1. Intro to Business Forecasting Virtually all business decisions require decision- makers to form expectations about business/market conditions in the future. Hiring Purchase of raw materials, semi-finished and finished goods for inventories Plant/store closures Purchase of capital goods (machinery, factories trucks, commercial office space, …)

2. The goal of forecasting To transform available data into equations that provide the best possible forecasts of economic variables—e.g., sales revenues and costs of production—that are crucial for management.

3. Time -series data: historical data--i.e., the data sample consists of a series of daily, monthly, quarterly, or annual data for variables such as prices, income, employment, output, car sales, stock market indices, exchange rates, and so on. Observations correspond to hours, days, months, quarters, … Cross-sectional data: All observations in the sample are taken from the same point in time and represent different individual entities (such as persons, households, corporations, states, etc.) Types of data

4. Example of Time Series Data

5. Student IDSexAgeHeightWeight 777672431M216’1”178 lbs. 231098765M285’11”205 lbs. 111000111F195’8”121 lbs. 898069845F225’4”98 lbs. 000341234M206’2”183 lbs. Example of cross sectional data

6. Two Kinds of Forecasting Structural : Use data (time series or cross-sectional) to estimate (precisely) structural relationships between a dependent variable (sales, profits, …) and one or more independent (explanatory) variables. Time Series: Use only past values of the variable of interest (profits, sales, …) to forecast future values.