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Labor Supply of New York City Cabdrivers: One Day at a Time
Abstract
Life-cycle models of labor supply predict a positive relationship between hours supplied and transitory changes in wages.
We tested this prediction using three samples of wages and hours of New York City cabdrivers, whose wages are correlated within
days but uncorrelated between days. Estimated wage elasticities are significantly negative in two out of three samples. Elasticities
of inexperienced drivers average approximately −1 and are less than zero in all three samples (and significantly less than
for experienced drivers in two of three samples). Our interpretation of these findings is that cabdrivers (at least inexperienced
ones): (i) make labor supply decisions “one day at a time” instead of intertemporally substituting labor and leisure across
multiple days, and (ii) set a loose daily income target and quit working once they reach that target.
... We also found that yellow taxis' degree of change in fraudulent behavior varied with competition intensity; it was highest on routes where yellow taxis compete with green taxis for both pickups and post-drop-off pickups. The change in the fraudulent behavior of yellow taxis was greater during the hours of a change in driving shifts, indicating a desire to meet an income target set as a reference point (Camerer et al. 1997;Kukavica et al. 2022). In addition, we found higher levels of change in fraudulent behavior by yellow taxis for passengers traveling to or from hotels (who tend to be tourists and may be less knowledgeable about optimal routes), whereas the same did not hold true for trips to or from office buildings (where passengers tend to be locals and more familiar with optimal routes). ...
... Additionally, previous studies have observed that NYC cab drivers may set an income target as a reference point and attempt to meet their income targets (Camerer et al. 1997;Kukavica et al. 2022). Since the launch of green taxis, yellow taxis have to search more for post-12 drop-off pickups on trips within CR EN, which delays their achieving the specific income target. ...
... Grynbaum 2011). These observations echo the notion of an income reference point for taxi drivers, indicating that taxi drivers may set an income target as the reference point (Camerer et al. 1997;Kukavica et al. 2022). The increase in the fraudulent behavior of yellow taxis before the change in their working shifts may be a result of attempts to reach their unmet income targets (driven by the decrease in their market share as a consequence of the introduction of thousands 24 of green taxis in a span of a few months). ...
Increased competition can result in market efficiency. However, alternatively, it may provoke unethical behavior by sellers attempting to avoid losses-a risk that may be greater in credence goods markets, where consumers find it difficult to determine the value of goods or services received. The New York City (NYC) taxi market allows us to investigate how increased competition due to the launch of green-colored taxis (to serve only certain parts of NYC) may lead to fraudulent behavior by drivers of the established yellow taxis. An empirical study of more than 17 million matched yellow taxi trips revealed that fraudulent behavior was most prevalent on routes in which drivers faced increased competition for both pickups and post-drop-off pickups. However, after the launch of green taxis, there was no significant change in the trip distances of yellow taxis for rides subject to a flat-rate fare or for trips to/from office buildings where passengers were more familiar with optimal routes.
... Economists typically expect labor supply elasticities to be positive. Yet, using a novel dataset consisting of New York City cabdrivers, Camerer et al. [11] showed that certain groups of workers have a negative CONTACT Justin Petrovich justin.petrovich@stvincent.edu labor supply elasticity. While the aforementioned papers all estimate labor supply elasticities at a particular point in time, Heim [25], Blau and Kahn [9], and Eckstein et al. [15] all estimate labor supply elasticities in different years using the same method across years. ...
... Since these effects of an increased hourly wage occur simultaneously, the higher wage has an ambiguous effect on labor supply. Empirical evidence supporting both positive and negative labor supply elasticities exists [see, for example [11,25]]. Evidence from [15,25] also suggests married female labor supply elasticities have decreased over time, which is similar to our results. ...
In this work we propose a functional concurrent regression model to estimate labor supply elasticities over the years 1988 through 2014 using Current Population Survey data. Assuming, as is common , that individuals' wages are endogenous, we introduce instrumental variables in a two-stage least squares approach to estimate the desired labor supply elasticities. Furthermore, we tailor our estimation method to sparse functional data. Though recent work has incorporated instrumental variables into other functional regression models, to our knowledge this has not yet been done in the functional concurrent regression model, and most existing literature is not suited for sparse functional data. We show through simulations that this two-stage least squares approach greatly eliminates the bias introduced by a naive model (i.e. one that does not acknowledge endogeneity) and produces accurate coefficient estimates for moderate sample sizes.
... Since then, the experiments have been replicated and extended in many ways, in parallel with a rich theoretical literature seeking to model reference dependence (see O'Donoghue and Sprenger, 2018, for a review). Empirical evidence of reference dependence has been found in experiments around the world (Ruggeri et al., 2020), and a wide range of field settings including the daily labor supply of taxi drivers (Camerer et al., 1997;Crawford and Meng, 2011;Thakral and Tô, 2021) and bicycle messengers (Fehr and Goette, 2007), job search (DellaVigna et al., 2017), behavioral responses to taxation (Homonoff, 2018;Rees-Jones, 2018), housing transactions (Andersen et al., 2022), and the timing of retirement (Seibold, 2021). ...
... Most closely related to our empirical application is the evidence from field settings described above (e.g. Camerer et al., 1997;DellaVigna et al., 2017;Homonoff, 2018;Rees-Jones, 2018). Existing work on reference dependence largely focuses on positive analysis of behavior and has so far refrained from formal welfare analysis. ...
... In a study of the work patterns of taxi drivers in New York City, Camerer et al. (1997) observed that taxi drivers, especially inexperienced ones, set a daily goal for themselves and when they reach that goal, they stop working for the day. This study has several noteworthy features. ...
This book chapter explains the necessity of behavioral economics to more accurately explain human economic decision-making processes.
