Download Automated Supply-Use Balancing in the United Kingdom: A New

Automated Supply-Use Balancing in
the United Kingdom: A New
Approach
Introduction
• SU balancing is the reconciliation of data
sources to provide a GDP estimate
• It should depend on the quality of each data
source
• Traditionally, this has been done manually
• But better computers are helping NSIs
automate this
• So how to specify the algorithm?
Quadratic Programming - A Model
• QP is a well-established algorithm with
multiple easily-available software
implementations
• But what constraints and objective to use?
• Usual model
– Weight the objective (squared adjustments) for
relative quality
– Accounting constraints
– Optional soft constraints for economic ratios
Literature Review
• Chen (2012) presents this model in matrix
algebra terms
• Key points: Covariance matrix between initial
estimates and true values must be known;
initial estimates must be unbiased estimators
of true values; if so, model produces unique
best solution
• Similar conclusions in Bikker et al (2013) and
van Tongeren and Picavet (2016)
The UK Position
• We do not know the covariance matrix (Chen)
• Nor do we know the standard errors of the
underlying dist. of the initial estimates – or
even whether they are normally distributed
(Bikker et al, van Tongeren and Picavet)
• So can we develop a model suited to these
conditions?
An Alternative Model
• Consider the matrices and vectors underlying the
SU system
• For each cell, we should be able to allocate upper
and lower bounds (eg, the UK agriculture industry
produces less than £100 trillion for each product,
and more than £0 for the agriculture product)
• Real bounds are much narrower
• So we can apply these as additional constraints in
a LP/QP model
• No weights on the objective
Comparison of Models
• This model does not guarantee a unique best
solution (indeed, the solution may not be unique
– but this is unlikely)
• And, if the constraints are not set correctly, the
problem can be infeasible
• These are consequences of the unavailable
information
• So we can’t guarantee the outcome will be as
good as the other model – but we don’t have to
make its assumptions
Testing
• Testing was done on past UK SU tables
• Upper and lower bounds based on manual
adjustments – if a cell had been manually
adjusted by + or – x%, the upper and lower
bounds were set as +/- x%
• Some different treatment based on different
manual procedures (eg trade in goods)
Results
• See tables in paper
• For the 4 main SU aggregates (GDP(P), GDP(I),
total supply, and total demand) total
adjustments were lower for all except GDP(I)
• At the lower level, the lower manual GDP(I)
adjustments were the result of higher (in
absolute terms) adjustments netting off
• So results are positive
Conclusions
• Automation of the SU process is viable
• ONS is still not able to deliver the more
ambitious aims of the alternative model
• That requires more work to establish the
needed metadata
• This work should be a top priority for ONS and
the other NSIs working on automated
balancing