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

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.

Impact of Financial Risks on the Profitability of Systematically Important Banks in Nigeria

Paradigm ◽  
2019 ◽  
Vol 23 (2) ◽  
pp. 117-129
Author(s):  
Olufemi Adewale Aluko ◽  
Funso Tajudeen Kolapo ◽  
Patrick Olufemi Adeyeye ◽  
Patrick Olajide Oladele
Keyword(s):  
Interest Rate ◽  
Fixed Effects ◽  
Positive Impact ◽  
Financial Risks ◽  
Cross Sectional ◽  
Bank Profitability ◽  
Alternative Measures ◽  
Cross Sectional Dependence ◽  
Fixed Effects Regression ◽  
The Impact

This study examines the impact of financial risks in form of credit, interest rate and liquidity risk on the profitability of systematically important banks in Nigeria over the period from 2010 to 2016. The fixed effects regression model is estimated with Driscoll–Kraay standard errors in order to produce results that are robust to heteroscedaticity, autocorrelation, cross-sectional dependence and temporal dependence. After controlling for some bank-specific, industry-specific, macroeconomic and institutional factors, the empirical results show that credit and liquidity risks have a positive impact on bank profitability while interest rate does not have an impact. The results are robust to alternative measures of profitability.

scholarly journals Dam effect confirmation on weaning weight of Boer Goat crosses in Indonesia

2021 ◽  
Vol 902 (1) ◽  
pp. 012001
Author(s):  
T Nugroho ◽  
A Nurhidayati ◽  
N Widyas ◽  
S Prastowo
Keyword(s):  
Fixed Effects ◽  
Mixed Model ◽  
Random Effect ◽  
Fixed Effect ◽  
Weaning Weight ◽  
Boer Goat ◽  
Significant Difference ◽  
Weight Trait ◽  
Observation Results ◽  
Birth Type

Abstract This study aimed to confirm the present of dam effect on weaning weight trait of Boer goat crosses. A total of 1081 weaning weight records (standardized to 77 days) from 527 does and 16 bucks were analyzed. Data were derived from Boer, Boerja F1 (Boer 3 × Jawarandu ?), and Boerja F2 (Boer 3 × Boerja F1 ?). Two statistic models namely Model 1 and Model 2 were compared using F-test for overall significance. Model 1 is Analysis of Variance (ANOVA) which consist only fixed effect as factor, while Model 2 is mixed model which includes fixed effect as factor and dam as a random effect. The fixed effects in both models are buck, doe type, parity of the dam, sex of kid, birth type, and year of observation. Results showed that buck, doe type, sex, birth type, and observation year affect significantly (P<0.05) to weaning weight, while parity had no effect (P=0.53). Based on the model’s comparison, there was a significant difference (P<0.05) between Model 1 and Model 2. Therefore, it is confirmed the present of dam effect on the weaning weight trait of Boer goat crosses in the studied population.

scholarly journals Pengaruh PDRB, Upah Minimum Provinsi, dan Angkatan Kerja Terhadap Investasi Asing Langsung di Indonesia Tahun 2013-2016

2019 ◽  
Vol 4 (2) ◽  
pp. 101-109
Author(s):  
Siti Utma ◽  
◽  
Arif Rakhman
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Fixed Effects ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Fixed Effects Model ◽  
Common Effect ◽  
Effect Model

Penelitian ini bertujuan menganalisis pengaruh produk domestik regional bruto (PDRB), upah minimum provinsi (UMP), dan angkatan kerja terhadap investasi asing langsung di Indonesia tahun 2013 – 2016. Data yang digunakan dalam penelitian ini adalah data panel yang merupakan gabungan data provinsi sebagai cross section dan tahun 2013 – 2016 sebagai time series. Investasi asing langsung merupakan variabel dependen, sedangkan variabel Independen yang digunakan adalah produk domestik regional bruto (PDRB), upah minimum provinsi (UMP), dan angkatan kerja. Metode penelitian menggunakan analisis regresi dengan tiga model yaitu common effect model, fixed effect model, dan random effect model. Dari tiga model tersebut, fixed Effects Model (FEM) terpilih sebagai model regresi data panel yang paling tepat. Hasil regresi produk domestik regional bruto (PDRB) berpengaruh positif signifikan terhadap investasi asing langsung. Hal ini berarti setiap kenaikan produk domestik regional bruto (PDRB) akan menaikkan investasi asing langsung di Indonesia. Adapun variabel upah minimum provinsi (UMP) dan Angkatan Kerja, tidak berpengaruh signifikan terhadap investasi asing langsung di Indonesia tahun 2013 – 2016.

