Microfinance, Efficiency and Agricultural Production in Bangladesh

The objectives of this study were to make a detailed and systematic empirical analysis of microfinance borrowers and non-borrowers in Bangladesh and also examine how efficiency measures are influenced by the access to agricultural microfinance. In the empirical analysis, this study used both parametric and non-parametric frontier approaches to investigate differences in efficiency estimates between microfinance borrowers and non-borrowers. This thesis, based on five articles, applied data obtained from a survey of 360 farm households from north-central and north-western regions in Bangladesh. The methods used in this investigation involve stochastic frontier (SFA) and data envelopment analysis (DEA) in addition to sample selectivity and limited dependent variable models. In article I, technical efficiency (TE) estimation and identification of its determinants were performed by applying an extended Cobb-Douglas stochastic frontier production function. The results show that farm households had a mean TE of 83% with lower TE scores for the non-borrowers of agricultural microfinance. Addressing institutional policies regarding the consolidation of individual plots into farm units, ensuring access to microfinance, extension education for the farmers with longer farming experience are suggested to improve the TE of the farmers. In article II, the objective was to assess the effects of access to microfinance on household production and cost efficiency (CE) and to determine the efficiency differences between the microfinance participating and non-participating farms. In addition, a non-discretionary DEA model was applied to capture directly the influence of microfinance on farm households production and CE. The results suggested that under both pooled DEA models and non-discretionary DEA models, farmers with access to microfinance were significantly more efficient than their non-borrowing counterparts. Results also revealed that land fragmentation, family size, household wealth, on farm-training and off farm income share are the main determinants of inefficiency after effectively correcting for sample selection bias. In article III, the TE of traditional variety (TV) and high-yielding-variety (HYV) rice producers were estimated in addition to investigating the determinants of adoption rate of HYV rice. Furthermore, the role of TE as a potential determinant to explain the differences of adoption rate of HYV rice among the farmers was assessed. The results indicated that in spite of its much higher yield potential, HYV rice production was associated with lower TE and had a greater variability in yield. It was also found that TE had a significant positive influence on the adoption rates of HYV rice. In article IV, we estimated profit efficiency (PE) and profit-loss between microfinance borrowers and non-borrowers by a sample selection framework, which provided a general framework for testing and taking into account the sample selection in the stochastic (profit) frontier function analysis. After effectively correcting for selectivity bias, the mean PE of the microfinance borrowers and non-borrowers were estimated at 68% and 52% respectively. This suggested that a considerable share of profits were lost due to profit inefficiencies in rice production. The results also demonstrated that access to microfinance contributes significantly to increasing PE and reducing profit-loss per hectare land. In article V, the effects of credit constraints on TE, allocative efficiency (AE) and CE were assessed while adequately controlling for sample selection bias. The confidence intervals were determined by the bootstrap method for both samples. The results indicated that differences in average efficiency scores of credit constrained and unconstrained farms were not statistically significant although the average efficiencies tended to be higher in the group of unconstrained farms. After effectively correcting for selectivity bias, household experience, number of dependents, off-farm income, farm size, access to on farm training and yearly savings were found to be the main determinants of inefficiencies. In general, the results of the study revealed the existence substantial technical, allocative, economic inefficiencies and also considerable profit inefficiencies. The results of the study suggested the need to streamline agricultural microfinance by the microfinance institutions (MFIs), donor agencies and government at all tiers. Moreover, formulating policies that ensure greater access to agricultural microfinance to the smallholder farmers on a sustainable basis in the study areas to enhance productivity and efficiency has been recommended. Key Words: Technical, allocative, economic efficiency, DEA, Non-discretionary DEA, selection bias, bootstrapping, microfinance, Bangladesh.

Optimal multispecies fishery management in the Baltic Sea: A bioeconomic analysis

The aim of the thesis is to assess the fishery of Baltic cod, herring and sprat by simulation over 50 years time period. We form a bioeconomic multispecies model for the species. We include species interactions into the model because especially cod and sprat stocks have significant effects on each other. We model the development of population dynamics, catches and profits of the fishery with current fishing mortalities, as well as with the optimal profit maximizing fishing mortalities. Thus, we see how the fishery would develop with current mortalities, and how the fishery should be developed in order to yield maximal profits. Especially cod stock has been quite low recently and by optimizing the fishing mortality it could get recovered. In addition, we assess what would happen to the fisheries of the species if more favourable environmental conditions for cod recruitment dominate in the Baltic Sea. The results may yield new information for the fisheries management. According to the results the fishery of Baltic cod, herring and sprat are not at the most profitable level. The fishing mortalities of each species should be lower in order to maximize the profits. By fishing mortality optimizing the net present value would be almost three times higher in the simulation period. The lower fishing mortality of cod would result in a cod stock recovery. If the environmental conditions in the Baltic Sea improved, cod stock would recover even without a decrease in the fishing mortality. Then the increased cod stock would restrict herring and sprat stock remarkably, and harvesting of these species would not be as profitable anymore.

