Doctor of Philosophy, The Ohio State University, 2003, Economics

This dissertation investigates the relationship between inflation and economic growth emphasizing the financial sector and differences across countries. The first essay uses a cash-in-advance model with credit as an alternative means of payment and simulates several steady-state relationships. Exogenous financial innovations lead to upward trending velocity as has been observed in the last half century or more. Differences in financial innovation across countries, or within a country and across time, affects how inflation affects output growth. Lower costs of intermediation imply that inflation affects output less than in countries with higher costs and similar effects hold within the same country when intermediation costs have changed over time. Either case presents difficulties for empirical tests. The second essays examines the robustness of empirical inflation-growth results. Bayesian Model Averaging is used to explore the relationship between inflation and growth. Cross-sectional data over long periods of time provide no evidence of an inflation-growth relationship. Panel data, using 5-year averages, produces starkly different results, in particular, inflation is one of the more robust variables. Threshold affects are discussed but do not alter the main conclusions. Parameter heterogeneity across countries is investigated with the finding that coefficients vary widely with even small changes in the sample. The negative relationship of inflation and growth is still strong, but the importance of the point estimates is questionable. The third essay utilizes standard time series methods. Structural inflation shocks are identified by imposing long-run restrictions on the model, and the effects of inflation on separate sectors of the economy are examined. This approach is applied to seven industrialized countries, with the results that inflation affects sectoral output differently, with little similarity across countries. Sectors such as manufacturing, agriculture an (open full item for complete abstract)

Committee: Eric Fisher (Advisor) Subjects: Economics, General

Doctor of Philosophy, The Ohio State University, 2003, Economics

Despite the success of inflation tageting in the 1990s around the world, recognizing the weaknesses of inflation targeting, many have argued that more refinements are needed. When output is persistent, inflation targeting tends to have high long-run inflation volatility. So price-path targeting, which promises lower inflation volatility, can be considered as an alternative. However, I argue that an optimally chosen hybrid of inflation targeting and price-path targeting gives even lower inflation volatility. Another weakness of inflation targeting is that central bankers, when left to act under discretion, tend to create a bias toward output stabilization. Therefore, I argue that central bankers should be appropriately conservative, and the level of conservativeness depends on output persistence. Also, I show that there is a close relationship between central bankers' conservativeness and the horizon over which price level is brought back to the desired path. One of the important aspects of inflation targeting is that it is inherently forward-looking. So, this requires a good inflation forecast, such as trimmed mean estimators suggested here. I show several methods of finding these trimmed mean estimators of inflation, which are more efficient than headline CPI inflation. However, these suggestions and elaborations should be implemented together with measures to earn the public's trust, without which success cannot be guaranteed. That is, central banks need to find the right balance between performing monetary policy optimally and earning the public's trust.

Committee: Stephen Cecchetti (Advisor) Subjects: Economics, General

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2024, Media and Communication

The World Bank classifies the Lebanese economic crisis as one of the 10 worst such crises globally since the 19th century—and possibly one of the top three. Azma fawq ‘azma [crisis upon crisis] includes financial collapse, inability to care for 1.5 million refugees, the highest number of refugees per capita in the world, the devastation of the COVID-19 pandemic on an already fragile healthcare system, and the catastrophic explosion in Beirut, one of the worst non-nuclear explosions in human history, that killed 218 people, injured 7,000, and left 300,000 unhoused. Due to unprecedented levels of inflation, the Lebanese pound has lost 90% of its value, food prices have risen 500%, and 80% of the population lives in poverty. These crises have transformed Lebanon from a beacon of success to a failed state. Given the severe lack of organizational communication research in the Mashreq (Middle East), this dissertation is of particular importance as it fills a critical gap in research. The dissertation takes an interdisciplinary approach to examine how NGOs mobilize support, provide services, and engage in interorganizational collaboration to support citizens, residents, and asylum seekers struggling to survive in Lebanon. The triangulated methodological approach includes policy analysis, two phases of field research in Lebanon, and in-depth interviews with leaders, administrators, employees, and volunteers representing 52 NGOs. Interview respondents (n = 64) provided first-hand experiences, insights, and assessments of NGOs' efforts to combat intersecting crises, reflected on the complexity of these crises, and highlighted the need for economic and political reform to assuage the feelings of being trapped in the azma fawq ‘azma. Emergent themes include the importance of collective identity through interorganizational collaboration, the benefits of group cohesion in providing support and services, a sense of purpose that has expanded alongside the crises, a continuing (open full item for complete abstract)

