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Demystifying Causal Inference : Public Policy Applications with R / / Vikram Dayal and Anand Murugesan
| Demystifying Causal Inference : Public Policy Applications with R / / Vikram Dayal and Anand Murugesan |
| Autore | Dayal Vikram |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore Pte Ltd., , [2023] |
| Descrizione fisica | 1 online resource (304 pages) |
| Disciplina | 320.6 |
| Soggetto topico |
Political planning - Data processing
Political planning - Statistical methods R (Computer program language) - Statistical methods |
| ISBN | 981-9939-05-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Acknowledgements -- Contents -- About the Authors -- 1 John Snow and Causal Inference -- 1.1 Grey Skies and Cholera Deaths in London -- 1.2 Curious Dr. Snow's Early Investigations -- 1.2.1 Unpacking the Mode of Communication of Cholera -- 1.2.2 Snow's Clinical Work on the Pathology of Cholera -- 1.2.3 Mechanisms and Conditions of Cholera Transmission -- 1.3 Cholera, a Waterborne Disease -- 1.4 The Interesting but Inconclusive Broad Street Pump Incident -- 1.5 The Grand Experiment in London -- 1.5.1 Snow's Shoe-Leather Work for Identifying the Causal Links -- 1.6 Snow's Quasi-experimental Design -- 1.6.1 Treatment Intensity and Comparative Cases -- 1.7 Archimedean Lever: Instrumental Variables -- 1.8 Potential Outcomes -- 1.9 The Chapters Ahead -- 2 RStudio and R -- 2.1 Introduction -- 2.2 RStudio -- 2.3 Use Projects and a Script -- 2.4 Typical R Code -- 2.4.1 Making a Vector -- 2.4.2 Installing and Loading Packages -- 2.4.3 Data -- 2.4.4 Graphs -- 2.4.5 Regression -- 2.5 Bare Bones Example of Working with R -- 2.6 Resources -- 2.6.1 For Better Understanding -- 2.6.2 For Exploring Further -- 3 Regression and Simulation -- 3.1 Introduction -- 3.2 Sampling Distribution and Simulation -- 3.3 Mean and Regression -- 3.3.1 Estimating the Mean is the Same as Regressing on a Constant -- 3.3.2 Sampling Distribution of the Mean -- 3.4 Bivariate Regression -- 3.4.1 Bivariate Regression and Conditional Means -- 3.4.2 Sampling Distribution of the Regression Coefficient in a Bivariate Regression -- 3.4.3 Estimating a Difference is the Same as Regressing on an Indicator Variable -- 3.5 The P Value Function: A Tool for Inference -- 3.6 Systematic and Random Error -- 3.7 Resources -- 3.7.1 For Better Understanding -- 3.7.2 For Going Further -- 4 Potential Outcomes -- 4.1 Introduction -- 4.2 Basic Ideas -- 4.3 Basic Identity of Causal Inference.
4.4 Rubin Doctor Example -- 4.5 Assumptions for Causal Inference Using Potential Outcomes -- 4.6 Manski Bounds: Recidivism -- 4.7 R Code (Corresponding to Section 4.4) -- 4.8 Resources -- 4.8.1 For Better Understanding -- 4.8.2 For Going Further -- 5 Causal Graphs -- 5.1 Introduction -- 5.2 Concepts and Examples -- 5.2.1 Causal Graphs for Two Variables -- 5.2.2 Causal Graphs for Three Variables -- 5.2.3 Causal Graphs with ggdag Package -- 5.2.4 Assumptions for Causal Inference Using Causal Graphs -- 5.2.5 Electoral Systems -- 5.2.6 Collider Bias in Public Health -- 5.3 R code -- 5.3.1 Causal Graphs for two Variables (Corresponding to Section 5.2.1) -- 5.3.2 Causal Graphs for Three Variables (Corresponding to section 5.2.2) -- 5.3.3 ggadag use (Corresponding to section 5.2.3) -- 5.3.4 Electoral Systems (Corresponding to section 5.2.5) -- 5.4 Resources -- 5.4.1 For Better Understanding -- 5.4.2 For Going Further -- 6 Experiments -- 6.1 