The Nature of Econometrics and Economic data Here is an example of an equation that was derived through reasoning. E M PLE.2 (Job Training and worker productivity) Consider the problem posed at the beginning of Section 1. 1. a labor economist would like to examine the effects of job training on worker productivity. In this case, there is little need for formal economic theory. Basic economic understanding is sufficient for realizing that factors such as education, experience, and training affect worker productivity. Also, econ omits are well aware that workers are paid commensurate with their productivity This sim- le reasoning leads to a model such as where wage is hourly wage, educ is years of formal education, exper is years of workforce experience, and training is weeks spent in job training. Again, other factors generally affect he wage rate, but (1. 2) captures the essence of the problem After we specify an economic model, we need to turn it into what we call an econo- metric model. Since we will deal with econometric models throughout this text, it is important to know how an econometric model relates to an economic model. Take equa- tion(1. 1)as an example. The form of the function f( )must be specified before we car ndertake an econometric analysis. A second issue concerning(1. 1)is how to deal with variables that cannot reasonably be observed. For example, consider the wage that a person can earn in criminal activity. In principle, such a quantity is well-defined, but it yould be difficult if not impossible to observe this wage for a given individual. Even ariables such as the probability of being arrested cannot realistically be obtained for iven individual. but at least we can observe relevant arrest statistics and derive a var- able that approximates the probability of arrest. Many other factors affect criminal behavior that we cannot even list let alone observe but we must somehow account for them The ambiguities inherent in the economic model of crime are resolved by specify g a particular econometric model: crime=Bo+ B, wage B2othinc B3freqarr Bafreqcomv 13) Bsavgsen bage +l where crime is some measure of the frequency of criminal activity, wage is the wage at can be earned in legal employment, othinc is the income from other sources(assets inheritance, etc. freqarr is the frequency of arrests for prior infractions(to approxi- mate the probability of arrest), fregcomm is the frequency of conviction, and avgsen is the average sentence length after conviction. The choice of these variables is deter mined by th theory as well as data considerations. The term u contains unob-Here is an example of an equation that was derived through somewhat informal reasoning. EXAMPLE 1.2 (Job Training and Worker Productivity) Consider the problem posed at the beginning of Section 1.1. A labor economist would like to examine the effects of job training on worker productivity. In this case, there is little need for formal economic theory. Basic economic understanding is sufficient for realizing that factors such as education, experience, and training affect worker productivity. Also, econ￾omists are well aware that workers are paid commensurate with their productivity. This sim￾ple reasoning leads to a model such as wage
f(educ,exper,training) (1.2) where wage is hourly wage, educ is years of formal education, exper is years of workforce experience, and training is weeks spent in job training. Again, other factors generally affect the wage rate, but (1.2) captures the essence of the problem. After we specify an economic model, we need to turn it into what we call an econo￾metric model. Since we will deal with econometric models throughout this text, it is important to know how an econometric model relates to an economic model. Take equa￾tion (1.1) as an example. The form of the function f() must be specified before we can undertake an econometric analysis. A second issue concerning (1.1) is how to deal with variables that cannot reasonably be observed. For example, consider the wage that a person can earn in criminal activity. In principle, such a quantity is well-defined, but it would be difficult if not impossible to observe this wage for a given individual. Even variables such as the probability of being arrested cannot realistically be obtained for a given individual, but at least we can observe relevant arrest statistics and derive a vari￾able that approximates the probability of arrest. Many other factors affect criminal behavior that we cannot even list, let alone observe, but we must somehow account for them. The ambiguities inherent in the economic model of crime are resolved by specify￾ing a particular econometric model: crime
0 + 1wagem + 2othinc  3 freqarr  4 freqconv  5avgsen  6age  u, (1.3) where crime is some measure of the frequency of criminal activity, wagem is the wage that can be earned in legal employment, othinc is the income from other sources (assets, inheritance, etc.), freqarr is the frequency of arrests for prior infractions (to approxi￾mate the probability of arrest), freqconv is the frequency of conviction, and avgsen is the average sentence length after conviction. The choice of these variables is deter￾mined by the economic theory as well as data considerations. The term u contains unob￾Chapter 1 The Nature of Econometrics and Economic Data 4 14/99 4:34 PM Page 4