Committee: Lara Martin Lengel Ph.D. (Committee Chair); Lori Brusman Lovins Ph.D. (Committee Member); Terry Rentner Ph.D. (Committee Member); Ellen Gorsevski Ph.D. (Committee Member) Subjects: Area Planning and Development; Banking; Communication; Economics; Management; Middle Eastern Studies; Minority and Ethnic Groups; Near Eastern Studies; Organization Theory; Organizational Behavior; Peace Studies; Political Science; Regional Studies; Rhetoric; Sustainability

PhD, University of Cincinnati, 2023, Arts and Sciences: Physics

The cosmic microwave background (CMB) is a snapshot of the universe at recombination, the moment when the universe became transparent. Understanding the CMB could allow us to constrain or rule out aspects of inflation theory, which suggests that the Universe underwent a period of rapid expansion mere moments after the Big Bang. Specifically, we hope to detect primordial gravitational waves (PGW), an as yet unobserved phenomenon predicted by many inflationary models. BICEP/Keck is an experiment based at the South Pole with telescopes that are specified to observe B-mode polarization patterns caused by PGW at microwave wavelengths. The tensor-to-scalar ratio r is a parameter which if constrained could provide indirect evidence of PGWs. Presented is the work I have done in an internal linear combination (ILC) component separation method to separate the CMB signal from galactic foregrounds while minimizing noise, and the likelihood analysis I performed with the ILC results in an effort to constrain r.

Committee: Colin Bischoff Ph.D. (Committee Chair); L. C. R. Wijewardhana Ph.D. (Committee Member); Kay Kinoshita Ph.D. (Committee Member); Adam Aurisano Ph.D. (Committee Member) Subjects: Astrophysics

Doctor of Philosophy, The Ohio State University, 2023, Statistics

Exponential family PCA (Collins et al., 2001) is a widely used dimension reduction tool for capturing a low-dimensional latent structure of exponential family data such as binary data or count data. As an extension of principal component analysis (PCA), it imposes a low-rank structure on the natural parameter matrix, which can be factorized into two matrices, namely, the principal component loadings matrix and scores matrix. These loadings and scores share the same interpretation and functionality as those in PCA. Loadings enable exploration of associations among variables, scores can be utilized as low-dimensional data embeddings, and estimated natural parameters can impute missing data entries. Despite the popularity of exponential family PCA, we find several statistical issues associated with this method. We investigate these issues from a statistical perspective and propose remedies in this dissertation. Our primary concern arises from the joint estimation of loadings and scores through the maximum likelihood method. As in the well-known incidental parameter problem, this formulation with scores as separate parameters may result in inconsistency in the estimation of loadings under the classical asymptotic setting where the data dimension is fixed. We examine the population version of this formulation and show that it lacks Fisher consistency in loadings. Additionally, estimating scores can be viewed as performing a generalized linear model with loadings as covariates. Maximum likelihood estimation (MLE) bias is naturally involved in this process but is often ignored. Upon identifying two major sources of bias in the estimation process, we propose a bias correction procedure to reduce their effects. First, we deal with the discrepancy between true loadings and their estimates under a limited sample size. We use the iterative bootstrap method to debias loadings estimates. Then, we account for sampling errors in loadings by treating them as covariates with me (open full item for complete abstract)

Committee: Yoonkyung Lee (Advisor); Asuman Turkmen (Committee Member); YunZhang Zhu (Committee Member) Subjects: Statistics

Master of Arts (MA), Bowling Green State University, 1950, Economics

Committee: Lloyd A. Helms (Advisor) Subjects: Economics

PhD, University of Cincinnati, 2021, Arts and Sciences: Physics

The Cosmic Microwave Background (CMB) has provided a wealth of information since its discovery in the 1960s. The blackbody nature and the temperature anisotropies of the CMB have helped form the current cosmological paradigm of a hot Big Bang and the ?CDM model of the Universe. We are now looking to the polarization field of the CMB for answers about the early Universe. The theory of Cosmic Inflation postulates that the Universe went through a period of exponential expansion in the earliest moments. This theory generally predicts a stochastic background of primordial gravitational waves which would leave a faint B-mode pattern in the polarization of the CMB. The BICEP/Keck Array telescopes are small aperture multi-frequency microwave polarimeters at the Amundsen–Scott South Pole Station. These telescopes continuously observe a ~1% patch of the Southern sky targeting degree angular scales where the amplitude of the primordial gravitational waves is predicted to peak. The multi-frequency observation allows for the disentanglement of galactic foreground signals from the CMB signal. To date, these experiments provide the tightest constraints on the tensor-to-scalar ratio at r < 0.07 at 95% confidence. The discussion of this thesis is split into two parts. In the first part, it will discuss the design, development, and performance of the BICEP Array Housekeeping system. The Housekeeping system is an electronics data acquisition system designed to read out the thermistors of the cryogenically cooled receivers and provide temperature control. The second part of the thesis will discuss high level data analysis using a multi-component model of the bandpower data. In particular, there will be discussion of a novel minimum variance quadratic estimator used as an alternative to the maximum likelihood estimator.

