Essays on Finance and Labor

My dissertation applies different empirical methodologies with a variety of administrative datasets to investigate the interrelationship between firms and labor market outcomes. Chapter 1 examines how and why market power affect wages differently in financial industries. Increasing industry concentration has raised concerns that declining competition among firms for labor has led to slow wage growth. However, I find that finance wages have increased by almost three times the increase in non-finance wages, despite similar trends in market concentration. Using data from the U.S. Census, I construct measures of firm-specific market power and show that higher market power is associated with significantly higher wages in finance than in non-finance. I provide evidence that rent-sharing plays an essential role in driving the more pronounced effect of market power on finance wages for two reasons. First, financial firms with higher market power can extract relatively higher rents to share. Second, financial firms give a relatively higher share of rents to workers, especially high-skill workers, due to relatively higher worker bargaining power. As rents are disproportionally distributed to high-skill workers, financial firms with higher market power are associated with relatively higher within-firm inequality. Chapter 2 is joint work with Paige Ouimet and Elena Simintzi. This chapter confronts the question of how mergers and acquisitions (M&As) contribute to important trends in job polarization and wage inequality. We document shifts in occupational composition following M&As along with increases in average wages and wage inequality. We propose M&As act as a catalyst for technological change. Due to an increase in scale, improved efficiency and lower financial constraints, M&As facilitate technology adoption, disproportionately increasing the productivity of high-skill workers and enabling the displacement of mid-income routine occupations. We document these findings in M&A impacted establishments as compared to a matched sample of control establishments. These results generalize within industries, suggesting M&A activity is an important driver of economy-wide trends in job polarization and income inequality. Chapter 3 is joint work with Tania Babina, Paige Ouimet and Rebecca Zarutskie. This chapter answers why young firms pay less. Using US Census employer-employee matched data, we show that lower wages at new firms are driven by the selection of lower quality workers into new firms. After including worker fixed effects, nearly three quarters of the new firm wage difference disappears. Once we control for firm fixed effects, absorbing time-invariant firm quality, the wage difference between new and established firms becomes economically unimportant. Overall, our findings indicate that, for a given worker who has job opportunities at similar quality new and established firms, the expected wage penalty of working at the new firm is, on average, economically insignificant. Moreover, young firms that can hire high-quality workers have higher future survival rates and total employment, suggesting that human capital is an important predictor of young firm success.Doctor of Philosoph

Good news or bad news, which do you want first? The importance of the sequence and organization of Information for financial decision-making: a neuro-electrical imaging study

Investment decisions are largely based on the information investors received from the target firm. Thaler introduced the hedonic editing framework, in which suggests that integration/segregation of information influence individual's perceived value. Meanwhile, when evaluating the evidence and information in a sequence, order effect and biases have been found to have an impact in various areas. In this research, the influence of the Organization of Information (Integration vs. Segregation) and the Sequence of Information (Negative-Positive order vs. Positive-Negative order) on individual's investment decision-making both at the behavioral level (decision) and neurometrix level (measured by an individual's emotion and Approach Withdraw tendency) was assessed for the three groups of information: a piece of Big Positive Information and a piece of Small Negative Information, a piece of Big Negative Information and a piece of Small Positive Information, and a piece of Small Negative information. The behavioral results, which are an individual's final investment decision, were consistent for all three scenarios. In general, individuals will invest more/retire less when receiving two pieces of information in a Negative-Positive order. However, the neurometric results (Emotional Index, Approach Withdraw Index and results from LORETA) show differences among information groups. An effect of the Sequence of Information and the Organization of Information was found for the different scenarios. The results suggest that in the scenarios that involve large-scale information, the organization of information (Integration vs. Segregation) influences the emotion and Approach Withdraw tendency. The results of this investigation should provide insight for effective communication of information, especially when large-scale information is involved

A lightweight identity-based cloud storage auditing supporting proxy update and workload-based payment

Cloud storage auditing allows the users to store their data to the cloud with a guarantee that the data integrity can be efficiently checked. In order to release the user from the burden of generating data signatures, the proxy with a valid warrant is introduced to help the user process data in lightweight cloud storage auditing schemes. However, the proxy might be revoked or the proxy’s warrant might expire. These problems are common and essential in real-world applications, but they are not considered and solved in existing lightweight cloud storage auditing schemes. In this paper, we propose a lightweight identity-based cloud storage auditing scheme supporting proxy update, which not only reduces the user’s computation overhead but also makes the revoked proxy or the expired proxy unable to process data on behalf of the user any more. The signatures generated by the revoked proxy or the expired proxy can still be used to verify data integrity. Furthermore, our scheme also supports workload-based payment for the proxy. The security proof and the performance analysis indicate that our scheme is secure and efficient

