Course description
The Rcademy Practical Econometrics Course for Effective Managerial Decision-Making emphasizes design, analysis, and how to draw sound inferences to support strategic and operational decision-making. Participants are exposed to how to perform high-level multivariate econometric analysis using a variety of business and economic data. The training course integrates advanced multivariate econometrics modeling ideas, variable analysis, interpretation, and applications to forecasting and managerial decision-making. In addition to performing fundamental econometric analysis, the course teaches participants how to interpret and apply econometrics outputs to various quantitative and qualitative problem-solving situations. It covers all aspects of hypothesis testing, variable selection, data types, statistical analysis, error tolerances, inferences, insights, correlations, and trends. The course begins with the basics of econometrics, an overview of managerial decision-making and economics, and ends with critiquing original econometric findings.
What is an effective managerial decision-making process?
Decisions determine how a business will develop. While making, the correct choices can boost profitability, foster growth, and sustain stability, making the wrong ones can have the opposite effect and even endanger the health of a firm. Decisions made by managers, therefore, have a significant impact on businesses. The goal of an efficient managerial decision-making process is to enable the effective and efficient performance of corporate tasks while also resolving recognized problems. It requires being able to comprehend data, interpret it, and use it.
What is the relevance of statistics in effective managerial decision-making?
The mathematical and statistical examination of economic relationships is frequently used as a foundation for financial forecasting. Governments occasionally utilize such data to formulate monetary policy, while private businesses use it to make choices regarding prices, inventories, and output. Despite the abundance of data available, statistics give managers greater confidence in handling uncertainty, allowing them to act more quickly and wisely while also giving their workforce, who depend on them, stronger leadership.
Upcoming start dates
Suitability - Who should attend?
The Practical Econometrics for Managerial Decision-Making Training Course by Rcademy is designed to help participants achieve the following objectives:
- Recognize the fundamental concepts, terminology, and modeling used in modern economics
- Develop a new managerial outlook on the best methods for doing applied business research
- Understand the use of formal, unbiased economic models and statistical results
- Able to evaluate the data, results, and conclusions of existing econometric studies with objectivity
- Discover proactive, forward-looking methods for handling massive data for research design
- Bring sensible, real-world econometrics to internal and external enterprises
- Recognize techniques for obtaining information to aid in making decisions
- Learn to evaluate and rate alternatives to find the best solutions
Training Course Content
Module 1: Basics of Econometrics
- Introduction to econometrics
- Introduction to sense-making
- Types of variables
- Types of economic data
- The goals of econometrics
- The stages of econometrics
- Residuals and regression types
- Scales of measurement
Module 2: Overview of Managerial Decision-Making
- Introduction to managerial decision-making
- Strategic analysis
- Programmed and non-programmed decisions
- Strategic management process
- Decision-making process
– Decision recognition
– Alternative generation
– Implementation and evaluation
– Alternative analysis and selection
Module 3: Managerial Economics
- Introduction
- Nature of managerial economics
- Scope of managerial economics
- Principles of managerial economics
- Consumer demand
- Price elasticity of supply
- Managerial and microeconomics
Module 4: Econometrics: Methods and Applications
- Introduction
- Simple regression
- Model specification
- Multiple regression
- Endogeneity
- Binary choice
- Time series
Module 5: Overview of Contemporary Econometrics and Decision Models
- Introduction
- Confirmation metrics
- Model design and outcomes
- Structure, hypotheses, and variables
- Qualitative inputs
- Quantitative inputs
- Software Options
- Linking models
Module 6: Observational Decision-Making with Econometrics
- Introduction
- Non-central location measures
- Central location measures
- Quantifying dispersion in sample data
- Transformation of numeric descriptors to profile numeric sample data
- Breakdown analysis of numeric measures
- Numeric measures distribution (Bimodal and skewness)
- Relationships between numeric descriptors
Module 7: Understand Different Types and Forms of Research Data
- Longitudinal tracking
- Pooled cross-sectional aggregation
- Cross-sectional samples
- Surrogates and indicators
- Time series sequences
- Primary acquisition and data costs
- Secondary acquisition and data costs
- Descriptive outcomes
- Dummy variables
- Predictive outcomes
Module 8: Keys to Managing Big Data: Model and Hypothesis Design
- Targeted outcomes input formations
- Single-variable descriptors and predictors
- Multi-variable descriptors and predictors
- Punctuated Trending
- Real-time Fluidity
- Static figures, active learning models
- Dynamic-changing active learning models
- Association and correlation cause-and-effect
- Accurate models for delegates’ markets, industries, and firms
Module 9: Models for Firm, Industry, and Competitive Market
- Coordinating data availability
- Managing databases of targeted variables
- Micro-economic decisions
- Macro-economic decisions
- Barometers and bellwethers
- Categorizing decision areas
- Indicators and lagged variables
- Rounds of differing regressions
- Problems of multi-collinearity
- Problems of autocorrelation
Module 10: Presenting and Evaluating: Critiquing Original Econometric Findings
- Packaging analysis results for optimum explanation
- Caveats in explaining variance
- Drawing inferences rather than conclusions
- Confidence intervals in econometric forecasts
- Problems with overreach from statistical outputs
- Discussion, critique, and interaction
- Personal managerial bias impacts the interpretation
- Data output distillation
- Data output dissemination
Course delivery details
This course is designed to fulfill the needs of participants while also improving their knowledge and skills in the field. This course will be presented using a variety of practical ways to ensure attendees’ active and continuous learning. Renowned experts and professionals with years of work and experience will teach the course. The course modules are also based on thorough research into the subject.
The Rcademy Practical Econometrics Course for Effective Managerial Decision-Making integrates practical and theoretical learning by providing attendees with cases, studies, lectures, slides on the concepts, and real-life scenarios. Participants will also engage in presentations, seminar workshops, quizzes, and regular feedback on lessons learned to confirm their optimum satisfaction.
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Rcademy is a global training and consultation organisation set out to bridge the gap between you now and what you can be in the near future. We are facilitators of knowledge impartation. Our team of established and experienced training enthusiasts...