Nonlinear pricing is a term that looks at the relationship between price and quantity. Normally firms bundle breakfast cereals together and then sell them at least a price that is a third of the single unit price. This shows a lack of linearity between the price and the quantity. Most of the breakfast cereal brands like Kellogg’s , Post and others employ nonlinear pricing schedules as a way of motivating consumers to purchase their products. They use these methods to increase their product sales and boost profits respectively. An example of nonlinear pricing is when a consumer is given an option to buy two boxes of cereal and get and the third one for free.
According to Market Watch (10/08/2018), 85% of breakfast cereal brand companies use the nonlinear pricing model. This is a very popular and competitive market strategy used by other companies as well. The purpose of this thesis is to therefore evaluate the effectiveness of the nonlinear pricing strategy popular in the breakfast cereal industry, as well as ascertaining whether this strategy fosters loyalty amongst cereal consumers. I have always wondered if breakfast cereal companies that use nonlinear pricing models shortchange themselves by recycling their own customers instead of attracting new ones. To respond to that question, l used data from the breakfast cereal industry for the year 2017. This data received integrity research and assurance approval at Arizona State University . Moreover, the study used breakfast cereal data as the backbone of the analysis because consumption of breakfast cereals happens throughout the year and breakfast cereals have a longer shelf life. The data is based on receipt uploads from over 400,000 users of the Omni panel website. My goal with the thesis is to evaluate the effectiveness of nonlinear pricing schedules in relation to increasing sales and fostering customer loyalty. At the end of the study, l would like to have developed a strong and data-based opinion on why consumers choose the breakfast cereal they purchased and also on the relationship between nonlinear pricing and consumer loyalty. I hope to use my findings to propose a better model which, if used by these businesses, can enable them to generate more returns and cultivate customer loyalty.

The purpose of this analysis is to determine the economic impact that the distribution of the SolarSPELL digital library system to Peace Corps volunteers in Vanuatu will have on the citizens of Vanuatu by quantifying the potential for SolarSPELL and its health education content to reduce rates of certain illnesses and thereby reduce the demands on the Vanuatu healthcare system. The research was carried out by researching the most prominent non-communicable diseases in Vanuatu that could be affected by lifestyle changes as a result of exposure to the health education content on the SolarSPELL and determining the expected changes in rates of each non-communicable disease as well as the expected changes in the individual and hospital costs, the loss of income due to missed work, transport costs within Vanuatu, and international medical evacuation costs. Ultimately, these costs were collectively reduced by approximately 2.046% due to SolarSPELL intervention, a reduction of approximately $7,000. However, given the limited scope of available information within the healthcare system of Vanuatu, it can be inferred that the impact of the distribution of the SolarSPELL is likely significantly larger. Consequently, it is recommended that the Vanuatu Ministry of Health, the SolarSPELL team, and the Peace Corps implement policies to increase the volume of healthcare data collected in Vanuatu in order to assist in future analyses of the healthcare system.

This study attempts to reconcile the gap in literature between the abundant research in the social consequences of sanctions but a consistent lack of information regarding its economic effectiveness. I apply a modified neoclassical growth model to analyze the extent that sanctions imposed by the US and UN impact real per capita GDP growth rate. Using the original data, I modify the model employed in the Neuenkirch and Neumeier (2015) study by replacing a fixed effect model with time trends. The results are more aligned with previous economic research on sanctions where sanctions imposed by the US have a moderate but significant 1.5 percent decline effect on GDP growth rate. On the other hand, sanctions imposed by the UN are similarly negative, imposing about a .9 percent decline in GDP growth, however are not statistically significant. While I cannot reject the conclusion by the original authors, I feel that this model provides a more fitting analysis of the impact sanctions impose on GDP growth.

