and international) and international maritime transport show the highest availability (around 90%)

From the variable type perspective, the two categories with the lowest values of data availability are trip purpose and trip commercial arrangement (60% to 70%)

Data quality descriptorsDescriptor

Measurement scale

Indicator adopted for results processing

Sub-Attribute data availabilityY-Yes Percentage of sub-attribute data

availableN-No

Data quality

1 - lowest quality Average of the available data estimated quality (measured from 1 to 5, being 5 the highest quality)5 - highest quality

Is time series availableY-Yes Percentage of data available for which

time series do existN-No

Is data subject to quality assurance protocols

Y-Yes Percentage of data are available, in which quality assurance protocols are utilizedN-No

Is data accessible to third partiesY-Yes Percentage of data, within those

available, that are actually accessible to third partiesN-No

Who collects data

1 - Government

Dominant type of entity collecting data

2 - University

3 - Industry Association

4 - Private Sector

5 - Other

How often is data collected

1 -Annual

Typical data collection frequency2 - Biannual

3 - Triennial

4 - Other

Data quality: modal perspective

The joint analysis of data availability at the sub-attributes level and data quality by transport mode reveals that:

Non motorized modes show the weakest scores in both descriptors There are three notable data breakdown weaknesses:

– emissions data for railways and pipelines– activity (task) data for domestic water transportation (surely attributable to

IWT)– disaggregated fuel related data for road transportation

In terms of data quality, the most remarkable weaknesses are:– fuel related data in all modes – vehicles and activity level in road transportation.

The international transportation practice (air and water) tend to show better results than the domestic one, both in data breakdown availability and quality

Report objectives and organization

Survey results

Conclusions and recommendations

Main findings

The assessment done is based on an specific utilization of transport (and non-transport) data; it allowed to find out the major gaps with this purpose

In Latin America transport data are available for a fairly large proportion of the applicable attributes, but data breakdown and quality are poor

The quality of the transport data looks relatively weak when compared with those from other sectors in which there are international standards and supervising institutions (energy, national accounts, demographics)

International transportation and those modes in which services are supplied by few large firms exhibit better data availability

Quality assurance protocols for transport data are very scarce in the Region

Main findings (continued) The generation of transport-related information is highly

fragmented, with a myriad of institutions, public and private, generating data in each country– The public sector is the dominant provider; but many data it collects are

not processed– The private sector is a relevant actor, gathering transport-related data in

several areas (particularly freight)– The growing role of TICs – particularly in freight – may ease data

capture and register Many available data usually emerge from administrative needs:

– All countries have vehicles registers, fuel sales registers, etc. – Data breakdowns - useful for policy but without sizeable administrative

meaning - seem to have no incentive

Proposed actions

Mainresponsible

sector

Level of complexity

CostExpected

impact

SHO

RTTE

RM

Process data already collected by public agencies

Public sector

Urge the utilization of TIC and digital registration

Public and private

Involve the private sector in data collectionPrivate and

public

LON

G T

ERM

Include transport related questions in the national Demo-Eco censuses

Public

Generate new transport related statistics and products

Public

Promote the utilization of quality assurance protocols

Public

Create a national observatory Public

HighMid-highMid-lowLow Mid