Develop level ratio change elasticity functions • PrjCompPPTS

library(tibble)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(tidyr)
library(stringr)
library(readr)
library(kableExtra)
#> 
#> Attaching package: 'kableExtra'
#> The following object is masked from 'package:dplyr':
#> 
#>     group_rows

library(PrjCompPPTS)
# If resave outputs to data, only do this during development

Working through three core functions of PrjCompPPTS-Issue 7. This was developed prior to functionalizing.

Algorithm outline

Three core files

We follow the steps below, which produces three separable files, then merge together. Each file’s unit of observation are ultimately locType x loc

Step 1 file, levels and ratios, flr:

Start with long file, keep all locations and location types, select a subst of years, select teachers, schools, students, youthpop so different ratios can be constructed, and levels we want kept
Vars kept from long to wide
- unit of obs: locType x loc x time
RATIO/LEVELS: Compute key ratios within time periods, year level/ratio stats done:
- Teacher over student: var_rat_t2s
- Teacher over youthpop: var_rat_t2y
- School over student: var_rat_s2s
- School over youthpop: var_rat_sty

Step 2 file, percentage change, fpc, also contains levels:

From levels/ratios file (keep ranks), variables are levels and ratios, convert all vars to long
- unit of obs: locType x loc x time x var(level/change)
Generate ranks, grouped by locType x loc x time x var(level/change)
Select subperiods of interest, time from long to wide
- unit of obs: locType x loc x var(level/change)
Compute stats ratios over time for level and change vars
- 1980 to 2020 change
- 80 to 00, 00 to 20

Step 3 file, elasticity, fel:

From fpc, keep percentage changes as stats vars, drop level and rank vars
From percentage change file, variables are changes over time, convert all change spans to long
- unit of obs: locType x loc x vars(level/change) x changeSpan
Convert vars(level/change) to wide
- unit of obs: locType x loc x changeSpan
ELASTICITY: ratio of percentage changes across vars
Convert to standard format
- unit of obs: locType x loc x vars, and year spans as columns

Output file

We now proceed to outline the development of tables relevant for different components of the paper, corresponding to each paper section.

Global changes in youth population table:

From file flr, keep levels in 1960, 80, 00, 20, country + 7 regions
From fpc, changes 60t80, 80t20, 00t20, country + 7 regions
From file flr, keep ranks in 1960, 20, country + 7 regions
Group by region type an region, sort by country, 9 variable/column table

Global children and teachers file, two versions, pupil- and children-based separately:

Unit of observation: country at selected years
var country
var (3) children to teacher ratio in 1980, 2000, 2020: from fpc, select level col ratio rows
var (3) children to teacher ranking in 1980 vs 2020: from fpc, select level col ranks row
var (1) children to teacher ratio change over time 1980 to 2020: from fpc, select change col and ratio row
var (1) percentage change in children 1980 to 2020: from fpc, select change col and level row
var (1) percentage change in teachers 1980 to 2020: from fpc, select change col and level row
var (1) teacher-children elasticity over time: from fel, select changeSpan row

Teachers and Schools vs children and pupil in sub-regions.

Load data inputs and review

We load in the key file

ppts_code_wrk <- ppts_country_code

We load in the global population data.

ppts_wrk <- ppts_easia_weuro_world_pchg
colnames(ppts_wrk)
#> [1] "location_code"  "location_level" "variable"       "year_bins_type"
#> [5] "year_bins"      "pchg"           "pchg_interp1"   "value"         
#> [9] "value_interp1"
print(ppts_wrk %>% distinct(variable))
#> # A tibble: 5 × 1
#>   variable
#>   <fct>   
#> 1 gdp     
#> 2 student 
#> 3 teacher 
#> 4 youthpop
#> 5 school
print(ppts_wrk %>% distinct(location_level))
#> # A tibble: 4 × 1
#>   location_level
#>   <fct>         
#> 1 country       
#> 2 multicountry  
#> 3 multiprovince 
#> 4 province
print(ppts_wrk %>% distinct(year_bins_type))
#> # A tibble: 5 × 1
#>   year_bins_type
#>   <fct>         
#> 1 1920t2020i05  
#> 2 1920t2020i10  
#> 3 1920t2020i20  
#> 4 1925t2015i15  
#> 5 1940t2020i01
print(ppts_wrk %>% distinct(year_bins, year_bins_type) %>%
  arrange(year_bins_type, year_bins), n = 200)
#> # A tibble: 142 × 2
#>     year_bins year_bins_type
#>     <chr>     <fct>         
#>   1 1921-1925 1920t2020i05  
#>   2 1926-1930 1920t2020i05  
#>   3 1931-1935 1920t2020i05  
#>   4 1936-1940 1920t2020i05  
#>   5 1941-1945 1920t2020i05  
#>   6 1946-1950 1920t2020i05  
#>   7 1951-1955 1920t2020i05  
#>   8 1956-1960 1920t2020i05  
#>   9 1961-1965 1920t2020i05  
#>  10 1966-1970 1920t2020i05  
#>  11 1971-1975 1920t2020i05  
#>  12 1976-1980 1920t2020i05  
#>  13 1981-1985 1920t2020i05  
#>  14 1986-1990 1920t2020i05  
#>  15 1991-1995 1920t2020i05  
#>  16 1996-2000 1920t2020i05  
#>  17 2001-2005 1920t2020i05  
#>  18 2006-2010 1920t2020i05  
#>  19 2011-2015 1920t2020i05  
#>  20 2016-2020 1920t2020i05  
#>  21 1921-1930 1920t2020i10  
#>  22 1931-1940 1920t2020i10  
#>  23 1941-1950 1920t2020i10  
#>  24 1951-1960 1920t2020i10  
#>  25 1961-1970 1920t2020i10  
#>  26 1971-1980 1920t2020i10  
#>  27 1981-1990 1920t2020i10  
#>  28 1991-2000 1920t2020i10  
#>  29 2001-2010 1920t2020i10  
#>  30 2011-2020 1920t2020i10  
#>  31 1921-1940 1920t2020i20  
#>  32 1941-1960 1920t2020i20  
#>  33 1961-1980 1920t2020i20  
#>  34 1981-2000 1920t2020i20  
#>  35 2001-2020 1920t2020i20  
#>  36 1926-1940 1925t2015i15  
#>  37 1941-1955 1925t2015i15  
#>  38 1956-1970 1925t2015i15  
#>  39 1971-1985 1925t2015i15  
#>  40 1986-2000 1925t2015i15  
#>  41 2001-2015 1925t2015i15  
#>  42 1920      1940t2020i01  
#>  43 1921      1940t2020i01  
#>  44 1922      1940t2020i01  
#>  45 1923      1940t2020i01  
#>  46 1924      1940t2020i01  
#>  47 1925      1940t2020i01  
#>  48 1926      1940t2020i01  
#>  49 1927      1940t2020i01  
#>  50 1928      1940t2020i01  
#>  51 1929      1940t2020i01  
#>  52 1930      1940t2020i01  
#>  53 1931      1940t2020i01  
#>  54 1932      1940t2020i01  
#>  55 1933      1940t2020i01  
#>  56 1934      1940t2020i01  
#>  57 1935      1940t2020i01  
#>  58 1936      1940t2020i01  
#>  59 1937      1940t2020i01  
#>  60 1938      1940t2020i01  
#>  61 1939      1940t2020i01  
#>  62 1940      1940t2020i01  
#>  63 1941      1940t2020i01  
#>  64 1942      1940t2020i01  
#>  65 1943      1940t2020i01  
#>  66 1944      1940t2020i01  
#>  67 1945      1940t2020i01  
#>  68 1946      1940t2020i01  
#>  69 1947      1940t2020i01  
#>  70 1948      1940t2020i01  
#>  71 1949      1940t2020i01  
#>  72 1950      1940t2020i01  
#>  73 1951      1940t2020i01  
#>  74 1952      1940t2020i01  
#>  75 1953      1940t2020i01  
#>  76 1954      1940t2020i01  
#>  77 1955      1940t2020i01  
#>  78 1956      1940t2020i01  
#>  79 1957      1940t2020i01  
#>  80 1958      1940t2020i01  
#>  81 1959      1940t2020i01  
#>  82 1960      1940t2020i01  
#>  83 1961      1940t2020i01  
#>  84 1962      1940t2020i01  
#>  85 1963      1940t2020i01  
#>  86 1964      1940t2020i01  
#>  87 1965      1940t2020i01  
#>  88 1966      1940t2020i01  
#>  89 1967      1940t2020i01  
#>  90 1968      1940t2020i01  
#>  91 1969      1940t2020i01  
#>  92 1970      1940t2020i01  
#>  93 1971      1940t2020i01  
#>  94 1972      1940t2020i01  
#>  95 1973      1940t2020i01  
#>  96 1974      1940t2020i01  
#>  97 1975      1940t2020i01  
#>  98 1976      1940t2020i01  
#>  99 1977      1940t2020i01  
#> 100 1978      1940t2020i01  
#> 101 1979      1940t2020i01  
#> 102 1980      1940t2020i01  
#> 103 1981      1940t2020i01  
#> 104 1982      1940t2020i01  
#> 105 1983      1940t2020i01  
#> 106 1984      1940t2020i01  
#> 107 1985      1940t2020i01  
#> 108 1986      1940t2020i01  
#> 109 1987      1940t2020i01  
#> 110 1988      1940t2020i01  
#> 111 1989      1940t2020i01  
#> 112 1990      1940t2020i01  
#> 113 1991      1940t2020i01  
#> 114 1992      1940t2020i01  
#> 115 1993      1940t2020i01  
#> 116 1994      1940t2020i01  
#> 117 1995      1940t2020i01  
#> 118 1996      1940t2020i01  
#> 119 1997      1940t2020i01  
#> 120 1998      1940t2020i01  
#> 121 1999      1940t2020i01  
#> 122 2000      1940t2020i01  
#> 123 2001      1940t2020i01  
#> 124 2002      1940t2020i01  
#> 125 2003      1940t2020i01  
#> 126 2004      1940t2020i01  
#> 127 2005      1940t2020i01  
#> 128 2006      1940t2020i01  
#> 129 2007      1940t2020i01  
#> 130 2008      1940t2020i01  
#> 131 2009      1940t2020i01  
#> 132 2010      1940t2020i01  
#> 133 2011      1940t2020i01  
#> 134 2012      1940t2020i01  
#> 135 2013      1940t2020i01  
#> 136 2014      1940t2020i01  
#> 137 2015      1940t2020i01  
#> 138 2016      1940t2020i01  
#> 139 2017      1940t2020i01  
#> 140 2018      1940t2020i01  
#> 141 2019      1940t2020i01  
#> 142 2020      1940t2020i01

We review all unique values in variables. We get all unique “variable” values, drop enroll_ratio

ar_st_vars <- unique(ppts_wrk %>% pull(variable))
ar_year_bins_type <- unique(ppts_wrk %>% pull(year_bins_type))
print(ar_st_vars)
#> [1] gdp      student  teacher  youthpop school  
#> Levels: gdp school student teacher youthpop
print(ar_year_bins_type)
#> [1] 1920t2020i05 1920t2020i10 1920t2020i20 1925t2015i15 1940t2020i01
#> Levels: 1920t2020i05 1920t2020i10 1920t2020i20 1925t2015i15 1940t2020i01

Conduct some basic sorting and other common operations on the file.

ppts_wrk <- ppts_wrk %>%
  arrange(location_level, location_code, year_bins)
# %>%
# filter(!(location_level %in% c("province", "multiprovince")))

Implement FLR file

For the FLR file, we proceed as beolow. This is functionalized in [PrjCompPPTS::ff_ppts_lrce_flr()].

First, start with long file, keep all locations and location types, select a subst of years, select teachers, schools, students, youthpop so different ratios can be constructed, and levels we want kept

df_ysts <- ppts_wrk %>%
  filter(variable %in% c(
    "youthpop", "student",
    "teacher", "school"
  )) %>%
  filter(year_bins_type == "1940t2020i01") %>%
  mutate(year_bins = as.numeric(year_bins)) %>%
  filter(year_bins %in% c(1960, 1980, 1990, 2000, 2010, 2020))
# review years
print(unique(df_ysts %>% pull(year_bins)))
#> [1] 1960 1980 1990 2000 2010 2020

Second, vars kept from long to wide: unit of obs: locType x loc x time

df_ysts_wide <- df_ysts %>%
  pivot_wider(
    id_cols = c("location_code", "location_level", "year_bins"),
    names_from = variable,
    names_prefix = "var_lvl_",
    names_sep = "_",
    values_from = c(value_interp1)
  )
print(glue::glue("dim of youth wide file: {dim(df_ysts_wide)}"))
#> dim of youth wide file: 1616
#> dim of youth wide file: 7

Third, RATIO/LEVELS: Compute key ratios within time periods, year level/ratio stats done:

Teacher over student: var_rat_t2s
Teacher over youthpop: var_rat_t2y
School over student: var_rat_s2s
School over youthpop: var_rat_sty

df_flr <- df_ysts_wide %>%
  mutate(
    var_rat_y2t = var_lvl_youthpop / var_lvl_teacher,
    var_rat_s2t = var_lvl_student / var_lvl_teacher,
    var_rat_y2s = var_lvl_youthpop / var_lvl_school,
    var_rat_s2s = var_lvl_student / var_lvl_school
  )
print(colnames(df_flr))
#>  [1] "location_code"    "location_level"   "year_bins"        "var_lvl_youthpop"
#>  [5] "var_lvl_student"  "var_lvl_teacher"  "var_lvl_school"   "var_rat_y2t"     
#>  [9] "var_rat_s2t"      "var_rat_y2s"      "var_rat_s2s"
print(glue::glue("dim of youth wide ratio file: {dim(df_flr)}"))
#> dim of youth wide ratio file: 1616
#> dim of youth wide ratio file: 11

Review output.

kable(df_flr[1:300,], caption="FLR")