... 3 These intertemporal daily labor supply findings contribute to a debate in labor economics regarding labor supply elasticity across more and less productive work time, though this context is complicated by the fact that firm owners with workers are working on a production process in conjunction with worker labor inputs. Camerer et al. (1997), Farber (2015, and Dupas, Robinson, and Saavedra (2018) presented evidence on the labor supply of vehicle and bicycle taxi drivers; Chang and Gross (2014) considered the labor supply of pear packers; Nguyen and Leung (2013) examined labor supply in fisheries; and Oettinger (1999) studied the labor supply of stadium vendors. ...
... For instance, combining loss aversion and myopia, Benartzi and Thaler (1995) provided an explanation to the equity premium puzzle. Camerer et al. (1997) used loss aversion to make sense of cab drivers' decisions on their daily working hours. Genesove and Mayer (2001) found that it explained the behavior of sellers on the housing market in Boston in the 1990s. ...
In this paper, we investigate how loss aversion affects people’s behavior in private litigation. We find that a loss-averse plaintiff demands a higher settlement for intermediate claims to maintain her threat to proceed to trial following rejection compared to a loss-neutral plaintiff. For larger claims, a loss-averse plaintiff demands a lower offer to increase the settlement probability as loss pains her extra in trial. We also investigate how various policies affect loss-averse litigants’ settlement decisions. Only a reduction in the asymmetry of information about trial odds uniformly leads to higher settlement rates.
... Meanwhile, there is an ongoing debate on the underlying behavioral assumptions for modeling the taxi driver objectives in the research community (28,29,30,31). In an early work, Camerer et al. (32) presented a regression of log-transformation of drivers' daily work hours on log-transformation of average hourly earnings and characterized taxi drivers as having RDP behavior with a daily income target and quit driving once the target is met. Then, Kőszegi and Rabin (33) proposed a theory of preferred personal equilibrium addressing that the anticipated wage will impact drivers' stopping decision (the drivers decide whether or not to look for an additional trip after the current trip). ...
While the growth of TNCs took a substantial part of ridership and asset value away from the traditional taxi industry, existing taxi market policy regulations and planning models remain to be reexamined, which requires reliable estimates of the sensitivity of labor supply and income levels in the taxi industry. This study aims to investigate the impact of TNCs on the labor supply of the taxi industry, estimate wage elasticity, and understand the changes in taxi drivers' work preferences. We introduce the wage decomposition method to quantify the effects of TNC trips on taxi drivers' work hours over time, based on taxi and TNC trip record data from 2013 to 2018 in New York City. The data are analyzed to evaluate the changes in overall market performances and taxi drivers' work behavior through statistical analyses, and our results show that the increase in TNC trips not only decreases the income level of taxi drivers but also discourages their willingness to work. We find that 1% increase in TNC trips leads to 0.28% reduction in the monthly revenue of the yellow taxi industry and 0.68% decrease in the monthly revenue of the green taxi industry in recent years. More importantly, we report that the work behavior of taxi drivers shifts from the widely accepted neoclassical standard behavior to the reference-dependent preference (RDP) behavior, which signifies a persistent trend of loss in labor supply for the taxi market and hints at the collapse of taxi industry if the growth of TNCs continues. In addition, we observe that yellow and green taxi drivers present different work preferences over time. Consistently increasing RDP behavior is found among yellow taxi drivers. Green taxi drivers were initially revenue maximizers but later turned into income targeting strategy
... Source: own elaboration. 17 An alternative explanation to this behaviour would be that farmers follow a satisfying rule (Camerer et al. 1997). That is, farmers could have a particular amount that they view as an optimum that they want to donate, irrespective of the nature of the donation (mandatory or voluntary). ...
Agri-environmental policies generally build around two complementary approaches: mandatory requirements and (compensated) voluntary measures. One of the challenges of the future EU Common Agricultural Policy is precisely to find the right balance between these two types of interventions. We conducted an experiment with farmers in three EU Member States to assess the impact of (1) increasing mandatory contributions to the environment , and of (2) decreasing unconditional income support. We also assess the effect of two key behavioural factors: environmental concern and trait reactance. Results show that both interventions reduce voluntary contributions to the environment, but the reduction is higher when mandatory contributions increase than when income decreases.. However, when mandatory contribution increases substantially, this more than offsets the reduction of voluntary contributions, leading to higher total contributions.
... A central finding in this literature is that the majority of TNC drivers operate part-time and that the value of flexible work is significant for drivers. 26,27 Camerer et al. 42 have also shown previously that taxi drivers make labor Environmental Science & Technology pubs.acs.org/est Article supply decisions "1 day at a time" and have loose income targets in mind for the day. ...
Transportation network companies (TNCs), such as Uber and Lyft, have pledged to fully electrify their ridesourcing vehicle fleets by 2030 in the United States. In this paper, we introduce AgentX, a novel agent-based model built in Julia for simulating ridesourcing services with high geospatial and temporal resolution. We then instantiate this model to estimate the life cycle air pollution, greenhouse gas, and traffic externality benefits and costs of serving rides based on Chicago TNC trip data from 2019 to 2022 with fully electric vehicles. We estimate that electrification reduces life cycle greenhouse gas emissions by 40-45% (9-10¢ per trip) but increases life cycle externalities from criteria air pollutants by 6-11% (1-2¢ per trip) on average across our simulations, which represent demand patterns on weekdays and weekends across seasons during prepandemic, pandemic, and post-vaccination periods. A novel finding of our work, enabled by our high resolution simulation, is that electrification may increase deadheading for TNCs due to additional travel to and from charging stations. This extra vehicle travel increases estimated congestion, crash risk, and noise externalities by 2-3% (2-3¢ per trip). Overall, electrification reduces net external costs to society by 3-11% (5-24¢ per trip), depending on the assumed social cost of carbon.
