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R new syntax for ECMEN #229

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200 changes: 200 additions & 0 deletions Indicators/Economic-Capacity-to-Meet-Essential-Needs/ECMEN-ExcludingAssistance.R
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# ------------------------------------------------------------
# WFP Standardized Scripts
# Economic Capacity to Meet Essential Needs (ECMEN) – Assessments
# Version excluding assistance (and deducting humanitarian cash used for consumption)
# Last Updated: January 2026
# ------------------------------------------------------------

library(dplyr)

# -----------------------------
# 0) Food expenditure inputs (7D recall)
# -----------------------------
food_purch_7d <- c(
"HHExpFCer_Purch_MN_7D","HHExpFTub_Purch_MN_7D","HHExpFPuls_Purch_MN_7D",
"HHExpFVeg_Purch_MN_7D","HHExpFFrt_Purch_MN_7D","HHExpFAnimMeat_Purch_MN_7D",
"HHExpFAnimFish_Purch_MN_7D","HHExpFFats_Purch_MN_7D","HHExpFDairy_Purch_MN_7D",
"HHExpFEgg_Purch_MN_7D","HHExpFSgr_Purch_MN_7D","HHExpFCond_Purch_MN_7D",
"HHExpFBev_Purch_MN_7D","HHExpFOut_Purch_MN_7D"
)

food_gift_7d <- c(
"HHExpFCer_GiftAid_MN_7D","HHExpFTub_GiftAid_MN_7D","HHExpFPuls_GiftAid_MN_7D",
"HHExpFVeg_GiftAid_MN_7D","HHExpFFrt_GiftAid_MN_7D","HHExpFAnimMeat_GiftAid_MN_7D",
"HHExpFAnimFish_GiftAid_MN_7D","HHExpFFats_GiftAid_MN_7D","HHExpFDairy_GiftAid_MN_7D",
"HHExpFEgg_GiftAid_MN_7D","HHExpFSgr_GiftAid_MN_7D","HHExpFCond_GiftAid_MN_7D",
"HHExpFBev_GiftAid_MN_7D","HHExpFOut_GiftAid_MN_7D"
)

food_own_7d <- c(
"HHExpFCer_Own_MN_7D","HHExpFTub_Own_MN_7D","HHExpFPuls_Own_MN_7D",
"HHExpFVeg_Own_MN_7D","HHExpFFrt_Own_MN_7D","HHExpFAnimMeat_Own_MN_7D",
"HHExpFAnimFish_Own_MN_7D","HHExpFFats_Own_MN_7D","HHExpFDairy_Own_MN_7D",
"HHExpFEgg_Own_MN_7D","HHExpFSgr_Own_MN_7D","HHExpFCond_Own_MN_7D",
"HHExpFBev_Own_MN_7D","HHExpFOut_Own_MN_7D"
)

# -----------------------------
# 1) Non-food expenditure inputs (cash/credit only for ECMEN)
# 1M recall (short-term)
# -----------------------------
nf_purch_1m <- c(
"HHExpNFHyg_Purch_MN_1M","HHExpNFTransp_Purch_MN_1M","HHExpNFFuel_Purch_MN_1M",
"HHExpNFWat_Purch_MN_1M","HHExpNFElec_Purch_MN_1M","HHExpNFEnerg_Purch_MN_1M",
"HHExpNFDwelSer_Purch_MN_1M","HHExpNFPhone_Purch_MN_1M","HHExpNFRecr_Purch_MN_1M",
"HHExpNFAlcTobac_Purch_MN_1M"
)

# 6M recall (long-term) converted to monthly average by /6
nf_purch_6m <- c(
"HHExpNFMedServ_Purch_MN_6M","HHExpNFMedGood_Purch_MN_6M","HHExpNFCloth_Purch_MN_6M",
"HHExpNFEduFee_Purch_MN_6M","HHExpNFEduGood_Purch_MN_6M","HHExpNFRent_Purch_MN_6M",
"HHExpNFHHSoft_Purch_MN_6M","HHExpNFHHMaint_Purch_MN_6M"
)

