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meanreturns.log
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meanreturns.log
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___ ____ ____ ____ ____ (R)
/__ / ____/ / ____/
___/ / /___/ / /___/ 16.0 Copyright 1985-2019 StataCorp LLC
Statistics/Data Analysis StataCorp
4905 Lakeway Drive
MP - Parallel Edition College Station, Texas 77845 USA
800-STATA-PC http://www.stata.com
979-696-4600 stata@stata.com
979-696-4601 (fax)
Single-user 2-core Stata perpetual license:
Serial number: 501606204617
Licensed to: Miklos Koren
CEU MicroData
Notes:
1. Stata is running in batch mode.
2. Unicode is supported; see help unicode_advice.
3. More than 2 billion observations are allowed; see help obs_advice.
4. Maximum number of variables is set to 5000; see help set_maxvar.
. do meanreturns.do
. use "data/unido/unido-dollar.dta", clear
. gen ccode=.
(96,430 missing values generated)
.
. * rename
. ren ind isic
.
. * drop weird stuff
. * drop if cnum==""
. drop if isic==300
(0 observations deleted)
.
. * create categ variables
. egen countrysector = group(cnum isic)
.
. gen share = empl
(35,852 missing values generated)
. gen logshock = log(val)-log(empl) if (val~=.)&(empl~=.)
(44,735 missing values generated)
.
. * deflate logshock TO INTERNATIONAL DOLLARS not domestic constant price
. sort cnum year
. merge cnum year using "data/pwt/pwt_prices.dta"
(note: you are using old merge syntax; see [D] merge for new syntax)
variables cnum year do not uniquely identify observations in the master data
. tab _
_merge | Freq. Percent Cum.
------------+-----------------------------------
1 | 4,980 4.92 4.92
2 | 4,855 4.79 9.71
3 | 91,450 90.29 100.00
------------+-----------------------------------
Total | 101,285 100.00
. drop if _==2
(4,855 observations deleted)
. drop _
.
. sort cnum year
. merge cnum year using "data/wdi/wdinew.dta"
(note: you are using old merge syntax; see [D] merge for new syntax)
variables cnum year do not uniquely identify observations in the master data
(note: variable ccode was str3 in the using data, but will be float now)
(note: variable cname was str32, now str34 to accommodate using data's
values)
. tab _
_merge | Freq. Percent Cum.
------------+-----------------------------------
1 | 11,875 11.88 11.88
2 | 3,515 3.52 15.40
3 | 84,555 84.60 100.00
------------+-----------------------------------
Total | 99,945 100.00
. drop if _==2
(3,515 observations deleted)
. drop _
.
. gen temp=cpi if cnum==840
(95,727 missing values generated)
. egen cpiUSA=mean(temp), by(year)
(1637 missing values generated)
.
. * use cpi here but PPPfa elsewhere
. replace logshock = logshock-log(p)-log(cpiUSA)
(51,695 real changes made, 6,442 to missing)
.
. * now back for the level of labor prod
. * <=. WAS WRONG
. gen laborprod0 = (val/p*100)/empl if (val+empl+p<.)
(50,602 missing values generated)
.
. su laborprod0, d
laborprod0
-------------------------------------------------------------
Percentiles Smallest
1% 1.070421 -159.1546
5% 2.629073 -42.08187
10% 3.925706 -17.84368 Obs 45,828
25% 7.359031 -14.06624 Sum of Wgt. 45,828
50% 14.57732 Mean 22.6615
Largest Std. Dev. 30.57024
75% 28.56588 823.3418
90% 48.23658 824.1932 Variance 934.5397
95% 63.77706 1416.589 Skewness 12.46141
99% 125.2678 1835.237 Kurtosis 450.5568
.
. tsset countrysector year
panel variable: countrysector (unbalanced)
time variable: year, 1963 to 2000, but with gaps
delta: 1 unit
.