... result in above-average remuneration, the flexibility itself is of significant value and benefits women drivers and those from lowest-income census tracts in particular. Interestingly, Chen and Sheldon (2015) find that Uber drivers tend to drive more when potential earnings are high, contradicting a disputed but notable finding -made famous by Camerer et al. (1997) -that traditional taxi drivers quit once they hit a daily income target. As a result of surge pricing Uber drivers adjust their schedules to demonstrate a positive elasticity of supply, and ensure wider availability of taxi services than would otherwise be the case. ...
Because of their novelty, the rise of large platform companies, such as Uber, pose a genuine challenge to our attempts to classify and understand economic activities. This article utilises a broad view of cultural economics and subjectivist economic analysis to provide some clarity. We see how economic analysis is capable of dealing with companies that provide information based services, and why such industries are increasingly common. Goods, product categories and consumption rituals are all considered as social constructs, and subject to cultural interpretation. The main implication of this approach is how the prevention of exclusion and the elimination of entry barriers are both related and relevant to the well-functioning of market orders.
... In these situations, a decision maker perceives any negative departure from her status quo as a loss, while perceiving any positive departure from the same status quo as a gain (Tversky and Kahneman, 1981;Louie and De Martino, 2014). Later, there is growing evidence that people evaluate the outcomes in light of the expectations or their subjective goals which act as a reference point, similar to the status quo as a reference point (Camerer et al., 1997;Heath et al., 1999;Koszegi and Rabin, 2006;Abeler et al., 2011;Suomala et al., 2017). Therefore, the prospect theory is crucial to understanding the framing effect. ...
The human brain has evolved to solve the problems it encounters in multiple environments. In solving these challenges, it forms mental simulations about multidimensional information about the world. These processes produce context-dependent behaviors. The brain as overparameterized modeling organ is an evolutionary solution for producing behavior in a complex world. One of the most essential characteristics of living creatures is that they compute the values of information they receive from external and internal contexts. As a result of this computation, the creature can behave in optimal ways in each environment. Whereas most other living creatures compute almost exclusively biological values (e.g., how to get food), the human as a cultural creature computes meaningfulness from the perspective of one’s activity. The computational meaningfulness means the process of the human brain, with the help of which an individual tries to make the respective situation comprehensible to herself to know how to behave optimally. This paper challenges the bias-centric approach of behavioral economics by exploring different possibilities opened up by computational meaningfulness with insight into wider perspectives. We concentrate on confirmation bias and framing effect as behavioral economics examples of cognitive biases. We conclude that from the computational meaningfulness perspective of the brain, the use of these biases are indispensable property of an optimally designed computational system of what the human brain is like. From this perspective, cognitive biases can be rational under some conditions. Whereas the bias-centric approach relies on small-scale interpretable models which include only a few explanatory variables, the computational meaningfulness perspective emphasizes the behavioral models, which allow multiple variables in these models. People are used to working in multidimensional and varying environments. The human brain is at its best in such an environment and scientific study should increasingly take place in such situations simulating the real environment. By using naturalistic stimuli (e.g., videos and VR) we can create more realistic, life-like contexts for research purposes and analyze resulting data using machine learning algorithms. In this manner, we can better explain, understand and predict human behavior and choice in different contexts.
... Baker and Nofsinger's high-level survey of behavioral finance has at most a few pages devoted to experimental evidence out of 700 pages (Baker & Nofsinger, 2010). The classic behavioral economic investigation of taxi driver labor supply (Camerer et al., 1997) is purely observational. We are not complaining about observational evidence but just pointing out that some or much behavioral economics does not have the experimental economics OP. ...
From the mid-1960s until the late 1980s, the well-known general philosophies of science of the time were applied to economics. The result was disappointing: none seemed to fit. This paper argues that this is due to a special feature of economics: it possesses ‘orientational paradigms’ in high number. Orientational paradigms are similar to Kuhn’s paradigms in that they are shared across scientific communities, but dissimilar to Kuhn’s paradigms in that they are not generally accepted as valid guidelines for further research. As will be shown by several examples, orientational paradigms provide economics with common points of reference that support its epistemic coherence and make scientific discourse more easily possible across school boundaries. With the help of systematicity theory, a newer general philosophy of science, one can further elucidate the role of orientational paradigms with regard to scientific progress.
... Also, even if spend a bit more money in this month, people still have a chance to earn those money back in the future. 14 Camerer et al. (1997) survey of cab drivers finds that the number of hours that a driver works on a given day is strongly inversely related to his average hourly 14 Barberis (2013) suggests that "upon receiving a negative income shock, the individual prefers to lower future consumption rather than current consumption. After all, news that future consumption will be lower than expected is less painful than news that current consumption is lower than expected." ...
The seminal works by Daniel Kahneman, Amos Tversky and Richard Thaler have inspired many researches in behavioral economics. Behavioral economics and behavioral finance incorporate the concepts and methods in psychology science into traditional economics (finance).
... 10 Our treatment of driver labor supply is simple, ignoring behavioral considerations, such as income targeting (Camerer et al., 1997;Thakral and Tô, 2017) and even whether labor supply changes are due to extensive or intensive margin adjustments. Rather, we assume that labor supply can be captured with a single supply curve of total hours-worked. ...
... Moreover, it is well known that increasing the 'gift' does not necessarily lead to agents making more effort since the marginal effect decreases. For the context of monetary incentives, this observation has been explained by a crowding-out effect of rewards or individual earnings targets that pose an upper limit on effort (Camerer et al. 1997;Frey and Oberholzer-Gee 1997). We observe that performance does not increase but perhaps even decreases if learning is promoted too intensely. ...
Previous research on organizations often focuses on either the individual, team, or organizational level. There is a lack of multidimensional research on emergent phenomena and interactions between the mechanisms at different levels. This paper takes a multifaceted perspective on individual learning and autonomous group formation. To analyze interactions between the two levels, we introduce an agent-based model that captures an organization with a population of heterogeneous agents who learn and are limited in their rationality. To solve a task, agents form a group which experiences turnover from time to time, i.e., its composition changes periodically. We explore organizations that promote learning and changes in group composition either simultaneously or sequentially and analyze the interactions between the activities and the effects on performance. We observe underproportional interactions when tasks are interdependent and show that pushing learning and group turnover too far might backfire and decrease performance significantly.
