in co-operation with Monitoring, Modeling and Forecasting Prisoners Criminological and Econometric Aspects Rainer Metz and Werner Sohn in co-operation with Upcoming EUROPRIS Oslo Conference, Nov

in co-operation with Goal of our Analysis Upcoming EUROPRIS Oslo Conference, Nov Derivation of statements about future developments of selected series of the penal system using statistical methods of modern time series analysis for monitoring, uni- and multivariate modeling and forecasting considering criminological theories as well as statistical and econometric research.

in co-operation with The Analysis Includes Upcoming EUROPRIS Oslo Conference, Nov Modeling the dynamics of tme series and their components by structural time series models Identification of factors that have influenced the penal system directly or indirectly by using the cointegration concept Development of stochastic time series models with one dependent and several independent variables Forecasting of selected series of the penal system

in co-operation with Our Approach (I) Upcoming EUROPRIS Oslo Conference, Nov No extrapolation of trends No intuition No stories about criminal policy No eclectic comparisons of numbers and No eclectic correlation analysis But instead:

in co-operation with Our Approach (II) Upcoming EUROPRIS Oslo Conference, Nov Development of uni- and multivariate dynamic time series models for selected data of the penal system with systematic consideration of a variety of (potential) impact factors from the fields of law enforcement, crime, demography and economics as well as their possible interdependence.

in co-operation with Our Methods: Univariate and multivariate techniques of modern time series analysis Upcoming EUROPRIS Oslo Conference, Nov Univariate: Modeling the components of a time series with structural time series models  Trend  Deviations from trend  Seasonal components  Outliers, structural breaks, missing values Multivariate: Pairwise tests for causality between a dependent and an independent variable (including their components) Development of multivariate causal stochastic models for a dependent and several independent variables using ex post forecasts Dynamic ex ante forecasts using dynamic causal models specified

in co-operation with Working steps (I) Upcoming EUROPRIS Oslo Conference, Nov Preparation, documentation and description of long time series of  Prisoners  Prosecution  Crime  Economy and Society  Demography

in co-operation with Working steps (II) Upcoming EUROPRIS Oslo Conference, Nov Univariate modeling of time series 3.Monitoring of selected series of the panel system with time series models 4.Identification of causal factors for  Prison  Prosecution  Crime 5.Development and testing of causal models on the basis of the identified factors 6.Dynamic short, medium and long-term forecasts for selected series of the penal system

in co-operation with Example 1 Preparation, Documentation and Description of Prison Statistics Upcoming EUROPRIS Oslo Conference, Nov

in co-operation with Example 2 Univariate Modeling of Time Series Prisoner in the execution of prison sentence in a German bundesland Upcoming EUROPRIS Oslo Conference, Nov

in co-operation with Example 3 Monitoring Prison development Upcoming EUROPRIS Oslo Conference, Nov

in co-operation with Example 4 Identification of causal factors Upcoming EUROPRIS Oslo Conference, Nov

in co-operation with Example 5 Development and testing of causal models (foreign suspects and foreign population) Upcoming EUROPRIS Oslo Conference, Nov

in co-operation with Example 6 Dynamic ex ante forecasts Upcoming EUROPRIS Oslo Conference, Nov

in co-operation with Topics for Future Research Upcoming EUROPRIS Oslo Conference, Nov Construction of a data base a.with long time series for  Prisoners  Prosecution  Crime  Economy and Society  Demography b.with monthly /quarterly time series for different prison populations (foreigners /Germans, remand prisoners, youth offenders etc.) up to the present Further development of the existing forecasting models Development of forecasting methods for monthly / quarterly series Monitoring, modelling and forecasting of different groups of prisoners Monitoring, modelling and forecasting prison populations for all German federal states (bundeslaender) Evaluation of other forecasting methods (f.e. Delphi-methods)