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 GLOMACS 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 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 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 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 GLOMACS Practical Econometrics for Managerial Decision Making 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