Course Outline

Challenges Facing Forecasters for Government

  • Customer Demand Planning: Accurately predicting the needs of constituents to ensure effective resource allocation.
  • Investor Uncertainty: Managing financial forecasts in an environment with fluctuating market conditions and investment risks.
  • Economic Planning: Developing reliable economic projections to inform policy decisions and budgetary planning.
  • Seasonal Changes in Demand/Utilization: Accounting for periodic variations in service utilization to optimize resource deployment.
  • Roles of Risk and Uncertainty: Incorporating risk assessment and uncertainty management into forecasting models to enhance decision-making processes.

Time Series Methods for Government

  • Moving Average: A technique that averages data points over a specified period to smooth out short-term fluctuations and highlight longer-term trends.
  • Exponential Smoothing: A method that assigns exponentially decreasing weights to past observations, giving more importance to recent data.
  • Extrapolation: The process of extending current trends into the future to make predictions based on historical data.
  • Linear Prediction: A statistical technique that uses linear relationships between variables to forecast future values.
  • Trend Estimation: Analyzing long-term patterns in data to identify and predict underlying trends.
  • Growth Curve: Modeling the growth of a variable over time using mathematical functions to project future outcomes.

Econometric Methods (Causal Methods) for Government

  • Regression Analysis Using Linear Regression or Non-Linear Regression: Statistical techniques that model the relationship between dependent and independent variables to make predictions.
  • Autoregressive Moving Average (ARMA): A model that combines autoregressive and moving average components to forecast future values based on past data.
  • Autoregressive Integrated Moving Average (ARIMA): An extension of ARMA that includes differencing to handle non-stationary data, making it suitable for forecasting time series with trends or seasonality.
  • Econometrics: The application of statistical methods to economic data to test hypotheses and forecast economic trends.

Judgmental Methods for Government

  • Surveys: Collecting data through structured questionnaires to gather expert opinions and public sentiment.
  • Delphi Method: A structured communication technique that relies on a panel of experts to reach a consensus on future trends or outcomes.
  • Scenario Building: Developing detailed narratives of potential future scenarios to explore different outcomes and their implications.
  • Technology Forecasting: Predicting the development and impact of new technologies on government operations and services.
  • Forecast by Analogy: Using historical data from similar situations to make predictions about current or future events.

Simulation and Other Methods for Government

  • Simulation: Creating computer models to simulate complex systems and predict outcomes under various scenarios.
  • Prediction Market: Utilizing market mechanisms to aggregate individual forecasts into a collective prediction of future events.
  • Probabilistic Forecasting and Ensemble Forecasting: Methods that incorporate uncertainty by generating multiple possible outcomes and their probabilities.
  • Reference Class Forecasting: Comparing the current situation to historical data from similar contexts to make more accurate predictions.

Requirements

Proficiency with Excel or other spreadsheet software for government use

Strong mathematical and statistical knowledge for government applications

 14 Hours

Number of participants


Price per participant

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