Consistent Misspecification Testing in Spatial Autoregressive Models

Lee, Jung-Yoon; Phillips, Peter C.B.; Rossi, Francesca

doi:10.2139/ssrn.3683830

Cited by 4 publications

(3 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…interactions. However, while adding higher-order spatial lags helps to address potential specification errors, it does not, of course, eliminate the possibility; for a recent contribution on an omnibus test for weights matrix misspecification see Lee, Phillips, and Rossi (2021).…”

Section: Parameterized Spatial Weightsmentioning

confidence: 99%

Simultaneous Equations Models With Higher-Order Spatial or Social Network Interactions

Drukker¹,

Egger²,

Prucha³

2022

Econom. Theory

View full text Add to dashboard Cite

This paper develops an estimation methodology for network data generated from a system of simultaneous equations, which allows for network interdependencies via spatial lags in the endogenous and exogenous variables, as well as in the disturbances. By allowing for higher-order spatial lags, our specification provides important flexibility in modeling network interactions. The estimation methodology builds, among others, on the two-step generalized method of moments estimation approach introduced in Kelejian and Prucha (1998, Journal of Real Estate Finance and Economics 17, 99–121; 1999, International Economic Review 40, 509–533; 2004, Journal of Econometrics 118, 27–50). The paper considers limited and full information estimators, and one- and two-step estimators, and establishes their asymptotic properties. In contrast to some of the earlier two-step estimation literature, our asymptotic results facilitate joint tests for the absence of all forms of network spillovers.

show abstract

Section: Parameterized Spatial Weightsmentioning

confidence: 99%

Simultaneous Equations Models With Higher-Order Spatial or Social Network Interactions

Drukker¹,

Egger²,

Prucha³

2022

Econom. Theory

View full text Add to dashboard Cite

show abstract

“…The setting of Su and Qu (2017) is a very special case of our framework. There has been recent interest in specification testing for spatial models (see, for example, Sun, 2020, for a kernelbased model specification test and Lee, Phillips, and Rossi, 2020, for a consistent omnibus test). We contribute to this literature by studying a linear process-based increasing parameter dimension framework.…”

Section: Introductionmentioning

confidence: 99%

Consistent Specification Testing Under Spatial Dependence

Gupta

2022

Econom. Theory

View full text Add to dashboard Cite

We propose a series-based nonparametric specification test for a regression function when data are spatially dependent, the “space” being of a general economic or social nature. Dependence can be parametric, parametric with increasing dimension, semiparametric or any combination thereof, thus covering a vast variety of settings. These include spatial error models of varying types and levels of complexity. Under a new smooth spatial dependence condition, our test statistic is asymptotically standard normal. To prove the latter property, we establish a central limit theorem for quadratic forms in linear processes in an increasing dimension setting. Finite sample performance is investigated in a simulation study, with a bootstrap method also justified and illustrated. Empirical examples illustrate the test with real-world data.

show abstract

“…There has been recent interest in specification testing for spatial models, see for example Lee, Phillips, and Rossi (2020) for a consistent omnibus test.…”

Section: Introductionmentioning

confidence: 99%

Consistent specification testing under spatial dependence

Gupta¹,

Qu²

2021

Preprint

View full text Add to dashboard Cite

We propose a series-based nonparametric specification test for a regression function when data are spatially dependent, the 'space' being of a general economic or social nature. Dependence can be parametric, parametric with increasing dimension, semiparametric or any combination thereof, thus covering a vast variety of settings.These include spatial error models of varying types and levels of complexity. Under a new smooth spatial dependence condition, our test statistic is asymptotically standard normal. To prove the latter property, we establish a central limit theorem for quadratic forms in linear processes in an increasing dimension setting. Finite sample performance is investigated in a simulation study and empirical examples illustrate the test with real-world data.

show abstract

Consistent Misspecification Testing in Spatial Autoregressive Models

Cited by 4 publications

References 30 publications

Simultaneous Equations Models With Higher-Order Spatial or Social Network Interactions

Simultaneous Equations Models With Higher-Order Spatial or Social Network Interactions

Consistent Specification Testing Under Spatial Dependence

Consistent specification testing under spatial dependence

Contact Info

Product

Resources

About