/* -------------------------------------------------------------------------------------- */
/* -------------------------------------------------------------------------------------- */
/* -------------------------------------------------------------------------------------- */
/* 
   This program file contains RATS programs for "Unemployment Insurance Claims and Economic            Activity" by William T. Gavin and Kevin L. Kliesen in the May/June 2002  issue of the        Federal Reserve Bank of St. Louis Review.

   Data used by the programs is found in the accompanying data file.                                                                                                                  */
/* -------------------------------------------------------------------------------------- */
/* -------------------------------------------------------------------------------------- */
/* -------------------------------------------------------------------------------------- */

********************************************************************************************
********************************************************************************************
* Table2.prg
* This program generated table 2
********************************************************************************************
********************************************************************************************

cal 1955 1 4
all 0 2002:3


*------------------------------------------------------------------------
* Data input and transformation
*-----------------------------------------------------------------------------

open data tab2.rat

data(format=rats) /             $
LR1 LANAGRA1 LIPRIVA1 LICM1 LIUM1 $
LR2 LANAGRA2 LIPRIVA2 LICM2 LIUM2 $
LR3 LANAGRA3 LIPRIVA3 LICM3 LIUM3 $
GDPQ
close data
* Note that lium is the growth rate of the number of insured unemployed
* lr is the unemployment rate
*note that we have loaded 16 series
*See "quart vars.xls" to see how series 1-15 are constructed
*GDPQ is GDP quantity index

set dy / = log(GDPQ/GDPQ(t-1))*400

*------------------------------------------------------------------------------
* Estimate forecasting models
*------------------------------------------------------------------------------
*******************************************************************
/*
This program estimates out of sample forecasts using current quarter
monthly labor market information.
*/
********************************************************************

decl vector[series] forcasts(16)

dofor x  = 1 to 15

	do i = 1,87

  	 smpl 1967:1 1979:2+i
   	 linreg(noprint) dy /
         # constant x dy{1 to 4}

   prj x+17 1979:3+i  1979:3+i
   end do i
end do x


dofor x = 1 to 15

    smpl 1967:1 2001:2
    linreg dy /
    # constant x dy{1 to 4}

  prj x+17 2001:3 2001:3

end do x

**********************************
* AR Forecasts
*********************************

do i = 1,87

  	 smpl 1967:1 1979:2+i
   	 linreg(noprint) dy /
         # constant  dy{1 to 4}

   prj 33 1979:3+i  1979:3+i
 end do i

    smpl 1967:1 2001:2
    linreg dy /
    # constant dy{1 to 4}

  prj 33 2001:3 2001:3
smpl 1979:4 2001:3
decl vector[series] sqerrors(16)  cperrors(15)

***************************************************
* creates series of squared errors numbered 34 to 49
***************************************************

dofor x = 18 to 33
  set  [series]x+16 = (dy-[series]x)**2
end do x
***************************************************
* creates series of error cross products numbered 50 to 64
***************************************************

dofor x = 18 to 32
  set  [series]x+32 = (dy-[series]x)*(dy-[series]33)
end do x

************************
*     store data       *
************************

smpl 1979:4 2001:3

open copy table2forecasts.XLS
copy(org=obs,format=xls,dates) / [series] 18 to 33
close copy
open copy table2squarederrors.XLS
copy(org=obs,format=xls,dates) / [series] 34 to 49
close copy

open copy table2xproducts.XLS
copy(org=obs,format=xls,dates) / [series] 50 to 64
close copy


********************
*   Compute error squared
********************

  Make sematrix 1990:1 2001:3
  # 34 to 49
  Make cpemat 1990:1 2001:3
  # 50 to 64
decl vector mse(16)
decl vector mcpe(15)

dofor x = 1 to 16

  compute mse(x) = %sum(%xcol(sematrix,x)) / %rows(sematrix)

end do x

compute rmse = %sqrt(mse)

write rmse

dofor x = 1 to 15

  compute mcpe(x) = %sum(%xcol(cpemat,x)) / %rows(cpemat)

end do x
write mcpe
write mse

compute [vect] armse = ||mse(16),mse(16),mse(16),mse(16),mse(16),$
mse(16),mse(16),mse(16),mse(16),mse(16),$
mse(16),mse(16),mse(16),mse(16),mse(16) ||



compute labormse = %xsubmat(mse,1,15,1,1)
 write labormse



compute p = %rows(sematrix)
write p

********************************************************************************************
********************************************************************************************
* Table3.prg
* This program generated table 3
********************************************************************************************
********************************************************************************************

