Abstract
This chapter focuses on the poverty increase in Mexico that is clearly observed from 2006 to date after the country achieved a sustainable poverty decline during the 2000s for the first time since the lost decades of the 1980s and 1990s. In particular, it examines the impoverishment of the most marginalized rural localities, and conducts empirical analyses from the perspective of household vulnerability using household survey panel data for 2003 and 2007. In addition, this study applies a probit model to identify the characteristics and determinants of poverty, and the vulnerability of rural households in terms of both the impoverishment of non-poor households and emergence from poverty of poor households. The regression results indicate that the households susceptible to falling into poverty and vulnerability were those who were indigenous, with a migrant member, engaged in agriculture, without self-consumption for 2007, or access to credit. Meanwhile, households with highly educated household heads, and those with access to non-agricultural or wage income (especially in 2007) are likely to have resiliency to impoverishment. In addition, the study focuses on the relationship between household vulnerability (impoverishment) and the marked de-agriculturalization observed over the same period. The regression results imply that vulnerability may be mitigated in cases where wage income is secured after household members quit agricultural activities. However, the mitigating effects are not observed in cases where households relied on migration, remittances, or self-employment.
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Notes
- 1.
See the discussions in Chap. 1 for the details of the World Bank’s international poverty lines.
- 2.
A unique characteristic of the ENCEL is that the randomized experiment was implemented at the beginning of the program to evaluate the effects of the program accurately. The details of this randomization and utilization of the data are discussed in Chap. 1.
- 3.
The information how the consumption variable are calculated is available upon request. Consumption for each year is deflated by the annual CPI.
- 4.
The food basket corresponds to 23.27 pesos per capita per day (as of June 2011), which is equivalent to US$2 according to the exchange rate of the same period. See CONEVAL (2011) for details.
- 5.
There are three national poverty lines: the food poverty line (Pobreza alimentaria, the level that covers the minimum food basket); the human capital poverty line (Pobreza de capacidades, the level that covers the minimum necessary expenditures for food basket, education, and healthcare); and the asset poverty line (Pobreza de patrimonio, the human poverty line plus the minimum expenditures pertaining to clothing, housing, and transportation) (CONEVAL 2011).
- 6.
Ideally, the selection into the initial poverty or non-poverty status should be endogenously determined by the household observable and unobservable characteristics, which may influence the results of the probit models (Imai and You 2014). However, for simplicity it is assumed here that the initial poverty status is exogenously determined.
- 7.
Ideally, presence of migrant members and/or remittances should be treated as endogenous variables, for instance, because the change in poverty status would facilitate migration through improved nutrition. However, because of the data limitations, these variables will be treated as exogenous in the model. The endogeneity concern may also be raised for savings and debt, as poverty status could influence the household capacity or incentives to save or borrow. However, this is also treated as exogenous for simplicity. CCT status can be considered random or exogenous due to the experimental design.
- 8.
As question items regarding non-agricultural income exist only in the 2007 survey, wage income (including day laborers) and self-employment (non-agricultural), which were comparable for both years, were used as proxies for the existence of non-agricultural income. According to the sample, 70% of households with non-agricultural activities were engaged in wage labor in 2007.
- 9.
Refer to Appendix 4.1 of Chap. 4 for the details of how these variables were created and the summary statistics of these variables.
- 10.
According to the author’s calculation based on the sample, about 24% of the household heads received no education.
- 11.
According to the author’s calculation based on the sample, the dependency ratio was 42.7%.
- 12.
According to the author’s calculation based on the sample, a farming household has 4.8 ha. of land on average, but the median household only owned or cultivated 2 ha. of land, indicating a high number of small poor farmers and few large farmers. In addition, land with full or partial irrigation accounted for 9.3% of those who owned/cultivated land in 2003, suggesting that most of the land was rain-fed with poor yields.
- 13.
Here, the price for tortillas is used as a proxy for food price changes in 2003 and 2007. ENCEL data show that notable price changes were observed mainly in corn-related products, that is, tortilla and maize grain. Prices of other food products, such as wheat, rice, beans, fruit and vegetables, meats, and even eggs and milk, remained almost unchanged. Some food prices even dropped during the period. Attanacio et al. (2013) pointed out a price rise in meat and dairy products because of the rise in the price of feed grains; however, this price increase was not felt in the marginal rural areas, suggesting that villagers in these areas are self-sufficient in raising their own livestock. Detailed data will be made available upon request.
- 14.
On the other hand, considering the argument that remittances are ex post strategies for consumption smoothing (Skoufias 2007), we can also infer that this result captures reverse causality, where a family member migrates upon an increase in poverty and vulnerability.
- 15.
The summary statistics will be made available upon request.
- 16.
I also conducted a regression using the non-agricultural employment dummy for 2007. The dummy becomes negative and significant at the 1% level, indicating that the access to non-agricultural employment decreases the probability of impoverishment by approximately 31% points. Unfortunately, as I could only obtain non-agricultural employment data for 2007, a comparison with 2003 could not be carried out. This result will be made available upon request.
- 17.
The coefficients of the non-agricultural income dummy for 2007 itself are positive and significant in all models, confirming a certain effect on emerging from poverty that is the same as the results in Table 2.4. The results will be made available upon request.
- 18.
The regression results will be made available upon request.
- 19.
According to a field report by Fitting (2011), costs are higher for cultivating corn by rainfed agriculture, resulting in an operating loss. Hence, she reports that the only people engaged in farming are the elderly or those who are unable to find any other work, while young people aspire to work as wage laborers in the nearby maquila factories.
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Uchiyama, N. (2017). Determinants of the Recent Poverty Increase and Household Vulnerability in Rural Mexico. In: Household Vulnerability and Conditional Cash Transfers. SpringerBriefs in Economics(). Springer, Singapore. https://doi.org/10.1007/978-981-10-4103-7_2
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