The Impact of the 2009 Federal Tobacco Excise Tax Increase on Youth Tobacco Use

Based on surveys of eighth-, tenth-, and twelfth-grade students, examines how the tobacco tax increase affected their use of cigarettes and other tobacco products. Considers contributing factors, such as the size of the tax hike, and policy implications

The earnings of American Jewish men: human capital, denomination and religiosity

This paper analyzes the determinants of the earnings of American Jewish men using the 2000/01 National Jewish Population Survey. Non-response to the question on earnings is analyzed. Earnings are related to conventional human capital variables, as well as Jewish-specific variables. Except for the size of place and region variables, the standard human capital variables have similar effects for Jews and the general population. Jewish day schooling as a youth enhances earnings. Earnings vary by denomination, with Conservative Jews earning the most. The effect on earnings of religiosity (measured by synagogue attendance) is not monotonic. Earnings are highest for those who attend only once a wee

Semi-supervised multiscale dual-encoding method for faulty traffic data detection

Inspired by the recent success of deep learning in multiscale information encoding, we introduce a variational autoencoder (VAE) based semi-supervised method for detection of faulty traffic data, which is cast as a classification problem. Continuous wavelet transform (CWT) is applied to the time series of traffic volume data to obtain rich features embodied in time-frequency representation, followed by a twin of VAE models to separately encode normal data and faulty data. The resulting multiscale dual encodings are concatenated and fed to an attention-based classifier, consisting of a self-attention module and a multilayer perceptron. For comparison, the proposed architecture is evaluated against five different encoding schemes, including (1) VAE with only normal data encoding, (2) VAE with only faulty data encoding, (3) VAE with both normal and faulty data encodings, but without attention module in the classifier, (4) siamese encoding, and (5) cross-vision transformer (CViT) encoding. The first four encoding schemes adopted the same convolutional neural network (CNN) architecture while the fifth encoding scheme follows the transformer architecture of CViT. Our experiments show that the proposed architecture with the dual encoding scheme, coupled with attention module, outperforms other encoding schemes and results in classification accuracy of 96.4%, precision of 95.5%, and recall of 97.7%.Comment: 16 pages, 8 figure

Open Banking: Credit Market Competition When Borrowers Own the Data

Open banking facilitates data sharing consented to by customers who generate the data, with the regulatory goal of promoting competition between traditional banks and challenger fintech entrants. We study lending market competition when sharing banks’ customer transaction data enables better borrower screening. Open banking can make the entire financial industry better off yet leave all borrowers worse off, even if borrowers have the control of whether to share their banking data. We highlight the importance of the equilibrium credit quality inference from borrowers’ endogenous sign-up decisions. We also study extensions with fintech affinities and data sharing on borrower preferences

Open Banking: Credit Market Competition When Borrowers Own the Data

Open banking facilitates data sharing consented by customers who generate the data, with a regulatory goal of promoting competition between traditional banks and challenger fintech entrants. We study lending market competition when sharing banks’ customer data enables better borrower screening or targeting by fintech lenders. Open banking could make the entire financial industry better off yet leave all borrowers worse off, even if borrowers could choose whether to share their data. We highlight the importance of equilibrium credit quality inference from borrowers’ endogenous sign-up decisions. When data sharing triggers privacy concerns by facilitating exploitative targeted loans, the equilibrium sign-up population can grow with the degree of privacy concerns

COMS: Customer Oriented Migration Service

Virtual machine live migration has been studied for more than a decade, and this technique has been implemented in various commercial hypervisors. However, currently in the cloud environment, virtual machine migration is initiated by system administrators. Cloud customers have no say on this: They can not initiate a migration, and they do not even know whether or not their virtual machines have been migrated. In this paper, we propose the COMS framework, which is short for Customer Oriented Migration Service . COMS gives more control to cloud customers so that migration becomes a service option and customers are more aware of the migration process. We have implemented a suite of modules in our COMS framework. Our evaluation results show that these modules could either bring performance benefit to cloud customers, or mitigate security threats in the cloud environment

The impacts of product characteristics and regulatory environment on smokers preferences for tobacco and alcohol: Evidence from a volumetric choice experiment.

OBJECTIVE: Concurrent use of alcohol and cigarettes is well-documented in the literature. However, it is unclear how e-cigarette regulations in a growing number of localities impact the use of tobacco and alcohol in the US. This study aims to evaluate the impacts of excise taxes, tobacco use restrictions in restaurants/bars, and availability of alcohol flavor in e-cigarettes on tobacco consumption, and their cross impacts on alcohol consumption. METHOD: A total of 181 US adult smokers who were using e-cigarettes and consuming alcohol participated in online volumetric choice experiments and reported on the quantity they would purchase among cigarettes, closed-system e-cigarettes, beer, and one other alcohol product (wine/liquor) under varying policy scenarios. RESULTS: Estimated own-price elasticities of demand for beer, liquor/wine, and cigarettes were -0.10, -0.11, and -0.16, respectively (p <  0.001). Higher beer (cross-price elasticity =  0.13) and liquor/wine prices (cross-price elasticity =  0.05) increased e-cigarette consumption (p <  0.05). If e-cigarettes were allowed in bars/restaurants, their consumption increased by 2.4 units (p <  0.001), and if cigarettes were allowed in bars/restaurants, e-cigarette consumption increased by 1.9 units (p <  0.01), relative to the mean consumption level. Greater reported weekly spending on alcohol and/or tobacco was associated with higher consumption of all products (p <  0.001). CONCLUSIONS: Higher taxes or prices may reduce the consumption of beer, liquor/wine, and cigarettes. E-cigarettes are economic substitutes for alcohol among smokers who are currently drinking and using e-cigarettes. Regulating tobacco indoor use will have an impact on e-cigarette consumption

Security and Energy-aware Collaborative Task Offloading in D2D communication

Device-to-device (D2D) communication technique is used to establish direct links among mobile devices (MDs) to reduce communication delay and increase network capacity over the underlying wireless networks. Existing D2D schemes for task offloading focus on system throughput, energy consumption, and delay without considering data security. This paper proposes a Security and Energy-aware Collaborative Task Offloading for D2D communication (Sec2D). Specifically, we first build a novel security model, in terms of the number of CPU cores, CPU frequency, and data size, for measuring the security workload on heterogeneous MDs. Then, we formulate the collaborative task offloading problem that minimizes the time-average delay and energy consumption of MDs while ensuring data security. In order to meet this goal, the Lyapunov optimization framework is applied to implement online decision-making. Two solutions, greedy approach and optimal approach, with different time complexities, are proposed to deal with the generated mixed-integer linear programming (MILP) problem. The theoretical proofs demonstrate that Sec2D follows a [O(1∕V),O(V)] energy-delay tradeoff. Simulation results show that Sec2D can guarantee both data security and system stability in the collaborative D2D communication environment