include it here because in the next step of the analyses, the sample will be restricted to plots which were crop cut. In this case, parcel or household fixed effects reduce the sample size substantially, since not all households had at least two plots with a crop cut and even fewer parcels had more than one plot that was crop cut.<sup>17</sup> In sum, in the full sample, the plot-size IR based on self-reported yields is remarkably stable (Table 3) when examining differences in land productivity between large and small plots within a household (column 1), within the same parcel (column 2), or between households in the same enumeration area (column 3). This shows that the conventional hypotheses, notably missing markets or unobserved plot characteristics, do no explain the plot-size IR.

Table 4 (columns 1 to 3) presents the same regressions as Table 3, but limits the sample to plots that were crop cut. This reduces the sample size from over 25,000 observations to slightly over 5,000. The table (columns 4 to 6) also presents the results of the relation between plot size and crop cuts. The regression results show that the IR for self-reports continues to hold no matter what the level of fixed effects, although the relationship weakens in comparison to the results for the full sample. One explanation of the latter finding is that the IR in wave 2 appeared to be stronger on mixed-stand than on pure-stand plots.<sup>18</sup> Since pure-stand plots were more likely to be crop cut, restricting the sample to plots with crop cuts automatically weakens the IR for self-reports.

The IR disappears, however, if crop cuts are used as the dependent variable (Table 4, columns 4 to 6). This holds for each of the specifications with fixed effects separately for household, parcel and enumeration area. We even observe a positive and highly significant association between plot size and crop cuts in all specifications. Yields, as measured by crop cuts, increase by 10 percent if plot size doubles.

The regressions discussed so far have not included labor inputs, allowing our results to be comparable with previous IR studies, which lack data on labor input at the plot level. Controlling for labor input is, however, important in our study since crop-cut and self-reported

> 17 Pooling the waves, 1,405 households had at least two plots selected for a crop cut. Similarly, of the 3,822 parcels with a plot selected for crop cuts, 1,224 had at least two plots selected.

> 18 In wave 2, the IR for self-reports with household fixed effects was -0.381 on pure-stand plots, and - 0.492 on mixed-stand plots. In wave 1, the IR for self-reports was stronger on pure-stand (-0.308) than on mixed-stand plots (-0.215) but this finding must be interpreted carefully: because the area devoted to each crop in mixed-stand plots was not reported in wave 1, yields on mixed-stand plots were underestimated in that wave. Since we have many more observations on self-reported production in wave 2 than in wave 1, the results for the full sample are primarily driven by wave 2. When estimating the IR for crop cuts separately for pure-stand and mixed-stand plots, in both cases we observed a positive association between plot size and crop cuts. This shows that sample selection issues do not drive the IR for either self-reports or crop cuts.

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