Cal 1966 1 12
all 2002:11

open data tab3.rat

data(format=rats) / LIC1 LIC2 LIC3 LIC4 LIC5 LIU1 LIU2 LIU3 LIU4 LIU5 LICM LIUM LANAGRA LIPRIVA LTU LF

close data
*    table
**16 SERIES LOADED INTO PROGRAM

*Transform independent variables into monthly growth rates
set dlic1 / = (log(lic1) - log(licm{1})) * 100
set dlic2 / = (log(lic2) - log(licm{1})) * 100
set dlic3 / = (log(lic3) - log(licm{1})) * 100
set dlic4 / = (log(lic4) - log(licm{1})) * 100
set dlic5 / = (log(lic5) - log(licm{1})) * 100
set dliu1 / = (log(liu1) - log(lium{1})) * 100
set dliu2 / = (log(liu2) - log(lium{1})) * 100
set dliu3 / = (log(liu3) - log(lium{1})) * 100
set dliu4 / = (log(liu4) - log(lium{1})) * 100
set dliu5 / = (log(liu5) - log(lium{1})) * 100
**INDEPENDENT VARS USED IN REGRESSIONS ARE SERIES 17-26

*Transform Labor Market vars to monthly growth rates
set dlanagra / = (log(lanagra) - log(lanagra{1})) * 100
set dlipriva / = (log(lipriva) - log(lipriva{1})) * 100
set UR / = (ltu/lf) * 100
**DEPENDENT VARS USED IN REGRESSIONS ARE SERIES 27,28,29

decl rect[real] Table3(11,9)

*************************************************
**** UNEMPLOYMENT RATE REGRESSIONS   ************
*************************************************

	smpl 1968:02 2001:11
	linreg(noprint) ur
	# constant  ur{1 to 12}

        compute table3(1,1) = 0
	compute Table3(1,2) = 0
	compute Table3(1,3) = %seesq**.5

Dofor x = 17 to 26

	linreg(noprint) ur
	# constant x ur{1 to 12}

        compute table3(x-15,1) = %beta(2)
	compute Table3(x-15,2) = %tstats(2)
	compute Table3(x-15,3) = %seesq**.5

end dofor x
*************************************************
**** payroll jobs -- LANAGRA REGRESSIONS   **********************
*************************************************

	smpl 1968:02 2001:11
	linreg(noprint) dlanagra
	# constant  dlanagra{1 to 12}

        compute table3(1,4) = 0
	compute Table3(1,5) = 0
	compute Table3(1,6) = %seesq**.5

Dofor x = 17 to 26

	linreg(noprint) dlanagra
	# constant x dlanagra{1 to 12}

        compute table3(x-15,4) = %beta(2)
	compute Table3(x-15,5) = %tstats(2)
	compute Table3(x-15,6) = %seesq**.5

end dofor x


*************************************************
**** hours worked --  LIPRIVA REGRESSIONS   **********************
*************************************************
* decl rect[real] Table3(11,9)

	smpl 1968:02 2001:11
	linreg(noprint) dlipriva
	# constant  dlipriva{1 to 12}

        compute table3(1,7) = 0
	compute Table3(1,8) = 0
	compute Table3(1,9) = %seesq**.5

Dofor x = 17 to 26

	linreg(noprint) dlipriva
	# constant x dlipriva{1 to 12}

        compute table3(x-15,7) = %beta(2)
	compute Table3(x-15,8) = %tstats(2)
	compute Table3(x-15,9) = %seesq**.5

end dofor x

WRITE table3



********************************************************************************************
********************************************************************************************
* Table4.prg
* This program generated table 4
********************************************************************************************
********************************************************************************************


