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BUSINESS economics. Class 9 9 December, 2009. Recap. Cost Curves Marginal Cost Curve Average Cost Curve Fixed and Variable Costs Short-run and Long-run Costs Price Control Ceiling and floor pricing Support price Monopoly restrictions. Price Controls. Criticism
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BUSINESS economics Class 9 9 December, 2009
Recap • Cost Curves • Marginal Cost Curve • Average Cost Curve • Fixed and Variable Costs • Short-run and Long-run Costs • Price Control • Ceiling and floor pricing • Support price • Monopoly restrictions
Price Controls • Criticism • Prices kept artificially low • Demand is increased to the point where supply can not keep up • Shortages in the price-controlled product. • Shortages lead to black markets where prices for the same good exceed those of an uncontrolled market. • Once controls are removed, prices will immediately be subject to rampant inflation, which can temporarily shock the economic system. • Example of how price controls cause shortages • Arab oil embargo between October 19, 1973 and March 17, 1974. • Long lines of cars and trucks quickly appeared at retail gas stations in the U.S. and some stations closed because of a shortage of fuel. • The fixed price was below what the market would otherwise bear and, as a result, the inventory disappeared.
Forecasting Techniques • Forecasting is the establishment of future expectations by the analysis of past data, or the formation of opinions. • Forecasting is an essential element of capital budgeting. • Capital budgeting requires the commitment of significant funds today in the hope of long term benefits. The role of forecasting is the estimation of these benefits.
Quantitative Forecasting • Quantitative: Regression with related variable • Data set of ‘Sales’ as related to both time and the number of households.
Quantitative Forecasting • Quantitative: Sales plotted related to households.
Regression • Straight line Y = mx + C is the trend line that represents the regressed data • Co-efficient of the Y axis intercept and slope can be derived using regression analysis.
Regression Analysis • Predicting with the regression output. • Regression equation is: • Sales(for year) = -348.218 + ( 3.316 x households). • Assuming that a separate data set forecasts the number of households at 1795 for the year 2006, then: • Sales(2006) = -348.218 + ( 3.316 x 1795) = 5,604 units.
Time series • Sales plotted as a function of time.
Forecasting Routes Top-Down where international and national events affect the future behaviour of local variables.
Forecasting Routes Where local events affect the future behaviour of local variables. Bottom-Up
Forecasting: Summary • Sophisticated forecasting is essential for capital budgeting decisions • Quantitative forecasting uses historical data to establish relationships and trends which can be projected into the future • Qualitative forecasting uses experience and judgment to establish future behaviours • Forecasts can be made by either the ‘top down’ or ‘bottom up’ routes.