Modified panel data regression model and its applications to the airline industry: Modeling the load factor of Europe North and Europe Mid Atlantic flights

This article conducts a stochastic analysis on the passenger load factor of the airline industry. Used to measure competence and performance of the airline, load factor is the percentage of seats filled by revenue passengers. It is considered a complex metric in the airline industry. Thus, it is affected by several dynamic factors. This paper applies advanced stochastic models to obtain the best fitted trend of load factor for Europe's North Atlantic (NA) and Mid Atlantic (MA) flights in the Association of European Airlines. The stochastic model's fit helps to forecast the load factor of flights within these geographical regions and evaluate the airline's demand and capacity management. The paper applies spectral density estimation and dynamic time effects panel data regression models on the monthly load factor flights of NA and MA from 1991 to 2013. The results show that the load factor has both periodic and serial correlations. Consequently, the author acknowledges that the use of an ordinal panel data model is inappropriate for a realistic econometric model of load factor. Therefore, to control the periodic correlation structure, the author modified the existing model was modified by introducing dynamic time effects. Moreover, to eradicate serial correlation, the author applied the Prais–Winsten methodology was applied to fit the model. In this econometric analysis, the study finds that AEA airlines have greater demand and capacity management for both NA and MA flights. In conclusion, this study prosperous in finding an effective and efficient dynamic time effects panel data regression model fit, which empowers engineers to forecast the load factor off AEA airlines

Structure of the Norwegian imports trade concentration : the seemingly unrelated autoregressive regression modelling approach

Purpose: This article is proposed to analyse the structure of the trade concentration index (HHI) of Norwegian imports across continents. Design/ Methodology/ Approach: The paper analyse the concentration index (HHI) by fitting a seemingly unrelated (SUR) regression model using exogenous variables of revenue collected from export and number of Norwegian export countries. Findings: The results suggest that the structure of the concentration index (HHI) Norwegian imports show different feature across continents. The estimation result predicts that the Norwegian import: from the continent of Africa is increasing in the extensive margin, from the continent of Asia and Oceania is increasing in the intensive margin, from the continent of Europe is increasing in both the extensive and the intensive margin, from the continent of North and Central America shows stagnation for both the extensive and the intensive margin, and from the continent of South America is increasing in the intensive margin. Research implications: The overall econometric analysis suggested that the Norwegian bilateral trade with European countries benefits Norway. Originality/ Value: The methodological approach employed in this study is unique and new to analyse trade concentration index (HHI). Keywords: Trade Concentration Index (HHI), determinants of HHI, SUR models and NorwaypublishedVersio

Intercontinental variations of the import trade pattern of Norway: applications to best linear unbiased estimable functions of hierarchical econometric model

This paper’s main purpose is an analysis of the intercontinental variations of Norwegian import expenditures based on yearly import data from 1988 to 2014. We estimate functions for the best linear unbiased estimator (BLUE) of the two-stage non-full rank hierarchical linear econometric model. The results confirm that the top three import-items across continents (in descending order) are machinery and transport equipment, manufactured goods classified mainly by material, and miscellaneous manufactured articles. These three import-items cover more than 60% of the Norwegian imports. Furthermore, the model predicts that Europe is the leading continent for Norwegian imports. The European continent is therefore influential for the Norwegian trade pattern, while other continents show lack of stability and predictability. The results imply that any governmental (or private) trade stability programs have only marginal effects