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**<u>Table 9. Fixed-effect panel regression on livestock and nonagricultural income</u>**

||<br>Livesto<br>Coef.|<br>ck income<br>Std.Err.|<br>Livesto<br>Coef.|<br>ck income<br>Std.Err.|<br>NonAG<br>Coef.|<br>income<br>Std.Err.|NonAG<br>Coef.|income<br>Std.Err.|
|---|---|---|---|---|---|---|---|---|
|D<sup>RSDP2km</sup><br>|-0.638|(0.304) **|0.564|(0.997)|<sup>2.018</sup>|<sup>(0.396) ***</sup>|<sup>-1.105</sup>|<sup>(0.982)</sup>|
|D<sup>URRAP2km</sup><br>|0.119<br>|(0.325)|<sup>0.206</sup>|<sup>(0.325)</sup>|<sup>-1.414</sup>|<sup>(0.379) ***</sup>|<sup>-1.640</sup>|<sup>(0.383) ***</sup>|
|D<sup>RSDP2km</sup>•D<sup>URRAP2km</sup>|||-1.425|(1.010)|||3.701|(1.042) ***|
|ln_L_|0.166|(0.091) *|0.168|(0.091) *|0.160|(0.109)|<sup>0.155</sup>|<sup>(0.109)</sup>|
|ln_G_|0.056|(0.094)|<sup>0.056</sup>|<sup>(0.094)</sup>|||||
|ln_SIZE_|0.332|(0.265)|<sup>0.347</sup>|<sup>(0.264)</sup>|<sup>0.421</sup>|<sup>(0.320)</sup>|<sup>0.383</sup>|<sup>(0.319)</sup>|
|ln_MALE_|0.472|(0.353)|<sup>0.471</sup>|<sup>(0.352)</sup>|<sup>-0.475</sup>|<sup>(0.417)</sup>|<sup>-0.472</sup>|<sup>(0.415)</sup>|
|ln_AGE_|0.684|(0.464)|<sup>0.698</sup>|<sup>(0.464)</sup>|<sup>-0.646</sup>|<sup>(0.502)</sup>|<sup>-0.681</sup>|<sup>(0.501)</sup>|
|EDU2|-0.175|(0.364)|<sup>-0.169</sup>|<sup>(0.364)</sup>|<sup>-0.087</sup>|<sup>(0.430)</sup>|<sup>-0.102</sup>|<sup>(0.430)</sup>|
|EDU3|-0.612|(0.369) *|-0.613|(0.369) *|0.919|(0.455) **|0.919|(0.453) **|
|EDU4|-0.440|(0.683)|<sup>-0.440</sup>|<sup>(0.682)</sup>|<sup>1.463</sup>|<sup>(0.699) **</sup>|1.463|(0.697) **|
|EDU5|-0.973|(0.398) **|-0.975|(0.401) **|0.507|(0.560)|<sup>0.512</sup>|<sup>(0.553)</sup>|
|EDU6|-1.648|(0.546) ***|-1.667|(0.545) ***|<br>1.339|(0.757) *|1.388|(0.748) *|
|EDU7|0.000|(0.533)|<sup>-0.006</sup>|<sup>(0.533)</sup>|<sup>0.181</sup>|<sup>(0.542)</sup>|<sup>0.196</sup>|<sup>(0.543)</sup>|
|COOK|-0.537|(0.403)|<sup>-0.523</sup>|<sup>(0.403)</sup>|<sup>0.355</sup>|<sup>(0.445)</sup>|<sup>0.319</sup>|<sup>(0.443)</sup>|
|LIGH|-0.597|(0.331) *|-0.607|(0.331) *|1.597|(0.422) ***|1.621|(0.420) ***|
|T2013|2.134|(0.240) ***|<br>2.125|(0.239) ***|<br>4.909|(0.296) ***|4.933|(0.297) ***|
|T2014|2.270|(0.270) ***|<br>2.255|(0.269) ***|<br>4.649|(0.308) ***|4.688|(0.308) ***|
|T2015|2.109|(0.280) ***|<br>2.104|(0.280) ***|<br>6.529|(0.323) ***|6.541|(0.324) ***|
|T2016|2.140|(0.305) ***|<br>2.102|(0.305) ***|<br>6.110|(0.335) ***|6.210|(0.338) ***|
|Constant|-7.580|(1.867)***|-7.652|(1.865)***|0.788|(1.920)|0.986|(1.917)|
|Obs.|4639||4639||4639||4639||
|No. of groups|1004||1004||1004||1004||
|R-square|||||||||
|within|0.0406||0.0412||0.1861||0.189||
|between|0.2514||0.2507||0.2791||0.2785||
|overall|0.1145||0.1164||0.1912||0.1949||
|F-stat.|8.8||8.39||38.2||37.32||

The dependent variable is the log of livestock or nonagricultural income. Robust standard errors are shown in parentheses. *, ** and *** indicate the statistical significance at the 10, 5 and 1 percent, respectively.

To investigate the indirect effects of improved road accessibility more deeply, two additional pieces of data are used, which were collected together with the household surveys. First, the demand for transport services is estimated from passenger survey data. Note that the surveyed passengers may not be the same persons over time, although the surveys were carried out at the same locations that are normally village centers where formal and informal transport services are offered. Thus, the data are cross-sectional at five periods of time and reflect overall demand for transport.