Important codes

Question 1

Do file

Answer 1

This is where we type all of our codes
Allows you to save codes

Question 2

How to set up a sheet

Answer 2

1. Clear all (*removes all previous codes we had done before *)
2. Right click the file and then click on properties and then copy location (Tell stata where we are saving the file)
3. Cd “(location)”
4. Use auto.data, clear (open the data set and clear means if there is already data opened on stat clear it and use the data that we have just opened)

Question 3

Answer 3

Run all code in the do file editor
If you want specific codes then highlight the code and press the button
If there is no red once you run the code, then it’s fine

Question 4

Browse

Answer 4

Opens spreadsheet so we can see all of our data
Browse (variable) in order to see specific variables
Use br to view many variables

Question 5

Code: Describe

Answer 5

Shows our data set
Understand variables
Int- integer

Question 6

Code: List

Answer 6

Shows us all of our observations one at a time
Negative: Gives us too much information

Question 7

Code: list (** VARIABLES**)

Answer 7

Only shows observation for specific variables

Question 8

Code: list (VARIABLES) in 1/(NUMBER OF OBSERVATIONS YOU WANT TO BE INCLUDED)

Answer 8

Restricts to certain observations

EXAMPLES
- 1/l: List on everything
- 70/l: List starts from the 70th observation to the last
(Lowercase L denotes the final observation)

Question 9

Code: list (variables) if (outcome of interest)==1

Answer 9

If command, therefore only includes observations that comply with the outcome of interest
Needs 2 equal signs!!

Question 10

List code with multiple conditions

Answer 10

!= (value): Not equal to
&: means and
|: means or
==0: Not equal to
List (Anything e.g. a letter)*: Lists any variable that starts with the letter or follows the conditions

Question 11

Code: Count

Answer 11

Counts the number of observations satisfying the condition

Question 12

Code: Summarise or sum

Answer 12

Descriptive statistics of variables
Able to add if commands
,detail: More detailed breakdown (e.g. median, Skewness)
(On the example there is 1 less rep78 observation as one of the observations has nothing)

Question 13

Code: tabulate/tab (Variable of interest)

Answer 13

• Breaks down each discrete variable into what values they take and the frequency, percentage and cumulative percentage
• Apply to apply if
• Used for 2 variables which shows a cross tab (first variable is on the rows sand the second it the rows)

Question 14

Code: gen (title of the new variable) = function

Answer 14

• Makes a new variable
• 1 equal sign: assigning the variable to be equal to a certain function
• 2 equal signs: Equality already holds, checking if it holds
• If you want a space (put _)
• Able to multiply variables by putting * between them (called an interaction)
• Running code again doesn’t lead to 2 duplicated variables as in the beginning we clear all

Question 15

Code: Replace (variable name) = (function in which the variable changes)

Answer 15

• If you make a mistake, run a clear all and then do the variable again

Question 16

How to remove blank values when generating a new variable?
(1: Less than or equal to 2 or 0 if rep 78 is greater than 3)

Answer 16

• Use replace and mention the Newley generated function and then the original function (using 2 equal signs for this one)
• Or you could add if (variable we want to code) !=.

Question 17

CODE: Corr (variables )

Answer 17

• Tells us the correlation
• Adding “, cov” at the end tells us the covariance

Question 18

How to save the new version of data

Answer 18

1. Save (name of the file), replace
   - replace means that we are replacing the previous data
   - Never write the name auto as we do not want to overwrite the original data so give it a new data
2. Under cd write: capture log close
   - If we are currently creating a log file close it and if there is not a log file, ignore that
3. Log using (log name).log, replace text
   -Creating a log file in log form in which we can read. If a file is already with the same name we replace the text
4. Log close (At the bottom)

Question 19

Running a t -test in which we test if a variable is equal to a certain value

Answer 19

ttest (variable we are testing) ==0
- Provided with standard deviation (measure of spread of all values)
- Provided with standard error (measure of precision of the average across samples)
- Provided with t value (hypothesised mean minus observed mean divided by standard error)
- Provides confidence interval
- Ha: mean !=0: Two sided alternative, this then shows the probability of getting the test statistic or one more extreme. If it’s less than 0.05 than we reject the null hypothesis.
- Ha: mean < 0 is a one sided test assuming that the mean is positive

Question 20

T-test for a difference in mean

Answer 20

Ttest (variable we are testing), by (variable we are separating to find the difference between groups. E.g. Binary variable)

Ttest for willingness to spend based of whether someone is employed or not

Question 21

Code: Reg (outcome variable, independent variables)

Answer 21

Constant is worked out through: Average value of outcome minus (coefficient estimate for the independent variable * average value of the independent variable )

Question 22

Code: Predict (name of the new variable E.g. y_hat)

Answer 22

• Needs to be run after a reg command
• predict residual, resid: Needs to be underneath a reg command

Question 23

Show properties of regressors

Answer 23

Question 24

Code: twoway
Creating a graph

Answer 24

• scatter (outcome variable regressor): Scatter graph
• lift (outcome variable regressor): Regression line
• graphregion(color(white)): Change background colour to white (needs to be after a comma)

Question 25

Difference between 1 equal sign and 2 equal signs?

