Table 7 Selection into Sickness and Symptoms
Acute Illness Beginning = 14
Before Survey Fever
Symptoms Cough
Symptoms Headache
Symptoms Days of rainfall × no facility
0.00167 −0.0112
−0.00176 −0.00886
0.00421 0.00711
0.00702 0.00621
No facility −0.0713
0.162 0.0742
−0.104 0.0565
0.109 0.0891
0.0749 Days of rainfall
0.0125 −0.0273
0.0475 0.0215
0.0226 0.0454
0.0370 0.0286
Observations 7,094
1,954 1,954
1,954 Mean of dependent variable
0.276 0.367
0.280 0.266
Notes: Robust standard errors in parentheses p 0.01, p 0.05, p 0.1. See Table II for addi- tional comments. Sample in Column 1 not restricted by acute illness; analysis conducted on all children
aged 7–19 inclusive.
order to check for this selection into reporting acute illness, we first regress the incidence of sickness using a binary variable for reporting an illness which began
in the past 14 days on the full set of regressors including the interaction instrument in a linear probability OLS regression. The results from this regression are reported
in Column 1 of Table 7, and verify that the instrument does not predict selection into the sample.
In Columns 2–4, we report results from the regressions of binaries for the re- porting of fever symptoms, cough, and headaches, respectively, on the instrument
and the usual set of controls. Again, we find no significant effects of the instrument on the probability of reporting specific symptoms. These results provide further
evidence that the instrument is orthogonal to illness severity and heterogeneous severity thresholds for reporting illness.
Finally, in Table 8 we report first- and second-stage regression results from spec- ifications identical to those reported in Tables II and III, but with the symptom
binaries as additional controls. The results appear quite robust to the inclusion of these additional controls. That is, there does not seem to be any evidence that se-
lection into sickness or symptoms is driving the results.
D. Instrument Checks
The main reason we use an interaction instrument is that it improves on using facility existence alone as an instrument for healthcare choice, since, as mentioned earlier,
endogenous allocation of health facilities to communities on the basis of the com- munity’s health stock would render invalid facility existence as an instrument. Here,
we present evidence that this important distinction is relevant in our context.
The Journal
of Human
Resources
Table 8 Robustness to Inclusion of Symptom Controls
First Stage Second-stage IV
Whole Sample
Enrolled Sample
Health Schooling
Labor
Formal Healthcare Still Ill
School Hours Last Week
Any School Last Week
Days Last Week
Hours per Day Last
Week Farm
Labor Nonfarm
Labor Formal healthcare
−0.860 33.76
0.841 4.520
1.344 13.63
3.089 0.483
18.10 0.506
2.569 2.001
13.06 9.623
Days of rainfall × no facility −0.0173
−0.0224 0.00600
0.00816 Fever symptoms
0.142 0.151
0.0451 −5.913
−0.139 −0.826
−0.107 −2.840
−0.807 0.0229
0.0268 0.0739
3.048 0.0861
0.429 0.319
1.925 1.350
Cough symptoms −0.0613
−0.0633 0.0294
1.335 0.0299
0.185 0.0698
1.211 1.346
0.0223 0.0275
0.0403 1.577
0.0410 0.216
0.138 0.880
0.820 Headache symptoms
0.0474 0.0651
−0.0551 −2.748
−0.0613 −0.400
−0.0369 −0.750
−0.467 0.0243
0.0297 0.0401
1.693 0.0449
0.238 0.155
0.908 0.786
F -test: rain × distance = 0
8.359 7.549
Prob F 0.00420
0.00651 Observations
1,954 1,224
1,953 1,224
1,224 1,224
1,010 1,954
1,954 Mean of dependent variable
0.226 0.242
0.367 23.51
0.825 3.559
6.604 8.748
12.68 Notes: Robust standard errors in parentheses p 0.01, p 0.05, p 0.1. For Columns 1, 3, 6–7, refer to Table II for additional comments. For Columns 2,
4–5, refer to Table 3 for additional comments. Samples are restricted to all individuals aged 7–19 inclusive who reported being ill in the two weeks prior to survey. The sample on which the regression reported in Columns 2, 4–5 are run is further restricted to individuals aged 7–19 inclusive who also reported being enrolled in
school.
First, we regress indicators for various chronic illnesses on the facility existence variable alone along with the full set of controls used across all specifications. The
results, reported in Columns 1–4 of Table 9, show that we fail to accept that facility existence is not correlated with measures of chronic illness in the nonacutely ill
population. In particular, in Columns 2 and 3 we see that facility existence is a positive predictor of chronic rash at the 10 percent level of significance and a neg-
ative predictor of chronic fever at the 5 percent level.
Second, we include the interaction term along with the main effects and the full set of controls, and verify that the interaction instrument, in contrast, is not signifi-
cantly correlated with chronic illness measures. These results are reported in Col- umns 5–8 of Table 9. The results indicate that the instrument is not, in fact, a
predictor of measures of chronic illness at conventional levels of statistical signifi- cance.
E. First-Stage Robustness
