Intercept Homogeneity Test for Fixed Effect Models Under Cross-Sectional Dependence: Some Insights

2015 ◽  
Author(s):  
Gopal K. Basak ◽  
Samarjit Das
Keyword(s):  
Fixed Effect ◽  
Homogeneity Test ◽  
Cross Sectional ◽  
Cross Sectional Dependence

Intercept Homogeneity Test for Fixed Effect Models under Cross-sectional Dependence: Some Insights

2017 ◽  
Vol 6 (1) ◽  
Author(s):  
Gopal K. Basak ◽  
Samarjit Das
Keyword(s):  
Fixed Effects ◽  
Random Effect ◽  
Error Component ◽  
Fixed Effect ◽  
Homogeneity Test ◽  
Cross Sectional ◽  
Cross Sectional Dependence ◽  
Component Models

AbstractThis paper develops a test for intercept homogeneity in fixed-effects one-way error component models assuming slope homogeneity. We show that the proposed test works equally well when intercepts are assumed to be either fixed (non-stochastic) or random. Moreover, this test can also be used to test for random effect vs. fixed effect although in the restrictive sense. The test is shown to be robust to cross-sectional dependence; for both

THE ENVIRONMENTAL KUZNETS CURVE FOR CARBON DIOXIDE EMISSIONS AND TRADE ON BELT AND ROAD INITIATIVE COUNTRIES: A SPATIAL PANEL DATA APPROACH

2019 ◽  
Vol 65 (04) ◽  
pp. 1099-1126 ◽  
Author(s):  
YASIR KHAN ◽  
QIU BIN
Keyword(s):  
Foreign Direct Investment ◽  
Carbon Emissions ◽  
Direct Investment ◽  
Homogeneity Test ◽  
Foreign Direct Investment Inflow ◽  
Belt And Road Initiative ◽  
Cross Sectional ◽  
Cross Sectional Dependence ◽  
Belt And Road ◽  
Spatial Panel Data

This paper empirically examines the nexus between CO2 emissions and international trade for the 65 Belt and Road Initiative (BRI) economies over the period of 1985–2017. We first consider the cross-sectional dependence and slope homogeneity test in the panel, and we observed from the results that there is substantial heterogeneity and cross-sectional dependence. We employed the results of the common correlated effects mean group (CCEMG) estimator and determined that for all 65 BRI economies, foreign direct investment inflow, gross domestic product (GDP) squared and urbanization had a positive and significant impact on carbon emissions (CO2). Moreover, this study found that foreign direct investment inflow led to an increase in carbon emissions in BRI countries across South Asia, Southeast Asia, East Asia and Europe. Finally, on the basis of the panel causality test, we found evidence of various causality associations among the selected variables across the regions. These findings are significant for the related policymakers in BRI countries, as they can assist in developing appropriate carbon emission, trade and energy policies with the goal of reducing carbon emissions.

scholarly journals Pengaruh Tingkat Edukasi dan Spesialisasi Pendidikan CEO terhadap Performa Perusahaan di Indonesia

2017 ◽  
Vol 16 (2) ◽  
pp. 177
Author(s):  
Kevin Wiyarta Erlim ◽  
Rita Juliana
Keyword(s):  
Firm Performance ◽  
Fixed Effect Model ◽  
Education Level ◽  
Fixed Effect ◽  
Decision Making Process ◽  
Managerial Decision ◽  
Cross Sectional ◽  
Effect Model ◽  
Cross Sectional Dependence ◽  
The Impact

Using sample of non financial Indonesia public licted firms over the period from 2005-2014, we analyze the impact of CEO education level education specialization on firm performance. Globalization has a lot of impact on professionals’ careers and thus it will affect the qualification that a CEO needed.  We believe that education level and CEO education specialization will affect the managerial decision making process and their strategy. This study is using panel data with fixed effect model methodology. We also did classic assumption test such as autocorrelation test, heteroscedasticity test and cross-sectional dependence test. Our analysis results that CEO education level does have impact on firm performance, and should be considered as an important aspect of a CEO.  Keywords: CEO Education Level; CEO Education Specialization; Fixed Effect Model; Firm Performance; TobinsQ

ANALISIS PENGARUH RASIO LIKUIDITAS, RASIO PROFITABILITAS, RASIO SOLVABILITAS DAN RASIO PASAR TERHADAP HARGA SAHAM PADA PERUSAHAAN YANG BERADA PADA INDEKS LQ45 DI BURSA EFEK INDONESIA

2016 ◽  
Vol 11 (02) ◽  
pp. 1-16
Author(s):  
Dilawatil Hikmah
Keyword(s):  
Fixed Effect Model ◽  
Fixed Effect ◽  
Cross Sectional ◽  
Effect Model