The Medicaid expansion policy that was introduced during the Obama administration has been a political point of controversy. The expansion aimed to increase health insurance coverage for those who are unable to afford health insurance for themselves.
This analysis aimed to determine the economic effect of the Medicaid expansion on real GDP per capita. The expansion is believed to result in greater worker productivity and increases in healthcare service consumption and consumption of other goods. As health insurance coverage may increase real GDP per capita due to healthier workers being more productive, an analysis was first done on the effect of the expansion on health insurance coverage, then the effect of the health insurance coverage on real GDP per capita. The data used was in the time frame of 1999 to 2016 and organized by state, and gathered from the Bureau of Economic Analysis, the U.S Census Bureau, the Kaiser Family Foundation, Bureau of Labor Statistics, and the Federal Reserve Bank of St. Louis. The analysis was structured as a 2-stage multivariable linear regression. These regressions were modeled as a fixed-effects regression so states may be compared to itself over time. The first regression was of health insurance coverage on proportions of industry output from the agriculture, resources, manufacturing, and finance sector, median income, employment rate, poverty rate, Medicaid expansion status, and year. The predicted values of this regression were then used as an instrumental variable in the second regression. The second regression was of real GDP per capita on proportions of industry output from the agriculture, resources, manufacturing, and finance sector, median income, employment rate, poverty rate, the instrumental variable, and year. Regressions were also done on the expansion’s effect on per capita personal consumption expenditures and healthcare consumption expenditures using the instrumental variable.
The results of the regressions show that the expansion had a positive effect on health insurance coverage and real GDP per capita. It also increased personal expenditures per capita and healthcare expenditures per capita, suggesting that the lower price of healthcare results in increased overall consumption. The data was constrained by time, as the expansion was only implemented recently, and some states are still deciding whether or not to. Thus, the results of support expectations, but more time would need to pass to more accurately estimate the effects of the expansion on these states.

This dissertation focuses on consequences of public policy on consumption responses.

Chapter 1 evaluates the effect of Thailand's car tax rebate scheme in 2012 on household consumption by examining aggregate and administrative data. Car sales doubled during the policy and dramatically declined afterwards while domestic household spending was sluggish following the policy, suggesting a substantial dampening effect of the policy on future household consumption.



Chapter 2 develops a formal model to evaluate Thai household consumption responses. A life-cycle model of consumption and saving is developed with features including uninsured income risks, liquidity constraints, durable goods with embedded adjustment costs and non-homothetic preference in durable goods. Adjustment costs and liquidity constraints are important frictions in the evaluation of the shorter-term responses to changes in relative prices, while non-homotheticity captures the income effect given that cars are luxury goods in the Thai economy context. Key parameters and the partial equilibrium responses, which are key inputs to inform the aggregate outcome of the policy, are estimated. The results show that the car-tax rebates had a sizable impact on slowing Thai household consumption following the policy due to high level of elasticity of intertemporal substitution among Thai households.

Chapter 3 examines the effect of public smoking bans in the EU countries. Using individual-level data, this chapter investigates whether nationwide smoke-free laws in Europe lead to higher smoking reduction and cessation rates among mature smokers. Exploiting the different timing in imposing smoking ban laws and using a difference-in-differences approach, I find that light smokers and heavy smokers were more likely to quit smoking after comprehensive bans were in place while there was no significant effect on average smokers. The results confirm that smoking bans, particularly when enforced more strictly and comprehensively, lead to higher smoking cessation rates even among mature smokers with well-established addiction.

The dissertation is composed by three chapters. In Chapter 2 (coauthored with Matthew Wiswall) I develop new results for the identification and estimation of the technology of children’s skill formation when children’s skills are unobserved. In Chapter 3 I shed light on the importance of dynamic equilibrium interdependencies between children’s social interactions and parental investments decisions in explaining developmental differences between different social environments. In Chapter 4 (coauthored with Giuseppe Sorrenti) I study the effect of family income and maternal hours worked on both cognitive and behavioral child development.

This dissertation comprises three chapters.

In chapter one, using a rich dataset for the United States, I estimate a series of models to document the birth order effects on cognitive outcomes, non-cognitive outcomes, and parental investments. I estimate a model that allows for heterogeneous birth order effects by unobservables to examine how birth order effects varies across households. I find that first-born children score 0.2 of a standard deviation higher on cognitive and non-cognitive outcomes than their later-born siblings. They also receive 10\% more in parental time, which accounts for more than half of the differences in outcomes. I document that birth order effects vary between 0.1 and 0.4 of a standard deviation across households with the effects being smaller in households with certain characteristics such as a high income.

