scholarly journals Validity of Okun’s Law in a spatially dependent and cyclical asymmetric context

2021 ◽  
pp. 3-3
Author(s):  
Hasan Duran
Keyword(s):  
Spatial Dependence ◽  
Spatial Association ◽  
Panel Cointegration ◽  
Spatial Proximity ◽  
Panel Unit Root Tests ◽  
Specification Tests ◽  
Spatial Panel ◽  
Panel Regressions ◽  
Asymmetric Cycle ◽  
Current Article

The current article analyzes the validity of Okun?s Law and sizable distortions that can occur in the estimation when spatial dependence and cyclical asymmetric impacts are not considered, which is a concern commonly ignored by the existing literature. Primarily spatial panel regressions (SDM, SAR, and SEM) and nonparametric regressions along with specification tests are adopted in terms of the methodology (such as panel unit root tests, panel cointegration, Moran?s I and Geary?s C tests of global spatial dependence, spatial LM, and Hausman tests). Additionally, spatial heterogeneity and cross-regional variation in Okun?s Law are investigated by adopting geographically weighted regression, LISA (local indicators for spatial association), and local Geary?s C analysis. A panel of 26 Turkish NUTS-2 regions from 2004 to 2018 was analyzed. The results clearly revealed that failing to incorporate spatial proximity and asymmetric cycle impacts leads to the biased estimation of Okun?s coefficient, such that during the downswing years of the national economy, Okun?s Law holds robustly: unemployment increases quickly in response to a decline in output. In contrast, during upswing years, the size of Okun?s coefficient is relatively much lower. Moreover, spatial dependence and heterogeneity are sizably evident. Okun?s coefficient is demonstrated to vary significantly across regions that have different industrial and labor market characteristics. As a policy implication, it has been understood that the reduction of unemployment is more difficult than initially understood, as economic growth itself does not provide a solution during upswing periods. The necessary special and region-specific policies are discussed throughout the text.

Evaluation on Methods of Spatial Dependence Test

2013 ◽  
Vol 397-400 ◽  
pp. 675-678
Author(s):  
Tong Xian Ren ◽  
Lu Mei Yang
Keyword(s):  
Data Model ◽  
Spatial Dependence ◽  
Wald Test ◽  
Spatial Panel ◽  
Section Data ◽  
Lm Test ◽  
Post Test ◽  
Spatial Panel Data ◽  
Lr Test ◽  
Spatial Section

Methods of spatial dependence test are divided into prior-test and post-test in this paper. Prior-test main includes Moran's I test, the joint LM test, the maximum likelihood LM test, robust LM test, etc. Post-test main includes conditions LM test, LR test, Wald test etc. Research on methods of spatial dependence are evaluated in this paper. It pointed out that methods of spatial dependence test are mainly based on spatial section data model. The research on spatial dependence test of the spatial panel data model needs to be deepened.

scholarly journals Building W Matrices Using Selected Geostatistical Tools: Empirical Examination and Application

Stats ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 112-133 ◽  
Author(s):  
Elżbieta Antczak
Keyword(s):  
Spatial Data ◽  
Spatial Dependence ◽  
Regression Models ◽  
Seemingly Unrelated Regression ◽  
Spatial Data Analysis ◽  
Spatial Dependency ◽  
Empirical Examination ◽  
Spatial Panel ◽  
Spatial Weights ◽  
Unrelated Regression

This paper investigates how to determine the values (elements) of spatial weights in a spatial matrix (W) endogenously from the data. To achieve this goal, geostatistical tools (standard deviation ellipsis, semivariograms, semivariogram clouds, and surface trend models) were used. Then, in the econometric part of the analysis, the effect of applying different variants of matrices was examined. The study was conducted on a sample of 279 Polish towns from 2005–2015. Variables were related to the quantity of produced waste and economic development. Both exploratory spatial data analysis and estimations of spatial panel and seemingly unrelated regression models were performed by including particular W matrices in the study (exogenous-random as well as distance and directional matrices constructed based on data). The results indicated that (1) geostatistical tools can be effectively used to build Ws; (2) outcomes of applying different matrices did not exclude but supplemented one another, although the differences were significant; (3) the most precise picture of spatial dependence was achieved by including distance matrices; and (4) the values of the assessed parameter at the regressors did not significantly change, although there was a change in the strength of the spatial dependency.

scholarly journals Panel unit root tests and spatial dependence

2007 ◽  
Vol 22 (2) ◽  
pp. 339-360 ◽  
Author(s):  
Badi H. Baltagi ◽  
Georges Bresson ◽  
Alain Pirotte
Keyword(s):  
Unit Root ◽  
Spatial Dependence ◽  
Unit Root Tests ◽  
Panel Unit Root Tests ◽  
Panel Unit Root

scholarly journals Investment and Saving Nexus in Asian Countries: Panel Cointegration and Causality

