<p> Conventional cereal crop residues, namely, rice (<i> Oryza sativa</i> L.), corn (<i>Zea mays</i> L.), and wheat (<i>Triticum aestivum</i> L.) is very abundant and readily available widely. It has been a nuisance to agronomic producers to manage these immense &ldquo;so-called wastes&rdquo;. The Energy Independence and Security Act (EISA) promulgated by the United States and The EU&rsquo;s renewable energy directive mandated the substantial incorporation of renewable energy in their final energy consumption. These led to the increase in R&amp;D&rsquo;s on biomass and bioenergy products in the United States as well. </p><p> Hammer mill grinds of different cereal crop residues, rice, wheat, and corn, sieved through 5"/64 , 1"/8 , and 5"/32 hammer mill screen sizes (details in chapter 3) are mixed with different binders namely gelatin, wheat gluten, and dry milk at 1:10, 1:15, and 1:20 proportions (Chapter 4). Applying Taguchi-Grey relational analysis for four factors with three levels each, optimal operating level for the control factors based on multi-response characteristics was determined. The multi-responses used for the study are bulk density, durability, compressive strength, and gross heating values. Binder ratio was most influential in determining pellet quality. Binder type was next influential factor. The combination of factor levels A₁B₁C₃D₁ was found to be optimal conditions for pelletization as final results were confirmed with tests. </p><p> The pelletization parameters for making better quality composite pellets were also investigated (in Chapter V). The same Taguchi &ndash;Grey relational analysis method was used for optimization. The process (material variables) parameters those are material type, particle size or grind size, binder type, and proportion of binder were closely studied using L9 Taguchi orthogonal array. Binder ratio (blending ratio) has most significant impact, and particle size (Hammer mill grind) has second greatest impact on pelleting composite wastes. Tests conducted employing optimal conditions (A3B3C2D1) has confirmed that better pellets were produced compared with the hypothesized conditions. </p><p> The cost analysis using Invest for excel was carried out in order to study the feasibility of solid biofuel project. The biomass assessment using Biopower Atlas and associated GIS tools from NREL demonstrated that the State of Arkansas has agricultural residues sufficient to support 50 kilotons and 66 kilotons biomass pellet plant. Economy of scale effect can be observed when comparing 50 kilotons and 66 kilotons pellet mill. Gelatin-wheat pellet mill at 50 kiloton and even 66 kilotons were predicted to be unprofitable at the current stage. However, analysis results showed pellet produced from pine shavings &ndash; wheat residue blends is profitable. Crop residues are promising resources due to its wide distribution and availability. It can be termed as a &ldquo;Backstop resource&rdquo; because it is renewable and will be economically viable option as the price of oil and gas become expensive. </p><p>

According to Munich Re (2013), economic losses related to natural disasters have increased from an average of $50 billion in the 1980s to $200 billion over the last decade. The cost of natural disasters is accumulating rapidly and some claim that climate change is responsible. Others believe that human behaviors like population growth or land use should be blamed for these rising costs. The process of climate change has already taken place, and it is expected to continue to impact the future. As a result, people are more vulnerable today. Therefore, understanding the economic aspects of climate change and natural hazard risks should be considered as a major issue and addressed in greater detail. This dissertation aimed to explore household preferences of climate change adaptation and the economic impacts of natural hazards at both micro- and macro- levels. The dissertation consisted of three related empirical studies based on the two main changes that will occur with climate change predicted by scientific climate models: stronger hurricanes and rising sea levels. The first chapter examined the impact of a recent hurricane on household activities. The objective was to find out whether a more intensified hurricane caused greater damages, and whether such damages had a long-lasting impact on household recovery. If the impact of natural hazards is worse than before, people should avoid putting themselves in harm's way. However, evidence indicates that the population in coastal cities is still growing fast, as people tend to reside near the beaches and attractive landscapes. Concerns are thus prompted by the possible lack of perceptions for future risks caused by natural hazards. Therefore, the second chapter focused on household perceptions and preferences for adapting to sea level rise in Florida. Lastly, although a disaster strikes rich or poor nations indifferently, some small island nations are among the most vulnerable. In the third chapter, the macroeconomic implications of natural hazards in Central America and the Caribbean were investigated. A careful examination of the economic factors that can lead to smaller losses and higher abilities to cope with disasters is crucial in such countries.

