Navigating the Complexity of Climate Change: A Closer Look at the Scientific Method and Its Challenges
The physical sciences have greatly advanced knowledge by elucidating the workings of simple phenomena. In a simple phenomenon, we have a limited number of important variables, all of which are identifiable and measurable. This allows us to run a scientific experiment. In such an experiment, we hold all other variables constant and examine the influence of one variable on the phenomenon. We can therefore measure this variable’s direction and how important it is to this phenomenon. We can then do this same experiment to all the other variables to determine their direction of influence and relative importance. We can identify which assumed relationships are correct and which are wrong. We can draw conclusions on hypotheses about simple phenomena.
Complex phenomena, on the other hand, have some or many unmeasurable or unobservable factors or variables, whose influences and interactions may vary. Thus, it is impossible to run a scientific experiment to separate the influences of each factor. This greatly limits the value of empirical or historical evidence on complex phenomena since it is impossible to distinguish between causation and association.
Economists know this problem all too well. Over a hundred years ago, the limits of empiricism in economics were made crystal clear. In the article “The Elasticity of Demand for Wheat,” R. A. Lehfeldt (1914) attempted to determine the elasticity of demand by looking at the historical data of the price of wheat against the consumption of wheat. He attempted to correct for changes in other factors (ceteris paribus) and found the elasticity of the demand for wheat to be a positive factor of 0.6.
Should we conclude from this study that the demand
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