Spatial Autoregressive
A spatial autoregressive Poisson gravity model
... incorporates spatial dependence of the explained variable without relying on restrictive distribu- tional assumptions of the underlying data generating ...a spatial residual variable that captures origin- ...
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Comparison of the Sampling Efficiency in Spatial Autoregressive Model
... A random walk Metropolis-Hastings algorithm has been widely used in sampling the parameter of spatial interaction in spatial autoregressive model from a Bayesian point of view. In addition, as an ...
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Estimation and Inference in Functional Coefficient Spatial Autoregressive Panel Data Models with Fixed Effects
... which means that the derived estimator has the asymptotic bias and variance different from those of the pooled local linear estimator. Unfortunately, it is difficult to conclude which estimator is better due to the ...
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Semiparametric Estimation and Testing of Smooth Coefficient Spatial Autoregressive Models
... Further, we contribute to the literature by putting forward two test statistics to test for pa- rameter constancy in our model. These model specification tests allow us to discriminate between a standard linear ...
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Time trend in spatial dependence: Specification strategy in the first order spatial autoregressive model
... IDENTIFICATION OF SPATIAL DEPENDENCE STRUCTURE IN THE FIRST-ORDER SPATIAL AUTOREGRESSIVE MODEL The joint representation of the space-time Moran’s I coefficient STI in combination with th[r] ...
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First-Order Fractionally Integrated Non-Separable Spatial Autoregressive (FINSSAR(1,1)) Model and Some of its Properties
... separable spatial autoregressive (FISSAR) ...non-separable spatial autoregressive (FINSSAR) ...separable autoregressive (SSAR) ...
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Simulation and application of spatial autoregressive geographically weighted regression model (SAR GWR)
... on spatial data are not appropriate because of the characteristics of the spatial ...data. Spatial data has two characteristics are spatial dependence and spatial ...Modeling ...
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OLS Estimator for a Mixed Regressive, Spatial Autoregressive Model: Extended Version
... The possibility of a non-normal asymptotics leads to an important issue of the choice of the theoretical assumptions and format of the asymptotic expres- sion. Suppose that one researcher claims that under Set 1 of ...
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Asymptotic Distribution of the OLS Estimator for a Mixed Regressive, Spatial Autoregressive Model
... In this paper we develop further their method to apply to the general case (1.1). While doing this, we keep the number of conditions low and use only low-level assumptions. Note that when there are no spatial ...
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Essays on spatial autoregressive models with increasingly many parameters
... It has been noted that that autoregressive spectral estimation is also better at esti- mating peaked spectra, as compared to weighted/windowed periodogram estimation, see e.g. Ensor and Newton (1988). For lattice ...
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Testing for Spatial Correlations with Randomly Missing Observations in the Dependent Variable
... Abstract We consider LM tests for spatial correlations in the spatial error model SEM and spatial autoregressive model SAM with randomly missing data in the dependent variable.. We deriv[r] ...
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Spatial Dynamic Panel Model and System GMM: A Monte Carlo Investigation
... a spatial dynamic panel model with only exogenous ...the Spatial MLE, Spatial Dynamic MLE and ...that Spatial Dynamic MLE has the better overall performance in terms of bias reduction and root ...
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Cultural similarities and housing market linkage: evidence from OECD countries
... a spatial autoregressive model and impulse response function to estimate the speed and duration of spatial house price diffusion across the US from 1975 to ...notable spatial diffusion pattern ...
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Distinguishing Between Spatial Heterogeneity and Inefficiency: Spatial Stochastic Frontier Analysis of European Airports
... assumptions. Spatial proximity is rarely used in such models, which generally leads to lose of information in case the spatial structure plays a ...of spatial econometrics [13] allows including ...
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Spatial externalities and growth in a Mankiw Romer Weil world: Theory and evidence
... to spatial proximity and allow for ideas to flow to nearby regional ...of spatial autoregressive processes, the simple dependence on a small number of neighbouring regions leads to a reduced form ...
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Bayesian Inference in Spatial Sample Selection Models
... For an easy comparison of the point estimates from all algorithms, we provide the estimates of the posterior means in Figure 5. This figure also includes the estimates reported in Flores- Lagunes and Schnier, (2012) ...
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Efficiency of broadband internet adoption in European Union member states
... proposed spatial autoregressive stochastic frontier model is used for estimation of broadband adoption ...positive spatial effects also have been revealed, so higher broadband penetration rates in ...
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GMM estimation of Spatial Panels with Fixed Effects
... and spatial autoregressive (SAR) ...and spatial lags both in the dependent variable and in the disturbances, under homoskedastic errors, has been developed by Lee and Yu ...a spatial dynamic ...
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Spatial Random Slope Multilevel Modeling Using Multivariate Conditional Autoregressive Models: A Case Study of Subjective Travel Satisfaction in Beijing
... of spatial units might not be strictly ...chosen spatial units and the spatial scales at which certain social processes under exploration operate, spatial dependence tends to occur (Anselin ...
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Did the single market cause competition in excise taxes? Evidence from EU countries
... One problem in implementing (3) is that it is difficult to define ”neighbors” when a country is an island, or part of an island, or has no direct EU neighbors. These problems arise for three of the eight countries in our ...
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