Status signalling in the market for consumer goods

2021 ◽  
Author(s):  
HAIMEI YU ◽  
Edward Vul
Keyword(s):  
Social Status ◽  
Consumer Goods ◽  
Instrumental Variable ◽  
Causal Effect ◽  
Department Stores ◽  
Purchasing Decisions ◽  
Social Signals ◽  
Status Signalling ◽  
Goods Market ◽  
Using Data

People are concerned with signalling their social status to others, and conspicuous consumption may be a prevalent means of signalling, such that purchasing decisions are motivated not only by the direct value of a product, but by the indirect value gained from what the product might communicate to others. Here we measure which products people might use as signals and ask how the signalling potential of products relates to the distribution of product offerings in the consumer goods market. In particular, we asked how the signalling potential of products influences the number, price, and dispersion of prices within and across department stores. Using data scraped from 11 department stores, we found that products with greater signalling potential are available in greater quantity, more expensive within a given store, and that more expensive stores stock more products with higher signalling potential, leading to greater global variance in prices for goods with greater signalling potential. Further, we use product visibility as an instrumental variable to estimate the causal effect of signalling potential on product offerings. Altogether, these results suggest that consumers demand to use visible goods as social signals, and being sensitive to this demand, suppliers of consumer goods position their product offerings to supply ample material for signalling via consumption.

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 Selection bias in instrumental variable analyses

2017 ◽  
Author(s):  
Rachael A. Hughes ◽  
Neil M. Davies ◽  
George Davey Smith ◽  
Kate Tilling
Keyword(s):  
Confidence Interval ◽  
Selection Bias ◽  
Instrumental Variable ◽  
Causal Effect ◽  
Major Effect ◽  
Directed Acyclic Graphs ◽  
Factors Affecting ◽  
Exposure Effect ◽  
Using Data ◽  
The Uk

AbstractParticipants in epidemiological and genetic studies are rarely true random samples of the populations they are intended to represent, and both known and unknown factors can influence participation in a study (known as selection into a study). The circumstances in which selection causes bias in an instrumental variable (IV) analysis are not widely understood by practitioners of IV analyses. We use directed acyclic graphs (DAGs) to depict assumptions about the selection mechanism (factors affecting selection) and show how DAGs can be used to determine when a two-stage least squares (2SLS) IV analysis is biased by different selection mechanisms. Via simulations, we show that selection can result in a biased IV estimate with substantial confidence interval undercoverage, and the level of bias can differ between instrument strengths, a linear and nonlinear exposure-instrument association, and a causal and noncausal exposure effect. We present an application from the UK Biobank study, which is known to be a selected sample of the general population. Of interest was the causal effect of education on the decision to smoke. The 2SLS exposure estimates were very different between the IV analysis ignoring selection and the IV analysis which adjusted for selection (e.g., 1.8 [95% confidence interval −1.5, 5.0] and −4.5 [−6.6, −2.4], respectively). We conclude that selection bias can have a major effect on an IV analysis and that statistical methods for estimating causal effects using data from nonrandom samples are needed.

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 Causal inference in continuous time: an example on prostate cancer therapy

Biostatistics ◽  
2018 ◽  
Vol 21 (1) ◽  
pp. 172-185 ◽  
Author(s):  
Pål Christie Ryalen ◽  
Mats Julius Stensrud ◽  
Sophie Fosså ◽  
Kjetil Røysland
Keyword(s):  
Prostate Cancer ◽  
Continuous Time ◽  
Causal Effect ◽  
Structural Models ◽  
Marginal Structural Models ◽  
Cancer Treatments ◽  
Discrete Parameter ◽  
Inverse Probability Weights ◽  
Using Data ◽  
Prostate Cancer Treatments

Abstract In marginal structural models (MSMs), time is traditionally treated as a discrete parameter. In survival analysis on the other hand, we study processes that develop in continuous time. Therefore, Røysland (2011. A martingale approach to continuous-time marginal structural models. Bernoulli 17, 895–915) developed the continuous-time MSMs, along with continuous-time weights. The continuous-time weights are conceptually similar to the inverse probability weights that are used in discrete time MSMs. Here, we demonstrate that continuous-time MSMs may be used in practice. First, we briefly describe the causal model assumptions using counting process notation, and we suggest how causal effect estimates can be derived by calculating continuous-time weights. Then, we describe how additive hazard models can be used to find such effect estimates. Finally, we apply this strategy to compare medium to long-term differences between the two prostate cancer treatments radical prostatectomy and radiation therapy, using data from the Norwegian Cancer Registry. In contrast to the results of a naive analysis, we find that the marginal cumulative incidence of treatment failure is similar between the strategies, accounting for the competing risk of other death.

scholarly journals Nonparametric Instrumental Variable Methods for Dynamic Treatment Evaluation

2020 ◽  
Vol 102 (2) ◽  
pp. 355-367
Author(s):  
Gerard J. van den Berg ◽  
Petyo Bonev ◽  
Enno Mammen
Keyword(s):  
Instrumental Variable ◽  
Causal Effect ◽  
Asymptotic Properties ◽  
Right Censoring ◽  
Unemployment Duration ◽  
Dynamic Selection ◽  
Average Causal Effect ◽  
Variable Approach ◽  
Dynamic Treatment ◽  
Job Finding

We develop an instrumental variable approach for identification of dynamic treatment effects on survival outcomes in the presence of dynamic selection, noncompliance, and right-censoring. The approach is nonparametric and does not require independence of observed and unobserved characteristics or separability assumptions. We propose estimation procedures and derive asymptotic properties. We apply our approach to evaluate a policy reform in which the pathway of unemployment benefits as a function of the unemployment duration is modified. Those who were unemployed at the reform date could choose between the old and the new regime. We find that the new regime has a positive average causal effect on the job finding rate.

