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Globally, 21 percent of young women are married before their 18th birthday. Despite some progress in addressing child marriage, it remains a widespread practice, in particular in South Asia. While household predictors of child marriage have been studied extensively in the literature, the evidence base on macro-economic factors contributing to child marriage and models that predict where child marriage cases are most likely to occur remains limited. In this paper we aim to fill this gap and explore region-level indicators to predict the persistence of child marriage in four countries in South Asia, namely Bangladesh, India, Nepal and Pakistan. We apply machine learning techniques to child marriage data and develop a prediction model that relies largely on regional and local inputs such as droughts, floods, population growth and nightlight data to model the incidence of child marriages. We find that our gradient boosting model is able to identify a large proportion of the true child marriage cases and correctlyclassifies 78% of the true marriage cases, with a higher accuracy in Bangladesh (90% of the cases) and a lower accuracy in Nepal (71% of cases). In addition, all countries contain in their top 10 variables for classification nighttime light growth, a shock index of drought over the previous and the last two years and the regional level of education, suggesting that income shocks, the regional economic activity and regional education levels play a significant role inpredicting child marriage. Given the accuracy of the model to predict child marriage, our model is a valuable tool to support policy design in countries where household-level data remains limited.

Globally, 21 percent of young women are married before their 18th birthday. Despite some progress in addressing child marriage, it remains a widespread practice, in particular in South Asia. While household predictors of child marriage have been studied extensively in the literature, the evidence base on macro-economic factors contributing to child marriage and models that predict where child marriage cases are most likely to occur remains limited. In this paper we aim to fill this gap and explore region-level indicators to predict the persistence of child marriage in four countries in South Asia, namely Bangladesh, India, Nepal and Pakistan. We apply machine learning techniques to child marriage data and develop a prediction model that relies largely on regional and local inputs such as droughts, floods, population growth and nightlight data to model the incidence of child marriages. We find that our gradient boosting model is able to identify a large proportion of the true child marriage cases and correctly classifies 78% of the true marriage cases, with a higher accuracy in Bangladesh (90% of the cases) and a lower accuracy in Nepal (71% of cases). In addition, all countries contain in their top 10 variables for classification nighttime light growth, a shock index of drought over the previous and the last two years and the regional level of education, suggesting that income shocks, the regional economic activity and regional education levels play a significant role in predicting child marriage. Given the accuracy of the model to predict child marriage, our model is a valuable tool to support policy design in countries where household-level data remains limited.

In this paper, we investigate the link between intra-household resource allocation and familial ties between household members. We show that, within the same geographic, economic and social environments, households where members have "stronger" familial ties (e.g. a nuclear family household) achieve near Pareto efficient allocation of productive resources and Pareto efficient allocation of consumption while households with "weaker" familial ties (e.g. an extended family household) do not. We propose a theoretical model of the household based on the idea that altruism between household members vary with familial ties which generates predictions consistent with the observed empirical patterns.

This paper disentangles the ethnic drivers of the effect of food-related income shocks on African conflict employing geo-localized information. We consider diversity and political ethnic variables and several conflict definitions. We find that differentiating between organized armed-force and non-organized conflict can be more informative than between factor and output conflict. We show evidence that conflict is driven by the opportunity cost and state capacity mechanisms. Furthermore, ethnic cleavages have a large role in the transmission process of income shocks on organized armed-force conflict; whereas their role in non-organized violence is more limited. The sensitivity to ethnic heterogeneity for producer-price and droughts shocks is much larger than for consumer-price changes. Financial support from the Spanish Ministry of Economy and Competitiveness (Projects PGC2018-093542-B-I00 and PID2019-111208GB-I00) is gratefully acknowledged.

This paper studies how the sensitivity of consumption to income has changed over time as the degree of financial integration has risen. In standard theory, greater financial integration facilitates international borrowing and lending, helping to reduce the sensitivity of consumption growth to fluctuations in income. The paper examines the empirical validity of this prediction using an array of indicators of financial integration for a large sample of advanced and developing countries over the period 1960-2011. Two main results are reported. First, the sensitivity of consumption to income has declined over time as the degree of financial integration has risen. The decline has been more pronounced in advanced economies than in developing ones. Second, the regression analysis indicates that a higher degree of financial integration is associated with a lower sensitivity of consumption to income. This finding is robust to the use of a wide range of empirical specifications, country-specific characteristics, and other controls, such as interest rates and outcome-based measures of financial integration. The paper also discusses other potential sources of the temporal changes in the sensitivity of consumption to income.

This paper uses a stochastic dynamic programming model to characterize the optimal savings-consumption decisions and the role of livestock inventories as a buffer stock in rural Ethiopia. The results show that relatively land-rich households use accumulation and liquidation of cattle and other animal inventories for partial consumption smoothing, while low-income households appear not to do so. The results highlight the need for improvement in livestock markets, which are often affected by high transaction costs and price risk, and for investigation of other approaches to risk management.

