Browsing by Subject "Mathematische Modellierung"

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Modeling crop yield and farmer adaptation to rainfall variability : the case of Southern Ethiopia
(2016) Bocher, Temesgen Fitamo; Berger, Thomas
Improving the livelihood of poor households in developing countries by increasing agricultural productivity and production becomes the priority agenda for development actors. However, variability in rainfall has confronted success in achieving this goal. There is pressing interest in analyzing the effects of rainfall variability on household welfare and identifying policy interventions to mitigate its adverse effects. Ethiopian economy primarily depends on rain-fed agriculture. Agriculture is the backbone of the country’s economy; it contributes the lions share of GDP, employment, export earnings, and livelihood. Fluctuations in rainfall distribution and intensity have severely affected the economy in general and the livelihood of smallholder households in particular; the agricultural sector is more prone to changes in climatic condition, which increases the risk of poverty and hunger for poor farm households. Few studies have attempted to analyze the direct effects of rainfall variability on crop yield and its indirect effect on household welfare. Therefore, this thesis aimed at filling the knowledge gap on the impacts of rainfall variability on crop yield and welfare. Moreover, the study explores the role of adaptation strategies in mimicking the negative effects of rainfall variability accounting for household performance decision under resource constraint for Ethiopian farmers. The study employed Mathematical Programming Based Multi-Agent System (MP-MAS) computer simulation techniques to analyze the effects of rainfall variability on crop yield, household welfare and the role of adaptation strategies in mitigating the adverse effects of rainfall variability. Prior to application to the study, the MP-MAS simulation model is parametrized, calibrated, and validated using data from the Ethiopian Rural Household Survey (ERHS), primary data collected from the research area and thirty year rainfall time series data obtained from meteorological stations located near to the study area. To address the mentioned research question a wide range of rainfall and adaptation strategy scenarios were designed. The agent - based model enables us to incorporate different bioeconomic systems in the decision-making process by smallholder farmers, which is otherwise difficult under a real world situation where farm households face inseparable decision-making process. Moreover, the model accounts for the heterogeneity in resource endowment, investment, production, consumption, agro-ecology, input constraints, and demographic distribution among households. Livestock, consumption, crop growth and irrigation water distribution models were combined in this study. The household food consumption decision is estimated by using three stages advanced consumption module and crop water requirement and irrigation water distribution modeled using inbuilt FAO CropWat and EDIC modules, and finally an empirical analysis was done by using STATA version 12. The simulation result suggested that: (i) Both current and future rainfall variability would have negative effects on crop yield and household welfare. (ii) The yield of cereals crops and vegetables are negatively affected by rainfall variability: some perennial crops such as enset gains yield under rainfall variability. (iii) Household welfare deteriorated with rainfall variability; resource poor households are severely affected by rainfall variability. (iv) Adaptation strategies such as non-farm activities, irrigation, and soil and water conservation activities mitigate the negative effects of rainfall variability. (v) Improving the financial or non-farm constraints alone leads to increased income inequality. Therefore, the recommended solution to reduce adverse effects of rainfall variability includes: (i) Implementing integrated policy interventions than a single strategy. (ii) Improving access to credit and access to non-farm activities. (iii) Designing a pro-poor intervention (such as improving the asset base of the poor households). (iv) Improving access and use of improved agricultural technologies, and (v) Increasing access and use of irrigation to enhance agricultural productivity.
Targeting the poor and smallholder farmers : empirical evidence from Malawi
(2009) Houssou, Nazaire; Zeller, Manfred
This paper develops low cost, reasonably accurate, and simple models for improving the targeting efficiency of development policies in Malawi. Using a stepwise logistic regression (weighted) along with other techniques applied in credit scoring, the research identifies a set of easily observable and verifiable indicators for correctly predicting whether a household is poor or not, based on the 2004-05 Malawi Integrated Household Survey data. The predictive power of the models is assessed using out-of-sample validation tests and receiver operating characteristic curves, whereas the model?s robustness is evaluated by bootstrap simulation methods. Finally, sensitivity analyses are performed using the international and extreme poverty lines. The models developed have proven their validity in an independent sample derived from the same population. Findings suggest that the rural model calibrated to the national poverty line correctly predicts the status of about 69% of poor households when applied to an independent subset of surveyed households, whereas the urban model correctly identifies 64% of poor households. Increasing the poverty line improves the model?s targeting performances, while reducing the poverty line does the opposite. In terms of robustness, the rural model yields a more robust result with a prediction margin ±10% points compared to the urban model. While the best indicator sets can potentially yield a sizable impact on poverty if used in combination with a direct transfer program, some non-poor households would also be targeted as the result of model?s leakage. One major feature of the models is that household score can be easily and quickly computed in the field. Overall, the models developed can be potential policy tools for Malawi.
The convergence of the gender pay gap : an alternative estimation approach
(2017) Töpfer, Marina; Castagnetti, Carolina; Rosti, Luisa
So far, little work has been done on directly estimating differences of wage gaps. Studies estimating pay differentials, generally compare them across different subsamples. This comparison does not allow to conduct any inference or, in the case of decompositions, to confront the respective decomposition components across subsamples. We propose an exten- sion of an Oaxaca-Blinder type decomposition based on the omitted variable bias formula to directly estimate the change in pay gaps across subsamples. The method proposed can be made robust to the index-number problem of the standard Oaxaca-Blinder decomposition and to the indeterminacy problem of the intercept-shift approach. Using Italian micro data, we estimate the difference in the gender pay gap across time (2005 and 2014). By applying our proposed decomposition, we find that the convergence of the gender pay gap over time is only driven by the catching-up of women in terms of observable characteristics, while the impact of anti-discrimination legislation is found to be negligible.