Three Essays on Corruption and Government Finance

There are three chapters in my dissertation. In chapter one I study the impact of government corruption on tax avoidance by corporations with tax liability in China. I begin by developing a model of a firm\u27s choice of tax avoidance based on the level of corruption in the firm\u27s province. I show that a higher level of government corruption and a higher tax rate are predicted to increase a firm\u27s tax avoidance. My empirical estimates show that a one-standard-deviation increase in government corruption corresponds to a 6% increase in tax avoidance by firms, based on data from nearly 600,000 firms from 1998 to 2007. When I separate the sample by type of ownership of firms, I find that domestic private firms tend to avoid a larger portion of their tax liabilities than foreign or state-owned firms. I also find that tax avoidance increases when the effective tax rate increases. The size of the firm, age of the firm, and whether the firm exports from China also influence tax avoidance. In chapter two, a joint work with Sergey Mityakov, we study the impact of competition on tax avoidance by corporations in Mexico. Using more than 2,000 firm level data, we show that firms tend to avoid more taxes in less competitive markets, that is more concentrated market. A one standard deviation increase in competition leads to a 7.7% increase in tax avoidance. By splitting the sample based on ownership structure, we show that domestic firms avoid more taxes. When we separate the firms according to the plant size, we find that larger firms tend to avoid more taxes. We find robust and consistent results by using different competition measures and other robustness tests. In chapter three, I theoretically demonstrate how fiscal decentralization affects corruption. The theory predicts that fiscal decentralization reduces corruption. This result is then tested using a panel data set of 31 provincial level government from 1998 to 2007 in China. My estimates suggest that fiscal decentralization in government expenditures and government revenue is negatively correlated with corruption. Using leader and location dummy variables, I find that central government leaders can influence the corruption level in China. I also find that more developed regions in China tend to be less corrupt

Saliency guided local and global descriptors for effective action recognition

This paper presents a novel framework for human action recognition based on salient object detection and a new combination of local and global descriptors. We first detect salient objects in video frames and only extract features for such objects. We then use a simple strategy to identify and process only those video frames that contain salient objects. Processing salient objects instead of all frames not only makes the algorithm more efficient, but more importantly also suppresses the interference of background pixels. We combine this approach with a new combination of local and global descriptors, namely 3D-SIFT and histograms of oriented optical flow (HOOF), respectively. The resulting saliency guided 3D-SIFT–HOOF (SGSH) feature is used along with a multi-class support vector machine (SVM) classifier for human action recognition. Experiments conducted on the standard KTH and UCF-Sports action benchmarks show that our new method outperforms the competing state-of-the-art spatiotemporal feature-based human action recognition metho

On Rachel Carson's Continuing Legacy: How Students at the University of Maryland Aim to Commemorate Carson in 21st Century Environmental Activism

I go by "Cecilia" Sun. This paper was also recently accepted to be presented at the 10th annual James C. McCroskey and Virginia P. Richmond Undergraduate Scholars Conference (USC) which is also held concurrently with the Eastern Communication Association’s 111th annual convention.Winner of the 2020 Library Award for Undergraduate ResearchThis paper explores gender discrepancies in public commemoration rhetoric in the context of current environmental activism. Simply who deserves to be remembered reveals a long history of gender inequality in the United States. In 2017, a group of students at the University of Maryland recognized the same pattern of the unequal representation of men to women in building dedications and attempted to reform that by starting a petition to dedicate the Plant Sciences building to ecologist and writer, Rachel Carson. Though the final result was unsuccessful, the recognition of this problem of unequal representation and taking action to reform is a step forward towards a more equitable future. Through this case study, this paper also looks at the wider uprise of youth-lead environmental activism

3D GLOH features for human action recognition

Human action recognition from videos has wide applicability and receives significant interests. In this work, to better identify spatio-temporal characteristics, we propose a novel 3D extension of Gradient Location and Orientation Histograms, which provides discriminative local features representing not only the gradient orientation, but also their relative locations. We further propose a human action recognition system based on the Bag of Visual Words model, by combining the new 3D GLOH local features with Histograms of Oriented Optical Flow (HOOF) global features. Along with the idea from our recent work to extract features only in salient regions, our overall system outperforms existing feature descriptors for human action recognition for challenging real-world video datasets

Study on the Formalized Development of the Street Stall Economybased on Domestic and International Experiences and Perspectives

The ground-floor economy has a long history as a significant part of the informal economy. Due to the dependence on its own social status and relationship to the government’s political and economic objectives, it has developed precariously in recent years. In the face of post-epidemic problems, a shortcut is to learn from international experience. This paper used the structural theory and drew from the secondary data, demonstrating the background of informal economy and exploring the rational ways to maintain and develop street vending. Spatialization, legalization and network digitization are proven international approaches, which display the empirical and theoretical implications to urban practice and studies