MultiPOP – DIDAKTOR Project

Project Summary

The current project is entitled “Multidimensional ambiguous stochastic dynamical models with applications to Cyprus population distribution (MultiPOP)” (POST-DOC/0916/0139). The project is implemented within the “Framework Programme for Research, Technological Development and Innovation RESTART 2016-2010” (Pillar II: Sustainable RTDI system – DIDAKTOR Programme) of the Cyprus Research Promotion Foundation (RPF). The project is co-funded by the European Regional Development Fund and the Republic of Cyprus, through the RPF. The project duration is 36 months (to be completed by October 31st, 2021).

The proposed research project involves both interesting and challenging theoretical and application-oriented research in the context of complex and ambiguous stochastic multidimensional population models for policy-making and planning. The main objective is to provide a new approach to the modeling and analysis of stochastic dynamical population models subject to uncertainty and ambiguity to the stage that these tools are readily accessible not only to the research world but also to demographers, social scientists, and government agencies, and can be applied generically across the field of population sciences.

The consortium of the present project is comprised of a balanced team of research organizations and an individual researcher. In particular, it involves three universities namely the University of Cyprus (Cyprus), the University of Ottawa (Canada), and Aalto University (Finland), and an individual researcher from the Italian National Institute of Statistics.

 
 
 

Project Objectives

In this project, we will develop a new Science, Technology, Engineering, and Mathematics (STEM) approach to the modeling and analysis of dynamical population models through the study of modern systems and stochastic control theory. Our aim is to provide a general mathematical framework for the study of multidimensional ambiguous stochastic dynamical models with application to the Cyprus population for policy-making and planning. In particular, through this project we wish: (i) first to develop a mathematical tool known as the Total Variation distance metric that captures the “ambiguity effect” on stochastic dynamical models, and codifies the impact of incorrect dynamical models on the performance of optimal decisions; (ii) then apply this tool to model the short-term and long-term distribution of the population by considering different categorical variables/dimensions, using the interesting case study of Cyprus; (iii) develop efficient parameter estimation algorithms that center on the estimation of missing statistical data necessary for the analysis of multidimensional population models. We believe that the developed multidimensional ambiguous stochastic dynamical population models and the identified parameters will be useful aids in governmental efforts to address some of the fundamental questions that concern Cyprus society, such as: (a) what is the role of immigration in Cyprus society, and how should the target level of immigration be determined so as to satisfy the work power demand and keep the unemployment rate low, and (b) what economic policies should the Cyprus government adopt to support the needs of different population groups and at the same time safeguard robust public finances, necessary to maintain internal macroeconomic stability. The long-term objective of the study is to gain an increased understanding of the natural evolution of different population groups and how they interact with each other which may, in turn, lead to a better understanding of social and political problems and lead to improved, more efficient, and viable socio-economic policies.

The major Scientific and Technological Objectives are the following:

  • To provide a mathematical analysis of ambiguous stochastic dynamical models to address the risk of having incorrect population models and to deal with the optimality of stochastic control policies, by employing Total Variation distance metric as a new tool for codifying the level of ambiguity. The developed mathematical theory will set the stage for the rest of the project and will provide modeling methods and optimality criteria, including the principle of optimality and dynamic programming.

  • To develop and test stochastic dynamical population models describing the population variation in Cyprus by any set of given characteristics such as age, sex, education level, employment, and marital status. The population models, which will take into account some potential sources of uncertainty, will be developed starting from simple to more complex and complete models and will capture the short-term and long-term projections of population growth. Furthermore, to expand the multidimensional stochastic dynamical population models by including the region (place) of residence as an additional categorical variable/dimension. The developed “multiregional” models will be provided as an improved tool for the assessment of spatially differentiated impacts of national and/or regional policies.

  • To address the lack of adequate statistical data by studying issues related to parameter identification and parameter estimation problems. The developed data estimation methods will provide efficient mathematical toolsets for identifying a large number of unknown parameters, which are embedded in the multidimensional dynamical population models.

