How granular should data be to compile BoP statistics?
Carla Marques
Porto, 20|22 June 2013
Outline
1.
How to define microdata?
2.
The Portuguese experience: direct reporting for
Balance of Payments and integration with other
systems
3.
The troika experience
4.
Advantages and disadvantages of microdata
How granular should data be to compile BoP statistics
Porto, 20|22 June 2013
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1
1. How to define (statistical) microdata?
“an observation data collected on an individual object – statistical unit”
(OECD , “Terminology on Statistical Metadata”)
“data on the characteristics of units of a population, such as individuals, households or
establishments, collected by a census, survey or experiment”
(United States Bureau of the Census)
Statistical
Unit
Entity
Security
Operation
(fiscal
number)
...
(ISIN)
How granular should data be to compile BoP statistics
Porto, 20|22 June 2013
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1. How to define (statistical) microdata?
Securities
Fiscal Number
Instrument
Country
……
BoP
Loans
Fiscal Number
Instrument
Country
……
Fiscal Number
Instrument
Country
……
....
Fiscal Number Unique Key identifier
……
Shared reference
tables
Entities
Complete
‘virtual’ microdatabase
Fiscal Number
Inst. Sector
Econ. Activity
.....
Fiscal Number
How granular should data be to compile BoP statistics
Porto, 20|22 June 2013
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2
2. The PT experience: direct reporting for BoP and integration with other systems
A SYSTEM WITH MULTIPLE DATASOURCES
Settlements
Direct report
SIET
Payments data
Securities databse
BoP /
IIP
NFC Balance sheet database
internal
external
MFI Statistics Accounting data
Surveys
(ISII, derivatives)
(Supervised fin. Inst.)
Microdata
GRANULARITY
How granular should data be to compile BoP statistics
Macrodata
Porto, 20|22 June 2013
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2. The PT experience: direct reporting for BoP and integration with other systems
GENERAL OVERVIEW OF DATA STORAGE
PURPOSE
GRANULARITY
Acquisition
Max: as detailed as
available
Stability
Flexibility
Quality control
Processing
Exploration
Disclosure
As detailed as necessary
for BOP and IIP
compilation
As detailed as
necessary for
other
statistical
domains
Min: strictly to
a minimum
Quality control
Cross check with
other data sources
Estimation process
Support some
compilation processes
Flexibility for
new requier.
Integration
with other
statistical
databases
How granular should data be to compile BoP statistics
Feedback for
reporting
entities
Porto, 20|22 June 2013
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3
2. The PT experience: direct reporting for BoP and integration with other systems
SETTLEMENTS AND DIRECT REPORTING
Settlements
Direct report
SIET
Payments data
Securities databse
BoP /
IIP
NFC Balance sheet database
Surveys
(ISII, derivatives)
MFI Statistics Accounting data
internal
external
(Supervised fin. Inst.)
Microdata
GRANULARITY
How granular should data be to compile BoP statistics
Macrodata
Porto, 20|22 June 2013
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Porto, 20|22 June 2013
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Resident banks
Companies with cross
border operations
OLD SYSTEM
Direct report of all
cross border operations
(Direct Reporters)
Direct report of clearing operations
and operations from external accounts
How granular should data be to compile BoP statistics
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Resident banks
Companies with cross
border operations
Direct report
Statistical
Statistical
classification
of cross
classification
of
cross border
border
operations
NEW
SYSTEM
OLD SYSTEM
operations
Reporte direto de todas as operações
Reporte direto das operações de
compensação e contas no estrangeiro
(Direct Reporters)
How granular should data be to compile BoP statistics
Porto, 20|22 June 2013
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2. The PT experience: direct reporting for BoP and integration with other systems
SETTLEMENTS AND DIRECT REPORTING
Acquisition phase
Settlements
Operation-byoperation
Client-by-client
Production phase
access and
classify
Quality control
Transactions
and stocks
Settlements are made available for
reporting entities to support their own
data reporting
How granular should data be to compile BoP statistics
Identification of nonresponses
Estimation
Porto, 20|22 June 2013
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5
2. The PT experience: direct reporting for BoP and integration with other systems
DIRECT INVESTMENT ANNUAL SURVEY AND IES (NFC MICRO DATABASE)
Settlements
Direct report
SIET
Payments data
Securities databse
BoP /
IIP
NFC Balance sheet database
Surveys
(ISII, derivatives)
internal
external
MFI Statistics Accounting data
Microdata
(Supervised fin. Inst.)
