scholarly journals From Mad Men to Maths Men: Concentration and Buyer Power in Online Advertising

2021 ◽  
Vol 111 (10) ◽  
pp. 3299-3327
Author(s):  
Francesco Decarolis ◽  
Gabriele Rovigatti
Keyword(s):  
Instrumental Variable ◽  
Online Advertising ◽  
Machine Learning Algorithms ◽  
Keyword Auctions ◽  
Online Platforms ◽  
Mad Men ◽  
Buyer Power ◽  
Using Data ◽  
Average Rise ◽  
The Impact

This paper analyzes the impact of intermediary concentration on the allocation of revenue in online platforms. We study sponsored search documenting how advertisers increasingly bid through a handful of specialized intermediaries. This enhances automated bidding and data pooling, but lessens competition whenever the intermediary represents competing advertisers. Using data on nearly 40 million Google keyword auctions, we first apply machine learning algorithms to cluster keywords into thematic groups serving as relevant markets. Using an instrumental variable strategy, we estimate a decline in the platform’s revenue of approximately 11 percent due to the average rise in concentration associated with intermediary merger and acquisition activity. (JEL C45, D44, G34, L13, L81, M37)

International Remittances and Private Healthcare in Kerala, India

2020 ◽  
Vol 17 (3) ◽  
pp. 445-460
Author(s):  
Mohd Imran Khan ◽  
Valatheeswaran C.
Keyword(s):  
Instrumental Variable ◽  
Capital Investment ◽  
Healthcare Expenditure ◽  
Healthcare Services ◽  
Private Healthcare ◽  
International Remittances ◽  
Variable Approach ◽  
Using Data ◽  
The Impact ◽  
Instrumental Variable Approach

The inflow of international remittances to Kerala has been increasing over the last three decades. It has increased the income of recipient households and enabled them to spend more on human capital investment. Using data from the Kerala Migration Survey-2010, this study analyses the impact of remittance receipts on the households’ healthcare expenditure and access to private healthcare in Kerala. This study employs an instrumental variable approach to account for the endogeneity of remittances receipts. The empirical results show that remittance income has a positive and significant impact on households’ healthcare expenditure and access to private healthcare services. After disaggregating the sample into different heterogeneous groups, this study found that remittances have a greater effect on lower-income households and Other Backward Class (OBC) households but not Scheduled Caste (SC) and Scheduled Tribe (ST) households, which remain excluded from reaping the benefit of international migration and remittances.

scholarly journals Do Sports Crowd Out Books? The Impact of Intercollegiate Athletic Participation on Grades

2017 ◽  
Vol 20 (1) ◽  
pp. 115-153 ◽  
Author(s):  
Michael A. Insler ◽  
Jimmy Karam
Keyword(s):  
Instrumental Variable ◽  
Causal Effect ◽  
Peer Groups ◽  
Sports Participation ◽  
Athletic Participation ◽  
Naval Academy ◽  
Intercollegiate Athletic ◽  
Using Data ◽  
Promotion Rates ◽  
The Impact

We investigate the influence of intercollegiate athletic participation on grades using data from the U.S. Naval Academy. Athletic participation is an endogenous decision with respect to educational outcomes. To identify a causal effect, we develop an instrument via the Academy’s random assignment of students into peer groups. Instrumental variable (IVs) estimates suggest that sports participation modestly reduces recruited athletes’ grades. This finding has implications beyond college, as we also show that grades—not athletic participation—are most strongly associated with postcollegiate outcomes such as military tenure and promotion rates.

scholarly journals Do Study Abroad Programs Enhance the Employability of Graduates?

2015 ◽  
Vol 10 (2) ◽  
pp. 223-243 ◽  
Author(s):  
Giorgio Di Pietro
Keyword(s):  
Study Abroad ◽  
Instrumental Variable ◽  
Fixed Effects ◽  
International Student ◽  
Study Abroad Programs ◽  
Large Sample ◽  
Instrumental Variable Estimation ◽  
Studying Abroad ◽  
Using Data ◽  
The Impact

Using data on a large sample of recent Italian graduates, this paper investigates the extent to which participation in study abroad programs during university studies impacts subsequent employment likelihood. To address the problem of endogeneity related to participation in study abroad programs, I use a combination of fixed effects and instrumental variable estimation where the instrumental variable is exposure to international student exchange schemes. My estimates show that studying abroad has a relatively large and statistically meaningful effect on the probability of being in employment three years after graduation. This effect is mainly driven by the impact that study abroad programs have on the employment prospects of graduates from disadvantaged (but not very disadvantaged) backgrounds, though positive but imprecise effects are also found for graduates from advantaged backgrounds.

scholarly journals The Impact of Social Isolation on Subjective Health: An Instrumental Variable Approach

2018 ◽  
Author(s):  
Emiliano Sironi ◽  
Amelie Nadine Wolff
Keyword(s):  
Social Isolation ◽  
Instrumental Variable ◽  
Subjective Health ◽  
European Social Survey ◽  
Perceived Health Status ◽  
Variable Model ◽  
Significant Deterioration ◽  
Variable Approach ◽  
Using Data ◽  
The Impact

