1. Learning ObjectivesLearning Objectives  LO1: Define economics, microeconomics, and macroeconomics.  LO2: Identify John Maynard Keynes, Alfred Marshall, and Adam Smith, and their influence in economics.  LO3: State and explain the problem of scarcity and its relation to opportunity cost.  LO4: Explain how a rational decision maker applies the cost–benefit principle.  LO5: State how three pitfalls can undermine rational economic decisions.  LO6: Explain how data are used to evaluate economic theories.  LO7: Distinguish positive economics from welfare economics.  LO8: Define an economic naturalist. © 2012 McGraw-Hill Ryerson Limited Ch1 -1

2. LO6: Explain how data are used to evaluate economic theories  In the real world, many things can happen at the same time for many different reasons; therefore, one concept that is absolutely essential in evaluating theories is that of “all other conditions being held constant.” The Latin expression for “all else equal” is ceteris paribus.  Not all concerns about the realism of economics models are justified. Economic models that assume rational behaviour can lead to accurate predictions about the behaviour of large groups of people even if some people do not behave rationally. © 2012 McGraw-Hill Ryerson Limited Ch1 -2 LO6: Economic Theories and Data

3. LO6: Explain how data are used to evaluate economic theories  Models in economics or other disciplines cannot be perfectly realistic, but this is no more of a problem than the fact that a map is not a full- scale reproduction of the area it represents.  On the other hand, the predictions of models do depend on the assumptions they are based upon, and choosing the right assumptions makes the difference between a model that performs well and one that does not. © 2012 McGraw-Hill Ryerson Limited Ch1 -3 LO6: Economic Theories and Data

4. LO6: Explain how data are used to evaluate economic theories  As scientists, economists must be concerned with evaluating their predictions using evidence in the form of data. Formal evaluation of economic theories and predictions typically involves the application of econometrics.  In evaluating statistical evidence, it is important to be aware of possible pitfalls such as the fallacy of composition and the argument that a spurious correlation implies cause and effect.  If two variables move together but are otherwise unrelated, we have a spurious correlation. Cause and effect and correlation are two very different things.  The fallacy of composition occurs if one argues that what is true for a part must also necessarily be true for the whole. © 2012 McGraw-Hill Ryerson Limited Ch1 -4 LO6: Economic Theories and Data