# -----------------------------
# 2) Assistance variables (assessments)
# -----------------------------
asst_vars <- c("HHAsstWFPCBTRecTot","HHAsstUNNGOCBTRecTot","HHAsstCBTCShare")

# If your HH size variable is not HHSize, rename here:
hh_size_var <- "HHSize" # <-- change if needed (e.g., "hh_size")

# If your MEB variables are named differently, rename here:
meb_var <- "MEB" # per capita MEB
smeb_var <- "sMEB" # per capita SMEB (optional)

# -----------------------------
# 3) Convert SYSMIS (NA) expenditures to 0 (SPSS: SYSMIS=0)
# -----------------------------
all_exp_inputs <- c(food_purch_7d, food_gift_7d, food_own_7d, nf_purch_1m, nf_purch_6m)

df <- df %>%
mutate(across(all_of(all_exp_inputs), ~ as.numeric(.x))) %>%
mutate(across(all_of(all_exp_inputs), ~ dplyr::coalesce(.x, 0)))

# -----------------------------
# 4) (Optional) quick overview for outliers (min/max/mean)
# -----------------------------
exp_overview <- df %>%
summarise(across(all_of(all_exp_inputs),
list(min = ~min(.x, na.rm = TRUE),
max = ~max(.x, na.rm = TRUE),
mean = ~mean(.x, na.rm = TRUE))))
exp_overview

# -----------------------------
# 5) Compute monthly food totals by source (7D -> 1M with 30/7)
# -----------------------------
df <- df %>%
mutate(
HHExp_Food_Purch_MN_1M = rowSums(across(all_of(food_purch_7d))) * (30/7),
HHExp_Food_GiftAid_MN_1M = rowSums(across(all_of(food_gift_7d))) * (30/7),
HHExp_Food_Own_MN_1M = rowSums(across(all_of(food_own_7d))) * (30/7)
)

# -----------------------------
# 6) Compute monthly non-food (cash/credit only) = 30D + (6M/6)
# -----------------------------
df <- df %>%
mutate(
HHExpNFTotal_Purch_MN_30D = rowSums(across(all_of(nf_purch_1m))),
HHExpNFTotal_Purch_MN_6M = rowSums(across(all_of(nf_purch_6m))),
HHExpNFTotal_Purch_MN_1M = HHExpNFTotal_Purch_MN_30D + (HHExpNFTotal_Purch_MN_6M / 6)
)

# -----------------------------
# 7) Household economic capacity for ECMEN (ASSESSMENTS)
# IMPORTANT: exclude in-kind gifts/aid from the aggregate
# Food: Purch + Own (exclude GiftAid)
# Non-food: Purch only
# -----------------------------
df <- df %>%
mutate(
HHExpF_ECMEN = HHExp_Food_Purch_MN_1M + HHExp_Food_Own_MN_1M,
HHExpNF_ECMEN = HHExpNFTotal_Purch_MN_1M,
HHExp_ECMEN = HHExpF_ECMEN + HHExpNF_ECMEN
)

# -----------------------------
# 8) Deduct humanitarian cash assistance used for consumption (ASSESSMENTS)
# -----------------------------
df <- df %>%
mutate(
HHAsstWFPCBTRecTot = dplyr::coalesce(as.numeric(HHAsstWFPCBTRecTot), 0),
HHAsstUNNGOCBTRecTot = dplyr::coalesce(as.numeric(HHAsstUNNGOCBTRecTot), 0),
HHAsstCBTCShare = as.numeric(HHAsstCBTCShare),

HHAsstCBTRec = HHAsstWFPCBTRecTot + HHAsstUNNGOCBTRecTot,
HHAsstCBTRec_1M = HHAsstCBTRec / 3
)

