1. A STATISTICAL ANALYSIS OF COST EFFECTIVENESS OS ANSP

2. COST EFFECTIVENESS
Cost Effectiveness = Provision Costs/Composite flight hour.
These costs cover, as far as possible, the costs that are under the direct control of ANSPs and include stuff costs, non stuff operating, depreciation and costs of capital.

3. PROVISION COSTS
DEPENDENT VARIABLE

4. SKY VARIABILITY
If traffic is highly variable, resources may be underutilised, or made available when there is little demand for them
It can be temporal: Seasonal, Weekly, Hourly.Or sparcial.
Traffic Variability = traffic in the peak week/average weekly traffic

5. SKY COMPLEXITY
The relationship between “traffic complexity” and cost- effectiveness, or ATM performance, is not straightforward
Positive effect: Higher density is expected to contribute to a better utilisation of resources and to more effective exploitation of economies of scale
Negative effect: Higher structural complexity entails higher ATCO workload and more sophisticated ATM systems and tools for the same volume of traffic.

6. COMPOSITE FLIGHT HOURS
The sum of the En-route flight hours and IFR airport movements weighted by a factor that reflects the relative importance of terminal and en-route costs in the cost base
Composite flight hours = enroute flight hours+0.26*IFR airport movements

7. ATCO – HOUR PRODUCTIVITY
The efficiency with which an ANSP utilizes the ATCO man-power.
ATCO hour productivity = composite flight hours/total ATCO hours on duty

8. DUMMY VARIABLE
In order to examine whether the currency influenced the dependent variable or not, a dummy variable was used.
According to this dummy, each country that has euros as main currency is getting the value “1”, while countries that do not use euros get “0”.

9. SPSS For the analysis a software was used
SPSS Statistics is a software package produced by SPSS Inc. and acquired by IBM in 2009

10. VARIABLES REVIEW

11. DESCRIPTIVE STATISTICS

12. CORRELATIONS

13. MODEL SUMMARY

14. ANOVA

15. RESULTS

16. SCATTERPLOT

17. HISTOGRAM

18. P-P PLOT

19. UNSTANDARDIZED RESIDUAL

20. CONCLUSIONS
Variability (b = 0.126): Every unit of increase in variability leads to % increase in costs
Complexity (b = 0.3): Every unit of increase in complexity generates 30% increase in costs. 

Productivity (b = ): Every unit of decrease in productivity causes 24.5% increase in costs
Composite flight hours (b = 1.051): Every unit of increase of flight hours creates % increase in costs

21. CONCLUSIONS
Provision Costs= Variability Complexity – Productivity Composite flight-hours – Euro.
If the country’s currency is €: Provision Costs= Variability Complexity – Productivity Composite flight-hours – 0.12.
If the country has different currency: Provision Costs= Variability Complexity – Productivity Composite flight-hours.