Table 6

Difference-in-Difference Estimates for the Effect of Mobile Money on Health Investments

Preventative Health ExpenditureBed Net Use
VariablesIndicatorln Health ExpenditureUntreatedTreated
(1)(2)(3)(4)
Mobile money

−0.003

(0.007)

−0.031

(0.105)

0.044

(0.129)

−0.027

(0.166)

Rainfall shock

0.003***

(0.001)

0.048***

(0.019)

0.018

(0.023)

0.062**

(0.027)

Interaction (MM × RS)

−0.023***

(0.009)

−0.340***

(0.128)

−0.104

(0.070)

−0.119

(0.087)

Overall effect

−0.020***

(0.008)

−0.292***

(0.114)

−0.086*

(0.050)

−0.057

(0.066)

Mean outcome0.003-6.9680.7070.511
Individual fixed effectsYesYesYesYes
Year fixed effectsYesYesYesYes
ControlsYesYesYesYes
Observations14,99414,99413,18813,188
R-squared0.0100.0090.0200.028
  • Notes: The entries of the table report the DiD coefficients of mobile money, rainfall shock, and their interaction term on health expenditure and bed net use. The entries in Column 1 present the coefficients from a linear probability model on an indicator variable for preventative health expenditure; entries in Column 2 are from a linear regression on log preventative healthcare expenditure. The preventative health expenditure indicator in Column 1 takes a value of one if an individual spends a positive amount on preventative health in the four weeks prior to the survey, and zero otherwise. Preventative health expenditure in Column 2 is calculated as the natural logarithm of real preventative health expenditure (in thousand Tanzanian shillings). Results in Columns 3 and 4 represent estimated coefficients for indicators of bed net use and treated bed net use. The bed net use question refers to sleeping under bed net the night before the survey. See notes in Table 3 (Column 2) for the specification and the set of controls used in the estimations. Robust standard errors, clustered at the enumeration area, are reported in parentheses. Significance: p < 0.10, **p < 0.05, ***p < 0.01.