| Date | Venue | Fees | |
|---|---|---|---|
| 28 Sep - 02 Oct 2026 | Los Angeles - USA | $ 7,950 | |
| 21 - 25 Dec 2026 | London - UK | $ 5,950 | |
| 26 - 30 Apr 2027 | London - UK | $ 5,950 | |
| 27 Sep - 01 Oct 2027 | Los Angeles - USA | $ 7,950 | |
| 20 - 24 Dec 2027 | London - UK | $ 5,950 |
Introduction
This Practical Econometrics for Managerial Decision Making training course focuses on performing high-level multivariate econometric analysis using a range of business and economic data - with an emphasis on design, analysis, and drawing sound inferences to support strategic and operational decision-making. It's no longer specialty PhDs with $10,000 software packages doing high-end econometrics.
This training course dispels all the myths and misconceptions about intuitive multivariate modeling and analysis, making it practical-accessible for all managers using inexpensive software applications that work within industry standard Excel spreadsheets.
This Practical Econometrics training course will highlight:
- Working with a range of multivariate models, variables, and statistical output
- Modeling and hypothesis design, variable-selection, and managing big-data
- Developing original research projects, relational hypotheses, and parameters for inferences
- Understanding benefits and costs of primary data vs. secondary data for research
- Use of cross-sectional, time-series, longitudinal, and pooled cross-sectional data sets
- Comparing original research output with published research results on various topics
- Critical review, analysis, and critique of research models, methods, and conclusions drawn
Objectives
At the end of this Practical Econometrics training course, you will learn to:
- Design-produce an original research study
- Collect and format various types of data
- Perform different models of multivariate econometric analyses
- Analyze detailed statistical output from econometric model-software
- Draw inferences to support high-level managerial decision-making
- Write a detailed, yet succinct, executive summary of research findings
Training Methodology
This Practical Econometrics training course will use an inductive reasoning approach for introducing new terms-concepts-models-methods, followed with highly interactive case-discussion, and small-group team case projects applied directly to the attendees’ firms/organizations. The main focus is “hands-on” doing high level econometric modeling, analysis, and interpretation of statistical results.
Organisational Impact
Attendees will have immediate Return-On-Investment (ROI) to their own firms / organizations by bringing those requisite skills, models, and research practices directly to their workplace and colleagues.
The Return-On-Investment (ROI) is that attendees will be ready to demonstrate these tangible skills and competencies:
- Review, interpret, and critique existing/published econometric research studies
- Design and implement original econometric research for their firm, market, and industry
- Write high-level executive summaries with insights-inferences from econometric statistics
- Convert generic Big Data into actionable intel that improves organizational performance
Personal Impact
Attendees to this Practical Econometrics training course will further their own professional development by:
- Understanding key nuances, terminology, modeling of contemporary econometrics
- Gaining a new managerial mindset about “best practices” for applied business research
- Enhancing their use of formal and objective econometric models and statistical outputs
- Being able to objectively assess existing econometric studies’ data, output, and conclusions
- Learning proactive forward-thinking approaches to managing big data toward research design
- Bringing practical common-sense econometrics to both in-house and client-facing projects
Who should Attend?
This Practical Econometrics training course is suitable to a wide range of professionals but will greatly benefit:
- Research and Development / Product Development Teams looking for direct connections
- Business Development Staff looking to proactively open up new opportunities
- Financial Officers looking to design-execute original finance-accounting econometric research studies
- Revenue Officers looking to develop new forms and insights for marketing and competition research
- Board Members looking to fully monetize Big Data for the shareholders / stakeholders
Overview of Contemporary Econometrics and Decision Models
- Model Design, Hypotheses, Variables, Structure, Outcomes
- Quantitative and Qualitative Inputs
- Applications: From Wall Street to Marketing to Production to Consumer Behavior
- Software Options
- Linking Models and Confirmation Metrics
Understand Different Forms and Types of Research Data
- Cross Sectional Samples
- Time Series Sequences
- Longitudinal Tracking
- Pooled Cross-Sectional Aggregation
- Primary Data Costs and Acquisition
- Secondary Data Costs and Acquisition
- Descriptive Outcomes vs. Predictive Outcomes
- Dummy Variables / Indicators / Surrogates
Model and Hypothesis Design as Keys to Managing Big Data
- Targeted Outcomes Determine Input Formations
- Single-Variable vs. Multi-Variable Descriptors and Predictors
- Punctuated Trending vs. Real-time Fluidity
- Static Formations vs. Dynamic-Changing-Active Learning Models
- Correlation and Association vs. Cause-And-Effect
- Building Real Models for Delegates’ Firms, Industries, Markets
Designing Original Models for Your Firm, Competitive Market, and Industry
- Categorizing Decision Areas and Coordinating Data Availability
- Micro-economic vs. Macro-economic Decisions
- Indicators, Lagged Variables, Barometers / Bellwethers
- Running Several Rounds of Differing Regressions
- Managing Databases of Targeted Variables
- Problems of Multi-collinearity
- Problems of Autocorrelation
Presenting and Evaluating-Critiquing Original Econometric Findings
- Drawing Inferences Rather than Conclusions
- Caveats of Explaining Variance
- Individual and Team Presentations and Discussion-Interaction-Critique
- Confidence Intervals in Econometric Forecasts
- Packaging Analysis-results for Optimum Explanation
- Problems with Overreach from Statistical Outputs
- Personal-Managerial Bias Impacts Interpretation
- Distilling Data Output into Actionable Intel
- Disseminating Data Output for Maximum Decision Making Impact
- Upon successful completion of this training course, GLOMACS Certificate will be awarded to the delegates. Continuing Professional Education credits (CPE): In accordance with the standards of the National Registry of CPE Sponsors, one CPE credit is granted per 50 minutes of attendance