Answer 25

=: Assign this value to be equal ==: If equality already holds

Question 26

Omitted variable bias

Answer 26

Auxiliary regression: Reg (omitted variable) (regressor of interest) If you then type local coef = _b[variable]/ it will save the value of the coefficient for the variable, then you have to run your code all together

Question 27

Saving in a document file Code: outreg

Answer 27

Use reg to tell stata that we are creating a new document, therefore we type replace (Not typing replace adds on a new column, typically done when adding a new control) Document tells us if something is significant through asterisk (*) sdec (4): standard errors with 4 decimal places Bdec (4): Beta to have 4 decimal places

Question 28

Hypothesis test for coefficent

Answer 28

Question 29

Code: Lincom

Answer 29

Write that the variable associated with the coefficient

Question 30

Code: test

Answer 30

Test in which the null hypothesis is requires multiple equal signs and there is the use of the word and First need to run the regression to show stata which regression we are talking about Want to tester multiple hypothesis at the same time. Can use F-test for single hypothesis as-well but just a single bracket with the equal sign and what the hypothesised value is

Question 31

Standardising

Answer 31

Egen is standardising R(sd) refers to the standard deviation from the previous sum command. When running a reg and interpreting the coefficient, mention that the specific variable increasing by 1 standard deviation is equal to the outcome variable increasing by the coefficient holding fixed other variables. We can also standardise the outcome. Makes it easier to understand

Question 32

What is normalising?

Answer 32

Transforming the variable to make it easier to read

Question 33

Code: Egen

Answer 33

Creates a variable that is the average value If instead of mean there was an sd, then it would be the standard deviation of them

Question 34

Code: Insheet

Answer 34

Insheet using name of data.csv, clear - Open a new dataset - Excel format therefore we need a cvs name

Question 35

Code: Split VARIABLE

Answer 35

Creating separate variables for the day month and year: Rename: Change the name of a variable rename (original variable name) (new variable name) - replace VARIABLE = regexr (variable, “what we want to take out”, “what we want to put in”)

Question 36

Code: Destring variable, replace

Answer 36

Command tells stata that a certain variable is actually a number Used with split command

Question 37

When we browse, why are certain variables in red?

Answer 37

Stata thinks that this variable is just words and not numbers (E.g. Months )

Question 38

Changing months in numerical values

Answer 38

Add destring code at the end

Question 39

Code: Inrange

Answer 39

, if I range (variable, starting point number, ending point number) Includes the first and last number

Question 40

Code: Inlist

Answer 40

For words

Question 41

What should your add at the end of any regression code?

Answer 41

,Robust to show the use of robust standard errors

Question 42

Binary variables i.

Answer 42

I. Create a dummy variable for each possible outcome

Question 43

Code: xi

Answer 43

Stat also creates variables which you can browse

Question 44

Functional form

Answer 44

Question 45

Finding observation of percentiles

Answer 45

Question 46

Scalar name of constant =_b[coefficient name]

Answer 46

- Display needs to be after the reg command but not scalar

Question 47

Egen panel_id= group (variable variable)

Answer 47

Gives each possible combination of each variable a specific ID code

Question 48

Xtset panelidvariable timeidvariable

Answer 48

Informs stata that we have panel data

Question 49

Diff-in-diff Binary variable for treated

Answer 49

Gen variablename = Inlist (variable we are focusing on, values that we want our binary variable to equal 1 for)

Question 50

Diff and Diff Binary variable for being after treated

Answer 50

Binary variable that is either 1 or 0 depending on if it’s after or before treatment

Question 51

Diff and Diff regression:

Answer 51

Reg outcomevariable treated after interaction, robust, if variable == “specific value/word that is the treated group”

Question 52

Diff and Diff Generating the interaction term

Answer 52

Multiplying treated and control Gen interaction = treated*after

Question 53

Diff and Diff Graph for the trends before treatment

Answer 53

Two way (lift outcome binary variable(for time) if treated ==1 & after == 0 & cname == “Treated group”) (lift outcome binary variable(for time) if treated ==0 & after == 0 & cname == “Treated group”) Trend in outcome for the treated group prior to treatment as well as the trend in prices for the control group

Question 54

Checking for parallel trends

Answer 54

Question 55

Fixed effect estimators

Answer 55

Question 56

Time fixed effect

Answer 56

Question 57

Creating fake data

Answer 57

Gen fake_regressor = rnormal () Distributed with mean 0 and standard deviation of 1

Question 58

Time fixed effects

Answer 58

Sort panel_id timevariable

Question 59

First difference regression

Answer 59

Question 60

Regression discontinuity

Answer 60

Image

Question 61

2SLS

Answer 61

Ivregress 2SLS price (treatment that might have bias = instruments) control variables, robust if product == “treated group”

Question 62

Panel Data Regression

Answer 62