Macrodata
GRANULARITY
How granular should data be to compile BoP statistics
Porto, 20|22 June 2013
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2. The PT experience: direct reporting for BoP and integration with other systems
DIRECT INVESTMENT ANNUAL SURVEY AND IES (NFC MICRO DATABASE)
NFC
Balance
sheet
database
NFC-by-NFC
Detailed balance
sheet data
(administrative
database)
Entity-by-entity
Security-bysecurity
• Own funds data
• Group structure
Foreign direct investment compilation
No data is asked twice
Complete group structure
Balanced approach
Complete perspective, integrating the
investment within the remaining activity
How granular should data be to compile BoP statistics
Direct Investment
Survey (ISII)
Quality control
Analysis
Compilation
Identification of non-responses
Other uses for IES (other than FDI)
Identification of universe
Commercial credits
Porto, 20|22 June 2013
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2. The PT experience: direct reporting for BoP and integration with other systems
SECURITIES’ DATABASE
Settlements
Direct report
SIET
Payments data
Securities databse
BoP /
IIP
NFC Balance sheet database
Surveys
(ISII, derivatives)
internal
external
MFI Statistics Accounting data
(Supervised fin. Inst.)
Microdata
Macrodata
GRANULARITY
How granular should data be to compile BoP statistics
Porto, 20|22 June 2013
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2. The PT experience: direct reporting for BoP and integration with other systems
ISSUES
SIET
Securities
databse
Security-bysecurity
PORTFOLIO
Security-bysecurity
Investor-byinvestor
Filter with Foreign Direct Investment
microdata
SECURITIES’ DATABASE
Residual
approach
BOP/IIP
Portfolio,
liabilities
BOP/IIP
Portfolio,
assets
Compilation of investment portfolio
(assets and liabilities)
How granular should data be to compile BoP statistics
Porto, 20|22 June 2013
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2. The PT experience: direct reporting for BoP and integration with other systems
MFI STATISTICS
Settlements
Direct report
SIET
Payments data
Securities databse
BoP /
IIP
NFC Balance sheet database
Surveys
(ISII, derivatives)
internal
MFI Statistics Accounting data
Microdata
external
(Supervised fin. Inst.)
GRANULARITY
How granular should data be to compile BoP statistics
Macrodata
Porto, 20|22 June 2013
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2. The PT experience: direct reporting for BoP and integration with other systems
MFI STATISTICS
MFI Statistics
MFI-by-MFI
Full country
and currency
breakdown
BOP/IIP
Other
investment,
MFIs
Compilation of MFIs other
investment
Quality control of MFIs
portfolio investment
For loans granted by non-resident MFIs: the MoU between Credit Registers
Other countries
Credit Register
Creditor-bycreditor
Loan-by-loan
No unique identifier
No harmonized criteria
For sporadic consultation
Only big operations
How granular should data be to compile BoP statistics
Porto, 20|22 June 2013
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3. The troika experience
The challenge:
To produce in a very short time new outputs with good quality
The response:
The output:
To exploit the microdatabases
External debt at nominal value
To integrate different statistical
New institutional sector breakdown
domains
To assume estimates (when no data available
and the relative weight allowed)
To require new data (very limited, only when
no data available and for more sensitive details) q
(e.g. Identify the state owned
enterprises)
Amortization plans for external debt
Breakdown by economic activity
sector and size of the company
How granular should data be to compile BoP statistics
Porto, 20|22 June 2013
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4. Advantages and disadvantages of microdata
☺ Flexibility to adapt new outputs
☺ Possibility to integrate other microdatabases (given some pre conditions)
☺ Better quality control
☺ More comprehensive analysis
☺ More stability in terms of the requirements to the reporting entities
IT demanding
Human resources more demanding
Data management more demanding
“microdatabase trap”: the risk to drown in detailed data and lose focus of the
macro perspective
How granular should data be to compile BoP statistics
Porto, 20|22 June 2013
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Carla Marques
Head of the Balance of Payments and International Investment Position Statistics Division
csmarques@bportugal.pt
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