This thesis consists of a summary and four papers. The first two papers are theoretical contributions within the area of optimal taxation and public expenditures under asymmetric information between the government and the private sector, and the last two are empirical contributions to the literature on local public expenditures. Paper [I] concerns the optimal use of publicly provided private goods in an economy with equilibrium unemployment. The paper points out that imperfect competition in the labor market gives rise to additional policy incentives associated with the self-selection constraint, which motivates adjustments in the public provision of private goods. It also addresses employment related motives behind publicly provided private goods. Paper [II] addresses optimal income and commodity taxation in a dynamic economy, where used durable goods are subject to second-hand trade. In our framework, the government is unable to directly control second-hand transactions via commodity taxation. We show how the appearance of a second-hand market affects the use of commodity taxation on the new durable goods as well as the use of income taxation. Paper [III] relates the existence and size of the flypaper effect to observable municipal characteristics. The analysis is based on a political economy model, which implies that the effect of a change in the tax base on the majority voter's tax share will be crucial for finding a flypaper effect. The empirical part is based on Swedish data on municipal expenditures and revenues for the period 1996-2004. The results show that the size of the flypaper effect varies among municipalities depending on the relative composition of grant and tax base. In Paper [IV], the composition of municipal expenditures in Sweden is analyzed by estimating a demand system for local public services, in which tax revenue collection is treated as endogenous. The estimation is based on the QAIDS specification and uses panel data for the period 1998-2005 and for six local public services. The results show that the point estimates of the income elasticities are positive (with one exception), whereas the point estimates of the own-price elasticities are negative and less than one.

This thesis contains three essays on topics in agricultural economics. Essays one and two share a focus on international trade and economic development, and essays two and three apply dynamic tools to agricultural economic policy issues.<p>Essay one analyses trade-related implications of a developing country's decision to adopt genetically-modified crop technology. A fixed-proportions model is constructed that evaluates the welfare implications of a range of adoption policies and export market responses. The model in this essay illustrates the importance of the prospective adopter formulating a projection of probable export market effects before making an adoption decision and of the role that high transaction costs may play in a developing country's adoption decision. The model also considers the effects of a new policy tool; a check-off style levy on genetically-modified technology in place of a technology-use agreement. A levy could be useful tool in developing countries, which are characterised by high transaction costs. <p>Essay two models the effects of emergency food aid on a recipient country's agricultural industry. This essay formulates a definition of needed aid in the context of a food emergency and constructs an optimal control model that solves a path of aid shipments that best meets that need. The effects of a range of food aid paths on recipient-country agricultural production are illustrated through numerical simulations. There are two key results. First, a non-optimal amount of aid can hinder a recipient-country's recovery from an exogenous food shock. Second, an exogenous shock can affect farmer revenue and therefore impact planting decisions. This effect must be considered in aid allocation policies. <p>Essay three uses time-series econometric techniques to develop a demand model that assesses the effectiveness of commodity advertising. This essay describes the importance of considering long-run and dynamic effects in demand systems, especially in the case of closely substitutable commodities. A demand system that tests for and accommodates dynamic and time-series properties is developed and applied to US meat data. The results of this model are compared to a traditional static demand system. The dynamic model produces econometrically and theoretically sound results and generates some more intuitively appealing estimates.

This thesis contains three essays on topics in agricultural economics. Essays one and two share a focus on international trade and economic development, and essays two and three apply dynamic tools to agricultural economic policy issues.<p>Essay one analyses trade-related implications of a developing country's decision to adopt genetically-modified crop technology. A fixed-proportions model is constructed that evaluates the welfare implications of a range of adoption policies and export market responses. The model in this essay illustrates the importance of the prospective adopter formulating a projection of probable export market effects before making an adoption decision and of the role that high transaction costs may play in a developing country's adoption decision. The model also considers the effects of a new policy tool; a check-off style levy on genetically-modified technology in place of a technology-use agreement. A levy could be useful tool in developing countries, which are characterised by high transaction costs. <p>Essay two models the effects of emergency food aid on a recipient country's agricultural industry. This essay formulates a definition of needed aid in the context of a food emergency and constructs an optimal control model that solves a path of aid shipments that best meets that need. The effects of a range of food aid paths on recipient-country agricultural production are illustrated through numerical simulations. There are two key results. First, a non-optimal amount of aid can hinder a recipient-country's recovery from an exogenous food shock. Second, an exogenous shock can affect farmer revenue and therefore impact planting decisions. This effect must be considered in aid allocation policies. <p>Essay three uses time-series econometric techniques to develop a demand model that assesses the effectiveness of commodity advertising. This essay describes the importance of considering long-run and dynamic effects in demand systems, especially in the case of closely substitutable commodities. A demand system that tests for and accommodates dynamic and time-series properties is developed and applied to US meat data. The results of this model are compared to a traditional static demand system. The dynamic model produces econometrically and theoretically sound results and generates some more intuitively appealing estimates.

