1 Changes from previous version

  • Added section of variable descriptions so that I don’t forget what each variable means
  • Modified the coverage regressions:
    • Added regression of coverage on GDP growth, digital ID coverage, and log GDP
    • For regressions which use dig_reg restricted sample to countries with coverage > 0. (That way our regression is not just picking up on whether a country expanded cts.)

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 Table 2 - Coverage regressions

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

Dependent variable:
coverage
(1) (2) (3) (4) (5) (6) (7) (8)
rGDPg2020 -0.020*** -0.007 -0.011* -0.011* -0.006 -0.010* -0.008 -0.005
(0.006) (0.006) (0.006) (0.006) (0.007) (0.005) (0.005) (0.006)
dig_id 0.002** -0.0005
(0.001) (0.001)
log_gdp 0.208*** 0.103** 0.081*
(0.032) (0.046) (0.043)
dig_reg 0.319*** 0.317*** 0.235***
(0.074) (0.063) (0.083)
eap 0.266*** 0.228** 0.305*** 0.252***
(0.089) (0.092) (0.083) (0.089)
dig_xcheck 0.375*** 0.380*** 0.282***
(0.063) (0.053) (0.084)
Constant 0.077 -1.446*** 0.156*** 0.107*** -0.716** 0.123*** 0.083*** -0.550*
(0.071) (0.219) (0.047) (0.041) (0.342) (0.030) (0.025) (0.318)
Observations 82 81 67 67 67 82 82 81
R2 0.224 0.472 0.351 0.469 0.521 0.468 0.590 0.615
Adjusted R2 0.204 0.452 0.330 0.444 0.490 0.455 0.575 0.594
Residual Std. Error 0.275 (df = 79) 0.229 (df = 77) 0.252 (df = 64) 0.230 (df = 63) 0.220 (df = 62) 0.228 (df = 79) 0.201 (df = 78) 0.197 (df = 76)
F Statistic 11.406*** (df = 2; 79) 22.952*** (df = 3; 77) 17.282*** (df = 2; 64) 18.575*** (df = 3; 63) 16.874*** (df = 4; 62) 34.769*** (df = 2; 79) 37.489*** (df = 3; 78) 30.305*** (df = 4; 76)
Note: p<0.1; p<0.05; p<0.01

4 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)
coverage -0.012 -0.002 -0.014
(0.008) (0.008) (0.010)
log_gdp -0.006* -0.006** -0.007**
(0.003) (0.003) (0.003)
rGDPg2020 -0.0001 -0.0003
(0.001) (0.001)
Constant 0.027*** 0.073** 0.027*** 0.076*** 0.083***
(0.005) (0.028) (0.005) (0.026) (0.029)
Observations 61 61 60 61 60
R2 0.041 0.090 0.044 0.089 0.095
Adjusted R2 0.024 0.058 0.010 0.073 0.063
Residual Std. Error 0.018 (df = 59) 0.018 (df = 58) 0.019 (df = 57) 0.018 (df = 59) 0.018 (df = 57)
F Statistic 2.493 (df = 1; 59) 2.860* (df = 2; 58) 1.301 (df = 2; 57) 5.755** (df = 1; 59) 2.977* (df = 2; 57)
Note: p<0.1; p<0.05; p<0.01

5 Table 4 - Spending regressions

The dependent variable is spending as a share of GDP.

Dependent variable:
spending
(1) (2) (3) (4)
dig_id -0.00002
(0.00004)
dig_reg -0.002 -0.002
(0.003) (0.003)
log_gdp 0.004*** 0.004** 0.004**
(0.001) (0.002) (0.002)
non_ct_spending 0.088 0.093 0.093
(0.073) (0.076) (0.079)
rGDPg2020 -0.0003** 0.00000
(0.0002) (0.0002)
Constant -0.024*** 0.006*** -0.027** -0.027**
(0.007) (0.001) (0.012) (0.013)
Observations 60 60 60 60
R2 0.200 0.046 0.199 0.199
Adjusted R2 0.157 0.029 0.156 0.141
Residual Std. Error 0.008 (df = 56) 0.008 (df = 58) 0.008 (df = 56) 0.008 (df = 55)
F Statistic 4.668*** (df = 3; 56) 2.789 (df = 1; 58) 4.634*** (df = 3; 56) 3.414** (df = 4; 55)
Note: p<0.1; p<0.05; p<0.01