# Median share used for consumption (if all missing -> treat as 0)
asst_share_med <- median(df$HHAsstCBTCShare, na.rm = TRUE)
if (is.na(asst_share_med)) asst_share_med <- 0

df <- df %>%
mutate(
HHAsstCBTCShare_med = asst_share_med,
HHAsstCBTRec_Cons_1M = HHAsstCBTRec_1M * (HHAsstCBTCShare_med / 100),
HHAsstCBTRec_Cons_1M = dplyr::coalesce(HHAsstCBTRec_Cons_1M, 0),
HHExp_ECMEN = HHExp_ECMEN - HHAsstCBTRec_Cons_1M
)

# -----------------------------
# 9) Per-capita economic capacity (monthly)
# -----------------------------
df <- df %>%
mutate(
PCExp_ECMEN = HHExp_ECMEN / .data[[hh_size_var]]
)

# -----------------------------
# 10) ECMEN classification vs MEB (per-capita)
# -----------------------------
df <- df %>%
mutate(
ECMEN_exclAsst = if_else(
!is.na(PCExp_ECMEN) & !is.na(.data[[meb_var]]),
as.integer(PCExp_ECMEN > .data[[meb_var]]),
NA_integer_
)
)

df <- df %>%
mutate(
ECMEN_exclAsst = factor(
ECMEN_exclAsst,
levels = c(0, 1),
labels = c("Below MEB", "Above MEB")
)
)


table(df$ECMEN_exclAsst, useNA = "ifany")

# Optional SMEB version (only if SMEB exists in your dataset)
if (smeb_var %in% names(df)) {
df <- df %>%
mutate(
ECMEN_exclAsst_SMEB = if_else(
!is.na(PCExp_ECMEN) & !is.na(.data[[smeb_var]]),
as.integer(PCExp_ECMEN > .data[[smeb_var]]),
NA_integer_
)
)

df <- df %>%
mutate(
ECMEN_exclAsst_SMEB = factor(
ECMEN_exclAsst_SMEB,
levels = c(0, 1),
labels = c("Below MEB", "Above MEB")
)
)

smeb_tab <- table(df$ECMEN_exclAsst_SMEB, useNA = "ifany")
print(smeb_tab)
}


174 changes: 174 additions & 0 deletions Indicators/Economic-Capacity-to-Meet-Essential-Needs/ECMEN-IncludingAssistance.R
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# ------------------------------------------------------------
# WFP Standardized Scripts
# Economic Capacity to Meet Essential Needs (ECMEN) – Monitoring
# Version INCLUDING assistance (in-kind gifts/aid included)
# Last Updated: January 2026
# ------------------------------------------------------------

library(dplyr)

# -----------------------------
# 0) Food expenditure inputs (7D recall)
# -----------------------------
food_purch_7d <- c(
"HHExpFCer_Purch_MN_7D","HHExpFTub_Purch_MN_7D","HHExpFPuls_Purch_MN_7D",
"HHExpFVeg_Purch_MN_7D","HHExpFFrt_Purch_MN_7D","HHExpFAnimMeat_Purch_MN_7D",
"HHExpFAnimFish_Purch_MN_7D","HHExpFFats_Purch_MN_7D","HHExpFDairy_Purch_MN_7D",
"HHExpFEgg_Purch_MN_7D","HHExpFSgr_Purch_MN_7D","HHExpFCond_Purch_MN_7D",
"HHExpFBev_Purch_MN_7D","HHExpFOut_Purch_MN_7D"
)