... For example, Genesove and Mayer (2001) find that condo owners in downtown Boston rely on mark-ups relative to their purchase prices when setting selling prices. In labor economics, Camerer et al. (1997) show evidence that New York City cabdrivers use daily earnings targets as a reference point to determine their labor supply. Chira et al. (2019) show the role of reference points in the merger and acquisition. ...
When stocks are trading near their 52-week high investors tend to have low expectation about their future returns. We contrast such expectations against firms’ fundamental strength. For firms with strong fundamentals, we confirm that investors’ expectations are too low, which is consistent with the hypothesis that the 52-week high acts as a psychological anchor. We report that a fundamental-strength enhanced 52-week high trading strategy significantly outperform the unconditional strategy by nearly doubling its average return. Moreover, we provide interesting evidence that this anomalous effect is most evident when investor sentiment is high, but absent among more sophisticated institutions and short sellers.
... In the context of the COVID-19 pandemic, it is less clear how expectations would influence behaviors in case of negative surprises, especially since observation of others was limited during the lockdowns, which likely reduced the potential role of social norms to serve as reference points for compliant behaviors. 4 Abeler et al. (2011), for instance, show that setting ambitious expectations can lead people to work longer hours and earn more money (see also Camerer et al., 1997 andThakral andTô, 2017 for similar results). However, other studies suggest that this effect could go in the opposite direction, reducing rather than increasing effort. ...
We study the behavioral impact of announcements about the duration of a policy and their relationship with people's expectations in the context of the COVID-19 lockdowns. We surveyed representative samples of Italian residents at three moments of the first wave of the COVID-19 pandemic to test how intentions to comply with social-isolation measures depend on the duration of their possible extension. Individuals were more likely to reduce, and less likely to increase, their compliance effort if the hypothetical extension was longer than they expected, whereas positive surprises had a lesser impact. The behavioral response to the (mis)match between expected versus hypothesized extensions is consistent with expectations acting as reference points and can help explain the increase in observed social proximity in Italy following lockdown extension announcements. Our findings suggest that public authorities should consider citizens' expectations when announcing policy changes.
... Driver labor supply has been extensively studied in the literature (Camerer et al., 1997;Farber, 2005;Rosenblat and Stark, 2016;Sinchaisri et al., 2019;Sun et al., 2019;Xue and Zeng, 2019). Chen et al. (2019) estimated how drivers' reservation wages varied with time and examined the implications of flexible and traditional work arrangements on surplus and supply. ...
A R T I C L E I N F O Keywords: Multiple ride-sourcing platforms Multi-homing behavior Dynamic decision High-order hidden Markov model (HO-HMM) On-demand ride services A B S T R A C T Ride-sourcing drivers enjoy flexibility in scheduling work hours and choosing platforms, which generates multi-homing behavior on multiple platforms. It is challenging to observe the labor supply of multi-homing ride-sourcing drivers due to data limitations, which motivates our research on modeling drivers' dynamic decisions on labor supply in the competitive ride-sourcing market with multiple platforms. We propose a dynamic discrete choice framework by modeling drivers' high-frequency decision sequences on platform switching as high-order hidden Markov processes and considering time-varying factors. The high-order hidden Markov framework relaxes the first-order Markovian assumption and builds interdependencies of unobserved states across multiple time periods. The estimation of the proposed model takes advantage of city-scale multiple platforms datasets in Hangzhou, China, including more than 16 million records of the order payment information and more than 46 thousand records of active ride-sourcing drivers' information. The case study results indicate that the high-order hidden Markov model (HO-HMM) has superior explanatory power in fitting multiple platforms datasets than the multinomial logit model and the first-order hidden Markov model. HO-HMM performs an advantage in modeling the extended historical dependency of drivers' decisions and individual driver behavior modeling with high interpretability. The results uncover the variations of drivers' attitudes in different hidden (unobservable) states and towards different platforms. In general, ride-sourcing drivers respond actively and positively to income and working time. The findings support the platforms' decision-making on pricing, reward, and personalized management of ride-sourcing drivers, and provide beneficial suggestions for improving income in the competitive ride-sourcing market.
In this chapter, we conduct an empirical study using data from a live streaming platform to examine the impact of social incentives on users’ digital content contribution behavior. Our findings indicate that both social interaction and monetary rewards can increase users’ short-term frequency of content contribution and long-term retention on the platform. Furthermore, we observe that the effect of social interaction varies among users with different levels of experience on the platform.
This chapter provides an overview of the live streaming industry, highlighting its three primary stakeholders: broadcasters, viewers, and platforms. The chapter introduces the industry and its context, emphasizing the unique aspects of live streaming that make it an intriguing subject for studying digital contribution and consumption behavior. The empirical analyses in this chapter focus on the economics of live streaming and address several key questions. Through a review of relevant literature and data analysis from a popular Chinese live streaming platform, the chapter investigates factors influencing broadcasters’ receipt of gifts and viewers’ motivations to send them. It also explores the impact of gifting on churn rates for both broadcasters and viewers, as well as the correlation between economic, geographic factors, and the growth of the live streaming industry. The findings offer valuable insights into the economics of live streaming in China and pose further research questions. The subsequent parts of the book build upon live streaming as an empirical context, delving deeper into social incentives, motivations, and dynamics of digital content contribution and consumption behavior, including their social aspects.
