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Адрес: АУК "Покровский бульвар", Покровский б-р, д. 11, каб. S1009
Время работы: 10:00–19:00
Адрес: АУК "Покровский бульвар", Покровский б-р, д. 11, каб. S1009
Время консультаций: Monday & Tuesday, 15:00–16:20 (via Zoom): please, write me an email if you would like to attend these office hours
Расписание
ORCID: 0000-0002-9893-9192
ResearcherID: P-8253-2017
Scopus AuthorID: 57200224536
Google Scholar
Руководитель
Пекарский С. Э.
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Анцыгина Анастасия Леонидовна

  • Начала работать в НИУ ВШЭ в 2017 году.
  • Научно-педагогический стаж: 10 лет.

Образование, учёные степени

  • 2017
    PhD: Европейский университет-институт во Флоренции
  • 2012

    Магистратура: Уральский федеральный университет им. первого Президента России Б.Н. Ельцина, специальность «Экономика», квалификация «Магистр»

  • 2010

    Бакалавриат: Уральский государственный университет им. А.М. Горького, специальность «Экономика»

Достижения и поощрения

  • Благодарность Факультета экономических наук НИУ ВШЭ (февраль 2020)
  • Лучший преподаватель – 2022, 2021, 2020

Административные обязанности

1. Всероссийская олимпиада школьников "Высшая проба" (профиль "Экономика"): председатель методической комиссии / жюри (2018/2019 учебный год), член методической комиссии (2019/2020 и 2020/2021 учебный год). 

2. Участие в комиссиях по защите бакалаврских и магистерских выпускных квалификационных работ.

3. Отбор заявок, поданных на XX Апрельскую международную научную конференцию по проблемам развития экономики и общества (Москва, Россия).

4. Участие в отборе статей для HSE WP BRP Series.

5. Участие в отборе статей для Economic Journal, Southern Economic Journal, International Economic Review, International Journal of Game Theory, Journal of the European Economic Association, Games and Economic Behaviour, Journal of Economic Behavior and Organization.

Учебные курсы (2021/2022 уч. год)

Учебные курсы (2020/2021 уч. год)

Учебные курсы (2019/2020 уч. год)

Учебные курсы (2018/2019 уч. год)

Учебные курсы (2017/2018 уч. год)

Microeconomics-2 (Бакалавриат; где читается: Факультет экономических наук; направление "38.03.01. Экономика", направление "38.03.01. Экономика"; 2-й курс, 1, 2 модуль)Анг

Публикации2

Конференции

  • 2022
    EUI Alumni Conference in Economics (Florence). Доклад: Optimal Information Disclosure in Contests with Communication
  • Contests: Theory and Evidence (Reading). Доклад: Optimal Information Disclosure in Contests with Communication
  • Conference on Mechanism and Institution Design (Singapore). Доклад: Optimal Information Disclosure in Contests with Communication
  • EARIE (Vienna). Доклад: Optimal Information Disclosure in Contests with Communication
  • 2021
    SAET (Seoul). Доклад: Optimal Information Disclosure in Contests with Stochastic Prize Valuations
  • GAMES 2020.1 (Budapest). Доклад: Optimal Information Disclosure in Contests with Stochastic Prize Valuations
  • Contests: Theory and Evidence (Berlin). Доклад: Optimal Information Disclosure in Competing Contests with Capacity Constrained Players
  • EARIE (Bergen). Доклад: Optimal Information Disclosure in Competing Contests with Capacity Constrained Players
  • 2020

    St. Petersburg Economic Seminar (Санкт-Петербург). Доклад: Settlements under Unequal Access to Justice: Why Do Policemen in Russia Settle as Often as CEOs? (with Madina Kurmangaliyeva)

  • 2019

    Bern Workshop on Contest Theory (Bern). Доклад: Optimal Allocation of Multi-Dimensional Prizes in Contests with Heterogeneous Agents

  • ASSET (Athens). Доклад: Optimal Allocation of Multi-Dimensional Prizes in Contests with Heterogeneous Agents

  • NES Brown Bag Seminar (Москва). Доклад: Settlements under Unequal Access to Justice: Why Do Policemen in Russia Settle as Often as CEOs? (with Madina Kurmangaliyeva)

  • Workshop on Information Acquisition, Diffusion and Disclosure in Markets (Вена). Доклад: The Optimal Information Revelation in Contests with Stochastic Abilities
  • 2018

    The Micro and Macro Foundations of Conflict (Bath). Доклад: Settlements under Unequal Access to Justice: Why Do Policemen in Russia Settle as Often as CEOs? (with Madina Kurmangaliyeva)

