Mental Illness and the Demand for Alcohol, Cocaine and Cigarettes

The purpose of this paper is to estimate the effect that mental illness has on the demand for addictive goods. Mental illness could affect the level of consumption of addictive goods and could affect the price elasticities of addictive goods. Demand theory suggests that mental illness would affect consumption if mental illness affected marginal utility. In addition, mental illness would affect the price elasticity if mental illness affected the rate at which marginal utility diminishes. The empirical models allow for endogeneity between mental illness and addictive consumption since prior research suggests such a relationship. The results show that individuals with a history of mental illness are 25 percent more likely to consume alcohol, 69 percent more likely to consume cocaine and 94 percent more likely to consume cigarettes. Individuals with a history of mental illness are responsive to price although the price elasticites differ somewhat from whose without mental illness. These results provide an added justification for higher taxes and other supply reduction activities since they show that these policies are effective with this high participation group. The results also suggest that an additional method of reducing the consumption of addictive goods is to subsidize the treatment of mental illness.

Risk Tolerance and Alcohol Demand Among Adults and Older Adults

This study has two primary goals. These are the examination of the effect of risk tolerance on individuals' demand for alcohol and second, the examination of the demand for alcohol by older adults over the age of 55. The data sets employed are multiple waves from the Panel Study of Income Dynamics (PSID) and the Health and Retirement Study (HRS). While risk tolerance can impact the level of alcohol consumption, it may also affect the sensitivity of demand to prices. There are parallels between the economist's and the psychologist's concept of risk tolerance. Research on attitudes towards risk by psychologists is part of a larger theoretical and empirical literature on personality traits. Psychologists have found risk tolerance to be an important determinant of alcohol consumption. The empirical results indicate that risk aversion has a significant negative effect on alcohol consumption, with the prevalence and consumption among risk-tolerant individuals being six to eight percent higher. Furthermore, the tax elasticity is similar across both risk-averse and risk-tolerant individuals. This suggests that tax policies may be effective in deterring alcohol consumption even among those who have a higher propensity for alcohol use. The significance of research on alcohol demand by individuals ages 55 and older is highlighted by the increased potential for alcohol-related adverse consequences among this demographic group. Comparing younger adults (ages 21-54) with older adults, responses to taxes and prices are higher among the older sub-population. The tax elasticity is estimated at -0.05 for younger adults, compared to -0.20 for older adults.

Alcohol Advertising and Alcohol Consumption by Adolescents

The purpose of this paper is to empirically estimate the effects of alcohol advertising on adolescent alcohol consumption. The theory of brand capital is used to explain the effects of advertising on consumption. The industry response function and the evidence from prior studies indicate that the empirical strategy should maximize the variance in the advertising data. The approach in this paper to maximizing the variance in advertising data is to employ cross sectional data. The Monitoring the Future (MTF) and the National Longitudinal Survey of Youth 1997 (NLSY97) data sets, which include only data for adolescents, are employed for the empirical work. These data sets are augmented with alcohol advertising data, originating on the market level, for five media. Use of both the MTF and the NLSY97 data sets improves the empirical analysis since each data set has its own unique advantages. The large size of the MTF makes it possible to estimate regressions with race and gender specific subsamples. The panel nature of the NLSY97 makes it possible to estimate individual fixed effects models. In addition, very similar models can be estimated with both data sets. Since the data sets are independent, the basically consistent findings increase the confidence in all the results. The results indicate that blacks participate in alcohol less than whites and their participation cannot be explained with the included variables as well as it can for whites. A comparison of male and female regressions shows that price and advertising effects are generally larger for females. Models which control for individual heterogeneity result in larger advertising effects implying that the MTF results may understate the effect of alcohol advertising. The results based on the NLSY97 suggest that a compete ban on all alcohol advertising could reduce adolescent monthly alcohol participation by about 24 percent and binge participation by about 42 percent. The past month price-participation elasticity was estimated at about -0.28 and the price-binge participation elasticity was estimated at about -0.51. Both advertising and price policies are shown to have the potential to substantially reduce adolescent alcohol consumption.

The Impact of Direct-to-Consumer Advertising on Pharmaceutical Prices and Demand

Expenditures on prescription drugs are one of the fastest growing components of national health care spending, rising by almost three-fold between 1995 and 2007. Coinciding with this growth in prescription drug expenditures has been a rapid rise in direct-to-consumer advertising (DTCA), made feasible by the Food and Drug Administration’s (FDA) clarification and relaxation of the rules governing broadcast advertising in 1997 and 1999. This study investigates the separate effects of broadcast and non-broadcast DTCA on price and demand, utilizing an extended time series of monthly records for all advertised and non-advertised drugs in four major therapeutic classes spanning 1994-2005, a period which enveloped the shifts in FDA guidelines and the large expansions in DTCA. Controlling for promotion aimed at physicians, results from fixed effects models suggest that broadcast DTCA positively impacts own-sales and price, with an estimated elasticity of 0.10 and 0.04 respectively. Relative to broadcast DTCA, non-broadcast DTCA has a smaller impact on sales (elasticity of 0.05) and price (elasticity of 0.02). Simulations suggest that the expansion in broadcast DTCA may be responsible for about 19 percent of the overall growth in prescription drug expenditures over the sample period, with over two-thirds of this impact being driven by an increase in demand as a result of the DTCA expansion and the remainder due to higher prices.