This study proposes one plausible procedure to address two methodological issues, which are common in micro- and macro- econometric analyses, for the full realization of research potential brought by recently available high dimensional data. To address the issue of how to infer the causal structure from empirical regularities, graphical causal models are proposed to inductively infer causal structure from non-temporal and non-experimental data. However, the (probabilistic) stability condition for the graphical causal models can be violated for high dimensional data, given that close co-movements and thus near deterministic relations are oftentimes observed among variables in high dimensional data. Aggregation methods are proposed as one possible way to address this matter, allowing one to infer causal relationships among disaggregated variables based on aggregated variables. Aggregation methods also are helpful to address the issue of how to incorporate a large information set into an empirical model, given that econometric considerations, such as degrees-of-freedom and multicollinearity, require an economy of parameters in empirical models. However, actual aggregation requires legitimate classifications for interpretable and consistent aggregation. Based on the generalized condition for the consistent and interpretable aggregation derived from aggregation theory and statistical dimensional methods, we propose plausible methodological procedure to consistently address the two related issues of causal inference and actual aggregation procedures. Additional issues for empirical studies of micro-economics and macro-economics are also discussed. The proposed procedure provides an inductive guidance for the specification issues among the direct, inverse, and mixed demand systems and an inverse demand system, which is statistically supported, is identified for the consumer behavior of soft drink consumption. The proposed procedure also provides ways to incorporate large information set into an empirical model with allowing structural understanding of U.S. macro-economy, which was difficult to obtain based on the previously used factor augmented vector autoregressive (FAVAR) framework. The empirical results suggest the plausibility of the proposed method to incorporate large information sets into empirical studies by inductively addressing multicollinearity problem in high dimensional data.

The U.S. furniture industry has faced the challenge from increasing imports of furniture from foreign countries over the last decades. In the first part of this thesis, the import pattern of wooden bedroom furniture and the antidumping investigation against China were summarized, and furthermore, intervention analysis was employed to assess its impacts on the import value and unit price of China. The results revealed that the impact on import values was temporary but there was no significant impact on unit prices. The traditional suppliers have been substituted by the newly developing countries such as China and Vietnam. In the second part of this thesis, to explain the market structure change, a dynamic AIDS model was used to analyze the consumer behavior and evaluate the impacts of antidumping investigation on the major competitors in the second part. The results indicated that most imported wooden bedroom furniture can be substituted between suppliers and trade diversion occurred from China to Vietnam, Indonesia, and Brazil.

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This collection of essays examines the impact of two antecedents of household food consumption: SNAP and habit formation to nutrients. Household food choice invariably plays a substantial role in health outcomes such as obesity. Low-income households may be especially vulnerable to obesity as they face a more restricted set of food choices due to income constraints and may have less information on healthy eating relative to high-income households. This dissertation unravels this dynamic by providing causal estimates of the effect of two major determinants of food choice. Chapter 2 and chapter 3 test the impact of SNAP participation on consumption of foods that are likely to cause obesity. With some exceptions, SNAP restricts benefits to be spent only on unprepared grocery food items from participating retailers. Chapter 2 considers the broad category of Food Away From Home (FAFH) which is shown to be less healthy than meals prepared at home and shows that SNAP significantly reduces FAFH expenditure of participants. However, the magnitude of this decrease is not large enough to have a tangible impact on obesity. Chapter 3 considers household expenditure on carbonated soda, which is the key source of sugar intake among low-income households. Not only is carbonated soda SNAP-eligible, it is cheaper when purchased with SNAP benefits relative to cash because benefits are exempt from all sales taxes. Results show that SNAP participation leads to a significant rise in carbonated soda sales in low-income counties. I also find that the SNAP tax exemption does not lead to higher consumption among participants relative to non-participants. Chapter 4 tests habit formation to dietary fat using purchases of ground meat and milk products. Products in both categories have salient fat content information on the packaging. Products within each category differ only by fat content and are usually identical otherwise. Differences in habit formation are, therefore, caused by different levels of fat content. Results show a positive association between habit formation and fat content for all products in the ground meat category and all products, except fat-free milk, in the milk category. However, this relationship is modest leading to the conclusion that policy interventions, such as a saturated fat tax, might be effective in discouraging consumption of high fat products.

