Research Seminars

We investigate whether audit clients’ climate-related risks disclosure influence audit planning and fees. Using the Task Force on Climate-related Financial Disclosures (TCFD) framework in the UK, we distinguish between clients who mandatorily comply with TCFD (mandatory clients) and those who do not. We find that mandatory TCFD adoption is associated with higher audit fees, but fewer key audit matters disclosed by auditors, suggesting that enhanced climate-related disclosures reduce perceived audit risk through greater transparency, yet do not reduce audit pricing. Cross-sectional analyses reveal important heterogeneity in auditors’ responses to mandatory TCFD adoption. The increase in audit fees is concentrated among clients of small audit firms, while clients of large audit firms experience fee reductions. In addition, auditors apply higher materiality levels to clients with high climate impact, consistent with reduced audit effort. Further tests indicate that mandatory TCFD adoption does not translate into improvement in actual environmental performance. Given the growing interest in climate-related risks in practice and research, our study sheds light on how auditors respond to changes in climate-related disclosure requirements.

Does the legal protection of free speech change how managers use stock prices to guide corporate investment? We study this question using the staggered enactment of anti-SLAPP laws across U.S. states from 1992 to 2022, a setting that lowers the litigation cost of speaking out and empowers journalists, NGOs, employees, and short sellers to bring firm-specific information into public view. In a stacked difference-in-differences design, we find that stronger free-speech protections reduce the sensitivity of corporate investment to Tobin's Q by roughly 34%. We interpret this through revelatory price efficiency, the component of price informativeness that managers actually learn from: anti-SLAPP laws expand public information about matters managers already know, crowding out private information acquisition about the growth opportunities they most need prices to reveal. Consistent with this composition-shift mechanism, the effect is stronger for firms with higher pre-treatment informed trading and in states with broader statutory protections, and it survives controls for forecasting price efficiency. Channel tests show that anti-SLAPP enactment raises fundamental investor information acquisition, while analyst forecasts pin down the crowded-out information as growth-related: long-horizon forecast accuracy deteriorates even as short-horizon accuracy is unchanged. Cross-sectionally, the decline is most pronounced for firms with high discretionary accruals, low disclosure frequency, and high CEO ability, characteristics tied to greater pre-existing reliance on managerial learning from prices. Our findings reveal an unintended cost of transparency reform: laws that strengthen public discourse and corporate accountability can simultaneously weaken the informational feedback from stock prices to real investment decisions.

This talk explores how implementation science and behavioral nudges can drive the successful design, adoption, and impact of digital health interventions for chronic disease management. Using the pediatric obesity pandemic as a focal point, we examine a novel eHealth solution launched within a major US safety-net hospital system for families with children ages 6–12 diagnosed with overweight or obesity. Key theoretical frameworks and evidence-based practices will be introduced alongside practical methodological considerations. The case study invites the audience to critically engage with real-world challenges—highlighting how behavioral insights, technology, and context-sensitive methods intersect to shape research outcomes, patient care experiences, and broader societal wellbeing. Participants will gain actionable strategies for integrating behavioral economics and scientific rigor into digital health, with lessons applicable to business, marketing, and health innovation.

When financial markets become turbulent, how do investors price the fear of uncertainty itself? Does that fear spread across different corners of the global economy? This research investigates the Variance Risk Premium (VRP), defined as the gap between what investors expect volatility to be and what it actually turns out to be, across five distinct asset classes: equities, fixed income, foreign exchange, cryptocurrencies, and commodities. While VRP has been studied extensively in stock markets, its behaviour in bond markets, currency markets, commodity markets, and the rapidly growing cryptocurrency space remains poorly understood — particularly in a unified, comparative framework.
Using intraday and high-frequency data spanning 2018–2025 — a period capturing COVID-19, the 2022 rate hiking cycle, and multiple crypto boom-bust episodes — the research employs advanced econometric models including GARCH, HAR, VAR, VECM, and Dynamic Conditional Correlation to examine how VRP behaves, what drives it, and whether volatility risk in one market spills over into others.

