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- W2783147086 abstract "In this chapter we deal with spatial models which have additional endogenous regressors. Since most economic variables are determined in an economy-wide system, additional endogenous regressors will often arise. As will typically be the case, we assume that the system determining these additional regressors is not known. Despite this, the researcher may know some of the exogenous variables that are in the unknown system. This is often the case considered in many applied studies. After some introductory comments, identification and estimation issues in a linear system are discussed. We then introduce notation for a nonlinear structural equation model, and consider its estimation. Large sample issues are discussed, as are applications to spatial models. This chapter concludes with a discussion of maximum likelihood that highlights some of the problems with that approach." @default.
- W2783147086 created "2018-01-26" @default.
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- W2783147086 date "2017-01-01" @default.
- W2783147086 modified "2023-09-27" @default.
- W2783147086 title "Additional Endogenous Variables: Possible Nonlinearities * *Spatial models involving additional endogenous variables were considered, among others, by Anselin (2011), Drukker et al. (2013c,d), Fingleton and Le Gallo (2008), Kelejian and Piras (2014), and Kelejian and Prucha (2007a). Useful references relating to issues involving nonlinearities which are discussed in this chapter are Amemiya (1985), Cameron and Trivedi (2005), Greene (2003), Kelejian (1971), and Pötscher and Prucha (1997, 2000)." @default.
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- W2783147086 doi "https://doi.org/10.1016/b978-0-12-813387-3.00006-8" @default.
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