Estimating Vulnerability

Many existing measures of vulnerability lack a theoretical basis. In this paper we propose to measure vulnerability rigorously as the welfare of a household which solves an intertemporal optimisation model under risk.In such models, in essence a stochastic version of the Ramsey model, an important part of chronic poverty may be caused by the ex ante response of households to risks. Our simulation results indicate that whether or not a household is to be classified as vulnerable depends strongly on the time horizon considered. We use the model to assess the accuracy of existing regression-based vulnerability measures. We find that these methods can be vastly improved by including asset measures in the regression.Vulnerability, household models.

Growth and Risk: Methodology and Micro Evidence

There has been a revival of interest in the effect of risk on economic growth. We quantify both ex ante and ex post effects of risk using a stochastic version of the Ramsey model. We develop a simulation-based econometric methodology which allows us to estimate the model in the structural form suggested by theory. The methodology is applied to micro data from a remarkable long-running panel data set for rural households in Zimbabwe. We find that risk substantially reduces growth: in the ergodic distribution the mean (across households) capital stock is 46% lower than in the absence of risk. About two-thirds of the impact of risk is due to the ex ante effect (i.e. the behavioral response to risk) which is usually not taken into account in policy design. Our results suggest that the e¤ectiveness of policy interventions which reduce exposure to shocks or help households in risk management may be seriously underestimated.Farm household models, stochastic Ramsey growth models, estimation by simulation.

Vulnerability in a Stochastic Dynamic Model

Most measures of vulnerability are a-theoretic and essentially static. In this paper we use a stochastic Ramsey model to find a household's optimal welfare and we measure vulnerability as the shortfall from the welfare attained if the household consumed permanently at the poverty line. The results indicate that vulnerability is very sensitive to the time horizon considered. We find that the accuracy of existing regression-based vulnerability measures can be greatly improved by including asset measures in the regression

Vulnerability in a Stochastic Dynamic Model

Most measures of vulnerability are a-theoretic and essentially static. In this paper we use a stochastic Ramsey model to find a household's optimal welfare and we measure vulnerability as the shortfall from the welfare attained if the household consumed permanently at the poverty line. The results indicate that vulnerability is very sensitive to the time horizon considered. We find that the accuracy of existing regression-based vulnerability measures can be greatly improved by including asset measures in the regression.vulnerability, expected poverty, risk, Ramsey model, consumption regressions

Insurance and Rural Welfare: What can Panel Data tell us?

Assessing the scope for insurance in rural communities usually requires a structural model of household behavior under risk. One of the few empirical applications of such models is the study by Rosenzweig and Wolpin (1993) who conclude that Indian farmers in the ICRISAT villages would not benefit from the introduction of formal weather insurance. In this paper we investigate how models such as theirs can be estimated from panel data on production and assets. We show that if assets can take only a limited number of values the coefficients of the model cannot be estimated with reasonable precision. We also show that this can affect the conclusion that insurance would not be welfare improving

Growth and Risk: Methodology and Micro Evidence

There has been a revival of interest in the effect of risk on economic growth. We quantify both ex ante and ex post effects of risk using a stochastic version of the Ramsey model. We develop a simulation-based econometric methodology which allows us to estimate the model in the structural form suggested by theory. The methodology is applied to micro data from a remarkable long-running panel data set for rural households in Zimbabwe. We find that risk substantially reduces growth: in the ergodic distribution the mean (across households) capital stock is 46% lower than in the absence of risk. This is, we believe, the first micro-based estimate of the effect of shocks on growth. About two-thirds of the impact of risk is due to the ex ante effect (i.e. the behavioral response to risk) which is usually not taken into account in policy design. Our results suggest that the effectiveness of policy interventions which reduce exposure to shocks or help households in risk man!agement may be seriously underestimated

Cross-national differences in social background effects on educational attainment and achievement: absolute vs. relative inequalities and the role of education systems

We use PIAAC data to study the relationship between parental education and educational success among adults from 23 advanced economies. We consider educational success in terms of both educational attainment (formal qualifications) and educational achievement (competencies) and in both absolute and relative terms (i.e. as the individual’s rank in the distribution of educational success). Parental education effects are stronger for educational attainment than for achievement in all countries. Cross-national variation in the strength of social background effects follows broadly similar patterns for the different ways of measuring success, but a few countries combine relatively strong achievement with relatively weak attainment effects and vice versa. Tracking in secondary education is associated with stronger background effects for educational attainment but not for achievement. Greater prevalence of formal (non-formal) AET is associated with stronger (weaker) background effects for both attainment and achievement, while vocational orientation of upper secondary education does not matter much

Local spread of classical swine fever upon virus introduction into The Netherlands: Mapping of areas at high risk

Background In the recent past, the introduction of Classical Swine Fever Virus (CSFV) followed by between-herd spread has given rise to a number of large epidemics in The Netherlands and Belgium. Both these countries are pork-exporting countries. Particularly important in these epidemics has been the occurrence of substantial "neighborhood transmission" from herd to herd in the presence of base-line control measures prescribed by EU legislation. Here we propose a calculation procedure to map out "high-risk areas" for local between-herd spread of CSFV as a tool to support decision making on prevention and control of CSFV outbreaks. In this procedure the identification of such areas is based on an estimated inter-herd distance dependent probability of neighborhood transmission or "local transmission". Using this distance-dependent probability, we derive a threshold value for the local density of herds. In areas with local herd density above threshold, local transmission alone can already lead to epidemic spread, whereas in below-threshold areas this is not the case. The first type of area is termed 'high-risk' for spread of CSFV, while the latter type is termed 'low-risk'. Results As we show for the case of The Netherlands, once the distance-dependent probability of local transmission has been estimated from CSFV outbreak data, it is possible to produce a map of the country in which areas of high-risk herds and of low-risk herds are identified. We made these maps even more informative by estimating border zones between the two types of areas. In these border zones the risk of local transmission of infection to a nearby high-risk area exceeds a certain level. Conclusion The risk maps provide an easily understandable visualization of the spatial heterogeneities in transmission risk. They serve as a tool for area-specific designs of control strategies, and possibly also for spatial planning of areas where livestock farming is allowed. Similar risk maps can in principl