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Robert Tanton - One of the best experts on this subject based on the ideXlab platform.
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Projecting Small Area Statistics with Australian Microsimulation Model (SPATIALMSM)
The Australasian Journal of Regional Studies, 2020Co-Authors: Yogi Vidyattama, Robert TantonAbstract:'Think Global, Act Local' has become a theme for development planning of governments around the world. This is partly due to the increasing recognition of the importance of planning at a small area level. As a consequence, there is a need to derive estimates of socio-economic variables for local areas, and project these into future. Regional scientists have been involved in both the small area estimation and the application of regional estimates to Government policy. This paper will describe a new technique to project small area socio-economic statistics into the future using a spatial Microsimulation model. Spatial Microsimulation models are a new form of Microsimulation models that allow small area estimates of socio-economic variables to be derived from survey data, and allow scenario modelling using survey microdata. This paper extends the spatial Microsimulation methodology by adding a projection technique that allows projections of the microdata to be derived. The paper applies this method to project variables that target service delivery populations for Australian State Governments. The spatial Microsimulation method used also allows some scenario modeling, and the paper will calculate projections of service delivery populations after a scenario of increasing unemployment as a result of the global financial crisis.
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Methodological Issues in Spatial Microsimulation Modelling for Small Area Estimation
The International Journal of Microsimulation, 2020Co-Authors: Azizur Rahman, Ann Harding, Robert TantonAbstract:In this paper, some vital methodological issues of spatial Microsimulation modelling for small area estimation have been addressed, with a particular emphasis given to the reweighting techniques. Most of the review articles in small area estimation have highlighted methodologies based on various statistical models and theories. However, spatial Microsimulation modelling is emerging as a very useful alternative means of small area estimation. Our findings demonstrate that spatial Microsimulation models are robust and have advantages over other type of models used for small area estimation. The technique uses different methodologies typically based on geographic models and various economic theories. In contrast to statistical model-based approaches, the spatial Microsimulation model-based approaches can operate through reweighting techniques such as GREGWT and combinatorial optimization. A comparison between reweighting techniques reveals that they are using quite different iterative algorithms and that their properties also vary. The study also points out a new method for spatial Microsimulation modelling
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Spatial Microsimulation: Developments and Potential Future Directions
The International Journal of Microsimulation, 2017Co-Authors: Robert TantonAbstract:This paper summarises some of the latest developments in methods to estimate and validate spatial Microsimulation models. The paper also attempts to identify where the potential is for new areas of development in spatial Microsimulation models, based on the author’s reading of the spatial Microsimulation landscape in 2018. The methods outlined in this paper are identified as significant developments in the field, and include a number of new methods for calculating or adding indicators to a spatial Microsimulation model; as well as new methods of validation and estimating confidence intervals. Potential new areas of research include further development of methods for calculating confidence intervals; work on getting spatial Microsimulation into the mainstream of policy analysis; work on linking models to provide input into managing complex problems in society; and work on using big data in spatial Microsimulation models.
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Microsimulation modelling and the use of evidence
Evidence-Based Policy Making in the Social Sciences, 2016Co-Authors: Robert Tanton, Ben PhillipsAbstract:This chapter provides an overview of Microsimulation modelling and how it is used to evaluate policy with an emphasis on tax and government cash benefits. The chapter will provide a brief history and introduction to Microsimulation modelling.
