1 Changes from previous version

  • Replace per capita GDP growth 2020 with change in forecasted 2020 GDP per capita growth between Jan 2020 and June 2020.

2 Variable descriptions

Variable Description
coverage % pop living in hh reached by COVID-19 cash transfer
spending Total marginal spending on COVID-19 cash transfers as % GDP
spending_pc Marginal COVID-19 cash transfer spending as share of GDP per capita (ratio of spending over coverag)
pre_coverage % pop receiving cash transfers prior to COVID-19
pre_spending Spending on cash transfers as share of GDP prior to COVID
dig_reg Dummy for whether existing databases used for horizontal expansion
fsi Public service delivery component (P2) of Fragile States Index
non_ct_spending Total COVID-19 spending (excluding spending on cash transfers) as share of GDP
dig_id % pop with a digital ID
dig_xcheck Use of digital ID for cross-checking databases
deaths Total COVID-19 deaths per million up to 31-12-2020
region Country region
eap Dummy for region == East Asia and Pacific
atm Number of ATMs per 100,000 adults
soc_reg_coverage % population included in a social registry
pop_2018 Country population in 2018
rGDPg2020 Real GDP growth per capita in 2020
gdp_per_capita GDP per capita, PPP (constant 2011 international $)
log_gdp Log of GDP per capita

3 Correlation matrix of digital ID vars

##              dig_reg    dig_id dig_xcheck
## dig_reg    1.0000000 0.4794406  0.8617094
## dig_id     0.4794406 1.0000000  0.4521009
## dig_xcheck 0.8617094 0.4521009  1.0000000

4 Coverage regressions

In the regressions below the dependent variable is the share of the population in a household that received a COVID-19 cash transfer.

4.1 OLS

Dependent variable:
coverage
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
delta_2020 -0.014 -0.022 -0.021 -0.005 -0.020** -0.020** -0.010 -0.015 -0.014 -0.009
(0.010) (0.015) (0.014) (0.011) (0.010) (0.008) (0.010) (0.011) (0.010) (0.010)
dig_id 0.001 0.002** -0.0002
(0.001) (0.001) (0.001)
eap 0.285*** 0.140 0.253** 0.194* 0.261*** 0.216**
(0.108) (0.097) (0.099) (0.100) (0.086) (0.092)
log_gdp 0.195*** 0.114** 0.082
(0.032) (0.047) (0.051)
dig_reg 0.328*** 0.335*** 0.228***
(0.067) (0.059) (0.086)
dig_xcheck 0.353*** 0.362*** 0.273***
(0.063) (0.056) (0.094)
Constant 0.209*** 0.132 0.022 -1.364*** 0.056 0.011 -0.852*** 0.101 0.055 -0.568
(0.068) (0.117) (0.089) (0.228) (0.054) (0.055) (0.326) (0.063) (0.066) (0.365)
Observations 83 65 65 65 65 65 65 65 65 65
R2 0.021 0.062 0.181 0.408 0.335 0.436 0.503 0.387 0.494 0.521
Adjusted R2 0.009 0.032 0.140 0.369 0.314 0.409 0.470 0.367 0.469 0.490
Residual Std. Error 0.303 (df = 81) 0.296 (df = 62) 0.279 (df = 61) 0.239 (df = 60) 0.249 (df = 62) 0.232 (df = 61) 0.219 (df = 60) 0.240 (df = 62) 0.220 (df = 61) 0.215 (df = 60)
F Statistic 1.754 (df = 1; 81) 2.051 (df = 2; 62) 4.487*** (df = 3; 61) 10.341*** (df = 4; 60) 15.643*** (df = 2; 62) 15.737*** (df = 3; 61) 15.211*** (df = 4; 60) 19.539*** (df = 2; 62) 19.818*** (df = 3; 61) 16.348*** (df = 4; 60)
Note: p<0.1; p<0.05; p<0.01

4.2 Linear regression diagnostics

Plot suggested by Alan for a regression of coverage on delta_2020, dig_id, eap, and log_gdp.

