scholarly journals Analiza zróżnicowania sytuacji kobiet na lokalnych rynkach pracy w Polsce w latach 2010–2016

2019 ◽  
Vol 2 (341) ◽  
pp. 99-115
Author(s):  
Karolina Lewandowska‑Gwarda
Keyword(s):  
Seemingly Unrelated Regression ◽  
Spatial Lag ◽  
Spatial Lag Model ◽  
Unrelated Regression ◽  
Lag Model

Głównym celem artykułu jest ocena sytuacji kobiet na lokalnych rynkach pracy w Polsce oraz analiza jej zróżnicowania w czasie i przestrzeni. Podjęto w nim również próbę specyfikacji determinant badanego zjawiska. W analizach wykorzystano taksonomiczny miernik rozwoju, metody geograficznych systemów informacyjnych, metody eksploracyjnej analizy danych przestrzennych oraz wielorównaniowy model o równaniach pozornie niezależnych z autoregresją przestrzenną SUR‑SLM (Seemingly Unrelated Regression Spatial Lag Model). Badania przeprowadzono na podstawie danych statystycznych dla NUTS4 w latach 2010, 2012, 2014 i 2016. Na podstawie uzyskanych wyników zauważono, że zróżnicowanie sytuacji kobiet na lokalnych rynkach pracy w Polsce nie jest duże, niemniej jednak w nieco lepszej sytuacji są Polki mieszkające w okolicach stolicy oraz w zachodniej części kraju. Stwierdzono również, że sytuacja kobiet na lokalnych rynkach pracy nie zmieniła się znacząco w czasie. Dodatkowo potwierdzono, że nie tylko czynniki ekonomiczne, ale w dużej mierze również społeczne wpływają na analizowane zjawisko.

scholarly journals Bayesian Estimation of the Functional Spatial Lag Model

2020 ◽  
Vol 12 (2) ◽  
Author(s):  
Alassane Aw ◽  
Emmanuel Nicolas Cabral
Keyword(s):  
Bayesian Estimation ◽  
Linear Model ◽  
Unemployment Rate ◽  
Simulation Study ◽  
Data Modeling ◽  
Functional Linear Model ◽  
Bayesian Mcmc ◽  
Spatial Lag ◽  
Spatial Lag Model ◽  
Lag Model

AbstractThe spatial lag model (SLM) has been widely studied in the literature for spatialised data modeling in various disciplines such as geography, economics, demography, regional sciences, etc. This is an extension of the classical linear model that takes into account the proximity of spatial units in modeling. In this paper, we propose a Bayesian estimation of the functional spatial lag (FSLM) model. The Bayesian MCMC technique is used as a method of estimation for the parameters of the model. A simulation study is conducted in order to compare the results of the Bayesian functional spatial lag model with the functional spatial lag model and the functional linear model. As an illustration, the proposed Bayesian functional spatial lag model is used to establish a relationship between the unemployment rate and the curves of illiteracy rate observed in the 45 departments of Senegal.

Spatial Aspects of Mortality Rates and Neighborhood Environmental Characteristics in Seoul Mega City Region, South Korea

2015 ◽  
Vol 6 (4) ◽  
pp. 44-64
Author(s):  
Yoohyung Joo ◽  
Hee Yeon Lee
Keyword(s):  
Spatial Patterns ◽  
Statistical Significance ◽  
Mortality Rates ◽  
Spatial Disparity ◽  
City Region ◽  
Spatial Lag ◽  
Spatial Lag Model ◽  
Spatial Aspect ◽  
Lag Model ◽  
Gwr Model

This study of the spatial patterns of standardized mortality rates (SMRs) in Seoul Mega City Region (SMCR) explores whether neighborhood characteristics affect mortality rates and identifies important determinants of spatial disparity in mortality rates in SMCR. Spatial patterns of mortality rates show a strong positive spatial autocorrelation, suggesting that mortality rates are spatially clustered. A spatial lag model and a GWR model were used to reflect the spatial aspect of mortality rates. The spatial lag model showed better model fitness by considering spatial dependence of mortality rates. It indicates that a higher level of residential deprivation, a less walkable environment, less economic affluence and less social participation are all associated with higher mortality rates with statistical significance. This study suggests that health and welfare policy could incorporate urban planning to consider the neighborhood factors which determine mortality rates in order to improve the health of neighborhood residents.

scholarly journals NONTESTABILITY OF EQUAL WEIGHTS SPATIAL DEPENDENCE

2011 ◽  
Vol 27 (6) ◽  
pp. 1369-1375 ◽  
Author(s):  
Federico Martellosio
Keyword(s):  
Spatial Autocorrelation ◽  
Parameter Space ◽  
Spatial Dependence ◽  
Elliptical Distribution ◽  
Spatial Error ◽  
Spatial Lag ◽  
Spatial Lag Model ◽  
Lag Model ◽  
Invariant Test

We show that any invariant test for spatial autocorrelation in a spatial error or spatial lag model with equal weights matrix has power equal to size. This result holds under the assumption of an elliptical distribution. Under Gaussianity, we also show that any test whose power is larger than its size for at least one point in the parameter space must be biased.

