I.  Introduction to forecasting


  1. Why do we need forecasts? 

To make timely decisions in the face of uncertainty about the future.


  1. Who makes forecasts? 

Business, households, government, etc.


  1. What are the ingredients for good forecasting? 

Good judgment applied to the identification of appropriate information, and application of forecasting process.


  1. What is good judgement?

The ability to ask the right questions. 

a.  What are we concerned about?  Example:  age distribution of/population in year 2025 or next months sales.

            b.  What is the time period to be forecasted?

            c.  What is the level of aggregation required?

            d.  How much are we willing to spend to acquire information?

            e.  Is historical data relevant for the future?

            f.  What is the penalty for forecasting inaccuracy?


      5.  The Forecasting Process:

            a.  Collect appropriate data

            b.  Examine data patterns

            c. Choose a forecasting method (model)

            d.  Apply the model to past periods (ex post)

            e.  Examine the accuracy of model by examining ex post errors

            f.  If adequate (errors random and sufficiently small) use the model to     forecast the future (ex ante)

            g.  Periodically check the accuracy of forecasts with actual experience

h.  If inadequate errors, reexamine data patterns and choose an alternative forecasting method (model).


II.     What are the forecasting methods used? 

Qualitative versus quantitative.

Autoregressive versus causal. 

Judgemental versus scientific.


      Quantitative methods applied to forecasting:  Hotel feasibility study


            Autoregressive (time series) models:                  Causal models:

            1.  Naive                                                          1.  Simple regression

            2.  Averaging                                                    2.  Multiple regression

            3.  Smoothing                                                   3.  Econometric models

            4.  Decomposition

5.   Box-Jenkins


III.  The Business Cycle:  Past and Present


1.  Schools of Business Cycle Theory

            Differences based upon the role of causal forces affecting turning points (exogenous versus endogenous forces)

                        a.  Purely exogenous theories

                        b.  Underconsumption theories (endogenous)

                        c.  Overinvestment theories (time lags in information)

                        d.  Psychological theories (adds to uncertainty and mutual generation of                                     errors)  Keynesians

                        e.  Monetary theories (the role of limits to economic expansion)                                                 Monetarists

                        f.  The role of supply shocks--The Real Business Cycle Theory


2.  Mitchell’s Profit Theory of the Cycle

            Attempt to determine a purely endogenous theory of the cycle resulted in the formulation of the National Bureau for Economic Research latter transferred to the Department of Commerce.


3.  Forecasting in a market versus a “mixed” economy.  Increasing need for determining the role of outside influences:  political, social, environmental forces.


4.  How do we measure the business cycle?

            Personal income and employment?

            GDP (fixed versus chain weighted)


5.  Role of aggregate (absolute) versus relative (incremental) measures.


6.  The importance of disaggregation 

            Sources of personal income

            Components of GDP

            Other measures

                        Interdependence and diffusion indexes


7.  The role of commercial vendors

            Most likely and interval forecasts


8.  Forecasting tips