Over the past dozen years, policymakers have largely abandoned long-standing popular approaches for addressing risk in agriculture without fully resolving the question of how best to manage the negative consequences of volatile agricultural markets. The article reviews the transition from past policies and describes current approaches that distinguish between the trade-related fiscal consequences of commodity market volatility and the consequences of price and production risks for vulnerable rural households and communities. Current policies rely more heavily on markets, even though markets for risk are incomplete in numerous ways. The benefits and limitations of market-based instruments are examined in the context of risk management strategies, and innovative approaches to extend the reach of risk markets are discussed.

Moving beyond the simple comparisons of averages typical of most analyses of household income shocks, this article employs quantile analysis to generate a complete distribution of such shocks by type of household during the 1995 crisis in Mexico. It compares the distributions across normal and crisis periods to see whether observed differences were due to the crisis or are intrinsic to the household types. Alternatively, it asks whether the distribution of shocks during normal periods was a reasonable predictor of vulnerability to income shocks during crises. It finds large differences in the distribution of shocks by household types both before and during the crisis but little change in their relative positions during the crisis. The impact appears to have been spread fairly evenly. Households headed by people with less education (poor), single mothers, or people working in the informal sector do not appear to experience disproportionate income drops either in normal times or during crises.

The article assesses the impact of Argentina's main social policy response to the severe economic crisis of 2002. The program was intended to provide direct income support for families with dependent sand whose head had become unemployed because of the crisis. Counter factual comparisons are based on a matched subset of applicants not yet receiving program assistance. Panel data spanning the crisis are also used. The program reduced aggregate unemployment, though it attracted as many people into the workforce from inactivity as it did people who otherwise would have been unemployed. Although there was substantial leakage to formally ineligible families and incomplete coverage of those who were eligible, the program did partially compensate many losers from the crisis and reduced extreme poverty.

Authors assess the dynamics behind the high net resource transfers by donors and creditors to Sub-Saharan African countries. Analyzing the determinants of overall net transfers for a panel of 37 recipient countries in 1978-98, Authors find that country policies mattered little. Donors especially bilateral donors actually made greater transfers to countries with high debt, largely owed to multilateral creditors, when policies were 'bad'. Authors conclude that comprehensive debt relief has the potential, though not the certainty, to restore selectivity in support of good policies. That would make development assistance more effective going forward and increase public support in donor countries.

Transnational families where one or more members are employed abroad while others remain back home are likely be characterized by a higher degree of private information relative to households where members are co-resident. Consequently, international migrants, who can only imperfectly monitor and control uses of remittances by family members left behind, may remit less money home if intra-household preferences differ. On the other hand, a sending household's inability to monitor the migrant's financial choices may enable him to privately spend more, thereby remitting less. Using a novel dataset of married male Indian migrants working in Qatar and their wives back home that were interviewed simultaneously but separately, the extent of information asymmetry with respect to overseas earnings is measured by the discrepancy between migrant's report of his earnings and his wife's account. We find that the greater the under-reporting of overseas income by the wife, expressed as a ratio of her account to his own, the lower the annual remittances sent home. The finding demonstrates how remittance flows can be affected by the presence of information gaps arising from imperfect monitoring of intra-household allocations. It also shows the mechanism by which remitters may vary the amount transferred home by exploiting the incomplete information recipients have of foreign earnings. Interventions that improve monitoring of intra-household allocations could potentially enhance the amount of remittances sent.

Despite recent multilateral efforts to single out child labor in debt bondage as one of the worst forms of child labor, several important questions have yet to be addressed: How pervasive is the phenomenon? Are there systematic correlations between the incidence of children in debt bondage and the economic, legislative, and financial development indicators of the economy? How does an understanding of these correlates affect the way national and international policy measures aimed at targeting this form of child labor are perceived? This article addresses each of these questions. The empirical findings suggest strong correlation between the likelihood of the incidence of child labor in debt bondage with the stage of development of an economy, the stage of financial development, and enforcement of core labor rights. Building on this evidence, the article presents a theoretical model that highlights the drawbacks and merits of a number of policies aimed at putting checks on child labor in debt bondage.