Cal 1966 1 12
all 2002:11

open data tab4.rat

data(format=rats) / LIC1 LIC2 LIC3 LIC4 LIC5 LIU1 LIU2 LIU3 LIU4 LIU5 LICM LIUM LANAGRA LIPRIVA LTU LF

close data

**16 SERIES LOADED INTO PROGRAM

*Transform independent variables into monthly growth rates
set dlic1 / = (log(lic1) - log(licm{1})) * 100
set dlic2 / = (log(lic2) - log(licm{1})) * 100
set dlic3 / = (log(lic3) - log(licm{1})) * 100
set dlic4 / = (log(lic4) - log(licm{1})) * 100
set dlic5 / = (log(lic5) - log(licm{1})) * 100
set dliu1 / = (log(liu1) - log(lium{1})) * 100
set dliu2 / = (log(liu2) - log(lium{1})) * 100
set dliu3 / = (log(liu3) - log(lium{1})) * 100
set dliu4 / = (log(liu4) - log(lium{1})) * 100
set dliu5 / = (log(liu5) - log(lium{1})) * 100
**INDEPENDENT VARS USED IN REGRESSIONS ARE SERIES 17-26

*Transform Labor Market vars to monthly growth rates
set UR / = (ltu/lf) * 100
set dlanagra / = (log(lanagra) - log(lanagra{1})) * 100
set dlipriva / = (log(lipriva) - log(lipriva{1})) * 100
**DEPENDENT VARS USED IN REGRESSIONS ARE SERIES 27,28,29

*************************************************
**** UNEMPLOYMENT RATE REGRESSIONS   ************
*************************************************

decl vector[series] URFor(11)

* First estimation period ends in 1990:06, last forecast data pt=2001:11
* Creates recursive UR forecast series 30 to 40 from July 1990 to Nov 2001

Dofor x = 17 to 26
	do i = 1,137

	smpl 1968:02 1990:05+i
	linreg(noprint) UR
	# constant x UR{1 to 12}

	prj ((x+29)-16) 1990:06+i 1990:06+i

	end do i
end dofor x

	do i = 1,137

	smpl 1968:02 1990:05+i

	linreg(noprint) UR
	# constant UR{1 to 12}

	prj (40) 1990:06+i 1990:06+i


	end do i



*************************************************
**** LANAGRA REGRESSIONS   **********************
*************************************************


decl vector[series] jobsFor(11)

*First estimation period ends in 1990:06, last forecast data pt=2001:11
* Creates recursive Jobs forecast series 41 to 51 from July 1990 to Nov 2001

Dofor x = 17 to 26

	do i = 1,137

	smpl 1968:02 1990:05+i
	linreg(noprint) dlanagra
	# constant x dlanagra{1 to 12}

	prj ((x+40)-16) 1990:06+i 1990:06+i

	end do i

end dofor x

	do i = 1,137

	smpl 1968:02 1990:05+i

	linreg(noprint) dlanagra
	# constant dlanagra{1 to 12}

	prj (51) 1990:06+i 1990:06+i


	end do i

*************************************************
**** LIPRIVA REGRESSIONS   **********************
*************************************************

decl vector[series] hoursFor(11)

* First estimation period ends in 1990:06, last forecast data pt=2001:11
* Creates recursive hours forecast series 52 to 62 from July 1990 to Nov 2001

Dofor x = 17 to 26
	do i = 1,137

	smpl 1968:02 1990:05+i
	linreg(noprint) dlipriva
	# constant x dlipriva{1 to 12}

	prj ((x+51)-16) 1990:06+i 1990:06+i

	end do i
end dofor x

	do i = 1,137

	smpl 1968:02 1990:05+i

	linreg(noprint) dlipriva
	# constant dlipriva{1 to 12}

	prj (62) 1990:06+i 1990:06+i

	end do i


  smpl 1990:07 2001:11

***************************************************
* creates series of squared errors numbered 63 to 95
***************************************************
decl vector[series] sqerrors(33)

