# **Table A6: Robustness**

## **Coefficient estimates , standard errors in parentheses, p-values in braces**

||**A. Lea**<br>**Activ**<br>**(h/w**|**rning**<br>**ities**<br>**eek)**|**B. Leisu**<br>**Spent w**<br>**(h/w**|**re Time**<br>**ith Men**<br>**eek)**|**C. Out of**<br>**Wedlock**<br>**Pregnancy**|**D. Transactional**<br>**Sex**|
|---|---|---|---|---|---|---|
|**Age Cohort:**|**12-17**|**18-25**|**12-17**|**18-25**|**12-17**|**18-25**|
||**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|**(6)**|
|**Disruption Effect**|-12.2***|-2.37|1.27***|.620|.072*|-.002|
||(2.35)|(1.54)|(.444)|(.551)|(.039)|(.018)|
|**_Baseline, RI_**|{.003}|{.106}|{.037}|{.404}|{.064}|{.949}|
|**_Baseline, MHT_**|{.002}|{.526}|{.128}|{.730}|{.490}|{.896}|
|**_No controls_**|-12.7***|-4.16***|.966|.529|.064|-.014|
||(2.81)|(1.48)|(.595)|(532)|(.042)|(.017)|
|**_Baseline, within district disruption_**|-8.51**|.351|2.01***|.032|.100|.000|
|**_dummy_**|(3.42)|(2.22)|(.621)|(.546)|(.040)|(.022)|
|**_Baseline, alternative construction_**|-9.55***|-1.99|.886**|.793|.038|-.018|
|**_disruption dummy_**|(2.37)|(1.59)|(.396)|(.508)|(.036)|(.017)|
|**Treatment Effect in High Disruption**|9.69***|2.42*|-1.86***|-1.68***|-.075**|.054***|
||(2.61)|(1.41)|(.452)|(.475)|(.038)|(.021)|
|**_Baseline, RI_**|{.012}|{.154}|{.003}|{.004}|{.043}|{.098}|
|**_Baseline, MHT_**|{.015}|{.503}|{.009}|{.027}|{.416}|{.156}|
|**_No controls_**|8.72***|3.44**|-1.59***|-1.75***|-.066*|.054**|
||(3.02)|(1.39)|(.533)|(.466)|(.040)|(.022)|
|**_Baseline, within district disruption_**|7.46**|.140|-2.59**|-1.32**|-.131***|.047**|
|**_dummy_**|(3.41)|(2.29)|(.661)|(.530)|(.041)|(.023)|
|**_Baseline, alternative construction_**|7.08***|1.23|-1.49***|-1.73***|-.041|.058***|
|**_disruption dummy_**|(2.35)|(1.54)|(.384)|(.410)|(.033)|(.018)|
|**Treatment Effect in Low Disruption**|-2.96**|-.839|-.602***|-1.32***|-.010|.018|
||(1.30)|(.929)|(.211)|(.328)|(.017)|(.011)|
|**_Baseline, RI_**|{.062}|{.386}|{.012}|{.000}|{.583}|{.151}|
|**_Baseline, MHT_**|{.284}|{.730}|{.128}|{.009}|{.796}|{.526}|
|**_No controls_**|-4.12**|-1.77|-.505*|-1.33***|.001|.014|
||(1.72)|(1.19)|(.269)|(.326)|(.018)|(.011)|
|**_Baseline, within district disruption_**|-1.41|-.294|-.662***|-1.43***|-.010|.021**|
|**_dummy_**|(1.41)|(.859)|(.188)|(.306)|(.016)|(.011)|
|**_Baseline, alternative construction_**|-3.71**|-.659|-.596**|-1.31***|-.012|.013|
|**_disruption dummy_**|(1.43)|(.938)|(.233)|(.342)|(.017)|(.012)|
|**_F-statistic [p-value], Baseline_**|{.000}|{.280}|{.000}|{.000}|{.168}|{.022}|
|**Observations**|2,345|2,367|2,379|2,401|2,382|2,244|

**Notes:** ***, ** and * denote significance at the 1%, 5%, and 10% levels. Respondents were provided a set of 25 beads and a board with 6 circles representing: "Education", "IGA", "Leisure", "Household Chores", "Sleep" and "Other". The Learning category includes schooling, vocational training and study time. "IGA" includes paid and unpaid work of any kind. Respondent were then asked to allocate beads into each circle in a way that represents time allocation in an average day. Data points were later converted into weekly hours. Estimates obtained from a system of SUR using all time use categories excluding "other". ITT effects estimated via SUR on all time use categories excluding "other". A similar approach is used to estimate ITTs for time spent with men, which was recorded together with other forms of leisure. The exact phrasing for the "Men" category is, "With boys or men you have a sexual relationship with". Transactional Sex is defined as, "Receiving anything such as money, gifts, help with school work or something else in exchange for sexual intercourse." Control variables include: age, PPI score, household size, illiteracy, village size (nr of dwellings), village average PPI score, distances form key facilities (clinic, secondary school and market), a dummy equal to one if the village is a political stronghold (i.e. has a resident paramount and/or section chief), the number of NGOs active within the village before the Ebola outbreak (excluding BRAC), share of Christian households, distance from Freetown and distance from Kailahun. All specifications control for baseline values of the outcome, with Column 5 controlling for any pregnancy at baseline. All specifications include dummies for the randomization strata (district), and errors are clustered at the community level. Randomization Inference preformed by comparing the parameters from benchmark specifications to the estimated distribution of each parameter under the null hypothesis of ELA's ITT being zero (β2=β3=0). To estimate this distribution, treatment villages are randomly resampled with probability equal to the original treatment allocation, and parameters estimated using these placebo treatments (1,000 permutations). Reported p-values test the null hypothesis of the parameters being zero using this empirically estimated parameter distribution. P-values adjusted for multiple hypothesis testing are computed using the step-down procedure of Romano and Wolf [2016] (1,000 bootstrap iteration) . The No Control rows control include baseline outcome values, district FE and standard errors are clustered at the village level. The last two robustness checks for each outcome employ different measures of disruptions. The first measure ("within district") is a dummy equal to 1 if the village is in the top quartile of the distribution of disruptions within each district, while the core measure of disruption is defined at the national level. The second measure ("alternative construction") also uses characteristics of local markets to construct the index. The F-test at the foot of each Column is reported for the null hypothesis of joint insignificance (β1=β2=β3=0).