reporting has no effect on the female employment rate, but decreases the male employment rate compared to self‐reporting, mainly because agricultural activities are underreported by proxy respondents. They do not find evidence that the proxy respondent’s sex affects measurement error. In other words, men or women do not systematically under‐ or overreport the employment status of household members of the opposite sex. Although the data are available, it was not reported whether the youth employment rate is sensitive to proxy reporting.<sup>20</sup> Table 3: Rate of proxy respondent use by LSMS‐ISA survey

|Country||Age Group: 15‐|24||Age Group: 15‐64||
|---|---|---|---|---|---|---|
||Overall|Male|Female|Overall|Male|Female|
|Malawi (2017)|64.1|72.2|56.7|45.0|55.1|36.1|
|Niger (2014)|44.8|43.1|46.5|42.0|37.8|45.6|
|Nigeria (2016)|34.1|35.3|32.7|24.2|27.9|20.9|
|Tanzania (2013)|35.3|42.9|28.1|24.1|30.3|18.3|
|Mali (2014)|99.0|98.2|99.8|84.9|70.5|98.1|
|Uganda (2014)|76.8|83.6|70.0|55.8|65.6|46.6|

Source: Based on the latest LSMS‐ISA round in each country. The only exception is Tanzania where the authors used the previous wave (2013) because the last wave (2015) did not include the proxy respondent question. Note: The gender difference in the rate of proxy respondent use in each country and age group is statistically significant at 1%, with the exception of Nigeria Age Group 15‐24 (5% significance), Mali Age Group 15‐24 (5% significance), Niger Age Group 15‐24 (10% significance).

Expanding Bardasi’s work to Nigeria, we explored the potential effects of proxy reporting on employment rate by sex and age. Using the previous and new definitions of employment, we observe striking differences between the self‐reported employment rate and the employment rate based on proxy reporting. Table 4 suggests that proxy respondents may underestimate the male and female employment rates in both age groups. Results are consistent regardless the definition of employment.

Table 4: The employment rate in Nigeria (2014) by sex and age, self‐reporting vis‐à‐vis proxy reporting

|||Youth Employ <br>|ment Rate(%)|||Adult Employ <br>|ment Rate(%)||
|---|---|---|---|---|---|---|---|---|
||Self‐<br>respondent|Proxy‐<br>respondent|Diff|Number of<br>observations|Self‐<br>respondent|Proxy‐<br>respondent|Diff|Number of<br>observations|
|**Old definition**|||||||||
|_Women_|43.96|26.21|17.75***|2,532|68|42.26|25.74***|7,703|
|_Men_|57.79|29.58|28.21***|2,919|74.6|50.8|23.8***|6,915|
|**Previous definition**|||||||||
|_Women_|20.36|12.68|7.68***|2,532|41.78|27.28|14.5***|7,703|
|_Men_|22.67|14.26|8.41***|2,919|45.55|33.94|11.61***|6,915|

Source: Based on 2013/14 Nigeria LSMS‐ISA data. Note: ***, ***,* indicate statistical significance at the 1%, 5% and 10% level.

> (own calculations). Hence, individuals who did not self‐report are less likely to be employed than individuals who self‐reported their activities. This is counterintuitive. One candidate explanation is underreporting by proxy respondents, as observed by Bardasi et al. (2011). An alternative explanation is that socioeconomic characteristics differ between the two groups. 20 The authors did test the sensitivity of child labor statistics to proxy reporting relative to self‐reports (Dillon et al., 2012). They did not observe significant differences.

20