O.A.M.D.G.

household error terms by clustering. Using a bi-variate probit we assume also We estimate the above model for both asset specifications. Note, that in this non-linear approach we cannot control for sample selection, because we do not have the proportions of asset choice in the underlying SISBEN population (cf. Boyes, Hoffman and Low (1989)). Results-Table 4 presents the regression results and the following table summarizes marginal effects.

|||Fixed asset d|efinition (1)|||Fixed asset d|efinition (2)||
|---|---|---|---|---|---|---|---|---|
|**ent variable = Participation in**<br>**Depend**|**Fixed Assets**||**Mobile Assets**||**Fixed Assets**||**Mobile Assets**||
||Coefficient|z-statistic|Coefficient|z-statistic|Coefficient|z-statistic|Coefficient|z-statistic|
|_ence_<br>_Viol_|||||||||
|blic order problem<br>pu|0.120<br>-|-1.31|0.063|0.55|0.140<br>-|-1.41|0.120|0.90|
|errilla attack rate<br>gu|0.036<br>**|2.02|0.020<br>**|1.97|0.016<br>*|1.59|0.018<br>*|1.54|
|micide rate<br>ho|0.0001|0.11|0.0011<br>-<br>**<br>-|2.00<br>|0.0009<br>*|1.61<br>|0.0005<br>-|0.80<br>-|
|_cipality controls_<br>_Muni_|||||||||
|ouped settlement<br>gr|0.423<br>***|3.67|0.415<br>***|4.17|0.174<br>-<br>**|-1.98|0.295<br>***|2.58|
|<br>ral sparse settlement<br><br>ru|0.451<br>***|3.15|0.295<br>***|2.97|0.045<br>-|-0.29|0.131|1.06|
|<br>riental Region<br>O|0.091|0.58|0.166<br>-|-1.22|0.222<br>*|1.56<br>|0.194<br>-|1.16<br>-|
|tral Region<br>Cen|0.176|1.31|0.086<br>-|-0.63|0.458<br>**|2.21|0.091|0.50|
|<br>acific Region<br>P|0.210|1.08|0.108|0.58|0.414<br>**|2.04|0.323|1.36|
|<br>titude<br>al|-1.77E-04|-0.72|-6.35E-04 ***|-2.89|-2.36E-04|-0.98|-4.04E-04 *|1.50<br>-|
|titude2<br>al|8.34E-08|0.75|2.57E-07 ***|3.26|1.68E-08|0.20|1.78E-07 *|1.83|
|rcentage of people in lowest two strata<br>pe|0.009<br>-|-0.04|0.240<br>-|-0.97|0.158<br>-|-0.68<br>|0.235<br>-|0.90<br>-|
|<br>ndex of quality of life<br><br>i|0.036<br>-<br>**|-2.09|0.034<br>-<br>*|-1.50|0.025<br>-|-1.44<br>|0.016<br>-|0.62<br>-|
|pture rate<br>ca|2.60E-05|0.24|-3.28E-05|-0.25|-4.58E-05|-0.33|-1.26E-04|0.83<br>-|
|_ehold/ head variables_<br>_Hous_|||||||||
|e<br>ag|0.046<br>***|2.79|0.042<br>***|2.84|0.042<br>***|4.10|0.041<br>**|2.06|
|e2<br>ag|0.0002<br>-|-1.12|0.0003<br>-<br>**|-2.25|0.0002<br>-<br>*<br>|1.45<br>-<br>|0.0003<br>-<br>*|1.65<br>-|
|arried<br>m|0.052|0.5|0.255<br>***|2.67|0.249<br>***|4.69|0.271<br>**|2.23|
|male<br>fe|0.365<br>-<br>***|-5.14|0.357<br>-<br>***|-4.84|0.012|0.23<br>|0.389<br>-<br>***|4.90<br>-|
|me or complete primary education<br>so|0.009<br>-|-0.1|0.068|1|0.020|0.32|0.156<br>**|2.08|
|<br>me secondary or more education<br>so|0.090|0.95|0.324<br>***|3.09|0.086|0.93|0.512<br>***|3.68|
|nstant<br>co|0.981<br>*|1.35|1.550<br>**|1.94|0.076<br>-|-0.14|1.139|1.15|
|ρ|0.836<br>***|8.35|||0.387<br>***|5.29|||
|_W_<br>_ald tests_|||||||||
|ρ|0|||||0|||
|vi<br>olence variables (p value)|0.01|||||0.03|||
|w<br>elfare indicators (p value)|0.24|||||0.60|||
|a<br>ccess of the state (p value)|0|||||0|||
|Lo<br>g pseudo likelihood|2,674.48<br>-|||||-5153.02|||
|Number of obs|7500|||||7500|||

# Results-Table 4: Coefficient estimates from bi-variate Probit model of ownership of fixed and mobile assets of Colombian households

_Note: Dependent variables are the participation in fixed assets, and mobile assets, respectively. The first and the second columns use the asset definition (1) of Table 2, the third and the fourth asset definition (2) of Table 3. Regressions are Probit, allowing for individual error correlation across the two decisions. Standard errors are robust, adjusted for clustering on municipality._ _Default household education level is ‘none’. Default region is Atlantic, default rurality degree is ‘urban’. Stars mark significance at the 10% (*), 5% (**) and 1% (***) levels._ _The Wald tests (chi2) examine joint significance of groups of variables in both specifications, in this order of the violence variables: public order problem, attack rate, homicide rate; of the welfare indicators: the index of quality of life and the share of population in the lowest two income sixtiles; of the variables indicating access of the state: rurality, region, altitude, and capture rate, respectively._ 38