Candidates who are in the process of defending their doctoral dissertation or master's thesis may submit their information to the Office of Graduate Studies for posting to this page. Submissions intended for this page should be sent at least two weeks before the date of the defense.
Student Name: Cassie J. Gould
Graduate Level: PhD
Field of Study/Major: Behavior, Cognition, and Neuroscience
Committee Chair: Victoria P. Connaughton
Date of Presentation: May 22
Presentation Location: Hurst 101
Time of Presentation: 11:00 AM -2:00 PM
Title of Dissertation: Using zebrafish to investigate cognitive deficits and vascular complications associated with type II diabetes.
The prevalence of obesity and associated type-II diabetes mellitus is at an unprecedented level globally and is an epidemic in the United States today. All forms of diabetes are characterized by high blood sugar levels (or hyperglycemia), which, if not corrected, carries the risk of long-term complications that typically develop 10-20 years due to the damage of blood vessels. Two such complications are diabetic retinopathy and dementia, with recent reports suggesting there may be a correlation between changes observed in retina with those occurring in the brain. The studies described in this dissertation aimed to (1) use the zebrafish DMT2 model developed in our lab to assess cognitive (brain-based behavior) changes (2) correlate those cognitive changes with changes in visually-guided behaviors, and (3) relate anatomical and neurochemical changes in retina and brain to the observed behaviors. Our analyses were performed after 4- and 8-weeks of hyperglycemia, with the expectation that more deleterious effects would be seen at the later time point. In Chapter 2, we improved and implemented the three-chamber choice associative learning task typically used in rodents with zebrafish using a live shoal as a reinforcer. We then employed this behavioral task (Chapter 3) to assess hyperglycemia-induced changes in cognition and vision after 4 and 8 weeks of exposure. At the 4-week time point, glucose-treated fish displayed an impaired ability to learn and maintain memory evidenced by an increase in the number of force-rewarded trials, a decrease in the number of high performing fish by ~20% on the first day of reversal, and a decrease in discrimination ratio. At 8-weeks, behavioral analyses revealed dampened effects of glucose with responses that were either comparable to controls or due to osmotic effects. However, examining the 8-week behavioral data based on fish performance (high performing vs. low performing), revealed a glucose-specific effect on discrimination ratio in the high performing group. The optomotor response, a vision-based behavior, was larger in glucose-treated fish at both time points. After 4 weeks of treatment (Chapter 4) tight junction markers were reduced, while inflammatory markers (NF-kB, IKK) were increased in brain and retina, consistent with observed behavioral deficits. At 8-weeks, inflammatory markers in brain were still elevated, as were levels of two enzymes, tyrosine hydroxylase and glutamic acid decarboxylase, important for neurotransmitter synthesis. In retina, though, only tyrosine hydroxylase, a neurotransmitter precursors and Nf-KB were upregulated. No changes in tight junction markers were evident at 8 weeks. Taken together, these findings suggest differential sensitivity to glucose by individual fish and similar hyperglycemia-induced changes in brain and retina are related after 4- and 8-weeks of treatment.
Student Name: Zidong An
Graduate Level: PhD
Field of Study/Major: Economics
Committee Chairs: Xuguang Sheng
Date of Presentation: May 15
Presentation Location: Kreeger Economics Conference Room 100
Time of Presentation: 10:00 am - 12:00 pm
Title of Dissertation: Information Rigidity and Macroeconomic Dynamics
This dissertation consists of three essays on the expectation formation process. The first chapter estimates information stickiness using the common component of professional forecasters' inattention to many economic variables. Information stickiness is hard to measure, but important for monetary policy effectiveness. Professional forecasters in the U.S. Survey of Professional Forecasters and cross-country Consensus Forecasts on average update information every three to four months. More importantly, forecaster inattention is state-dependent, and it is driven by both economic fundamentals and market volatility. Using a dynamic stochastic general equilibrium (DSGE) model with inattentive firms, this chapter characterizes the relationship between inattention and monetary policy effectiveness. Using empirical analyses, this paper confirms that monetary policy is more effective when firms are inattentive.