. gen Dshock = logshock-L5.logshock
(62,141 missing values generated)
. * to take fifth difference
. * alternatively, we may take a fancier filter, e.g. Baxter-King, Hodrick-Pres
> cott
. * these programs are avaiable for Stata
.
. * drop outliers
.
.
. ************FOR UNIDO DATA
. drop if (cname=="Peru") & (year>=1979) & (year<=1981)
(57 observations deleted)
. drop if (cname=="Angola")
(704 observations deleted)
. drop if (cname=="Azerbaijan")
(95 observations deleted)
. drop if (cname=="Brazil") & (year==1985)
(17 observations deleted)
.
. count if (Dshock>5*log(2))&(Dshock!=.)
78
. l cname year isic Dshock if (Dshock>5*log(2))&(Dshock!=.)
+-----------------------------------+
| cname year isic Dshock |
|-----------------------------------|
7629. | Brazil 1990 311 20.02413 |
7666. | Brazil 1990 321 19.932 |
7799. | Brazil 1990 331 20.11984 |
7836. | Brazil 1990 332 20.57726 |
7873. | Brazil 1990 341 19.99116 |
|-----------------------------------|
7910. | Brazil 1990 342 20.41765 |
7947. | Brazil 1990 351 19.74609 |
7984. | Brazil 1990 355 19.71843 |
8021. | Brazil 1990 356 20.07973 |
8058. | Brazil 1990 361 20.38589 |
|-----------------------------------|
8127. | Brazil 1990 381 20.6492 |
8164. | Brazil 1990 383 20.03058 |
8201. | Brazil 1990 384 20.14464 |
43000. | Jamaica 1969 371 3.747217 |
43001. | Jamaica 1970 371 3.531042 |
|-----------------------------------|
43002. | Jamaica 1971 371 3.760158 |
44380. | Jordan 1976 381 5.095486 |
52410. | Malawi 1998 361 3.569022 |
63959. | Nigeria 1996 384 3.557865 |
67418. | Peru 1984 311 14.91828 |
|-----------------------------------|
67419. | Peru 1985 311 14.72851 |
67420. | Peru 1986 311 14.40442 |
67453. | Peru 1984 321 15.0054 |
67454. | Peru 1985 321 14.98823 |
67455. | Peru 1986 321 14.68074 |
|-----------------------------------|
67488. | Peru 1984 322 15.29756 |
67489. | Peru 1985 322 14.85804 |
67490. | Peru 1986 322 14.73667 |
67523. | Peru 1984 323 14.62147 |
67524. | Peru 1985 323 14.24103 |
|-----------------------------------|
67525. | Peru 1986 323 14.7304 |
67558. | Peru 1984 324 14.87209 |
67559. | Peru 1985 324 14.57669 |
67560. | Peru 1986 324 14.18979 |
67593. | Peru 1984 331 14.53943 |
|-----------------------------------|
67594. | Peru 1985 331 14.35476 |
67595. | Peru 1986 331 14.13841 |
67628. | Peru 1984 332 15.049 |
67629. | Peru 1985 332 14.43611 |
67630. | Peru 1986 332 13.49648 |
|-----------------------------------|
67663. | Peru 1984 341 15.03092 |
67664. | Peru 1985 341 14.79048 |
67665. | Peru 1986 341 14.4397 |
67698. | Peru 1984 342 15.32601 |
67699. | Peru 1985 342 14.90226 |
|-----------------------------------|
67700. | Peru 1986 342 14.43399 |
67733. | Peru 1984 351 15.84165 |
67734. | Peru 1985 351 15.99331 |
67735. | Peru 1986 351 15.11001 |
67768. | Peru 1984 355 15.74734 |
|-----------------------------------|
67769. | Peru 1985 355 15.15907 |
67770. | Peru 1986 355 14.76474 |
67803. | Peru 1984 356 15.29914 |
67804. | Peru 1985 356 15.04368 |
67805. | Peru 1986 356 14.63203 |
|-----------------------------------|
67838. | Peru 1984 361 15.48235 |