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spatial Microsimulation a reference guide for users
2013Co-Authors: Robert Tanton, Kimberley L EdwardsAbstract:Part 1: Background: Chapter 1: Introduction to spatial Microsimulation - History, Methods and Applications: Robert Tanton and Kimberley Edwards.- Chapter 2: Building a static spatial Microsimulation model: data preparation: Rebecca Cassells, Riyana Miranti and Ann Harding.- Part 2: Static spatial Microsimulation models.- Chapter 3: An Evaluation of Two Synthetic Small-Area Microdata simulation methodologies: Synthetic Reconstruction and Combinatorial Optimisation methodologies: Paul Williamson.- Chapter 4: Estimating Small Area Income Deprivation: An Iterative Proportional Fitting Approach: Ben Anderson.- Chapter 5: SimObesity: Combinatorial Optimisation (deterministic) model: Kimberley Edwards and Graham Clarke.- Chapter 6: Spatial Microsimulation using a generalised regression model: Robert Tanton, Ann Harding and Justine McNamara.- Chapter 7: Creating a Spatial Microsimulation model of the Irish Local Economy: Niall Farrell, Karyn Morrissey and Cathal O'Donoghue.- Chapter 8: Linking static spatial Microsimulation modelling to meso-scale models: The Relationship between Access to GP services & Long Term Illness: Karyn Morrissey, Graham Clarke and Cathal O'Donoghue.- Chapter 9: Projections using a static Spatial Microsimulation model: Yogi Vidyattama and Robert Tanton.- Chapter 10: Limits of static Spatial Microsimulation models: Robert Tanton and Kimberley Edwards.- Part 3: Dynamic spatial Microsimulation models.- Chapter 11: Moses: A dynamic spatial Microsimulation model for demographic planning: Belinda Wu and Mark Birkin.- Chapter 12: Design principles for micro models: Einar Holm and Kalle Makila.- Chapter 13: SimEducation: a dynamic spatial Microsimulation model for understanding educational inequalities: Dimitris Kavroudakis, Dimitris Ballas and Mark Birkin.- Chapter 14: Challenges for spatial dynamic Microsimulation modelling: Mark Birkin.- Part 4: Validation of spatial Microsimulation models and conclusion.- Chapter 15: Validation of spatial Microsimulation models: Kimberley Edwards and Robert Tanton.- Chapter 16: Conclusions and the future of spatial Microsimulation modelling: Graham Clarke and Ann Harding.
Amedeo Spadaro - One of the best experts on this subject based on the ideXlab platform.
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Microsimulation Models in the Analysis of Redistribution Policies: An Outline
2020Co-Authors: Francois Bourguignon, Amedeo SpadaroAbstract:During the last twenty years, Microsimulation models have been increasingly used in the analysis of redistribution policies. This note provides a brief survey discussion of these Microsimulation with particular emphasis on the recent developments of this discipline and directions for future research.
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Microsimulation as a tool for evaluating redistribution policies
Journal of Economic Inequality, 2006Co-Authors: Francois Bourguignon, Amedeo SpadaroAbstract:During the last 20 years, Microsimulation models have been increasingly applied in qualitative and quantitative analysis of public policies. This paper discusses Microsimulation techniques and their theoretical background as a tool for the analysis of public policies. It next analyses basic principles for using Microsimulation models and interpreting their results, with emphasis on tax incidence, redistribution and poverty analysis. It then discusses social welfare analysis permitted by Microsimulation techniques and points to the limits of present approaches and some directions for future developments.
Joachim Merz - One of the best experts on this subject based on the ideXlab platform.
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MICSIM-4j - A General Microsimulation Model User Guide (Version 1.1)
2020Co-Authors: Joachim Merz, Lars RuschAbstract:Microsimulation models allow targeted simulations to analyze the impacts of alternative policies, measures, scenarios based on microunits like persons, families, households, firms etc. Meanwhile it is out of question that Microsimulation models are a helpful, successful and an imperative instrument for a wide range of policy analyses in the political administration, business area, private and university institutes and consulting groups in general. Though there is a multitude of Microsimulation models nowadays developed and in use, however, in most cases they still need skilled handling and experience or another program system when applied. A general, generic stand-alone and platform independent Microsimulation model which provides all necessary simulation tools under a common shield, and which is easy to use for non-expert scholars, is still required. The overall objective of this paper and of the new MICSIM-4J is to describe and offer such a userfriendly, non-technical and powerful general Microsimulation model, to support impact microanalyses for applied research, teaching and consulting. Though the stand-alone MICSIM-4J as a general tool also allows dynamic model building, its focus is on static Microsimulation with a powerful module for the adjustment of microdata.
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micsim concept developments and applications of a pc Microsimulation model for research and teaching
Social Science Microsimulation [Dagstuhl Seminar May 1995], 1996Co-Authors: Joachim MerzAbstract:It is the growing societal interest about the individual and its behaviour in our and 'modern' societies which is asking for microanalyses about the individual situation. In order to allow these microanalyses on a quantitative and empirically based level Microsimulation models were developed and increasingly used for economic and social policy impact analyses. Though Microsimulation is known and applied (mainly by experts), an easy to use and powerful PC Microsimulation model is hard to find. The overall aim of this study and of MICSIM - A PC Microsimulation Model is to describe and offer such a user-friendly and powerful general Microsimulation model for (almost) any PC, to support the impact microanalyses both in applied research and teaching. Above all, MICSIM is a general microdata handler for a wide range of typical microanalysis requirements. This paper presents the concept, developments and applications of MICSIM. After some brief remarks on Microsimulation characteristics in general, the concept and substantive domains of MICSIM: the simulation, the adjustment and aging, and the evaluation of microdata, are described by its mode of operation in principle. The realisations and developments of MICSIM then are portrayed by the different versions of the computer program. Some MICSIM applications and experiences in research and teaching are following with concluding remarks..
