Matching Items (14)
Filtering by
- All Subjects: Economics
- Creators: Kuminoff, Nicolai
Description
This survey takes information on a participant’s beliefs on privacy security, the general digital knowledge, demographics, and willingness-to-pay points on if they would delete information on their social media, to see how an information treatment affects those payment points. This information treatment is meant to make half of the participants think about the deeper ramifications of the information they reveal. The initial hypothesis is that this information will make people want to pay more to remove their information from the web, but the results find a surprising negative correlation with the treatment.
ContributorsDeitrick, Noah Sumner (Author) / Silverman, Daniel (Thesis director) / Kuminoff, Nicolai (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Amid the fast-growing market of plant-based alternatives to conventional meat, there still lies uncertainty about consumers’ preferences for these new products. Through an online survey using a Becker-DeGroot-Marschak mechanism, I test the effect that environmental information provision has on consumers’ immediate and long-term willingness- to-pay for the Whopper and Impossible Whopper from Burger King. Respondents were randomly assigned to either a control group or a treatment group, and both received information on taste in an attempt to isolate the effect of environmental information. Results show that certain groups respond to the information differently. Specifically, consumers who care about climate change are affected greatly by environmental in- formation suggesting these “climate advocates” are not fully informed despite the efforts of Impossible Foods. Vegetarians and highly educated individuals have relatively stronger preferences for the plant-based burger, in line with previous studies. Results also show a lasting effect of information on WTP, suggesting little need for repeated interventions.
ContributorsStreff, Adam (Author) / Silverman, Daniel (Thesis director) / Kuminoff, Nicolai (Committee member) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This study estimates the effect of district wealth on Arizona Empowerment Scholarship Account program participation using data from the Arizona Department of Education. We find that students from poor districts are not more likely to participate as school performance decreases.Conversely, those from wealthy districts do increase participation as school performance decreases. We briefly try to explain the observed heterogeneity through survey results and commenting on the program design.
ContributorsAngel, Joseph Michael (Author) / Kostol, Andreas (Thesis director) / Kuminoff, Nicolai (Committee member) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
There is a growing interest among policymakers and economists in quantifying the relationship between climate and economic output. Previous studies have demon- strated a clear relationship between temperature on economic growth but they generally do not report significant impacts of rainfall in regions outside of developing countries. Using gridded panel data, this paper estimates the effects of the number of days during the growing season with no rainfall on per capita gross domestic product (GDP) growth in the areas of the United States over the Ogallala and Mississippi Aquifers. Measuring precipitation in terms of growing season dry days instead of aggregate rainfall levels reveals a strong negative relationship between rainfall deficits and economic growth.
ContributorsMann, John (Author) / Hanemann, Michael (Thesis director) / Kuminoff, Nicolai (Committee member) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Agent Based modeling has been used in computer science to simulate complex phenomena. The introduction of Agent Based Models into the field of economics (Agent Based Computational Economics ACE) is not new, however work on making model environments simpler to design for individuals without a background in computer science or computer engineering is a constantly evolving topic. The issue is a trade off of how much is handled by the framework and how much control the modeler has, as well as what tools exist to allow the user to develop insights from the behavior of the model. The solutions looked at in this thesis are the construction of a simplified grammar for model construction, the design of an economic based library to assist in ACE modeling, and examples of how to construct interactive models.
ContributorsAnderson, Brandon David (Author) / Bazzi, Rida (Thesis director) / Kuminoff, Nicolai (Committee member) / Roberts, Nancy (Committee member) / Computer Science and Engineering Program (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
There is a growing consensus that environmental hazards and changing weather patterns disproportionately affect the poor, vulnerable, minority communities. My dissertation studies the nature of risk faced by vulnerable groups of individuals, how these risks affect their labor choice, income, consumption, and migration patterns. In Chapter 1, I study how seniors of different racial and income groups respond to information about hazardous waste sites in their neighborhood and their cleanup process. I find white seniors tend to move out at a higher rate when informed about the presence of a waste site as well as when the site is cleaned up compared to non-white seniors. This suggests that neighborhood gentrification exhibits inertia in the manifestation after the cleanup of Superfund sites. I find an assortative matching of seniors to neighborhoods based on their race and income, reinforcing findings in the environmental justice literature. Chapter 2 documents the effect of drought on labor choices, income, and consumption of rural households in India. I find that household consumption, as well as agricultural jobs, declines in response to drought. Further, I find that these effects are mediated by job skills and land ownership. Specifically, I find that households with working members who have completed primary education account for most of the workers who exit the agricultural sector. In contrast, I find that households with farmland increase their agricultural labor share post-drought. Cultural norms, relative prices, and land market transaction costs provide potential explanations for this behavior. Chapter 3 builds a simple model of household labor allocation based on reduced-form evidence I find in chapter 2. Simulation of the calibrated model implies that projected increases in the frequency of droughts over the next 30 years will have a net effect of a 1\% to 2\% reduction in agricultural labor. While small in percentage terms, this implies that 2.5 to 5 million individuals would leave agriculture. An increase in drought will also increase the size of the manufacturing wage subsidy needed to meet the goals of `Make in India’ policy by 20\%. This is driven by the need to incentivize landowners to reduce farm labor.