In chapter two, I build a model of intra-household resource allocation that endogenously generates the decreasing birth order effects in household income with the aim of using the model for counterfactual policy experiments. The model has a life-cycle framework in which a household with two children confronts a sequence of time constraints and a lifetime monetary constraint, and divides the available time and monetary resources between consumption and investment. The counterfactual experiment shows that an annual income transfer of 10,000 USD to low-income households decreases the birth order effects on cognitive and non-cognitive skills by one-sixth, which is five times bigger than the effect in high-income household.

In chapter three, with Francesco Agostinelli and Matthew Wiswall, we examine the relative importance of investments at home and at school during an important transition for many children, entering formal schooling at kindergarten. Moreover, our framework allows for complementarities between children's skills and investments from schools. We find that investments from schools are an important determinant of children's skills at the end of kindergarten, whereas parental investments, although strongly correlated with end-of-kindergarten outcomes, have smaller effects. In addition, we document a negative complementarity between children's skills at kindergarten entry and investments from schools, implying that low-skill children benefit the most from an increase in the quality of schools.

The current American opioid crisis is seeing an exponential number of fatalities. The opioid epidemic is a problem with massive scope, and while no clear reason has been identified, many causal relationships have been linked to its genesis. This thesis examines the role of the pharmaceutical industry in perpetuating the abuse rates we see today. Topics of sociological norms and values, economic incentives that benefitted private business practices, and political-legal means of restitution and market completion are examined to make sense of specific mechanisms that the pharmaceutical industry took advantage of, and the future trajectory of what is to come from the industry as well. Combined with policies (or, lack thereof) that do not provide adequate checks against opioid marketing strategies and incentives, governmental interferences come too little, too late in attempting to solve the issue.

The Clean Power Plan seeks to reduce CO2 emissions in the energy industry, which is the largest source of CO2 emissions in the United States. In order to comply with the Clean Power Plan, electric utilities in Arizona will need to meet the electricity demand while reducing the use of fossil fuel sources in generation. The study first outlines the organization of the power sector in the United States and the structural and price changes attempted in the industry during the period of restructuring. The recent final rule of the Clean Power Plan is then described in detail with a narrowed focus on Arizona. Data from APS, a representative utility of Arizona, is used for the remainder of the analysis to determine the price increase necessary to cut Arizona's CO2 emissions in order to meet the federal goal. The first regression models the variables which affect total demand and thus generation load, from which we estimate the marginal effect of price on demand. The second regression models CO2 emissions as a function of different levels of generation. This allows the effect of generation on emissions to fluctuate with ranges of load, following the logic of the merit order of plants and changing rates of emissions for different sources. Two methods are used to find the necessary percentage increase in price to meet the CPP goals: one based on the mass-based goal for Arizona and the other based on the percentage reduction for Arizona. Then a price increase is calculated for a projection into the future using known changes in energy supply.

I conduct a two-fold study on the relationship between adverse selection and nonlinear pricing in competitive insurance markets. First, I reassess empirical evidence of adverse selection in life insurance with the Health and Retirement Study (HRS) data used by Cawley and Philipson (1999). Specifically, I evaluate the shape of the premium schedule and present indications of quantity premia beyond a certain coverage level. The observed pricing schedule appears like the "backward-S-shaped" curve described by Chade and Schlee (2012); I discuss why this result cannot be entirely explained by fixed costs of underwriting. Second, I critique the arguments against adverse selection in existing literature by modifying the Rothschild and Stiglitz (1976) model of competitive insurance markets. I present several existing models and a new framework to explain how adverse selection and quantity discounts can coexist in equilibrium. These modifications deviate from the standard models of competitive insurance, but produce plausible hypotheses with conclusions contrary to conventional theoretical results.