Lecture 1 Static Microsimulation Models-Books Pdf

Lecture 1 Static microsimulation models
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Outline of the course, I Tax and benefit microsimulation models. 1 Static microsimulation models MSM, 2 Tutorial 1 using python for microsimulation. 3 Behavioural responses and dynamic MSM, 4 Tutorial 2 microsimulation in practice. II Modelling macro shocks and policies, 1 Evaluating the impact of macro shocks and policies on. poverty and income distribution, 2 Computable General Equilibrium models.
3 Integrating CGE and Microsimulation models, 4 Tutorial Integrating CGE and Microsimulation models. Outline of the lecture, I Why microsimulation, II Typology of modelling techniques. III Static microsimulation models, IV Example TAXIPP model for France. I Why microsimulation, 1 Evaluation, 3 Modelling complexity. I Why microsimulation, Evaluation of public policies.
Objectives, Inform policy makers on the impact of policy. Contribute to academic knowledge, Part of the democratic process. Methods of evaluation, Ex post evaluation methods, Natural experiments. Econometrics, Ex ante evaluation methods, Macrosimulation. Microsimulation, I Why microsimulation, Evaluation of public policies.
Microsimulation definition, Simulation based tool with micro unit of analysis. Simulate actual or counterfactual policies, Ex post evaluation of complex policies. Computer based laboratory for running policy experiment. ex ante evaluation, I Why microsimulation, Guy Orcutt 1917 2006. Guy Orcutt American Economist and, Econometrician Prof at Harvard. Wisconsin and Yale He joined the, Urban Institute to develop DYNASIM.
the dynamic microsimulation model of, the Institute. Existing models of our socio economic system have proved. to be of rather limited predictive usefulness This is. particularly true with respect to predictions about the. effects of alternative governmental actions, I Why microsimulation. Orcutt RESTAT 1957 AER 1960, Criticism of representative agent models common in. macroeconomics, Criticism of sectorial modelling a la Leontief. Non linear relationship at the individual level cannot be. estimated at the aggregated level, Distribution of variables across household is of major.
Main objectives, Modelling at the unit of decision individuals households. Simulation of the economy with computer power, Very ambitious project for the time. I Why microsimulation, Slow beginnings, Lack of computer power. Lack of micro data, Few attempts in the 1970s in demographics. Take off of the field, 1980 90s development of personal computer.
Explosion in computer power, From academia to administrations. Development of models in academia 1980s, Administrations have incorporated these models need for. significant resources, Specialized institutes Urban Institute NATSEM IFS. DIW ZEW CPB etc, I Why microsimulation, Microsimulation a tool for public debate. Debate around budget decisions, Debate around election platforms.
IFS and the Green Budget U K, TAXBEN model used for post budget analysis. Green Budget pre budget discussions, CPB Netherlands. Analysis of election platforms, Impact evaluation of policy proposals. Table 1 Some static microsimulation models, Country Model Institution Software. Australia STINMOD NATSEM SAS, Belgium Flanders MEFISTO Leuven Univ Euromod Java.
E U EUROMOD Essex Univ NET, Finland TUJA, France INES Insee Drees Cnaf SAS. France SAPHIR DG Tre sor SAS, France TAXIPP IPP Stata Python. Germany IZA MOD IZA Stata, Germany MIKMOD Min of finance Java. Ireland SWITCH ESRI C, Luxemburg LuxTaxBen LISER SAS. Sweden FASIT Statistics Sweden SAS, Sweden SWEtaxben Univ of Gothenburg SAS.
U K TAXBEN IFS Delphi Stata, U K Euromod Essex Univ NET. U K FORTAX A Shephard FORTRAN, U S TRIM3 Urban Institute C. U S TAXSIM NBER FORTRAN, Sources Li et al Table 3 1 p 53 with additions. I Why microsimulation, Modelling complexity, Population complexity. Complex units of decisions individuals couples family. Distribution of characteristics income demographics. occupation etc, Joint distribution of all these variables.
Policy complexity, Non linear tax and benefit schedules. Interaction between benefits taxes, Need modelling to assess impact of changes in policy. I Why microsimulation, Modelling complexity, Behavioural complexity. Different margins of behavioural responses labour supply. savings education etc, Heterogeneous preferences information set. Difference in behavioural responses at the individual level. Temporal complexity, Policy can depend on life cycle history e g pensions.
Behavioural responses can be dynamic, Historical analysis vs projections. Spatial complexity, Location can matter for policy behaviour population. heterogeneity, II Typology of microsimulation models. 1 Hypothetical models, 2 Static models, 3 Behavioural responses. 4 Dynamic models, 5 Agent based modelling, II Typology of microsimulation models.
Hypothetical models, Definition, Construct ideal synthetic individuals households. Focus on policy complexity, Objectives, Illustrative purpose. Validation, Cross country comparisons, Communication with the public. Lecture 1 Static microsimulation models Antoine Bozio Paris School of Economics PSE Ecole des hautes etudes en sciences sociales EHESS Master PPD Paris January 2019 1 81 Outline of the course I Tax and bene t microsimulation models 1 Static microsimulation models MSM 2 Tutorial 1 using python for microsimulation 3 Behavioural responses and dynamic MSM 4 Tutorial 2

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