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Additionally, because race is a categorical variable that has three potential values—1 if white, 2 if black, and 3 otherwise—we have to create a dummy variable in order to use this variable. The transformations we use are shown in Figure 3.

Stata commands to transform the data.
Transformations of the variables to create new variables.

The last step before estimating the regressions is to identify the data set as a panel data. shows the two commands that must be entered in order for Stata to know that idcode is the individual category and that year is the time series variable. Figure 4 shows these two commands.

Declaring the category and time identifiers.
Declaring the category and time identifiers.

We are now ready to estimate the model (the natural logarithm of wages as a function of various variables). We begin with the random-effects model. Figure 5 shows the command and the results of the estimation of the random-effects model. There are several things to note here. First, in the command we are able to refer to all variables that have age in them by using age* , the * tells Stata to use and variable that begins with the letters age. Second, we will need to use the estimation results in the Hausman test. Thus, we have stored these results in “random_effects” using the command estimates store random_effects .

Stata output from the random-effects estimation.
The random-effects estimation.

Notice that three R-squared values are reported in Figure 5. Also, wages reach a peak when the woman is 0.036806 2 ( 0.0007133 ) = 25.7998 MathType@MTEF@5@5@+=feaagyart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaeyOeI0YaaSaaaeaacaaIWaGaaiOlaiaaicdacaaIZaGaaGOnaiaaiIdacaaIWaGaaGOnaaqaaiaaikdadaqadaqaaiabgkHiTiaaicdacaGGUaGaaGimaiaaicdacaaIWaGaaG4naiaaigdacaaIZaGaaG4maaGaayjkaiaawMcaaaaacqGH9aqpcaaIYaGaaGynaiaac6cacaaI3aGaaGyoaiaaiMdacaaI4aaaaa@4CCE@ years old and after 9.795857 years on the job. The interpretation of the other variables demands a bit of algebra. For instance, the fact that black is a dummy variable affects our interpretation; when an individual is a black, her wage level is: ln w B = β 0 + β 1 + . MathType@MTEF@5@5@+=feaagyart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaciiBaiaac6gacaWG3bWaaSbaaSqaaiaadkeaaeqaaOGaeyypa0JaeqOSdi2aaSbaaSqaaiaaicdaaeqaaOGaey4kaSIaeqOSdi2aaSbaaSqaaiaaigdaaeqaaOGaey4kaSIaeS47IWKaaiOlaaaa@445D@ When she is nonblack, her wage level is ln w N B = β 0 + . MathType@MTEF@5@5@+=feaagyart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaciiBaiaac6gacaWG3bWaaSbaaSqaaiaad6eacaWGcbaabeaakiabg2da9iabek7aInaaBaaaleaacaaIWaaabeaakiabgUcaRiabl+Uimjaac6caaaa@41BC@ Thus, we have: ln w B ln w N B = β 1 MathType@MTEF@5@5@+=feaagyart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaciiBaiaac6gacaWG3bWaaSbaaSqaaiaadkeaaeqaaOGaeyOeI0IaciiBaiaac6gacaWG3bWaaSbaaSqaaiaad6eacaWGcbaabeaakiabg2da9iabek7aInaaBaaaleaacaaIXaaabeaaaaa@42FB@ or w B w N B = e β 1 = e 0.0530532 = 0.94833. MathType@MTEF@5@5@+=feaagyart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaSaaaeaacaWG3bWaaSbaaSqaaiaadkeaaeqaaaGcbaGaam4DamaaBaaaleaacaWGobGaamOqaaqabaaaaOGaeyypa0JaamyzamaaCaaaleqabaGaeqOSdi2aaSbaaWqaaiaaigdaaeqaaaaakiabg2da9iaadwgadaahaaWcbeqaaiabgkHiTiaaicdacaGGUaGaaGimaiaaiwdacaaIZaGaaGimaiaaiwdacaaIZaGaaGOmaaaakiabg2da9iaaicdacaGGUaGaaGyoaiaaisdacaaI4aGaaG4maiaaiodacaGGUaaaaa@5001@ Thus, the wage level of a black is, everything else held constant, 94.8 percent of the wage level of a nonblack.

