Course Introduction

"Doing econometrics can feel like trying to learn the laws of electricity by playing the radio." - Economist Guy Orcutt

“Econometrics is the quantitative analysis of actual phenomena, based on the concurrent development of theory and observation, related by inferences.”  Economist Paul Samuelson

This comprehensive training course will integrate the concepts, variable-analysis, interpretation, and applications to forecasting and managerial decision making of sophisticated multivariate econometrics modeling.

It will provide senior managers with high-level skills and techniques to both perform basic econometric analysis, as well as interpret and apply econometrics outputs to a wide range of quantitative and qualitative problem-solving – covering all facets of hypothesis testing, variables selection, data types, statistical analysis and error tolerances, along with inferences-insights, correlations, and trends.

The Oxford Management Centre training Course will utilize inexpensive software applications linked within Excel to perform high-level econometric research-analysis-review on par with the “best practices” used in contemporary economics, corporate forecasting, and Wall Street investment banking – helping managers become fluent in the terminology and process-application of econometrics to everyday decision making contexts.

Objectives

Specifically you will learn to:

• Design and produce all facets of an original business research study
• Collect and format various types of quantitative and qualitative data
• Perform different models of multivariate econometric analyses with applications in Excel
• 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

Who Should Attend?

• CFOs looking to design-execute original finance-accounting econometric research studies
• CEOs looking to improve quantitative-based decision -making
• CROs looking to develop new forms and insights for marketing and competition research
• Board Members looking to fully monetize Big Data for the shareholders/stakeholders
• R+D/ Product Development Teams looking for direct connections
• Business Development Directors looking to proactively open up new opportunities

Course Outline

• Model Design, Hypotheses, Variables, Structure, Outcomes, Quantitative and Qualitative Inputs
• Software Options - Linking Models and Confirmation Metrics
• Cross Sectional Samples - Time Series Sequences - Longitudinal Tracking
• Primary Data vs. Secondary Data Costs and Acquisition .
• Descriptive Outcomes vs. Predictive Outcomes - Dummy Variables / Indicators / Surrogates
• Single-Variable vs. Multi-Variable Descriptors and Predictors - Correlation vs. Cause-And-Effect
• Punctuated Trending vs. Real-time Fluidity - Static Formations vs. Dynamic-Changing Models
• Micro-economic vs. Macro-economic Decisions - Indicators, Lagged Variables, Barometers/Bellwethers
• Problems of Multicollinearity and Autocorrelation - Caveats of Explaining Variance
• Drawing Inferences Rather than Conclusions and Confidence Intervals in Econometric Forecasts
• Packaging analysis-results for Optimum Explanation & Problems with Overreach of Statistical Outputs
• Personal-Managerial Bias Impacts Interpretation and Distilling Data Output into Actionable Intel
• Disseminating Data Output for Maximum Decision Making Impact