Measurement of Soil Water Content with Dielectric Dispersion Frequency

Frequency domain reflectometry (FDR) is an inexpensive and attractive methodology for repeated measurements of soil water content (θ). Although there are some known measurement limitations for dry soil and sand, a fixed-frequency method is commonly used with commercially available FDR probes. The purpose of our study was to determine if the soil dielectric spectrum could be used to measure changes in θ. A multifrequency FDR probe was constructed with a 6-mm diameter, and a soil dielectric spectrum was obtained. Using the dielectric spectrum, the dielectric dispersion frequency (fd) was determined. It was discovered that changes in fd were highly correlated with changes in θ, and a third-order polynomial equation (R2 = 0.96) was developed describing the relationship. The effectiveness of fd for θ measurement was evaluated for three soils and a sand across a range of θ. The effects of soil temperature and soil salinity were also evaluated. Accurate measurements of θ were obtained even in dry soil and sand. The root mean square error of the θ estimated by the fdmeasurement was 0.021. The soil temperature and soil salinity had no measureable effects on θ determination. The use of fd for θ determination should be an effective and accurate methodology, especially when dry soils, soil temperature, and/or soil salinity could potentially cause problems with the θ measurements

DCSAU-Net: A deeper and more compact split-attention U-Net for medical image segmentation

Deep learning architecture with convolutional neural network achieves outstanding success in the field of computer vision. Where U-Net has made a great breakthrough in biomedical image segmentation and has been widely applied in a wide range of practical scenarios. However, the equal design of every downsampling layer in the encoder part and simply stacked convolutions do not allow U-Net to extract sufficient information of features from different depths. The increasing complexity of medical images brings new challenges to the existing methods. In this paper, we propose a deeper and more compact split-attention u-shape network, which efficiently utilises low-level and high-level semantic information based on two frameworks: primary feature conservation and compact split-attention block. We evaluate the proposed model on CVC-ClinicDB, 2018 Data Science Bowl, ISIC-2018, SegPC-2021 and BraTS-2021 datasets. As a result, our proposed model displays better performance than other state-of-the-art methods in terms of the mean intersection over union and dice coefficient. More significantly, the proposed model demonstrates excellent segmentation performance on challenging images. The code for our work and more technical details can be found at https://github.com/xq141839/DCSAU-Net

Trichoderma reesei FS10-C enhances phytoremediation of Cd-contaminated soil by Sedum plumbizincicola and associated soil microbial activities

This study aimed to explore the effects of Trichoderma reesei FS10-C on the phytoremediation of Cd-contaminated soil by Sedum plumbizincicola as well as soil fertility. After characterizing the Cd tolerance of T. reesei FS10-C, a pot experiment was carried out to investigate the plant growth and Cd uptake of S. plumbizincicola with the addition of inoculation agents with/without T. reesei FS10-C. The soil samples in pots were analyzed for pH, available phosphorus (P), microbial biomass C, enzyme activities, microbial community functional diversity and Trichoderma colonization ability. The results indicated that FS10-C possessed high Cd resistance up to 300 mg L-1. All inoculation agents enhanced the biomass of plant shoots by 6-53% fresh weight and 16-61% dry weight as well as Cd uptake in plant shoots by 10-53% compared with the control. In addition, soil biomass C, enzyme activities and microbial community evenness were all increased to varying degrees by all inoculation agents, indicating that soil microbial biomass and activities were both enhanced. It was also found that the two inoculation agents accompanied by FS10-C were better compared with the inoculation agents without FS10-C on all accounts, from which it could be concluded that T. reesei FS10-C was effective in improving Cd phytoremediation of S. plumbizincicola and soil fertility. Furthermore, among all the inoculation agents, solid fermentation powder of FS10-C demonstrated the greatest capacity to enhance plant growth, Cd uptake, nutrient release, and microbial biomass and activities, as indicated by its superior ability to colonize Trichoderma. Thus, we could also conclude that solid fermentation powder of FS10-C was a good candidate for use as an inoculation agent for T. reesei FS10-C to improve the phytoremediation of Cd-contaminated soil and soil fertility