Introduction -- 6.2 Examples and Concepts -- 6.2.1 Anchoring Affects Judgments -- 6.2.2 Women as Policymakers -- 6.2.3 Small Class Size and Student Learning Outcomes -- 6.2.4 Simulate to Understand -- 6.3 R Code -- 6.3.1 Anchoring Affects Judgments -- 6.3.2 Women as Policymakers -- 6.3.3 Small Class Size and Student Learning Outcomes -- 6.3.4 Simulate to Understand -- 6.4 Resources -- 6.4.1 For Better Understanding -- 6.4.2 For Going Further -- 7 Matching -- 7.1 Introduction -- 7.2 Concepts and Examples -- 7.2.1 Lalonde's Study -- 7.2.2 Simple Numerical Example -- 7.2.3 Generating Apples to Apples -- 7.2.4 Exact Matching -- 7.2.5 Coarsened Exact Matching -- 7.2.6 Decentralized Forest Management -- 7.2.7 Propensity Score Matching -- 7.2.8 Mahalanobis Distance Matching -- 7.2.9 Genetic Matching -- 7.2.10 Model Dependence and Cherry-Picking -- 7.3 R Code -- 7.3.1 Lalonde's Data -- 7.3.2 Decentralized Forest Management. 7.3.3 Your Turn, Compensation for Injury -- 7.4 Resources -- 7.4.1 For Better Understanding -- 7.4.2 For Exploring Further -- 8 Instrumental Variables -- 8.1 Introduction -- 8.2 Concepts and Examples -- 8.2.1 A Basic Example with an Encouragement Design -- 8.2.2 Prologue to Leveraging Instrumental Variables -- 8.2.3 Colonial Origins of Economic Development -- 8.2.4 Globalization, Voter Preferences, and Brexit -- 8.2.5 Wrights' Lever Solves the `Chicken and Egg Problem' -- 8.2.6 Taxes and Consumption of Cigarettes -- 8.2.7 Overidentification Test is only Indicative of IV Validity -- 8.3 R Code -- 8.3.1 A Basic Example with an Encouragement Design -- 8.3.2 Colonial Origins of Economic Development -- 8.3.3 Globalization, Voter Preferences, and Brexit -- 8.3.4 Taxes on Consumption of Cigarettes -- 8.3.5 Overidentification is Only Indicative of IV Validity -- 8.4 Resources -- 8.4.1 For Better Understanding -- 8.4.2 For Going Further -- 9 Regression Discontinuity Design -- 9.1 Introduction -- 9.2 Concepts and Examples -- 9.2.1 Minimum Legal Drinking Age and Fatalities in the US -- 9.2.2 Term Limits and Politician Performance in Brazil -- 9.2.3 Rural Roads and Economic Development in India -- 9.3 R Code -- 9.3.1 Minimum Legal Drinking Age and Fatalities in the US -- 9.3.2 Term Limits and Politician Performance in Brazil -- 9.3.3 Rural Roads and Economic Development in India -- 9.3.4 Simple Example with Simulation -- 9.4 Resources -- 9.4.1 For Better Understanding -- 9.4.2 For Going Further -- 10 Panel Data and Fixed Effects -- 10.1 Introduction -- 10.2 Concepts and Examples -- 10.2.1 Schooling and Wages -- 10.2.2 Alcohol Policies and Traffic Fatalities -- 10.2.3 Causal Graphs for Panel Data -- 10.2.4 Income and Democracy -- 10.3 R Code -- 10.3.1 Schooling and Wages -- 10.3.2 Alcohol Policies and Traffic Fatalities -- 10.3.3 Causal Graphs for Panel Data. 10.3.4 Income and Democracy -- 10.4 Resources -- 10.4.1 For Better Understanding -- 10.4.2 For Going Further -- 11 Difference-in-Differences -- 11.1 Introduction -- 11.2 Concepts and Examples -- 11.2.1 Worker Injury Benefits and Time Out of Work -- 11.2.2 Great Depression Policies to Avoid Banking Collapse -- 11.2.3 Snow's Prototype DID Design -- 11.2.4 Assumptions and DID Validity -- 11.2.5 Informative Bounds on the Effect of Right-to-Carry Gun Laws -- 11.2.6 The Synthetic Control Method -- 11.3 R Code -- 11.3.1 Worker Injury Benefits and Time Out of Work -- 11.3.2 Great Depression Policies to Avoid Banking Collapse -- 11.3.3 Informative Bounds on the Effect