FLR
location_code	location_level	year_bins	var_lvl_youthpop	var_lvl_student	var_lvl_teacher	var_lvl_school	var_rat_y2t	var_rat_s2t	var_rat_y2s	var_rat_s2s
ABW	country	1960	23769	NA	NA	NA	NA	NA	NA	NA
ABW	country	1980	15934	NA	NA	NA	NA	NA	NA	NA
ABW	country	1990	15257	NA	NA	NA	NA	NA	NA	NA
ABW	country	2000	21062	9.263000e+03	486.0000	NA	43.33745	19.059671	NA	NA
ABW	country	2010	21221	9.858000e+03	586.0000	NA	36.21331	16.822526	NA	NA
ABW	country	2020	18558	NA	NA	NA	NA	NA	NA	NA
AFG	country	1960	3791398	NA	NA	NA	NA	NA	NA	NA
AFG	country	1980	6167998	9.595830e+05	19322.0360	NA	319.22091	49.662624	NA	NA
AFG	country	1990	5996166	6.225130e+05	15106.0000	NA	396.93936	41.209652	NA	NA
AFG	country	2000	10160022	7.493600e+05	32367.5553	NA	313.89525	23.151579	NA	NA
AFG	country	2010	14061038	5.279326e+06	118858.0000	NA	118.30115	44.417086	NA	NA
AFG	country	2020	16280845	7.018950e+06	137376.2272	NA	118.51283	51.092903	NA	NA
AGO	country	1960	2298278	NA	NA	NA	NA	NA	NA	NA
AGO	country	1980	3846099	1.420839e+06	32700.8247	NA	117.61474	43.449638	NA	NA
AGO	country	1990	5635397	1.041126e+06	31504.3503	NA	178.87679	33.047055	NA	NA
AGO	country	2000	7738638	1.666859e+06	40080.8122	NA	193.07588	41.587457	NA	NA
AGO	country	2010	10987155	4.273006e+06	93734.0000	NA	117.21632	45.586511	NA	NA
AGO	country	2020	15248424	6.463250e+06	50712.6412	NA	300.68290	127.448500	NA	NA
ALB	country	1960	646025	NA	NA	NA	NA	NA	NA	NA
ALB	country	1980	961426	2.722770e+05	NA	NA	NA	NA	NA	NA
ALB	country	1990	1077154	2.784460e+05	NA	NA	NA	NA	NA	NA
ALB	country	2000	937016	2.832490e+05	12551.0000	NA	74.65668	22.567843	NA	NA
ALB	country	2010	654121	2.247810e+05	11409.0000	NA	57.33377	19.702077	NA	NA
ALB	country	2020	489128	1.621700e+05	9668.0000	NA	50.59247	16.773893	NA	NA
AND	country	1980	NA	2.908487e+03	251.7682	NA	NA	11.552243	NA	NA
AND	country	1990	NA	3.681188e+03	343.2481	NA	NA	10.724568	NA	NA
AND	country	2000	NA	4.033574e+03	327.1314	NA	NA	12.330135	NA	NA
AND	country	2010	NA	4.367000e+03	453.0000	NA	NA	9.640177	NA	NA
AND	country	2020	NA	4.246000e+03	411.0000	NA	NA	10.330900	NA	NA
ARE	country	1960	41184	NA	NA	NA	NA	NA	NA	NA
ARE	country	1980	286609	8.047000e+04	4949.0000	NA	57.91251	16.259850	NA	NA
ARE	country	1990	567999	2.155320e+05	11921.0000	NA	47.64693	18.080027	NA	NA
ARE	country	2000	816214	2.731440e+05	16916.0000	NA	48.25100	16.147080	NA	NA
ARE	country	2010	1124863	3.265880e+05	19401.0000	NA	57.97964	16.833565	NA	NA
ARE	country	2020	1465172	4.623330e+05	24646.0000	NA	59.44867	18.758947	NA	NA
ARG	country	1960	6359619	NA	NA	NA	NA	NA	NA	NA
ARG	country	1980	8485078	3.917449e+06	193640.0000	NA	43.81883	20.230577	NA	NA
ARG	country	1990	10041981	4.965396e+06	271035.5882	NA	37.05041	18.320089	NA	NA
ARG	country	2000	10494238	4.900956e+06	244412.0000	NA	42.93667	20.052027	NA	NA
ARG	country	2010	10619665	4.947105e+06	262899.9195	NA	40.39433	18.817446	NA	NA
ARG	country	2020	11087953	4.824506e+06	NA	NA	NA	NA	NA	NA
ARM	country	1960	724437	NA	NA	NA	NA	NA	NA	NA
ARM	country	1980	938303	NA	NA	NA	NA	NA	NA	NA
ARM	country	1990	1063000	2.287273e+05	12440.8129	NA	85.44458	18.385241	NA	NA
ARM	country	2000	792297	1.803060e+05	11747.9665	NA	67.44120	15.347848	NA	NA
ARM	country	2010	559945	1.018190e+05	7386.7351	NA	75.80413	13.784033	NA	NA
ARM	country	2020	617311	1.549050e+05	8066.0000	NA	76.53248	19.204686	NA	NA
ASM	country	1980	NA	6.521841e+03	358.5114	NA	NA	18.191448	NA	NA
ASM	country	1990	NA	8.574000e+03	461.0000	NA	NA	18.598699	NA	NA
ATG	country	1960	23267	NA	NA	NA	NA	NA	NA	NA
ATG	country	1980	23489	9.899027e+03	400.8789	NA	58.59376	24.693311	NA	NA
ATG	country	1990	19252	9.782756e+03	527.8360	NA	36.47345	18.533704	NA	NA
ATG	country	2000	21808	1.302500e+04	695.0000	NA	31.37842	18.741007	NA	NA
ATG	country	2010	21426	1.125400e+04	747.0000	NA	28.68273	15.065596	NA	NA
ATG	country	2020	21398	1.048651e+04	798.2935	NA	26.80468	13.136154	NA	NA
AUS	country	1960	3101573	NA	NA	NA	NA	NA	NA	NA
AUS	country	1980	3717172	1.718352e+06	91026.2921	NA	40.83625	18.877535	NA	NA
AUS	country	1990	3769581	1.583024e+06	94778.8309	NA	39.77239	16.702295	NA	NA
AUS	country	2000	3999611	1.905951e+06	106342.1695	NA	37.61077	17.922815	NA	NA
AUS	country	2010	4193157	2.015017e+06	NA	NA	NA	NA	NA	NA
AUS	country	2020	4956854	2.280007e+06	NA	NA	NA	NA	NA	NA
AUT	country	1960	1566864	5.161100e+05	21499.0000	4393.00	72.88079	24.006233	356.6729	117.48463
AUT	country	1980	1549231	4.013960e+05	27525.0000	3450.00	56.28451	14.582961	449.0525	116.34667
AUT	country	1990	1299884	3.719710e+05	29404.0000	3386.00	44.20773	12.650354	383.8996	109.85558
AUT	country	2000	1348118	3.935860e+05	33853.0000	3360.00	39.82270	11.626326	401.2256	117.13869
AUT	country	2010	1230814	3.276630e+05	32605.0000	3171.00	37.74924	10.049471	388.1470	103.33113
AUT	country	2020	1285114	3.475210e+05	37296.0000	3014.00	34.45715	9.317916	426.3816	115.30226
AZE	country	1960	1539915	NA	NA	NA	NA	NA	NA	NA
AZE	country	1980	2146219	4.704598e+05	NA	NA	NA	NA	NA	NA
AZE	country	1990	2382349	5.035980e+05	25656.5572	NA	92.85537	19.628432	NA	NA
AZE	country	2000	2506956	7.001360e+05	37469.0000	NA	66.90747	18.685740	NA	NA
AZE	country	2010	2067587	4.815510e+05	43610.0000	NA	47.41085	11.042215	NA	NA
AZE	country	2020	2373427	6.512580e+05	40160.0000	NA	59.09928	16.216584	NA	NA
BDI	country	1960	1226079	NA	NA	NA	NA	NA	NA	NA
BDI	country	1980	1857676	1.597290e+05	4623.0000	NA	401.83344	34.550941	NA	NA
BDI	country	1990	2605955	5.960880e+05	9049.0000	NA	287.98265	65.873356	NA	NA
BDI	country	2000	3194025	7.047850e+05	12731.0000	NA	250.88563	55.359752	NA	NA
BDI	country	2010	3916196	1.849861e+06	36557.0000	NA	107.12575	50.602101	NA	NA
BDI	country	2020	5380807	2.256960e+06	51732.6584	NA	104.01180	43.627372	NA	NA
BEL	country	1960	2152022	NA	NA	NA	NA	NA	NA	NA
BEL	country	1980	1985822	8.617460e+05	44212.0000	NA	44.91591	19.491224	NA	NA
BEL	country	1990	1786760	7.228110e+05	52543.7597	NA	34.00518	13.756362	NA	NA
BEL	country	2000	1800715	7.737420e+05	62644.0299	NA	28.74520	12.351408	NA	NA
BEL	country	2010	1839474	7.317610e+05	66317.0000	NA	27.73759	11.034290	NA	NA
BEL	country	2020	1966443	8.249863e+05	74698.4332	NA	26.32509	11.044225	NA	NA
BEN	country	1960	936951	NA	NA	NA	NA	NA	NA	NA
BEN	country	1980	1660673	3.573480e+05	6547.0000	NA	253.65404	54.581946	NA	NA
BEN	country	1990	2279693	4.182720e+05	13693.0000	NA	166.48601	30.546411	NA	NA
BEN	country	2000	3099203	9.324240e+05	17710.0000	NA	174.99735	52.649577	NA	NA
BEN	country	2010	4033506	1.787940e+06	38540.0000	NA	104.65765	46.391801	NA	NA
BEN	country	2020	5085024	2.182724e+06	57002.0000	NA	89.20782	38.292060	NA	NA
BFA	country	1960	1995469	NA	NA	NA	NA	NA	NA	NA
BFA	country	1980	3109926	1.848290e+05	3490.0000	NA	891.09628	52.959599	NA	NA
BFA	country	1990	4163498	4.729790e+05	8572.0000	NA	485.70905	55.177205	NA	NA
BFA	country	2000	5429021	8.521600e+05	17435.0000	NA	311.38635	48.876398	NA	NA
BFA	country	2010	7213252	2.047630e+06	39077.0000	NA	184.59073	52.399877	NA	NA
BFA	country	2020	9274847	3.240347e+06	87304.0000	NA	106.23622	37.115676	NA	NA
BGD	country	1960	20191455	NA	NA	NA	NA	NA	NA	NA
BGD	country	1980	35606527	8.240169e+06	153859.0000	NA	231.42310	53.556627	NA	NA
BGD	country	1990	43429145	1.193995e+07	189508.0000	NA	229.16787	63.004987	NA	NA
BGD	country	2000	47178540	1.464509e+07	282439.6897	NA	167.03934	51.852100	NA	NA
BGD	country	2010	47204866	1.698711e+07	395281.0000	NA	119.42103	42.974760	NA	NA
BGD	country	2020	44061889	1.760384e+07	582702.6042	NA	75.61643	30.210677	NA	NA
BGR	country	1960	2052880	NA	NA	NA	NA	NA	NA	NA
BGR	country	1980	1962711	5.212790e+05	NA	NA	NA	NA	NA	NA
BGR	country	1990	1773939	4.788870e+05	NA	NA	NA	NA	NA	NA
BGR	country	2000	1279448	3.928760e+05	23344.0000	NA	54.80843	16.829849	NA	NA
BGR	country	2010	998134	2.603400e+05	14885.0000	NA	67.05637	17.490091	NA	NA
BGR	country	2020	1017877	2.511105e+05	22219.3094	NA	45.81047	11.301454	NA	NA
BHR	country	1960	67072	NA	NA	NA	NA	NA	NA	NA
BHR	country	1980	124427	4.867200e+04	2479.0000	NA	50.19242	19.633723	NA	NA
BHR	country	1990	162120	6.400000e+04	3059.0000	NA	52.99771	20.921870	NA	NA
BHR	country	2000	200319	7.772000e+04	4505.6752	NA	44.45926	17.249357	NA	NA
BHR	country	2010	252039	9.236493e+04	7315.6874	NA	34.45185	12.625598	NA	NA
BHR	country	2020	311089	1.177931e+05	9112.0000	NA	34.14058	12.927248	NA	NA
BHS	country	1960	46429	NA	NA	NA	NA	NA	NA	NA
BHS	country	1980	77862	3.184200e+04	1218.0000	NA	63.92611	26.142857	NA	NA
BHS	country	1990	83113	3.289900e+04	1671.4147	NA	49.72614	19.683326	NA	NA
BHS	country	2000	87348	3.390388e+04	2273.1308	NA	38.42630	14.915058	NA	NA
BHS	country	2010	95420	3.397700e+04	2402.0000	NA	39.72523	14.145296	NA	NA
BHS	country	2020	84947	2.839622e+04	1443.7632	NA	58.83721	19.668196	NA	NA
BIH	country	1960	1225443	NA	NA	NA	NA	NA	NA	NA
BIH	country	1980	1201151	NA	NA	NA	NA	NA	NA	NA
BIH	country	1990	1078368	NA	NA	NA	NA	NA	NA	NA
BIH	country	2000	776939	NA	NA	NA	NA	NA	NA	NA
BIH	country	2010	583133	1.752710e+05	9303.8845	NA	62.67629	18.838476	NA	NA
BIH	country	2020	476455	1.523330e+05	9443.0000	NA	50.45589	16.131844	NA	NA
BLR	country	1960	2369415	NA	NA	NA	NA	NA	NA	NA
BLR	country	1980	2197454	7.331000e+05	NA	NA	NA	NA	NA	NA
BLR	country	1990	2336436	8.680000e+05	27858.2429	NA	83.86875	31.157744	NA	NA
BLR	country	2000	1848790	5.997320e+05	32940.0000	NA	56.12599	18.206800	NA	NA
BLR	country	2010	1412685	3.577960e+05	23907.0000	NA	59.09085	14.966161	NA	NA
BLR	country	2020	1617137	4.374147e+05	21737.7061	NA	74.39318	20.122394	NA	NA
BLZ	country	1960	41686	NA	NA	NA	NA	NA	NA	NA
BLZ	country	1980	67102	2.804100e+04	NA	NA	NA	NA	NA	NA
BLZ	country	1990	81511	3.575400e+04	NA	NA	NA	NA	NA	NA
BLZ	country	2000	100758	4.478800e+04	1921.0000	NA	52.45081	23.314940	NA	NA
BLZ	country	2010	114838	5.265000e+04	2367.0000	NA	48.51627	22.243346	NA	NA
BLZ	country	2020	116103	4.944900e+04	2598.0000	NA	44.68938	19.033487	NA	NA
BMU	country	1980	NA	5.986000e+03	262.0000	NA	NA	22.847328	NA	NA
BMU	country	1990	NA	5.672995e+03	378.2420	NA	NA	14.998323	NA	NA
BMU	country	2000	NA	5.175416e+03	520.8715	NA	NA	9.936072	NA	NA
BMU	country	2010	NA	4.473000e+03	608.0000	NA	NA	7.356908	NA	NA
BMU	country	2020	NA	4.390206e+03	520.8518	NA	NA	8.428897	NA	NA
BOL	country	1960	1507690	NA	NA	NA	NA	NA	NA	NA
BOL	country	1980	2279052	8.569330e+05	NA	NA	NA	NA	NA	NA
BOL	country	1990	2728649	1.097661e+06	NA	NA	NA	NA	NA	NA
BOL	country	2000	3177025	1.461816e+06	59909.2940	NA	53.03059	24.400488	NA	NA
BOL	country	2010	3465712	1.444023e+06	76782.0733	NA	45.13699	18.806773	NA	NA
BOL	country	2020	3525599	1.394029e+06	76841.0418	NA	45.88172	18.141727	NA	NA
BRA	country	1960	31157132	NA	NA	NA	NA	NA	NA	NA
