Essays on Uncertainty, Imperfect Information, and Investment Dynamics

Understanding how imperfect information affects firms' investment decision helps answer important questions in economics, such as how we may better measure economic uncertainty; how firms' forecasts would affect their decision-making when their beliefs are not backed by economic fundamentals; and how important are the business cycle impacts of changes in firms' productivity uncertainty in an environment of incomplete information. This dissertation provides a synthetic answer to all these questions, both empirically and theoretically. The first chapter, provides empirical evidence to demonstrate that survey-based forecast dispersion identifies a distinctive type of second moment shocks different from the canonical volatility shocks to productivity, i.e. uncertainty shocks. Such forecast disagreement disturbances can affect the distribution of firm-level beliefs regardless of whether or not belief changes are backed by changes in economic fundamentals. At the aggregate level, innovations that increase the dispersion of firms' forecasts lead to persistent declines in aggregate investment and output, which are followed by a slow recovery. On the contrary, the larger dispersion of future firm-specific productivity innovations, the standard way to measure economic uncertainty, delivers the ``wait and see" effect, such that aggregate investment experiences a sharp decline, followed by a quick rebound, and then overshoots. At the firm level, data uncovers that more productive firms increase investments given rises in productivity dispersion for the future, whereas investments drop when firms disagree more about the well-being of their future business conditions. These findings challenge the view that the dispersion of the firms' heterogeneous beliefs captures the concept of economic uncertainty, defined by a model of uncertainty shocks. The second chapter presents a general equilibrium model of heterogeneous firms subject to the real productivity uncertainty shocks and informational disagreement shocks. As firms cannot perfectly disentangle aggregate from idiosyncratic productivity because of imperfect information, information quality thus drives the wedge of difference between the unobserved productivity fundamentals, and the firms' beliefs about how productive they are. Distribution of the firms' beliefs is no longer perfectly aligned with the distribution of firm-level productivity across firms. This model not only explains why, at the macro and micro level, disagreement shocks are different from uncertainty shocks, as documented in Chapter 1, but helps reconcile a key challenge faced by the standard framework to study economic uncertainty: a trade-off between sizable business cycle effects due to changes in uncertainty, and the right amount of pro-cyclicality of firm-level investment rate dispersion, as measured by its correlation with the output cycles.

ASSESSING THE LEVEL OF TECHNOLOGY INTEGRATION OF TITLE I TEACHERS IN A LARGE URBAN SCHOOL DISTRICT

By law, Title I schools employ teachers who are both competent in their subject knowledge and State certified. In addition, Title I teachers receive ongoing professional development in technology integration and are equipped with the latest innovative resources to integrate technology in the classroom. The aim is higher academic achievement and the effective use of technology in the classroom. The investment to implement technology in this large urban school district to improve student achievement has continued to increase. In order to infuse current and emerging technology throughout the curriculum, this school district needs to know where teachers have, and have not, integrated technology. Yet the level of how technology is integrated in Title I schools is unknown. This study used the Digital-Age Survey Levels of Teaching Innovation (LoTi) to assess 508 Title I teachers’ technology integration levels using three major initiatives purchased by Title I— the iPads program, the Chromebook initiative, and the interactive whiteboards program. The study used a quantitative approach. Descriptive statistics, regression analysis, and statistical correlations were used to examine the relationship between the level of technology integration and the following dependent variables: personal computer use (PCU), current instructional practices (CIP), and levels of teaching innovation (LoTi). With this information, budgetary decisions and professional development can be tailored to the meet the technology implementation needs of this district. The result of this study determined a significant relationship between the level of teaching innovation, personal computer use, and current instructional practices with teachers who teach with iPad, Chromebook, and/or interactive whiteboard. There was an increase in LoTi, PCU, and CIP scores with increasing years of experience of Title I teachers. There was also a significant relationship between teachers with 20 years or more teaching experience and their LoTi score.

Toxicity and Contamination in Bear Creek Sediment: Spatial Analysis and Implications for Risk Assessment

The sediments of Bear Creek near Baltimore, Maryland demonstrate substantial toxicity to benthic organisms, and contain a complex mixture of organic and inorganic contaminants. The present study maps the spatial extent and depth profile of toxicity and contamination in Bear Creek, and explores correlations between heavy metals, organic contaminants, and toxic responses. Two novel analytical techniques – handheld XRF and an antibody-based PAH biosensor – were applied to samples from the site to quantify total metals and total PAHs in sediments. By comprehensively assessing toxicity in Bear Creek, the present study provides data to inform future risk assessments and management decisions relating for the site, while demonstrating the benefits of applying joint biological assays and chemical assessment methods to sediments with complex contaminant mixtures.