Grad–Shafranov Reconstruction of Magnetic Clouds: Overview and Improvements

The Grad–Shafranov reconstruction is a method of estimating the orientation (invariant axis) and cross section of magnetic flux ropes using the data from a single spacecraft. It can be applied to various magnetic structures such as magnetic clouds (MCs) and flux ropes embedded in the magnetopause and in the solar wind. We develop a number of improvements of this technique and show some examples of the reconstruction procedure of interplanetary coronal mass ejections (ICMEs) observed at 1 AU by the STEREO, Wind, and ACE spacecraft during the minimum following Solar Cycle 23. The analysis is conducted not only for ideal localized ICME events but also for non-trivial cases of magnetic clouds in fast solar wind. The Grad–Shafranov reconstruction gives reasonable results for the sample events, although it possesses certain limitations, which need to be taken into account during the interpretation of the model results.

Jatrophanviljely ja maankäyttö Vietnamissa

Biofuels are under discussion all over the world today. There are fears that the farming of biofuel plants hurts food production and weakens the food security of the poor. On the other hand, biofuel production could lessen the green house gas emissions caused by transportation, and it could also spread the profits from fuel markets more evenly between countries. The aim of this thesis is to find out how an oil plant called jatropha curcas L., which is used for biodiesel production, can affect the sustainability of livelihoods in Vietnam from the point of view of land use. Special attention is given to the effects of jatropha farming on food production, land productivity, natural resources of livelihoods and global livelihood. Jatropha belongs to the family Euphorbiaceae, and it grows naturally in tropical and subtropical areas. It can be grown on poor soils, its seeds have high oil content, and it cannot be eaten due to its toxicity. The plant grows naturally in Vietnam, and during the past few years it has also begun to be farmed for making biodiesel. Population growth in Vietnam has slowed down, but the population's standard of living and energy consumption are still rising quickly. An interest in the international biodiesel markets has awoken following Vietnam's opening up to international trade. Jatropha diesel plays a significant part in Vietnam’s clean fuel strategy, and many companies have set up jatropha plantations to produce raw material for biodiesel. Diesel made from jatropha is planned to be used both locally and for export. This thesis uses a theoretical concept of sustainable livelihoods. According to the theory, the resources that people have shape their livelihood possibilities. Farming of jatropha affects the livelihoods of people especially through land use, as land use changes have effects on many of the livelihood resources. In addition to the written sources, the material of the thesis is based on 14 interviews in Vietnam and Finland, and on observation during a field trip to Northern Vietnam in the spring of 2008. The results of the thesis show that jatropha diesel can support the sustainability of livelihoods at different scales if it is produced with deliberation. However, positive results are only possible if decisions are made carefully and more experience is collected. The possibilities of sustainable jatropha farming depend mainly on the previous land use methods and ways of production. Farming of jatropha does not threaten food production in Vietnam if the farming plans are implemented as planned. Jatropha may take some land from cassava, but at the same time, food production can be increased if mixed farming is used on some farms. Plenty of new research information and practical experiences on jatropha farming has to be collected before results of the real sustainability of the farming are ready. Carefully considered continuation and documentation of present and future projects would help to understand the possibilities of jatropha diesel in Vietnam and elsewhere.

Water quality estimation by optical remote sensing in boreal lakes

In lake-rich regions, the gathering of information about water quality is challenging because only a small proportion of the lakes can be assessed each year by conventional methods. One of the techniques for improving the spatial and temporal representativeness of lake monitoring is remote sensing from satellites and aircrafts. The experimental material included detailed optical measurements in 11 lakes, air- and spaceborne remote sensing measurements with concurrent field sampling, automatic raft measurements and a national dataset of routine water quality measurements from over 1100 lakes. The analyses of the spatially high-resolution airborne remote sensing data from eutrophic and mesotrophic lakes showed that one or a few discrete water quality observations using conventional monitoring can yield a clear over- or underestimation of the overall water quality in a lake. The use of TM-type satellite instruments in addition to routine monitoring results substantially increases the number of lakes for which water quality information can be obtained. The preliminary results indicated that coloured dissolved organic matter (CDOM) can be estimated with TM-type satellite instruments, which could possibly be utilised as an aid in estimating the role of lakes in global carbon budgets. Based on the results of reflectance modelling and experimental data, MERIS satellite instrument has optimal or near-optimal channels for the estimation of turbidity, chlorophyll a and CDOM in Finnish lakes. MERIS images with a 300 m spatial resolution can provide water quality information in different parts of large and medium-sized lakes, and in filling in the gaps resulting from conventional monitoring. Algorithms that would not require simultaneous field data for algorithm training would increase the amount of remote sensing-based information available for lake monitoring. The MERIS Boreal Lakes processor, trained with the optical data and concentration ranges provided by this study, enabled turbidity estimations with good accuracy without the need for algorithm correction with field measurements, while chlorophyll a and CDOM estimations require further development of the processor. The accuracy of interpreting chlorophyll a via semi empirical algorithms can be improved by classifying lakes prior to interpretation according to their CDOM level and trophic status. Optical modelling indicated that the spectral diffuse attenuation coefficient can be estimated with reasonable accuracy from the measured water quality concentrations. This provides more detailed information on light attenuation from routine monitoring measurements than is available through the Secchi disk transparency. The results of this study improve the interpretation of lake water quality by remote sensing and encourage the use of remote sensing in lake monitoring.