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Since 1980, land subsidence has accelerated and groundwater levels have decreased in the centre of Shanghai, although the net withdrawn volume of groundwater has not increased. Theoretical analysis of the monitored data shows that the decrease in the groundwater level is the primary reason for...
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The quaternary deposit of Shanghai is composed of an alternated multi-aquifer-aquitard system (MAAS) consisting of a sequence of aquitards laid over aquifers one by one. In the MAAS, any drawdown of groundwater head in an aquifer may cause consolidation of the overburden aquitard. When...
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This paper studies the generalized spatial two stage least squares (GS2SLS) estimation of spatial autoregressive models with autoregressive disturbances when there are endogenous regressors with many valid instruments. Using many instruments may improve the efficiency of estimators...
Persistent link: https://www.econbiz.de/10010421298
An information matrix of a parametric model being singular at a certain true value of a parameter vector is irregular. The maximum likelihood estimator in the irregular case usually has a rate of convergence slower than the Ín-rate in a regular case. We propose to estimate such models by the...
Persistent link: https://www.econbiz.de/10011995209
This paper is concerned with the use of the bootstrap for statistics in spatial econometric models, with a focus on the test statistic for Moran’s I test for spatial dependence. We show that, for many statistics in spatial econometric models, the bootstrap can be studied based on...
Persistent link: https://www.econbiz.de/10011117413
This paper studies large sample properties of the matrix exponential spatial specification (MESS). We find that the quasi-maximum likelihood estimator (QMLE) for the MESS is consistent under heteroskedasticity, a property not shared by the QMLE of the SAR model. For the general model that has...
Persistent link: https://www.econbiz.de/10010930191
This paper studies large sample properties of the matrix exponential spatial specification (MESS). We find that the quasi-maximum likelihood estimator (QMLE) for the MESS is consistent under heteroskedasticity, a property not shared by the QMLE of the SAR model. For the general model that has...
Persistent link: https://www.econbiz.de/10010935045
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