**Table 4:** Sectoral Predictors of Rural Non-Farm Employment

||(1)<br>Farm|(2)<br>Farm<br>Labour|(3)<br>Manufacturing|(4)<br>Trade|(5)<br>Construction|(6)<br>Service|
|---|---|---|---|---|---|---|
|Female|.078<sup>_∗∗∗_</sup>|-.010|.014<sup>_∗∗_</sup>|-.025<sup>_∗∗∗_</sup>|-.041<sup>_∗∗∗_</sup>|-.023<sup>_∗∗∗_</sup>|
||(.009)|(.009)|(.006)|(.002)|(.004)|(.003)|
|Literate|-.085<sup>_∗∗∗_</sup>|-.111<sup>_∗∗∗_</sup>|.034<sup>_∗∗∗_</sup>|.023<sup>_∗∗∗_</sup>|.001|.030<sup>_∗∗∗_</sup>|
||(.005)|(.006)|(.004)|(.002)|(.002)|(.003)|
|Educated|-.148<sup>_∗∗∗_</sup>|-.118<sup>_∗∗∗_</sup>|-.005|.026<sup>_∗∗∗_</sup>|-.015<sup>_∗∗∗_</sup>|.104<sup>_∗∗∗_</sup>|
||(.006)|(.007)|(.003)|(.003)|(.002)|(.004)|
|Age|-.004<sup>_∗∗∗_</sup>|.001|-.002<sup>_∗∗∗_</sup>|.001<sup>_∗∗∗_</sup>|.001<sup>_∗∗∗_</sup>|.008<sup>_∗∗∗_</sup>|
||(.001)|(.001)|(.000)|(.000)|(.000)|(.000)|
|Sq. Age|.000<sup>_∗∗∗_</sup>|-.000<sup>_∗∗∗_</sup>|.000<sup>_∗∗∗_</sup>|-.000<sup>_∗∗_</sup>|-.000<sup>_∗∗∗_</sup>|-.000<sup>_∗∗∗_</sup>|
||(.000)|(.000)|(.000)|(.000)|(.000)|(.000)|
|SC/ST|.045<sup>_∗∗∗_</sup>|.150<sup>_∗∗∗_</sup>|-.020<sup>_∗∗∗_</sup>|-.024<sup>_∗∗∗_</sup>|.013<sup>_∗∗∗_</sup>|-.015<sup>_∗∗∗_</sup>|
||(.006)|(.008)|(.004)|(.002)|(.003)|(.003)|
|Muslim|-.092<sup>_∗∗∗_</sup>|-.025<sup>_∗∗_</sup>|.031<sup>_∗∗∗_</sup>|.044<sup>_∗∗∗_</sup>|.005|.011<sup>_∗_</sup>|
||(.015)|(.011)|(.010)|(.006)|(.005)|(.006)|
|Marginal Landowner|-.238<sup>_∗∗∗_</sup>|.250<sup>_∗∗∗_</sup>|.073<sup>_∗∗∗_</sup>|.045<sup>_∗∗∗_</sup>|.034<sup>_∗∗∗_</sup>|.075<sup>_∗∗∗_</sup>|
||(.007)|(.009)|(.004)|(.003)|(.003)|(.003)|
|Fraction rural|-.173<sup>_∗∗∗_</sup>|-.173<sup>_∗∗∗_</sup>|.095<sup>_∗∗∗_</sup>|.021|.002|.044<sup>_∗_</sup>|
||(.053)|(.051)|(.017)|(.017)|(.032)|(.024)|
|Fraction salaried workers|-.366<sup>_∗∗∗_</sup>|-.329<sup>_∗∗∗_</sup>|-.007|.012|-.037|.340<sup>_∗∗∗_</sup>|
||(.089)|(.104)|(.035)|(.027)|(.049)|(.049)|
|Fraction public employment|-.283<sup>_∗∗∗_</sup>|.083|-.033<sup>_∗_</sup>|-.015|.283<sup>_∗∗∗_</sup>|.052<sup>_∗_</sup>|
||(.066)|(.064)|(.017)|(.017)|(.050)|(.030)|
|Fraction manufacturing|-.647<sup>_∗∗∗_</sup>|-.215<sup>_∗∗∗_</sup>|.834<sup>_∗∗∗_</sup>|-.017|-.084<sup>_∗∗_</sup>|-.074<sup>_∗_</sup>|
||(.077)|(.078)|(.040)|(.026)|(.040)|(.040)|
|Fraction educated|-.015|.059|.068<sup>_∗∗∗_</sup>|-.001|-.052|.018|
||(.066)|(.091)|(.021)|(.023)|(.037)|(.036)|
|Branch per capita (Log)|-.034<sup>_∗∗_</sup>|-.034<sup>_∗∗_</sup>|.002|.011<sup>_∗∗_</sup>|.018<sup>_∗∗_</sup>|.006|
||(.013)|(.017)|(.004)|(.005)|(.008)|(.006)|
|Credit per capita (Log)|.026<sup>_∗_</sup>|.026|.009<sup>_∗_</sup>|-.006|-.026<sup>_∗∗∗_</sup>|-.003|
||(.015)|(.017)|(.005)|(.005)|(.010)|(.007)|
|Observations|453161|453161|453161|453161|453161|453161|
|R<sup>2</sup>|.21|.28|.08|.05|.06|.09|
|Dep Var Mean|.75|.32|.07|.04|.03|.08|

This table shows the impact of individual and district characteristics on rural non-farm employment by employment sector. The unit of observation is rural individuals aged 15-65, who participate in the labour force. Farm labour refers to workers who are employed as casual workers in the agricultural activities. Educated refers to individuals with secondary education or better. Maginal landowners are workers in households with less than 0.5 acres of land holding. Standard errors in parentheses, clustered by district.

45