BRA	country	1980	46094176	1.608973e+07	556335.0327	NA	82.85327	28.920938	NA	NA
BRA	country	1990	52387547	2.031224e+07	676660.7098	NA	77.42070	30.018353	NA	NA
BRA	country	2000	52329021	2.021151e+07	815079.0000	NA	64.20116	24.796990	NA	NA
BRA	country	2010	48582701	1.689349e+07	762132.0000	NA	63.74578	22.166095	NA	NA
BRA	country	2020	44019351	1.543299e+07	768375.3810	NA	57.28886	20.085224	NA	NA
BRB	country	1960	87977	NA	NA	NA	NA	NA	NA	NA
BRB	country	1980	75086	3.129900e+04	1315.1598	NA	57.09268	23.798629	NA	NA
BRB	country	1990	62692	2.851600e+04	1602.0000	NA	39.13358	17.800250	NA	NA
BRB	country	2000	59208	2.447500e+04	1393.0000	NA	42.50395	17.569993	NA	NA
BRB	country	2010	55701	2.265900e+04	1742.0000	NA	31.97532	13.007463	NA	NA
BRB	country	2020	48164	1.924200e+04	1476.0000	NA	32.63144	13.036585	NA	NA
BRN	country	1960	35551	NA	NA	NA	NA	NA	NA	NA
BRN	country	1980	75467	3.051300e+04	1671.0000	NA	45.16278	18.260323	NA	NA
BRN	country	1990	89629	3.939476e+04	2688.3463	NA	33.33983	14.653901	NA	NA
BRN	country	2000	102138	4.542800e+04	3324.0000	NA	30.72744	13.666667	NA	NA
BRN	country	2010	100886	4.421500e+04	3896.0000	NA	25.89476	11.348819	NA	NA
BRN	country	2020	97664	3.964900e+04	4258.0000	NA	22.93659	9.311649	NA	NA
BTN	country	1960	94002	NA	NA	NA	NA	NA	NA	NA
BTN	country	1980	177671	2.989900e+04	945.3473	NA	187.94257	31.627529	NA	NA
BTN	country	1990	230565	5.310188e+04	1709.4232	NA	134.87883	31.064211	NA	NA
BTN	country	2000	235302	8.509200e+04	2068.0000	NA	113.78240	41.147002	NA	NA
BTN	country	2010	213689	1.103690e+05	4262.0000	NA	50.13820	25.896058	NA	NA
BTN	country	2020	192089	9.416500e+04	2941.0000	NA	65.31418	32.018021	NA	NA
BWA	country	1960	219410	NA	NA	NA	NA	NA	NA	NA
BWA	country	1980	435482	1.719140e+05	5316.0000	NA	81.91911	32.338977	NA	NA
BWA	country	1990	578604	2.835160e+05	8956.0000	NA	64.60518	31.656543	NA	NA
BWA	country	2000	635233	3.242830e+05	12135.0000	NA	52.34718	26.722950	NA	NA
BWA	country	2010	694859	3.324515e+05	13407.9564	NA	51.82438	24.795090	NA	NA
BWA	country	2020	785530	3.648943e+05	11612.1785	NA	67.64708	31.423415	NA	NA
CAF	country	1960	570960	NA	NA	NA	NA	NA	NA	NA
CAF	country	1980	928400	2.434190e+05	4010.0000	NA	231.52120	60.702993	NA	NA
CAF	country	1990	1228797	3.236610e+05	3581.0000	NA	343.14354	90.382854	NA	NA
CAF	country	2000	1575406	4.337708e+05	4409.9475	NA	357.23918	98.361893	NA	NA
CAF	country	2010	1932637	6.368710e+05	7553.0000	NA	255.87674	84.320270	NA	NA
CAF	country	2020	2102963	9.998486e+05	11513.1893	NA	182.65686	86.843756	NA	NA
CAN	country	1960	6040212	NA	NA	NA	NA	NA	NA	NA
CAN	country	1980	5578695	2.205865e+06	143285.6387	NA	38.93408	15.394879	NA	NA
CAN	country	1990	5729961	2.345000e+06	149500.0000	NA	38.32750	15.685619	NA	NA
CAN	country	2000	5880513	2.456434e+06	141045.0000	NA	41.69246	17.415959	NA	NA
CAN	country	2010	5606922	2.168022e+06	NA	NA	NA	NA	NA	NA
CAN	country	2020	6000465	2.408472e+06	NA	NA	NA	NA	NA	NA
CHE	country	1960	1315049	5.730520e+05	17449.2007	NA	75.36442	32.841163	NA	NA
CHE	country	1980	1279347	4.404003e+05	25230.3099	NA	50.70675	17.455207	NA	NA
CHE	country	1990	1179241	4.111542e+05	30392.5974	NA	38.80027	13.528104	NA	NA
CHE	country	2000	1253186	4.737390e+05	36611.1231	NA	34.22965	12.939756	NA	NA
CHE	country	2010	1178302	4.360730e+05	44102.0000	4527.00	26.71765	9.887828	260.2832	96.32715
CHE	country	2020	1291911	5.302300e+05	54777.0000	4610.00	23.58492	9.679793	280.2410	115.01735
CHI	country	1960	23546	NA	NA	NA	NA	NA	NA	NA
CHI	country	1980	23439	NA	NA	NA	NA	NA	NA	NA
CHI	country	1990	22684	NA	NA	NA	NA	NA	NA	NA
CHI	country	2000	25306	NA	NA	NA	NA	NA	NA	NA
CHI	country	2010	24827	NA	NA	NA	NA	NA	NA	NA
CHI	country	2020	26034	NA	NA	NA	NA	NA	NA	NA
CHL	country	1960	3208362	NA	NA	NA	NA	NA	NA	NA
CHL	country	1980	3823972	1.754075e+06	NA	NA	NA	NA	NA	NA
CHL	country	1990	3998236	1.593486e+06	NA	NA	NA	NA	NA	NA
CHL	country	2000	4193301	1.798515e+06	55808.0000	NA	75.13799	32.226831	NA	NA
CHL	country	2010	3767708	1.546543e+06	66059.0000	NA	57.03550	23.411541	NA	NA
CHL	country	2020	3677716	1.565850e+06	95462.7332	NA	38.52515	16.402735	NA	NA
CHN	country	1960	265641893	9.379100e+07	2693000.0000	726484.00	98.64162	34.827701	365.6542	129.10264
CHN	country	1980	352611901	1.462700e+08	5499000.0000	917316.00	64.12291	26.599382	384.3952	159.45432
CHN	country	1990	324546177	1.224140e+08	5582000.0000	766072.00	58.14156	21.930133	423.6497	159.79438
CHN	country	2000	312993544	1.301330e+08	5860000.0000	553622.00	53.41187	22.206997	565.3560	235.05749
CHN	country	2010	249615182	9.940700e+07	5617000.0000	257410.00	44.43923	17.697525	969.7183	386.18158
CHN	country	2020	249901204	1.072535e+08	6434200.0000	157979.00	38.83951	16.669283	1581.8634	678.90986
CIV	country	1960	1496544	NA	NA	NA	NA	NA	NA	NA
CIV	country	1980	3636087	9.541900e+05	24609.0000	NA	147.75436	38.774026	NA	NA
CIV	country	1990	5379225	1.405187e+06	38722.0000	NA	138.91909	36.289112	NA	NA
CIV	country	2000	7179531	1.943101e+06	43205.0000	NA	166.17361	44.973985	NA	NA
CIV	country	2010	8956696	2.563666e+06	56514.9682	NA	158.48361	45.362596	NA	NA
CIV	country	2020	10949219	4.101430e+06	101085.0000	NA	108.31695	40.574071	NA	NA
CMR	country	1960	2066923	NA	NA	NA	NA	NA	NA	NA
CMR	country	1980	3852220	1.302974e+06	25289.0000	NA	152.32789	51.523350	NA	NA
CMR	country	1990	5471853	1.946301e+06	37804.0000	NA	144.74270	51.483996	NA	NA
CMR	country	2000	6995203	2.237083e+06	41998.5829	NA	166.55807	53.265678	NA	NA
CMR	country	2010	8887234	3.510396e+06	76655.0000	NA	115.93809	45.794743	NA	NA
CMR	country	2020	11166234	4.607127e+06	99454.0307	NA	112.27533	46.324189	NA	NA
COD	country	1960	6612287	NA	NA	NA	NA	NA	NA	NA
COD	country	1980	11755475	4.054758e+06	99361.2797	NA	118.31042	40.808231	NA	NA
COD	country	1990	15617193	3.429633e+06	114365.0382	NA	136.55566	29.988474	NA	NA
COD	country	2000	21452139	4.452456e+06	156028.1009	NA	137.48895	28.536241	NA	NA
COD	country	2010	29790152	1.057242e+07	285640.0000	NA	104.29265	37.013100	NA	NA
COD	country	2020	41014814	1.920163e+07	652095.4320	NA	62.89695	29.446041	NA	NA
COG	country	1960	425386	NA	NA	NA	NA	NA	NA	NA
COG	country	1980	819733	3.830180e+05	6852.0000	NA	119.63412	55.898716	NA	NA
COG	country	1990	1051806	4.921430e+05	7639.0000	NA	137.68896	64.425056	NA	NA
COG	country	2000	1318699	4.187070e+05	6923.0000	NA	190.48086	60.480572	NA	NA
COG	country	2010	1779358	7.050930e+05	14347.0000	NA	124.02300	49.145675	NA	NA
COG	country	2020	2277331	8.004810e+05	33133.3199	NA	68.73235	24.159395	NA	NA
COL	country	1960	7497972	NA	NA	NA	NA	NA	NA	NA
COL	country	1980	10766636	4.168200e+06	136381.0000	NA	78.94528	30.562908	NA	NA
COL	country	1990	11931200	4.246658e+06	141936.0000	NA	84.06042	29.919527	NA	NA
COL	country	2000	12908990	5.221018e+06	197374.0000	NA	65.40370	26.452410	NA	NA
COL	country	2010	12331562	5.084972e+06	180760.0000	NA	68.22064	28.131069	NA	NA
COL	country	2020	11287640	4.224512e+06	184850.6967	NA	61.06355	22.853643	NA	NA
COM	country	1960	78957	NA	NA	NA	NA	NA	NA	NA
COM	country	1980	137879	5.460648e+04	1160.6850	NA	118.79106	47.046768	NA	NA
COM	country	1990	189111	6.782500e+04	1900.0000	NA	99.53211	35.697368	NA	NA
COM	country	2000	238510	9.342100e+04	2536.0000	NA	94.04968	36.837934	NA	NA
COM	country	2010	283080	1.147186e+05	4021.4341	NA	70.39280	28.526790	NA	NA
COM	country	2020	339315	1.298704e+05	2100.5643	NA	161.53516	61.826444	NA	NA
CPV	country	1960	85006	NA	NA	NA	NA	NA	NA	NA
CPV	country	1980	134286	5.811100e+04	1396.0000	NA	96.19341	41.626791	NA	NA
CPV	country	1990	155787	6.776100e+04	2028.0000	NA	76.81805	33.412722	NA	NA
CPV	country	2000	183960	9.163600e+04	3190.0000	NA	57.66771	28.726019	NA	NA
CPV	country	2010	159192	7.113400e+04	3009.0000	NA	52.90528	23.640412	NA	NA
CPV	country	2020	156130	6.110155e+04	3143.8216	NA	49.66249	19.435439	NA	NA
CRI	country	1960	603128	NA	NA	NA	NA	NA	NA	NA
CRI	country	1980	880420	3.486740e+05	12596.0000	NA	69.89679	27.681327	NA	NA
CRI	country	1990	1111065	4.352050e+05	13651.0000	NA	81.39074	31.880815	NA	NA
CRI	country	2000	1234692	5.514650e+05	22111.0000	NA	55.84062	24.940753	NA	NA
CRI	country	2010	1112649	5.206090e+05	29163.0000	NA	38.15276	17.851696	NA	NA
CRI	country	2020	1061003	4.927610e+05	43093.0000	NA	24.62124	11.434827	NA	NA
CUB	country	1960	2503849	NA	NA	NA	NA	NA	NA	NA
CUB	country	1980	3124091	1.550323e+06	86519.0000	NA	36.10873	17.918873	NA	NA
CUB	country	1990	2464759	8.855760e+05	71887.0000	NA	34.28657	12.319001	NA	NA
CUB	country	2000	2401518	1.045578e+06	90920.0000	NA	26.41353	11.499978	NA	NA
CUB	country	2010	1991584	8.527440e+05	93414.0000	NA	21.31997	9.128653	NA	NA
CUB	country	2020	1803279	7.598030e+05	84629.0000	NA	21.30805	8.978045	NA	NA
CUW	country	1960	51456	NA	NA	NA	NA	NA	NA	NA
CUW	country	1980	45907	NA	NA	NA	NA	NA	NA	NA
CUW	country	1990	39609	NA	NA	NA	NA	NA	NA	NA
CUW	country	2000	33363	NA	NA	NA	NA	NA	NA	NA
CUW	country	2010	30796	2.552826e+04	NA	NA	NA	NA	NA	NA
CUW	country	2020	28165	1.292200e+04	NA	NA	NA	NA	NA	NA
CYM	country	1980	NA	2.109000e+03	112.0000	NA	NA	18.830357	NA	NA
CYM	country	1990	NA	2.619048e+03	155.5292	NA	NA	16.839595	NA	NA
CYM	country	2000	NA	3.435000e+03	237.0000	NA	NA	14.493671	NA	NA
CYM	country	2010	NA	3.900209e+03	322.8460	NA	NA	12.080708	NA	NA
CYM	country	2020	NA	4.534000e+03	347.0000	NA	NA	13.066282	NA	NA
CYP	country	1960	210309	NA	NA	NA	NA	NA	NA	NA
CYP	country	1980	171294	5.057900e+04	2200.0000	NA	77.86091	22.990454	NA	NA
CYP	country	1990	195411	6.084100e+04	2846.0000	NA	68.66163	21.377723	NA	NA
CYP	country	2000	211296	6.395200e+04	3608.0000	NA	58.56319	17.725055	NA	NA
CYP	country	2010	198453	5.480600e+04	3985.0000	NA	49.80000	13.753074	NA	NA
CYP	country	2020	200146	5.990104e+04	5356.0320	NA	37.36834	11.183848	NA	NA
CZE	country	1960	2471190	NA	NA	NA	NA	NA	NA	NA
CZE	country	1980	2411901	6.729224e+05	22879.3838	NA	105.41809	29.411736	NA	NA
CZE	country	1990	2227371	5.667620e+05	23145.0000	NA	96.23552	24.487449	NA	NA
CZE	country	2000	1684165	6.449560e+05	38196.0000	NA	44.09271	16.885433	NA	NA
CZE	country	2010	1491710	4.633570e+05	24769.0000	NA	60.22488	18.707134	NA	NA
CZE	country	2020	1685507	5.801289e+05	NA	NA	NA	NA	NA	NA
DEU	country	1990	12768494	NA	181026.5562	18001.15	70.53382	NA	709.3154	NA
DEU	country	2000	12884644	3.352935e+06	215437.0000	17275.00	59.80702	15.563413	745.8549	194.09175
DEU	country	2010	11095807	2.837737e+06	228438.0000	16290.00	48.57251	12.422351	681.1422	174.20117
DEU	country	2020	11605595	2.842302e+06	237828.0000	15447.00	48.79827	11.951082	751.3171	184.00350
DJI	country	1960	36262	NA	NA	NA	NA	NA	NA	NA
DJI	country	1980	166794	1.522700e+04	360.0000	NA	463.31667	42.297222	NA	NA
DJI	country	1990	265743	3.137800e+04	711.0000	NA	373.75949	44.132208	NA	NA