The construction sector serves as the engine of growth to the South Africa economy because of its catalytic role in the growth and development of the country. This study focuses mainly on the influence of the macro-economic environment on the contribution of the private sector to construction in the South Africa economy from 1984 to 2011. Government construction work is considered to be an injection into the economy; in this regard, state construction is regarded as public investment in the economy; and therefore, it is anti-cyclic (Keynes, 1936). The aim of this study has been to develop an econometric model for predicting the influence of the macroeconomic environment on the contribution of the private sector to the construction sector in the South Africa economy. The research design adopted in this study was an “ex-post facto” type, otherwise known as a causal-comparative design. The data were extracted from the published sources of the South African National Statistics, namely SARB, Stats SA and Quantec SA. The estimation technique used in this study was the ARDL model using quarterly data from 1984 to 2011. This is because in the construction sector, the influence of the independent variables is always felt over time – rather than all at once. The results of this study show that there is a long run causal relationship between inflation rate, interest rate, real exchange rate, GDP and gdp in the construction sector. The descriptive statistical analysis shows that there is a negative relationship between variables inflation rate and interest rate and the private sector spending in construction. However, economic growth as well as growth in the construction sector has a positive relationship with the private sector spending in construction. Likewise, the real exchange rate and labour productivity in construction have a negative relationship with the private sector’s spending in construction and they are statistically insignificant. The variance decomposition analysis show that the private sector spending in construction explains about 75 per cent of it variations, followed by inflation rate that explains 21 per cent on the average; while the remaining variations, comprising about 4 per cent, were shared among the other independent variables, such as GDP, GDP in construction, the interest rate and the real exchange rate. It was discovered that only the inflation rate does Granger-cause the private sector spending in construction. From the finding it can be concluded that inflation rate is a significant explanatory variable in explaining the variation in the dependent variable during period under review. Policy recommendations are as follows: firstly, the monetary authorities in South Africa should embark on sound policies that would bring about low prices of the construction materials. This would ensure growth and development in the construction sector; secondly, a stimulating development plan that would encourage private sector investment in properties and infrastructural development must be instituted; thirdly, an alternative policy to the present inflation targeting is recommended that would bring about low inflation, high growth, low unemployment and stable exchange rate; fourthly, the present policy on interest rate must be reviewed to allow for more participation in construction projects by the private sectors of the economy; fifthly, due to the fact that fluctuation in the crude oil prices in the international market is one of the major factors causing high inflation rate in South Africa, government must source local alternative products that would bring down prices of construction materials.

Community-based approaches to natural resource management have become increasingly popular because of their potential to stimulate rural economic development and promote sustainable natural resource use. The appeal of such approaches have been supported by recent developments in economic theory regarding collective action and common property institutions, which have replaced the long-held idea that resources held in common are doomed to overuse and degradation. In particular, a wide array of empirical and experimental studies have led to the emergence of ‘second generation’ collective action theories which are able to reconcile observed behaviour in social dilemma settings with rational choice theory. Second generation theories of collective action also encompass the concept of social capital; viewing forms of social capital as the fundamental motivations for collective action. Therefore, based on a second generation theoretical framework, social capital ought to play an important role in the emergence and maintenance of self-driven CBNRM projects. Despite this, there have been limited assessments of the explicit role of social capital in cases of self-driven CBNRM. Consequently, this study set out to evaluate the role of social capital and its relationship with the performance of a self-driven CBNRM case study in South Africa. In order to achieve this aim, a mixed methods research design was employed to assess the roles and relationships of social capital at different levels of analysis. Qualitative results highlighted the major role of social capital in building various forms of trust at the project level. On the other hand, quantitative results obtained from exploratory factor analysis uncovered a number of latent dimensions of social capital at the household level. In addition, two binary logistic regression models demonstrated both positive and negative relationships between latent dimensions of household-level social capital and indicators of successful collective action in the Umgano Project. The crucial role of traditional leaders in maintaining and mobilizing social capital was a cross-cutting feature of the results in this study. Overall, the findings of this study support the stance of second generation collective action theories regarding the role of social capital in enhancing collective action outcomes. / Dissertation (MSc)--University of Pretoria, 2015. / Agricultural Economics, Extension and Rural Development / Unrestricted

