Browsing by Subject "Risk analysis"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Publication
    Vulnerability and Risk Management for Sustainable Livelihoods of Farm Households in Northern Thailand-
    (2007) Sricharoen, Thitiwan; Heidhues, Franz
    This research attempts to explain the relationship between poverty, livelihood difficulties, risk and risk management and vulnerability to poverty of farm households in Northern Thailand. Furthermore, this study proposes a health insurance concept addressing risks and poverty of farm households. In line with the objective was to analyse risk and risk management strategies of vulnerable rural households in Northern Thailand. Firstly, the result of a principal component analysis (PCA) was utilized to determine the important factors affecting household poverty. Furthermore, a poverty index was developed. The PCA retained 16 out of 65 possible poverty determining variables. Six of the 16 variables relate to the human resource factor: (1) percentage of adults who can write, (2) percentage of adults who completed primary school, (3) percentage of adults with non-farm occupation, (4) number of children, (5) percentage of unemployed to employed, and (6) family size. There are two variables that relate to food security and which were significant: (7) crop yield and (8) value of main crop yield. Four variables relating to the dwelling show a high correlation to poverty. These are the (9) housing condition, (10) quality of latrine, (11) water system, and (12) furniture. Four variables related to assets: (13) value of transportation assets, (14) farmland owned, (15) value of assets per adult equivalent, and (16) value of agricultural assets. The explicit factors relevant for assessing poverty are the dwelling conditions, assets, human resources, and food security, respectively. The factor which can lead the poor to become even poorer is the human resource factor, where e.g. the number of dependents is comprised. Secondly, results of the PRA showed that the most pressing problem plaguing households is their debt. Households try to honor their debt repayment obligations, but it appears that the frequent occurrence of income shocks and their low risk management capacities prevent them from doing so. Land issues relate to the second most important problem area. Often, farm households lack sufficient land and have land certificate problems. Another pressing problem negatively influencing households? livelihoods are droughts, which lead to water shortages, higher fertilizer prices and middleman problems. The results of the PRA provided an overview of all livelihood problems; they concentrated on livelihood shocks related to idiosyncratic and covariate risks. One idiosyncratic risk of main importance is poor health. Thirdly, results of the risk and risk management analysis found that there are five major types of risks frequently encountered in rural areas: 1) Natural risks (fire, heavy rainfall, heavy wind, damage to house, and drought); 2) Theft risks (theft of livestock, crop and consumer goods); 3) Production risks (crop loss from weather, crop loss from insects, storage loss, low production prices, low production, higher factor price, death of chickens); 4) Life-cycle risks/human risks (birth of children, funeral costs, unemployment, sudden moving away of working family member, old age, death of working member, son is placed in jail, risks of being cheated); 5) Health risks (prolonged sickness, chronic disease, working disability, alcohol problems of head of household and other family member). Fourthly, respondents reported that the burden of health expenses became lower after they had signed up for health insurance. However, 42% of the respondents stated that the health expenses still represented a relatively high burden to their household budget. The respondents were asked about their first choice of treatment when falling ill. The first choice for medical treatment service that households selected was the local health unit because of its proximity to the villagers. The next choice was the state hospital because there were more complete medical instruments than the local health unit; households went there when they became severely ill. The third choice was purchasing medicine from the pharmacy because the price of medicine was cheaper in comparison to traveling to consult a doctor at state hospital. Fifthly, conjoint analysis on health insurance aims to provide concepts for new, alternative health insurance products to support the exiting health insurance system in Thailand, and to help the government reduce health support costs. The analysis will be particularly useful when compared to the governmental health policy that already provides 30 Baht Health Insurance Cards to the rural poor. The households were asked which types of social security services they presently have. The 30 Baht Health Insurance is the most popular, with 88% of households participating in it. Others social security services in the region are the old age health insurance card and others account for the remainder. However, the public hospital was selected most when a household member was severely sick, with 77% respondents. Some gave the reason that the hospital provides full medical treatment and is ready in the case of an emergency operation. Finally, the study examines the linkage between poverty and vulnerability to poverty by the classification of a vulnerable group of farm households, and proposes an empirical measure that allows the setting of a vulnerability to poverty by applying Thailand?s poverty line as a benchmark. The results demonstrated that while 42% of the populations in the study area were poor in 2003, the majority of these are chronically poor (11% of the population). The information further shows that almost one-third of the population is transitorily poor i.e., 30.5% of the total population. This is dominated by a low expected mean consumption (LM vulnerability- the low expected mean consumption) accounting for 31% of total vulnerability (or 13.5% of the total population) and almost one-third was accounted for by high volatility of consumption (or 30% of the total population).