Implement FPC file

Step 2, we will generate the FPC file. This is functionalized in [PrjCompPPTS::ff_ppts_lrce_fpc()].

First, from levels/ratios file (keep ranks), variables are levels and ratios, convert all vars to long. unit of obs: locType x loc x time x var(level/change).

df_ysts_longer <- df_flr %>%
  pivot_longer(
    cols = matches("var"),
    names_to = c("vartype", "variable"),
    names_pattern = paste0("var_(.*)_(.*)"),
    values_to = "stat"
  ) %>%
  drop_na(stat)
print(glue::glue("dim of youth wide ratio file: {dim(df_ysts_longer)}"))
#> dim of youth wide ratio file: 6644
#> dim of youth wide ratio file: 6

Second, generate ranks, grouped by locType x time x var(level/change). Ranking across locations.

df_ysts_longer_rank <- df_ysts_longer %>%
  group_by(location_level, variable, year_bins) %>%
  arrange(stat, ..by_group = TRUE) %>%
  mutate(rank = row_number()) %>%
  arrange(location_level, variable, year_bins, location_code) %>%
  select(-stat, -vartype) %>%
  mutate(vartype = "rank") %>%
  rename(stat = rank)
print(glue::glue("dim of youth wide ratio file: {dim(df_ysts_longer_rank)}"))
#> dim of youth wide ratio file: 6644
#> dim of youth wide ratio file: 6

Third, select subperiods of interest, time from long to wide: unit of obs: locType x loc x var(level/change).

ar_it_years_chg <- c(1960, 1980, 2000, 2020)
df_ysts_longer_wide <- bind_rows(df_ysts_longer, df_ysts_longer_rank) %>%
  filter(year_bins %in% ar_it_years_chg) %>%
  pivot_wider(
    id_cols = c("location_code", "location_level", "vartype", "variable"),
    names_from = year_bins,
    names_prefix = "year",
    names_sep = "_",
    values_from = c(stat)
  )
print(glue::glue("dim of youth wide ratio file: {dim(df_ysts_longer_wide)}"))
#> dim of youth wide ratio file: 2728
#> dim of youth wide ratio file: 8

Fourth, compute stats ratios over time for level and change vars. 1980 to 2020 change, 80 to 00, 00 to 20.

df_fpc <- df_ysts_longer_wide %>%
  mutate(
    chg_80v60 = (year1980 - year1960) / year1960,
    chg_00v80 = (year2000 - year1980) / year1980,
    chg_20v00 = (year2020 - year2000) / year2000,
    chg_20v80 = (year2020 - year1980) / year1980
  )
print(glue::glue("dim FPC: {dim(df_fpc)}"))
#> dim FPC: 2728
#> dim FPC: 12

Review output.

kable(df_fpc[1:300,], caption="FPC")