Committee: Colin Bischoff Ph.D. (Committee Chair); Matthew Bayliss Ph.D. (Committee Member); Alexandre Sousa Ph.D. (Committee Member); Hans-Peter Wagner Ph.D. (Committee Member) Subjects: Physics

Master of Arts, Miami University, 2021, Economics

This paper presents a novel dataset of debt projections from 29 countries to analyze the relationship between public debt projections and economic growth. I find that when year-of debt is estimated to be above 90 percent, a 10-percentage point increase in the four-year projected debt level is associated with a 6.73 percentage point decline in 5-year forward average GDP per capita growth. Declines in economic growth are estimated to be larger for projections in the high debt regime as opposed to the normal debt regime. This study also finds that as the uncertainty of projection accuracy increases due to an increase in the projection horizon, the magnitude of the coefficient on the normal regime becomes statistically insignificantly different from zero. Alternative threshold levels are tested to identify the point at which high projected debt levels signal to agent's a possible policy change. My findings support the existing debt-growth and economic uncertainty literature and contribute the importance of debt projections and expectations in advancing our understanding of the relationship between government debt and economic growth.

Committee: Jonathan Wolff (Advisor); David Lindequist (Committee Member); Nam Vu (Committee Member) Subjects: Economics

Doctor of Philosophy, The Ohio State University, 2018, Educational Studies

While studying rare events or behaviors in education and social science research, it is usual to encounter zero-inflated and/or overdispersed count data. Modeling the total number of serious violent incidents reported to the police that occurred on school campus from the 2010 School Survey on Crime and Safety (SSOCS) represents one such case and is the motivation for this dissertation. Generally, when overdispersion relative to Poisson is observed, Negative Binomial (NB) models are used. If there is additional zero-inflation in the NB model, then Hurdle Negative Binomial (HNB) model is used among other alternative models. The HNB models are fairly popular in Econometrics, Ecology, and Public Health, but is nascent in educational research. This study has been undertaken to learn the mechanisms of HNB models and make them accessible to educational researchers. To this effect, the HNB distribution was studied and its correct variance formula was derived using moment generating function. Simulation study was conducted to understand the effects of zero-inflation, overdispersion, and sample size on the HNB and NB models. It was also seen that in practice the flexibility of HNB models in accommodating different sets of predictors for binary and count parts were rarely made use of. The simulation study was expanded to examine the consequences of using different sets of predictors on conditional mean and probability of zero for varying levels of zero-inflation, overdispersion, and sample size. Finally, a demonstration of applying HNB models were presented using the 2010 SSOCS data. In this demonstration, detailed graphical exploratory data analysis for categorical variables are presented. Model fit evaluation has also been discussed. Finally, issues faced in applying HNB models were discussed and recommendations were provided for educational and social science researchers.

Committee: Ann O'Connell (Advisor); Robert Cudeck (Committee Member); Eloise Kaizar (Committee Member); Jessica Logan (Committee Member) Subjects: Educational Sociology; Social Research; Statistics

Doctor of Philosophy, The Ohio State University, 1986, Graduate School

Committee: Not Provided (Other) Subjects: Economics

Doctor of Philosophy, The Ohio State University, 1986, Graduate School

Committee: Not Provided (Other) Subjects: Economics

Doctor of Philosophy, The Ohio State University, 1984, Graduate School

Committee: Not Provided (Other) Subjects: Economics

Doctor of Philosophy, The Ohio State University, 1983, Graduate School

Committee: Not Provided (Other) Subjects: Economics

Doctor of Philosophy, The Ohio State University, 1974, Graduate School

Committee: Not Provided (Other) Subjects: Business Administration

Doctor of Philosophy, The Ohio State University, 1969, Graduate School

Committee: Not Provided (Other) Subjects: Economics

Doctor of Philosophy, The Ohio State University, 1963, Graduate School

Committee: Not Provided (Other) Subjects: Economics

Doctor of Philosophy, The Ohio State University, 1959, Graduate School

Committee: Not Provided (Other) Subjects: Economics

PhD, University of Cincinnati, 2014, Medicine: Biostatistics (Environmental Health)

