Practical Econometrics for Managerial Decision Making

Start Date End Date Venue Fees (US $)
31 May 2026 Riyadh, KSA $ 3,900 Register
06 Sept 2026 Kuala Lumpur, Malaysia $ 4,500 Register
15 Nov 2026 Dubai, UAE $ 3,900 Register

Practical Econometrics for Managerial Decision Making

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.

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

Course Outline

Day 1: 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

Day 2: 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

Day 3: 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

Day 4: 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

Day 5: 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

Accreditation

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