4.3 Fractional regression

Dependent variable:
coverage
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
delta_2020 -0.064 -0.118** -0.121** -0.048 -0.113** -0.114*** -0.071 -0.091 -0.093* -0.063
(0.046) (0.059) (0.056) (0.051) (0.047) (0.042) (0.048) (0.055) (0.051) (0.055)
dig_id 0.014* 0.018*** 0.001
(0.008) (0.006) (0.006)
eap 1.670*** 0.818* 1.500** 1.133** 1.608*** 1.247**
(0.569) (0.442) (0.596) (0.522) (0.491) (0.496)
log_gdp 1.185*** 0.737*** 0.606**
(0.191) (0.239) (0.269)
dig_reg 2.054*** 2.125*** 1.420***
(0.384) (0.353) (0.484)
dig_xcheck 2.055*** 2.178*** 1.474***
(0.340) (0.318) (0.524)
Constant -1.270*** -2.652*** -3.217*** -11.670*** -2.736*** -3.026*** -8.734*** -2.446*** -2.790*** -7.483***
(0.322) (0.668) (0.502) (1.464) (0.377) (0.403) (1.689) (0.397) (0.451) (1.921)
Observations 83 80 80 80 80 80 80 80 80 80
Log Likelihood -48.111 -44.213 -39.995 -32.356 -37.652 -34.286 -30.967 -35.267 -31.357 -29.914
Akaike Inf. Crit. 100.222 94.427 87.991 74.713 81.304 76.572 71.933 76.534 70.714 69.828
Note: p<0.1; p<0.05; p<0.01

Regression diagnostics for fractional regresssion.

5 Table 3 - Average benefit regressions

The dependent variable is the average benefit size divided by GDP (calculated by dividing spending as a share of GDP divided by coverage).

Dependent variable:
avg_ben
(1) (2) (3) (4) (5)
delta_2020 -0.00003 0.001 0.0003 0.0001 0.0003
(0.001) (0.001) (0.001) (0.001) (0.001)
non_ct_spending 0.064 0.067 0.067 0.139
(0.111) (0.098) (0.099) (0.106)
dig_xcheck -0.013*** -0.010* -0.011*
(0.005) (0.006) (0.006)
log_gdp -0.002 -0.002
(0.004) (0.005)
regionECA 0.010
(0.006)
regionLAC 0.001
(0.006)
regionMENA 0.020**
(0.009)
regionSAR 0.004
(0.009)
regionSSA 0.003
(0.007)
Constant 0.023*** 0.026*** 0.029*** 0.048 0.043
(0.007) (0.006) (0.006) (0.032) (0.039)
Observations 68 60 60 60 60
R2 0.00001 0.011 0.128 0.135 0.225
Adjusted R2 -0.015 -0.024 0.081 0.072 0.085
Residual Std. Error 0.020 (df = 66) 0.019 (df = 57) 0.018 (df = 56) 0.018 (df = 55) 0.018 (df = 50)
F Statistic 0.001 (df = 1; 66) 0.312 (df = 2; 57) 2.735* (df = 3; 56) 2.138* (df = 4; 55) 1.610 (df = 9; 50)
Note: p<0.1; p<0.05; p<0.01

6 Table 4 - Spending regressions

The dependent variable is spending as a share of GDP.

Dependent variable:
spending
(1) (2) (3) (4) (5)
delta_2020 -0.001 -0.0005 -0.0003 -0.0004 -0.0001
(0.0004) (0.0004) (0.0004) (0.0004) (0.0003)
dig_xcheck 0.004** 0.003 0.003* -0.001
(0.002) (0.002) (0.002) (0.004)
non_ct_spending 0.099 0.070 0.081
(0.079) (0.068) (0.068)
eap 0.005** 0.003
(0.003) (0.003)
log_gdp 0.003*
(0.002)
Constant 0.003 0.002 0.001 0.0003 -0.023*
(0.002) (0.002) (0.002) (0.002) (0.013)
Observations 77 76 68 68 68
R2 0.035 0.094 0.156 0.205 0.261
Adjusted R2 0.022 0.069 0.116 0.154 0.202
Residual Std. Error 0.008 (df = 75) 0.008 (df = 73) 0.008 (df = 64) 0.008 (df = 63) 0.007 (df = 62)
F Statistic 2.734 (df = 1; 75) 3.783** (df = 2; 73) 3.943** (df = 3; 64) 4.057*** (df = 4; 63) 4.386*** (df = 5; 62)
Note: p<0.1; p<0.05; p<0.01