food_gift_7d <- c(
"HHExpFCer_GiftAid_MN_7D","HHExpFTub_GiftAid_MN_7D","HHExpFPuls_GiftAid_MN_7D",
"HHExpFVeg_GiftAid_MN_7D","HHExpFFrt_GiftAid_MN_7D","HHExpFAnimMeat_GiftAid_MN_7D",
"HHExpFAnimFish_GiftAid_MN_7D","HHExpFFats_GiftAid_MN_7D","HHExpFDairy_GiftAid_MN_7D",
"HHExpFEgg_GiftAid_MN_7D","HHExpFSgr_GiftAid_MN_7D","HHExpFCond_GiftAid_MN_7D",
"HHExpFBev_GiftAid_MN_7D","HHExpFOut_GiftAid_MN_7D"
)

food_own_7d <- c(
"HHExpFCer_Own_MN_7D","HHExpFTub_Own_MN_7D","HHExpFPuls_Own_MN_7D",
"HHExpFVeg_Own_MN_7D","HHExpFFrt_Own_MN_7D","HHExpFAnimMeat_Own_MN_7D",
"HHExpFAnimFish_Own_MN_7D","HHExpFFats_Own_MN_7D","HHExpFDairy_Own_MN_7D",
"HHExpFEgg_Own_MN_7D","HHExpFSgr_Own_MN_7D","HHExpFCond_Own_MN_7D",
"HHExpFBev_Own_MN_7D","HHExpFOut_Own_MN_7D"
)

# -----------------------------
# 1) Non-food expenditure inputs (1M recall + 6M recall)
# Purchases (cash/credit) and GiftAid both used in monitoring ECMEN
# -----------------------------
nf_purch_1m <- c(
"HHExpNFHyg_Purch_MN_1M","HHExpNFTransp_Purch_MN_1M","HHExpNFFuel_Purch_MN_1M",
"HHExpNFWat_Purch_MN_1M","HHExpNFElec_Purch_MN_1M","HHExpNFEnerg_Purch_MN_1M",
"HHExpNFDwelSer_Purch_MN_1M","HHExpNFPhone_Purch_MN_1M","HHExpNFRecr_Purch_MN_1M",
"HHExpNFAlcTobac_Purch_MN_1M"
)

nf_gift_1m <- c(
"HHExpNFHyg_GiftAid_MN_1M","HHExpNFTransp_GiftAid_MN_1M","HHExpNFFuel_GiftAid_MN_1M",
"HHExpNFWat_GiftAid_MN_1M","HHExpNFElec_GiftAid_MN_1M","HHExpNFEnerg_GiftAid_MN_1M",
"HHExpNFDwelSer_GiftAid_MN_1M","HHExpNFPhone_GiftAid_MN_1M","HHExpNFRecr_GiftAid_MN_1M",
"HHExpNFAlcTobac_GiftAid_MN_1M"
)

nf_purch_6m <- c(
"HHExpNFMedServ_Purch_MN_6M","HHExpNFMedGood_Purch_MN_6M","HHExpNFCloth_Purch_MN_6M",
"HHExpNFEduFee_Purch_MN_6M","HHExpNFEduGood_Purch_MN_6M","HHExpNFRent_Purch_MN_6M",
"HHExpNFHHSoft_Purch_MN_6M","HHExpNFHHMaint_Purch_MN_6M"
)

nf_gift_6m <- c(
"HHExpNFMedServ_GiftAid_MN_6M","HHExpNFMedGood_GiftAid_MN_6M","HHExpNFCloth_GiftAid_MN_6M",
"HHExpNFEduFee_GiftAid_MN_6M","HHExpNFEduGood_GiftAid_MN_6M","HHExpNFRent_GiftAid_MN_6M",
"HHExpNFHHSoft_GiftAid_MN_6M","HHExpNFHHMaint_GiftAid_MN_6M"
)

# Set these to your actual names if different
hh_size_var <- "HHSize" # household size
meb_var <- "MEB" # per-capita MEB
smeb_var <- "sMEB" # per-capita SMEB (optional)