scholarly journals Psychological treatments for early psychosis can be beneficial or harmful, depending on the therapeutic alliance: an instrumental variable analysis

2015 ◽  
Vol 45 (11) ◽  
pp. 2365-2373 ◽  
Author(s):  
L. P. Goldsmith ◽  
S. W. Lewis ◽  
G. Dunn ◽  
R. P. Bentall
Keyword(s):  
Therapeutic Alliance ◽  
Effect Size ◽  
Instrumental Variable ◽  
Structural Equation ◽  
Psychological Treatment ◽  
Causal Effect ◽  
Controlled Trial ◽  
Behavioural Therapy ◽  
Psychological Treatments ◽  
Symptomatic Outcome

BackgroundThe quality of the therapeutic alliance (TA) has been invoked to explain the equal effectiveness of different psychotherapies, but prior research is correlational, and does not address the possibility that individuals who form good alliances may have good outcomes without therapy.MethodWe evaluated the causal effect of TA using instrumental variable (structural equation) modelling on data from a three-arm, randomized controlled trial of 308 people in an acute first or second episode of a non-affective psychosis. The trial compared cognitive behavioural therapy (CBT) over 6 weeks plus routine care (RC) v. supportive counselling (SC) plus RC v. RC alone. We examined the effect of TA, as measured by the client-rated CALPAS, on the primary trial 18-month outcome of symptom severity (PANSS), which was assessed blind to treatment allocation.ResultsBoth adjunctive CBT and SC improved 18-month outcomes, compared to RC. We showed that, for both psychological treatments, improving TA improves symptomatic outcome. With a good TA, attending more sessions causes a significantly better outcome on PANSS total score [effect size −2.91, 95% confidence interval (CI) −0.90 to −4.91]. With a poor TA, attending more sessions is detrimental (effect size +7.74, 95% CI +1.03 to +14.45).ConclusionsThis is the first ever demonstration that TA has a causal effect on symptomatic outcome of a psychological treatment, and that poor TA is actively detrimental. These effects may extend to other therapeutic modalities and disorders.

The effect of retirement on social relationships

2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Simona Lorena Comi ◽  
Elena Cottini ◽  
Claudio Lucifora
Keyword(s):  
Social Network ◽  
Social Relationships ◽  
Causal Effect ◽  
Strong Ties ◽  
The Social ◽  
Using Data

Abstract We analyze the causal effect of retirement on individual social relationships using data from the Survey of Health, Ageing and Retirement in Europe. We find that retirement changes the composition of the individual’s social network, inducing a substitution between weak (friends or colleagues) and strong ties (family), along with an increase in the intensity of the surviving ties, and there is no effect on the network’s size. These changes in the social network’s composition are associated with a higher satisfaction and stronger relationships. Interestingly, females reduce the share of friends while males that of colleagues.

scholarly journals Division of Housework, Communication, and Couples’ Relationship Satisfaction

2020 ◽  
Vol 6 ◽  
pp. 237802312092480
Author(s):  
Daniel L. Carlson ◽  
Amanda J. Miller ◽  
Stephanie Rudd
Keyword(s):  
Relationship Satisfaction ◽  
Instrumental Variable ◽  
Important Predictor ◽  
Male Partners ◽  
Communication Quality ◽  
Female Partners ◽  
Division Of Housework ◽  
Using Data

The gendered division of housework is an important predictor of relationship satisfaction, but the mechanisms linking these variables remain poorly understood. Using data on N = 487 couples from the 2006 Marital and Relationship Survey, the authors examine the association of heterosexual partners’ communication quality with the division of housework and the role of partners’ communication quality in the association between the division of housework and relationship satisfaction. Results from instrumental variable models and Actor-Partner Interdependence Models indicate that the quality of women’s communication with their male partners predicts how couples divide housework. The quality of men’s communication with their female partners, however, appears to be an outcome of domestic arrangements. Men’s communication quality mediates the association between the division of housework and women’ relationship satisfaction, while women’s communication quality confounds the association for men.

Shrouded Prices and Firm Reputation: Evidence from the U.S. Hotel Industry

2020 ◽  
Author(s):  
Bennett Chiles
Keyword(s):  
Rating Scale ◽  
Causal Effect ◽  
Hotel Industry ◽  
Firm Characteristics ◽  
Firm Reputation ◽  
Using Data ◽  
Online Travel ◽  
The Impact ◽  
Shed Light ◽  
The U.S

Firms in many industries engage in price obfuscation—tactics that intentionally make prices more difficult for consumers to discern. Although existing research has focused on the short-term financial gains that motivate firms to obfuscate, reputational concerns may at least partially counteract these incentives if consumers punish deceptive firms via loss of loyalty in future transactions and/or publicly observable negative feedback. This paper addresses the latter possibility, exploring the impact of mandatory shrouded surcharges on firm reputation in the U.S. hotel industry. Using data collected from two major online travel sites, I exploit differences in surcharge disclosure across booking channels to identify the causal effect of hidden “resort fees” on traveler ratings. I find that hidden fees decrease ratings by roughly 0.15 points (on a rating scale ranging from 1 to 5). The magnitude of this effect varies based on firm characteristics, and this variation is consistent with observed heterogeneity in resort fee adoption patterns: when the expected punishment is more severe, firms are substantially less likely to adopt shrouded surcharges. Results shed light on the extent to which reputational mechanisms may act as a check against price obfuscation and other similar practices intended to exploit boundedly rational consumers. This paper was accepted by Eric Anderson, marketing.

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