Motherhood is associated with persistent penalties in both labour market outcomes and health. However, the role of family policies in mitigating these effects, particularly with respect to maternal mental health, remains unclear. This paper examines the impact of extending paternity leave on maternal mental health. Using administrative health records covering all publicly funded births in Catalonia (Spain) between 2006 and 2024, we implement a local difference-in-differences design around the April 1st, 2019 reform, which introduced partially mandatory paternity leave for fathers. The analysis focuses on first time mothers giving birth within a three-month window around the reform cutoff and compares them to a control cohort from 2016. Maternal mental health is measured using diagnoses and prescription records for stress-related, mood-related, and broader mental health conditions drawn from primary care and pharmacy data. We find an increase in stress-related diagnoses and in the use of antidepressants and anxiolytics from the second year after childbirth among mothers exposed to the reform. These effects are concentrated among older mothers (above the median age of 31) and among those who do not have a second child within four years after birth. We find suggestive evidence that these patterns may be related to increased healthcare use and to stress-related mechanisms, including delayed fertility, changes in labour market attachment, and relationship instability. Ongoing work will extend the analysis to additional mental health outcomes and to subsequent paternity leave reforms

Germany was the first country worldwide to introduce a structured reimbursement pathway for digital therapeutics (DiGA), effectively allowing physicians to prescribe smartphone apps covered by statutory health insurance. In this seminar, Simon Reif presents recent research evaluating whether this pioneering regulation successfully incentivized innovation in the digital health market.  Using high-frequency data from the Apple App Store and synthetic control methods, the study analyzes the market entry of health apps following the policy's introduction. The findings reveal a significant increase in the number of German-language digital therapeutics; however, this quantity did not translate into a broader diversity of medical conditions treated. Furthermore, the surge was largely driven by apps that monetize patient data for advertising rather than high-quality applications backed by scientific evidence. The presentation will discuss the implications of these results for designing policy that balances market incentives with patient privacy and care quality.

Teaser: Simon will be holding a separate, short workshop on the reproducible research tools used at his institute. Join us to learn how to implement these transparent workflows in your own analysis. 

This research explores how mobility big data can be used to understand urban travel behavior and evaluate policy implications. The data sources include public transport smart cards, public bike systems, and mobile phone data. In particular, the transport card–based analysis demonstrates the benefits of Seoul’s integrated fare system with free transfers. The presentation will also briefly introduce data from autonomous delivery robots deployed in Seoul as a potential emerging urban data source.

The death of a child is a devastating and life-altering event for the entire family, extending beyond the initial grief and shaping the short and long-term life trajectories of the surviving siblings and parents. Although a growing literature documents its negative impact on parental outcomes, very little is known about its causal impact on the human capital accumulation of surviving siblings. This paper examines the effect of losing a sibling during childhood on educational outcomes, using detailed register data from the entire population of Finland. I exploit the timing of an unexpected sibling loss relative to the time of 9th-grade GPA measurement. I find that losing a sibling 2 years before the 9th grade has a negative impact of 19% of a standard deviation on the 9th-grade GPA. The effect is more pronounced and prevalent across different ages at the time of sibling loss for children with a lower socioeconomic background. Further, I find a 12-14 percentage points decrease in the probability of general track choice in the upper-secondary school following a sibling loss. Exploring potential mechanisms, I find notable negative mental health effects on both surviving children and their parents, along with adverse effects on the labor market outcomes for mothers. These findings highlight the large social and economic consequences of such losses, emphasizing the need for targeted policies to support bereaved family members.

We study how secondary markets for durable goods interact with consumers’ social-responsibility motives to mitigate environmentally harmful new production. On the positive side, secondary markets may allow responsible consumers to acquire used goods that would otherwise be discarded, reducing premature waste. On the negative side, secondary markets introduce two major harmful forces. First, the possibility of buying used goods and thereby causing less harm can raise the demand of responsible consumers, often increasing the production necessary to serve the market. Second, said demand can increase the price of used goods, encouraging purchases of new goods. These forces imply that if used goods have positive private consumption value, then secondary markets always erode the benefits of social responsibility. If, instead, used goods may have negative private value, then secondary markets can enhance or erode the benefits of social responsibility.

We study the effect of working from home (WFH) on health-related absenteeism. We draw on a monthly panel (2018–2023) of nearly 1.9 million workers insured under a major German statutory health insurance fund. Our identification strategy leverages the differential exposure to the unexpected shift to WFH in 2020, resulting in about one-quarter of German employees regularly working remotely today. Specifically, our difference-in-differences design compares sick leave take-up across workers with different WFH potential, i.e., the teleworkability of their occupation in February 2020. Our results imply a nontrivial lasting response to WFH. Compared to the pre-treatment mean, the monthly likelihood of sick leave take-up declined by 3.3% by 2023 due to a 10-percentage-point increase in WFH potential (comparable to a shift from performing and entertainment professions to media documentation and information services). These effects are driven by reductions in respiratory infections and musculoskeletal disorders, such as back pain. The response reflects not only behavioral changes in sick leave take-up, but also genuine health improvements.