We investigate the relationship between social isolation and subjective health, considering that this relationship is potentially affected by endogeneity due to the presence of self-reported measures. Thus, if an increase in social isolation may impact the perception on health, alternative paths of causality may also be hypothesized. Using data from round 7 of the European Social Survey, we estimate an instrumental variable model in which isolation is explained as being a member of an ethnic minority and having experienced some serious family conflicts in the past. Our results confirm that changes in social isolation influence subjective general health. In particular, greater isolation produces a strong and significant deterioration of the perceived health status. With respect to the literature on social isolation and health, we try to advance it by supporting a path of causality running from social isolation to subjective health.

scholarly journals Smart Recommendation System for Off-the Shelf Medicines

2018 ◽  
Vol 7 (2.24) ◽  
pp. 417
Author(s):  
Ratna Sathappan ◽  
Tholu Sai Indira ◽  
A Meenapriyadarsini
Keyword(s):  
Machine Learning ◽  
Recommendation System ◽  
Opinion Mining ◽  
Recommendation Systems ◽  
Product Category ◽  
Machine Learning Algorithms ◽  
Patient Feedback ◽  
The People ◽  
Using Data ◽  
The Impact

Internet usage has been at an all-time high from 2000’s vintage years. The people who have access to the internet use it for numerous reasons such as social networking, marketing, promoting, enhancing businesses, consultancy, research, gaming and the list goes on. In the recent years, Review websites have flourished, where people share their opinion about a product, with an increase in response rate and reliability. Recommendations are made by mining data from review websites. Traditional Recommendation systems are limited as they only consider certain metrics, such as product purchase details, product category. Recommendation systems are yet to gain popularity in the medical field. These days most patients are unable to figure out the medication that works in healing them in the best way possible, hence they turn to review websites in order to obtain a second opinion on the prescribed medication. In this work, we have developed a smart recommendation system for off-the Shelf Medical Drugs using machine learning and data analytics based on patient feedback. The patient feedback is unstructured data which is processed using data analytic tools. After which machine learning is used to recommend the best fit and compare the drugs. In this work, we predict the impact of a drug/ medicine on the patient to whom the medication was prescribed, using data mining techniques. Firstly, we detect the user’s polarity (positive/ negative/neutral) based on the patient feedback for a certain drug using sentiment analysis and opinion mining following which we use machine learning algorithms to track sentiment variation and to make a recommendation based on user polarity

scholarly journals Does Social Insurance Block the Inter-Generational Transmission of Poverty? Evidence from the 2018 China Family Panel Survey

2022 ◽  
Vol 14 (2) ◽  
pp. 750
Author(s):  
Xianhua Dai ◽  
Nian Gu
Keyword(s):  
Instrumental Variable ◽  
Social Insurance ◽  
Geographical Location ◽  
Probit Model ◽  
Medical Insurance ◽  
Panel Survey ◽  
Pension Insurance ◽  
Generational Transmission ◽  
Using Data ◽  
The Impact

In this research, we explored whether participation in pension insurance and medical insurance for children and fathers blocks the inter-generational transmission of poverty. Using data from the China Family Panel Survey of 2018, this paper took the average level of insurance participation of a sample group as an instrumental variable, applied the IV-probit model, and found that the participation of children in pension insurance and the participation of fathers in medical insurance significantly reduce the probability of the inter-generational transmission of poverty, but that the participation of children in medical insurance and the participation of fathers in pension insurance increase it. These results were robust. Furthermore, there was heterogeneity in household registration, geographical location, and marriage with regard to the impact of social insurance participation on the inter-generational transmission of poverty. These results could help the formulation of anti-poverty policies to address the inter-generational transmission of poverty.

Accent Policy and Accent Modification Enterprises as Potential Indicators of Intercultural Power Relations: A Call for an Updated Research Agenda

2013 ◽  
Vol 3 (1) ◽  
pp. 22-33 ◽  
Author(s):  
Brynne D. Ovalle ◽  
Rahul Chakraborty
Keyword(s):  
International Relations ◽  
Identity Construction ◽  
Social Theory ◽  
Power Relations ◽  
Linguistic Diversity ◽  
Cultural Organization ◽  
Using Data ◽  
The Individual ◽  
The Impact ◽  
The Relationship

This article has two purposes: (a) to examine the relationship between intercultural power relations and the widespread practice of accent discrimination and (b) to underscore the ramifications of accent discrimination both for the individual and for global society as a whole. First, authors review social theory regarding language and group identity construction, and then go on to integrate more current studies linking accent bias to sociocultural variables. Authors discuss three examples of intercultural accent discrimination in order to illustrate how this link manifests itself in the broader context of international relations (i.e., how accent discrimination is generated in situations of unequal power) and, using a review of current research, assess the consequences of accent discrimination for the individual. Finally, the article highlights the impact that linguistic discrimination is having on linguistic diversity globally, partially using data from the United Nations Educational, Scientific and Cultural Organization (UNESCO) and partially by offering a potential context for interpreting the emergence of practices that seek to reduce or modify speaker accents.