We propose an account of individual differences in risk preferences called “reference-point theory” for choices between sure things and gambles. Like most descriptive theories of risky choice, preferences depend on two drivers—hedonic sensitivities to change and beliefs about risk. But unlike most theories, these drivers are estimated from judged feelings about choice options and gamble outcomes. Furthermore, the reference point is assumed to be the less risky option (i.e., sure thing). Loss aversion (greater impact of negative change than positive change) and pessimism (belief the worst outcome is likelier) predict risk aversion. Gain seeking (greater impact of positive change than negative change and optimism (belief the best outcome is likelier) predict risk seeking. But other combinations of hedonic sensitivities and beliefs are possible, and they also predict risk preferences. Finally, feelings about the reference point predict hedonic sensitivities. When decision makers feel good about the reference point, they are frequently loss averse. When they feel bad about it, they are often gain seeking. Three studies show that feelings about reference points, feelings about options and feelings about outcomes predict risky choice and help explain why individuals differ in their risk preferences.
In this paper, we employ large‐scale sensor data to examine the impact of data‐based intelligence and work‐related experience on the time efficiency of individual taxi drivers, measured by their propensity of choosing the fastest routes. The identification strategy is built on 1) a unique exogenous policy shock banning taxi‐hailing apps with embedded GPS system, and 2) a measure of Non‐Recurring Congestion (NRC) avoidance, enabled by the real‐time sensor data, which serves as a proxy for GPS usage. Our empirical model provides evidence that data‐based intelligence improves taxi drivers’ routing decisions by close to 3%, as measured by trip speed. Our results further demonstrate that inexperienced drivers have a higher chance of choosing the fastest route, as they are more likely to rely on the real‐time traffic information from GPS technology than experienced drivers. The general implications of our findings on the adoption and utilization of data‐based performance‐enhancing technology are discussed in closing.
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The role of information asymmetry in automobile insurance markets has been studied extensively. However, not all empirical studies found correlation between driver risk and chosen coverage. There are two explanations for this (Cohen and Siegelman 2010): (1) information asymmetry may not characterise environments in which consumers cannot act on private information; (2) most studies measure not risky driver behaviour, but ex post realisations of such behaviour, e.g. claims. In Taiwan’s taxi insurance market, insurers cannot freely use rating factors. Usage density (e.g. daily distance), a direct measure of risk, therefore constitutes private information. Using ordinary least squares models, we find that usage density is positively correlated with total premiums. Using logistic models, we find high-density drivers more likely to buy additional policies. Thus, usage density is positively correlated with insurance demand, consistent with the risk-coverage hypothesis. Unlimited-mileage coverage may disproportionately attract high-risk drivers, an argument in favour of usage-based insurance.
We conduct an experiment to determine competitiveness among shrimpers who engage in collecting shrimp seeds in the southwestern coastal region of Bangladesh. We then examine how competitiveness affects the labour supply decisions and labour market performance of these shrimpers. Our results show that shrimpers who prefer competition are more productive than shrimpers who do not prefer competition. Competitive shrimpers secure better prices and earn higher incomes selling their catches. We estimate that their wage elasticity of participation ranges from 0.4 to 0.5, which is consistent with preferences under neoclassical assumptions. Competitive shrimpers have a slightly greater wage elasticity than non‐competitive shrimpers, suggesting that they might be more responsive to expected earnings. Our results have important policy implications for the efficient management of common pool resources.
This paper tests the effect of a novel credit card payment format – repayment-by-purchase – on consumers’ payments toward credit card debt. In contrast to typical balance repayment, where consumers make repayments relative to a total amount owed, repayment-by-purchase prompts consumers to select items (e.g., a Starbucks coffee) or categories of purchase (e.g., restaurant and café purchases), and to make payments toward their related debt. A field experiment first suggests that customers who opted into repayment-by-purchase paid 12.18% more toward their statement balance than a control group. Subsequently, five lab experiments show that consumers repaying-by-purchase increase repayment by an average of 22.47% over typical balance repayment. Process evidence suggests that these differences may be driven by repayment-by-purchase’s power to increase purchase salience, which in turns increases perceptions of progress toward reducing debt. Consistent with this theory, the effect of repayment-by-purchase on bill repayment emerges regardless of whether consumers repay durable vs. non-durable goods, and for specific items or categories of purchases, as long as the bill uses labels that are concrete enough to raise past purchase salience.
In the sharing economy, how do changes in supply impact demand? We study this question by collaborating with a ride-sharing platform to conduct a natural field experiment. Our experimental design employs an instrumental variable strategy: by exogenously manipulating the driver subsidy schedule, we use the subsidy as an instrumental variable to identify the cross-side network effects of driver supply on orders, cancellations, and the aggregate customer lifetime value (CLV) of users. The results show that increasing the number of drivers at work by 1% will increase the number of customer orders by 2.01% and, conditional on the orders, further reduce the cancellation rate by 0.48%. The results also imply a long-term impact on the future revenue and profitability of the platform. We find that, for a 1% increase in the number of drivers working in the afternoon or at night, the aggregate CLV of users will increase by 1.62% or 0.50%, respectively. Our findings can help platforms improve operations, adjust incentives for suppliers, and strengthen the user experience.
What produces a happy society and a happy life? Thanks to the new science of wellbeing, we can now answer this question using state-of-the-art empirical evidence. This transforms our ability to base our decisions on the outcomes that matter most, namely the wellbeing of us all including future generations. Written by two of the world's leading experts on the economics of wellbeing, this book shows how wellbeing can be measured, what causes it and how it can be improved. Its findings are profoundly relevant to all social sciences, including psychology, economics, politics, behavioural science and sociology. A field-defining text on a new science that aims to span the whole of human life, this will be an invaluable resource for undergraduate and graduate students, policy-makers and employers, who can apply its insights in their professional and private lives. This title is also available as Open Access on Cambridge Core.