FPC
location_code	location_level	vartype	variable	year1960	year1980	year2000	year2020	chg_80v60	chg_00v80	chg_20v00	chg_20v80
ABW	country	lvl	youthpop	2.376900e+04	1.593400e+04	2.106200e+04	1.855800e+04	-0.3296310	0.3218275	-0.1188871	0.1646793
ABW	country	lvl	student	NA	NA	9.263000e+03	NA	NA	NA	NA	NA
ABW	country	lvl	teacher	NA	NA	4.860000e+02	NA	NA	NA	NA	NA
ABW	country	rat	y2t	NA	NA	4.333745e+01	NA	NA	NA	NA	NA
ABW	country	rat	s2t	NA	NA	1.905967e+01	NA	NA	NA	NA	NA
AFG	country	lvl	youthpop	3.791398e+06	6.167998e+06	1.016002e+07	1.628084e+07	0.6268400	0.6472155	0.6024419	1.6395672
AFG	country	lvl	student	NA	9.595830e+05	7.493600e+05	7.018950e+06	NA	-0.2190775	8.3665931	6.3145838
AFG	country	lvl	teacher	NA	1.932204e+04	3.236756e+04	1.373762e+05	NA	0.6751628	3.2442571	6.1098215
AFG	country	rat	y2t	NA	3.192209e+02	3.138953e+02	1.185128e+02	NA	-0.0166833	-0.6224447	-0.6287435
AFG	country	rat	s2t	NA	4.966262e+01	2.315158e+01	5.109290e+01	NA	-0.5338229	1.2068864	0.0287999
AGO	country	lvl	youthpop	2.298278e+06	3.846099e+06	7.738638e+06	1.524842e+07	0.6734699	1.0120746	0.9704274	2.9646468
AGO	country	lvl	student	NA	1.420839e+06	1.666859e+06	6.463250e+06	NA	0.1731513	2.8775024	3.5488968
AGO	country	lvl	teacher	NA	3.270082e+04	4.008081e+04	5.071264e+04	NA	0.2256820	0.2652598	0.5508062
AGO	country	rat	y2t	NA	1.176147e+02	1.930759e+02	3.006829e+02	NA	0.6415959	0.5573302	1.5565069
AGO	country	rat	s2t	NA	4.344964e+01	4.158746e+01	1.274485e+02	NA	-0.0428584	2.0645899	1.9332465
ALB	country	lvl	youthpop	6.460250e+05	9.614260e+05	9.370160e+05	4.891280e+05	0.4882179	-0.0253894	-0.4779940	-0.4912474
ALB	country	lvl	student	NA	2.722770e+05	2.832490e+05	1.621700e+05	NA	0.0402972	-0.4274649	-0.4043933
ALB	country	lvl	teacher	NA	NA	1.255100e+04	9.668000e+03	NA	NA	-0.2297028	NA
ALB	country	rat	y2t	NA	NA	7.465668e+01	5.059247e+01	NA	NA	-0.3223316	NA
ALB	country	rat	s2t	NA	NA	2.256784e+01	1.677389e+01	NA	NA	-0.2567348	NA
AND	country	lvl	student	NA	2.908487e+03	4.033574e+03	4.246000e+03	NA	0.3868289	0.0526645	0.4598655
AND	country	lvl	teacher	NA	2.517682e+02	3.271314e+02	4.110000e+02	NA	0.2993356	0.2563760	0.6324541
AND	country	rat	s2t	NA	1.155224e+01	1.233013e+01	1.033090e+01	NA	0.0673369	-0.1621421	-0.1057234
ARE	country	lvl	youthpop	4.118400e+04	2.866090e+05	8.162140e+05	1.465172e+06	5.9592317	1.8478310	0.7950832	4.1120935
ARE	country	lvl	student	NA	8.047000e+04	2.731440e+05	4.623330e+05	NA	2.3943581	0.6926347	4.7454082
ARE	country	lvl	teacher	NA	4.949000e+03	1.691600e+04	2.464600e+04	NA	2.4180643	0.4569638	3.9799960
ARE	country	rat	y2t	NA	5.791251e+01	4.825100e+01	5.944867e+01	NA	-0.1668293	0.2320712	0.0265256
ARE	country	rat	s2t	NA	1.625985e+01	1.614708e+01	1.875895e+01	NA	-0.0069355	0.1617548	0.1536974
ARG	country	lvl	youthpop	6.359619e+06	8.485078e+06	1.049424e+07	1.108795e+07	0.3342117	0.2367875	0.0565753	0.3067591
ARG	country	lvl	student	NA	3.917449e+06	4.900956e+06	4.824506e+06	NA	0.2510580	-0.0155989	0.2315428
ARG	country	lvl	teacher	NA	1.936400e+05	2.444120e+05	NA	NA	0.2621979	NA	NA
ARG	country	rat	y2t	NA	4.381883e+01	4.293667e+01	NA	NA	-0.0201319	NA	NA
ARG	country	rat	s2t	NA	2.023058e+01	2.005203e+01	NA	NA	-0.0088258	NA	NA
ARM	country	lvl	youthpop	7.244370e+05	9.383030e+05	7.922970e+05	6.173110e+05	0.2952168	-0.1556065	-0.2208591	-0.3420984
ARM	country	lvl	student	NA	NA	1.803060e+05	1.549050e+05	NA	NA	-0.1408772	NA
ARM	country	lvl	teacher	NA	NA	1.174797e+04	8.066000e+03	NA	NA	-0.3134131	NA
ARM	country	rat	y2t	NA	NA	6.744120e+01	7.653248e+01	NA	NA	0.1348030	NA
ARM	country	rat	s2t	NA	NA	1.534785e+01	1.920469e+01	NA	NA	0.2512951	NA
ASM	country	lvl	student	NA	6.521841e+03	NA	NA	NA	NA	NA	NA
ASM	country	lvl	teacher	NA	3.585114e+02	NA	NA	NA	NA	NA	NA
ASM	country	rat	s2t	NA	1.819145e+01	NA	NA	NA	NA	NA	NA
ATG	country	lvl	youthpop	2.326700e+04	2.348900e+04	2.180800e+04	2.139800e+04	0.0095414	-0.0715654	-0.0188004	-0.0890204
ATG	country	lvl	student	NA	9.899027e+03	1.302500e+04	1.048651e+04	NA	0.3157859	-0.1948940	0.0593471
ATG	country	lvl	teacher	NA	4.008789e+02	6.950000e+02	7.982935e+02	NA	0.7336907	0.1486237	0.9913582
ATG	country	rat	y2t	NA	5.859376e+01	3.137842e+01	2.680468e+01	NA	-0.4644751	-0.1457607	-0.5425335
ATG	country	rat	s2t	NA	2.469331e+01	1.874101e+01	1.313615e+01	NA	-0.2410492	-0.2990690	-0.4680278
AUS	country	lvl	youthpop	3.101573e+06	3.717172e+06	3.999611e+06	4.956854e+06	0.1984796	0.0759822	0.2393340	0.3335014
AUS	country	lvl	student	NA	1.718352e+06	1.905951e+06	2.280007e+06	NA	0.1091738	0.1962569	0.3268568
AUS	country	lvl	teacher	NA	9.102629e+04	1.063422e+05	NA	NA	0.1682577	NA	NA
AUS	country	rat	y2t	NA	4.083625e+01	3.761077e+01	NA	NA	-0.0789856	NA	NA
AUS	country	rat	s2t	NA	1.887753e+01	1.792281e+01	NA	NA	-0.0505744	NA	NA
AUT	country	lvl	youthpop	1.566864e+06	1.549231e+06	1.348118e+06	1.285114e+06	-0.0112537	-0.1298147	-0.0467348	-0.1704826
AUT	country	lvl	student	5.161100e+05	4.013960e+05	3.935860e+05	3.475210e+05	-0.2222666	-0.0194571	-0.1170392	-0.1342191
AUT	country	lvl	teacher	2.149900e+04	2.752500e+04	3.385300e+04	3.729600e+04	0.2802921	0.2299001	0.1017044	0.3549864
AUT	country	lvl	school	4.393000e+03	3.450000e+03	3.360000e+03	3.014000e+03	-0.2146597	-0.0260870	-0.1029762	-0.1263768
AUT	country	rat	y2t	7.288079e+01	5.628451e+01	3.982270e+01	3.445715e+01	-0.2277182	-0.2924748	-0.1347360	-0.3878039
AUT	country	rat	s2t	2.400623e+01	1.458296e+01	1.162633e+01	9.317916e+00	-0.3925344	-0.2027459	-0.1985502	-0.3610409
AUT	country	rat	y2s	3.566729e+02	4.490525e+02	4.012256e+02	4.263816e+02	0.2590036	-0.1065062	0.0626978	-0.0504861
AUT	country	rat	s2s	1.174846e+02	1.163467e+02	1.171387e+02	1.153023e+02	-0.0096861	0.0068074	-0.0156774	-0.0089767
AZE	country	lvl	youthpop	1.539915e+06	2.146219e+06	2.506956e+06	2.373427e+06	0.3937256	0.1680802	-0.0532634	0.1058643
AZE	country	lvl	student	NA	4.704598e+05	7.001360e+05	6.512580e+05	NA	0.4881952	-0.0698122	0.3843011
AZE	country	lvl	teacher	NA	NA	3.746900e+04	4.016000e+04	NA	NA	0.0718194	NA
AZE	country	rat	y2t	NA	NA	6.690747e+01	5.909928e+01	NA	NA	-0.1167014	NA
AZE	country	rat	s2t	NA	NA	1.868574e+01	1.621658e+01	NA	NA	-0.1321412	NA
BDI	country	lvl	youthpop	1.226079e+06	1.857676e+06	3.194025e+06	5.380807e+06	0.5151356	0.7193660	0.6846477	1.8965261
BDI	country	lvl	student	NA	1.597290e+05	7.047850e+05	2.256960e+06	NA	3.4123797	2.2023382	13.1299322
BDI	country	lvl	teacher	NA	4.623000e+03	1.273100e+04	5.173266e+04	NA	1.7538395	3.0635188	10.1902787
BDI	country	rat	y2t	NA	4.018334e+02	2.508856e+02	1.040118e+02	NA	-0.3756477	-0.5854215	-0.7411569
BDI	country	rat	s2t	NA	3.455094e+01	5.535975e+01	4.362737e+01	NA	0.6022647	-0.2119298	0.2626971
BEL	country	lvl	youthpop	2.152022e+06	1.985822e+06	1.800715e+06	1.966443e+06	-0.0772297	-0.0932143	0.0920346	-0.0097587
BEL	country	lvl	student	NA	8.617460e+05	7.737420e+05	8.249863e+05	NA	-0.1021229	0.0662291	-0.0426573
BEL	country	lvl	teacher	NA	4.421200e+04	6.264403e+04	7.469843e+04	NA	0.4169011	0.1924270	0.6895511
BEL	country	rat	y2t	NA	4.491591e+01	2.874520e+01	2.632509e+01	NA	-0.3600219	-0.0841917	-0.4139027
BEL	country	rat	s2t	NA	1.949122e+01	1.235141e+01	1.104422e+01	NA	-0.3663092	-0.1058328	-0.4333745
BEN	country	lvl	youthpop	9.369510e+05	1.660673e+06	3.099203e+06	5.085024e+06	0.7724225	0.8662331	0.6407522	2.0620261
BEN	country	lvl	student	NA	3.573480e+05	9.324240e+05	2.182724e+06	NA	1.6092884	1.3409136	5.1081187
BEN	country	lvl	teacher	NA	6.547000e+03	1.771000e+04	5.700200e+04	NA	1.7050558	2.2186335	7.7065832
BEN	country	rat	y2t	NA	2.536540e+02	1.749973e+02	8.920782e+01	NA	-0.3100944	-0.4902333	-0.6483091
BEN	country	rat	s2t	NA	5.458195e+01	5.264958e+01	3.829206e+01	NA	-0.0354031	-0.2726996	-0.2984482
BFA	country	lvl	youthpop	1.995469e+06	3.109926e+06	5.429021e+06	9.274847e+06	0.5584938	0.7457075	0.7083830	1.9823369
BFA	country	lvl	student	NA	1.848290e+05	8.521600e+05	3.240347e+06	NA	3.6105319	2.8025101	16.5315941
BFA	country	lvl	teacher	NA	3.490000e+03	1.743500e+04	8.730400e+04	NA	3.9957020	4.0073989	24.0154728
BFA	country	rat	y2t	NA	8.910963e+02	3.113863e+02	1.062362e+02	NA	-0.6505581	-0.6588283	-0.8807803
BFA	country	rat	s2t	NA	5.295960e+01	4.887640e+01	3.711568e+01	NA	-0.0771003	-0.2406217	-0.2991700
BGD	country	lvl	youthpop	2.019146e+07	3.560653e+07	4.717854e+07	4.406189e+07	0.7634453	0.3249970	-0.0660608	0.2374666
BGD	country	lvl	student	NA	8.240169e+06	1.464509e+07	1.760384e+07	NA	0.7772804	0.2020301	1.1363445
BGD	country	lvl	teacher	NA	1.538590e+05	2.824397e+05	5.827026e+05	NA	0.8357047	1.0631045	2.7872507
BGD	country	rat	y2t	NA	2.314231e+02	1.670393e+02	7.561643e+01	NA	-0.2782080	-0.5473137	-0.6732546
BGD	country	rat	s2t	NA	5.355663e+01	5.185210e+01	3.021068e+01	NA	-0.0318266	-0.4173683	-0.4359115
BGR	country	lvl	youthpop	2.052880e+06	1.962711e+06	1.279448e+06	1.017877e+06	-0.0439232	-0.3481221	-0.2044405	-0.4813923
BGR	country	lvl	student	NA	5.212790e+05	3.928760e+05	2.511105e+05	NA	-0.2463230	-0.3608403	-0.5182800
BGR	country	lvl	teacher	NA	NA	2.334400e+04	2.221931e+04	NA	NA	-0.0481790	NA
BGR	country	rat	y2t	NA	NA	5.480843e+01	4.581047e+01	NA	NA	-0.1641711	NA
BGR	country	rat	s2t	NA	NA	1.682985e+01	1.130145e+01	NA	NA	-0.3284875	NA
BHR	country	lvl	youthpop	6.707200e+04	1.244270e+05	2.003190e+05	3.110890e+05	0.8551258	0.6099319	0.5529680	1.5001728
BHR	country	lvl	student	NA	4.867200e+04	7.772000e+04	1.177931e+05	NA	0.5968113	0.5156084	1.4201406
BHR	country	lvl	teacher	NA	2.479000e+03	4.505675e+03	9.112000e+03	NA	0.8175374	1.0223384	2.6756757
BHR	country	rat	y2t	NA	5.019242e+01	4.445926e+01	3.414058e+01	NA	-0.1142235	-0.2320929	-0.3198059
BHR	country	rat	s2t	NA	1.963372e+01	1.724936e+01	1.292725e+01	NA	-0.1214424	-0.2505664	-0.3415794
BHS	country	lvl	youthpop	4.642900e+04	7.786200e+04	8.734800e+04	8.494700e+04	0.6770122	0.1218309	-0.0274878	0.0909943
BHS	country	lvl	student	NA	3.184200e+04	3.390388e+04	2.839622e+04	NA	0.0647534	-0.1624493	-0.1082150
BHS	country	lvl	teacher	NA	1.218000e+03	2.273131e+03	1.443763e+03	NA	0.8662815	-0.3648570	0.1853556
BHS	country	rat	y2t	NA	6.392611e+01	3.842630e+01	5.883721e+01	NA	-0.3988951	0.5311705	-0.0796059
BHS	country	rat	s2t	NA	2.614286e+01	1.491506e+01	1.966820e+01	NA	-0.4294786	0.3186805	-0.2476646
BIH	country	lvl	youthpop	1.225443e+06	1.201151e+06	7.769390e+05	4.764550e+05	-0.0198230	-0.3531712	-0.3867537	-0.6033346
BIH	country	lvl	student	NA	NA	NA	1.523330e+05	NA	NA	NA	NA
BIH	country	lvl	teacher	NA	NA	NA	9.443000e+03	NA	NA	NA	NA
BIH	country	rat	y2t	NA	NA	NA	5.045589e+01	NA	NA	NA	NA
BIH	country	rat	s2t	NA	NA	NA	1.613184e+01	NA	NA	NA	NA
BLR	country	lvl	youthpop	2.369415e+06	2.197454e+06	1.848790e+06	1.617137e+06	-0.0725753	-0.1586673	-0.1252998	-0.2640861
BLR	country	lvl	student	NA	7.331000e+05	5.997320e+05	4.374147e+05	NA	-0.1819233	-0.2706498	-0.4033356
BLR	country	lvl	teacher	NA	NA	3.294000e+04	2.173771e+04	NA	NA	-0.3400818	NA
BLR	country	rat	y2t	NA	NA	5.612599e+01	7.439318e+01	NA	NA	0.3254676	NA
BLR	country	rat	s2t	NA	NA	1.820680e+01	2.012239e+01	NA	NA	0.1052131	NA
BLZ	country	lvl	youthpop	4.168600e+04	6.710200e+04	1.007580e+05	1.161030e+05	0.6097011	0.5015648	0.1522956	0.7302465
BLZ	country	lvl	student	NA	2.804100e+04	4.478800e+04	4.944900e+04	NA	0.5972326	0.1040681	0.7634535
BLZ	country	lvl	teacher	NA	NA	1.921000e+03	2.598000e+03	NA	NA	0.3524206	NA
BLZ	country	rat	y2t	NA	NA	5.245081e+01	4.468938e+01	NA	NA	-0.1479754	NA
BLZ	country	rat	s2t	NA	NA	2.331494e+01	1.903349e+01	NA	NA	-0.1836356	NA
BMU	country	lvl	student	NA	5.986000e+03	5.175416e+03	4.390206e+03	NA	-0.1354132	-0.1517192	-0.2665877
BMU	country	lvl	teacher	NA	2.620000e+02	5.208715e+02	5.208518e+02	NA	0.9880590	-0.0000378	0.9879839
BMU	country	rat	s2t	NA	2.284733e+01	9.936072e+00	8.428897e+00	NA	-0.5651101	-0.1516872	-0.6310773
BOL	country	lvl	youthpop	1.507690e+06	2.279052e+06	3.177025e+06	3.525599e+06	0.5116184	0.3940116	0.1097171	0.5469586
BOL	country	lvl	student	NA	8.569330e+05	1.461816e+06	1.394029e+06	NA	0.7058697	-0.0463716	0.6267657
BOL	country	lvl	teacher	NA	NA	5.990929e+04	7.684104e+04	NA	NA	0.2826231	NA
BOL	country	rat	y2t	NA	NA	5.303059e+01	4.588172e+01	NA	NA	-0.1348065	NA
BOL	country	rat	s2t	NA	NA	2.440049e+01	1.814173e+01	NA	NA	-0.2565015	NA
BRA	country	lvl	youthpop	3.115713e+07	4.609418e+07	5.232902e+07	4.401935e+07	0.4794101	0.1352632	-0.1587966	-0.0450127
BRA	country	lvl	student	NA	1.608973e+07	2.021151e+07	1.543299e+07	NA	0.2561743	-0.2364255	-0.0408173
BRA	country	lvl	teacher	NA	5.563350e+05	8.150790e+05	7.683754e+05	NA	0.4650866	-0.0572995	0.3811379
BRA	country	rat	y2t	NA	8.285327e+01	6.420116e+01	5.728886e+01	NA	-0.2251221	-0.1076663	-0.3085504
BRA	country	rat	s2t	NA	2.892094e+01	2.479699e+01	2.008522e+01	NA	-0.1425938	-0.1900137	-0.3055127
BRB	country	lvl	youthpop	8.797700e+04	7.508600e+04	5.920800e+04	4.816400e+04	-0.1465269	-0.2114642	-0.1865288	-0.3585489
BRB	country	lvl	student	NA	3.129900e+04	2.447500e+04	1.924200e+04	NA	-0.2180261	-0.2138100	-0.3852200
BRB	country	lvl	teacher	NA	1.315160e+03	1.393000e+03	1.476000e+03	NA	0.0591869	0.0595836	0.1222971
BRB	country	rat	y2t	NA	5.709268e+01	4.250395e+01	3.263144e+01	NA	-0.2555272	-0.2322728	-0.4284480
BRB	country	rat	s2t	NA	2.379863e+01	1.756999e+01	1.303659e+01	NA	-0.2617225	-0.2580199	-0.4522128
BRN	country	lvl	youthpop	3.555100e+04	7.546700e+04	1.021380e+05	9.766400e+04	1.1227814	0.3534127	-0.0438035	0.2941286
BRN	country	lvl	student	NA	3.051300e+04	4.542800e+04	3.964900e+04	NA	0.4888080	-0.1272123	0.2994134
BRN	country	lvl	teacher	NA	1.671000e+03	3.324000e+03	4.258000e+03	NA	0.9892280	0.2809868	1.5481747
BRN	country	rat	y2t	NA	4.516278e+01	3.072744e+01	2.293659e+01	NA	-0.3196292	-0.2535469	-0.4921351
BRN	country	rat	s2t	NA	1.826032e+01	1.366667e+01	9.311649e+00	NA	-0.2515649	-0.3186599	-0.4900611
BTN	country	lvl	youthpop	9.400200e+04	1.776710e+05	2.353020e+05	1.920890e+05	0.8900768	0.3243692	-0.1836491	0.0811500
BTN	country	lvl	student	NA	2.989900e+04	8.509200e+04	9.416500e+04	NA	1.8459815	0.1066258	2.1494364
BTN	country	lvl	teacher	NA	9.453473e+02	2.068000e+03	2.941000e+03	NA	1.1875558	0.4221470	2.1110259
BTN	country	rat	y2t	NA	1.879426e+02	1.137824e+02	6.531418e+01	NA	-0.3945895	-0.4259729	-0.6524780
BTN	country	rat	s2t	NA	3.162753e+01	4.114700e+01	3.201802e+01	NA	0.3009869	-0.2218626	0.0123466
BWA	country	lvl	youthpop	2.194100e+05	4.354820e+05	6.352330e+05	7.855300e+05	0.9847865	0.4586895	0.2366014	0.8038174
BWA	country	lvl	student	NA	1.719140e+05	3.242830e+05	3.648943e+05	NA	0.8863094	0.1252341	1.1225398
BWA	country	lvl	teacher	NA	5.316000e+03	1.213500e+04	1.161218e+04	NA	1.2827314	-0.0430838	1.1843827
BWA	country	rat	y2t	NA	8.191911e+01	5.234718e+01	6.764708e+01	NA	-0.3609894	0.2922776	-0.1742210