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Social Science Microsimulation - MICSIM: Concept, Developments, and Applications of a PC Microsimulation Model for Research and Teaching
SSRN Electronic Journal, 1995Co-Authors: Joachim MerzAbstract:It is the growing societal interest about the individual and its behaviour in our and 'modern' societies which is asking for microanalyses about the individual situation. In order to allow these microanalyses on a quantitative and empirically based level Microsimulation models were developed and increasingly used for economic and social policy impact analyses. Though Microsimulation is known and applied (mainly by experts), an easy to use and powerful PC Microsimulation model is hard to find. The overall aim of this study and of MICSIM - A PC Microsimulation Model is to describe and offer such a user-friendly and powerful general Microsimulation model for (almost) any PC, to support the impact microanalyses both in applied research and teaching. Above all, MICSIM is a general microdata handler for a wide range of typical microanalysis requirements. This paper presents the concept, developments and applications of MICSIM. After some brief remarks on Microsimulation characteristics in general, the concept and substantive domains of MICSIM: the simulation, the adjustment and aging, and the evaluation of microdata, are described by its mode of operation in principle. The realisations and developments of MICSIM then are portrayed by the different versions of the computer program. Some MICSIM applications and experiences in research and teaching are following with concluding remarks..
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Microsimulation - A Survey of Methods and Applications for Analyzing Economic and Social Policy
1994Co-Authors: Joachim MerzAbstract:This essential dimensions of Microsimulation as an instrument to analyze and forecast the individual impacts of alternative economic and social policy measures are surveyed in this study. The basic principles of Microsimulation, which is a tool for practical policy advising as well as for research and teaching, are pointed out and the static and dynamic (cross-section and life-cycle) approaches are compared to one another. Present and past developments of Microsimulation models and their areas of application are reviewed, focusing on the US, Europe and Australia. Based on general requirements and components of Microsimulation models a Microsimulation model's actual working mechanism are discussed by a concrete example: the concept and realization of MICSIM, a PC Microsimulation model based on a relational database system, an offspring of the Sfb 3 Statitic Microsimulation Model. Common issues of Microsimulation modeling are regarded: micro/macro link, behavioural response and the important question of evaluating Microsimulation results. The concluding remarks accentuate the increasing use of microcomputers for Microsimulation models also for teaching purposes.
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Microsimulation as an Instrument to Evaluate Economic and Social Programmes
1993Co-Authors: Joachim MerzAbstract:In recent years Microsimulation models (MSMs) have been increasingly applied in quantitative analyses of the individual impacts of economic and social programme policies. The suitability of using Microsimulation as an instrument to analyze main and side policy impacts at the individual level will be discussed in this paper by characterizing: the general approach and principles of the two general Microsimulation approaches: static and dynamic (cross-section and lifecycle) Microsimulation, the structure of MSMs with institutional regulations and behavioural response, panel data and behavioural change, deterministic and stochastic Microsimulation, the 4M-strategy to combine microtheory, microdata, microestimation and Microsimulation, and pinpointing applications and recent developments. To demonstrate the evaluation of economic and social programmes by Microsimulation, two examples concerning a dynamic (cross-section and life-cycle) Microsimulation of the German retirement pension reform and a combined static/dynamic Microsimulation of the recent German tax reform with its behavioural impacts on formal and informal economic activities of private households are briefly described. Evaluating the evaluation of economic and social programmes with Microsimulation models finally is followed by concluding remarks about some future developments.
Cathal O'donoghue - One of the best experts on this subject based on the ideXlab platform.
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Spatial Microsimulation for Rural Policy Analysis - Spatial Microsimulation for rural policy analysis
Advances in Spatial Science, 2020Co-Authors: Cathal O'donoghue, Graham Clarke, Stephen Hynes, Dimitrios Ballas, Karyn MorrisseyAbstract:The aim of this book is to explore the challenges facing rural communities and economies and to demonstrate the potential of spatial Microsimulation for policy and analysis in a rural context. This is done by providing a comprehensive overview of a particular spatial Microsimulation model called SMILE (Simulation Model of the Irish Local Economy). The model has been developed over a ten year period for applied policy analyis in Ireland which is seen as an ideal study area given its large percentage of population living in rural areas. The book reviews the policy context and the state of the art in spatial Microsimulation against which SMILE was developed, describes in detail its model design and calibration, and presents example of outputs showing what new information the model provides using a spatial matching process. The second part of the book explores a series of rural issues or problems, including the impacts of new or changing government or EU policies, and examines the contribution that spatial Microsimulation can provide in each area.
