Table 8 Machine Learning: Classification Analysis (CLAN)

||Total<br>|Total<br>|Outside<br>|Direct<br>|
|---|---|---|---|---|
||Consumption<br>(1)|Transactions<br>(2)|Transactions<br>(3)|Transactions<br>(4)|
|Female|-0.295|-0.851|-0.774|-0.854|
||[0.000]|[0.000]|[0.000]|[0.000]|
||(-0.373,-0.214)|(-0.904,-0.797)|(-0.839,-0.710)|(-0.926,-0.785)|
|Married|-0.016|-0.033|-0.022|-0.097|
||[1.000]|[0.975]|[1.000]|[0.224]|
||(-0.100,0.064)|(-0.123,0.060)|(-0.113,0.069)|(-0.215,0.023)|
|Dependent children|-0.079<br>|-0.158<br>|-0.201<br>|-0.335<br>|
||[0.224]|[0.004]|[0.000]|[0.000]|
||(-0.175,0.019)|(-0.258,-0.057)|(-0.300,-0.104)|(-0.462,-0.209)|
|Education|0.197|1.337|1.682|1.694|
||[0.330]|[0.000]|[0.000]|[0.000]|
||(-0.082,0.481)|(1.011,1.654)|(1.364,2.003)|(1.319,2.073)|
|Literate|0.095|0.236|0.380|0.301|
||[0.128]|[0.000]|[0.000]|[0.000]|
||(-0.006,0.195)|(0.141,0.331)|(0.289,0.472)|(0.172,0.430)|
|Digit span score|0.042|0.687|0.734|0.612|
||[1.000]|[0.000]|[0.000]|[0.000]|
||(-0.216,0.296)|(0.420,0.942)|(0.491,0.980)|(0.298,0.930)|
|Experience in current job, years|-0.832|1.109|0.231|0.650|
||[0.000]|[0.000]|[0.466]|[0.024]|
||(-1.199,-0.484)|(0.735,1.474)|(-0.151,0.604)|(0.141,1.163)|
|Expected tenure in job, years|0.753|0.484|-0.174|0.743|
||[0.000]|[0.012]|[0.585]|[0.001]|
||(0.413,1.073)|(0.146,0.801)|(-0.515,0.151)|(0.312,1.179)|
|Ever used mobile money|0.397|0.190|0.174|0.350|
||[0.000]|[0.000]|[0.000]|[0.000]|
||(0.313,0.481)|(0.102,0.276)|(0.089,0.257)|(0.241,0.460)|
|Income sharing|2.358<br>|6.065<br>|3.582<br>|14.04<br>|
||[0.797]|[0.042]|[0.371]|[0.000]|
||(-3.182,7.966)|(0.939,11.28)|(-1.742,8.772)|(6.841,21.09)|
|Basic expenditures control|0.189|0.418|0.340|0.573|
||[0.000]|[0.000]|[0.000]|[0.000]|
||(0.096,0.284)|(0.326,0.511)|(0.243,0.436)|(0.460,0.685)|
|Has savings|0.166<br>|-0.060<br>|-0.022<br>|0.296<br>|
||[0.002]|[0.504]|[1.000]|[0.000]|
||(0.066,0.265)|(-0.162,0.043)|(-0.124,0.081)|(0.165,0.428)|
|Has formal savings|0.063<br>|0.008<br>|-0.019<br>|0.320<br>|
||[0.243]|[1.000]|[1.000]|[0.000]|
||(-0.023,0.147)|(-0.076,0.095)|(-0.106,0.070)|(0.219,0.423)|
|Has loans|-0.068|-0.011|0.046|0.005|
||[0.364]|[1.000]|[0.753]|[1.000]|
||(-0.169,0.032)|(-0.113,0.091)|(-0.056,0.149)|(-0.132,0.141)|
|Sent remittances|0.229<br>|0.168<br>|0.046<br>|0.262<br>|
||[0.000]|[0.000]|[0.444]|[0.000]|
||(0.153,0.309)|(0.092,0.247)|(-0.028,0.117)|(0.165,0.354)|
|Need to borrow|0.095|0.073|0.120|0.097|
||[0.126]|[0.290]|[0.042]|[0.330]|
||(-0.005,0.195)|(-0.029,0.176)|(0.018,0.221)|(-0.040,0.234)|
|Able to save Tk 5,000|0.021|0.095|0.114|0.107|
||[1.000]|[0.043]|[0.007]|[0.124]|
||(-0.065,0.112)|(0.014,0.176)|(0.038,0.191)|(-0.006,0.218)|

Notes: Classification analysis for total consumption and mobile money person-to-person transfers at endline. Columns (1) to (3) report results on total consumption, columns (4) to (6) report results on person-to-person mobile money transactions, both measured at endline. The sample is divided into _K_ =5 groups, _δK_ , based on the quintiles of the CATE proxy predictor _S_ ( _Z_ ). Medians over 100 splits. 90% confidence interval in parentheses, _p_ -values for the hypothesis that the parameter is equal to zero in brackets.

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