local Nobs = r(N)

local numitems = wordcount("$col_vars $row_vars")									// count variables

	matrix C = J(`numitems',`numitems',.)											// empty matrix where are going to be saved significance stars

	*Now begin to count how many stars are required by p-values
	/*	p-value <= 0.05 => 1 star
		p-value <= 0.01 => 2 stars
		p-value <= 0.001 => 3 stars
	*/
	forvalues m	= 1(1)`numitems'{													// m row index
		forvalues n = 1(1)`numitems'{												// n column index
			mat C [`m',`n'] = 0
			
			if B[`m',`n']<=0.05 {	
				mat C [`m',`n'] = 1
				}
			
			if B[`m',`n']<=0.01 {	
				mat C [`m',`n'] = 2
				}
				
			if B[`m',`n']<=0.001 {	
				mat C [`m',`n'] = 3
				}
		}
	}

	matrix D = J(`numitems',`numitems',.)												// D matrix round coef. correlation values
	forvalues m	= 1(1)`numitems'{														// m row index
		forvalues n = 1(1)`numitems'{													// n column index
			mat D [`m',`n'] = round(A [`m',`n'],0.001)
		}
	}

	svmat C																				// turn C matrix in variables in dataset
	svmat D																				// turn D matrix in variables in dataset

	forvalues i = 1(1)`numitems'{											// create a Z matrix as variables converting D matrix in strings
		gen Z`i'=""
	}

	forvalues i = 1(1)`numitems'{
		replace Z`i'=string(D`i',"%9.3f")
	}

	forvalues i = 1(1)`numitems'{											// create a X matrix with stars strings by how many stars are required
		gen X`i'=""
	}

	forvalues i = 1(1)`numitems'{
		replace X`i'="" if C`i'==0
		replace X`i'="*" if C`i'==1
		replace X`i'="**" if C`i'==2
		replace X`i'="***" if C`i'==3
	}

	forvalues i = 1(1)`numitems'{											// S matrix concatenate Z (coef.) and X (stars) string matrices
		egen S`i'=concat(Z`i' X`i')
	}

	keep S*																	// Keep S matrix in dataset, it will be exported in Excel
	drop if S1=="."															// Drop unnecesary observations
	gen Variable = ""														// First column with variables names of exported matrix
	order Variable, first													// Order this column at the begining of matrix


	local aux1 = `numitems'+1												// this index the last row of result matrix

	expand 2 in 1															// generate a new row with random values (are stored as observations)

	forvalues j=1(1)`numitems'{
		replace S`j'="" in `aux1'											// replace last row with an empty string
	}

	local aux2 = `numitems'+2												 

	expand 2 in 1

	forvalues j=1(1)`numitems'{
		replace S`j'="" in `aux2'											// make the same in a new row
	}

	replace Variable = "Prueba: $typetest" in `aux1'						// add a legend with matrix title at bottom of the matrix
	replace Variable = "Legend: * p<0.05, ** p<0.01, *** p<0.001" in `aux2'	// add legend of stars significance at bottom of the matrix



	local j = 1
	foreach i in $row_vars $col_vars {										// now assing variables names at first column
		replace Variable = "`i'" in `j'
		local j = `j'+1
	}

	local j = 1
	foreach i in $row_vars $col_vars {										// now assing variables names at first row
		rename S`j' `i'	
		local j = `j'+1
	}

	gen Obs = .																// where is shown number of observations of sample
	replace Obs = `Nobs' in 1

	
	*Now drop uninterested data and keep only submatrix placed at the up-right of the whole correlation matrix 
	drop $row_vars															// drop correlations between subsales of the same test ('asq' & 'asq')

	foreach aux in $col_vars {
		drop if Variable=="`aux'" 											// drop correlations between subsales of the same test ('bay' & 'bay')
	}