If we assume that grade is a continuous variable (it really is not), we have the following interpretation of the parameter: ln w = β 0 + β 1 g r a d e + MathType@MTEF@5@5@+=feaagyart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaciiBaiaac6gacaWG3bGaeyypa0JaeqOSdi2aaSbaaSqaaiaaicdaaeqaaOGaey4kaSIaeqOSdi2aaSbaaSqaaiaaigdaaeqaaOGaam4zaiaadkhacaWGHbGaamizaiaadwgacqGHRaWkcqWIVlctaaa@474A@ implies that 1 w w g r a d e = β 1 MathType@MTEF@5@5@+=feaagyart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLnhiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=xfr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaSaaaeaacaaIXaaabaGaam4DaaaadaWcaaqaaiabgkGi2kaadEhaaeaacqGHciITcaWGNbGaamOCaiaadggacaWGKbGaamyzaaaacqGH9aqpcqaHYoGydaWgaaWcbaGaaGymaaqabaaaaa@43BC@ . Thus, in our case a increase of 1 year of schooling causes wages to increase by 6.46 percent.

We can compare the results of using the re option with using the mle option (which directs Stata to use maximum likelihood techniques to estimate the parameters of the system. The mle parameter estimates, shown in Figure 6, are the same as those generated using the re command. However, the estimates of the standard errors (and, thus, the z-values) are different.

Stata output from the maximum likelihood estimation.
The maximum likelihood estimation.

The estimation of the fixed-effects model is straightforward and is shown in Figure 7. The command is the same as in the random-effects model but with the re replaced by fe . Notice from the results that the variables grade and black are dropped from the estimation results. They are dropped because the amount of schooling and race of an individual is fixed over all observations. These two variables, thus, are perfectly correlated with the dummy variables that hold constant the individual level characteristics. The effects of education and race differences are absorbed into the residual.

Questions & Answers

what are the products of Nano chemistry?
Maira Reply
There are lots of products of nano chemistry... Like nano coatings.....carbon fiber.. And lots of others..
Even nanotechnology is pretty much all about chemistry... Its the chemistry on quantum or atomic level
Preparation and Applications of Nanomaterial for Drug Delivery
Hafiz Reply
Application of nanotechnology in medicine
what is variations in raman spectra for nanomaterials
Jyoti Reply
I only see partial conversation and what's the question here!
Crow Reply
what about nanotechnology for water purification
RAW Reply
please someone correct me if I'm wrong but I think one can use nanoparticles, specially silver nanoparticles for water treatment.
yes that's correct
I think
what is the stm
Brian Reply
is there industrial application of fullrenes. What is the method to prepare fullrene on large scale.?
industrial application...? mmm I think on the medical side as drug carrier, but you should go deeper on your research, I may be wrong
How we are making nano material?
what is a peer
What is meant by 'nano scale'?
What is STMs full form?
scanning tunneling microscope
how nano science is used for hydrophobicity
Do u think that Graphene and Fullrene fiber can be used to make Air Plane body structure the lightest and strongest. Rafiq
what is differents between GO and RGO?
what is simplest way to understand the applications of nano robots used to detect the cancer affected cell of human body.? How this robot is carried to required site of body cell.? what will be the carrier material and how can be detected that correct delivery of drug is done Rafiq
analytical skills graphene is prepared to kill any type viruses .
Any one who tell me about Preparation and application of Nanomaterial for drug Delivery
what is Nano technology ?
Bob Reply
write examples of Nano molecule?
The nanotechnology is as new science, to scale nanometric
nanotechnology is the study, desing, synthesis, manipulation and application of materials and functional systems through control of matter at nanoscale
Is there any normative that regulates the use of silver nanoparticles?
Damian Reply
what king of growth are you checking .?
What fields keep nano created devices from performing or assimulating ? Magnetic fields ? Are do they assimilate ?
Stoney Reply
why we need to study biomolecules, molecular biology in nanotechnology?
Adin Reply
yes I'm doing my masters in nanotechnology, we are being studying all these domains as well..
what school?
biomolecules are e building blocks of every organics and inorganic materials.
anyone know any internet site where one can find nanotechnology papers?
Damian Reply
sciencedirect big data base
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Source:  OpenStax, Econometrics for honors students. OpenStax CNX. Jul 20, 2010 Download for free at http://cnx.org/content/col11208/1.2
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