BWA	country	rat	s2t	NA	3.233898e+01	2.672295e+01	3.142341e+01	NA	-0.1736612	0.1758962	-0.0283114
CAF	country	lvl	youthpop	5.709600e+05	9.284000e+05	1.575406e+06	2.102963e+06	0.6260333	0.6969044	0.3348705	1.2651476
CAF	country	lvl	student	NA	2.434190e+05	4.337708e+05	9.998486e+05	NA	0.7819923	1.3050161	3.1075208
CAF	country	lvl	teacher	NA	4.010000e+03	4.409947e+03	1.151319e+04	NA	0.0997375	1.6107316	1.8711195
CAF	country	rat	y2t	NA	2.315212e+02	3.572392e+02	1.826569e+02	NA	0.5430085	-0.4886987	-0.2110577
CAF	country	rat	s2t	NA	6.070299e+01	9.836189e+01	8.684376e+01	NA	0.6203796	-0.1170996	0.4306339
CAN	country	lvl	youthpop	6.040212e+06	5.578695e+06	5.880513e+06	6.000465e+06	-0.0764074	0.0541019	0.0203982	0.0756037
CAN	country	lvl	student	NA	2.205865e+06	2.456434e+06	2.408472e+06	NA	0.1135922	-0.0195250	0.0918493
CAN	country	lvl	teacher	NA	1.432856e+05	1.410450e+05	NA	NA	-0.0156376	NA	NA
CAN	country	rat	y2t	NA	3.893408e+01	4.169246e+01	NA	NA	0.0708473	NA	NA
CAN	country	rat	s2t	NA	1.539488e+01	1.741596e+01	NA	NA	0.1312827	NA	NA
CHE	country	lvl	youthpop	1.315049e+06	1.279347e+06	1.253186e+06	1.291911e+06	-0.0271486	-0.0204488	0.0309012	0.0098205
CHE	country	lvl	student	5.730520e+05	4.404003e+05	4.737390e+05	5.302300e+05	-0.2314829	0.0757010	0.1192450	0.2039729
CHE	country	lvl	teacher	1.744920e+04	2.523031e+04	3.661112e+04	5.477700e+04	0.4459293	0.4510770	0.4961846	1.1710792
CHE	country	rat	y2t	7.536442e+01	5.070675e+01	3.422965e+01	2.358492e+01	-0.3271791	-0.3249489	-0.3109799	-0.5348762
CHE	country	rat	s2t	3.284116e+01	1.745521e+01	1.293976e+01	9.679793e+00	-0.4684961	-0.2586879	-0.2519339	-0.4454496
CHE	country	lvl	school	NA	NA	NA	4.610000e+03	NA	NA	NA	NA
CHE	country	rat	y2s	NA	NA	NA	2.802410e+02	NA	NA	NA	NA
CHE	country	rat	s2s	NA	NA	NA	1.150174e+02	NA	NA	NA	NA
CHI	country	lvl	youthpop	2.354600e+04	2.343900e+04	2.530600e+04	2.603400e+04	-0.0045443	0.0796536	0.0287679	0.1107129
CHL	country	lvl	youthpop	3.208362e+06	3.823972e+06	4.193301e+06	3.677716e+06	0.1918767	0.0965826	-0.1229544	-0.0382471
CHL	country	lvl	student	NA	1.754075e+06	1.798515e+06	1.565850e+06	NA	0.0253353	-0.1293651	-0.1073073
CHL	country	lvl	teacher	NA	NA	5.580800e+04	9.546273e+04	NA	NA	0.7105564	NA
CHL	country	rat	y2t	NA	NA	7.513799e+01	3.852515e+01	NA	NA	-0.4872747	NA
CHL	country	rat	s2t	NA	NA	3.222683e+01	1.640273e+01	NA	NA	-0.4910224	NA
CHN	country	lvl	youthpop	2.656419e+08	3.526119e+08	3.129935e+08	2.499012e+08	0.3273957	-0.1123568	-0.2015771	-0.2912854
CHN	country	lvl	student	9.379100e+07	1.462700e+08	1.301330e+08	1.072535e+08	0.5595313	-0.1103234	-0.1758163	-0.2667430
CHN	country	lvl	teacher	2.693000e+06	5.499000e+06	5.860000e+06	6.434200e+06	1.0419606	0.0656483	0.0979863	0.1700673
CHN	country	lvl	school	7.264840e+05	9.173160e+05	5.536220e+05	1.579790e+05	0.2626789	-0.3964762	-0.7146446	-0.8277813
CHN	country	rat	y2t	9.864162e+01	6.412291e+01	5.341187e+01	3.883951e+01	-0.3499406	-0.1670393	-0.2728299	-0.3942959
CHN	country	rat	s2t	3.482770e+01	2.659938e+01	2.220700e+01	1.666928e+01	-0.2362579	-0.1651311	-0.2493680	-0.3733207
CHN	country	rat	y2s	3.656542e+02	3.843952e+02	5.653560e+02	1.581863e+03	0.0512536	0.4707676	1.7979951	3.1152004
CHN	country	rat	s2s	1.291026e+02	1.594543e+02	2.350575e+02	6.789099e+02	0.2350973	0.4741369	1.8882715	3.2577075
CIV	country	lvl	youthpop	1.496544e+06	3.636087e+06	7.179531e+06	1.094922e+07	1.4296559	0.9745212	0.5250605	2.0112643
CIV	country	lvl	student	NA	9.541900e+05	1.943101e+06	4.101430e+06	NA	1.0363879	1.1107652	3.2983368
CIV	country	lvl	teacher	NA	2.460900e+04	4.320500e+04	1.010850e+05	NA	0.7556585	1.3396598	3.1076435
CIV	country	rat	y2t	NA	1.477544e+02	1.661736e+02	1.083170e+02	NA	0.1246613	-0.3481700	-0.2669120
CIV	country	rat	s2t	NA	3.877403e+01	4.497398e+01	4.057407e+01	NA	0.1598998	-0.0978324	0.0464240
CMR	country	lvl	youthpop	2.066923e+06	3.852220e+06	6.995203e+06	1.116623e+07	0.8637463	0.8158888	0.5962702	1.8986491
CMR	country	lvl	student	NA	1.302974e+06	2.237083e+06	4.607127e+06	NA	0.7169053	1.0594351	2.5358551
CMR	country	lvl	teacher	NA	2.528900e+04	4.199858e+04	9.945403e+04	NA	0.6607451	1.3680330	2.9326992
CMR	country	rat	y2t	NA	1.523279e+02	1.665581e+02	1.122753e+02	NA	0.0934181	-0.3259088	-0.2629365
CMR	country	rat	s2t	NA	5.152335e+01	5.326568e+01	4.632419e+01	NA	0.0338163	-0.1303182	-0.1009088
COD	country	lvl	youthpop	6.612287e+06	1.175548e+07	2.145214e+07	4.101481e+07	0.7778229	0.8248636	0.9119219	2.4889967
COD	country	lvl	student	NA	4.054758e+06	4.452456e+06	1.920163e+07	NA	0.0980817	3.3125931	3.7355795
COD	country	lvl	teacher	NA	9.936128e+04	1.560281e+05	6.520954e+05	NA	0.5703109	3.1793461	5.5628727
COD	country	rat	y2t	NA	1.183104e+02	1.374889e+02	6.289695e+01	NA	0.1621034	-0.5425309	-0.4683735
COD	country	rat	s2t	NA	4.080823e+01	2.853624e+01	2.944604e+01	NA	-0.3007234	0.0318823	-0.2784289
COG	country	lvl	youthpop	4.253860e+05	8.197330e+05	1.318699e+06	2.277331e+06	0.9270333	0.6086933	0.7269529	1.7781375
COG	country	lvl	student	NA	3.830180e+05	4.187070e+05	8.004810e+05	NA	0.0931784	0.9117927	1.0899304
COG	country	lvl	teacher	NA	6.852000e+03	6.923000e+03	3.313332e+04	NA	0.0103619	3.7859772	3.8355692
COG	country	rat	y2t	NA	1.196341e+02	1.904809e+02	6.873235e+01	NA	0.5921951	-0.6391640	-0.4254787
COG	country	rat	s2t	NA	5.589872e+01	6.048057e+01	2.415940e+01	NA	0.0819671	-0.6005429	-0.5678005
COL	country	lvl	youthpop	7.497972e+06	1.076664e+07	1.290899e+07	1.128764e+07	0.4359397	0.1989808	-0.1255985	0.0483906
COL	country	lvl	student	NA	4.168200e+06	5.221018e+06	4.224512e+06	NA	0.2525834	-0.1908643	0.0135099
COL	country	lvl	teacher	NA	1.363810e+05	1.973740e+05	1.848507e+05	NA	0.4472251	-0.0634496	0.3553992
COL	country	rat	y2t	NA	7.894528e+01	6.540370e+01	6.106355e+01	NA	-0.1715312	-0.0663594	-0.2265079
COL	country	rat	s2t	NA	3.056291e+01	2.645241e+01	2.285364e+01	NA	-0.1344930	-0.1360468	-0.2522425
COM	country	lvl	youthpop	7.895700e+04	1.378790e+05	2.385100e+05	3.393150e+05	0.7462543	0.7298501	0.4226448	1.4609621
COM	country	lvl	student	NA	5.460648e+04	9.342100e+04	1.298704e+05	NA	0.7108043	0.3901630	1.3782970
COM	country	lvl	teacher	NA	1.160685e+03	2.536000e+03	2.100564e+03	NA	1.1849167	-0.1717018	0.8097626
COM	country	rat	y2t	NA	1.187911e+02	9.404968e+01	1.615352e+02	NA	-0.2082764	0.7175514	0.3598259
COM	country	rat	s2t	NA	4.704677e+01	3.683793e+01	6.182644e+01	NA	-0.2169933	0.6783364	0.3141486
CPV	country	lvl	youthpop	8.500600e+04	1.342860e+05	1.839600e+05	1.561300e+05	0.5797238	0.3699120	-0.1512829	0.1626677
CPV	country	lvl	student	NA	5.811100e+04	9.163600e+04	6.110155e+04	NA	0.5769131	-0.3332145	0.0514627
CPV	country	lvl	teacher	NA	1.396000e+03	3.190000e+03	3.143822e+03	NA	1.2851003	-0.0144760	1.2520212
CPV	country	rat	y2t	NA	9.619341e+01	5.766771e+01	4.966249e+01	NA	-0.4005025	-0.1388164	-0.4837226
CPV	country	rat	s2t	NA	4.162679e+01	2.872602e+01	1.943544e+01	NA	-0.3099151	-0.3234204	-0.5331026
CRI	country	lvl	youthpop	6.031280e+05	8.804200e+05	1.234692e+06	1.061003e+06	0.4597565	0.4023898	-0.1406739	0.2051101
CRI	country	lvl	student	NA	3.486740e+05	5.514650e+05	4.927610e+05	NA	0.5816063	-0.1064510	0.4132427
CRI	country	lvl	teacher	NA	1.259600e+04	2.211100e+04	4.309300e+04	NA	0.7553985	0.9489394	2.4211654
CRI	country	rat	y2t	NA	6.989679e+01	5.584062e+01	2.462124e+01	NA	-0.2010989	-0.5590802	-0.6477487
CRI	country	rat	s2t	NA	2.768133e+01	2.494075e+01	1.143483e+01	NA	-0.0990044	-0.5415204	-0.5869119
CUB	country	lvl	youthpop	2.503849e+06	3.124091e+06	2.401518e+06	1.803279e+06	0.2477154	-0.2312906	-0.2491087	-0.4227828
CUB	country	lvl	student	NA	1.550323e+06	1.045578e+06	7.598030e+05	NA	-0.3255741	-0.2733177	-0.5099066
CUB	country	lvl	teacher	NA	8.651900e+04	9.092000e+04	8.462900e+04	NA	0.0508674	-0.0691927	-0.0218449
CUB	country	rat	y2t	NA	3.610873e+01	2.641353e+01	2.130805e+01	NA	-0.2685002	-0.1932903	-0.4098920
CUB	country	rat	s2t	NA	1.791887e+01	1.149998e+01	8.978045e+00	NA	-0.3582198	-0.2192989	-0.4989615
CUW	country	lvl	youthpop	5.145600e+04	4.590700e+04	3.336300e+04	2.816500e+04	-0.1078397	-0.2732481	-0.1558013	-0.3864770
CUW	country	lvl	student	NA	NA	NA	1.292200e+04	NA	NA	NA	NA
CYM	country	lvl	student	NA	2.109000e+03	3.435000e+03	4.534000e+03	NA	0.6287340	0.3199418	1.1498340
CYM	country	lvl	teacher	NA	1.120000e+02	2.370000e+02	3.470000e+02	NA	1.1160714	0.4641350	2.0982143
CYM	country	rat	s2t	NA	1.883036e+01	1.449367e+01	1.306628e+01	NA	-0.2303029	-0.0984836	-0.3061054
CYP	country	lvl	youthpop	2.103090e+05	1.712940e+05	2.112960e+05	2.001460e+05	-0.1855127	0.2335283	-0.0527696	0.1684356
CYP	country	lvl	student	NA	5.057900e+04	6.395200e+04	5.990104e+04	NA	0.2643983	-0.0633437	0.1843066
CYP	country	lvl	teacher	NA	2.200000e+03	3.608000e+03	5.356032e+03	NA	0.6400000	0.4844878	1.4345600
CYP	country	rat	y2t	NA	7.786091e+01	5.856319e+01	3.736834e+01	NA	-0.2478486	-0.3619143	-0.5200629
CYP	country	rat	s2t	NA	2.299045e+01	1.772506e+01	1.118385e+01	NA	-0.2290254	-0.3690374	-0.5135439
CZE	country	lvl	youthpop	2.471190e+06	2.411901e+06	1.684165e+06	1.685507e+06	-0.0239921	-0.3017271	0.0007968	-0.3011707
CZE	country	lvl	student	NA	6.729224e+05	6.449560e+05	5.801289e+05	NA	-0.0415596	-0.1005139	-0.1378962
CZE	country	lvl	teacher	NA	2.287938e+04	3.819600e+04	NA	NA	0.6694506	NA	NA
CZE	country	rat	y2t	NA	1.054181e+02	4.409271e+01	NA	NA	-0.5817349	NA	NA
CZE	country	rat	s2t	NA	2.941174e+01	1.688543e+01	NA	NA	-0.4258947	NA	NA
DEU	country	lvl	youthpop	NA	NA	1.288464e+07	1.160560e+07	NA	NA	-0.0992693	NA
DEU	country	lvl	student	NA	NA	3.352935e+06	2.842302e+06	NA	NA	-0.1522943	NA
DEU	country	lvl	teacher	NA	NA	2.154370e+05	2.378280e+05	NA	NA	0.1039329	NA
DEU	country	lvl	school	NA	NA	1.727500e+04	1.544700e+04	NA	NA	-0.1058177	NA
DEU	country	rat	y2t	NA	NA	5.980702e+01	4.879827e+01	NA	NA	-0.1840711	NA
DEU	country	rat	s2t	NA	NA	1.556341e+01	1.195108e+01	NA	NA	-0.2321040	NA
DEU	country	rat	y2s	NA	NA	7.458549e+02	7.513171e+02	NA	NA	0.0073233	NA
DEU	country	rat	s2s	NA	NA	1.940918e+02	1.840035e+02	NA	NA	-0.0519767	NA
DJI	country	lvl	youthpop	3.626200e+04	1.667940e+05	2.940320e+05	2.856540e+05	3.5996911	0.7628452	-0.0284935	0.7126156
DJI	country	lvl	student	NA	1.522700e+04	3.819100e+04	6.913400e+04	NA	1.5081106	0.8102171	3.5402246
DJI	country	lvl	teacher	NA	3.600000e+02	1.041899e+03	2.310000e+03	NA	1.8941632	1.2171060	5.4166667
DJI	country	rat	y2t	NA	4.633167e+02	2.822078e+02	1.236597e+02	NA	-0.3908964	-0.5618132	-0.7330989
DJI	country	rat	s2t	NA	4.229722e+01	3.665519e+01	2.992814e+01	NA	-0.1333901	-0.1835225	-0.2924325
DMA	country	lvl	student	NA	1.560100e+04	1.177400e+04	6.185000e+03	NA	-0.2453048	-0.4746900	-0.6035511
DMA	country	lvl	teacher	NA	4.569721e+02	6.020000e+02	5.200000e+02	NA	0.3173671	-0.1362126	0.1379251
DMA	country	rat	s2t	NA	3.413994e+01	1.955814e+01	1.189423e+01	NA	-0.4271185	-0.3918526	-0.6516037
DNK	country	lvl	youthpop	1.154416e+06	1.067393e+06	9.861990e+05	9.494540e+05	-0.0753827	-0.0760676	-0.0372592	-0.1104926
DNK	country	lvl	student	NA	4.429310e+05	3.841970e+05	4.554759e+05	NA	-0.1326030	0.1855269	0.0283224
DNK	country	lvl	teacher	NA	3.512372e+04	3.795600e+04	4.633317e+04	NA	0.0806373	0.2207074	0.3191420
DNK	country	rat	y2t	NA	3.038952e+01	2.598269e+01	2.049189e+01	NA	-0.1450116	-0.2113255	-0.3256924
DNK	country	rat	s2t	NA	1.261060e+01	1.012217e+01	9.830449e+00	NA	-0.1973283	-0.0288198	-0.2204612
DOM	country	lvl	youthpop	1.588639e+06	2.482179e+06	2.957529e+06	2.976593e+06	0.5624563	0.1915051	0.0064459	0.1991855
DOM	country	lvl	student	NA	1.069117e+06	1.363609e+06	1.223677e+06	NA	0.2754535	-0.1026189	0.1445679
DOM	country	lvl	teacher	NA	2.096810e+04	4.394100e+04	6.504100e+04	NA	1.0956116	0.4801893	2.1019019
DOM	country	rat	y2t	NA	1.183788e+02	6.730682e+01	4.576487e+01	NA	-0.4314284	-0.3200560	-0.6134032
DOM	country	rat	s2t	NA	5.098778e+01	3.103273e+01	1.881393e+01	NA	-0.3913693	-0.3937390	-0.6310109
DZA	country	lvl	youthpop	4.929676e+06	8.903581e+06	1.066696e+07	1.349889e+07	0.8061189	0.1980524	0.2654868	0.5161195
DZA	country	lvl	student	NA	3.061252e+06	4.843313e+06	4.852322e+06	NA	0.5821347	0.0018601	0.5850776
DZA	country	lvl	teacher	NA	8.549900e+04	1.705620e+05	2.007490e+05	NA	0.9949005	0.1769855	1.3479690
DZA	country	rat	y2t	NA	1.041367e+02	6.254006e+01	6.724264e+01	NA	-0.3994425	0.0751932	-0.3542847
DZA	country	rat	s2t	NA	3.580454e+01	2.839620e+01	2.417109e+01	NA	-0.2069105	-0.1487915	-0.3249154
ECU	country	lvl	youthpop	1.972034e+06	3.355887e+06	4.434201e+06	4.832774e+06	0.7017389	0.3213201	0.0898861	0.4400884
ECU	country	lvl	student	NA	1.450109e+06	1.925420e+06	1.876429e+06	NA	0.3277760	-0.0254443	0.2939917
ECU	country	lvl	teacher	NA	3.983000e+04	8.280900e+04	7.629700e+04	NA	1.0790610	-0.0786388	0.9155662
ECU	country	rat	y2t	NA	8.425526e+01	5.354733e+01	6.334160e+01	NA	-0.3644630	0.1829086	-0.2482179
ECU	country	rat	s2t	NA	3.640746e+01	2.325134e+01	2.459375e+01	NA	-0.3613578	0.0577347	-0.3244860
EGY	country	lvl	youthpop	1.121519e+07	1.766131e+07	2.536962e+07	3.471288e+07	0.5747664	0.4364521	0.3682853	0.9654763
EGY	country	lvl	student	NA	4.537233e+06	7.947488e+06	1.391736e+07	NA	0.7516156	0.7511644	2.0673668
EGY	country	lvl	teacher	NA	1.370450e+05	3.458280e+05	5.274170e+05	NA	1.5234631	0.5250848	2.8484951
EGY	country	rat	y2t	NA	1.288723e+02	7.335907e+01	6.581676e+01	NA	-0.4307616	-0.1028136	-0.4892871
EGY	country	rat	s2t	NA	3.310761e+01	2.298104e+01	2.638777e+01	NA	-0.3058684	0.1482407	-0.2029698
ERI	country	lvl	youthpop	4.377160e+05	7.674830e+05	1.047868e+06	NA	0.7533812	0.3653306	NA	NA
ERI	country	lvl	student	NA	NA	2.959410e+05	3.553063e+05	NA	NA	0.2005983	NA
ERI	country	lvl	teacher	NA	NA	6.229000e+03	9.411820e+03	NA	NA	0.5109681	NA
ERI	country	rat	y2t	NA	NA	1.682241e+02	NA	NA	NA	NA	NA
ERI	country	rat	s2t	NA	NA	4.751019e+01	3.775107e+01	NA	NA	-0.2054112	NA
ESP	country	lvl	youthpop	8.333672e+06	9.727915e+06	5.978403e+06	6.820080e+06	0.1673024	-0.3854384	0.1407863	-0.2989166
ESP	country	lvl	student	NA	3.608854e+06	2.539995e+06	3.033276e+06	NA	-0.2961768	0.1942057	-0.1594904
ESP	country	lvl	teacher	NA	1.292956e+05	1.746380e+05	2.380446e+05	NA	0.3506884	0.3630747	0.8410892
ESP	country	rat	y2t	NA	7.523781e+01	3.423312e+01	2.865042e+01	NA	-0.5450012	-0.1630787	-0.6192018
ESP	country	rat	s2t	NA	2.791166e+01	1.454434e+01	1.274247e+01	NA	-0.4789152	-0.1238883	-0.5434715
EST	country	lvl	youthpop	2.798640e+05	3.194340e+05	2.456310e+05	2.193400e+05	0.1413901	-0.2310430	-0.1070345	-0.3133480
EST	country	lvl	student	NA	1.297835e+05	1.234060e+05	9.115491e+04	NA	-0.0491392	-0.2613413	-0.2976384
EST	country	lvl	teacher	NA	NA	8.616000e+03	8.315365e+03	NA	NA	-0.0348927	NA
EST	country	rat	y2t	NA	NA	2.850870e+01	2.637768e+01	NA	NA	-0.0747501	NA
EST	country	rat	s2t	NA	NA	1.432289e+01	1.096223e+01	NA	NA	-0.2346357	NA

