1. European Commission
Directorate General for Economic and Financial Affairs
The harmonised EU investment survey: What can it tell us about investment growth in the euro area?
Roberta Friz and Christian Gayer
Joint EC/OECD Workshop on Business and Consumer Surveys
12-13 November 2007, Brussels
European Commission 2007

2. Motivation Business investment is a key GDP component
GFCF accounts for approx. 20% of euro-area GDP
High volatility  significantly lager share of GDP growth
Since 1966: EC investment survey
Representative samples useful information on overall investment in industry sector
Released before statistical data should also be useful for forecasting
But: few studies on the usefulness of the data
European Commission 2007

3. Outline Overview of the EC Investment Survey Descriptive analysis
Usefulness in forecasting
Conclusions
European Commission 2007

4. 1. Overview of the EC Investment Survey
The investment survey is carried out twice a year :
in March/April (“spring”): percentage change in investment of the company from year t-2 to t-1 and from year t-1 to t
in October/November (“autumn”): percentage change in investment of the company from year t-1 to t and from year t to t+1
four consecutive estimates of investment growth are available for each year.
Example for year 2006:
European Commission 2007

5. 2. Descriptive analysis The data:
Investment survey covers only the manufacturing sector
therefore we choose equipment investment (metal products, machinery and transport) as reference series to approximate investment activity in the manufacturing sector.
Equipment accounts for approximately 40% of total investments and the two series are highly correlated
Focus is on nominal investment growth
European Commission 2007

6. Equipment investment growth and surveyed change of investment in the euro area – nominal value

7. Investment reported in each survey for the euro area – nominal value

8. Average revisions vis-à-vis the definitive survey estimate - 1992 to 2006
Minus  previous estimate was lower by … pp than the definitive estimate
Plus previous estimate was higher by … pp than the definitive estimate

9. Actual versus estimated
Minus  underestimation
Plus overestimation

10. The mismatch can partly be due to:
different coverage of the survey (manufacturing industry) and reference series (equipment)
Revisions in the National Account data:
Considering the years from 2000 to 2006, the mean absolute error has been 0.68 pp and the RMSE 0.91 pp.
In the period 2000 – 2006 the first releases have always been revised upwards. The negative bias amounts to (mean error).

11. Direction of the changes and correlation coefficients
Percentage of correct directional changes indicated in the survey
Correlation between investment survey data and actual investment in equipment

12. From Industry survey asked in January, April, July and October
Benchmark with other questions in the BCS
From Industry survey asked in January, April, July and October
factors limiting production
“none”, “insufficient demand”, “shortage of labour force”, “shortage of material and/or equipment”, “financial constraints” and “others”
Assessment of current production capacity
“more than sufficient”, “sufficient” or “not sufficient”
Capacity utilisation
quantitative figure reporting the percentage of full capacity they operate at

13. Correlation between quarterly industry survey data and actual growth in equipment investment

14. Signs of the correlation coefficients are correct
Investment is negatively correlated with the factor "insufficient demand limiting production” and with the “capacity assessment”
The correlation is positive for the results obtained from the capacity utilisation question and the other factors limiting the production.
For the euro area, correlation coefficients are high using October Industry survey results:
0.83 with capacity utilisation
-0.83 with the assessment on production capacity and
-0.87 with "demand" as factor limiting the production
For Germany, high correlation coefficients with capacity utilisation as reported in the July (0.81) and in the October industry surveys (0.76). In addition, correlation is with "demand" as factor limiting the production in the October survey.
For Spain, coefficients with factors "demand" and "shortage of material and/or equipment" with the July industry survey are and 0.74, respectively.
For France and Italy, correlation coefficients are lower than with the investment survey

15. 3. Usefulness in forecasting (explanatory power)
Basic regression method
Correction for bias by using a constant
Augmentation of AR model by investment plans
Degree of improvement of fit over AR
European Commission 2007

16. Table 1: In-sample statistics, euro area
adj. R²
const.
p-value
invest. plan
AR(1)
0.11
1st plan
0.47
-0.81
0.606
1.24
0.0084
2nd plan
0.71
-0.07
0.939
0.80
0.0002
3rd plan
0.67
2.44
0.029
0.69
0.0006
definitive
0.83
2.18
0.010
0.77
0.0000
N=15
European Commission 2007

17. In-sample results: euro area
Including 2nd plans improves R² to 0.71, slightly lower for 3rd plans
All survey vintages are Granger-causal
Significant underestimation of investment growth in t in the January and June releases of t+1
Based on 16 yearly observations only (since 1992) purely indicative results
23 observations available for FR and IT
European Commission 2007

18. Table 2: in-sample fit France and Italy
adj. R²
France
Italy
AR(1)
0.06
0.05
1st plan
0.23
0.31
2nd plan
0.51
0.33
3rd plan
0.66
0.61
definitive
0.67
0.47
N=22
European Commission 2007

19. In-sample results: France and Italy
Goodness of fit increases monotonously with maturity of investment plans
But: “definite investment plans” surveyed in t+1 (Mar/Apr) for t do not carry more information than 3rd plans (Oct/Nov)
For Italy, explanation becomes even worse
General problem: in-sample statistics overstate forecasting power
European Commission 2007

20. Out-of-sample forecasting
Euro-area time series too short
some indicative results for France and Italy
Division of sample: initial estimation over , forecast for 2001
recursive extension of sample until 2006, forecast for 2007
RMSE to reflect forecast uncertainty over
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21. France
Italy
European Commission 2007

22. Table 3: RMSEs for France and Italy RMSE France Italy 1st plan 3.53
3.60
2nd plan
3.63
4.62
3rd plan
3.32
2.43
N=7 ( )
European Commission 2007

23. Out-of-sample results (1)
RMSEs computed with respect to final NA figures
RMSE of first NA estimates with respect to final estimates is 0.91 for the euro area (total business inv.), likely higher for individual MS
Second investment plans perform worse than first
Superiority of third investment plans, esp. for IT
Forecasts look reasonable
Benchmark??
European Commission 2007

24. Out-of-sample results (2)
Commission’s Autumn Forecast, iterative-analytic, produced in October, published early November
i.a. forecast for real growth in equipment investment in t+1 (amplitude and general pattern very close to nominal growth)
RMSE over : 2.81 (FR) and 4.89 (IT)
Simple regression using 3rd investment plans: 3.32 (FR) and 2.43 (IT)
Comparable or even superior accuracy (IT)
But: results are released in late January only
European Commission 2007

25. Summary of forecast evaluation
Evidence for usefulness in forecasting is mixed
High in-sample explanatory power
But: low benchmark (past investment, low autocorrelation)
Many potential macroeconomic/survey data that might encompass info of investment survey
Out-of-sample: indication of usefulness for forecasting, but results are needed earlier
European Commission 2007

26. Conclusions and possible improvements
Investment survey contains useful information
For structural analysis and for forecasting
But data are available very late
Release the results earlier?
Survey covers manufacturing industry only
Extend the survey to other sectors?
Quarterly survey would allow estimating quarterly investment growth (see INSEE)
Increase the frequency (4 time per year)?
European Commission 2007