67839. | Peru 1985 361 15.0633 |
67840. | Peru 1986 361 14.82481 |
67873. | Peru 1984 371 14.42303 |
67874. | Peru 1985 371 14.16069 |
|-----------------------------------|
67875. | Peru 1986 371 14.26081 |
67908. | Peru 1984 381 14.87351 |
67909. | Peru 1985 381 14.6337 |
67910. | Peru 1986 381 14.49028 |
67943. | Peru 1984 383 15.19822 |
|-----------------------------------|
67944. | Peru 1985 383 14.85837 |
67945. | Peru 1986 383 14.59187 |
67978. | Peru 1984 384 15.16282 |
67979. | Peru 1985 384 14.52876 |
67980. | Peru 1986 384 14.5245 |
|-----------------------------------|
68013. | Peru 1984 385 15.404 |
68014. | Peru 1985 385 15.11253 |
68015. | Peru 1986 385 14.66162 |
68048. | Peru 1984 390 15.07403 |
68049. | Peru 1985 390 14.4357 |
|-----------------------------------|
68050. | Peru 1986 390 14.56088 |
82507. | Thailand 1991 342 5.007933 |
88240. | Egypt 1998 323 4.17321 |
+-----------------------------------+
. ************change this!!!
. drop if (Dshock>5*log(2))&(Dshock!=.)
(78 observations deleted)
.
. ***********change this!!!
. count if Dshock<-5*log(2)
8
. l cname year isic Dshock if Dshock<-5*log(2)
+-------------------------------------------------------+
| cname year isic Dshock |
|-------------------------------------------------------|
19127. | Costa Rica 1999 385 -4.169993 |
55345. | Mauritius 1998 361 -3.664863 |
63401. | Nigeria 1996 321 -4.909962 |
63509. | Nigeria 1996 324 -3.630276 |
63905. | Nigeria 1996 383 -3.902119 |
|-------------------------------------------------------|
88158. | Egypt 1993 323 -4.530517 |
89558. | United Republic of Tanzania 1995 323 -4.380703 |
89559. | United Republic of Tanzania 1996 323 -4.91194 |
+-------------------------------------------------------+
. drop if Dshock<-5*log(2)
(8 observations deleted)
.
.
. * now try to balance it somehow
. egen numind = count(laborprod0), by(cnum year)
. su numind
Variable | Obs Mean Std. Dev. Min Max
-------------+---------------------------------------------------------
numind | 95,471 8.895727 9.045071 0 19
. keep if numind==r(max)
(62,392 observations deleted)
. egen numyea = count(laborprod0), by(cnum isic)
. tab numyea
numyea | Freq. Percent Cum.
------------+-----------------------------------
2 | 114 0.34 0.34
4 | 76 0.23 0.57
5 | 380 1.15 1.72
6 | 114 0.34 2.07
7 | 133 0.40 2.47
8 | 152 0.46 2.93
9 | 342 1.03 3.96
10 | 380 1.15 5.11
11 | 418 1.26 6.38
12 | 228 0.69 7.06
13 | 494 1.49 8.56
14 | 266 0.80 9.36
15 | 285 0.86 10.22
18 | 342 1.03 11.26
19 | 722 2.18 13.44
20 | 380 1.15 14.59
21 | 399 1.21 15.80
22 | 418 1.26 17.06
23 | 874 2.64 19.70
24 | 456 1.38 21.08
25 | 950 2.87 23.95
27 | 513 1.55 25.50
28 | 1,064 3.22 28.72
29 | 551 1.67 30.38
30 | 3,420 10.34 40.72
31 | 1,178 3.56 44.28
32 | 608 1.84 46.12
33 | 4,389 13.27 59.39
34 | 1,938 5.86 65.25
36 | 684 2.07 67.32
37 | 703 2.13 69.44
38 | 10,108 30.56 100.00
------------+-----------------------------------
Total | 33,079 100.00
. su numyea
Variable | Obs Mean Std. Dev. Min Max
-------------+---------------------------------------------------------
numyea | 33,079 30.15221 8.6864 2 38
.