This project examines how an exogenous decline in immigration flows induces sorting across the distribution of health conditions in the local labor market adjustment process and documents significant changes in the community health indicators. In the 1920s, a set of immigration laws in the United States imposed quotas based on national origin and restricted immigrant flows. These policies cut immigration flows from constrained countries to around 150,000 individuals a year. The effects of this policy change are identified in a difference-in-difference framework utilizing the LIFE-M, historical labor survey, and full count census data. Results indicate that individuals in areas facing larger declines in immigration are observed transitioning into occupations and industries with worse associated health measures. Increasing native-born employment in high health cost (HHC) positions offset lost immigrant labor leading to no change in HHC employment share. Further, policy exposure was associated with declining average lifespan and increasing mortality rates among counties’ working age US-born population.

Accurate perception of social relationships is central to human social cognition, yet little is known about how well individuals perceive incoming social ties within their natural social environments. We collected data from 3,077 adolescents across 117 classrooms and analyzed complete social networks comprising four directed relational layers—friends, best friends, enemies, and worst enemies—alongside adolescents’ predictions of who would nominate them in each layer. Across all layers, perceptual accuracy was strikingly low. Only 0.29% of students assessed all of their relationships correctly. Errors were overwhelmingly driven by underestimation: adolescents systematically failed to recognize how many peers named them, both positively and negatively. Misperception was structured rather than random. Popularity (in-degree) was strongly associated with underestimation, whereas sociability (out-degree) was associated with overestimation. These structural patterns were consistent across relational layers and error types and showed no systematic improvement with age. Together, these findings reveal robust structural asymmetries in social cognition, suggesting that young people perceive far less of their social worlds than there is.

 This paper investigates the effects of a price transparency policy on spatial competition in a retail fuel market. Using post-policy data, I examine how increased consumer-side transparency affects competition. I develop an empirical model of demand and supply that accounts for both fully informed consumers and those facing price uncertainty. Prior research shows that major brands coordinated before the policy and continued to do so afterward. Building on this evidence, I model coordination among major brands and allow its stability to depend on the share of informed consumers. I find that as more consumers become informed, price dispersion and profit margins decline. However, the extent of coordination among major firms remains stable. These findings suggest that while consumer-side transparency increases competitive pressure, its pro-competitive effects may be limited or even reversed if coordinating firms can also access the same transparency tools.

This paper examines how the origin of income mobility—whether driven by individual effort or luck—affects preferences for redistribution. The existing literature emphasizes how expectations of future income shape redistributive support, while abstracting from the mechanisms that generate income mobility. I study this question using a laboratory experiment in which individuals face identical income transition structures but differ in whether their mobility prospects are generated by relative effort or by luck. The results reveal that the mobility mechanism triggers significant heterogeneity across the income distribution. Among low-income individuals, effort-based mobility increases support for redistribution relative to luck-based mobility when upward mobility prospects remain insufficient to reach top-income positions. This pattern suggests that meritocratic processes can be perceived as procedurally unfair when advancement opportunities are limited, highlighting the political relevance of procedural features of income mobility. Conversely, high-income individuals tend to reduce their support for redistribution under effort-based mobility when they are more productive than the average. The paper also documents that biased beliefs about relative performance moderate redistributive preferences. Participants who are poorer than average but expect to become richer than average in the future, due to overconfidence in their relative performance, tend to support lower levels of redistribution. Overall, the findings indicate that preferences for redistribution depend not only on expected future income but also on the perceived legitimacy of the process through which mobility is generated.

This paper examines how prison inmates anticipate being stigmatized by the inmate label and whether a brief self-affirmation intervention can recalibrate these beliefs. In Study 1, we assess the perceptions of inmates (N = 297) about the extent of trust and altruism that will be given to them by general society by manipulating disclosure of their prison status in an incentivized lab-in-the-field experiment. The findings reveal that when their prison status was disclosed, inmates anticipated greater altruism, reflecting optimism rather than anticipated stigma, although their expectations of trust did not differ. We find no significant effects of self-affirmation on their beliefs about altruism, trust, or trustworthiness; nor on the proposed psychological channels of inmates’ confidence and risk taking. In Study 2 (N=489), we conceptually replicate optimism about altruism in a one-shot setting using incentivized spectator predictions, and identify the likely underlying mechanism as the perception that society will treat them favorably due to hardships they face during incarceration spells and uncertainty about the nature of their crime. Their expectations were more realistic for longer-horizon trust-based domains such as securing employment and housing, and for general kindness ratings. 