Inconsistency in consumer time preferences has been well-established and used to explain seemingly short-sighted behaviors (e.g., failures of self-control). However, prior research has conflated time-inconsistent preferences (discount rates that vary over time) with present bias (greater discounting when outcomes are delayed specifically from the present, as opposed to from a future time). This research shows that time-inconsistent preferences are reliably observed only when choices are substantially delayed (e.g., months into the future), which cannot be explained by present bias. This seeming puzzle is explained by a novel cross-period discounting framework, which predicts that consumers are more impatient when choosing between options occurring in different subjective financial periods. As a result, they display inconsistent time preferences and are less willing to wait for an equally delayed outcome specifically when a common delay to both options moves the larger-later option into a subsequent financial period. Six studies and multiple supplementary studies demonstrate that sensitivity to subjective financial periods accounts for time-inconsistent consumer preferences better than current models of time discounting based on present bias.
We document a form of attribution bias wherein people wrongly ascribe sensations of positive or negative surprise to the underlying disutility of a real-effort task. Participants in our experiments learned from experience about two unfamiliar tasks, one more onerous than the other. We manipulated expectations about which task they would face: some participants were assigned their task by chance, while others knew their assignment in advance. Hours later, we elicited willingness to work again on that same task. Participants assigned the less (more) onerous task by chance were more (less) willing to work than those who knew their assignment in advance. (JEL C91, D84, D91, M54)
This article investigates how and why the traditional on-demand service (i.e., taxies) and ridesharing platforms (e.g., Uber) perform in contexts of urban uncertainty. We consider different types of unexpected urban anomalies and collect large-scale trip data on taxi and ridesharing services. Empirically, we employ a difference-in-differences econometric model to compare the platform-level performances (measured by the number of fulfilled trips) of a traditional taxi system and a ridesharing platform after urban anomaly shocks. We observe that the ridesharing platform significantly outperforms the traditional taxi platform in coping with the uncertainties brought about by unexpected anomalies. We conclude, conservatively, that the technological effect and technology-enabled supply elasticity, are the main factors determining the differences between the platforms during an urban anomaly. This work offers important insights into the design of platform strategies, especially for stimulation of the labor supply and incentivization of the adoption and use of technology in urban transportation systems in response to anomalous urban upheavals.
Problem definition: Gig economy companies benefit from labor flexibility by hiring independent workers in response to real-time demand. However, workers’ flexibility in their work schedule poses a great challenge in terms of planning and committing to a service capacity. Understanding what motivates gig economy workers is thus of great importance. In collaboration with a ride-hailing platform, we study how on-demand workers make labor decisions; specifically, whether to work and work duration. Our model revisits competing theories of labor supply regarding the impact of financial incentives and behavioral motives on labor decisions. We are interested in both improving how to predict the behavior of flexible workers and understanding how to design better incentives. Methodology/results: Using a large comprehensive data set, we develop an econometric model to analyze workers’ labor decisions and responses to incentives while accounting for sample selection and endogeneity. We find that financial incentives have a significant positive influence on the decision to work and on the work duration—confirming the positive income elasticity posited by the standard income effect. We also find support for a behavioral theory as workers exhibit income-targeting behavior (working less when reaching an income goal) and inertia (working more after working for a longer period). Managerial implications: We demonstrate via numerical experiments that incentive optimization based on our insights can increase service capacity by 22% without incurring additional cost, or maintain the same capacity at a 30% lower cost. Ignoring behavioral factors could lead to understaffing by 10%–17% below the optimal capacity level. Lastly, our insights inform the design of platform strategy to manage flexible workers amidst an intensified competition among gig platforms.
Funding: This study was supported by The Jay H. Baker Retailing Center, The William and Phyllis Mack Institute for Innovation Management, The Wharton Risk Management and Decision Processes Center, and The Fishman-Davidson Center for Service and Operations Management.
Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2023.1191 .
Social reference points have been identified to be important determinants of individuals’ welfare. We investigate the consequences of social reference points for risk taking in a laboratory experiment. In the main treatments, risk-taking subjects observe the predetermined earnings of peer subjects when making a risky choice. We exogenously manipulate peers’ earnings and find a significant treatment effect: decision makers make less risk-averse choices in the case of larger peers’ earnings. The treatment effect is consistent with an application of prospect theory to social reference points and cannot be explained by reference points based on counterfactual information, anchoring, and experimenter demand effects. In additional analyses, we show that diminishing sensitivity seems to play an important role in subjects’ risky choices. We explore also whether inequity aversion and expectations-based reference points can account for our findings and conclude that they do not provide plausible alternative explanations for them.
This paper was accepted by Yan Chen, behavioral economics and decision analysis.
Funding: This research was financially supported by the Bonn Graduate School of Economics and the Center for Economics and Neuroscience in Bonn.
Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4698 .
Purpose
Online ride-hailing platforms match drivers with passengers by receiving ride requests from passengers and forwarding them to the nearest driver. In this context, the low acceptance rate of offers by drivers leads to friction in the process of driver and passenger matching. What policies by the platform may increase the acceptance rate and by how much? What factors influence drivers' decisions to accept or reject offers and how much? Are drivers more likely to turn down a ride offer because they know that by rejecting it, they can quickly receive another offer, or do they reject offers due to the availability of outside options? This paper aims to answer such questions using a novel dataset from Tapsi, a ride-hailing platform located in Iran.
Design/methodology/approach
The authors specify a structural discrete dynamic programming model to evaluate how drivers decide whether to accept or reject a ride offer. Using this model, the authors quantitatively measure the effect of different policies that increase the acceptance rate. In this model, drivers compare the value of each ride offer with the value of outside options and the value of waiting for better offers before making a decision. The authors use the simulated method of moments (SMM) method to match the dynamic model with the data from Tapsi and estimate the model's parameters.
Findings
The authors find that the low driver acceptance rate is mainly due to the availability of a variety of outside options. Therefore, even hiding information from or imposing fines on drivers who reject ride offers cannot motivate drivers to accept more offers and does not affect drivers' welfare by a large amount. The results show that by hiding the information, the average acceptance rate increases by about 1.81 percentage point; while, it is 4.5 percentage points if there were no outside options. Moreover, results show that the imposition of a 10-min delay penalty increases acceptance rate by only 0.07 percentage points.