. ************** THRESHOLD ******************
. * keep only if more than 20 years
. keep if (numyea>=20)&(numyea!=.)
(4,446 observations deleted)
.
.
. tab cname if laborprod0<.
cname | Freq. Percent Cum.
-----------------------------------+-----------------------------------
Australia | 570 1.99 1.99
Austria | 722 2.52 4.51
Bangladesh | 532 1.86 6.37
Bolivia | 513 1.79 8.16
Canada | 722 2.52 10.68
Chile | 722 2.52 13.21
China, Hong Kong SAR | 475 1.66 14.86
China, Taiwan Province | 456 1.59 16.46
Colombia | 722 2.52 18.98
Denmark | 551 1.92 20.90
Ecuador | 684 2.39 23.29
Egypt | 627 2.19 25.48
El Salvador | 380 1.33 26.81
Finland | 608 2.12 28.93
France | 627 2.19 31.12
Germany, Western Part | 437 1.53 32.65
Ghana | 418 1.46 34.11
Greece | 722 2.52 36.63
Hungary | 589 2.06 38.69
India | 722 2.52 41.21
Indonesia | 437 1.53 42.73
Iran, Islamic Republic of | 570 1.99 44.72
Ireland | 722 2.52 47.25
Israel | 627 2.19 49.44
Italy | 646 2.26 51.69
Japan | 722 2.52 54.21
Korea, Republic of | 722 2.52 56.74
Malaysia | 627 2.19 58.93
Netherlands | 627 2.19 61.11
New Zealand | 532 1.86 62.97
Nicaragua | 399 1.39 64.37
Norway | 722 2.52 66.89
Pakistan | 570 1.99 68.88
Philippines | 646 2.26 71.13
Poland | 570 1.99 73.13
Portugal | 570 1.99 75.12
Singapore | 722 2.52 77.64
South Africa | 646 2.26 79.89
Spain | 722 2.52 82.42
Sri Lanka | 475 1.66 84.07
Sweden | 722 2.52 86.60
Turkey | 722 2.52 89.12
United Kingdom | 589 2.06 91.17
United States of America | 627 2.19 93.36
Uruguay | 570 1.99 95.36
Venezuela | 627 2.19 97.54
Zimbabwe | 703 2.46 100.00
-----------------------------------+-----------------------------------
Total | 28,633 100.00
.
.
. * create categ
. egen country=group(cnum)
. su country
Variable | Obs Mean Std. Dev. Min Max
-------------+---------------------------------------------------------
country | 28,633 24.50896 13.6194 1 47
. global J = r(max)
.
. egen sector=group(isic)
. su sector
Variable | Obs Mean Std. Dev. Min Max
-------------+---------------------------------------------------------
sector | 28,633 10 5.477321 1 19
. global S = r(max)
.
. * now demean it country by country and sector by sector
. egen mind = mean(Dshock), by(sector)
. egen mcnt = mean(Dshock), by(country)
. egen moverall = mean(Dshock)
. *egen mean = mean(Dshock), by(sector country)
.
. gen shock = Dshock-mind-mcnt+moverall
(4,829 missing values generated)
.
. * then the shares
. egen sumshare = sum(share), by(country year)
. replace share = share/sumshare
(28,633 real changes made)
.
. save "data/derived/shares.dta", replace
file data/derived/shares.dta saved
.
