Examine the Reliability of Econometrics Software: An Empirical Comparison of Time Series Modelling
Examine the Reliability of Econometrics Software: An Empirical Comparison of Time Series Modelling作者机构：Department of Statistics & Computer Science Faculty of Science University of Peradeniya Peradeniya Sri Lanka Department of Economics & Statistics Faculty of Arts University of Peradeniya Peradeniya Sri Lanka
出 版 物：《Open Journal of Statistics》 (统计学期刊（英文）)
年 卷 期：2023年第13卷第1期
页 面：25-45页
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：Econometrics Macroeconomic Determinants Software Packages Time Series Modelling
摘 要：Researchers must understand that naively relying on the reliability of statistical software packages may result in suboptimal, biased, or erroneous results, which affects applied economic theory and the conclusions and policy recommendations drawn from it. To create confidence in a result, several software packages should be applied to the same estimation problem. This study examines the results of three software packages (EViews, R, and Stata) in the analysis of time-series econometric data. The time-series data analysis which presents the determinants of macroeconomic growth of Sri Lanka from 1978 to 2020 has been used. The study focuses on testing for stationarity, cointegration, and significant relationships among the variables. The Augmented Dickey-Fuller and Phillips Perron tests were employed in this study to test for stationarity, while the Johansen cointegration test was utilized to test for cointegration. The study employs the vector error correction model to assess the short-run and long-term dynamics of the variables in an attempt to determine the relationship between them. Finally, the Granger Causality test is employed in order to examine the linear causation between the concerned variables. The study revealed that the results produced by three software packages for the same dataset and the same lag order vary significantly. This implies that time series econometrics results are sensitive to the software that is used by the researchers while providing different policy implications even for the same dataset. The present study highlights the necessity of further analysis to investigate the impact of software packages in time series analysis of economic scenarios.
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