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This dissertation focuses on analyzing peer effects in household decisions and the diffusion of renewable energy. The first chapter investigates peer effects in two family planning decisions among Chinese households – having a second child and having a son. The second chapter focuses on evaluating environmental policies (tax credit and Corporate Average Fuel Economy standard) on the diffusion of electric vehicles in the US. And the third chapter analyzes peer effects in residential solar panels adoption with a geographic focus on California. In summary, the first and third chapter adopt two structural peer effects models to analyze household behavior under two distinct decision-making context – family planning and solar panels adoption. And the second and third chapter focuses the diffusion of two renewable energy powered products – electric vehicle and solar panels.<br><div><br></div><div>Peer effect measures how much the decision made by an agent (usually refers to an house-hold in this dissertation) is influenced by peers’ decisions under the same decision context. Manski (1993) summarizes the obstacles in identifying peer effects. The first is to separate peer effects with contextual effects, or how much the observed similarity in decision making among peer group members are attributed to similar backgrounds between peers due to endogenous group formation. The second is to separate peer effects with correlated effects, which refers to unobserved household characteristics and are believed to be correlated with each other. We use static and dynamic structural peer effects models to analyze family planning decisions and solar panels adoption decision separately, and these models are capable of disentangling the difficulties mentioned above. For the demand estimation of electric vehicle, we use a random coefficient model which has been broadly used in industrial organization.<br></div><div><br></div><div>The first chapter is motivated by the increasingly unbalanced sex ratio in China. This phenomenon and associated social challenges have been widely documented, though few studies have rigorously investigated the role that peer effects have played in this unbalanced sex ratio. This paper fills this gap by focusing on peer effects in the decision to have a second child, and to have a son. The data we use comes from the 2016 data of China Family Panel Studies, and is a ten-year cohort of women aged 45-54 by 2016; we use a structural discrete choice model to estimate the peer effects. We find that peer choices significantly influence the probability that a family has a second child, but not the probability of having a son. Instead, having a son is largely driven by contextual effects, and in particular, by the education level of one’s peer group.<br></div><div><br></div><div>The second chapter uses the random coefficient model with post-estimation counterfactual analysis to answer two research questions: (1) How much the tax credit has facilitated the diffusion of EV; (2) How much the CAFE standard and penalty level have facilitated the diffusion of EV. We obtain the data from Wards Auto with a years range from 2012 to 2019.We find that the EV market share will decrease by 35.82% if there is no tax credit. CAFE marks down the price of EV in average by 3.4 percent but marks up the price of other types of vehicles by 3.26 percent, whose absolute value far exceeds the CAFE penalty itself. We also find that increasing the penalty level from$55 to$140 per vehicle per mpg below the standard will only increase the EV market share by 0.23% and decrease the non-EV market share by 0.12%.<br></div><div><br></div><div>The third chapter applies a utility-based structural optimal stopping time model developed by de Paula (2009) to analyze solar PV adoption. We use both econometrics model and nonparametric test to support the evidence of peer effects, using public solar PV data obstained from CaliforniaDGStats. And we apply the optimal stopping time model with a confidential data set obtained from PG&E. We find significant peer effects and correlated effects in a case study which contains 20 non-adjacent communities in the suburb of San Jose. And we predicted the adoption rate in this area will increase from 19.77% in 2019 to39.65% in 2029.<br></div>

