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Essays in Spatial Econometrics.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Essays in Spatial Econometrics./
作者:	Yang, Yang.
面頁冊數:	1 online resource (138 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-03, Section: A.
Contained By:	Dissertations Abstracts International84-03A.
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29444074click for full text (PQDT)
ISBN:	9798841762058

Essays in Spatial Econometrics.
Yang, Yang.

Essays in Spatial Econometrics. - 1 online resource (138 pages)

Source: Dissertations Abstracts International, Volume: 84-03, Section: A.

Thesis (Ph.D.)--The Ohio State University, 2022.

Includes bibliographical references

Spatial econometrics models, especially the spatial autoregressive (SAR) model and its extension to panel settings had been used widely in empirical research in several different fields, especially when we need to capture the effects from networks. However, more empirical researchers are focusing on new questions where the linear spatial econometrics models could not handle. My dissertation tries to extend traditional models to capture two types of effect: risk spillover through financial networks and heterogeneous peer effect through social networks, and develops likelihood approach to estimate these models.Chapter 1 tries to incorporate risk spillover effect with GARCH type models. By introducing both intra-temporal and inter-temporal risk spillover through network, we propose a new multivariate conditional volatility model. For stationary case, the model can capture the dynamic of conditional heteroskedasticity structure when there are long-run stable links among multiple markets, and it is easy to be estimated consistently by QMLE approach. By Monte Carlo simulations, we show good finite sample performance when n/T → 0.When applying the model to monthly stock return innovations of 11 eurozone countries from March 1999 to April 2021, by using geographical and institutional links to capture the network between the countries, the performance of our model dominates single variate GARCH(1,1), EGARCH(1,1) and multivariate GARCH with both constant correlation and dynamic conditional correlation settings by likelihood values and AIC criteria.Chapter 2 considers social interaction models with group fixed effects and observed heterogeneity among agents. By likelihood approach, with the control of group-level confounding effects of the common variables, both heterogeneous endogenous peer effects and exogenous contextual effects can be identified and estimated consistently. Under some regularity assumptions, we prove the consistency and asymptotic normality of the QMLE. Monte Carlo simulation results show that our QMLE has good finite sample performance. For an application, we investigate the China Education Panel Survey (CEPS) and focus on gender heterogeneity on academic achievement of Grade 8 students in junior high school. We capture significant gender disparities in peer effects from gender subgroups in a classroom. Besides, female students' test scores are more subject to both female and male peers' average achievement.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798841762058Subjects--Index Terms:

Social interaction modelsIndex Terms--Genre/Form:

542853
Electronic books.

Essays in Spatial Econometrics.
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520 $a Spatial econometrics models, especially the spatial autoregressive (SAR) model and its extension to panel settings had been used widely in empirical research in several different fields, especially when we need to capture the effects from networks. However, more empirical researchers are focusing on new questions where the linear spatial econometrics models could not handle. My dissertation tries to extend traditional models to capture two types of effect: risk spillover through financial networks and heterogeneous peer effect through social networks, and develops likelihood approach to estimate these models.Chapter 1 tries to incorporate risk spillover effect with GARCH type models. By introducing both intra-temporal and inter-temporal risk spillover through network, we propose a new multivariate conditional volatility model. For stationary case, the model can capture the dynamic of conditional heteroskedasticity structure when there are long-run stable links among multiple markets, and it is easy to be estimated consistently by QMLE approach. By Monte Carlo simulations, we show good finite sample performance when n/T → 0.When applying the model to monthly stock return innovations of 11 eurozone countries from March 1999 to April 2021, by using geographical and institutional links to capture the network between the countries, the performance of our model dominates single variate GARCH(1,1), EGARCH(1,1) and multivariate GARCH with both constant correlation and dynamic conditional correlation settings by likelihood values and AIC criteria.Chapter 2 considers social interaction models with group fixed effects and observed heterogeneity among agents. By likelihood approach, with the control of group-level confounding effects of the common variables, both heterogeneous endogenous peer effects and exogenous contextual effects can be identified and estimated consistently. Under some regularity assumptions, we prove the consistency and asymptotic normality of the QMLE. Monte Carlo simulation results show that our QMLE has good finite sample performance. For an application, we investigate the China Education Panel Survey (CEPS) and focus on gender heterogeneity on academic achievement of Grade 8 students in junior high school. We capture significant gender disparities in peer effects from gender subgroups in a classroom. Besides, female students' test scores are more subject to both female and male peers' average achievement.
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