The ginger industry is one of the key industries identified by the Fiji government in its diversification strategy to accommodate the remnants of the withdrawal of the European Union’s sugar preferences. There is considerable pressure on small industries such as ginger in search of ways in which they can be made to operate efficiently and sustain the economy. Expansion of commercial agriculture into marginal land which is unsustainable adds enormous pressure on land causing soil erosion. Coupled with this is the quality issue which is a serious problem of ginger production and has reduced its competitiveness over the years. This study focuses on two types of losses in ginger production to provide an integrated approach to policy making and computing production losses. One is the observable output loss at the farm site that is not sold due to sub-standard quality related to disease and the other is the unobserved output loss due to inefficient production. The research attempts to answer the question of whether the Fiji ginger farmers are producing efficiently, and at what levels. The relative importance of each input in ginger production is examined. The study undertakes to determine the effects of key variables on farm efficiency. Also examined is the overall farm profiles based on the efficiency rankings of the ginger producers. Furthermore, this research attempts to determine factors that influence soil erosion, and those that influence the observed ginger loss. Using cross-sectional data from a ginger farm survey conducted in June 2007, this research estimates a stochastic production frontier which incorporates soil erosion as an input in the framework. Very few studies have looked at the impact of soil erosion in this context; hence, this study fills the gap by incorporating land quality in the analysis. Farms were found to produce at 69% of their maximum potential output and soil erosion resulted in 6.8% loss in ginger output. This also implies that using the same resources, technology and farming techniques efficiently can lead to a 31% increase in output. While unobserved loss to farm income is a 27% (F$4.6m) increase over the observable loss at farm site, the revenue loss to the whole industry is at least 30% (F$5.07m). Profit was a key determinant of both losses, but staying on farm, slope of land, manure use and hot water treatment affected the observed but not unobserved loss. Although farmer education had no effect on both losses, it was important for undertaking soil conservation. Fiji is in a good position to increase production as education, age and experience of farmers were not significant determinants of efficiency. Thus, displaced farmers from sugar cane farming (given serious concerns of the viability of that industry) can be encouraged to move with ease into ginger as an alternative livelihood. Lastly, the study highlights some practical implication which calls for an integrated package of policies related to use of best farming techniques, land tenure and, agricultural extension and support services for sustainable agricultural growth.

This thesis compares different approaches to estimating budgets for Kuhn-Tucker (KT) demand systems, more specifically for the multiple discrete-continuous extreme value (MDCEV) model. The approaches tested include: (1) The log-linear regression approach (2) The stochastic frontier regression approach, and (3) arbitrarily assumed budgets that are not necessarily modeled as a function of decision maker characteristics and choice-environment characteristics. The log-linear regression approach has been used in the literature to model the observed total expenditure as way of estimating budgets for the MDCEV models. This approach allows the total expenditure to depend on the characteristics of the choice-maker and the choice environment. However, this approach does not offer an easy way to allow the total expenditure to change due to changes in choice alternative-specific attributes, but only allows a reallocation of the observed total expenditure among the different choice alternatives. To address this issue, we propose the stochastic frontier regression approach. The approach is useful when the underlying budgets driving a choice situation are unobserved, but only the expenditures on the choice alternatives of interest are observed. The approach is based on the notion that consumers operate under latent budgets that can be conceived (and modeled using stochastic frontier regression) as the maximum possible expenditure they are willing to incur. To compare the efficacy of the above-mentioned approaches, we performed two empirical assessments: (1) The analysis of out-of-home activity participation and time-use (with a budget on the total time available for out-of-home activities) for a sample of non-working adults in Florida, and (2) The analysis of household vehicle type/vintage holdings and usage (with a budget on the total annual mileage) for a sample of households in Florida. A comparison of the MDCEV model predictions (based on budgets from the above mentioned approaches) demonstrates that the log-linear regression approach and the stochastic frontier approach performed better than arbitrarily assumed budgets approaches. This is because both approaches consider heterogeneity in budgets due to socio-demographics and other explanatory factors rather than arbitrarily imposing uniform budgets on all consumers. Between the log-linear regression and the stochastic frontier regression approaches, the log-linear regression approach resulted in better predictions (vis-à-vis the observed distributions of the discrete-continuous choices) from the MDCEV model. However, policy simulations suggest that the stochastic frontier approach allows the total expenditures to either increase or decrease as a result of changes in alternative-specific attributes. While the log-linear regression approach allows the total expenditures to change as a result of changes in relevant socio-demographic and choice-environment characteristics, it does not allow the total expenditures to change as a result of changes in alternative-specific attributes.

