TAILIEUCHUNG - Toward improved models for decision making in economics

We elaborate upon four major revelations in statistical science toward improving traditional models for decision-making in social science, in particular in economics. | Asian Journal of Economics and Banking 2019 03 01 1-19 1 ĨRƯỜA Asian Journal of Economics and Banking ISSN 2588-1396 http . vn Home Toward Improved Models for Decision Making in Economics Hung T. Nguyen1 2 Department of Mathematical Sciences New Mexico State University USA 2Faculty of Economics Chiang Mai University Thailand Article Info Abstract Received 9 12 2018 Accepted 15 01 2019 Available online In Press Keywords Bayesian statistics Bohmian mechanics Decision-making Econometric models Expected utility Finance Machine learning Predictions P-values Quantum mechanics Quantum probability JEL classification CIO MSC2010 classification 60A99 62C99 We elaborate upon four major revelations in statistical science toward improving traditional models for decision-making in social science in particular in economics. These revelations concern how to repair statistical inference procedures based on the notion of p-values how to correctly obtain predictive modeling how to improve expected utility theory in economics and how to faithfully model economic dynamics . tCorresponding author Hung T. Nguyen Department of Mathematical Sciences New Mexico State University USA. Email addrcss hunguycn@ 2 Asian Journal of Economics and Banking 2019 3 1 1-19 1 INTRODUCTION If we ask what is new in statistical science at the dawn of the 21st century we may not get a clear answer instead we get either big data or data science and this sounds like until now everything is fine as far as statistical science is concerned so that let s face the challenging data-driven problems which obviously will be important for economic applications . Why new things are important in any kinds of sciences physical or social Well remember the dawn of the last century from Newton mechanics to Einstein s relativity and quantum mechanics. If we just view data science as the new things to focus on we might ignore the crucial fact that as a common definition data science is a combination of .

• Kinh tế học
• Bayesian statistics
• Bohmian mechanics
• Decision making
• Econometric models
• Expected utility
• Machine learning
• Mathematical Statistics
• Introduction to Mathematical Statistics
• Optimal Tests of Hypotheses
• Nonparametric statistics
• Think Bayes
• Bayesian Statistics Made Simple
• Software Performance
• Operating Committee
• Statistical Analysis
• Methods in psychology
• The error statistical perspective
• The new statistics
• Philosophy of statistics
• Business statistics
• Simple linear regression
• Multiple regression
• Time series
• Decision analysis
• Sampling methods
• Multivariate analysis
• Genome Biology
• Allele specific binding
• ChIP sequencing
• FAIRE sequencing
• Copy number change
• Allele frequency
• BMC Bioinformatics
• Homology based methods
• Multiple sequence alignment
• Sequence homology
• Error checking
• Survival analysis
• Hypothesis testing
• Bayesian methods
• Hematologic Disorders
• Hemolytic Anemia
• Immunologic Tolerance
• RNA Seq
• Unreplicated experiments
• Differential gene expression
• Sequencing coverage
• RNA binding proteins
• RNA protein interactions
• Cell type specific SNPs
• Tumour heterogeneity
• Cancer evolution
• Diagnosis tumours
• Bulk sequencing
• BMC Genomics
• Capture Hi C
• Chromatin conformation
• Variable selection
• Constrained Contingency
• Inequality Constrained
• Bayesian Evaluation
• Encompassing Prior
• Bayes Factors
• The binomial distribution
• likelihood estimation
• sampling distribution
• Updating one’s prior beliefs
• posterior density
• Bayesian analysis
• BMC Cancer
• Skeletal metastasis
• Prognostic model
• Postoperative survival
• Lecture Tourism theory concepts and models
• Tourism theory
• Tourism models
• The political economy of tourism
• Keynesian economics
• Marxist perspectives
• expected information
• matching priors
• multiparameter case
• Concluding remarks
• Objective Bayesian