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Growth Curve Modeling: Theory and Applications by Michael J. Panik

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PREFACE

The concept of growth is all-pervasive. Indeed, issues concerning national economic growth, human population growth, agricultural/forest growth, the growth of firms as well as of various insect, bird, and fish species, and so on, routinely capture our attention. But how is such growth modeled and measured?

The objective of this book is to convey to those who attempt to monitor the change in some variable over time that there is no “one–size-fits-all” approach to growth measurement; a growth model useful for studying an agricultural crop will most assuredly not be appropriate for fishery management. And if, for instance, one is interested in calculating a growth rate for some time series data set, a decision has to be made as to whether or not one needs to determine a relative rate of growth, an average annual growth rate, an ordinary least squares growth rate, a geometric mean growth rate, among others. Moreover, the choice of a growth rate is subject to the idiosyncrasies of the data set itself, for example, we need to ask if the data series is trended or if it is stationary and if it is presented on an annual, a quarterly, or monthly basis. But this is not the whole story—we also need to ask if the appropriate growth curve should be linear, sigmoidal (S-shaped), with an upper asymptote, or, say, increases to a maximum and then decreases thereafter.

The aforementioned issues concerning the selection of a growth modeling methodology are of profound importance to those looking ...

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