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Table 3 Language and preference for self-employment

From: Economic behavior of indigenous peoples: the Mexican case

 

Self-employed with no hired workers

Self-employed with hired workers

Total

Secondary sector

Total

Total sample

Rural sample,

6 States

Total sample

Rural sample,

6 States

Total sample

Observed mean

0.223

0.425

0.132

0.433

0.029

Results of Logit regressionsa

 Estimated meanb

0.200

0.370

0.100

0.547

0.017

 Personal information

  Age

0.006*

0.008*

0.006*

0.127*

0.001*

  Age2

0.000*

0.000*

0.000*

0.009*

0.000*

  Married

0.025*

0.032*

0.019*

0.023*

0.005*

  Unmarried

−0.045*

−0.068*

−0.030*

−0.052*

−0.008

  Number of children

0.001*

0.004*

0.001*

0.005*

0.000*

  Literacy

0.038*

0.056*

0.038*

0.127*

−0.009*

  No education

0.176*

0.453*

0.006*

0.234*

−0.013*

  Pre-school

0.142*

0.472*

0.023*

0.245*

−0.021*

  Elementary school

0.163*

0.479*

−0.005*

0.265*

−0.009*

  Middle school

0.128*

0.402*

−0.023*

0.134*

−0.006*

  High school

0.083*

0.268*

0.001

0.043

0.002*

  Teaching degreec

−0.173*

−0.233*

−0.049*

0.147

−0.014*

 Ethnic status

0.083*

0.043*

0.144*

0.217*

−0.006*

 Environment

  Semirural communities

0.004*

–

−0.015*

–

0.003*

  Small cities

−0.016*

–

−0.043*

–

0.005*

  Medium and large cities

−0.043*

–

−0.098*

–

0.001*

 Economic Sector

  Second sector

−0.103*

0.184*

–

–

−0.001*

  First sector

−0.127*

−0.032*

–

–

0.000

 Number of observations

3,662,999

886,966

477,242

70,786

3,662,999

 R2 (Nagelkerke)

0.12

0.25

0.24

0.22

0.04

  1. Source: The table was created with data from INEGI 2010
  2. * Indicates that the parameter is 95 % significant
  3. aThe values are the marginal effects with respect to estimated mean or response probability when the characteristic applies
  4. bThe estimated mean or probability of the answer is the calculation of the mean using the estimated parameters from the Logit regression (see Scott Long 1997 and Wooldrige 2002), in which \( \mu = \left( {{\raise0.7ex\hbox{${e^{{g(\bar{x})}} }$} \!\mathord{\left/ {\vphantom {{e^{{g(\bar{x})}} } {1 + e^{{g(\bar{x})}} }}}\right.\kern-0pt} \!\lower0.7ex\hbox{${1 + e^{{g(\bar{x})}} }$}}} \right) \), with \( g\left( {\bar{x}} \right) = \mathop \sum \limits_{i} \widehat{\beta }_{i} \bar{x}_{i} \)
  5. cIn Mexico, to be able to teach in a public school, a specific post-secondary teaching is required. This degree is in lieu of an undergraduate degree