. * go for the means
. collapse (mean) laborprod = laborprod0, by(cnum country isic sector)
. su laborprod, d
(mean) laborprod0
-------------------------------------------------------------
Percentiles Smallest
1% 3.171845 2.494038
5% 6.270967 2.56112
10% 8.927624 2.584828 Obs 893
25% 13.41063 2.594552 Sum of Wgt. 893
50% 20.17905 Mean 23.29936
Largest Std. Dev. 16.926
75% 28.38597 138.9766
90% 39.60019 142.8606 Variance 286.4894
95% 49.03619 159.8158 Skewness 3.784294
99% 93.29829 201.1104 Kurtosis 28.75851
.
. sort cnum isic
. save "data/derived/meanlaborprod_long.dta", replace
file data/derived/meanlaborprod_long.dta saved
.
. keep sector country laborprod
. reshape wide laborprod, i(country) j(sector)
(note: j = 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19)
Data long -> wide
-----------------------------------------------------------------------------
Number of obs. 893 -> 47
Number of variables 3 -> 20
j variable (19 values) sector -> (dropped)
xij variables:
laborprod -> laborprod1 laborprod2 ... laborp
> rod19
-----------------------------------------------------------------------------
.
. sort country
. save "data/derived/meanlaborprod_wide.dta", replace
file data/derived/meanlaborprod_wide.dta saved
.
.
. * now do the WIDE stuff
. use "data/derived/shares.dta", clear
.
. keep share country year sector cnum
. reshape wide share, i(country cnum year) j(sector)
(note: j = 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19)
Data long -> wide
-----------------------------------------------------------------------------
Number of obs. 28633 -> 1507
Number of variables 5 -> 22
j variable (19 values) sector -> (dropped)
xij variables:
share -> share1 share2 ... share19
-----------------------------------------------------------------------------
.
. sort cnum year
. save "data/derived/preparedshares.dta", replace
file data/derived/preparedshares.dta saved
.
. ********************************************
. * will need to create the sample second moment matrix here
.
. use "data/derived/shares.dta", clear
. * this is a unique identifier w/ last 2 digits = sector
. gen cntsec = country*100+sector
. keep cntsec year shock
. reshape wide shock, i(year) j(cntsec)
(note: j = 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117
> 118 119 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 2
> 18 219 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 31
> 8 319 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418
> 419 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518
> 519 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 6
> 19 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 71
> 9 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819
> 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919
> 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 10
> 16 1017 1018 1019 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112
> 1113 1114 1115 1116 1117 1118 1119 1201 1202 1203 1204 1205 1206 1207 1208 1
> 209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1301 1302 1303 1304 130
> 5 1306 1307 1308 1309 1310 1311 1312 1313 1314 1315 1316 1317 1318 1319 1401
> 1402 1403 1404 1405 1406 1407 1408 1409 1410 1411 1412 1413 1414 1415 1416 14
> 17 1418 1419 1501 1502 1503 1504 1505 1506 1507 1508 1509 1510 1511 1512 1513
> 1514 1515 1516 1517 1518 1519 1601 1602 1603 1604 1605 1606 1607 1608 1609 1
