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Agricultural policy analysis can be visualised as a multiple objective hierarchical optimisation problem whereby sequential non-cooperative interactions between the policy makers and the farmers take place. The objectives and choices of policy makers will almost always diverge from the objectives and choices of farmers. Policy makers exercise authority over some, but not all, of the variables in the total system whereas other variables affecting their multiple goals are under the direct control of myriad farmers who operate according to their own utility maximising motives. In order to advance their own objectives, the policy makers unilaterally and pre-emptively set the policy measures to influence the farmers. The farmers execute their decisions after, and in view of, the policies and make their production decisions that observe their goals best. Ultimately, the payoffs to both the policy makers and the farmers depend not only on the actions of the former, but also on the reactions of the latter. Such problems are difficult to solve due to their intrinsic nonconvexity and multiple objectives. This thesis shows how multi-objective genetic algorithms (MOGA) in conjunction with mathematical programming (MP) can be used for solving this type of problems. A MP model is developed to capture the production choices of farmers. The model is based on positive mathematical programming and its objective function parameters are estimated using the method of generalised maximum entropy. The model is nested in and controlled by a MOGA which captures the process of multi-objective optimisation of policy decisions. The approach is illustrated using a case study taken from the Scottish agricultural systems, where several socio-economic and environmental objectives for policy making are considered. Four types of policy instruments are examined: the current single payment scheme, a multi-payment scheme based on land use, an input taxation and a regulatory scheme. For a selection of scenarios alternative Pareto-optimal solutions are discovered and tradeoffs between the policy objectives are presented along with their associated production patterns. The performance of the modelling tool developed suggests that it is well suited to dealing with real-world policy issues. It offers considerable possibilities for exploring tradeoffs between non-commensurable and conflicting objectives relevant to sustainable development of Scottish agriculture.

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Agricultural production is affected by a range of policy and climatic variables. This research explored the impacts of cap and trade, climate change and agricultural policy scenarios on water resource use and allocation in agricultural production. The research is organized into three separate studies, one for each set of scenarios.The first study focused on cap and trade policy for controlling greenhouse gas emissions, combining cost of production estimates with output price projections to determine the overall economic impact of cap and trade legislation, as well as its impact on agricultural water consumption. Price projections that included carbon offsets were higher than projections that did not, due to land being taken out of production and prices being bid up. HR2454 will increase production costs, particularly energy intensive inputs. Output prices increase as producers reduce production in response to cost increases. If agricultural offsets are allowed, output prices will be bid up further. Offsets allow producers to receive payments for cutting emissions. Producers benefit due to indirect price effects. Since water is quantity limited, total water use is unchanged.The next study looked at the physical impacts of climate change on production, particularly rising temperatures and carbon dioxide concentrations. By analyzing the anticipated yield effects, it was found that overall net incomes would decrease and the water constraint would remain binding - meaning total water use is unchanged.The third paper analyzed the effects of agricultural policy on land and water resource allocation. Cotton is directly subsidized. Corn and grain sorghum are subsidized indirectly through ethanol subsidies. Sugar cane prices are artificially high due to tariff rate quotas on sugar imports. Removal of any of these interventions decreased net profits to producers, but water use remains unchanged. Removing all farm programs significantly decreases acres under cultivation, and reduces water use below the water constraint. It comes at a great cost to producers however, given the small amount of water saved.

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This dissertation includes three essays on the Thai economy. The first two chapters focus on the impact of the insurgency in Southern Thailand, and the third paper analyses the effect of the government's rice pledging scheme. The insurgency in the southern region of Thailand, including Yala, Pattani, and Narathiwat, and some parts of Songkhla province, began in 2004. As the end of 2017, the total number of deaths was 6,686 persons, including military, government officials, insurgents, and civilians. The conflict has run for more than a decade and is likely to continue in the near future. However, few studies focus on the effect of this insurgency. In particular, none of the economic literature has considered this issue yet, although the study of the economics of terrorism has been a very active field since the September 11 attack. Therefore, this research is among the first that analyses the economic effect of the insurgency in Southern Thailand. In the first chapter, I employ a synthetic control analysis to examine the economic impact of this insurgency. I use the Thai Socio-Economic Survey to construct panel data at the provincial level. The result shows that households in the affected provinces had real expenditure per capita lower than its predicted level about by about an average 16.21 percent per annum. Furthermore, I divide households into subgroups based on their characteristics and estimate the treatment effects separately. First, I divide the observations by urban and rural areas. The results indicate that the insurgency had an impact on urban households more than rural households. I next divide the sample by age of household head. The estimates exhibit that the most affected group was the youngest group, those 20 to 34 years old. On the contrary, the oldest group, whose older than 50 years, were the least affected. While the first chapter indicates the macroeconomic effect, and the affected area is treated as a single treatment unit, the second chapter examines the impact of the insurgency at the district level by exploiting the variation in violent incidents and deaths among districts from 2004 to 2017. The empirical results suggest that areas with a high insurgency intensity experienced migration outflows and hence negative net migration. Over the long-term, I also find that districts with high numbers of incidents and deaths had lower average growth in population and lights at night as compared to more peaceful districts. For the labour market, the results do not show any effect of the insurgency on monthly wages and working hours of local employees. This research contributes to the literature on the economics of terrorism, and the results are consistent with most studies that indicate the negative impact of insurgency on the economy and outflow migration. However, my study is among the first to illustrate the heterogeneous effect of the insurgency. In fact, the results suggest that the magnitude of the impact depends on the characteristics of households and the local-level intensity of the insurgency. In the third chapter, I examine the impact of the Thai rice pledging scheme. This policy aimed to resolve the rice over-supply problem during the harvest season. The program allowed farmers to use their products as collateral. Consequently, farmers could store their products during the low-price harvest season and redeem them back to sell when prices increased. Generally, the pledging price was set close to the market price, and a limited amount of rice was eligible for pledging for each household and each area. However, the rice pledging scheme during 2011 to 2014 allowed for an unlimited amount of rice to be pledged at a high price. Hence, rice farmers experienced temporary increases in sales prices during this period. This chapter aims to examine the impact of this program on revenues of rice farmers by using annual household panel data from 2009 to 2015. The results indicate that the policy did increase the nominal revenues of rice farmers by approximately 35 percent annually. Moreover, the heterogeneity analysis indicates that only the middle 50 percent rice farmers by income level benefited from the program, while the top and bottom 25 percent of rice farmers did not gain from the policy.