This paper attempts to provide experimental evidence on fire prevention and risk aversion among urban informal settlers using lottery choice data with real monetary prizes. The paper estimates the risk attitudes of a sample of 174 individuals from an informal housing development in Cape Town. The empirical analysis is performed within the expected utility theory specification, assuming constant relative risk aversion (CRRA) defined over the lottery prize. We tests the hypothesis that risk averse individuals will take precautionary measures in as far as possible to mitigate the risk of fire to their household. We find that individual-level fire prevention measures that are within the means of the households to effect, such as making sure that matches, lighters and paraffin are kept out of reach of children, is correlated with risk aversion, but measures, such as building of homes at least 3-5 meters from the neighbours, does not seem to be within the choice set of low-income informal dwellers. Our results further indicate that subjects who engage in fire prevention/fire safety strategies that require the "most effort" (that are most effective and costly) are significantly more risk averse relative to subjects engaging in fire safety measures that need "least effort". Contrary to expectation, distance from the main road, informal electricity connection, and the use of paraffin for lighting, heating and cooking are not correlated with risk aversion, indicating that irrespective of the risk profiles of decision makers, low-income households are often forced to make choices that increase their exposure to fire hazards.

No description available.

This study contributes to the discussion of managing tourism to a protected area in a developing country (Galapagos, Ecuador). The first part of the analysis provides quantitative data about preferences of tourists and potential impacts on park revenues from price discrimination. It uses the data from a choice experiment survey conducted in the summer of 2009 in which these four attributes of a tour of the Galapagos were described: tour length, depth of naturalist experience, level of protection of Galapagos from invasive species, and price of the tour. On average the Galapagos tourist would be willing to pay slightly more than 2.5 times for a trip with a high-level of environmental protection than for a trip that is equivalent on all other characteristics but has a lower level of environmental protection. The mean marginal willingness to pay (MWTP) for a trip with an in-depth naturalist experience is 1.8 times more than that for a trip with a less detailed naturalist experience but equivalent on other characteristics. The relatively inelastic demand for travel to the islands would allow managers to adjust access fees to shift the distribution of length of trips while not affecting the revenues. The second part of the analysis evaluates the influence on travel to the islands by depicting Galapagos as a standard market commodity as well as depicting it as an environmental commodity. This analysis compares the results obtained from two different choice experiment surveys given to tourists finishing their trip to Galapagos. One survey design portrays the archipelago as a standard holiday island destination while the other design highlights the uniqueness and vulnerability of the islands' biodiversity and the challenges that tourism poses to the islands' conservation. Results suggest that additional information modified an individual's decision-making process. In the first design case (which excludes environmental information), the influence of attributes such as length and depth of natural experience is attenuated. The MWTPs estimated for these attributes are smaller in absolute terms although differences on the MWTP are not statistically significant.

Empirical economics frequently involves testing whether a theoretical proposition is evident in a data set. This thesis explores methods for confronting such theoretical propositions with evidence. Chapter 1 develops a methodological framework for assessing whether binary (`Yes'/`No') observations exhibit a discrete change, confronting a theoretical model with data from an experiment investigating the effect of introducing a private finance option into a public system of finance. Chapter 2 expands the framework to identify two discrete changes, applying the method to the evaluation of adherence to clinical practice guidelines. The framework uses a combination of existing analytical techniques and provides results which are robust and visually intuitive. The overall result is a methodology for evaluation of guideline adherence which leverages existing patient care records and is generalizable across clinical contexts. An application to a set of field data on supplemental oxygen administration decisions of volunteer medical first responders illustrates. Chapter 3 compares the results of two mechanisms used to control industrial emissions. Cap and Trade imposes an absolute cap on emissions and any emission capacity not utilized by a firm can be sold to other firms via tradable permits. In Intensity Targets systems firms earn (owe) tradable credits for emissions below (above) a baseline implied by a relative Intensity Target. Cap and Trade is commonly believed to be superior to Intensity Targets because the relative Intensity Target subsidizes emissions. Chapter 3 reports on an experiment designed to test theoretical predictions in a long-run laboratory environment in which firms make emission abatement technology and output production decisions when demand for output is uncertain, and banking of tradable permits may or may not be permitted. Particular focus is placed on testing whether the flexibility inherent to Intensity Targets can lead them to be superior to Cap and Trade when demand is stochastic. / Thesis / Doctor of Philosophy (PhD)