2013 ◽  
Vol 18 ◽  
pp. 1-7 ◽  
Author(s):  
Mohsen Mehrara ◽  
Maysam Musai
Keyword(s):  
Unit Root ◽  
Panel Cointegration ◽  
Cointegration Analysis ◽  
Unit Root Tests ◽  
Domestic Investment ◽  
Panel Unit Root Tests ◽  
Asian Countries ◽  
Panel Unit Root ◽  
Long Run ◽  
Saving Rates

This paper investigates the causal relationship between gross domestic investment (INV) and saving rates for 40 Asian countries by using panel unit root tests and panel cointegration analysis for the period 1970-2010. The results indicate no long run relationship as well as no causalities between these two variables in these countries. The findings are attributed to non stationary deficits or surpluses in current accounts.

scholarly journals Overlooked runaway feedback in the marine nitrogen cycle: the vicious cycle

2012 ◽  
Vol 9 (7) ◽  
pp. 8905-8930
Author(s):  
A. Landolfi ◽  
H. Dietze ◽  
W. Koeve ◽  
A. Oschlies
Keyword(s):  
Ocean Circulation ◽  
Nitrogen Loss ◽  
Spatial Association ◽  
Circulation Model ◽  
Spatial Proximity ◽  
N Losses ◽  
Sources And Sinks ◽  
Close Spatial Proximity ◽  
Individual Rate ◽  
Apparent Stability

Abstract. The marine nitrogen (N) inventory is controlled by the interplay of nitrogen loss processes, here referred to as denitrification, and nitrogen source processes, primarily nitrogen fixation. The apparent stability of the marine N inventory on time scales longer than the estimated N residence time, suggests some intimate balance between N sinks and sources. Such a balance may be perceived easier to achieve when N sinks and sources occur in close spatial proximity, and some studies have interpreted observational evidence for such a proximity as indication for a stabilizing feedback processes. Using a biogeochemical ocean circulation model, we here show instead that a close spatial association of N2 fixation and denitrification can, in fact, trigger destabilizing feedbacks on the N inventory and, because of stoichiometric constrains, lead to net N losses. Contrary to current notion, a balanced N inventory requires a regional separation of N sources and sinks. This can be brought about by factors that reduce the growth of diazotrophs, such as iron, or by factors that affect the fate of the fixed nitrogen remineralization, such as dissolved organic matter dynamics. In light of our findings we suggest that spatial arrangements of N sinks and sources have to be accounted for in addition to individual rate estimates for reconstructing past, evaluating present and predicting future marine N inventory imbalances.

scholarly journals A Dynamic Spatial Panel of Subnational GHG Emissions: Environmental Effectiveness of Emissions Taxes in Spanish Regions

2020 ◽  
Vol 12 (7) ◽  
pp. 2872 ◽  
Author(s):  
Jaime Vallés-Giménez ◽  
Anabel Zárate-Marco
Keyword(s):  
Spatial Dependence ◽  
Ghg Emissions ◽  
Regional Level ◽  
Environmental Taxes ◽  
Spatial Panel ◽  
Spanish Regions ◽  
Environmental Effectiveness ◽  
Emissions Taxes ◽  
Temporal Persistence ◽  
Spatio Temporal

In this paper we study the effectiveness of environmental taxes and policies of the regional level of government to reduce GHG emissions. We use panel data for the 17 Spanish regions in the period 1999–2017, controlling the spatial nexus between regions and using a dynamic Durbin model. The results show there is spatial dependence and spatio-temporal persistence of GHG emissions at the regional level in Spain, and that in this context, the taxes and policies intended to manage emissions introduce a slight disincentive to generating them. This fact, together with some relative decoupling which seems to exist between growth and emissions at the regional level, would suggest the need for tougher measures to combat environmental pollution in order to meet EU commitments.

The Residential Solar PV in the Mid-Atlantic: A Spatial Panel Approach

2020 ◽  
pp. 016001762091406
Author(s):  
Oleg Kucher ◽  
Donald Lacombe ◽  
Sean T. Davidson
Keyword(s):  
Spatial Dependence ◽  
County Level ◽  
Solar Photovoltaic ◽  
Coefficient Estimate ◽  
Solar Pv ◽  
Spatial Panel ◽  
Electricity Rates ◽  
Panel Model ◽  
Percent Increase ◽  
Panel Estimates

This study examines residential solar photovoltaic (PV) adoption in mid-Atlantic counties over the 2005–2016 period. Using a spatial Durbin panel model, we find significant spatial dependence in residential solar PV adoption at the county level. In the presence of spatial dependence, major determinants of the solar adoptions are electricity rates and solar-related policy regulation. The combined direct and indirect effect of electricity rates on solar PV capacity is 5.37 percent increase for a 1 percent increase in electricity price. This spatial coefficient estimate is about twice as large as corresponding panel estimates. We also find that the regulation and incentives significantly boost solar PV demand, which explains about 38 percent variation in residential solar capacity.

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