An empirical approach to understanding the lower-middle and upper-middle income traps

2019 ◽  
Vol 18 (2) ◽  
pp. 171-190
Author(s):  
M. Adnan Kabir ◽  
Ashraf Ahmed
Keyword(s):  
Income Inequality ◽  
Random Effect ◽  
Exchange Rate Volatility ◽  
Growth Dynamics ◽  
Fixed Effect ◽  
Cross Sectional ◽  
Middle Income ◽  
Content Type ◽  
Income Groups ◽  
Middle Income Trap

Purpose The purpose of this paper is to investigate the factors that are significant in contributing to the per capita income growth of countries that are experiencing or have experienced the lower-middle and upper-middle income traps. Design/methodology/approach The study comprises 85 countries over the period 1960 to 2017 spanning across three income groups: lower-middle, upper-middle and high. A panel data structure was used to run a fixed effect and random effect estimation on three models of income groups. The Hausman specification test, which was used for further statistical fitness, confirmed the appropriateness of fixed effect over the random in explaining the estimation of factor variables. Findings The results show that unemployment is a pervasive problem that negatively affect countries at all income levels. Foreign direct investment and population of dependents are associated with economic progression of countries that have experienced or are experiencing the lower-middle income trap. Furthermore, rising income inequality and foreign aid assistance are detrimental to countries that have experienced or are experiencing the upper-middle income trap. Moreover, income inequality, disproportionate urban population and rising dependent population are damaging for high income countries that never experienced any of the middle-income traps. Conversely, openness to trade, inflation and exchange rate volatility had limited capacity in explaining growth dynamics. Research limitations/implications This study could not incorporate geopolitical, demographic, geographical and other such exogenous factors, which could have episodes of influences on the economic development of countries. These were outside the study's realm of quantitative analysis. Originality/value This paper contributes to existing literature by providing an empirical cross-sectional comparative analysis of countries belonging to different income groups. The prevailing literature lacks such a cross-tabulated presentation of factors affecting countries that avoided the middle income trap and those that could not.

Changing BMI scores among Canadian Indigenous and non-Indigenous children, youth, and young adults: Untangling age, period, and cohort effects

2017 ◽  
Vol 44 (1-2) ◽  
pp. 28 ◽  
Author(s):  
Piotr Wilk ◽  
Alana Maltby ◽  
Martin Cooke
Keyword(s):  
Fixed Effects ◽  
Random Effect ◽  
Indigenous Populations ◽  
Cohort Effects ◽  
Quadratic Term ◽  
Birth Cohorts ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Level 1 ◽  
Effets Aléatoires

The objective of this study was to examine age, period and cohort effects on BMI among Indigenous and non-Indigenous populations, using repeated cross-sectional survey data from the CCHS (2001 to 2014). Cross-classified random-effect two-level models were used to estimate fixed effects for age and its quadratic term (Level 1), and also to estimate random effects for time periods and birth cohorts (Level 2), while controlling for the effects of Level 1 control variables: sex, model of interview and response by proxy. Overall, the results support the hypothesis that age and period effects are primarily responsible for the current obesity epidemic.L’objectif de cette étude était d’examiner les effets de l’âge, de la période et de la cohorte sur l’IMC chez les populations autochtones et non autochtones, en utilisant des données d’enquêtes transversales répétées de l’ESCC (2001 à 2014). On a utilisé des modèles à deux niveaux à effets aléatoires croisés pour estimer les effets fixes pour l’âge et son terme quadratique (niveau 1), et également estimer les effets aléatoires pour les périodes et les cohortes de naissance (niveau 2), tout en contrôlant les effets du niveau 1 Variables de contrôle: sexe, modèle d’interview et réponse par procuration. Dans l’ensemble, les résultats confirment l’hypothèse selon laquelle les effets de l’âge et de la période sont les principaux responsables de l’épidémie actuelle d’obésité.

scholarly journals Network dependence in multi-indexed data on international trade flows

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Manfred M. Fischer ◽  
James P. LeSage
Keyword(s):  
Monte Carlo ◽  
Fixed Effects ◽  
Spillover Effects ◽  
Trade Flows ◽  
Monte Carlo Integration ◽  
Estimation Methods ◽  
Cross Sectional ◽  
Network Interaction ◽  
Cross Sectional Dependence ◽  
Network Dependence

AbstractFaced with the problem that conventional multidimensional fixed effects models only focus on unobserved heterogeneity, but ignore any potential cross-sectional dependence due to network interactions, we introduce a model of trade flows between countries over time that allows for network dependence in flows, based on sociocultural connectivity structures. We show that conventional multidimensional fixed effects model specifications exhibit cross-sectional dependence between countries that should be modeled to avoid simultaneity bias. Given that the source of network interaction is unknown, we propose a panel gravity model that examines multiple network interaction structures, using Bayesian model probabilities to determine those most consistent with the sample data. This is accomplished with the use of computationally efficient Markov Chain Monte Carlo estimation methods that produce a Monte Carlo integration estimate of the log-marginal likelihood that can be used for model comparison. Application of the model to a panel of trade flows points to network spillover effects, suggesting the presence of network dependence and biased estimates from conventional trade flow specifications. The most important sources of network dependence were found to be membership in trade organizations, historical colonial ties, common currency, and spatial proximity of countries.

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