Forecasting models and procedures Bank of Lithuania

1
Forecasting models and proceduresBank of
Lithuania
Ruta Rodzko Bank of Lithuania Economics Department

• April 23, 2008
• Sofia

2
Forecasting models

• Short term
• Inflation monthly, disagregate (92 COICOP),
  naive, 12m ahead.
• GDP (production approach, monthly, quarterly
  nowcast)
• Medium-term
• MCM style traditional macroeconometric model.

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Exogenous information

• Technical (oil price, exchange rate, short-term
  interest rate).
• Labour force natural demographics and migration.
• Fiscal revenue effective rates, expenditure
  (mainly) SCP, G budget.
• Foreign demand and price variables based on GDP
  and CPI projections from Consensus Economics. TCI
  more precise, but no breakdown, availability
  does mot match the BoL needs.
• EU funds.

4
Timing

• Strategy changed since 2007.
• Forecast produced in parallel with the quarterly
  review in Jan, Apr, Jul, Oct
• Timing and cut-off date for data influenced by
  data availability (last day of the quarter).

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Production process
Day 1 Data and assumptions
Day 4 1st meeting (latest developments, changes
in judgement)
Day 10 2nd meeting (internal presentation,
feedback)
Day 12 Final forecast
Day 15 Quarterly report submitted to the Board
Day 18-19 Forecast presented to the Board and
published.
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Publication

• Since 2008 published quarterly
• Short-list of indicators complemented with a
  note.
• Risk assessment qualitative.
• Endorsed by the board.