Rotse Instruction Manual How To User Variable Star

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If you have data in this format:

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Company______Accounts______2013______2014____2015
Petronas Total Assets 1500 1700 2000
Petronas EBIT 750 850 1000
An, you need to transpose the data to make it look like this:
Company________Year____Total Assets__________EBIT
Petronas 2013 1500 750
Petronas 2014 1700 850
Petronas 2015 2000 1000
Do the following:
1. In Excel, insert letter 'y' in front of each year, for example:
Company____Accounts________y2013____y2014____y2015
Petronas Total Assets 1500 1700 2000
Petronas EBIT 750 850 1000
2. Import the data into Stata,
3. Create unique IDs for Accounts and Companies:
sort Accounts
egen ida=group(Accounts)
sort Company
egen idc=group(Company)


4. Transpose data into long format:
reshape long y, i(idc ida) j(year)


5. Delete a column with Accounts, but keep ida (ID for Accounts):
drop Accounts


6. Transpose the data into wide format:
reshape wide y, i(idc year) j(ida)


7. Now, you can rename Accounts IDs (ida) as 'TotalAssets' and 'EBIT':
rename 1 'TotalAssets'
rename 2 'EBIT'
8. To locate the column 'idc' just before 'Company' column:
move Company idc


****************
Practice:

*0. Import the data:
use https://dl.dropboxusercontent.com/u/18255955/PhD-INCEIF/Panel%20Data_Tutorial.dta, clear

*1. Create unique identifiers for countries:
sort Country
egen idc=group(Country)

*2. Convert data into panel format
reshape long y, i(idc Variable) j(Year)
reshape wide y, i(idc Year) j(Variable) string

*3. Rename variables:
rename (yGDP yIF ySP) (GDP IF SP)

*4. Add labels:
label variable Year 'Period'
label variable GDP 'Gross Domestic Product'
label variable IF 'Inflation Rate'
label variable SP 'Stock Market'



Here is the video with instructions:



A. For example, your panel data has observations for years 2010 2013 2014 2015, but there are missing years (2011 and 2012). Use the following commands to fill the gaps:

xtset idc year
tsfill
B. If you want to make your panel data balanced (equal number of years for all panels), then use these commands:
xtset idc year
tsfill, full
See details here: LINK

The next commands fill the missing values in your data by averaging previous and next values, if those numbers are available. If not, then it takes the nearest available value.
1. Install nnipolate package:
ssc install nnipolate, replace

2. Define panel data:

Rotse Instruction Manual How To User Variable Star In 1

3. Fill in missing values:


The market concentration (HHI) is calculated by squaring the market share of each bank/firm competing in a market, and then summing the resulting numbers.
First, before we calculate HHI using Stata, install the package:
ssc install hhi, replace
Then, run the code. Example:
hhi Market_Value, by (Year Country)

Done!

Let's assume that you have the following list of variables: ROA, ASQ, LIQ, CAP, EFF.
Type and run the following code in the Stata command area (each line separately):
1. To transform all your variables into log form:

foreach var of varlist ROA ASQ LIQ CAP EFF {
gen log_`var' = log( `var' )
}

2. To transform all your variables into log form with zero skewness (normal distribution):

foreach var of varlist ROA ASQ LIQ CAP EFF {
lnskew0 L`var' = `var'
}

3. To transform all your variables using Box-Cox procedure for zero skewness (normal distribution):

foreach var of varlist ROA ASQ LIQ CAP EFF {
bcskew0 BC`var' = `var'

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}

NOTE: BE CAREFUL WITH THE TYPE OF APOSTROPHE IN THE SECOND LINE!

• ` is different from '
• The first one is located on the left of number 1 on your keyboard, another one is besides Enter.

• Option 1: Using PWCORR:

pwcorr YOUR_LIST_OF_VARIABLES, star(0.05)

• Option 2: Using ESTOUT package (to install: ssc install estout, replace ):

estpost correlate LIST_OF_YOUR_VARIABLES, matrix listwise
esttab, unstack not noobs compress

Hello,

I have been analyzing a candidate EA variable star and have had some trouble in determining its period. I have identified the star from ROTSE 3 light curves and classified it as an EA variable using data obtained from NSVS and SuperWASP. Previously, I have had trouble in fitting ROTSE 3 data with NSVS and SuperWASP, but I no longer think I have that issue.

My question is this: how do I go about determining the period of the EA star within precision limits of what VSX requires of its submissions? I am using an excel spreadsheet form of Eplot, which requires that I input a period into the spreadsheet to generate a phase plot. To even obtain this period, I had to 'hand scan' light curves available in the SuperWASP archive to determine the time between two consecutive, identical points on the available light curve. My initial estimate was about 2.12-2.13 days, which I refined to 2.126-2.127 days, as this period produces, in my opinion, the clearest pattern for the phase plot (which is attached to this post). Is there a more objective way of determining the star's period? Perhaps some software I can use to accommodate the large amount of data (well over 10000 observations)? I had used IDL when I was just phasing NSVS and ROTSE 3 data individually, but SuperWASP accounts for the the majority of all observations, so I had to use Eplot to handle the amount of information.

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Also, for submitting my phase plot to VSX, do I eliminate outlier observations before submitting? And is there an objective way to determine what counts as an outlier?

Mean well 480-48 user manual 2017. Thanks for your help,

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Alexander Wallace