dofor x = 30 to 40
  set  [series]x+33 = (UR-[series]x)**2
end do x

dofor x = 41 to 51
  set  [series]x+33 = (dlanagra-[series]x)**2
end do x

dofor x = 52 to 62
  set  [series]x+33 = (dlipriva-[series]x)**2
end do x


***************************************************
* creates series of error cross products numbered 96 to 125
***************************************************
decl vector[series]   cperrors(30)

dofor x = 30 to 39
  set  [series]x+66 = (ur-[series]x)*(ur-[series]40)
end do x

dofor x = 41 to 50
  set  [series]x+65 = (dlanagra-[series]x)*(dlanagra-[series]51)
end do x

dofor x = 52 to 61
  set  [series]x+64 = (dlipriva-[series]x)*(dlipriva-[series]62)
end do x

************************
*     store data       *
************************

/*
 table
open copy table4forecasts.XLS
copy(org=obs,format=xls,dates) / [series] 30 to 62
close copy
open copy table4squarederrors.XLS
copy(org=obs,format=xls,dates) / [series] 63 to 95
close copy

open copy table4xproducts.XLS
copy(org=obs,format=xls,dates) / [series] 96 to 125
close copy
*/

********************
*   Compute error squared
********************

  Make sematrix 1990:07 2001:11
  # 63 to 95
  Make cpemat 1990:07 2001:11
  # 96 to 125
decl vector mse(33)
decl vector mcpe(30)

dofor x = 1 to 33

  compute mse(x) = %sum(%xcol(sematrix,x)) / %rows(sematrix)

end do x

compute rmse = %sqrt(mse)

write rmse

dofor x = 1 to 30

  compute mcpe(x) = %sum(%xcol(cpemat,x)) / %rows(cpemat)

end do x

write mcpe

write mse

compute p = %rows(sematrix)
write p



open copy RMSE&mcpe.TXT
WRITE(UNIT=COPY)  'RMSE' RMSE 'Mcpe' McpE
close copy



********************************************************************************************
********************************************************************************************
* Table5.prg
* This program generated table 5
********************************************************************************************
********************************************************************************************

Cal 1966 1 12
all 2002:11

open data tab5.rat

data(format=rats) / LIC1 LIC2 LIC3 LIC4 LIC5 LIU1 LIU2 LIU3 LIU4 LIU5 LICM LIUM LANAGRA LIPRIVA LTU LF

close data

**16 SERIES LOADED INTO PROGRAM

*Transform independent variables into monthly growth rates
set dlic1 / = (log(lic1) - log(licm{1})) * 100
set dlic2 / = (log(lic2) - log(licm{1})) * 100
set dlic3 / = (log(lic3) - log(licm{1})) * 100
set dlic4 / = (log(lic4) - log(licm{1})) * 100
set dlic5 / = (log(lic5) - log(licm{1})) * 100
set dliu1 / = (log(liu1) - log(lium{1})) * 100
set dliu2 / = (log(liu2) - log(lium{1})) * 100
set dliu3 / = (log(liu3) - log(lium{1})) * 100
set dliu4 / = (log(liu4) - log(lium{1})) * 100
set dliu5 / = (log(liu5) - log(lium{1})) * 100
**INDEPENDENT VARS USED IN REGRESSIONS ARE SERIES 17-26

*Transform Labor Market vars to monthly growth rates
set UR / = (ltu/lf) * 100
set dlanagra / = (log(lanagra) - log(lanagra{1})) * 100
set dlipriva / = (log(lipriva) - log(lipriva{1})) * 100
**DEPENDENT VARS USED IN REGRESSIONS ARE SERIES 27,28,29

*************************************************
**** UNEMPLOYMENT RATE REGRESSIONS   ************
*************************************************

decl vector[series] URFor(11)

* First estimation period ends in 1990:06, last forecast data pt=2001:11
* Creates recursive UR forecast series 30 to 40 from July 1990 to Nov 2001

