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1.3    Data: Sources and Types	  53

   theory this experiment would estimate the effect on test scores of reducing class
   size, holding all else constant.

        The concept of an ideal randomized controlled experiment is useful because
   it gives a definition of a causal effect. In practice, however, it is not possible to
   perform ideal experiments. In fact, experiments are relatively rare in economet-
   rics because often they are unethical, impossible to execute satisfactorily, or pro-
   hibitively expensive. The concept of the ideal randomized controlled experiment
   does, however, provide a theoretical benchmark for an econometric analysis of
   causal effects using actual data.

   Forecasting and Causality

   Although the first three questions in Section 1.1 concern causal effects, the
   fourth—forecasting the growth rate of GDP—does not. You do not need to know
   a causal relationship to make a good forecast. A good way to “forecast” whether
   it is raining is to observe whether pedestrians are using umbrellas, but the act of
   using an umbrella does not cause it to rain.

        Even though forecasting need not involve causal relationships, economic
   theory suggests patterns and relationships that might be useful for forecasting. As
   we see in Chapter 14, multiple regression analysis allows us to quantify historical
   relationships suggested by economic theory, to check whether those relationships
   have been stable over time, to make quantitative forecasts about the future, and
   to assess the accuracy of those forecasts.

	 1.3	 Data: Sources and Types

                         In econometrics, data come from one of two sources: experiments or nonexperi-
                         mental observations of the world. This book examines both experimental and
                         nonexperimental data sets.

                   Experimental Versus Observational Data

                         Experimental data come from experiments designed to evaluate a treatment or
                         policy or to investigate a causal effect. For example, the state of Tennessee
                         financed a large randomized controlled experiment examining class size in the
                         1980s. In that experiment, which we examine in Chapter 13, thousands of students
                         were randomly assigned to classes of different sizes for several years and were
                         given standardized tests annually.
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