# -----------------------------
# 2) Convert NA to 0 for expenditure inputs
# -----------------------------
all_inputs <- c(food_purch_7d, food_gift_7d, food_own_7d,
nf_purch_1m, nf_gift_1m, nf_purch_6m, nf_gift_6m)

df <- df %>%
mutate(across(all_of(all_inputs), ~ as.numeric(.x))) %>%
mutate(across(all_of(all_inputs), ~ dplyr::coalesce(.x, 0)))

# -----------------------------
# 3) Compute monthly food totals by source (7D -> 1M with 30/7)
# -----------------------------
df <- df %>%
mutate(
HHExp_Food_Purch_MN_1M = rowSums(across(all_of(food_purch_7d))) * (30/7),
HHExp_Food_GiftAid_MN_1M = rowSums(across(all_of(food_gift_7d))) * (30/7),
HHExp_Food_Own_MN_1M = rowSums(across(all_of(food_own_7d))) * (30/7)
)

# -----------------------------
# 4) Compute monthly non-food totals (purchases + gift/aid)
# 30D + (6M/6)
# -----------------------------
df <- df %>%
mutate(
HHExpNFTotal_Purch_MN_30D = rowSums(across(all_of(nf_purch_1m))),
HHExpNFTotal_Purch_MN_6M = rowSums(across(all_of(nf_purch_6m))),
HHExpNFTotal_Purch_MN_1M = HHExpNFTotal_Purch_MN_30D + (HHExpNFTotal_Purch_MN_6M / 6),

HHExpNFTotal_GiftAid_MN_30D = rowSums(across(all_of(nf_gift_1m))),
HHExpNFTotal_GiftAid_MN_6M = rowSums(across(all_of(nf_gift_6m))),
HHExpNFTotal_GiftAid_MN_1M = HHExpNFTotal_GiftAid_MN_30D + (HHExpNFTotal_GiftAid_MN_6M / 6)
)

# -----------------------------
# 5) Household economic capacity (MONITORING, including assistance)
# Food: Purch + GiftAid + Own
# Non-food: Purch + GiftAid
# -----------------------------
df <- df %>%
mutate(
HHExpF_ECMEN = HHExp_Food_Purch_MN_1M + HHExp_Food_GiftAid_MN_1M + HHExp_Food_Own_MN_1M,
HHExpNF_ECMEN = HHExpNFTotal_Purch_MN_1M + HHExpNFTotal_GiftAid_MN_1M,
HHExp_ECMEN = HHExpF_ECMEN + HHExpNF_ECMEN
)

# -----------------------------
# 6) Per-capita economic capacity
# -----------------------------
df <- df %>%
mutate(
PCExp_ECMEN = HHExp_ECMEN / .data[[hh_size_var]]
)

# -----------------------------
# 7) ECMEN classification vs MEB (per-capita)
# -----------------------------
df <- df %>%
mutate(
ECMEN_inclAsst = if_else(
!is.na(PCExp_ECMEN) & !is.na(.data[[meb_var]]),
as.integer(PCExp_ECMEN > .data[[meb_var]]),
NA_integer_
)
)

df <- df %>%
mutate(
ECMEN_inclAsst = factor(
ECMEN_inclAsst,
levels = c(0, 1),
labels = c("Below MEB", "Above MEB")
)
)

print(table(df$ECMEN_inclAsst, useNA = "ifany"))

# -----------------------------
# 8) Optional SMEB version (if SMEB exists)
# -----------------------------
if (smeb_var %in% names(df)) {
df <- df %>%
mutate(
ECMEN_inclAsst_SMEB = if_else(
!is.na(PCExp_ECMEN) & !is.na(.data[[smeb_var]]),
as.integer(PCExp_ECMEN > .data[[smeb_var]]),
NA_integer_
)
)

df <- df %>%
mutate(
ECMEN_inclAsst_SMEB = factor(
ECMEN_inclAsst_SMEB,,
levels = c(0, 1),
labels = c("Below MEB", "Above MEB")
)
)


print(table(df$ECMEN_inclAsst_SMEB, useNA = "ifany"))
}