  • 2017

    RES PhD Meeting (London). Доклад: Optimal Allocation of Multi-Dimensional Prizes in Contests with Heterogeneous Agents: Theory and an Empirical Application

  • SAET (Faro). Доклад: Optimal Allocation of Multi-Dimensional Prizes in Contests with Heterogeneous Agents: Theory and an Empirical Application

  • Contests: Theory and Evidence (Norwich). Доклад: Optimal Allocation of Multi-Dimensional Prizes in Contests with Heterogeneous Agents: Theory and an Empirical Application

  • iCare 5 Conference (Пермь). Доклад: Optimal Allocation of Multi-Dimensional Prizes in Contests with Heterogeneous Agents: Theory and an Empirical Application

  • 2016

    SAEe Meeting (Bilbao). Доклад: Optimal Allocation of Multi-Dimensional Prizes in Contests with Heterogeneous Agents: Theory and Empirical Application

  • Econometric Society European Winter Meeting (Edinburg). Доклад: Optimal Allocation of Multi-Dimensional Prizes in Contests with Heterogeneous Agents: Theory and an Empirical Application

Неопубликованные статьи

1. Optimal Allocation of Multi-Dimensional Prizes in Contests with Heterogeneous Agents 

We develop a model where two players with asymmetric preferences engage in a contest game. The key novelty is the introduction of multi-dimensional rewards. We characterize the optimal prize allocation that maximizes aggregate effort. When heterogeneity in preferences is strong and the designer cannot assign identity-dependent prizes, the loser must get a positive reward, which is in stark contrast to the existing literature. Such allocation eliminates the advantage of the stronger competitor and incentivizes the opponent to exert more effort (the equilibrium effect). Using data from twelve professional tennis competitions where prizes include money and the ATP ranking points, we test our theoretical predictions empirically. The identification strategy relies on exogenous variation in prizes over both dimensions and random matching between the players. We document the equilibrium effect in the data and recover the underlying preference profiles that define its direction.

2. Information Disclosure in Contests with Communication 

We study information disclosure in static contests where players do not know their own values of winning. The designer chooses a disclosure policy that maximizes the total expected effort and commits to it before learning the realized value profile. The available disclosure regimes include (1) public disclosure, (2) private disclosure, when each contestant learns only his own type, and (3) concealment. A distinct feature of our model is that before the actual competition starts, contestants are allowed to communicate with each other by sending informative (truthful) or uninformative (empty) messages independently and simultaneously. Our results show that under private disclosure, the contestants reveal their types with a positive probability. The designer’s choice of the disclosure regime depends on the communication technology. If this technology is assortative (the types get revealed more often when the contestants’ values of winning are the same), then concealment always delivers the highest total effort. With a disassortative technology, the designer must choose private disclosure if and only if the correlation between the contestants’ values of winning is sufficiently high. These results are in a stark contrast with the no communication benchmark.

3. Optimal Information Disclosure in Competing Contests with Capacity Constrained Players 

This paper studies optimal information disclosure in competing contests with identical players. Each player faces a capacity constraint on the total effort contribution and is ex ante uninformed about the difficulty of the task to be performed in one of the contests. The task can be either difficult (associated with a high effort cost) or easy (associated with a low effort cost). Before the game starts, the designer of a contest with the unknown task can commit to (1) fully disclose the task type or to (2) keep it private in order to maximize the aggregate effort exerted in her competition. When the capacity constraint is slack, the game between contests is equivalent to the non-competitive case. Otherwise, the contests become linked, and there is a substitution effect which forces the players to reallocated their effort to a competition they perceive as easiest. If the difficult task is sufficiently costly, then full disclosure generates substantial competitive gains from revealing the easy task and, hence, mitigates the substitution effect. When the cost of performing a difficult task declines, full disclosure results in significant competitive losses from revealing the difficult task to the contestants, and concealment turns to be more attractive.

Текущие проекты

Adverse Selection in Job Promotion Contests with Multi-Dimensional Skills (with Anna Ponomarenko)

Опыт работы

Сентябрь 2011– Август 2017: Ассистент Кафедры эконометрики и статистики, ВШЭМ, УрФУ (Екатеринбург, Россия)

Сентябрь 2016 – Май 2017: Ассистент профессора Филиппо Таддеи, The Johns Hopkins University, SAIS Europe (Болонья, Италия)

Информация*

  • Общий стаж: 12 лет
  • Научно-педагогический стаж: 10 лет
  • Преподавательский стаж: 10 лет
Данные выводятся в соответствии с требованиями приказа N 831 от 14 августа 2020 г. Федеральной службы по надзору в сфере образования и науки

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