This dissertation aims to contribute to the field of economics of competition policy by analyzing the demand structure and the market power in the Turkish beverage industry and in the cola market in particular. First, a demand system for the beverage products has been estimated by using a multi-stage linearized Almost Ideal Demand System (AIDS). Using the own-price elasticity of cola in a SSNIP test (Small but Significant Non-Transitory Increase in Price), it is shown that cola market consists of a distinct relevant product market. Then, the demand elasticities of cola products at brand and package level have been estimated by the simple and nested logit models. Finally, the estimated demand elasticities of cola products have been used in measuring the degree of market power and predicting the effects of a hypothetical merger between Pepsi and Cola Turca by using a merger simulation technique. The results show that all cola suppliers have large price-cost margins for most of their products. Prices of the merging parties increase in average by 15 - 21% after the merger. The merger also causes the market price to increase by 16- 22% and consumer surplus to decrease by nearly 5% in average. Finally, depending on these results, the thesis recommends a stricter merger control criterion than dominance criterion for competition policy in Turkey.

This dissertation addresses: 1) the reliability of El Niño Southern Oscillation (ENSO) forecasts generated by the International Research Institute for Climate and Society (IRI) of Columbia University; 2) estimation of parameters of Mexican crop demand; and 3) the potential impacts of climate change on Mexican agriculture. The IRI ENSO forecasts were evaluated using prequential analysis, with calibration and scoring rules. Calibration tests and the Yates’ decomposition measures of the Brier score suggest that the IRI ENSO forecasts are improving in reliability and skill, showing a learning by doing behavior, i.e., these IRI ENSO forecasts show improved ability to predict the ENSO phases that really happen. In terms of estimation of the parameters of Mexican crop demand, an LA/AIDS model was used but the results were not very satisfactory with statistical tests rejecting homogeneity and symmetry. Furthermore, the estimated uncompensated price and income elasticities were found to be located in the tail regions of the Monte Carlo simulated density functions, showing poor validation of the initial estimates under similar economic (price and consumption) circumstances. Finally, in terms of the potential impacts that climate change has on Mexican agriculture, two 2050 climate change scenarios were examined. The central result indicates that Mexico benefits from climate change under the IPCC ensemble results for the B1 scenario and would experience welfare losses under the ensemble results for the A2 scenario. Moreover, dryland hectareage would decrease and would be replaced by irrigated areas. Finally, producer’s net income was found to decrease at the national level under both climate change scenarios. The results were generated using a mathematical programming sector model that was updated for the study.

Customer Relationship Management has been an integral part of the enterprise since two decades. Today, enterprises that focus on customer satisfaction need to manage their relationships with their customers effectively. This demand has allowed software vendors to create CRM solutions. The technology and broadband advancement allowed the CRM vendors to enhance their product portfolio by developing web-based CRM systems, in addition to their CRM on-premise solutions. These vendors adopted the business model in which CRM on-demand systems are provided via monthly-subscription fees, decreasing the total cost of ownership massively for enterprises in need of these systems. This business model is especially attractive for Small-To-Medium Enterprises who are searching for cost-efficient CRM systems. Currently, CRM on-demand market is quite saturated with more than 40 vendors providing similar solutions. Furthermore, CRM on-demand is delivered via Software-as-a-service method, which is a relatively new technology with unique benefits along with drawbacks. Thus, it’s of vital importance for managers in SMEs to make the right decision while evaluating the CRM on-demand option and systems. This research is meant to address this issue by building a proposed framework for CRM on-demand system evaluation. The inductive research uses qualitative and quantitative approaches for data collection and analysis. The evaluation criteria for CRM on-demand systems at a functional and general level were proposed. The general criteria were refined via collecting data from CRM on-demand experts and users in SMEs by structured questionnaires. Combining these criteria created the proposed framework which was applied to evaluate two major CRM on-demand systems in the market. The results indicate that CRM on-demand systems cover the basic functionalities of CRM including sales, marketing and service modules and offer enhanced functionality such as mobile CRM, social CRM and customizations. The research also revealed drawbacks of CRM on-demand systems such as disintegration with legacy applications, limited language support, limited country availability and technology maturity which needs to be addressed in the future. This research provides valuable insight for managers in SMEs when selecting CRM on-demand systems for their companies. Furthermore, the academicians interested in CRM and cloud computing could improve this initial proposed framework and adapt it further to different cases.