On the other hand, flood in July assist sowing of wet season rice by watering the fields (Islam et al 2004, Quasem 1992). Flood in August may wash away transplanted seedlings and increase the demand for labor when the water recedes and farmers replant their fields (Ahmed et al 2001). The timing of normal flood may increase or depress agricultural labor demand; Banerjee (2007) finds long run wages are higher in the flood prone areas. While normal floods may increase agricultural productivity and wage employment opportunities, heavy flood such as those in 1998, 2004, and 2007 have immediate devastating effects on the households.

It is clear from the discussion above that flood water in the flood prone Upazilas is a substitute for monsoon rain during the planting season. As a result, Households in flood prone Upazilas are not as dependent on rain for their crop cultivation as compared with households in non-flood prone Upazilas.

# **3. Data**

This study combines data from several sources such as Bangladesh Household Income Expenditure Survey of 2010 (HIES 2010), historical rainfall recorded at weather stations, rainfall data generated by Climate Research Unit (CRU) of the University of East Anglia, and flood data from Bangladesh Water Development Board. The HIES 2010 was a nationally representative survey undertaken in the 12 month period between January 2010 and January 2011. The original survey includes both rural and urban areas; however, we focus on 7,840 rural households from 333 Upazilas. **Map 1** shows the location of the Upazilas included in the HIES 2010 survey.

The HIES 2010 collected detailed information about the economic activities of each members of the households it surveyed along with other household level information. To get to the sectoral focus and diversification of household members, we focus on the primary economic activity of working age (10-65) members reported for the past 12 months. Where the members reported multiple economic activities, the highest total man-hour for the economic activity was used to arrive at the primary economic activity of the individual. We compare the economic activities of non-head members with that of the head of the household and construct a set of sectoral focus indicators for each working non-head members.

Low women’s participation in economic activities in Bangladesh, by international standards, as reported in household surveys requires some explanation. Some of the low participation is likely due to a range of factors from tradition to low bargaining power of women in the household and society (World Bank 2008). A part of low participation in economic activities may also be explained by low reporting of unpaid family work done by women in the survey. A recent survey seasonal economic activities in the _monga_ region as well as a national Labor Force Survey (LFS) suggest women’s participation in livestock rearing and other agricultural activities may be under reported in the current and previous HIES surveys (World Bank 2008, Mahadevan et al. 2012).

Table 1 shows the list of key variables and their descriptive statistics. The first set of variables are sectoral focus indicator for non-head members. The second set of variables include monthly per capita household consumption, access to credit and safety-net. The final set of variables are at the Upazila level: access to market, monsoon coefficient of variations, and historically flooded Upazilas.

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