This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF. The Current Stage Statistical and Decision-Making Support Model Presented by Dr. Ottó Hajdu Corvinus University of Budapest 2nd Transnational Thematic Workshop Budapest, May, 2014

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF. The Basic Stages of the Conception 1. Selecting the set of the Latent variables: determining the relevant statistical dimensions of the economic development Report on the manifest indicators.pdf (airLED Dropbox) 2. Selecting the set of the Manifest indicators, underlining the Latent dimensions Report on the SEM application.pdf (airLED Dropbox ) 3. Time series analysis of the economic indicators of the airport 4. Time series analysis of the final socio-economic indicators 5. Establishing the final framework of the predictive model 6. Creating a Modeling Tool for the transnational use

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF. The Availability of the Settlement Data Hungarian data, especially, can be downloaded from the websites as follows: 1. the National Land Development and Land Regulation Information System webpage: TeIR.hu, 2. the Hungarian Central Statistical Office webpage: KSH.huHungarian Central Statistical Office 3. As a result, a set of 58 socio-economic manifest indicators has been extracted, based mainly on 1.their economic meaning and, 2.statistical considerations. 4. The initial indicator list is presented in the airLED Dropbox.

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF. Selecting Target and Predictor Variables The main goal of the statistical model is to predict the so-called Target(Y) variable based on Predictor(X) data. Splitting of indicators into subsets needs two steps: 1.In the first Explorative step: Initial Y_caused_by_X sets are separated by the means of the method of Canonical Correlation Analysis, 2.In the second Confirmative step: The CCA findings are tested by the means of the Structural Equation Method.

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF. The Cross-Sectional Variable Selection where data available for each of the settlements This selection relies: 1.on the cross-sectional statistical data of the year of 2011, 2.and on the 69 settlements of the catchment area of the Liszt Ferenc Airport.

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF. The Reasons for Use of Time Series Data 1.The forecast of any target variable of a given Settlement requires time series data of both the target and the predictor variables. 2.Further, the economic development of the Airport is a process in time, which can be forecasted only in time mutatis mutandis. 3.As a consequence, the forecast needs time series observed data of the Airport and in the same structure for the settlement.

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF. The Basic Idea Behind the Predictive Model: the case of Vecsés Time index Local taxes Registered enterprises Gross production value of enterprises Number of flights Number of passengers Cargo shipping Profitability indicators of the Airport Balance sheet indicators of the Airport Target city: VecsésInternational Airport, Liszt Ferenc Target variable Predictor weighted by Coeff1Coeff2Coeff3Coeff4Coeff5Coeff6Coeff7 1. ######## 2. ######## t. ######## t+1. ######## T. ######## T+1. is to be Forecasted predicted The „ Coefficients ” are estimated by a regression model fitted on the observed data.

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF. Some Additional Time Series Data Needs Based on the Status Quo analysis possible airport-specific flow data are: 1.Number of passengers arriving and departing (Budapest Airport ) 2.Weight of the goods arriving and departing (Budapest Airport ) 3.Number of arriving and departing flights (Budapest Airport ). Nevertheless, the CSO websites are available for the years of 2004 – Finally, it is clear that the database needs to be supplemented by some municipality - specific data, available for the period indicated above, such as 1.infrastructure development, 2.regional development, 3.job training programs initiated, 4.investment tax incentive programs.

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF. The Preliminary Concept for the Partner Countries to Collect their Own Databases (highlighted points of view are as follows) 1.The framework accepted for the final model will be established especially on the data of Hungary. 2. The finalized list of the indicators are recommended for all. 3.These indicators must be extended in time series. 4.These indicators are not country-specific, so they are likely to be available in each partner country. 5.Finally, the precise forecast of the Target, requires additional turnover financial time series data about the airports as well.

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF. The transnational conclusions of the model 1.The definition of the relevant socio-economic indicators 1.of the impact zones and the related modeling activity are based on the hungarian databases. 2.Collecting the set of the analog indicators remains a task for the participant countries in the project. 2.These indicators may have local characteristics.

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF. Model Computations An R-project based R-program (written in a text file) will be behind the model calculations, The R-project is a free and open source program, Needs simply text.csv files as an input.

This project is implemented through the CENTRAL EUROPE Programme co-financed by the ERDF.