Spatial autoregressive analysis of nationwide street network patterns with global open data

2021 ◽  
pp. 239980832098784
Author(s):  
Qi Zhou ◽  
Hao Lin ◽  
Junya Bao
Keyword(s):  
Open Data ◽  
Ordinary Least Squares ◽  
Street Network ◽  
Spatial Error ◽  
Spatial Lag ◽  
Spatial Lag Model ◽  
Physical Form ◽  
Lag Model ◽  
Spatial Autoregressive ◽  
Network Patterns

The study of street network patterns is beneficial in understanding the layout or physical form of a city. Many studies have analyzed street network patterns, but the similarity and/or difference of street network patterns across a country or region are rarely quantitatively understood. To fill this gap, this research proposes a quantitative analysis of street network patterns nationwide. Specifically, the street network patterns across a country or region were first mapped, and then the relationship between such patterns and various landscape factors (calculated based on global open data) was quantitatively investigated by employing three regression models (ordinary least squares, spatial lag model, and spatial error model). Not only the whole region of China but also its subregions were used as study areas, which involved a total of 362 prefecture-level cities and 2081 built-up areas for analysis. Results showed that (1) similar street network patterns are spatially aggregated; (2) a number of factors, including both land-cover and terrain factors, are found to be significantly correlated with street network patterns; and (3) the spatial lag model is preferred in most of the application scenarios. Not only the analytical method and data can be applied to other countries and regions but also these findings are useful for understanding street network patterns and their associated urban forms in a country or region.

scholarly journals Determination of hedonic hotel room prices with spatial effect in Antalya

2018 ◽  
Author(s):  
Fusun Yalcin
Keyword(s):  
Spatial Effect ◽  
Spatial Lag ◽  
Hotel Room ◽  
Spatial Lag Model ◽  
Lag Model

El propósito de este estudio es identificar los factores que afectan el precio de la habitación hotelera en Antalya y crear un modelo de regresión hedónica. Para este propósito, se han seleccionado 1444 hoteles en Antalya. Puesto que estos hoteles están relacionados espacialmente, se ha propuesto un modelo de regresión espacial. Se aplicó la regresión paso a paso (stepwise) a las variables del análisis espacial. El modelo de regresión hedónica se ha construido según el modelo Lag o de retardo espacial (Spatial Lag Model), revelando que es posible utilizar dicho método en estudios similares.

scholarly journals Estimation of Spatial Lag Model Under Random Missing Data in the Dependent Variable. Two Stage Estimator with Imputation

Economía ◽  
2021 ◽  
Vol 44 (87) ◽  
pp. 1-19
Author(s):  
Alejandro Izaguirre
Keyword(s):  
Monte Carlo Simulation ◽  
Missing Data ◽  
Two Stage ◽  
Spatial Lag ◽  
The Third ◽  
Finite Samples ◽  
Spatial Lag Model ◽  
Alternative Version ◽  
Lag Model ◽  
Data Context

The main goal of this article is to propose estimators for the Spatial Lag Model (SLM) under missing data context. We present three alternatives estimators for the SLM based on Two Stage Least Squares estimation methodology. The estimators are eÿcient within their type and consistent under random missing data in the dependent variable. Unlike the IBG2SLS estimator presented in Wang and Lee (2013) which impute all missing data we only impute missing data in the spatial lag. Our first proposal is an alternative version of the IBG2SLS estimator, the second one is based on an approximation to the optimal instruments matrix and the third one is an alternative equivalent to the first. Thorough a Monte Carlo simulation we assess the estimators performance under finite samples. Results show a good performance for all estimators, moreover, results are quite similar to the IBG2SLS estimator suggesting that a complete imputation (as IBG2SLS does) does not add information.

scholarly journals Speed Limit Changes and Driver Behaviour: A Spatial Lag Model

Findings ◽  
2020 ◽  
Author(s):  
Catherine Toulouse ◽  
Saeid Amiri ◽  
Marie-Soleil Cloutier ◽  
Nicolas Saunier
Keyword(s):  
Speed Limit ◽  
Driver Behaviour ◽  
Spatial Lag ◽  
Spatial Lag Model ◽  
Lag Model
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