Table 3: Survey measurements, usual consumption and survey errors<sup>a</sup>

|||||**Sur**|**vey Err**|**ors**|
|---|---|---|---|---|---|---|
||**Measur**|**ements**|**Consumption**|**Mean**|**M**|**SE**|
||Diary|Recall||Recall|Diary|Recall|
||(1)|(2)|(3)|(4)|(5)|(6)|
|1st decile|4.7270|7.4550|7.1882|1.408|0.288|0.620|
|2nd decile|6.8615|9.7729|8.8986|1.356|0.267|0.512|
|3rd decile|8.5786|11.9128|10.3768|1.320|0.257|0.446|
|4th decile|10.3563|14.1222|11.8958|1.290|0.250|0.396|
|5th decile|12.4364|16.2122|13.4062|1.265|0.246|0.358|
|6th decile|14.7070|18.9989|15.2380|1.239|0.243|0.321|
|7th decile|17.5878|21.9847|17.3200|1.214|0.242|0.288|
|8th decile|21.7675|26.0026|20.3705|1.185|0.242|0.253|
|9th decile|29.4806|32.9604|25.2176|1.149|0.246|0.214|
|Mean|15.2130|18.6712|15.2050||||
|Gini index|0.3765|0.3143|0.2656||||

> a This table compares distributions of survey reports and usual consumption. Columns (1) considers data on _Y_<sup>_d_</sup> for all households. Columns (2) considers data on _Y_<sup>_r_</sup> for the _treatment sample_ – see note to Table 1 for definitions. Column (3) reports the estimated distribution of _Y_<sup>_∗_</sup> . Column (4) reports the estimated mean of _Y_<sup>_r_</sup> _/Y_<sup>_∗_</sup> conditional on deciles of _Y_<sup>_∗_</sup> at left. The mean of _Y_<sup>_d_</sup> _/Y_<sup>_∗_</sup> is not reported, and this is always one because of Assumption 1. Column (5) reports the Mean Squared Error (MSE) of _Y_<sup>_d_</sup> _/Y_<sup>_∗_</sup> conditional on deciles of _Y_<sup>_∗_</sup> at left. Column (6) shows the MSE of _Y_<sup>_r_</sup> _/Y_<sup>_∗_</sup> conditional on deciles of _Y_<sup>_∗_</sup> at left.

benchmark is less pronounced.

# **5 Errors in Survey Reports**

## **5.1 Diary and Recall Measurements**

The presumption that diaries outperform recall data for the measurement of well-being finds little empirical support. This can be seen in Figure 1, where diary and recall histograms are compared with the distribution of usual consumption, _fY ∗_ [ _y_ ] (the continuous line). The lower tail of the recall distribution is closer to that of usual consumption, and mismeasurement from diaries is more substantial at the bottom end. As diary measurements are centered at _Y_<sup>_∗_</sup> (because of Assumption 1), the difference in the modes of _fY ∗_ [ _y_ ] and _fY d_ [ _y_ ] suggests that diary errors must have a thick lower tail. Figure 1 also illustrates how the upper tail of the distribution of recall data is substantially thicker than the distribution of usual consumption, which is better approximated using data from diaries. These conclusions are confirmed by the first three columns of Table 3, where different percentiles of empirical and estimated distributions are compared. The bottom three deciles of the recall distribution are closer to the deciles of _Y_<sup>_∗_</sup> than are those of the diaries. The opposite conclusion applies for the remaining deciles. Consistent with predictions from the model in Section 2, the Gini coefficient from diaries overstates the real value of this index; the distance from the real value is minimized using recall data.

These findings have important implications for the computation of aggregate poverty statistics. This 19