Real-life count data are frequently characterized by over-dispersion (variance greater than mean) and excess zeros. Various methods exist in literature to combat zero-inflation and over-dispersion in count data. Among them Zero-inflated count models provide a parsimonious yet powerful way to model excess zeros in addition to allowing for over-dispersion. Such models assume that the counts are a mixture of two separate data generation process: one generates only zeros, and the other is a Poisson type data-generating process. Among mostly discussed models are zero-inflated Poisson (ZIP), zero inflated negative binomial (ZINB) and zero-inflated generalized Poisson (ZIGP). However, the performance and application condition of these models are not thoroughly studied. In this work, these common zero-inflation models are reviewed and compared under specified over-dispersion conditions via simulated data and real-life data in terms of statistical power and type I error rate. Performance of each model will be listed side by side to give a clear view of each model's pros and cons in specific over-dispersion and zero-inflation condition. Further, the ZIGP model is chosen to extend to a more general situation where a random effect is incorporated to account for within-subject correlation and between subject heterogeneity. Likelihood based estimation of treatment effect will be developed for analysis of randomized experiments with random effect. Effect of model misspecification on model's performance will be investigated in areas such as type I error rate, standard error and empirical statistical power. Case studies will be presented to illustrate the application these models.

Committee: Marepalli Rao Ph.D. (Committee Chair); Jianfei Guo Ph.D. (Committee Member); Rakesh Shukla Ph.D. (Committee Member); Paul Succop Ph.D. (Committee Member); Changchun Xie Ph.D. (Committee Member) Subjects: Biostatistics

PhD, University of Cincinnati, 2000, Arts and Sciences : Economics

Dispersion of prices of essentially homogeneous products has fascinated economists for decades. Explanations for the phenomenon include lack of information on the part of consumers (Stigler, 1961; Rothschild, 1973; Salop and Stiglitz, 1977); absence of market power, or ability to collude, on the part of producers (Means, 1935, 1939; Stigler and Kindahl, 1970; Carlton, 1986; Caucutt, Ghosh, and Kelton, 1999); uncertainty in pricing introduced by inflation or macroeconomic shocks (Vining and Elwertowski, 1976; Domberger, 1987; Van Hoomissen, 1988); and simple pricing independence of downstream resellers (Lafontaine, 1995, 1999). Our research offers the first integrated empirical study of price dispersion in the sense of explicitly accounting for all but the fourth explanation; we implicitly acknowledge the fourth. The theoretical foundation for our study is the Salop and Stiglitz two-price equilibrium in a monopolistically competitive market. After introducing variables that capture the comparative-static results from the Salop and Stiglitz equilibrium (including variables that account for the costs of consumer search), we add market-structure and inflation variables as well. We have a rich, unique data set of monthly gasoline prices from January 1984 through December 1998 for three different grades of gasoline at thirty-four gasoline stores spread across three geographic market zones within the Greater Cincinnati Metropolitan Area. We follow the time-series procedures of Granger and Newbold (1974) and Phillips (1986) in ensuring variable stationarity before model estimation. We find support for the positive impacts on dispersion of lack of consumer information, low seller concentration, and inflationary pressure. Moreover, differences in results across brands of gasoline, grades of gasoline, and geographic zones lend additional support to the lack-of-consumer-information hypothesis. Finally, as a byproduct of our research, we shed some light on the mechanics of gasol (open full item for complete abstract)

Committee: Christina Kelton (Advisor) Subjects: Economics, Theory

Doctor of Philosophy, The Ohio State University, 2010, Economics

My dissertation investigates what the main sources of fluctuations in some are of key macroeconomic variables and how they propagate in the economy. More importantly, I quantify these shocks by using statistical methods and study their transmission mechanism in both closed and open economy settings. The first essay, “Explaining International Business Cycles with Real Frictions and Technology Shocks: A Bayesian Approach”, uses a Bayesian approach to estimate a standard international real business cycle model augmented with time non-separable preferences, variable capacity utilization and investment adjustment costs. First, I find while most of the output and consumption fluctuations attribute to neutral and world technology shocks, investment-specific technology (IST) shocks explain the bulk of investment volatility. Second, my estimated model with IST shocks simultaneously accounts for the negative correlation between the real exchange rate and relative consumption and the negative correlation between the terms of trade and relative output. IST shocks act as demand shocks by giving firms an incentive to increase labor and capacity utilization and households an incentive to increase domestic absorption, thus causing appreciation of international prices when consumption and output are also rising. In addition, compared to other real shocks, IST shocks generate high volatilities in the relative prices. Third, by using marginal likelihood comparison, I find that the success of the model depends to a large extent on variable capacity utilization; investment adjustment costs play only a minor role. After a positive IST shock, increased capital utilization both induces a stronger response of labor by increasing the marginal product of labor and generates comovement of consumption and output. The second essay, “Monetary Policy and the Wealth Effect”, studies the transmission of monetary policy shocks under different wealth effects on labor hours. In our (open full item for complete abstract)

Committee: Bill Dupor (Advisor); Paul Evans (Committee Member); Nan Li (Committee Member) Subjects: Economics