I provide new evidence on the labor market impacts of military conscription using employer-employee administrative data covering the universe of men born between 1958 and 1975 in Argentina. For identification, I exploit the random assignment of draft eligibility generated by 18 draft lotteries. I find that draft eligibility depresses early-career outcomes: At ages 20-24, eligible men exhibit lower employment and earnings. These penalties fade with age and do not accumulate into sizable long-run losses. Eligibility to conscription increases the likelihood of holding formal employment and a permanent contract, with no average effect on medium- or long-run earnings. The enduring consequence of conscription is a modest reallocation of employment away from agricultural activities and toward service-oriented and higher-paying sectors, reducing employment in the lowest-wage activities among the most geographically disadvantaged individuals. Overall, these results indicate that conscription can affect industry sorting rather than merely disrupt labor market entry in early adulthood, but the magnitudes are modest and do not translate into measurable gains in earnings.

Older workers are often viewed as obstacles to innovation, suggesting that their exit allows firms to reallocate resources toward new capital and technology. I argue instead that older, experienced workers support both the continuity of current production and the capacity to integrate new technologies into existing operations. The key empirical challenge is that when retirements are anticipated, firms have time to transfer knowledge internally, making the productivity value of older workers difficult to observe. I address this by studying a 2014 German pension reform that unexpectedly lowered the early retirement age for experienced workers by up to 29 months, inducing a sudden and unanticipated loss of long-tenured employees. Firms exposed to the reform reduce capital accumulation, delay technology adoption, and experience subsequent declines in revenue and value added, consistent with the erosion of firm-specific human capital. To interpret these findings, I develop a stylized model in which older workers transfer uncodified, firm-specific knowledge that is essential for maintaining legacy capital and integrating new technologies into firms’ operations. The model predicts, and the data confirm, that unexpected retirements weaken firms’ ability to sustain production and slow the pace of technological upgrading.

This paper studies the relationship between patient cost-sharing and the demand for care after hospital stays (post-acute care), and how this relationship is mediated by non-medical custodial care needs and the presence of the family. Using plausibly exogenous variation in the number of free skilled nursing facility (SNF) days at hospital discharge, I first show that higher cost-sharing for SNFs leads to substitution away from SNFs to home health and routine discharges with no care. Moreover, for those who are already in a SNF, discharges rise sharply when cost-sharing begins. I further document that people with family are less likely to use SNFs, while people with custodial care needs are more likely to use SNFs. I use these findings to motivate a dynamic structural model that begins at hospital discharge and follows patients through further discharge decisions in different post-acute settings. Using the model, I explore the implications of alternative cost-sharing structures. I find that eliminating the non-linearity in SNF copay can generate large Medicare savings at small costs to the patients. Medicare subsidizing custodial care at home enhances patient welfare substantially for individuals without family, at no additional cost to Medicare. For patients with family, the same policy, while still beneficial to the patient, will increase Medicare costs substantially, resulting in a net zero effect overall.

We assess the welfare impact of the introduction of universal daycare services in Qu´ebec in 1997. Unlike the standard sufficient-statistic metric, which assumes marginal changes in fiscal policy, our approach accounts for the non-marginal nature of the program and quantifies nonpecuniary benefits. Through a structural model of childcare demand, we estimate substantial welfare gains from the policy, yielding a Marginal Value of Public Funds (MVPF) above 3.5. Using the sufficient-statistic approach underestimates welfare gains by half. Counterfactual simulations and a difference-in-differences analysis suggest that increasing availability, rather than solely improving affordability, is crucial for the effective design of universal programs.