DATA SOVEREIGNTY AND DATA RESIDENCY COMMUNICATIONS INVOLVING LOW EARTH ORBIT SATELLITES

In a Low Earth Orbit (LEO) satellite system, LEO satellites can collect data and relay the data to ground stations. Today, many countries and regions within the world (e.g., the European Union (EU), provinces or states within a country, or a country itself) have strict data sovereignty policies that do not allow sensitive data to be transmitted outside of national, regional, state, or provincial borders. Thus, if a LEO satellite is to collect ground terminal data from a sensor device (such as operational data of non-urban emergency vehicles), it must do so within bounds of the data residency and sovereignty polices based on the location of the customer. In other words, for the LEO satellite to be compliant, it cannot relay data to just any ground station - it must do to one that meets the requirements of the sovereignty policy. Presented herein is a technique to enforce data sovereignty policies when data is collected by LEO satellites in order to ensure that, when the data is passed back to ground stations, data sovereignty policies are enforced

INTENT-BASED NETWORKING FROM THE IOT EDGE TO THE APPLICATION SERVER

The dynamic management of traffic within an operational technology (OT) network raises a number of challenges. To address those types of challenges, techniques are presented herein that enable end-to-end intent-based networking to control access between the OT domain and on-premise or cloud-based data center (DC) domains. Aspects of the presented techniques employ deep packet inspection (DPI) of industrial protocols within the OT domain (e.g. by sensors) and map Internet of Things (IoT) devices and traffic flows to abstract tags (through, e.g. a robust security facility), export such tags to a common policy server that bridges both domains, assign the IoT devices to corresponding security profiles (e.g., based on their device characteristics as expressed by tag metadata), and map the security profiles to specific fabric overlay microsegments (e.g., endpoint groups (EPGs)) within a DC or cloud domain

Time Matters: Exploring the Effects of Urgency and Reaction Speed in Automated Traders

We consider issues of time in automated trading strategies in simulated financial markets containing a single exchange with public limit order book and continuous double auction matching. In particular, we explore two effects: (i) reaction speed - the time taken for trading strategies to calculate a response to market events; and (ii) trading urgency - the sensitivity of trading strategies to approaching deadlines. Much of the literature on trading agents focuses on optimising pricing strategies only and ignores the effects of time, while real-world markets continue to experience a race to zero latency, as automated trading systems compete to quickly access information and act in the market ahead of others. We demonstrate that modelling reaction speed can significantly alter previously published results, with simple strategies such as SHVR outperforming more complex adaptive algorithms such as AA. We also show that adding a pace parameter to ZIP traders (ZIP-Pace, or ZIPP) can create a sense of urgency that significantly improves profitability.Comment: 22 pages. To be published in A. P. Rocha et al. (Eds.), ICAART 2020, LNAI 12613, 2021. arXiv admin note: substantial text overlap with arXiv:1912.0277

A 275–425-GHz Tunerless Waveguide Receiver Based on AlN-Barrier SIS Technology

We report on a 275–425-GHz tunerless waveguide receiver with a 3.5–8-GHz IF. As the mixing element, we employ a high-current-density Nb–AlN–Nb superconducting–insulating– superconducting (SIS) tunnel junction. Thanks to the combined use of AlN-barrier SIS technology and a broad bandwidth waveguide to thin-film microstrip transition, we are able to achieve an unprecedented 43% instantaneous bandwidth, limited by the receiver's corrugated feedhorn. The measured double-sideband (DSB) receiver noise temperature, uncorrected for optics loss, ranges from 55 K at 275 GHz, 48 K at 345 GHz, to 72 K at 425 GHz. In this frequency range, the mixer has a DSB conversion loss of 2.3 1 dB. The intrinsic mixer noise is found to vary between 17–19 K, of which 9 K is attributed to shot noise associated with leakage current below the gap. To improve reliability, the IF circuit and bias injection are entirely planar by design. The instrument was successfully installed at the Caltech Submillimeter Observatory (CSO), Mauna Kea, HI, in October 2006

Encoding the infrared excess (IRX) in the NUVrK color diagram for star-forming galaxies

We present an empirical method of assessing the star formation rate (SFR) of star-forming galaxies based on their locations in the rest-frame color-color diagram (NUV-r) vs (r-K). By using the Spitzer 24 micron sample in the COSMOS field (~16400 galaxies with 0.2 < z < 1.3) and a local GALEX-SDSS-SWIRE sample (~700 galaxies with z = < L_IR / L_UV > can be described by a single vector, NRK, that combines the two colors. The calibration between and NRK allows us to recover the IR luminosity, L_IR, with an accuracy of ~0.21 dex for the COSMOS sample and ~0.27 dex for the local one. The SFRs derived with this method agree with the ones based on the observed (UV+IR) luminosities and on the spectral energy distribution fitting for the vast majority (~85 %) of the star-forming population. Thanks to a library of model galaxy SEDs with realistic prescriptions for the star formation history, we show that we need to include a two-component dust model (i.e., birth clouds and diffuse ISM) and a full distribution of galaxy inclinations in order to reproduce the behavior of the stripes in the NUVrK diagram. In conclusion, the NRK method, based only on rest-frame UV and optical colors available in most of the extragalactic fields, offers a simple alternative of assessing the SFR of star-forming galaxies in the absence of far-IR or spectral diagnostic observations.Comment: 21 pages, 22 figures, in publication in Astronomy & Astrophysic