Chapter 6: Forecasting Handouts



Chapter 6: Forecasting Handouts

Macroeconomic Forecasting: involves predicting aggregate measures of economic activity at the international, national, regional, or state level.

• Examples:

o Gross Domestic Product (GDP)

o Inflation

o Unemployment Rates

o Interest rates

o Consumer Spending/Consumer Confidence

o Trade Balance (exports and imports)

o Government Spending

• These leading economic indicators are routinely discussed in the national media because they impact all business activity.

• Important for business managers to have good information about the overall health of the economy in predicting sales and cost.

Microeconomic Forecasting: involves predicting disaggregate economic data at the industry, firm, plant, or product level.

• Examples:

o Demand for clothing

o Cost of cotton

• Typically not discussed in the national media because they are sector specific and generally have a much narrower focus and impact on the economy

• Very important for business managers to track input prices and other indicators that affect your sector specifically.

Problems in Forecasting:

• Changing expectations

o The way that consumers and producers feel about the state of the economy will heavily influence their demand for goods.

o Because consumer spending is the largest component of GDP, if consumers believe that the economy will weaken and begin to withhold demand, they can actually speed up the economic downturn (self-fulfilling prophecy). Surveys on consumer confidence.

o Producers have the same effect: if they believe the economy is strengthening and they want to increase inventory so product is available for consumers, they will increase production, thereby increasing either employment and/or wages, and the economic rebound is accelerated.

• Data Quality Problems

o Need accurate and reliable data adjusted for inflation, seasonality, etc. Lag in government data that is constantly revised.

o The more data points (observations) you have, the better.

Common Forecast Techniques:

1. Qualitative Analysis

• Use of expert opinion and panel consensus: having those actively involved in the area provide their own personal insight or have a group of experts discuss the issue and come to a consensus.

o

• Survey information: may be able to pick up some of the psychological behavior that drives economic decision-making and provide better information regarding consumers’ tastes and preferences. It is difficult to get information on tastes and preferences from other sources such as sales.

• Qualitative analysis is rarely used alone. It is typically a supplement to some type of quantitative analysis.

2. Trend Analysis and Projection

• This quantitative tool is predicated on the idea that future relationships are defined by historical relationships.

• Use time-series data (data that spans a period of time such as 5 years)

• Types of trends: (Graphs pp. 206-207)

o Secular trend or just “trend”: is the long run pattern of increase or decrease in a series of economic data.

▪

o Cyclical Fluctuation: rhythmic variation in economic series that is due to a pattern of expansion or contraction in the overall economy.

▪

o Seasonal variation or seasonality: rhythmic annual pattern in sales or profits caused by weather, consumer habit, or social custom.

▪ Ex:

▪ Ex:

o Irregular or random influences, called “external shocks”: are unpredictable shocks to the economic system and the pace of economic activity caused by war, strikes, natural disasters, etc.

• Two types of Trend Analysis:

o Linear Trend Analysis: assumes a constant period-by-period unit change in an important economic variable over time.

▪

▪

▪

▪ Find trend value (t) and forecast sales (S):

o Suppose you have sales data from 1999 to 2009 and you’re predicting sales for 2010.

o

o

o Estimate sales equation: S=a + b * t using regression analysis.

o Computer generates equation as: S= 5000 + 1350t

o Forecast for 2010:

o Growth Trend Analysis: assumes a constant period-by-period percentage change in an important economic variable over time.

▪ Ex:

▪

▪ Ex:

▪ Sales in t years depend on Current Sales (S0), the growth rate, g, and the # of years, t, in the future you’re forecasting: St = S0(1+g)t

▪

3. Exponential Smoothing: method for forecasting trends in unit sales, unit costs, wage expenses, etc.

• Identifies historical patterns of trend or seasonality in the data and then extrapolates these patterns forward into the forecast period.

• Basically, exponential smoothing is an averaging technique.

• Several types of exponential smoothing:

o One parameter (simple) exponential smoothing: is used to forecast slowly changing levels or almost constant levels of sales, expense, etc. Most appropriate for forecasting sales in very mature markets with no seasonality component. Allows for a constant growth in sales (flat).

o Two parameter (Holt) exponential smoothing: is used to forecast stable growth in markets. The data will fluctuate about a level that is changing with some constant or slowly drifting trend. Allows for basic growth trend.

o Three parameter (Winters) exponential smoothing: is used to forecast seasonally adjusted growth in markets. Best suited for markets with rapid growth and rapid decay with seasonal influences. Allows for growth trend and a seasonal component.

▪ Insert graph p. 222 of the Product Life Cycle

o Phase I:

▪

o Phase II:

▪

o Phase III:

▪

o Phase IV: Decline and abandonment

▪

4. Econometric Methods/Regression Analysis:

• Allows you to use historical data to isolate the effect of each independent variable (P, I, Psub, etc) on the dependent variable (Qd)

• Can compare forecasts of your model with actual data to improve your model in the future

• Results give you the magnitude and direction of the effect on the dependent variable from a change in an independent variable (ex: when Price increases by $1.00, Qd decreases by 32.3 units)

• Provides the most accurate estimate

................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download