> 610 1611 1612 1613 1614 1615 1616 1617 1618 1619 1701 1702 1703 1704 1705 170
> 6 1707 1708 1709 1710 1711 1712 1713 1714 1715 1716 1717 1718 1719 1801 1802
> 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 1814 1815 1816 1817 18
> 18 1819 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914
> 1915 1916 1917 1918 1919 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2
> 011 2012 2013 2014 2015 2016 2017 2018 2019 2101 2102 2103 2104 2105 2106 210
> 7 2108 2109 2110 2111 2112 2113 2114 2115 2116 2117 2118 2119 2201 2202 2203
> 2204 2205 2206 2207 2208 2209 2210 2211 2212 2213 2214 2215 2216 2217 2218 22
> 19 2301 2302 2303 2304 2305 2306 2307 2308 2309 2310 2311 2312 2313 2314 2315
> 2316 2317 2318 2319 2401 2402 2403 2404 2405 2406 2407 2408 2409 2410 2411 2
> 412 2413 2414 2415 2416 2417 2418 2419 2501 2502 2503 2504 2505 2506 2507 250
> 8 2509 2510 2511 2512 2513 2514 2515 2516 2517 2518 2519 2601 2602 2603 2604
> 2605 2606 2607 2608 2609 2610 2611 2612 2613 2614 2615 2616 2617 2618 2619 27
> 01 2702 2703 2704 2705 2706 2707 2708 2709 2710 2711 2712 2713 2714 2715 2716
> 2717 2718 2719 2801 2802 2803 2804 2805 2806 2807 2808 2809 2810 2811 2812 2
> 813 2814 2815 2816 2817 2818 2819 2901 2902 2903 2904 2905 2906 2907 2908 290
> 9 2910 2911 2912 2913 2914 2915 2916 2917 2918 2919 3001 3002 3003 3004 3005
> 3006 3007 3008 3009 3010 3011 3012 3013 3014 3015 3016 3017 3018 3019 3101 31
> 02 3103 3104 3105 3106 3107 3108 3109 3110 3111 3112 3113 3114 3115 3116 3117
> 3118 3119 3201 3202 3203 3204 3205 3206 3207 3208 3209 3210 3211 3212 3213 3
> 214 3215 3216 3217 3218 3219 3301 3302 3303 3304 3305 3306 3307 3308 3309 331
> 0 3311 3312 3313 3314 3315 3316 3317 3318 3319 3401 3402 3403 3404 3405 3406
> 3407 3408 3409 3410 3411 3412 3413 3414 3415 3416 3417 3418 3419 3501 3502 35
> 03 3504 3505 3506 3507 3508 3509 3510 3511 3512 3513 3514 3515 3516 3517 3518
> 3519 3601 3602 3603 3604 3605 3606 3607 3608 3609 3610 3611 3612 3613 3614 3
> 615 3616 3617 3618 3619 3701 3702 3703 3704 3705 3706 3707 3708 3709 3710 371
> 1 3712 3713 3714 3715 3716 3717 3718 3719 3801 3802 3803 3804 3805 3806 3807
> 3808 3809 3810 3811 3812 3813 3814 3815 3816 3817 3818 3819 3901 3902 3903 39
> 04 3905 3906 3907 3908 3909 3910 3911 3912 3913 3914 3915 3916 3917 3918 3919
> 4001 4002 4003 4004 4005 4006 4007 4008 4009 4010 4011 4012 4013 4014 4015 4
> 016 4017 4018 4019 4101 4102 4103 4104 4105 4106 4107 4108 4109 4110 4111 411
> 2 4113 4114 4115 4116 4117 4118 4119 4201 4202 4203 4204 4205 4206 4207 4208
> 4209 4210 4211 4212 4213 4214 4215 4216 4217 4218 4219 4301 4302 4303 4304 43
> 05 4306 4307 4308 4309 4310 4311 4312 4313 4314 4315 4316 4317 4318 4319 4401
> 4402 4403 4404 4405 4406 4407 4408 4409 4410 4411 4412 4413 4414 4415 4416 4
> 417 4418 4419 4501 4502 4503 4504 4505 4506 4507 4508 4509 4510 4511 4512 451
> 3 4514 4515 4516 4517 4518 4519 4601 4602 4603 4604 4605 4606 4607 4608 4609
> 4610 4611 4612 4613 4614 4615 4616 4617 4618 4619 4701 4702 4703 4704 4705 47
> 06 4707 4708 4709 4710 4711 4712 4713 4714 4715 4716 4717 4718 4719)
Data long -> wide
-----------------------------------------------------------------------------
Number of obs. 28633 -> 38
Number of variables 3 -> 894
j variable (893 values) cntsec -> (dropped)
xij variables:
shock -> shock101 shock102 ... shock4719
-----------------------------------------------------------------------------
. * this is very wide, may need more memory
.
.
.
end of do-file