1

REAL- TIME GDP FORECASTING IN THE EURO AREA

By

Alberto Baffi gi , Roberto Golinelli and Giuseppe Parigi

2

publication of quarterly

national accounts within 70 days after the end of reference period

State of the art in European statistics:

flash estimates in 45 days

National account data

High frequency data

Key targets:

Improvements in releases of short term indicators

BRIDGE MODELS

Need timelier information about National accounts

3

BRIDGE MODELS

High frequency data

National accounts variables

One bridge equation for each NA variable (Semi-structural ARDL

equations + indicators)

The whole set of regressors (lagged endogenous and exogenous variables) should be known

over the projection period (“Nowcast”)

No need of Bridge Models for weather forecasts!!

4

Real Time GDP Forecasting in the Euro Area

Comparing Forecasting performance

Area wide aggregate Bridge equation

Benchmark models(aggregate and disaggregate).

DisaggregateBridge Models

Larger information

set

Aggregate or Disaggregate?

National DataHigh frequency real data

Limited information set

Area wide data

5

Benchmark and Bridge models

Forecasts

Private consumption

Collective consumption

Gross fixed capital formation

Imports of goods and services

GDP= CON + COC + INV + EXP - IMP + VSP

GDP

Changes in stocks________________________________________________________________

(GDP+Imports)

SUPPLY SIDEDEMAND SIDE

Exports of goods and services

Bus. Surveys (exp. orders), constr. components

Retail sales, cons. conf, UR

Univariate model

Trade variables, real exch. Rates, IP, surveys

IP, business surveys

GDP, surveys

6

Aggregate supply-side equation

How to forecast euro area GDP

Euro Area GDP

1) Forecast GDP ForFrance, Germany and Italy

2) Run a regression of Euro area GDP growth rate on countries GDP growth rates

3) Apply coefficients estimated in 2) to GDP forecasts in 1) to get a euro area GDP forecast

7

Horse race

Area wide aggregate

Bridge equation

Benchmark models(aggregate and disaggregate).

DisaggregateBridge Models

8

Forecasts comparison

RMSE OF THE EURO AREA GDP FORECASTS(1999.1-2001.2)

Area-wide models Aggregation of national-models

ARIMA 0.32 ARIMA 0.33

AR(5) model 0.35 AR(5) models 0.32

Structural equation 0.37 VAR 0.34

Aggregate supply-side equation 0.34 BM supply-side equations 0.12

BM demand-side equations 0.25

BM average of supply and demand0.14

9

Forecasts comparison

RMSE OF SINGLE-COUNTRY GDP FORECASTS(1999.1-2001.2)

Germany France Italy

ARIMA 0.60 0.30 0.31

AR(5) 0.60 0.28 0.35

VAR 0.60 0.34 0.36

BM supply-side 0.32 0.15 0.16

BM demand-side 0.36 0.45 0.67

BM average 0.20 0.28 0.31

10

CONCLUSIONS

•Bridge models always better than benchmark models

•Forecasts with national data perform better than the aggregate bridge model