Implement FEL file

This is functionalized in [PrjCompPPTS::ff_ppts_lrce_fel()].

Note we also generate elasticity information on Compute Elasticities of School Resources to Changes in Populations. It is done more automatically there, across all possible combinations of variables, here, we generate a more selected subset of elasticities, note that this is manual because we specify below what the numerator and denominator for each elasticity is.

First, from fpc, keep percentage changes as stats vars, drop level and rank vars.

print(df_fpc %>% distinct(vartype))
#> # A tibble: 3 × 1
#>   vartype
#>   <chr>  
#> 1 lvl    
#> 2 rat    
#> 3 rank
df_fpc_base <- df_fpc %>%
  filter(vartype == "lvl") %>%
  select(-contains("year"), -vartype)
print(glue::glue("dim df_fpc_base: {dim(df_fpc_base)}"))
#> dim df_fpc_base: 818
#> dim df_fpc_base: 7

Second, from percentage change file, variables are changes over time, convert all change spans to long. unit of obs: locType x loc x vars(change) x changeSpan.

df_fel_long <- df_fpc_base %>%
  pivot_longer(
    cols = matches("chg"),
    names_to = c("yearcomp"),
    names_pattern = paste0("chg_(.*)"),
    values_to = "change"
  ) %>%
  drop_na(change)
print(glue::glue("dim df_fel_long: {dim(df_fel_long)}"))
#> dim df_fel_long: 2456
#> dim df_fel_long: 5

Third, convert vars(change) to wide. unit of obs: locType x loc x changeSpan.

df_fel_wide <- df_fel_long %>%
  pivot_wider(
    id_cols = c("location_code", "location_level", "yearcomp"),
    names_from = variable,
    names_prefix = "var_chg_",
    names_sep = "_",
    values_from = c(change)
  )
print(glue::glue("dim df_fel_wide: {dim(df_fel_wide)}"))
#> dim df_fel_wide: 1055
#> dim df_fel_wide: 7

Fourth, following our prior notations, we compute the percentage changes in education resources over percentage changes in the population. When changes in teachers is in the denominator, we call this the population-teacher elasticity. When the number of schools is in the denominator, we call this this population-school elasticity. In labor economics, the labor supply elasticity refers to the change in labor supply given a change in wages, which could also be referred to as the wage-labor-supply elasticity. We follow this form of terminology here.

We use the following variable names for the following elasticities:

Teacher over student : var_elsa_t2s
Teacher over youthpop: var_elas_t2y
School over student: var_elas_s2s
School over youthpop: var_elas_sty

df_fel_elas <- df_fel_wide %>%
  mutate(
    var_elas_y2t = var_chg_teacher / var_chg_youthpop,
    var_elas_s2t = var_chg_teacher / var_chg_student,
    var_elas_y2s = var_chg_school / var_chg_youthpop,
    var_elas_s2s = var_chg_school / var_chg_student
  )
print(glue::glue("dim df_fel_elas: {dim(df_fel_elas)}"))
#> dim df_fel_elas: 1055
#> dim df_fel_elas: 11

Fifth, we clean file and convert to standard format where unit of obs is locType x loc x vars, and year spans are columns.

df_fel <- df_fel_elas %>%
  select(-contains("var_chg")) %>%
  pivot_longer(
    cols = matches("var_elas"),
    names_to = c("variable"),
    names_pattern = paste0("var_elas_(.*)"),
    values_to = "elasticity"
  ) %>%
  drop_na(elasticity) %>%
  pivot_wider(
    id_cols = c("location_code", "location_level", "variable"),
    names_from = yearcomp,
    names_prefix = "elas_",
    names_sep = "_",
    values_from = c(elasticity)
  )
print(glue::glue("dim FEL: {dim(df_fel)}"))
#> dim FEL: 517
#> dim FEL: 7

Review output.

kable(df_fel[1:300,], caption="FEL")