Penelitian ini dilakukan dengan tujuan untuk menguji pengaruh rasio likuiditas (CR), rasio profitabilitas (NPM, ROA, ROE, EPS), rasio solvabilitas (DER) dan rasio pasar (PER) terhadap harga saham (Y) pada perusahaan yang berada pada indeks LQ45 di Bursa Efek Indonesia. Metode pengumpulan data dilakukan dengan menggunakan laporan keuangan anggota emiten LQ45 periode Januari 2014 yang selama 5 tahun eksis dari Februari 2009 sampai Januari 2014. Metode sampel yang digunakan adalah purpose sampling (sampling bersyarat). Adapun jumlah sampel yang terpilih memenuhi syarat sebanyak 21 emiten dari 45 emiten. Teknis analisis data menggunakan Eviews 7.1 yaitu dengan metode cross sectional weight dengan pendekatan fixed effect model. Hasil penelitian menunjukkan bahwa secara bersama-sama maupun secara parsial variabel CR, NPM, ROA, ROE, EPS, DER, dan PER memiliki pengaruh terhadap harga saham. Namun variabel yang berpengaruh signifikan terhadap harga saham adalah NPM dan PER. Maka para investor dapat menilai kinerja perusahaan dengan melihat dari rasio keuangan dan melakukan penilaian terhadap harga saham sehingga dengan mudah dapat menentukan saham yang baik sebelum berinvestasi di BEI.

Extent Pursuit for Cross-Sectional Dependence in Large Panels

2019 ◽  
Author(s):  
Jiti Gao ◽  
Guangming Pan ◽  
Yanrong Yang ◽  
Bo Zhang
Keyword(s):  
Cross Sectional ◽  
Large Panels ◽  
Cross Sectional Dependence

Nonparametric panel data regression with parametric cross-sectional dependence

2021 ◽  
Author(s):  
Alexandra Soberon ◽  
Juan M Rodriguez-Poo ◽  
Peter M Robinson
Keyword(s):  
Panel Data ◽  
Monte Carlo Study ◽  
Generalized Least Squares ◽  
Linear Estimator ◽  
Dependence Structure ◽  
Finite Sample ◽  
Cross Sectional ◽  
Panel Data Regression ◽  
Local Linear Estimator ◽  
Cross Sectional Dependence

Abstract In this paper, we consider efficiency improvement in a nonparametric panel data model with cross-sectional dependence. A Generalized Least Squares (GLS)-type estimator is proposed by taking into account this dependence structure. Parameterizing the cross-sectional dependence, a local linear estimator is shown to be dominated by this type of GLS estimator. Also, possible gains in terms of rate of convergence are studied. Asymptotically optimal bandwidth choice is justified. To assess the finite sample performance of the proposed estimators, a Monte Carlo study is carried out. Further, some empirical applications are conducted with the aim of analyzing the implications of the European Monetary Union for its member countries.

What Goes Up Might Not Come Down: Modeling Directional Asymmetry with Large-N, Large-T Data

2021 ◽  
pp. 008117502110463
Author(s):  
Ryan P. Thombs ◽  
Xiaorui Huang ◽  
Jared Berry Fitzgerald
Keyword(s):  
Fixed Effects ◽  
Directional Asymmetry ◽  
Cross Sectional ◽  
Monte Carlo Experiments ◽  
Long Run ◽  
Large N ◽  
Fixed Effects Estimator ◽  
Cross Sectional Dependence ◽  
Using Data ◽  
Heterogeneous Panel

Modeling asymmetric relationships is an emerging subject of interest among sociologists. York and Light advanced a method to estimate asymmetric models with panel data, which was further developed by Allison. However, little attention has been given to the large- N, large- T case, wherein autoregression, slope heterogeneity, and cross-sectional dependence are important issues to consider. The authors fill this gap by conducting Monte Carlo experiments comparing the bias and power of the fixed-effects estimator to a set of heterogeneous panel estimators. The authors find that dynamic misspecification can produce substantial biases in the coefficients. Furthermore, even when the dynamics are correctly specified, the fixed-effects estimator will produce inconsistent and unstable estimates of the long-run effects in the presence of slope heterogeneity. The authors demonstrate these findings by testing for directional asymmetry in the economic development–CO2 emissions relationship, a key question in macro sociology, using data for 66 countries from 1971 to 2015. The authors conclude with a set of methodological recommendations on modeling directional asymmetry.

Detecting common breaks in the means of high dimensional cross-dependent panels

2021 ◽  
Author(s):  
Lajos Horváth ◽  
Zhenya Liu ◽  
Gregory Rice ◽  
Yuqian Zhao
Keyword(s):  
Panel Data ◽  
Common Factors ◽  
Real Data ◽  
Change Points ◽  
High Dimensional ◽  
Asymptotic Results ◽  
Cross Sectional ◽  
Data Set ◽  
Monte Carlo Simulation Study ◽  
Cross Sectional Dependence

Abstract The problem of detecting change points in the mean of high dimensional panel data with potentially strong cross–sectional dependence is considered. Under the assumption that the cross–sectional dependence is captured by an unknown number of common factors, a new CUSUM type statistic is proposed. We derive its asymptotic properties under three scenarios depending on to what extent the common factors are asymptotically dominant. With panel data consisting of N cross sectional time series of length T, the asymptotic results hold under the mild assumption that min {N, T} → ∞, with an otherwise arbitrary relationship between N and T, allowing the results to apply to most panel data examples. Bootstrap procedures are proposed to approximate the sampling distribution of the test statistics. A Monte Carlo simulation study showed that our test outperforms several other existing tests in finite samples in a number of cases, particularly when N is much larger than T. The practical application of the proposed results are demonstrated with real data applications to detecting and estimating change points in the high dimensional FRED-MD macroeconomic data set.

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