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Spatial Microsimulation Modelling: a Review of Applications and Methodological Choices
The International Journal of Microsimulation, 2020Co-Authors: Cathal O'donoghue, Karyn Morrissey, John LennonAbstract:Spatial Microsimulation modelling has developed for over a half century and is now a mainstream analytical tool within the Microsimulation community accounting for a very significant proportion of papers at conferences and within the journal. There have been a number of recent surveys of “mainstream” spatial Microsimulation models and associated methodologies. The contribution of this paper relates mainly in extending these surveys by considering other micro based simulation models that incorporate a spatial or geographic dimension. We feel this is important as in many areas of Microsimulation modelling, there are parallel literatures that have developed that apply simulation techniques to micro units that are not labelled Microsimulation or in the case of the papers reviewed in this paper not labelled spatial Microsimulation. The paper reviews a number of different application areas of spatially focused Microsimulation models, including demography, welfare, health, regional development, transport planning, agri-environmental analysis, crisis planning, land use and planning. We also review a number of the methodological choices made by modellers including scope, and spatial disaggregation, data sources, data creation methodology, validation and calibration and simulating change
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A methodological survey of dynamic Microsimulation models
2020Co-Authors: Jinjing Li, Cathal O'donoghueAbstract:More than 10 years ago O'Donoghue (2001) surveyed the dynamic Microsimulation models that had been developed up to that point. However the 2000's have seen many of the barriers that existed for model development up until that point overcome. This paper surveys the development and practices in dynamic Microsimulation over the past decade, and discusses the methodological challenges today. The paper provides an overview of the methodological choices made in more than 60 known dynamic Microsimulation models and examines the advantages and disadvantages of different practices. In addition, this paper reviews the main progress made in the field and explores how future Microsimulation models could evolve.
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LIAM2: a New Open Source Development Tool for Discrete-Time Dynamic Microsimulation Models
Journal of Artificial Societies and Social Simulation, 2014Co-Authors: Gaëtan De Menten, Gijs Dekkers, Geert Bryon, Philippe Liégeois, Cathal O'donoghueAbstract:Most existing Microsimulation models have been developed by separate (teams of) researchers. The drawback of each team working on its own is that they have to put a lot of time and effort in the customary development of fairly general simulation tools. Hence, economies of scale cannot be exploited, which makes Microsimulation models even more expensive than strictly necessary. The objective of this paper is to present LIAM2, a free and open source modelling framework designed for the development of discrete-time dynamic models. It is meant to make Microsimulation models much easier to develop. This paper makes a comparison with other simulation frameworks, presents a minimal LIAM2 model and discusses its performance in terms of data capacity and simulation speed.
M. Lemessi - One of the best experts on this subject based on the ideXlab platform.
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Winter Simulation Conference - An SLX-based Microsimulation model for a two-lane road section
Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304), 2001Co-Authors: M. LemessiAbstract:A car-following and lane-changing Microsimulation model of a two-lane road section has been written in SLX (Simulation Language with eXtensibility) as part of an extensive research project by the University of Rome Transport Department to qualify and quantify the environmental impact of traffic. The Microsimulation model is part of a three-step approach, involving a traditional transport macroscopic model, the microscopic model, and an ultra-micro model. The Microsimulation model's car-following and lane-changing rules are presented and described in detail, and model outputs are commented. The paper includes a short description of the Microsoft Visual Basic user-interface developed by the author and the animation performed by means of Proof Animation.
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An SLX-based Microsimulation model for a two-lane road section
Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304), 2001Co-Authors: M. LemessiAbstract:A car-following and lane-changing Microsimulation model of a two-lane road section has been written in SLX (Simulation Language with eXtensibility) as part of an extensive research project by the University of Rome Transport Department to qualify and quantify the environmental impact of traffic. The Microsimulation model is part of a three-step approach, involving a traditional transport macroscopic model, the microscopic model, and an ultra-micro model. The Microsimulation model's car-following and lane-changing rules are presented and described in detail, and model outputs are commented. The paper includes a short description of the Microsoft Visual Basic user-interface developed by the author and the animation performed by means of Proof Animation.
