Estimation of Matrix Exponential Unbalanced Panel Data Models with Fixed Effects: An Application to US Outward FDI Stock

Ye Yang*, Osman Doğan, Süleyman Taşp Inar

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: ???type-name???Makalebilirkişi

Özet

In this article, we consider a matrix exponential unbalanced panel data model that allows for (i) spillover effects using matrix exponential terms, (ii) unobserved heterogeneity across entities and time, and (iii) potential heteroscedasticity in the error terms across entities and time. We adopt a likelihood based direct estimation approach in which we jointly estimate the common parameters and fixed effects. To ensure that our estimator has the standard large sample properties, we show how the score functions should be suitably adjusted under both homoscedasticity and heteroscedasticity. We define our suggested estimator as the root of the adjusted score functions, and therefore our approach can be called the M-estimation approach. For inference, we suggest an analytical bias correction approach involving the sample counterpart and plug-in methods to consistently estimate the variance-covariance matrix of the suggested M-estimator. Through an extensive Monte Carlo study, we show that the suggested M-estimator has good finite sample properties. In an empirical application, we use our model to investigate the third country effects on the U.S. outward foreign direct investment (FDI) stock at the industry level.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)469-484
Sayfa sayısı16
DergiJournal of Business and Economic Statistics
Hacim42
Basın numarası2
DOI'lar
Yayın durumuYayınlandı - 2024

Bibliyografik not

Publisher Copyright:
© 2023 American Statistical Association.

Parmak izi

Estimation of Matrix Exponential Unbalanced Panel Data Models with Fixed Effects: An Application to US Outward FDI Stock' araştırma başlıklarına git. Birlikte benzersiz bir parmak izi oluştururlar.

Alıntı Yap