  • To formulate optimum immigration and job creation stochastic policies while maintaining population levels close to certain pre-specified targets. Two different stochastic optimization methods will be used to determine the best immigration and job creation policies subject to any number of constraints that may be applicable, and the uncertainty in the models. Both methods are expected to result in optimum immigration and job creation policies that can be well formulated for fixed as well as for variable target sets, to avoid population decline, to solve the aging problem, and to maintain the necessary labor force for economic growth.

  • To address cost issues associated with different social and economic programs supported by the Cyprus government, and to identify resource allocation strategies that are important for short-term and long-term planning. The cost of several ongoing programs, as well as new programs like education, welfare, childcare, old age pension, etc., will be estimated. Through the costing of the appropriate allocation of various programs high-quality cost estimates that are optimum and comprehensive will be evaluated to support the needs of different population groups.

Impact

In this project, we will develop a new STEM approach to the modeling and analysis of ambiguous stochastic dynamical models for addressing the risk of having incorrect population models and to deal with the optimality of stochastic control policies. The developed approach is proposed as an improved tool, which can be used by scientists, demographers, and government agencies so that better and more efficient political and economic strategies can be formulated in the future. For the implementation of the project, a well-organized consortium has been created consisting of leading researchers in stochastic control systems, system identification, statistics and demography, and social and political sciences. The formation of this collaborative team presents the opportunity for considerable advancement in population dynamics for policy-making and planning, through the study of modern systems and stochastic control theory.

Theoretical and practical development of the new STEM approach will be focused at addressing some of the fundamental questions concerning the role of immigration in Cyprus society and how to determine the best immigration policies so that specific population growth can be sustained and in addition to calculate what the immigration rate should be so as to satisfy the manpower demand and keep the unemployment rate low, and also, what economic policies the Cyprus government should adopt to support the needs of different population groups and at the same time safeguard robust public finances necessary to maintain internal macroeconomic stability. These are at the heart of attempts to provide a basis for a comprehensive understanding of the population growth of Cyprus through which optimum immigration and job creation policies can be designed, and short and long-term costs of various social and economic programs can be accurately estimated.

Nowadays, foreign workers and other classes of people migrate in developed countries, having as one of their choice criteria the attractiveness of the social system, in their pursuit of better living standards and higher net incomes. Cyprus is a popular destination for new immigrants due to its geographical location, its European Union membership, and its generous welfare systems, all of which attract potential welfare recipients from other countries with less generous systems. Immigration plays an increasingly important role for any country’s growth as well as for maintaining its culture, but it can also cause many social and political problems if the government specifies no limits to immigration levels. From the implementation of this project, one can identify specific parameters that affect population growth and determine stochastic optimum immigration and job creation policies so as to satisfy the workforce demand and at the same time keep the unemployment rate low. We expect that this work will provide an effective tool to avoid population decline, maintain the necessary labor force for economic growth, and thereby ensure a balance between social and political problems.

Apart from contributions to the advancement of science, the expected results from the implementation of this project will also be an asset to the government in terms of short and long term planning to meet the specific needs of different groups of population in Cyprus. The impact of the recent financial crisis that hit the Cyprus economy has unavoidably affected the money the government spends for social programs in an effort to align with the policies of the Macroeconomic Adjustment Programme. It is clear now that as the economy is exiting the financial crisis, the government has found itself at a very challenging pace confronting higher economic and social needs in conjunction with policies to strengthen economic growth and bring the economy back to a sustainable and steady growth path. Through the costing of the appropriate allocation of several social programs, i.e., health care, old-age pension, unemployment insurance, etc., new and more efficient short-term and long-term government policies will be developed to support the needs of different population groups. Thus, the current research has important consequences in addressing social-economic policies and moreover estimating the viability of these policies.

Work Packages

The project structure has been organized into seven work packages numbered from WP1 to WP7, representing: one management work package, WP1; one dissemination work package, WP2; and five technical research & development work packages, WP3 through WP7. WP1 and WP2 span the entire duration of the project and are intended to monitor the progress of the project and the dissemination of the results.

A brief description of WP3 to WP7 is outlined below.

