Forecasting

7511 Words Feb 18th, 2012 31 Pages
Between a Causal Model And a Time- Series Model?
In: Business and Management
Choose One Of The Forecasting Methods And Explain The Rationale Behind Using It In Real Life. What Is The Difference Between a Causal Model And a Time- Series Model?
Choose one of the forecasting methods and explain the rationale behind using it in real life.
I would choose to use the exponential smoothing forecast method because it weighs the most recent past data more strongly than more distant past data. This makes it so that the forecast will react more strongly to immediate changes in the data. This is good to examine when dealing with seasonal patterns and trends that may be taking place. I would find this information very useful when examining the
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I. INTRODUCTION
Despite a recent revival in research, comparatively little is known about firm growth or its determinants. Indeed, standard microeconomics textbooks say little or nothing about the topic. Understanding how firms grow, however, especially small firms, is an important issue. In most U.S. industries, small firms account for much of the capital stock, employment, and a surprisingly large fraction of innovations (Acs and Audretsch, 1988, 1990). Studying firm growth can provide insights into the dynamics of the competitive process, strategic behavior, the evolution of market structure, and perhaps even the growth of the aggregate economy. This paper examines the long-standing theory that the growth of most small firms is constrained by the available quantity of internally generated finance. Butters and Lintner (1945) provide some of the earliest research to support this theory. They examine the early histories of several industries and conclude that: "[m]any small companies−even companies with promising growth opportunities−find it extremely difficult or

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