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Use the data in WAGE1 for this exercise.(i) Find the average education level in the sample. What are the lowest and highest years of education?(ii) Find the average hourly wage in the sample. Does it seem high or low?(iii) The wage data are reported in 1976 dollars. Using the Internet or a printed source, find theConsumer Price Index (CPI) for the years 1976 and 2013.(iv) Use the CPI values from part (iii) to find the average hourly wage in 2013 dollars. Now doesthe average hourly wage seem reasonable?(v) How many women are in the sample? How many men?

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Hi, Everyone Hope you're doing well. This is the first video solution for our introductory econometrics textbook by Jeffrey World Ridge. And today we begin by solving computer exercise C one. So since those are computer exercises, we need to use statistical software for Arlington's and purposes that will be using the software stada, since this is the most widely used off where in American universities and abroad. But of course, feel free to use your the software of your preference is your preference, such as our or mad love or he views or anything else? So the first thing we need to do for a question one is to, ah, download the older data sets from the official website, say engage brain dot com and then load the data set Wage one and stay there. All right, the first question asked. Find the average educational level education level in the sample one of the lowest and highest years of education. All right, before we begin, every time we have, we're dealing with a new data set. We must first find out what's going on, what kind of variables we have, what is a format and what is going on in our data set, so we will hit to describe my hidden described would have basic summary of our variables. So here we see that we have 526 operations. Since we're dealing with cross sectional data, this means that we have collected 526 observations at a specific point in time of different variables. And we have 24 variables. Uh, right here we can see our variables. This is a variable name. This is the storage time flowed and bite. We don't have to really worry about that right now, but the two things we need to keep in mind is the variable name and what it represents are here. For example, wage is the average hourly earnings, which is a continues variable, meaning that it can take any value inside the domain that's defined. Usually this is a close and about it said, but not necessarily the here. For example, Wage can take any value that is greater than zero, and it is mounted, of course, by certain valley. On the other hand, we have a discreet variables, such as the years of education or the years of potential experience, and those variables variables, of course, are discreet sins. They take values that correspond to natural numbers so it can have 012123 years of education. Someone. And finally, we can see that the variables that say equal one, if a certain conditions, those air binary or dummy variables, meaning that they take a value of one if a certain conditions satisfied and volume zero. Otherwise, for example, the dummy variable female is equaled one. If the online observation is female and zero otherwise of its mail here, we I guess the author's assumed that genders by name. So that's how it works. We can also see all those all these descriptions in the data browser you can see here that, for example, observation number one corresponds to wait 3.1 11 years of education, two years of experience. So right. Ah, back to a question. We need to find the average education level in the sample and the lowest and highest years of education. The men in the max. So the simplest way to do it is it safe? Summarize are very both injuries, which is at Duke. All right, so here we can see that the mean the averages 12.56. This is our answer for the average education level in the sample and the minimum zero. Is there someone who has never going to school? Zero years of education, someone with 18 years education eyes from this is a PC degree. All right. Another thing you can do is when you write summarize, followed by the very boy. You can write comma detail and get a more detailed descriptive analysis of the variable. So apart from the standard mean the and deviation brains, we can get the third and fourth moment of the distribution of skin missing. Trato sis. And you can get a breakdown of the values by person. Thous. So, for example, the 50th percentile would be the median in this case is relatively close. That mean is 12 means 12.56 went away. 12 points. 56 is ah is our answer in the mini and the maxi zero in 18 respectively. All right. Part two find the average hourly wage in the sample. Does it seem high or low? Average hourly wage. It's right here. The very was called Wage. So we're gonna do the same. Summarize wage and we see that the mean the average is $5.9 per hour. Does this seem higher? Low? Well, I think seems very low, given that um, the average national minimum wage in the US right now is 7.25 7.5 a thing. So this is extremely low. So there's something going on. I'm going to find out what? It isn't in part C. The wage data are reported in $1976. So we're actually looking at data from 1976. Using danger nor printed source, find the consumer price index a C p I for the years 90 76 2 1013 Alright. Already done it for you. I you can there many sources where you can find the official data is, um, reported by the U. S. Bureau of Labor Statistics. And to make it a little bit more interesting, I used the Fred database from the St Louis Fed. Ah, the data reported monthly frequency. So we go to edit graph and modify frequency from monthly annual. So let's find out what's, uh what does this say? The C b i in 1976? It is 56.93. All right. And in 2013 it is 2 32.95 All right, Done part. See? Use the C B. I values from part C to find the average hourly wage in $2013 now does the average way. Aren't we wait? Seem reasonable. Okay. What we need to do here, as we said we have, uh the number that we found is in 90 $76. So we have to do we have to adjust for inflation? How do we do that? We say we need to find the ever change the change in the CPI. I If we do that, we divide the number the CP level in 2013 by the superior. 11 19 7 nineteen six. And then we multiply with the average wage right here. Okay, So this part is the change in inflation. This is the average wage 1976. So this equation will give us the average wage in 2013 adjusted for inflation. Right. So, uh, what would the values we found? We said through the 6.8 to 3. All right, all right here because he's 6.93 divided by 2 32.5 All right, Very good. 0.5 wasn't 95. I forget. What's wrong with you? Times? The average wage, which was what? Uh, it was, as we said. Now it's education. 3.4 point 89 off course. If we had enter here, nothing will happen because we need to include the command. Displayed display is a command that makes whatever is after the man displaying performers to calculate. Right. They will perform this calculation for us. He had under and we get. Yeah, well, I wrote it the other way around. Okay. Sorry about that. Forces the other way around, right? It is like this it under and now the wage. The others wage in $2013. 24.10 dollars per hour. That's more than reasonable. You know, there's like, ah, a bit more than three times the U S. National average. So we seem to be the reasonable all right and finally part. Ah five says how many women are in the sample and how many men? Okay, as we saw before, the, um, the variable for women here is a binary variable dummy variable takes the value of zero and one. So if we want to find out how many women weaken, just count. How many? Once they're in this column right here, Right in a column of women. How many ones there are? Of course we're going to is manually. There is. Ah, command for that is gonna count. If so, we're account if and here's our condition, which is female equals to one. And be careful here. The equal operator is written with two equal signs. Otherwise, with wonderful sign. That would be Well, let's do it. But you can see what happens. It was with wonderful sign expression not allowed because this is logical. Appear either have the actual equal sign when you two equal signs counted. Right? So we have 252 females in this data set Now, what about men? That will be the compliment of that, right? It will be the number of observation minus the this number. But we can make it. We can do it faster. So we write the same command counted female. It was zero is a binary variable. Oh, okay. I didn't say See that way? Around of course, we learn from our mistakes to equal sign, and we see the They're 274 men in the sample just to make sure that we have the right we haven't made in mystique. Let's check if, uh 2 52 plus 2 74 to 74 1 Yeah, it's 5 26 and indeed, this is the number right here. You can see a number of our variable observations 526 and that's it.

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