of Right-to-Carry Gun Laws -- 11.3.4 Economic Costs of German Reunification -- 11.4 Resources -- 11.4.1 For Understanding Better -- 11.4.2 For Going Further -- 12 Integrating and Generalizing Causal Estimates -- 12.1 Introduction -- 12.2 Concepts and Examples -- 12.2.1 Statistical Approach -- 12.2.2 Analyses Guided by the Potential Outcomes Framework -- 12.2.3 Analyses Guided by Causal Graphs -- 12.3 R Code -- 12.3.1 Statistical Approach -- 12.3.2 Analyses Guided by the Potential Outcomes Framework -- 12.3.3 Analyses Guided by Causal Graphs -- 12.4 Resources -- 12.4.1 For Better Understanding -- 12.4.2 For Going Further. |
| Record Nr. | UNINA-9910746977403321 |
Dayal Vikram
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| Singapore : , : Springer Nature Singapore Pte Ltd., , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Quantum decision theory and complexity modelling in economics and public policy / / Anirban Chakraborti, Emmanuel Haven, Sudip Patra, Naresh Singh, editors
| Quantum decision theory and complexity modelling in economics and public policy / / Anirban Chakraborti, Emmanuel Haven, Sudip Patra, Naresh Singh, editors |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing AG, , 2023 |
| Descrizione fisica | 1 online resource (viii, 251 pages) : illustrations (some color) |
| Disciplina | 530.12 |
| Altri autori (Persone) |
ChakrabortiAnirban
HavenEmmanuel <1965-> PatraSudip SinghNaresh |
| Collana | New Economic Windows Series |
| Soggetto topico |
Decision making - Mathematical models
Economics - Statistical methods Political planning - Statistical methods |
| ISBN | 3-031-38833-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Part I Quantum Decision Theory -- 1 A Brief Overview of the Quantum-Like Formalism in Social Science -- Introduction -- Quantum Versus Quantum-Like -- Quantum Probabilistic Modelling of Decision Making: Is This Exotic? -- What is the Main Advantage of Quantum Information Processing? -- Classical Versus Quantum Probability -- Classical (Bayesian) Versus Quantum (Generally non-Bayesian) Rationality and Social Lasing -- Agreeing to Disagree -- Classical Physics Formalism in Economics and Finance -- Quantum-Like Formalism in Economics and Finance -- Conclusion -- References -- 2 Cooperative Functioning of Unconscious and Consciousness from Theory of Open Quantum Systems -- Introduction -- A Few Words About Quantum Formalism -- Indirect Measurement Scheme: Apparatus with Meter Interacting with a System -- More Technical Details -- Indirect Measurements of Mental Observables: Unconscious as a System and Consciousness as a Measurement Apparatus -- Contextuality -- Concluding Remarks -- References -- 3 Hilbert Space Modelling with Applications in Classical Optics, Human Cognition, and Game Theory -- Introduction -- A Brief Mathematical Detour -- Complex Euclidian Space -- Inner Products and Norms of Vectors -- Direct Sums and Direct Products -- Linear Operator Space -- Examples of Hilbert Spaces -- Operations on Hilbert Spaces -- Bounded and Un-Bounded Operators in Hilbert Space -- Hilbert Space in QM -- Born's Rule: A Small Note -- Application of Hilbert Space in Probability Theory -- Applications of Hilbert Space Representation Outside QM -- Hilbert Space Representation of Classical Optics -- Classical and Quantum Entanglements -- Human Cognition and Decision Modelling -- COM Approach (Patra and Ghose) -- Discussion: Application of COM in Game Theory -- References.
