Reshape wide with multiple j strings

[Natasha Drud Bendsen]

Hi,

How can I reshape my variables with multiple j strings? I have tried something like this:

reshape wide var1 var2 gap boundL boundH, i(variable eventtime) j(gender sector, string)

where I want to get the following system of variables out for "gap":

gapmenprivate
gapwomenprivate
gapmenpublic
gapwomenpublic

(Here gender is either "men" or "women" and sector is either "private" or "public".

Thanks in advance.

[Nick Cox]

We (or at least I) need a data example please.

[Natasha Drud Bendsen]

My data looks like this (an example)

Gap	variable	gender	sector
324.94	wage	men	private
350.84	wage	men	public
430.23	wage	women	private
433.43	wage	women	public
9532.48	income	men	private
4830.43	income	men	public
4820.43	income	women	private
4830.43	income	women	public
...	...	...	...

Many thanks.

[Natasha Drud Bendsen]

The thing is, that I want to uniquely identify my observations with gender and sector (per variable). I thought I could call them

gapmenprivate
gapwomenprivate
gapmenpublic
gapwomenpublic

for each variable: wage and income.

Hope it makes sence.

[Nick Cox]

#2 doesn't seem to match the syntax in #1. but it is what you give us.

#2 is helpful, but not a data example as we request here (FAQ Advice #12). Whether you have string variables or numeric variables with value labels is ambigous, in particular.

I don't understand quite what you're imagining, but this is what I would do

* Example generated by -dataex-. For more info, type help dataex
clear
input float gap str6 variable str5 gender str7 sector
 324.94 "wage"   "men"   "private"
 350.84 "wage"   "men"   "public"
 430.23 "wage"   "women" "private"
 433.43 "wage"   "women" "public"
9532.48 "income" "men"   "private"
4830.43 "income" "men"   "public"
4820.43 "income" "women" "private"
4830.43 "income" "women" "public"
end

. reshape wide gap, i(gender sector) j(variable) string
(j = income wage)

Data                               Long   ->   Wide
-----------------------------------------------------------------------------
Number of observations                8   ->   4          
Number of variables                   4   ->   4          
j variable (2 values)          variable   ->   (dropped)
xij variables:
                                    gap   ->   gapincome gapwage
-----------------------------------------------------------------------------

. rename (gap*) (*gap)

. l

     +---------------------------------------+
     | gender    sector   income~p   wagegap |
     |---------------------------------------|
  1. |    men   private    9532.48    324.94 |
  2. |    men    public    4830.43    350.84 |
  3. |  women   private    4820.43    430.23 |
  4. |  women    public    4830.43    433.43 |
     +---------------------------------------+