Originality/value
To answer the questions of the paper, the authors use a novel and new dataset from a ride-hailing company, Tapsi, located in a Middle East country, Iran and specify a structural discrete dynamic programming model to evaluate how drivers decide whether to accept or reject a ride offer. Using this model, the authors quantitatively measure the effect of different policies that could potentially increase the acceptance rate.
Recent research has revealed a pattern of choice characterized as
diversification bias: If people make combined choices of quantities of goods for future consumption, they choose more variety than if they make separate choices immediately preceding consumption. This phenomenon is explored in a series of experiments in which the researchers first eliminated several hypotheses that held that the discrepancy between combined and separate choice can be explained by traditional accounts of utility maximization. On the basis of results of further experiments, it was concluded that the diversification bias is largely attributable to 2 mechanisms:
time contraction, which is the tendency to compress time intervals and treat long intervals as if they were short, and
choice bracketing, which is the tendency to treat choices that are framed together differently from those that are framed apart. The researchers describe how the findings can be applied in the domains of marketing and consumer education. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Based upon a recently developed multiattribute generalization of prospect theory's value function (Tversky and Kahneman 1991), we argue that consumer choice is influenced by the position of brands relative to multiattribute reference points, and that consumers weigh losses from a reference point more than equivalent sized gains (loss aversion). We sketch implications of this model for understanding brand choice.
We develop a multinomial logit formulation of a reference-dependent choice model, calibrating it using scanner data. In addition to providing better fit in both estimation and forecast periods than a standard multinomial logit model, the model's coefficients demonstrate significant loss aversion, as hypothesized.
We also discuss the implications of a reference-dependent view of consumer choice for modeling brand choice, demonstrate that loss aversion can account for asymmetric responses to changes in product characteristics, and examine other implications for competitive strategy.
A new model of consumer behavior is developed using a hybrid of cognitive psychology and microeconomics. The development of the model starts with the mental coding of combinations of gains and losses using the prospect theory value function. Then the evaluation of purchases is modeled using the new concept of “transaction utility.” The household budgeting process is also incorporated to complete the characterization of mental accounting. Several implications to marketing, particularly in the area of pricing, are developed.
This survey aims at providing the reader with a thread through the literature on the topic of panel econometrics of labour supply, reporting also on the evaluation of the data used in these studies, and summarizing their substantive results. It documents the present trend away from models that take advantage of panel data almost exclusively in order to control for unobserved heterogeneity, towards fully dynamic models where wages become endogenous and consequently the concept of wage elasticity loses much of its appeal.
Contrary to theoretical expectations, measures of willingness-to-accept greatly exceed measures of willingness-to-pay. This paper reports several experiments that demonstrate that this "endowment effect" persists even in market settings with opportunities to learn. Consumption objects (e.g., coffee mugs) are randomly given to half the subjects in an experiment. Markets for the mugs are then conducted. The Coase theorem predicts that about half the mugs will trade, but observed volume is always significantly less. When markets for "induced-value" tokens are conducted, the predicted volume is observed, suggesting that transactions costs cannot explain the undertrading for consumption goods. Copyright 1990 by University of Chicago Press.
The equity premium puzzle refers to the empirical fact that stocks have outperformed bonds over the last century by a surprisingly
large margin. We offer a new explanation based on two behavioral concepts. First, investors are assumed to be “loss averse,”
meaning that they are distinctly more sensitive to losses than to gains. Second, even long-term investors are assumed to evaluate
their portfolios frequently. We dub this combination “myopic loss aversion.” Using simulations, we find that the size of the
equity premium is consistent with the previously estimated parameters of prospect theory if investors evaluate their portfolios
annually.
Myopic loss aversion is the combination of a greater sensitivity to losses than to gains and a tendency to evaluate outcomes
frequently. Two implications of myopic loss aversion are tested experimentally. 1. Investors who display myopic loss aversion
will be more willing to accept risks if they evaluate their investments less often. 2. If all payoffs are increased enough
to eliminate losses, investors will accept more risk. In a task in which investors learn from experience, both predictions
are supported. The investors who got the most frequent feedback (and thus the most information) took the least risk and earned
the least money.
"Adaptation levels appear as neutral or indifferent zones in bipolar responses… . Adaptation levels are revealed in all forms of behavior whether they are sensory, motor, or cognitive verbal in nature… . We have found that the weighted log mean definition of AL [Adaptation Level] is the best approximation to the neutral or indifferent region for sensory magnitudes." Studies indicating current trends that bear on fundamental issues in AL theory are considered under the following headings: Anchoring Effects of Subliminal Stimuli; Residual Effects of Anchors in Memory and Recall; Series Effects with an Absolute, Extraexperimentally Anchored Language; Neutral Zones in Unexpected Places; Assimilation and Contrast in Sensory and Social-judgmental Processes; The Methodological Importance for Social Psychology of Studies Leading to Functional Relations Between Variables; and An Adaptation-level for Reinforcement and Performance. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Wages and their effect on labour supply are not only an important subject for labour economists who aim at measuring substitution and income effects. Additionally, the government is interested in the impact of policy changes on the labour market and companies would like to know if it is possible to increase labour supply and especially productivity by increasing the wage rate. This paper introduces a dynamic version of the traditional model of labour supply and presents model extensions and the underlying behavioural assumptions arising from empirical findings, psychology and neuroscience. It evaluates findings and behavioural assumptions derived so far. None of the contributions investigated in this work is entirely free from criticism. The problem of analysing a comprehensive model of labour supply on the one hand, is the scarcity of suitable subjects to investigate and on the other hand, the individuality of each subject observed. With this work a critical analysis of existing research on labour supply decisions is provided. This shall contribute to motivate and ease future research in this area which has to take these problems into account.
