Data
This chapter is based on data from the Morocco Household and Youth Survey(MHYS) implemented in 2009/10. The survey is nationally representative (evenif it does not include the scarcely populated Western Sahara southern part of the country) and includes data on 2,000 households (1,216 in urban areas and 784in rural areas). The survey was implemented with funding from the World Bank between December 2009 and March 2010. Much of the questionnaire focused on issues critical to youth, and especially the obstacles that they encounter on elaborate market and for civic participation. Questions were also asked about young people's intentions to emigrate. Other more traditional modules deal with standard questions on household member demographics and education as well as employment information. The questionnaire also focused on various shocks affecting households and their ability to cope with these shocks. In order to be able to use the survey also for this work on migration in the MENA region, additional questions as well as options within existing questions were asked at the design stage of the survey on household perceptions regarding changes in climate,and whether this affected migration decisions. While the survey also included separate instrument administered to most young individuals in the surveyed households, that part of the survey is not used here.Apart from a range of household and individual characteristics which are used as controls in the regression analysis, a few central questions are used for the analysis presented in this chapter. In section 6B of the questionnaire devoted to climate change and shocks in agriculture, households are asked the following question: “Is one of the members of household involved in agriculture or agriculture related activities?” For those households involved in agriculture, the following question was then asked: “Over the last five years has your household faced the following problems?” The list of problems identified was as follows: (1) Reduction in agricultural yields due to inadequate rainfall (periodic and recurrent water scarcity due to droughts); (2) Reduction in agricultural yields due to too much water(too much rain or flooding); (3) Poor soil quality due to erosion reducing agricultural yields; (4) Changing and unpredictable climate and temperatures reducing agricultural yields (that is too hot, too cold, too rainy, too dry); (5) Pest or locust infestation reducing agricultural yields; (6) Reduced job opportunities in the agricultural sector; (7) Death of livestock due to bad weather conditions; (8)Reduction in the stock of livestock since the availability of grazing land is becoming less due to droughts and floods. Next households were asked: “How serious was the financial loss to the household due to these climate related factors listed above?” The potential answers were very serious, moderate, serious, and negligible.Finally households were asked “Was (the household) forced to change the economic activity after the shock?”In section 6A about the incidence of shocks and household responses, households are asked whether since November 2004, the respondent or a member of the household experienced various shocks. The shocks listed are as follows: (1)Weather shocks (droughts; floods; pest infestation, crop and livestock diseases);(2) Unexpected increase in prices of food or other essential commodities consumed; (3) Unexpected loss of job; (4) Involuntary reduction in employ mentor the number of hours worked; (5) Unexpected decline in prices or demand for products that you sell; (6) Unexpected increase in prices or shortages of inputs or products needed for your activity; (7) Loss of asset or of livestock due to theft,death, or accident; (8) Cut-off or decrease in remittances to household; (9)Death of main earner for the household; (10) Death of another member of the family; (11) Serious injury or illness that kept any member from doing normal activities; (12) Divorce or abandonment by husband; (13) Big amount of dowry for daughter’s marriage; (14) Other (specify). For every shock that they we refaced with, households are then asked “Have you managed to recovered from the negative consequences of this shock?” The possible answers were not at all, not much but some, much but not completely, or completely.
Basic Statistics
Information on the share of households involved in agriculture and affected by various climate and weather shocks is provided in table 5.1. The data are provided by type of shock, and information is also reported on the share of households that have been affected by at least one of the shocks in the last five year sin the sample of households involved in agriculture, as well as in the overall sample of households. Table 5.1 suggests that 28.1 percent of households are involved in agriculture, with the proportion being as expected much higher in rural areas and in the lower wealth quintiles of the population (following standard practice, wealth quintiles were obtained using factorial analysis on a range of assets owned by households as well as dwelling characteristics). For example,in the bottom quintile of wealth, 70.7 percent of households have at least one member involved in agriculture. Among those involved in agriculture, an overwhelming majority declares having been affected by at least one climate-related shock. That proportion is at 92.1 percent, and does not vary too much accordantly to the quintile of well-being of the household, although it is lower in the Quintilian in comparison with other quintiles. The most likely shock is a reduction in agricultural yields due to inadequate rainfall (62.2 percent of households) followed by reduced job opportunities in the agricultural sector (43.9 percent), a reduction in agricultural yields due to too much water (38.2 percent), and changing and unpredictable climate and temperatures reducing agricultural yields (34.5 percent). Other shocks affect less than a third of those involved in agriculture, but are still significant. Among those involved in agriculture, there are few differences between quintiles in terms of the likelihood to be affected by specific shocks. However, in the population as awhile, the likelihood of being affected by climate-related shocks is much higher in the bottom quintiles simply because the share of the population in quintessential involved in agriculture is much higher, as already mentioned. Forex ample the proportion of those affected by the various shocks listed in table 5.1is at 65.8 in the bottom quintile nationally, versus 5.3 percent in the top quintile. As to the seriousness of the shocks, it is also similar across quintiles, or at least
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