arXiv subjects

José Miguel Flores-Contró

Publications and source records attributed to José Miguel Flores-Contró.

6 recordsLinked to original sources

arXiv2026

On the Impact of Insurance on Households Susceptible to Random Proportional Losses: An Analysis of Poverty Trapping

The trapping probability is studied for households' capital assuming that losses are proportional to the accumulated capital. We consider households without insurance and those purchasing proportional insurance. Parameter conditions under which poverty trapping is not certain in both cases are derived. For the uninsured model, a new closed-form expression for the trapping probability is obtained when the remaining proportion of capital after a loss has a beta distribution, showing that the trapping probability decays algebraically as the initial capital increases. When insurance is purchased and the remaining proportion is uniformly distributed, the trapping probability is computed by solving a non-local integro-differential equation. Our results show that insurance can prevent otherwise certain trapping in some cases, although it may increase trapping risk for households with initial capital barely above the poverty line, while reducing trapping risk for households with higher initial capital.

q-fin.RM↗

arXiv2026

Linear Risk Sharing in Community-Based Insurance: Ruin Reduction in the Compound Poisson Model

This paper studies proportional risk sharing at claim occurrence time in community-based insurance. Each participant is modeled by an individual Cramér-Lundberg surplus process, and, whenever a claim is reported within the pool, its cost is redistributed according to a fixed allocation matrix. We compare the infinite-time ruin probability of each participant under stand-alone operation and under pool participation. Our main result shows that pooling reduces, for every participant, the infinite-time ruin probability when claim severities belong to a common scale family, the allocation rule satisfies full allocation and actuarial fairness, and each transfer remains bounded by an individual capacity condition. The proof relies on a convex-order comparison between the losses borne inside the pool and the corresponding stand-alone losses. We also clarify the role of these assumptions by showing that, outside this framework, pooling need not be beneficial for all participants. Numerical illustrations with Exponential and LogNormal severities support the theoretical findings and highlight how the design of proportional sharing rules affects solvency. The paper thus provides simple and interpretable sufficient conditions under which transparent linear risk-sharing arrangements improve individual solvency in community-based insurance.

math.PR↗

arXiv2026

Optimal Cash Transfers and Microinsurance to Reduce Social Protection Costs

Design and implementation of appropriate social protection strategies is one of the main targets of the United Nation's Sustainable Development Goal (SDG) 1: No Poverty. Cash transfer (CT) programmes are considered one of the main social protection strategies and an instrument for achieving SDG 1. Targeting consists of establishing eligibility criteria for beneficiaries of CT programmes. In low-income countries, where resources are limited, proper targeting of CTs is essential for an efficient use of resources. Given the growing importance of microinsurance as a complementary tool to social protection strategies, this study examines its role as a supplement to CT programmes. In this article, we adopt the piecewise-deterministic Markov process introduced in Kovacevic and Pflug (2011) to model the capital of a household, which when exposed to proportional capital losses (in contrast to the classical Cramér-Lundberg model) can push them into the poverty area. Striving for cost-effective CT programmes, we optimise the expected discounted cost of keeping the household's capital above the poverty line by means of injection of capital (as a direct capital transfer). Using dynamic programming techniques, we derive the Hamilton-Jacobi-Bellman (HJB) equation associated with the optimal control problem of determining the amount of capital to inject over time. We show that this equation admits a viscosity solution that can be approximated numerically. Moreover, in certain special cases, we obtain closed-form expressions for the solution. Numerical examples show that there is an optimal level of injection above the poverty threshold, suggesting that efficient use of resources is achieved when CTs are preventive rather than reactive, since injecting capital into households when their capital levels are above the poverty line is less costly than to do so only when it falls below the threshold.

q-fin.RM↗

arXiv2024

The Gerber-Shiu Expected Discounted Penalty Function: An Application to Poverty Trapping

In this article, we consider a risk process to model the capital of a household. Our work focuses on the analysis of the trapping time of such a process, where trapping occurs when a household's capital level falls into the poverty area. A function analogous to the classical Gerber-Shiu function is introduced, which incorporates information on the trapping time, the capital surplus immediately before trapping and the capital deficit at trapping. We derive, under some assumptions, a model belonging to the family of generalised beta (GB) distributions that describes the distribution of the capital deficit at trapping given that trapping occurs. Affinities between the capital deficit at trapping and a class of poverty measures, known as the Foster-Greer-Thorbecke (FGT) index, are presented. The versatility of this model to estimate FGT indices is assessed using household microdata from Burkina Faso's Enquête Multisectorielle Continue (EMC) 2014.

econ.GN↗

arXiv2024

Subsidising Inclusive Insurance to Reduce Poverty

In this article, we assess the benefits of coordination and partnerships between governments and private insurers, and provide further evidence for microinsurance products as powerful and cost-effective tools for achieving poverty reduction. To explore these ideas, we model the capital of a household from a ruin-theoretic perspective to measure the impact of microinsurance on poverty dynamics and the governmental cost of social protection. We analyse the model under four frameworks: uninsured, insured (without subsidies), insured with subsidised constant premiums and insured with subsidised flexible premiums. Although insurance alone (without subsidies) may not be sufficient to reduce the likelihood of falling into the area of poverty for specific groups of households, since premium payments constrain their capital growth, our analysis suggests that subsidised schemes can provide maximum social benefits while reducing governmental costs.

stat.AP↗

arXiv2024

The Role of Direct Capital Cash Transfers Towards Poverty and Extreme Poverty Alleviation -- An Omega Risk Process

Trapping refers to the event when a household falls into the area of poverty. Households that live or fall into the area of poverty are said to be in a poverty trap, where a poverty trap is a state of poverty from which it is difficult to escape without external help. Similarly, extreme poverty is considered as the most severe type of poverty, in which households experience severe deprivation of basic human needs. In this article, we consider an Omega risk process with deterministic growth and a multiplicative jump (collapse) structure to model the capital of a household. It is assumed that, when a household's capital level is above a certain capital barrier level that determines a household's eligibility for a capital cash transfer programme, its capital grows exponentially. As soon as its capital falls below the capital barrier level, the capital dynamics incorporate external support in the form of direct transfers (capital cash transfers) provided by donors or governments. Otherwise, once trapped, the capital grows only due to the capital cash transfers. Under this model, we first derive closed-form expressions for the trapping probability and then do the same for the probability of extreme poverty, which only depends on the current value of the capital given by some extreme poverty rate function. Numerical examples illustrate the role of capital cash transfers on poverty and extreme poverty dynamics.

econ.GN↗