ContributorsBasu, Sayahnika (Author) / Kuminoff, Nicolai (Thesis advisor) / Bishop, Kelly (Thesis advisor) / Herrendorf, Berthold (Committee member) / Mueller, Valerie (Committee member) / Murphy, Alvin (Committee member) / Arizona State University (Publisher)
Created2021
Description
This dissertation studies how forecasting performance can be improved in big data. The first chapter with Seung C. Ahn considers Partial Least Squares (PLS) estimation of a time-series forecasting model with data containing a large number of time series observations of many predictors. In the model, a subset or a whole set of the latent common factors in predictors determine a target variable. First, the optimal number of the PLS factors for forecasting could be smaller than the number of the common factors relevant for the target variable. Second, as more than the optimal number of PLS factors is used, the out-of-sample explanatory power of the factors could decrease while their in-sample power may increase. Monte Carlo simulation results also confirm these asymptotic results. In addition, simulation results indicate that the out-of-sample forecasting power of the PLS factors is often higher when a smaller than the asymptotically optimal number of factors are used. Finally, the out-of-sample forecasting power of the PLS factors often decreases as the second, third, and more factors are added, even if the asymptotically optimal number of the factors is greater than one. The second chapter studies the predictive performance of various factor estimations comprehensively. Big data that consist of major U.S. macroeconomic and finance variables, are constructed. 148 target variables are forecasted, using 7 factor estimation methods with 11 information criteria. First, the number of factors used in forecasting is important and Incorporating more factors does not always provide better forecasting performance. Second, using consistently estimated number of factors does not necessarily improve predictive performance. The first PLS factor, which is not theoretically consistent, very often shows strong forecasting performance. Third, there is a large difference in the forecasting performance across different information criteria, even when the same factor estimation method is used. Therefore, the choice of factor estimation method, as well as the information criterion, is crucial in forecasting practice. Finally, the first PLS factor yields forecasting performance very close to the best result from the total combinations of the 7 factor estimation methods and 11 information criteria.
ContributorsBae, Juhui (Author) / Ahn, Seung (Thesis advisor) / Pruitt, Seth (Committee member) / Kuminoff, Nicolai (Committee member) / Ferraro, Domenico (Committee member) / Arizona State University (Publisher)
Created2021
Description
The welfare consequences of price versus quantity-based regulation are known to differ when information about marginal benefits or costs of abatement is imperfect. Does uncertainty about demand for the polluting good also matter for welfare of these two approaches to regulation? In chapter 1, I use plant-level survey data and high frequency variation in power consumption to assess the dynamic implications of uncertainty about future demand for the relative welfare consequences of carbon taxes and cap-and-trade regulation. I address this question in the context of the electricity sector where demand risk is particularly salient. I show that the choice between policy instruments depends on how firms and consumers balance unpredictable output volatility (higher with carbon taxes) vs. price volatility (higher with cap-and-trade regulation). Over a wide range of policy-relevant abatement targets, I find carbon taxes outperform cap-and-trade in terms of welfare. Financial incentives like the Production Tax Credit are central initiatives behind wind power as the leading renewable energy source in the U.S. But do institutional design features of energy markets matter for cost-effectiveness of subsidies to wind investments? In chapter 2, I answer this question by investigating how the design of procurement contracts that are typically used by wind developers affects their investment incentives. Using unit-level data from wind farm production and installed capacity, I find that structuring subsidies based on key features of the type of procurement contracts associated to wind projects leads to major reductions in public expenditures in terms of subsidy payments to wind developers without undermining their investment incentives. The U.S. federal government is known to have a history of heavily subsidizing the wind power industry. Subsidies either to output (Production Tax Credit) or investment goods (Investment Tax Credit) have been critical to replace emissions-intensive technologies with wind power. Which type of subsidy is best to incentivize wind investments at the least cost? In chapter 3, I use plant-level data of wind facilities from the Texas electricity market to develop and estimate a model of investment decisions that accounts for productivity shocks at the wind farm level and prudent behavior of developers. I find that subsidizing production can increase average yearly investment rates in wind capacity up to 2.5 percentage points over mean investment rates under alternative subsidies to capital. This is driven by precautionary savings that developers accumulate to smooth out potential future shocks to investment income when adverse weather conditions lead to low subsidy payments.
ContributorsGómez Trejos, Felipe Alberto (Author) / Silverman, Daniel (Thesis advisor) / Fried, Stephie (Committee member) / Ventura, Gustavo (Committee member) / Kuminoff, Nicolai (Committee member) / Arizona State University (Publisher)
Created2023
Description
This thesis explores the relationship between the performance of beauty and Potential New Member (PNM) success across various formats of formal sorority recruitment at ASU. It builds off of existing scholarship in economics of beauty premiums in labor markets, as well as sociological research on the intersection of beauty and human interaction. Through interviews of women who went through formal recruitment across three different modalities (in-person, virtual, and hybrid), themes emerged that suggest the current policies in place by ASU Panhellenic make it so that the performance of beauty hinders the facilitation of a recruitment process that is truly values-based.
ContributorsCiaramello, Katherine (Author) / Fontinha de Alcantara, Christiane (Thesis director) / Kuminoff, Nicolai (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Information Systems (Contributor) / Economics Program in CLAS (Contributor)
Created2022-05
Description
In this dissertation, I study two different sides of inequality. In the first part of this dissertation, I show what the role of unwanted childbirth is on women’s wages and education. I document that on average, mothers whose first childbirth was unwanted have lower levels of education, lower wages, and have their first childbirth at younger ages compared to the rest of the mothers. In the second part of this dissertation, I show how the introduction of a carbon tax affects individuals with different educational attainment. In particular, I show how the carbon tax affects their consumption, but also how the tax reduces air pollution and consequently affects individual mortality. I find that introducing this mortality channel reduces the aggregate welfare cost of a carbon tax by about half. In terms of the distributional effect of the policy, the mortality channel deepens the regressivity of the tax, since the benefits in terms of mortality reductions are similar for all individuals, the valuation of this benefit is higher for more educated individuals.
ContributorsOdriozola, Juan (Author) / Bick, Alexander (Thesis advisor) / Vereshchagina, Galina (Thesis advisor) / Kuminoff, Nicolai (Committee member) / Fried, Stephie (Committee member) / Arizona State University (Publisher)
Created2022