Dofor x = 17 to 26
	do i = 1,137

	smpl 1968:02 1990:05+i
	linreg(noprint) UR
	# constant x UR{1 to 12}

	prj ((x+29)-16) 1990:06+i 1990:06+i

	end do i
end dofor x

	do i = 1,137

	smpl 1968:02 1990:05+i

	linreg(noprint) UR
	# constant UR{1 to 12}

	prj (40) 1990:06+i 1990:06+i


	end do i



*************************************************
**** LANAGRA REGRESSIONS   **********************
*************************************************


decl vector[series] jobsFor(11)

*First estimation period ends in 1990:06, last forecast data pt=2001:11
* Creates recursive Jobs forecast series 41 to 51 from July 1990 to Nov 2001

Dofor x = 17 to 26

	do i = 1,137

	smpl 1968:02 1990:05+i
	linreg(noprint) dlanagra
	# constant x dlanagra{1 to 12}

	prj ((x+40)-16) 1990:06+i 1990:06+i

	end do i

end dofor x

	do i = 1,137

	smpl 1968:02 1990:05+i

	linreg(noprint) dlanagra
	# constant dlanagra{1 to 12}

	prj (51) 1990:06+i 1990:06+i


	end do i

*************************************************
**** LIPRIVA REGRESSIONS   **********************
*************************************************

decl vector[series] hoursFor(11)

* First estimation period ends in 1990:06, last forecast data pt=2001:11
* Creates recursive hours forecast series 52 to 62 from July 1990 to Nov 2001

Dofor x = 17 to 26
	do i = 1,137

	smpl 1968:02 1990:05+i
	linreg(noprint) dlipriva
	# constant x dlipriva{1 to 12}

	prj ((x+51)-16) 1990:06+i 1990:06+i

	end do i
end dofor x

	do i = 1,137

	smpl 1968:02 1990:05+i

	linreg(noprint) dlipriva
	# constant dlipriva{1 to 12}

	prj (62) 1990:06+i 1990:06+i

	end do i


  smpl 1990:07 2001:11

***************************************************
* creates series of squared errors numbered 63 to 95
***************************************************
decl vector[series] sqerrors(33)

dofor x = 30 to 40
  set  [series]x+33 = (UR-[series]x)**2
end do x

dofor x = 41 to 51
  set  [series]x+33 = (dlanagra-[series]x)**2
end do x

dofor x = 52 to 62
  set  [series]x+33 = (dlipriva-[series]x)**2
end do x


***************************************************
* creates series of error cross products numbered 96 to 125
***************************************************
decl vector[series]   cperrors(30)

dofor x = 30 to 39
  set  [series]x+66 = (ur-[series]x)*(ur-[series]40)
end do x

dofor x = 41 to 50
  set  [series]x+65 = (dlanagra-[series]x)*(dlanagra-[series]51)
end do x

dofor x = 52 to 61
  set  [series]x+64 = (dlipriva-[series]x)*(dlipriva-[series]62)
end do x

************************
*     store data       *
************************

/*
 table
open copy table4forecasts.XLS
copy(org=obs,format=xls,dates) / [series] 30 to 62
close copy
open copy table4squarederrors.XLS
copy(org=obs,format=xls,dates) / [series] 63 to 95
close copy

open copy table4xproducts.XLS
copy(org=obs,format=xls,dates) / [series] 96 to 125
close copy
*/

********************
*   Compute error squared
********************

  Make sematrix 1991:04 2001:2
  # 63 to 95
  Make cpemat 1990:04 2001:2
  # 96 to 125
decl vector mse(33)
decl vector mcpe(30)

dofor x = 1 to 33

  compute mse(x) = %sum(%xcol(sematrix,x)) / %rows(sematrix)

end do x

compute rmse = %sqrt(mse)

write rmse

dofor x = 1 to 30

  compute mcpe(x) = %sum(%xcol(cpemat,x)) / %rows(cpemat)

end do x

write mcpe

write mse

compute p = %rows(sematrix)
write p



open copy RMSE&mcpe.TXT
WRITE(UNIT=COPY)  'RMSE' RMSE 'Mcpe' McpE
close copy