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Книга
Инжиниринг и отраслевая наука: повестка дня
В печати

Годунова Е. А., Княгинин В. Н., Харитонов М. А. и др.

2023.

Глава в книге
Global cognitive graph properties dynamics of hippocampal formation

Sorokin K., Andrey Z., Levin A. et al.

In bk.: Data Analytics and Management in Data Intensive Domains: 25th International Conference, DAMDID/RCDL 2023, Moscow, Russia, October 24–27, 2023, Revised Selected Papers. Vol. 2086: Communications in Computer and Information Science. Springer, 2024. P. 77-87.

Препринт
An Axiomatic Characterization of Weighted Congestion Games

Gusev V.

ECONOMICS. WP HSE 1/EC/2025. НИУ ВШЭ, 2025

Третье заседание регулярного научного семинара департамента экономики СПб ШЭМ НИУ ВШЭ

На третьем заседании регулярного научного семинара департамента экономики СПб ШЭМ НИУ ВШЭ с докладом "A daptive Learning and Survey Expectations of Inflation"  выступит профессор Центра экономических исследований и образования CERGE-EI (Прага) Сергей Слободян (Sergey Slobodyan).
 Дата и место: 3 декабря 15:20, ауд.  306, ул. Седова, 55, корп.2.
Аннотация доклада:

In this paper, we use data from the Survey of Professional Forecasters to evaluate alternative assumptions about the way expectations are formed in DSGE models. The integration of this additional source of information in our models can also improve their fit given the excellent predictive quality of these surveys. Consistency between the survey and the model forecast makes it easier for the modeler to integrate timely survey publications in the forecasting process and to deliver a more comprehensive interpretation of the actual and expected state of the economy. Such an interpretation of the business cycle should also leave room for a specific role of expectation errors, driven by over optimistic or -pessimistic beliefs (Milani 2012, Eusepi and Preston 2011, Fuster et al 2012) and of news innovations that are not yet incorporated in realized macroeconomic variables (Schmitt-Grohe and Uribe 2012). Most likely, the validity of these results will heavily depend on the consistency between the models that underlie the two forecasts.