tailieunhanh - Bài giảng Phân tích số liệu mảng - Chương 5: Dynamic panel model

Bài giảng Phân tích số liệu mảng - Chương 5: Dynamic panel model. Chương này cung cấp cho sinh viên những nội dung gồm: giới thiệu về Dynamic panel model; ước tính hiệu ứng cố định và ngẫu nhiên; ước tính biến công cụ (phương pháp IV) (Anderson và Hsiao, 1982); 2SLS, phương pháp tiếp cận mô men tổng quát (GMM) (Arenalloand Bond, 1985); . Mời các bạn cùng tham khảo! | 6 6 2022 Chapter 5 Dynamic Panel Model Mr U_KHOA TOÁN KINH TẾ 1 Objectives 2 1 Introduce about Dynamic Panel Model 2 Fixed and Random Effects Estimation 3 Instrumental Variable Estimation IV approach Anderson and Hsiao 1982 4 2SLS Generalized Method of Moment GMM approach Arenallo and Bond 1985 Mr U_KHOA TOÁN KINH TẾ 6 6 2022 Introduction 3 Linear dynamic panel data models include lag dependent variables as covariates along with the unobserved effects fixed or random and exogenous regressor p p yit 0 j y t j x it i u it j y t j x it u it i j 1 j 1 Notes The presence of lagged dependent variable as a regressor incorporates the entire history of it and any impact of xit on yit is conditioned on this history. We consider a dynamic panel model in the sense that it contains at least one lagged variables. For simplicity let us consider Mr U_KHOA TOÁN KINH TẾ yit γ1yit-1 β itxit αi uit 6 6 2022 yit γ1yit-1 β itxit αi uit 4 Eq. requires that γ By setting t 1 2 and so on the autoregressive process can be 5 expressed in the following way yi t 1 0 yi 0 i ui 0 yi 2 0 yi1 i ui 2 0 i 1 0 1 yi 0 i ui 0 ui 2 0 0 1 i i 1 12 yi 0 1ui1 ui 2 . t 1 yit 0 1 1 . t 1 1 1 i 1 . t 1 1 t 1 yi 0 1j ui t j j 0 Or t 1 t 1 t 1 yit 0 i yi 0 1j ui t j 1 j 1 j t 1 j 0 j 0 j 0 Therefore t 2 t 2 t 2 yit 1 0 i 1 j 1 j t 1 1 y 1j ui t 1 j i0 j 0 Mr U_KHOA TOÁN KINH TẾ j 0 j 0 6 6 2022 For l arg e t 1 1 6 E yit i 0 i 1 1 1 1 2 V yit i 1 12 Fixed and Random Effects Estimation yit γ0 γ1yit-1 αi uit Remark One possible cause for biasedness is the presence of the unknown individual effects αi which creates a correlation between the explanatory variables and the residuals y it y i 1 yit 1 y i 1 uit u i Notes yit 1 y i 1 will be correlated u it ui Mr U_KHOA TOÁN KINH TẾ 6 6 2022 yit y i 1 yit 1 y i 1 uit ui 7 depen on past value of uit depen on past value of uit The within estimator or fix effects estimator is y y N T it yi it 1 y i 1 1FE i 1 t 1 y N T 2 it 1 y i 1 i 1 t 1 y N T .