Presentation on theme: "Gil Dafnai, Jonathan Sidi Research Department, Bank of Israel."— Presentation transcript:
Gil Dafnai, Jonathan Sidi Research Department, Bank of Israel
Motivation : GDP data is being published at a six week lag after the end of the relevant quarter (and it is needed sooner). However : There is a lot of monthly data that is available before the policy meetings. Therefore : We use real-time monthly data in order to Nowcast the GDP 3 weeks ahead of publication.
General Data Set ( ): ◦ 170 monthly Indicators: 95% Domestic and 5% Global. History: ◦ All series begin at least at 1998Q1. Endpoints: ◦ All series have value for at least two month of the projected quarter.
1. Seasonal adjustment by X12-ARIMA 2. Holt and Winters exponential smoother is applied where necessary 3. Convert to lower frequency (quarterly) by average observation 4. Convert to percent change 5. Standardize The resulting sample size is defined as
1. Advantages ◦ General form of algorithm makes it applicable to many problems in econometrics. ◦ Ability to produce decomposition of variable contribution of the forecast. 2. Shortcomings ◦ Can not select more then n variables ◦ If n>p then ridge is better ◦ No grouping LASSO Conclusions
Conditional Selection Methods Unconditional Selection Methods Multiple Univariate LASSO Elastic Net Stepwise Regression Intermediary Step Final Step
Tomer Kriaf Research Department, Bank of Israel
Consumption Equation: Import of Durables, VAT, Confidence Index, Revenue Index (L), Imports of Raw Materials, TA Stock Market Index. Fixed Capital Formation Equation: Imports of investment Goods, Capital Utilization, PMI, lagged Inventories, TA Stock Market Index. Inventories Equation: Exports of goods, Revenue Index, Industrial Production Index. Exports Equation: Exports of Goods, PMI-USA. Import Equation: Imports of Goods, Imports of Services. GDP Equation: Derived GDP, Indirect Tax, Income Tax, TA Stock Market Index. Derived GDP