  • WP3 will set the stage for the rest of the project by formally introducing the general mathematical framework in which we are interested in. In particular, through WP3 we will provide a mathematical analysis for ambiguous stochastic control models to address the risk of having incorrect models and to deal with the optimality of stochastic control policies. With the completion of this work package, a new approach to the modeling and analysis of ambiguous stochastic control models will be developed, and an improved tool for policy-making and planning will emerge.

  • WP4 constitutes a fundamental part of the project and will involve research aiming at developing Multidimensional Stochastic Dynamical Population Models (SDPM). With the completion of this work package, SDPM will be developed to characterize the population variation in Cyprus by any set of given characteristics such as age, sex, education level, marital status, employment and place of residence, and to examine various policy implications on the overall growth and structure of the population.

  • WP5 focuses on developing mathematical methods for estimation and identification of system parameters, as they appear in the models. The successful completion of WP5, which will last a total of 10 months, is essential for the upcoming work packages.

  • WP6 involves the application of the results of the previous work packages to develop optimum immigration and job creation stochastic policies, in order to avoid population decline, to solve the aging problem and to maintain the necessary labor force for economic growth. This is to be achieved by using the optimality conditions for ambiguous stochastic control models, the SDPM, the identified parameters, and certain stochastic optimization methods.

  • WP7 will focus on evaluating the cost of various social and economic programs, and to identify resource allocation strategies that are important for short-term and long-term planning. The cost of several programs like education, welfare, childcare, old age pension, etc., will be estimated.

Consortium

HO: University of Cyprus  Cyprus www.ucy.ac.cy
FRO1: University of Ottawa Canada www.uottawa.ca
FRO2: Aalto University Finland www.aalto.fi
External Services
  • Participating Personnel: Dr. Federico Benassi
Italy

Deliverables

Deliverable* Description Work Package Status
D1 Interim progress report WP1 Completed
D2 Final progress report WP1 Pending
D3 Minutes/Agenda of the consortium meetings WP1 Pending
D4 Workshop package (agenda/invitation /pdf presentation/list of participants) WP2 Pending
D5 List of publications and other relevant activities WP2 Pending
D6 Published research papers WP2 Pending
D7 Project webpage WP2 Completed
D8 Modeling methods for ambiguous stochastic control systems (Report) WP3 Completed
D9 Optimality criteria including the principle of optimality and dynamic programming (Report) WP3 Completed
D10 Multidimensional stochastic dynamical population models (Report) WP4 Completed
D11 Simulation package (Software) WP4 Completed
D12 Mathematical methods and algorithms for estimation and identification of system parameters (Report) WP5 Pending
D13 Simulation package (Software) WP5 Pending
D14 Optimum immigration and job creation policies (Report) WP6 Pending
D15 Simulation package (Software) WP6 Pending
D16 Costing of several socio-economic programs (Report) WP7 Pending
D17 Simulation package (Software) WP7 Pending

Dissemination of Results

Peer-Reviewed Publications:
TitleAuthorsAffiliationsConferenceJournal
[1] Infinite Horizon Average Cost Dynamic Programming subject to Total Variation Distance AmbiguityIoannis Tzortzis, Charalambos D. Charalambous and Themistoklis Charalambous*University of Cyprus, Aalto University*SIAM Journal on Control and Optimization (SICON)
[2] Robust LQG for Markov Jump Linear SystemsIoannis Tzortzis, Charalambos D. Charalambous, and Christoforos N. HadjicostisUniversity of CyprusIEEE Conference on Decision and Control (CDC 2019)
[3] Canonical Dynamic Programming Equations subject to AmbiguityIoannis Tzortzis and Charalambos D. CharalambousUniversity of CyprusIFAC World Congress (IFAC 2020)
[4] Jump LQR Systems with Unknown Transition ProbabilitiesIoannis Tzortzis, Charalambos D. Charalambous, and Christoforos N. HadjicostisUniversity of CyprusIEEE Transactions on Automatic Control (TACON)
Software Apps:
TitleMATLAB Central
Modelling Population Dynamics AppMPD App (version 1)