4 Remodeling Leadership: Quantum Modeling of Wise Leadership -- Introduction -- Leadership -- Quantum Basics -- Classical and Quantum Ontology -- Quantum Modeling: Probability and Subjectivity -- Using Quantum-Like Modeling in Social Science -- Non-optimal But Normal Behavior -- Order Effects in Human Cognition -- Conjunction and Disjunction Effects -- Heisenberg-Robertson Inequalities -- Contextuality and Randomness -- Emergence of Concept Combinations Through Entanglement -- Emergent Cognitive State -- Modeling Wise Leader Interaction with Context -- Social Interaction Dynamics -- Implications for Leadership and Wisdom Research -- Wise Leaders as Entangled Actors -- Final Comments -- Appendix 1 -- Appendix 2 -- References -- 5 Quantum Financial Entanglement: The Case of Strategic Default -- Introduction -- Cognitive Entanglement -- Quantum Decision Theory -- Strategic Default -- Social Entanglement -- Financial Entanglement -- Discussion -- Conclusions -- References -- 6 Quantum-Like Contextual Utility Framework Application in Economic Theory and Wider Implications -- Introduction -- Epstien's Framework -- Modelling Background -- Overview of Quantum-Like Modelling Set Up -- Model Set-Up -- Model -- Partial Ambiguity Resolution: Dynamics and Hamiltonian Formulation -- Ambiguity Aversion- Attraction and Diversity of Investors' Opinion and Asset Pricing -- Entropic Measures -- POVM in Decision Models -- Conclusion and Further Discussion -- Objective or Subjective Probabilities? -- Application of Quantum-Like Modelling in Wider Context of Complex Economy -- Interpreting the Model- Real World Implications and Decision Making -- References -- Part II Complexity Modeling in Economics and Public Policy -- 7 Complexity Economics: Why Does Economics Need This Different Approach? -- What Difference Does Complexity Economics Make? -- Closing Thoughts. Questions and Answers -- 8 Policy and Program Design and Evaluation in Complex Situations -- Introduction -- Sense-Making in Today's World -- The Cynefin Framework -- The Stacey Matrix -- Integral (Meta) Theory (Ken Wilber) -- Complex Adaptive Systems (CAS) and How They Add Value to Public Policy -- Why Complex Adaptive Systems Thinking is Important to Public Policy -- Value Added of CAS to Public Policy -- Applications of CAS Public Policy -- Economics -- Power and Politics -- Law -- Health -- Education -- Sustainability and Complexity -- Program Design in Complex Systems -- Dealing with Complexity in Policy Design -- Monitoring and Evaluation in Complex Situations -- From New Public Management to Human Learning Systems -- Conclusion -- References -- 9 Market State Dynamics in Correlation Matrix Space -- Introduction -- Methodology -- Data Description -- Evolution of Cross-Correlation Structures -- Wishart Orthogonal Ensembles -- Power Map Technique -- Pairwise (dis)similarity Measures and Multidimensional Scaling -- Identifying States of a Financial Market -- Sectorial Analysis -- Trajectories in the Correlation Matrix Space -- Comparison of COVID-19 Case with Other Crash and Normal Periods -- Conclusions and Future Outlook -- References -- 10 Interstate Migration and Spread of Covid-19 in Indian States -- Introduction -- Impact of Pandemic on Migrants -- Data and Methodology -- Data -- Methodology of Network Construction -- Visualization of Complex Network of Migration -- Network Plots Using the Census-2011 Data -- Network Plots Using Covid-19 Special Train Data -- Possible Relationship Between Covid-19 Cases and Migrants -- Relationship Between Migration and Spread to Covid-19 -- Conclusion and Policy Recommendations -- References -- 11 Trade Intervention Under the Belt and Road Initiative with Asian Economies -- Introduction. Data and Methodology -- Gravity Model -- Neural Network Model -- Dataset -- Results and Analysis -- Conclusions -- Appendix -- References -- 12 Innovation Diffusion with Intergroup Suppression: A Complexity Perspective -- Introduction -- The Model -- Model for 2 Groups -- Two Group Example with Stable Positive Equilibrium -- Empirical Data on Tablet Use -- Conclusion -- References -- Epilogue: Nobel Prize in Physics for Complexity Studies and Weather Behavior-Implications for Social Sciences and Public Policy -- References. |
| Record Nr. | UNINA-9910746290303321 |
| Cham : , : Springer International Publishing AG, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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