Interculturalism and the Acceptance of Minority Groups

2020 ◽  
Vol 51 (2) ◽  
pp. 135-140 ◽  
Author(s):  
Maykel Verkuyten ◽  
Kumar Yogeeswaran
Keyword(s):  
Minority Groups ◽  
Psychological Research ◽  
Survey Experiment ◽  
Social Psychological ◽  
Negative Attitudes ◽  
Positive Attitudes ◽  
Social Psychological Research ◽  
Using Data ◽  
The Impact ◽  
Situational Effect

Abstract. Multiculturalism has been criticized and rejected by an increasing number of politicians, and social psychological research has shown that it can lead to outgroup stereotyping, essentialist thinking, and negative attitudes. Interculturalism has been proposed as an alternative diversity ideology, but there is almost no systematic empirical evidence about the impact of interculturalism on the acceptance of migrants and minority groups. Using data from a survey experiment conducted in the Netherlands, we examined the situational effect of promoting interculturalism on acceptance. The results show that for liberals, but not for conservatives, interculturalism leads to more positive attitudes toward immigrant-origin groups and increased willingness to engage in contact, relative to multiculturalism.

Forecasting US movies box office performances in Turkey using machine learning algorithms

2020 ◽  
Vol 39 (5) ◽  
pp. 6579-6590
Author(s):  
Sandy Çağlıyor ◽  
Başar Öztayşi ◽  
Selime Sezgin
Keyword(s):  
Machine Learning ◽  
Global Economy ◽  
Learning Algorithms ◽  
Forecast Model ◽  
Machine Learning Algorithms ◽  
Gradient Boosting ◽  
High Stakes ◽  
Box Office ◽  
Industry Forecast ◽  
The Impact

The motion picture industry is one of the largest industries worldwide and has significant importance in the global economy. Considering the high stakes and high risks in the industry, forecast models and decision support systems are gaining importance. Several attempts have been made to estimate the theatrical performance of a movie before or at the early stages of its release. Nevertheless, these models are mostly used for predicting domestic performances and the industry still struggles to predict box office performances in overseas markets. In this study, the aim is to design a forecast model using different machine learning algorithms to estimate the theatrical success of US movies in Turkey. From various sources, a dataset of 1559 movies is constructed. Firstly, independent variables are grouped as pre-release, distributor type, and international distribution based on their characteristic. The number of attendances is discretized into three classes. Four popular machine learning algorithms, artificial neural networks, decision tree regression and gradient boosting tree and random forest are employed, and the impact of each group is observed by compared by the performance models. Then the number of target classes is increased into five and eight and results are compared with the previously developed models in the literature.

The impact of algorithmic decision-making processes on young people’s well-being (Preprint)

2019 ◽  
Author(s):  
Elvira Perez Vallejos ◽  
Liz Dowthwaite ◽  
Helen Creswich ◽  
Virginia Portillo ◽  
Ansgar Koene ◽  
...  
Keyword(s):  
Young People ◽  
Significant Proportion ◽  
Well Being ◽  
Early Years ◽  
Negative Experiences ◽  
Children And Young People ◽  
Online Platforms ◽  
Internet Users ◽  
Decision Making Processes ◽  
The Impact

BACKGROUND Algorithms rule the online environments and are essential for performing data processing, filtering, personalisation and other tasks. Research has shown that children and young people make up a significant proportion of Internet users, however little attention has been given to their experiences of algorithmically-mediated online platforms, or the impact of them on their mental health and well-being. The algorithms that govern online platforms are often obfuscated by a lack of transparency in their online Terms and Conditions and user agreements. This lack of transparency speaks to the need for protecting the most vulnerable users from potential online harms. OBJECTIVE To capture young people's experiences when being online and perceived impact on their well-being. METHODS In this paper, we draw on qualitative and quantitative data from a total of 260 children and young people who took part in a ‘Youth Jury’ to bring their opinions to the forefront, elicit discussion of their experiences of using online platforms, and perceived psychosocial impact on users. RESULTS The results of the study revealed the young people’s positive as well as negative experiences of using online platforms. Benefits such as being convenient and providing entertainment and personalised search results were identified. However, the data also reveals participants’ concerns for their privacy, safety and trust when online, which can have a significant impact on their well-being. CONCLUSIONS We conclude by making recommendations that online platforms acknowledge and enact on their responsibility to protect the privacy of their young users, recognising the significant developmental milestones that this group experience during these early years, and the impact that technology may have on them. We argue that governments need to incorporate policies that require technologists and others to embed the safeguarding of users’ well-being within the core of the design of Internet products and services to improve the user experiences and psychological well-being of all, but especially those of children and young people. CLINICALTRIAL N/A

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