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Flourishing economy, rapid industrialization and increasing trend of motorization have been shaping societies in the developing countries like India in an unprecedented manner.Infrastructure backlog amid such rapid growth in all imaginable directions has heavily exacerbated the urban transport crisis in these countries by alarming increase in vehicular travel demand, road fatalities, and environmental pollution. To address urban transport challenges, the necessary development and implementation of effective transport planning and policies have generally lagged in the developing countries compared to that seen in the developed countries due to several constraints including resource constraints, knowledge constraints, institutional constraints and so on. However, in the recent past, with the rapid development seen by several emerging economies and the explosive growth in transportation infrastructure investment, there is a growing interest in the development and implementati on of advanced travel demand modeling systems in developing countries. But lack of necessary research and exploration of travel behavior in a developing country context has left very limited knowledge for us to understand the extent of applicability of these advanced theories and methodologies in a different socio-cultural perspective. Assessing the practical relevance of the subject, this research adopts a comprehensive approach to explore the activity engagement pattern and time use behavior from a developing country standpoint. To accomplish this goal, a series of empirical and analytical studies are performed on a household travel survey data set available from Thane Metropolitan Area in India. The study also introduces new concepts and facilitates enhancements of existing modeling methodologies in the field of travel behavior and time use research. The study results provide very insightful findings and plausible interpretations consistent with a developing country perspective reco gnizing a wide spectrum of differences and similarities in activity patterns and time use behavior between a developed and a developing country. Specified model structures are meaningfully able to incorporate various socio-cultural and institutional constraints and reflected sensitivity to the behavioral variability between the contexts suggesting that advanced analytical techniques may be satisfactorily applied on the data set from developing countries which may contribute important ingredients in the development of advanced activity-based model system in the countries like India.

This thesis contains an introduction followed by two independent chapters, each of them dealing with a different empirical issue of Brazilian sugarcane sector. The aim of the study in chapter 2 is the productivity of São Paulo state sugarcane mills in the post-2008 period. To evaluate the productivity changes a total factors productivity (TFP) approach combined with stochastic frontier models were used and then the TFP growth between 2010 and 2015 had been decomposed into four components: technical progress; change in technical efficiency; change in the production scale and change in the allocative efficiency. The results seem to be consistent and indicate an efficiency loss for the mills over the analyzed period, as well highlighted the importance of capital for the mills, indicating that financial problems can lead to productivity losses in this sector. Chapter 3 presents an analyze the existence of asymmetric price transmission between producers and retail markets for refined sugar at the State of Sao Paulo, considering aspects such as direction, magnitude and speed of price transmissions. The empirical analysis used monthly averages of prices for the period from May 2003 to February 2015 and the results suggest that the transmission of shocks is bidirectional. Formal tests suggest that the hypothesis of symmetry in price transmission both in the short and long-run from retail to producers cannot be rejected. / Esta tese foi elaborada contendo uma introdução, seguida de dois capítulos independentes, cada um deles sendo um estudo de uma questão empírica diferente sobre o setor canavieiro brasileiro. O objetivo do estudo no capítulo 2 é analisar a produtividade das usinas de cana-de-açúcar do Estado de São Paulo no período pós-2008. Para avaliar as mudanças na produtividade foi utilizada uma abordagem de produtividade total de fatores (TFP), combinada com modelos estocásticos de fronteira e, em seguida, o crescimento da PTF entre 2010 e 2015 foi decomposto em quatro componentes: progresso técnico; mudança na eficiência técnica; mudança na escala de produção e mudança na eficiência alocativa. Os resultados parecem consistentes e indicam uma perda de eficiência para as usinas no período analisado, bem como destacam a importância do capital para as usinas, indicando que os problemas financeiros podem levar a perdas de produtividade neste setor. O capítulo 3 apresenta uma análise da existência de uma transmissão assimétrica de preços entre produtores e mercados varejistas de açúcar refinado no Estado de São Paulo, considerando aspectos como direção, magnitude e a velocidade de transmissão de preços. A análise empírica utilizou médias mensais de preços para o período de maio de 2003 a fevereiro de 2015 e os resultados sugerem que a transmissão de choques é bidirecional. Testes formais sugerem que a hipótese de simetria na transmissão de preços tanto a curto como a longo prazo do varejo para os produtores não pode ser rejeitada.