Browsing by Author "Tirachini, Alejandro"

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    Flexible estimates of heterogeneity in crowding valuation in the New York City subway
    (2019) Bansal, Prateek; Hurtubia González, Ricardo; Tirachini, Alejandro; Daziano, Ricardo A.
    This paper aims at better understanding passenger valuation of subway crowding in New York City. To this end, we conducted a stated preference survey with a discrete choice experiment where New Yorkers chose an alternative from a set of two hypothetical unlabeled subway routes based on occupancy levels and other attributes. We used the collected data to estimate crowding multipliers that quantify the trade-off between travel time and standee density. The previous studies have resorted to parametric heterogeneity distributions in analyzing preference variations in crowding multipliers, which can lead to misspecification issues. The contribution of this study is thus to estimate crowding multipliers using state-of-the-art semi-nonparametric models – logit-mixed logit (LML)and mixture of normals multinomial logit (MON-MNL), and compare them across different parameter spaces. The estimated distribution of crowding multiplier of LML and MON-MNL coincide below median, but the former underestimates and the latter overestimates above median. Even though these flexible logit models can be useful for a comprehensive economic analysis of transit service improvements, these differences in estimates make model selection an important avenue for future research.
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    Mobility Changes, Teleworking, and Remote Communication during the COVID-19 Pandemic in Chile
    (2020) Astroza, Sebastián; Tirachini, Alejandro ; Hurtubia Gonzalez, Ricardo Daniel; Carrasco, Juan Antonio; Guevara, Angelo; Munizaga, Marcela; Figueroa, Macarena; Torres, Valentina
    Results from a mobility survey from Chile during the COVID-19 pandemic show a decrease of 44% of trips in Santiago, with metro (55%), ride-hailing (51%), and bus (45%) presenting the highest reduction. Modes with the lowest reduction are motorcycle (28%), auto (34%), and walking (39%). While 77% of workers from low-income households had to go out and work, 80% of workers from high-income households worked from home. Other important factors that correlate with teleworking are gender, educational level, employment status, and occupation. Regarding the number of trips for purposes other than work, significant factors are gender, age, and employment status.
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    Using Disaggregated and Latent Variable Analysis to Investigate the Role of Socioeconomic Factors in Concerns and Expectations Related to the Covid-19 Pandemic in Chile
    (2022) Tirachini, Alejandro; Guevara, Angelo; Munizaga, Marcela; Carrasco, Juan Antonio; Astroza, Sebastián; Hurtubia González, Ricardo
    The COVID-19 pandemic has triggered a complex set of psychosocial effects, such as anxiety, depression, financial loss, burnout, and fear of infection. We study the role of socioeconomic factors in the concerns related to the COVID-19 pandemic, as well as the expectations of social changes on a post-pandemic future. The analysis is performed by collecting 22 indicators from a sample of 4,395 adults in Chile. The analysis is performed first by descriptive statistics, then by fusing the indictors into three latent variables, and finally by modelling each indicator as a separate choice. We find that lower-income people are significantly more worried about a range of financial and health issues arising from the COVID-19 pandemic, including concerns about being infected by the virus, losing their job and not being able to pay debts. The concern about facing a large economic crisis is significantly larger in the extremes, i.e., for low- and high-income groups. Age, gender, having a university degree, the possibility of working from home, and the general health status also influence the fears related to the COVID-19 pandemic. From a policy point of view, we conclude that strong policy interventions are necessary to reduce the uneven negative effects of COVID-19 in society, including material and mental health problems. From a methodological point of view, our results show that, while using a latent variable approach allows disentangling the main drivers of the phenomenon, rich content may be omitted when a disaggregated analysis is neglected, therefore both approaches are complementary.