Does the period over which individuals evaluate outcomes influence their investment in risky assets? Results from this study
show that the more frequently returns are evaluated, the more risk averse investors will be. The results are in line with
the behavioral hypothesis of “myopic loss aversion,” which assumes that people are myopic in evaluating outcomes over time,
and are more sensitive to losses than to gains. The results have relevance for the equity premium puzzle, and also for the
marketing strategies of fund managers.
Much experimental evidence indicates that choice depends on the status quo or reference level: changes of reference point often lead to reversals of preference. The authors present a reference-dependent theory of consumer choice, which explains such effects by a deformation of indifference curves about the reference point. The central assumption of the theory is that losses and disadvantages have greater impact on preferences than gains and advantages. Implications of loss aversion for economic behavior are considered. Copyright 1991, the President and Fellows of Harvard College and the Massachusetts Institute of Technology.
Modern neoclassical business cycle theories posit that the observed fluctuations in consumption and employment correspond
to decisions of an optimizing representative individual. We estimate three first-order conditions that represent three tradeoffs
faced by such an optimizing individual. He can trade off present for future consumption, present for future leisure, and present
consumption for present leisure. The aggregate U. S. data lend no support to this model. The overidentifying restrictions
are rejected, and the estimated utility function is often convex. Even when it is concave, the estimates imply that either
consumption or leisure is an inferior good.
I test the disposition effect, the tendency of investors to hold losing investments too long and sell winning investments too soon, by analyzing trading records for 10,000 accounts at a large discount brokerage house. These investors demonstrate a strong preference for realizing winners rather than losers. Their behavior does not appear to be motivated by a desire to rebalance portfolios, or to avoid the higher trading costs of low priced stocks. Nor is it justified by subsequent portfolio performance. For taxable investments, it is suboptimal and leads to lower after-tax returns. Tax-motivated selling is most evident in December. Copyright The American Finance Association 1998.
This chapter presents a survey on the labor supply of men. This survey of male labor supply covers the determinants of whether men work for pay in the labor market and, if so, the determinants of their hours of work. The chapter also discusses the work behavior of men prior to their retirement from the labor force. Moreover, even though there are noteworthy investigations into the labor supply of men in many different countries, this survey is restricted almost entirely to the Anglo-American literature. The chapter identifies the major time-series and cross-section empirical regularities in male labor supply behavior. It is these that any economic theory should be designed to address. The chapter presents the canonical static model of labor supply and then immediately proceeds to deal with the problems in applying this model at the aggregative level. The static model is amended to handle the situation of nonlinear budget constraints. The chapter concludes with an outline of the most popular life-cycle model of labor supply. The chapter also addresses the issues in and results from the estimation of the static model. Problems in specifying the model are first considered and then the results are presented from the U.S. nonexperimental literature, the British literature, and the U.S. experimental literature. The chapter also discusses the estimates from the applications of the life-cycle model.
The paper presents a general theoretical framework for the analysis of integrated life-cycle models of consumption and family labor supply under uncertainty. Profit functions are used to represent intertemporally additive preferences and to yield convenient characterizations of "constant marginal utility of wealth" or "Frisch" demand functions. Conditions on preferences derived that allow additive fixed-effect specifications for the Frisch demands. Data from the British Family Expenditure Surveys from 1970-77 are used to derive panel-like information on male labor supply and consumption for several age cohorts over time. These data reproduce standard life-cycle patterns of hours and wages, but more detailed analysis shows that the theory is incapable of offering a satisfactory common explanation of the behavior of hours and wages over both the business cycle and the life cycle. Similarly, although the theory can explain the life-cycle behavior of hours and consumption separately, the same model cannot explain both, essentially because of a failure in symmetry.
Analysis of decision making under risk has been dominated by expected utility theory, which generally accounts for people's actions. Presents a critique of expected utility theory as a descriptive model of decision making under risk, and argues that common forms of utility theory are not adequate, and proposes an alternative theory of choice under risk called prospect theory. In expected utility theory, utilities of outcomes are weighted by their probabilities. Considers results of responses to various hypothetical decision situations under risk and shows results that violate the tenets of expected utility theory. People overweight outcomes considered certain, relative to outcomes that are merely probable, a situation called the "certainty effect." This effect contributes to risk aversion in choices involving sure gains, and to risk seeking in choices involving sure losses. In choices where gains are replaced by losses, the pattern is called the "reflection effect." People discard components shared by all prospects under consideration, a tendency called the "isolation effect." Also shows that in choice situations, preferences may be altered by different representations of probabilities. Develops an alternative theory of individual decision making under risk, called prospect theory, developed for simple prospects with monetary outcomes and stated probabilities, in which value is given to gains and losses (i.e., changes in wealth or welfare) rather than to final assets, and probabilities are replaced by decision weights. The theory has two phases. The editing phase organizes and reformulates the options to simplify later evaluation and choice. The edited prospects are evaluated and the highest value prospect chosen. Discusses and models this theory, and offers directions for extending prospect theory are offered. (TNM)
This paper discusses the bias that results from using nonrandomly selected samples to estimate behavioral relationships as an ordinary specification error or "omitted variables" bias. A simple consistent two stage estimator is considered that enables analysts to utilize simple regression methods to estimate behavioral functions by least squares methods. The asymptotic distribution of the estimator is derived.
Limited Computation and Fairness in Sequential Bargaining Experiments
- Eric J Johnson
- Colin F Camerer
- Talia Rymon
- Sankar Sen
Taxi Trip and Fare Data: A Compendium
- Limousine Nyc Taxi
- Commission
Labour Conditions in East Africa (London: Colonial Of ce
- G Orde-Brown
University of California at Berkeley working paper
- David Bowman
- Debby Minehart
- Matthew Rabin