Despite years of transparency reforms, their impact on civic participation is not well understood. We study whether government performance information from one of the largest transparency initiatives can motivate citizens to participate and whether changes in beliefs are the mechanisms driving this effect. The initiative tracks 112 of India’s 806 most underperforming districts across key development indicators and posts performance information online for public accountability. We conducted a randomized field experiment with 2,107 adults in a district targeted by the initiative. Over 90% in our setting were unaware of the initiative, and 75% overestimated their district’s performance. Our low-cost, scalable video intervention informed citizens that their district was included, revealed its declining performance relative to neighboring districts, and listed formal grievance channels. Citizens randomly assigned to watch the video were 5 pp more likely to sign the petitions and 8.4 pp more likely to attend workshops on complaint filing portals. They updated beliefs about their district’s low rank and became more aware of the initiative. Citizens who initially overestimated their district’s rank updated their beliefs and increased participation, while we observed no effects among those who had not overestimated prior to treatment. Beliefs about citizens’ influence over service delivery remained unchanged. One month later, beliefs about the district’s rank converged, yet citizens in the intervention group continued to meet civic officials and file complaints. Those who initially overestimated their district’s rank remained significantly more likely to participate. To explain why citizens continue participating despite low perceived influence, we develop a model where participation depends on expected performance gaps relative to aspirational service levels and perceived influence over government. Larger perceived gaps alone can sustain participation through an accountability channel. These findings have implications for 250 million Indians in most-underperforming districts and highlight how prior beliefs mediate effectiveness of transparency programs.

We study whether machine learning forecast combinations can improve on the equal-weight mean of survey forecasts from Slovak commercial banks for GDP growth and inflation. Using monthly bank forecasts with full histories (2007–2024; 216 observations per series) and real-time data vintages that respect publication lags, we run a rolling out-of-sample evaluation. We compare linear and penalised regressions (OLS, ridge, lasso, elastic net), nonlinear methods (trees, random forests, XGBoost, kNN, SVR), an ARIMA benchmark, and stacked ensembles estimated via non-negative least squares. Performance is measured by relative MSE versus the bank mean. For inflation, regularised linear combinations deliver consistent gains (RelMSE at around 0.81–0.82), while nonlinear and stacked approaches underperform, suggesting overfitting in small panels. For GDP, several nonlinear models and a restricted stack improve materially on equal weights.

How do parents respond to their peers’ choices when deciding whether and how much to invest in their children’s extracurricular education? Using a field experiment, we identify distinct mechanisms through which peer information shapes investment decisions: positive and negative social learning, as well as social utility. Consistent with positive social learning, we find that peers’ willingness to purchase a course increases both parents’ willingness to purchase and their level of investment. Negative social learning effects, however, depend on the nature of the signal.  Explicit peer criticism significantly reduces both willingness to invest and spending, whereas peer non-purchase without negative evaluation has no effect. Social utility effects also vary by peer purchase price: high-price peer purchases increase spending, whereas low-price peer purchases raise a parent’s willingness to invest but do not lead to higher expenditures. We further document heterogeneity in responses to negative peer signals across socioeconomic and residential contexts. Using an enhanced causal forest approach to complement our regression analyses, we find that peer non-purchase without explicit criticism increases purchase preference among parents in less central areas with smaller socioeconomic gaps, but reduces it among parents in central areas with larger gaps.

This paper investigates whether severe economic hardship undermines preferences for honesty. We use controlled, incentivized measures of cheating for private benefit in a large, diverse sample of 5,676 Kenyans, exploiting three complementary sources of variation: experimentally manipulated monetary incentives, randomized increase in salience of own financial situation, and the Covid‑19 income shock, exploiting randomized survey timing as a natural experiment with respondents surveyed before and during the crisis. We find that severe economic hardship—marked by a 50% drop in monthly earnings— leads to a sharp increase in the prevalence of cheating, from 43% to 72%. Cheating behavior is highly responsive to financial incentives and increases gradually with prolonged hardship. The effects are largest among the most economically impacted and are amplified when salience of own financial situation is experimentally increased. Predictable seasonal income fluctuations, in contrast, do not affect honesty. The results demonstrate that while most individuals exhibit a strong preference against cheating under normal conditions, severe economic hardship substantially erodes honesty.