Rural and urban households in developing countries face substantial idiosyncratic and common risk, resulting in high income variability. Households in risky environments have developed sophisticated (ex-ante) risk-management and (ex-post) risk-coping strategies, including self-insurance via savings and informal insurance mechanisms to do so while formal credit and insurance markets appear to contribute only little to reducing income risk and its consequences. Informal credit and insurance, however incomplete, helps to cope with risky incomes. Despite these strategies, vulnerability remains high, and is reflected in fluctuations in consumption. It is clear therefore, that further development of safety nets will be necessary. In this paper, we focus on the opportunities available to households to use risk-management and risk-coping strategies, and on the constraints on their effectiveness. Fluctuations in consumption usually imply relatively high levels of transient poverty. High income risk may also be a cause of persistent poverty. The failure to cope with income risk is not only reflected in household consumption fluctuations but affect nutrition, health and education and contribute to inefficient and unequal intrahousehold allocations. Deaton’s model provides a useful description of the advantages of self-insurance. Policy conclusions may be limited however. In practice, assets are risky, not safe. The covariance of asset values and income due to common shocks makes self-insurance a far less useful strategy than it seems. We quantify the consequences of holding risky assets that are covariate with incomes, using simulations. Access to relatively safe and profitable assets, which might be useful for consumption smoothing, may also be limited. Lumpiness in assets may be a reason why the poor cannot protect themselves easily via assets. Policies that influence asset market risks could be beneficial to households attempting to deal with shocks. Policies could include providing more attractive and diversified savings instruments. Microfinance initiatives should put savings for self-insurance on the agenda. Macroeconomic stability during income downturns would also allow self-insurance to function better. Income smoothing can be achieved by income portfolio adjustments. In practice relatively little income smoothing (even via income portfolio adjustments) is achieved by poorer households. Income diversification for effective risk-reduction appears limited. Observed diversification patterns are often not aimed at reducing risk. Households face entry constraints to enter into profitable activities. Income risk reduction often comes at a cost. Income skewing is likely if less protection is offered by investing in assets. The long-term consequences for the asset-poor are lower average incomes and a higher income gap relative to asset-rich households. Observing specialisation does not necessarily imply that the household follows a high-risk strategy. Also, entry constraints may limit the diversification that can be achieved, leaving only low-return activities free to the poor. Income portfolios must be seen in relation to the asset portfolio and other options available: a risky, specialised portfolio may mean lower consumption risk than a diversified portfolio, depending on the asset position. Finally, several income-based strategies are only be invoked when a crisis looms. These (income)‘coping’ or ‘survival’ strategies are especially important when the shock is economy-wide. There has been increasing interest in the empirical analysis of informal risk-sharing and theoretical modelling on the sustainability and consequences of these arrangements. Risk-sharing can be viewed as the cross-sectional equivalent of consumption smoothing over time. In the absence of enforcement problems, the existence of better savings opportunities and a public safety net providing transfers when common shocks occur, could improve welfare without crowding out the informal insurance arrangement. A transfer-based safety net is, however, likely to crowd out private (precautionary) savings. Informal insurance arrangements are likely to have to be self-enforcing, imposing sustainability constraints. Circumstances in which risk-sharing arrangements may be sustained are, inter alia: a low discount rate of the future, high frequency of interactions, situations in which idiosyncratic shocks are more frequent relative to other shocks. Evaluating the effects of alternative coping mechanisms such as savings, or of policy interventions such as providing better savings instruments or public safety nets, needs to take into account their effect on incentives to sustain the agreement rather than to go it alone. It is possible that opportunities for precautionary savings or a public safety net would actually be welfare reducing and displace the informal insurance arrangement by more than one to one. Any policy intervention that improves an individual’s position outside a private group-based informal risk-sharing arrangement may provide incentives to break down the informal arrangement. Targeted interventions that target only some members of communities or groups could be particularly counterproductive. Group-based savings schemes could provide a useful alternative or complement if one is concerned about crowding-out. The possibly negative welfare effects can be avoided. Whether the crowding-out and potential negative welfare effects of interventions on informal insurance mechanisms are significant is an empirical question. If common shocks are dominant and if groups and communities rather than just individuals are targeted, these negative effects are likely to be less significant. Standard quantitative poverty analysis assumes that consumption is smooth. If smoothing is not possible, especially when large negative shocks occur, then alternative measures of poverty and vulnerability need to be explored. If interiii temporal data are available, broader definitions can be used to describe vulnerability. Aggregate measures of ‘vulnerability’ can be obtained. Targeting assistance to the vulnerable population requires specific kinds of information. Analysing the characteristics of households experiencing chronic or transient poverty, or in general, their consumption fluctuations, can provide this information. Panel data are required for this analysis. If policies are exogenous to the risk management and coping strategies, then information on how households handle income risk is irrelevant. However, policies may affect household opportunities to cope with risk (e.g. by changing exit options from informal insurance). In that case, how households cope with risk is relevant for the design of policies, in turn increasing data requirements. If effective safety nets and other consumption risk-reducing policies require detailed knowledge of existing risk-reducing actions by households, then surveys need information on physical, human and social capital, on shocks, as well as on opportunities in labour, product and asset markets. Panel and cross-section surveys could be used to collect relevant information. The complexity of consumption-risk reducing strategies implies that a simple indicator is unlikely to be available. Measures of vulnerability would typically require detailed data, including from panels. Some indicators that aim to describe vulnerability are typically flawed. The emphasis on the ability to cope with risk via assets, human capital and informal insurance and on the opportunities available, marks a convergence of different disciplines, bridging gaps with more qualitative approaches.