scholarly journals Relationship of Foreign Trade and Economic Growth in Eurasian Economy: Panel Data Analysis

2017 ◽  
Vol 9 (9) ◽  
pp. 1 ◽  
Author(s):  
Nazife Özge Kilic ◽  
Murat Beser
Keyword(s):  
Economic Growth ◽  
Data Analysis ◽  
Panel Data ◽  
Foreign Trade ◽  
Panel Data Analysis ◽  
Homogeneity Test ◽  
Causality Test ◽  
Cross Sectional ◽  
Using Data ◽  
Relationship Of

In this study, relationship between foreign trade and economic growth had been examined for the countries of Eurasia Economic Union by using data in era of 1992-2015 with the help of panel data analysis. First of all, cross-sectional dependency and homogeneity test had been done in the study and it had been concluded that there is cross-sectional dependency in between the series. For this purpose, unit root and causality test considering the cross-sectional dependency had been applied. Relationship between the variables had been analyzed with the panel causality test developed by Konya (2006). It had been determined that there is bi-directional causality from growth to export and unidirectional causality from growth to import.

scholarly journals Panel Data Analysis on Technology Transfer and Economic Growth: The Case of Eurasian Economies

2020 ◽  
Author(s):  
Tuğçe Acar ◽  
İsmail Erkan Çelik
Keyword(s):  
Economic Growth ◽  
Data Analysis ◽  
Technology Transfer ◽  
Panel Data ◽  
Causal Relationship ◽  
Current Account ◽  
Direct Investment ◽  
Panel Data Analysis ◽  
Current Account Balance ◽  
Causality Test

Foreign Direct investments are interest to emerging countries as they may fuel growth. Countries compete with each other to attract new direct investment as they are permanent. This paper searches the relationship between technology transfer and economic growth in ten Eurasian countries via panel data analysis. For this purpose, gross domestic product, foreign direct investment, and current account balance are used as variables. The sample period is from 2000 to 2018. Dumitrescu and Hurlin panel causality test is used to because of heterogeneity The study provides evidence for a causal relationship from current account balances to GDP, and FDI to current account balance. Interestingly, the study provides evidence for no causal relationship from FDI to GDP but GDP levels affect FDI levels. Also, there is no found cointegration relationship between the variables.

An Examination of Audit Report Lag for Banks: A Panel Data Approach

2000 ◽  
Vol 19 (2) ◽  
pp. 159-174 ◽  
Author(s):  
B. Charlene Henderson ◽  
Steven E. Kaplan
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Panel Data Analysis ◽  
Explanatory Power ◽  
Omitted Variables ◽  
Audit Report ◽  
Cross Sectional ◽  
Cross Sectional Analysis ◽  
The Cross ◽  
Sectional Analysis

This study investigates the determinants of audit report lag (ARL) for a sample of banks. Researchers have been interested in the determinants of ARL, in part, because it impacts the timeliness of public disclosures. However, prior ARL research has relied exclusively on regression analysis of cross-sectional samples of companies from many industries. In addition to focusing exclusively on banks, panel data analysis is introduced and compared with cross-sectional analysis to demonstrate its power in dynamic settings and its potential to improve estimation. Results reveal important differences between cross-sectional analysis and panel data analysis. First, bank size is negatively related to ARL in cross-section but positively related to ARL using panel data analysis. The cross-sectional size estimate is subject to omitted variables bias, and furthermore, cross-sectional analysis fails to capture variation in size over time in relation to ARL. Panel data analysis both accounts for omitted variables and captures the dynamics of the relationship between size and ARL. As well, the panel data model's explanatory power far exceeds that of the cross-sectional model. This is primarily due to the panel model's use of firm-specific intercepts that both capture the role of reporting tradition and eliminate heterogeneity bias. Thus, panel data analysis proves to be a powerful tool in the analysis of ARL.

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