FEL
location_code	location_level	variable	elas_00v80	elas_20v00	elas_20v80	elas_80v60
AFG	country	y2t	1.0431807	5.3851784	3.7264844	NA
AFG	country	s2t	-3.0818450	0.3877632	0.9675731	NA
AGO	country	y2t	0.2229895	0.2733433	0.1857915	NA
AGO	country	s2t	1.3033806	0.0921840	0.1552049	NA
ALB	country	y2t	NA	0.4805559	NA	NA
ALB	country	s2t	NA	0.5373607	NA	NA
AND	country	s2t	0.7738193	4.8681019	1.3753024	NA
ARE	country	y2t	1.3085960	0.5747371	0.9678758	NA
ARE	country	s2t	1.0099008	0.6597473	0.8387047	NA
ARG	country	y2t	1.1073133	NA	NA	NA
ARG	country	s2t	1.0443717	NA	NA	NA
ARM	country	y2t	NA	1.4190635	NA	NA
ARM	country	s2t	NA	2.2247258	NA	NA
ATG	country	y2t	-10.2520289	-7.9053311	-11.1363048	NA
ATG	country	s2t	2.3233803	-0.7625874	16.7044041	NA
AUS	country	y2t	2.2144354	NA	NA	NA
AUS	country	s2t	1.5411916	NA	NA	NA
AUT	country	y2t	-1.7709862	-2.1762042	-2.0822435	-24.9066870
AUT	country	s2t	-11.8157461	-0.8689773	-2.6448281	-1.2610628
AUT	country	y2s	0.2009553	2.2034165	0.7412884	19.0746064
AUT	country	s2s	1.3407426	0.8798434	0.9415712	0.9657758
AZE	country	y2t	NA	-1.3483813	NA	NA
AZE	country	s2t	NA	-1.0287517	NA	NA
BDI	country	y2t	2.4380349	4.4745913	5.3731287	NA
BDI	country	s2t	0.5139638	1.3910301	0.7761105	NA
BEL	country	y2t	-4.4725013	2.0908127	-70.6602892	NA
BEL	country	s2t	-4.0823465	2.9054732	-16.1649155	NA
BEN	country	y2t	1.9683566	3.4625456	3.7373840	NA
BEN	country	s2t	1.0595091	1.6545686	1.5086930	NA
BFA	country	y2t	5.3582702	5.6571080	12.1147283	NA
BFA	country	s2t	1.1066796	1.4299320	1.4527016	NA
BGD	country	y2t	2.5714231	-16.0928252	11.7374415	NA
BGD	country	s2t	1.0751650	5.2621098	2.4528218	NA
BGR	country	y2t	NA	0.2356627	NA	NA
BGR	country	s2t	NA	0.1335189	NA	NA
BHR	country	y2t	1.3403748	1.8488201	1.7835783	NA
BHR	country	s2t	1.3698424	1.9827808	1.8840921	NA
BHS	country	y2t	7.1105215	13.2734395	2.0370021	NA
BHS	country	s2t	13.3781571	2.2459742	-1.7128453	NA
BLR	country	y2t	NA	2.7141448	NA	NA
BLR	country	s2t	NA	1.2565383	NA	NA
BLZ	country	y2t	NA	2.3140565	NA	NA
BLZ	country	s2t	NA	3.3864438	NA	NA
BMU	country	s2t	-7.2966206	0.0002489	-3.7060379	NA
BOL	country	y2t	NA	2.5759251	NA	NA
BOL	country	s2t	NA	-6.0947390	NA	NA
BRA	country	y2t	3.4383827	0.3608358	-8.4673339	NA
BRA	country	s2t	1.8155087	0.2423576	-9.3376498	NA
BRB	country	y2t	-0.2798908	-0.3194339	-0.3410890	NA
BRB	country	s2t	-0.2714669	-0.2786756	-0.3174734	NA
BRN	country	y2t	2.7990728	-6.4147130	5.2635988	NA
BRN	country	s2t	2.0237556	-2.2088020	5.1706935	NA
BTN	country	y2t	3.6611238	-2.2986609	26.0138775	NA
BTN	country	s2t	0.6433195	3.9591461	0.9821300	NA
BWA	country	y2t	2.7965138	-0.1820943	1.4734475	NA
BWA	country	s2t	1.4472726	-0.3440258	1.0550920	NA
CAF	country	y2t	0.1431151	4.8100135	1.4789733	NA
CAF	country	s2t	0.1275428	1.2342619	0.6021261	NA
CAN	country	y2t	-0.2890391	NA	NA	NA
CAN	country	s2t	-0.1376641	NA	NA	NA
CHE	country	y2t	-22.0588366	16.0571115	119.2480360	-16.4254950
CHE	country	s2t	5.9586690	4.1610525	5.7413464	-1.9264022
CHL	country	y2t	NA	-5.7790219	NA	NA
CHL	country	s2t	NA	-5.4926425	NA	NA
CHN	country	y2t	-0.5842840	-0.4860985	-0.5838511	3.1825730
CHN	country	s2t	-0.5950534	-0.5573224	-0.6375698	1.8622026
CHN	country	y2s	3.5287238	3.5452665	2.8418221	0.8023285
CHN	country	s2s	3.5937646	4.0647240	3.1032913	0.4694623
CIV	country	y2t	0.7754151	2.5514389	1.5451194	NA
CIV	country	s2t	0.7291271	1.2060692	0.9421850	NA
CMR	country	y2t	0.8098470	2.2943173	1.5446241	NA
CMR	country	s2t	0.9216630	1.2912853	1.1564932	NA
COD	country	y2t	0.6914002	3.4864237	2.2349859	NA
COD	country	s2t	5.8146520	0.9597756	1.4891592	NA
COG	country	y2t	0.0170232	5.2080092	2.1570712	NA
COG	country	s2t	0.1112054	4.1522347	3.5190954	NA
COL	country	y2t	2.2475788	0.5051780	7.3443845	NA
COL	country	s2t	1.7706037	0.3324330	26.3066112	NA
COM	country	y2t	1.6235069	-0.4062555	0.5542667	NA
COM	country	s2t	1.6670082	-0.4400770	0.5875095	NA
CPV	country	y2t	3.4740705	0.0956883	7.6968007	NA
CPV	country	s2t	2.2275455	0.0434435	24.3286878	NA
CRI	country	y2t	1.8772807	-6.7456657	11.8042257	NA
CRI	country	s2t	1.2988142	-8.9143310	5.8589425	NA
CUB	country	y2t	-0.2199287	0.2777611	0.0516693	NA
CUB	country	s2t	-0.1562392	0.2531585	0.0428410	NA
CYM	country	s2t	1.7751091	1.4506859	1.8247975	NA
CYP	country	y2t	2.7405670	-9.1811958	8.5169665	NA
CYP	country	s2t	2.4205907	-7.6485572	7.7835509	NA
CZE	country	y2t	-2.2187283	NA	NA	NA
CZE	country	s2t	-16.1082036	NA	NA	NA
DEU	country	y2t	NA	-1.0469801	NA	NA
DEU	country	s2t	NA	-0.6824478	NA	NA
DEU	country	y2s	NA	1.0659661	NA	NA
DEU	country	s2s	NA	0.6948233	NA	NA
DJI	country	y2t	2.4830244	-42.7152196	7.6011063	NA
DJI	country	s2t	1.2559843	1.5021974	1.5300348	NA
DMA	country	s2t	-1.2937666	0.2869507	-0.2285227	NA
DNK	country	y2t	-1.0600747	-5.9235657	-2.8883568	NA
DNK	country	s2t	-0.6081106	1.1896249	11.2681770	NA
DOM	country	y2t	5.7210561	74.4950647	10.5524860	NA
DOM	country	s2t	3.9774831	-4.6793479	14.5392020	NA
DZA	country	y2t	5.0234195	0.6666452	2.6117380	NA
DZA	country	s2t	1.7090555	95.1488677	2.3039148	NA
ECU	country	y2t	3.3582118	-0.8748717	2.0804141	NA
ECU	country	s2t	3.2920679	3.0906230	3.1142586	NA
EGY	country	y2t	3.4905617	1.4257556	2.9503523	NA
EGY	country	s2t	2.0269179	0.6990278	1.3778373	NA
ERI	country	s2t	NA	2.5472203	NA	NA
ESP	country	y2t	-0.9098428	2.5789073	-2.8137923	NA
ESP	country	s2t	-1.1840505	1.8695372	-5.2736036	NA
EST	country	y2t	NA	0.3259946	NA	NA
EST	country	s2t	NA	0.1335138	NA	NA
ETH	country	y2t	1.9452047	10.5636174	8.7205475	NA
ETH	country	s2t	0.8210905	2.0830506	1.6078918	NA
FIN	country	y2t	1.9690281	-2.9294110	-1.2133671	NA
FIN	country	s2t	10.2216282	-5.0667463	-2.6471855	NA
FJI	country	y2t	-0.0505080	-7.5807528	14.8642452	NA
FJI	country	s2t	-0.0438033	6.6500692	2.3171850	NA
FRA	country	y2t	-1.3050018	0.3115628	-2.6426883	NA
FRA	country	s2t	-0.8037875	-4.6051656	-0.8879751	NA
FRA	country	y2s	1.8468486	-4.5232103	6.7239517	NA
FRA	country	s2s	1.1375262	66.8569337	2.2593286	NA
FSM	country	y2t	-0.9297516	1.7131583	-11.8069542	NA
FSM	country	s2t	1.3494473	0.8305079	0.9866088	NA
GAB	country	y2t	0.6745992	NA	NA	NA
GAB	country	s2t	0.6539646	NA	NA	NA
GBR	country	y2t	1.5432393	2.2660501	11.7054314	NA
GBR	country	s2t	0.8395494	2.0040362	-1.1718906	NA
GEO	country	y2t	-0.2272791	-7.4255141	-2.7900770	NA
GEO	country	s2t	-0.7205343	9.4130761	600.4907270	NA
GHA	country	y2t	0.9927450	3.5391076	2.3318582	NA
GHA	country	s2t	0.6625396	1.8352091	1.2200158	NA
GIB	country	s2t	2.3747204	5.3922179	8.0483372	NA
GIN	country	y2t	1.8828819	3.2094337	3.2222692	NA
GIN	country	s2t	0.7640840	0.9197466	0.7718124	NA
GMB	country	y2t	1.9335006	1.8408326	2.4160122	NA
GMB	country	s2t	0.6520864	1.0483434	0.7195230	NA
GNB	country	y2t	0.1618751	NA	NA	NA
GNB	country	s2t	0.1021771	NA	NA	NA
GNQ	country	y2t	0.7824169	1.8028407	1.2869334	NA
GNQ	country	s2t	1.7091967	6.4781403	4.5408945	NA
GRC	country	y2t	-1.1466741	-6.0609511	-3.2245075	NA
GRC	country	s2t	-1.1575581	-24.4570266	-3.8473811	NA
GRD	country	y2t	-10.1301405	0.2090304	-1.1813692	NA
GRD	country	s2t	-2.6220350	0.2132098	-0.9083230	NA
GTM	country	y2t	2.4810217	8.9631122	5.0712591	NA
GTM	country	s2t	1.0656632	4.2519330	2.0169922	NA
GUY	country	y2t	-0.1923301	NA	NA	NA
GUY	country	s2t	-0.2136364	NA	NA	NA
HKG	country	y2t	-2.3399697	-1.7170203	-2.4245240	NA
HKG	country	s2t	-3.3416964	-1.1154578	-2.0506890	NA
HND	country	y2t	1.5668851	2.2411779	1.7598601	NA
HND	country	s2t	1.1720674	-12.6635481	1.6284448	NA
HRV	country	y2t	NA	-0.8045710	NA	NA
HRV	country	s2t	NA	-0.9110073	NA	NA
HTI	country	y2t	5.9834793	NA	NA	NA
HTI	country	s2t	1.6147269	NA	NA	NA
HUN	country	y2t	NA	1.0240811	NA	NA
HUN	country	s2t	NA	0.6423941	NA	NA
IDN	country	y2t	11.2039006	4.4157980	9.0006124	NA
IDN	country	s2t	4.6281544	10.9636635	7.0953089	NA
IND	country	y2t	2.1566895	-38.6149594	5.6908086	NA
IND	country	s2t	1.2210858	8.7038681	2.5341180	NA
IRL	country	y2t	-2.3730901	NA	NA	NA
IRL	country	s2t	6.8060670	NA	NA	NA
IRN	country	y2t	2.5924806	2.3047315	2.3601256	NA
IRN	country	s2t	1.2273402	-3.2137657	0.7219718	NA
IRQ	country	y2t	1.4499725	NA	NA	NA
IRQ	country	s2t	2.1207076	NA	NA	NA
ISL	country	y2t	14.3132448	4.7755539	9.3081115	NA
ISL	country	s2t	2.0928460	7.0598720	3.5714421	NA
ISR	country	y2t	0.7007668	1.3578743	1.0400544	NA
ISR	country	s2t	0.6228601	1.3762741	0.9811335	NA
ITA	country	y2t	0.1738063	0.5776067	0.2345122	NA
ITA	country	s2t	0.1605179	2.3761698	0.2336605	NA
JAM	country	y2t	-34.0811004	-0.2631850	-1.4656141	NA
JAM	country	s2t	-2.2315038	-0.1527276	-0.7242375	NA
JOR	country	y2t	1.8839431	1.4684272	1.9670803	NA
JOR	country	s2t	2.2792830	1.7197544	2.4438589	NA
JPN	country	y2t	0.4039457	-0.2228563	0.2249026	-12.6668932
JPN	country	s2t	0.3419692	-0.2536955	0.2076355	-4.9019448
JPN	country	y2s	0.1053393	1.1541884	0.5036933	3.0327597
JPN	country	s2s	0.0891773	1.3139067	0.4650217	1.1736438
KAZ	country	y2t	NA	1.3753412	NA	NA
KAZ	country	s2t	NA	1.8225920	NA	NA
KEN	country	y2t	NA	2.4271923	NA	NA
KEN	country	s2t	NA	1.4123767	NA	NA
KGZ	country	y2t	3.3219360	0.5354994	1.9695652	NA
KGZ	country	s2t	1.6759869	0.6354679	1.3428440	NA
KHM	country	y2t	0.6612784	6.5119994	0.8910134	NA
KHM	country	s2t	0.6013728	-4.0224379	0.9212257	NA
KIR	country	y2t	0.1299073	1.9549499	0.7416822	NA
KIR	country	s2t	0.5714742	2.0131092	1.5833628	NA
KNA	country	s2t	-0.4494984	-2.4204607	-1.8477643	NA
KOR	country	y2t	-0.7049645	-1.0698241	-1.1880832	NA
KOR	country	s2t	-0.6073787	-1.0670556	-1.1257338	NA
KOR	country	y2s	0.7539975	-0.4921557	0.1139663	NA
KOR	country	s2s	0.6496242	-0.4908821	0.1079854	NA
KWT	country	y2t	6.0589055	4.0592232	5.1599650	NA
KWT	country	s2t	-8.5009129	2.3753376	3.7316328	NA
LAO	country	y2t	1.4163370	37.2920941	2.1789616	NA
LAO	country	s2t	1.0578109	-3.0372030	2.0531506	NA
LBN	country	y2t	1.4595376	1.0205646	1.1880458	NA
LBN	country	s2t	6.5094995	1.5779900	2.4757821	NA
LBR	country	y2t	NA	1.1736303	NA	NA
LBR	country	s2t	NA	4.7111616	NA	NA
LCA	country	y2t	-7.3690605	0.0368175	-0.3953219	NA
LCA	country	s2t	-0.9199523	0.0329577	-0.2899011	NA
LIE	country	s2t	NA	-6.5290479	NA	NA
LKA	country	y2t	-1.1679946	5.2699621	-7.1196566	NA
LKA	country	s2t	-0.5563509	-3.7586635	-1.4633042	NA
LSO	country	y2t	2.1096275	-3.2146876	12.1004567	NA
LSO	country	s2t	1.0078676	-9.7595873	2.5236163	NA
LTU	country	y2t	-7.9928582	0.9349724	-0.5518053	NA
LTU	country	s2t	3.5416767	0.7859599	-0.8133922	NA
LUX	country	y2t	2.4073065	4.7964765	4.2522300	NA
LUX	country	s2t	1.8891958	3.7805493	3.2642100	NA
LVA	country	y2t	-1.5424277	-0.6721083	-1.2551373	NA
LVA	country	s2t	-6.1276702	-1.5784768	-3.2551365	NA
MAC	country	y2t	1.2372156	-13.1922787	3.1668826	NA
MAC	country	s2t	1.0058967	-2.1661867	5.6345881	NA
MAR	country	y2t	11.8283876	12.4308716	14.6218683	NA
MAR	country	s2t	1.7083893	1.2996966	1.7074105	NA
MCO	country	s2t	0.2657332	-52.4528205	3.4197797	NA
MDA	country	y2t	-9.4307826	0.9135818	-0.0032580	NA
MDA	country	s2t	5.1318294	0.8009827	-0.0036059	NA
MDG	country	y2t	0.4369061	3.3184164	1.6001231	NA
MDG	country	s2t	0.8791770	1.8287554	1.5771240	NA
MDV	country	y2t	NA	-11.7274950	NA	NA
MDV	country	s2t	NA	-2.4752910	NA	NA
MEX	country	y2t	5.1003374	-3.5356508	6.8372623	NA
MEX	country	s2t	12.9503510	-0.9827290	-58.4423471	NA
MKD	country	y2t	NA	-1.1960384	NA	NA
MKD	country	s2t	NA	-2.6036024	NA	NA
MLI	country	y2t	1.9109659	3.5613200	3.9204307	NA
MLI	country	s2t	0.5021430	2.3400171	1.1635468	NA
MLT	country	y2t	4.9143572	-4.7172691	-23.1934783	NA
MLT	country	s2t	2.5209223	-0.9767699	-2.2557549	NA
MMR	country	y2t	10.6020941	-3.1055261	-69.0241865	NA
MMR	country	s2t	3.5509185	4.8861947	4.3908412	NA
MNG	country	y2t	5.6887415	2.0085648	3.9698840	NA
MNG	country	s2t	0.9266906	1.2550936	1.0550629	NA
MOZ	country	y2t	2.4618269	2.8624703	3.7489723	NA
MOZ	country	s2t	1.7136523	1.1634743	1.5696817	NA
MRT	country	y2t	5.1095771	1.3567015	4.1376703	NA
MRT	country	s2t	1.0195151	0.8562611	0.9352009	NA
MUS	country	y2t	1.6859123	-0.3745038	0.2497160	NA
MUS	country	s2t	-3.7415939	-0.3021357	0.2755291	NA
MWI	country	y2t	NA	2.1212329	NA	NA
MWI	country	s2t	NA	1.6710722	NA	NA
MYS	country	y2t	2.6208284	-29.9387495	5.8537413	NA
MYS	country	s2t	2.1736084	45.0201253	4.3767267	NA
NAM	country	y2t	NA	3.0485395	NA	NA
NAM	country	s2t	NA	2.1817952	NA	NA
NER	country	y2t	1.8481771	3.0102612	3.5472306	NA
NER	country	s2t	0.9421744	1.0254977	0.9806881	NA
NGA	country	y2t	0.7421420	1.9062250	1.3576436	NA
NGA	country	s2t	0.6217969	2.2121154	1.3248624	NA
NIC	country	y2t	2.4761701	NA	NA	NA
NIC	country	s2t	0.9865400	NA	NA	NA
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NLD	country	s2t	NA	-0.4601022	NA	NA
NLD	country	y2s	NA	2.0553892	NA	NA
NLD	country	s2s	NA	1.5310948	NA	NA
NOR	country	y2t	-48.3172545	10.2905348	39.6339869	NA
NOR	country	s2t	7.1510672	4.9310164	6.9376308	NA
NPL	country	y2t	4.4597848	-7.1165299	17.8303495	NA
NPL	country	s2t	1.0135193	35.3783640	2.3612168	NA
NRU	country	s2t	0.6522808	2.0719535	-2.3465833	NA
NZL	country	y2t	-2.2392106	3.2301852	1.8070833	NA
NZL	country	s2t	1.3716846	5.2543021	17.8039005	NA
OMN	country	y2t	4.0692646	3.3844083	5.6714555	NA
OMN	country	s2t	0.9049293	-32.2597227	2.6015780	NA
PAK	country	y2t	2.5553326	0.3515035	1.7791634	NA
PAK	country	s2t	1.1925392	0.1376110	0.6324483	NA
PAN	country	y2t	1.5621194	0.9930289	1.3139791	NA
PAN	country	s2t	1.6612671	3.3105022	2.1700616	NA
PER	country	y2t	3.4801887	-3.7166708	15.6043009	NA
PER	country	s2t	2.1198162	-3.4621005	6.9590435	NA
PHL	country	y2t	0.9080816	4.9650688	1.8213303	NA
PHL	country	s2t	0.7518159	22.9568317	1.8591089	NA
PNG	country	y2t	1.3059335	5.3893748	3.6964484	NA
PNG	country	s2t	0.7408880	1.1022846	0.9210731	NA
POL	country	y2t	NA	1.2838038	NA	NA
POL	country	s2t	NA	1.0061453	NA	NA
PRI	country	y2t	-2.1657263	1.1170500	0.7038737	NA
PRI	country	s2t	-1.0053781	1.0154259	0.5771512	NA
PRT	country	y2t	0.3018684	0.9159128	0.5487513	NA
PRT	country	s2t	0.3048731	0.6638930	0.5020675	NA
PRY	country	y2t	2.0287829	NA	NA	NA
PRY	country	s2t	1.2121276	NA	NA	NA
PSE	country	y2t	NA	3.6956544	NA	NA
PSE	country	s2t	NA	3.9886688	NA	NA
PYF	country	y2t	2.6913425	NA	NA	NA
PYF	country	s2t	-8.2430220	NA	NA	NA
QAT	country	y2t	1.3231199	1.0989151	1.2895076	NA
QAT	country	s2t	1.1856686	1.0324342	1.1470273	NA
ROU	country	y2t	-0.2709849	0.9177502	0.4020552	NA
ROU	country	s2t	-0.4036253	1.1297323	0.5200447	NA