|Table 8.1: Probability|of Fallin|ginto Po<br>Std.|vertyin Hai<br>t-|ti,2001<br>Variables in Column 1||Std.|t-|
|---|---|---|---|---|---|---|---|
|P0|dF/dx|Err.|statistics|interacted with rural|dF/dx|Err.|statistics|
|Age|-0.00|0.00|-2.34|Rural age|0.00|0.00|0.57|
|Female*|-0.03|0.03|-1.23|Rural female*|0.08|0.03|2.22|
|Family size|0.12|0.02|7.73|Rural family size|-0.01|0.02|-0.57|
|Squared family size|-0.01|0.00|-6.02|R. squared family size|0.00|0.00|1.61|
|Primary education*|-0.20|0.03|-6.64|R. primary education*|0.06|0.04|1.66|
|Secondary education*|-0.27|0.03|-7.85|R. secondary edu.*|-0.02|0.05|-0.48|
|Tertiary education*|-0.43|0.03|-5.42|R. tertiary education*|-0.13|0.24|-0.51|
|Migrated*|-0.08|0.03|-2.36|Rural migrant*<br>R work|0.04|0.04|0.88|
|Work tenure>5years*|-0.10|0.06|-1.64|tenure>5years*|0.04|0.09|0.42|
|No info (work ten.)*|-0.05|0.06|-0.75|R. no info (work ten.)*|-0.03|0.08|-0.41|
|Industry*|0.18|0.07|2.35|Rural industry*|0.02|0.11|0.22|
|Agriculture*|0.16|0.07|2.36|Rural agriculture*|0.08|0.10|0.84|
|Service*|0.18|0.06|2.82|Rural service*|0.03|0.09|0.31|
|Inactive*|0.24|0.06|3.58|Rural inactive*|0.12|0.09|1.27|
|Catholic*|0.03|0.10|0.33|Rural catholic*|0.02|0.12|0.16|
|Baptist*|0.03|0.11|0.29|Rural Baptist*|0.09|0.12|0.78|
|Other Religion*|0.02|0.11|0.23|Rural other religion*|0.07|0.12|0.59|
|Social*|0.03|0.03|1.09|Rural social*|-0.12|0.03|-3.39|
|Rural*|-0.02|0.18|-0.13|||||
|Southeast*|0.22|0.06|3.56|Rural Southeast*|-0.09|0.07|-1.29|
|North*|0.25|0.04|6.08|Rural North*|-0.04|0.05|-0.67|
|Northeast*|0.47|0.02|10.29|Rural Northeast*|-0.18|0.07|-2.41|
|Artibonite*|0.38|0.03|9.42|Rural Artibonite*|-0.25|0.04|-5.00|
|Center*|0.28|0.04|5.70|Rural Center*|-0.15|0.06|-2.55|
|South*|0.20|0.05|3.97|Rural South*|0.03|0.06|0.45|
|Grand-Anse*|0.34|0.04|7.24|Rural Grand-Anse*|-0.21|0.05|-3.57|
|Northwest*|0.22|0.05|4.43|Rural Northwest*|0.00|0.06|0.05|

Note: Number of observations: 7,031; (*) dF/dx is for discrete change of dummy variable from 0 to 1; t is the test of the underlying coefficient being equal to 0.

_Source:_ Own calculations based on HLCS 2001.

The gender of head of households affects poverty in rural areas but not other areas. Households headed by women in rural Haiti are more likely to be poor than those headed by men, when other covariates are included in the analysis, such as labor market connection and education (Table 8.1). Moreover, female-headed households in rural areas are 11 percent more likely to be poor than female heads in the rest of Haiti. Hence, social policies favoring women, such as conditional cash transfer programs, e.g. _Bolsa Escola_ and _Bolsa Alimentação_ in Brazil, where the mother receives the benefit, should be introduced. Furthermore, introducing more kindergarten and childcare facilities for poor mothers could facilitate poor women’s labor market participation.

Social capital is important in rural areas to escape poverty. The probit regression findings presented in Table 8.1 show that rural dwellers with social capital are less likely to be poor than are rural dwellers with no social capital or political affiliation. That is, rural dwellers with no or little social capital have a higher incidence of poverty than their 46