This study investigates the effects of California’s Senate Bill 328 (SB 328)—the first state legislation requiring later school start times for middle and high schools—on adolescent sleep, mental health, and academic outcomes. Drawing on data from the Youth Risk Behavior Surveillance System (YRBS) for high school students (grades 9–12) and the American Time Use Survey (ATUS), which includes sleep duration for adolescents aged 15 above and bedtimes and wake-up times for children under 13, we analyze shifts in sleep patterns and mental health metrics. We then examine the impact on academic performance using district-level data from the Stanford Education Data Archive (SEDA) for students in grades 3–8 and SAT scores for high school students. Employing difference-in-differences (DID) and matched DID methods, we find that SB 328 led to a 14% increase in the share of students sleeping at least 8 hours per night, consistent with CDC recommendations for adolescents. We find suggestive evidence of a reduction in certain mental health problems, particularly difficulties concentrating, though the results are imprecisely estimated and not robust across specifications. Finally, we find evidence of significant improvements in math and English scores in grades 3–8 (approximately a .1 standard deviation increase), while SAT scores rose by 2%. We uncover substantial heterogeneity in the policy's effects, with larger improvements in sleep and mental health among boys and Hispanic students, and larger academic gains among Hispanic students.

Despite the potential of economics to serve as a vehicle for social mobility and its impact on society, persistent disparities in participation and progression raise important concerns for the discipline. This presentation examines the structure of the economics education pipeline in the UK, focusing on patterns of entry, attrition, and academic outcomes across key demographic dimensions. Using institutional-level data from UK universities, I analyse variations in enrolment, continuation rates, and degree attainment by gender, ethnicity, and socio-economic background. The analysis identifies systemic barriers and points of attrition that disproportionately affect students from underrepresented groups.

The notion of a “preference” lies at the heart of economic analysis. Yet, because preferences are typically inferred from observed behavior - and because such behavior is often shaped by cognitive biases and bounded rationality - this raises a fundamental challenge: how can we recover individuals’ true economic preferences when their decisions are systematically distorted? This paper addresses that challenge by proposing a novel method to identify true preferences in the presence of attenuation biases - a pervasive distortion that arises when individuals are uncertain about what choice is optimal and thus respond only weakly to economic incentives. Under mild assumptions, the two elicitations allow the direction and magnitude of the bias to be bounded; and under stronger but plausible assumptions, the method delivers a unique inference of the true preference. Evidence from two experiments confirms the validity and generalizability of the method. First, in an induced-value experiment that approximates product demand decisions, observable demand curves imply non-trivial attenuation bias and associated welfare distortions. Second, in a contingent valuation experiment where people evaluate policy programs, observable valuations are insensitive to the scope of the program – a pattern known as “scope neglect”. Applying the proposed method shows that scope neglect is largely attributable to attenuation bias and that true sensitivity of valuation to scopes are likely much higher than from observable behavior. 

The spread of disinformation is widely regarded as one of the most serious short-term global risks and a major societal challenge. In one laboratory and three online experiments, we measured trust in true, false, and disinformation statements related to the Russo-Ukrainian war, politics, climate, and health. We examined the effects of refuting disinformation using a corrective message containing factual information. By manipulating the timing of the message, we tested whether it is more effective to intervene before exposure to disinformation (i.e., to prebunk) or after exposure (i.e., to debunk). We found that debunking significantly outperformed prebunking. The positive effects of debunking persisted for at least two weeks. In the fifth experiment, we examined both direct and indirect (i.e., spillover) effects of endorsing some of the true statements and refuting some of the disinformation statements with either fact-based or logic-based corrective message. The two interventions performed similarly overall, but fact-based corrective messages resulted in marginally larger positive direct effects, while logic-based corrective messages generated significantly larger positive spillover effects.

While technology can magnify existing inequalities by excluding marginalized groups in society, paradoxically, it can also serve as a means for them to move from isolation to inclusion. In this paper, we report a study illustrating how individuals belonging to one marginalized group—people with lifelong disabilities (PWLD)—used technology to navigate this path. Our study was part of an initiative by the Norwegian government exploring how PWLD can attain social inclusion (SI) through the use of virtual worlds (VW), specifically Second Life (SL). Using a conceptualization of SI specific to PWLD, which consists of two interrelated domains—interpersonal relations and community participation—we trace how the actualization of affordances in VW enabled PWLD to achieve SI. This outcome was built upon the realization of five interrelated affordances: Communicability, Mobility, Personalizability, Engageability, and Self-actualizability. Based on these insights, we demonstrate the role of VW affordances in achieving SI and propose a model titled the affordance-based pathway model of social inclusion. We contribute to the discourse on affordance theory by extending the role of facilitating conditions. Specifically, the outcomes achieved by the actualization of certain affordances can serve as facilitating conditions that support the perception and eventual actualization of other affordances.