The second chapter discusses the assumption of Sticky Information model and derives two novel model implications. Both ex-ante forecast disagreement and ex-post forecast accuracy are associated with the level of inattention at individual level. Between ex-ante forecast disagreement and inattention, there is a U-shaped relationship. When an individual forecaster updates information much more or much less frequently relative to the average level, she has a larger disagreement. Between ex-post forecast accuracy and inattention, there is a strictly negative relationship. A forecaster who tend to update her forecast more frequently is expected to have a higher level of forecast accuracy. Using individual-level forecast data, this chapter finds that forecasters are not interchangeable in terms of forecast disagreement, forecast accuracy, and inattention. Furthermore, the empirical results confirm the model implications.
The third chapter provides an assessment of the IMF's unemployment forecasts, which have not received much scrutiny to date. The focus is on the internal consistency of the IMF's growth and unemployment forecasts, and specifically on seeing whether the relationship between the two is consistent with the relationship in the data, i.e., with Okun's Law. We find that the average performance is good, in the sense that the relationship between growth and unemployment forecasts is fairly comparable to that which prevails in the data: on average, the Okun coefficient in the forecasts mirrors the Okun coefficient in the data. Nevertheless, there is room for improvement, particularly in the year-ahead forecasts and for the group of middle-income countries. We show that a linear combination of Okun-based unemployment forecasts and WEO unemployment forecasts can deliver significant gains in forecast accuracy for developing economies.
Student Name: Sydney Gourlay
Graduate Level: PhD
Field of Study/Major: Economics
Committee Chairs: Professor Maria Floro
Date of Presentation: May 15, 2019
Presentation Location: Kreeger 100
Time of Presentation: 12:15 pm
Title of Dissertation: DO METHODS MATTER? IMPLICATIONS FOR UNDERSTANDING AGRICULTURAL PRODUCTIVITY DRIVERS IN SMALLHOLDER FARMING SYSTEMS
The effects of the structure and efficiency of agricultural systems are pervasive throughout developing economies, reaching numerous sectors including food security, health, economic growth, income inequality, poverty and vulnerability, and gender equality, among others. Despite the ubiquitous impacts of agricultural productivity on various indicators of wellbeing, realized productivity is generally well below its potential. Increasing agricultural productivity, therefore, is central to many poverty reduction policies. Policy aimed at increasing agricultural productivity is often informed by household surveys that rely on self-reported information. Measurement error in household survey data could potentially lead to inappropriate or insufficient understandings of the drivers of agricultural production and the policy levers that could be used to improve productivity.
I hypothesize that measurement error in household surveys, including that resulting from inadequate survey methodology, alters our understanding of certain agricultural productivity relationships. Unique survey data in Uganda and Ethiopia, which included the measurement of key agricultural inputs and production through both traditional self-reported methods as well as utilizing highly advanced data collection methodology, allows for unprecedented agricultural analysis. This dissertation, which takes the form of three essays, examines the following questions: (i) can the commonly observed inverse farm size-productivity relationship be explained by measurement error in production measurement?; (ii) how is agricultural productivity hindered by crop-specific soil suitability, and how are productivity constraints distributed across the agricultural population?; and (iii) does high-resolution plot-level soil data reveal gender-differentiated land quality endowments, and does this explain observed gender-based productivity gaps?
Through this research I illustrate that methods do matter. The controversial inverse farm size-productivity relationship vanishes when objective methods of measuring crop production and plot area are used in place of farmer estimated production. Analysis of crop-specific soil suitability reveals additional nuances of agricultural productivity that are otherwise undetectable with farmer-assessment of soils, highlighting limited potential production gains for maize farmers in Eastern Uganda. Finally, utilization of high-resolution plot-level soil data vis-à-vis geospatial soil data uncovers gender-based differences in soil quality endowments, which, when included in productivity analysis, are shown to make up as much as 31.2 percent of the total gender-based productivity gap in Malawi.