  • Thumbnail Image
    Publication
    Wirtschaftliche Analyse der Tierhaltungsbetriebe um die Metropole Moskau unter besonderer Berücksichtiung von Aufwands- und Ertragsrisiken
    (2017) Droganova, Yulia; Fuchs, Clemens
    The slow modernisation of the agricultural sector in the Russian Federation after the USSR era, the adoption and the ratification of the Basel Accords, the accession of Russia to the World Trade Organisation in 2012, and finally the crisis in the Ukraine, followed by the import ban on numerous agricultural, fishery products from the EU, USA, Canada, Australia, Norway in August 2014 are the most significant problems which found their reflection in this dissertation. This lead to an increased interest to analyse livestock farms in the Moscow region in consideration of risks in order to predict their profitable development. The goal of the current research was to identify the impending bankruptcy of the Russian livestock farms as early as possible in order to engage in efficient counter planning. The majority of the livestock farms in the Moscow region are dairy farms, which was why this type of livestock farming became the main topic of research for this thesis. The classification of dairy farms into solvent and insolvent farms is based on the application of the multivariate discriminant analysis, a bankruptcy predicting method that is widely used by many banks in Europe and the USA. The risk factor is taken into account in the empirical model of the dairy farm by setting up the stochastic Monte Carlo simulation with the most important random variables (prices, yields and interest rate) in order to quantitatively measure their influence on the economic profitability of a typical dairy farm. Following the results of the discriminant analysis, questions concerning the validation of this model were be raised. What measures were required for the dairy farms, classified as insolvent to deter bankruptcy? This question was examined using a cash flow model, summaries of relevant data and requirements for an empirical model of the dairy farms were collected through interviews of subject experts. On the basis of reference scenario/status quo scenario, three main scenarios were created: Scenario 1 Re-structuring, scenario 2 Improvement of Management and Marketing Activities, and scenario 3 Risk analysis, whereby the measures from scenarios 1 and 2 were stochastically simulated in the scenario 3 Risk analysis in order to be able to estimate the economic risks. From the data set of 31 farms, five typical model farms were selected: two correctly classified solvent, two correctly classified insolvent, and one, which showed up as a type 1 error in the discriminant analysis. A reference scenario describes the data period based on the average values of operational performance from 2008-2010, and the individualized data from the Russian statistics of 2011-2013 and forms a data basis for the scenarios 1 to 3. Scenario 1a Restructuring under Russian Insolvency Law is counterpoised to scenario 1b Restructuring under German Insolvency Law. Scenario 2a Improvement of Management and Marketing Activities without Investment and scenario 2b Improvement of Management and Marketing Activities with Investment contains measures to improve management and marketing. Labour costs were doubled, maintenance, repair costs as well as some other costs were adjusted; while the milk yields, the weight of the dairy cows, the silage yields and the yields of pastures, meadows have been estimated with a logistic function. Over a planning period of twelve years, the dairy farms classified as solvent maximised the increase of their equity capital in scenario 2b, which represents the best result compared to all other scenarios considered. Firstly, it has shown that an adequate insolvency law should support the restructuring process, secondly that training and education, consulting, motivation of employees through higher wages can lead to a better-combined performance in comparison to restructuring. In scenario 3 Risk Analysis, ten relevant random variables and their volatility were simulated and analysed within the frame conditions of the initial Scenarios 1 and 2. In addition, the target values selected were: equity after tax, equity change per hectare of agricultural area, internal equity interest and profit after tax. The presented results explain how on one hand, an adequate insolvency law can support the restructuring process and lead to reinstate solvency of the dairy farms. On the other hand, these results confirm, that the improvements in management can also lead to significant positive achievements in operational performance as opposed to restructuring. The farm, which belongs to type 1 error in the discriminant analysis, has ranked as a solvent dairy farm over the planning period of twelve years in all the scenarios considered. In this case, it can be concluded that the simulation model in the researched composition with the multivariate discriminant analysis has indirectly served to be applicable for validation purposes of the determined discriminant function.