15 proxied by an asset index<sup>25</sup> and the household size respectively. Together they help control for a household’s risk and time preferences as well as labor, liquidity, and credit constraints emanating from household specific factors. The use of assets to proxy for income is motivated by the need to circumvent simultaneity in the acquisition of income and the occurrence of post-harvest loss, whereby a household could for example be forced to engage in additional income earning activities when its harvest is eaten away through LGBs<sup>26</sup> . This could lead to an estimation bias.

To further capture the economic incentives from the broader economic environment facing households when making their decisions on storage, marketing, and PHL prevention through labor input, storage technology and crop protection, following proxies are included: 1) the location of the household (rural/urban and the geographic region) through indicator variables; 2) the distance to the main population center and the market place<sup>27</sup> to reflect market accessibility and thus the ability to rely on the market as opposed to home storage for food, with greater market access increasing the opportunity cost of loss during storage, suggesting an increase in PHL with increasing distance to markets; and 3) the wholesale and retail seasonal maize price gaps in the neighboring markets, with higher gaps increasing the opportunity cost of PHL during storage, suggesting a decline in PHL as seasonal price gaps increase.<sup>28</sup> To represent the climatic environment, temperature and rainfall related variables are added.<sup>29</sup> In addition to controlling for the AEZ, which only provides a very broad climatic 25 The asset index is the score along the first principal component of a principal component analysis applied to households’ assets (comprising durable goods of the household and livestock) (See Sahn and Stifel, 2003 for applications in other contexts).

26 For an illustration, see “Catherine’s plight” in Stathers, Morris, Riwa and Mvumi (2004).

27 Distance to the main population center has been calculated using the travel distance to the nearest town of more than 20,000 inhabitants, drawing on national census data, AfriPop sources and a gridding algorithm. Similarly, the distance to the nearest market place has been calculated as the travel distance to the closest FEWSNET market center.

> 28 Seasonal price gaps were obtained through econometric identification of the individual and independent month effects on maize prices in Tanzania’s 20 major (retail and wholesale) maize markets based on 13 years of monthly-based price series obtained from the Tanzanian national statistical office (Kaminski, Christiaensen, Gilbert and Udry, 2013). The gap was measured as the maximum monthly price spread for each of the markets and the price gap of the nearest market was mapped to each household, with the nearest market identified as the market with the shortest travel distance to the household’s enumeration area.

29 Values for each household were obtained as an inverse-distance weighted average of the values of the respective variables in the cell points on the climatic grid (their center coordinates) around the household.