Brazilian airline industry: Persistence and breaks

References

• Adrangi, B., Chatrath, A., & Raffee, K. (2001). The demand for US air transport service: A chaos and nonlinearity investigation. Transportation Research Part E, Logistic and Transportation Review, 37(5), 337–353.
   Web of Science ®Google Scholar
• Arteche, J. (2002). Semiparametric robust tests on seasonal or cyclical long memory time series. Journal of Time Series Analysis, 23, 251–286.
   Web of Science ®Google Scholar
• Arteche, J., & Robinson, P. M. (1999). In S. Ghosh (Ed.), Seasonal and cyclical long memory in asymptotics, non-parametrics and time series (115–149). New York: Marcel Dekker.
   Google Scholar
• Assaf, A., Barros, C. P., and Gil-Alana, L. A. (2013). Retail sales: Persistence in the short-term and long-term dynamics. IMA Journal of Management Mathematics, 25(3), 367–386.
   Google Scholar
• Bai, J., & P. Perron. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66, 47–78.
   Web of Science ®Google Scholar
• Barros, C. P., Gil-Alana, L. A., and Payne, J. E. (2013). US Disaggregated renewable energy consumption: Persistence and long memory behaviour. Energy Economics, 40, 425–432.
   Web of Science ®Google Scholar
• Bettini, H. F. A. J., & Oliveira, A. V. M. (2008). Airline capacity setting after re-regulation: The Brazilian case in the early 2000s. Journal of Air Transport Management, 14(6), 289–292.
   Web of Science ®Google Scholar
• Bhargava, A. (1986). On the theory of testing for unit roots in observed time series. Review of Economic Studies, 53, 369–384.
   Web of Science ®Google Scholar
• Box, C., Franses, P. H., & Ooms, M. (2001). Inflation, forecasting intervals and long memory in a regression model. International Journal of Forecasting, 18, 243–264.
   Web of Science ®Google Scholar
• Broadstock, D. C., & Collins, A. (2011). Measuring unobserved prices using the structural time-series model: The case of cycling. Transportation Research Part A, 44(4), 195–200.
   Google Scholar
• Candelon, B., Kool, C., Raabe, K., & van Veen, T. (2007). Long-run real exchange rate determinants: Evidence from eight new EU member states, 1993–2003. Journal of Comparative Economics, 35, 87–107.
   Web of Science ®Google Scholar
• Caporale, G. M., & Gil-Alana, L. A. (2004). Fractional cointegration and real exchange rates. Review of Financial Economics, 13, 327–340.
   Google Scholar
• Chambers, M. (1998). Long memory and aggregation in macroeconomic time series. International Economic Review, 39, 1053–1072.
   Web of Science ®Google Scholar
• Cheung, Y. W. (1993). Tests for fractional integration. A Monte Carlo investigation. Journal of Time Series Analysis, 14, 331–345.
   Google Scholar
• Cioczek-Georges, R., & Mandelbrot, B. B. (1995). A class of micropulses and anti-persistent fractional Brownian motion. Stochastic Processes and Their Applications, 60, 1–18.
   Web of Science ®Google Scholar
• Correia, T. C. V. D., & Soares de Mello, J. C. C. B. (2008). Avaliação da Eficiência das Companhias Aéreas Brasileiras com Modelo Fuzzy-DEA. Relatórios de Pesquisa em Engenharia de Produção, 8(5), 1–11.
   Google Scholar
• Correia, A. R., & Wirasinghe, S. C. (2007). Development of level of service standards for airport facilities: Application to São Paulo International Airport. Journal of Air Transport Management, 13(2), 97–103.
   Web of Science ®Google Scholar
• Correia, A. R., Wirasinghe, S. C., & Barros, C. P. (2008). A global index for level of service evaluation at airport passenger terminals. Transportation Research Part E, 44(4), 607–620.
   Google Scholar
• Dahlhaus, R. (1989). Efficient parameter estimation for self-similar process. Annals of Statistics, 17, 1749–1766.
   Web of Science ®Google Scholar
• Diebold, F. X., & Inoue, A. (2001). Long memory and regime switching. Journal of Econometrics, 105, 131–159.
   Web of Science ®Google Scholar
• Dufrénot, G., Grimaud, E., Latil, E., & Mignon, V. (2008). Modelling the slow mean reversion of the Central and Eastern European countries' real exchange rates. Manchester School, 76, 21–43.
   Web of Science ®Google Scholar
• Gil-Alana, L. A. (2005). Modelling international monthly arrivals using seasonal univariate long-memory processes. Tourism Management, 26, 867–878.
   Web of Science ®Google Scholar
• Gil-Alana, L. A. (2008). Fractional integration and structural breaks at unknown periods of time. Journal of Time Series Analysis, 29, 163–185.
   Web of Science ®Google Scholar
• Gil-Alana, L., Barros, C. P., & Araujo Jr., A. (2012). Aircraft accidents in Brazil. International Journal of Sustainable Transportation, 6, 111–126.
   Web of Science ®Google Scholar
• Gil-Alana, L., Barros, C. P., & Assaf, A. (2013). The US airline industry: Persistence and breaks. Transportmetrica A: Transport Science 9(8), 742–752.
   Web of Science ®Google Scholar
• Gil-Alana, L. A., & Gupta, R. (2014). Persistence and cycles in historical oil price data, Energy Economics, 45, 511–516, ISSN 0140-9883, http://dx.doi.org/10.1016/j.eneco.2014.08.018.
   Web of Science ®Google Scholar
• Giraitis, L., Kokoszka, P., & Leipus, R. (2001). Testing for long memory in the presence of a general trend. Journal of Applied Probability, 38, 1033–1054.
   Web of Science ®Google Scholar
• Gonzales Vega, D. J. (2013). Fractionally integrated and regime switching models to forecast the demand of a fast-growing emerging air transportation market. Iberoamerican Journal of Applied Computing, 3(1), 1–39.
   Google Scholar
• Granger, C. W. J. (1980). Long memory relationships and the aggregation of dynamic models. Journal of Econometrics, 14, 227–238.
   Web of Science ®Google Scholar
• Granger, C. W. J., & N. Hyung (2004). Occasional structural breaks and long memory with an application to the S&P 500 absolute stock return. Journal of Empirical Finance, 11, 399–421.
   Google Scholar
• Hidalgo, J., & Robinson, P. M. (1996). Testing for Structural Change in a Long-Memory Environment. Journal of Econometrics, 70(1): 159–174.
   Web of Science ®Google Scholar
• Karlaftis, M. G., & Vlahogianni, E. I. (2009). Memory properties and fractional integration in transportation time series. Transportation Research Part C, Emerging Technologies, 17(4), 444–453.
   Web of Science ®Google Scholar
• Lee, J., & Strazicich, M. C. (2003). Minimum Lagrange multiplier unit root test with two structural breaks. Review of Economics and Statistics, 85(4), 1082–1089.
   Web of Science ®Google Scholar
• Lee, J., & Strazicich, M. C. (2004). Minimum LM unit root test with one structural break (Department of Economics Working Paper No. 04–17). Appalachian State University, Boone, NC.
   Google Scholar
• Li, Z., Rose, J. M., & Hensher, D. A. (2010). Forecasting automobile petrol demand in Australia: An evaluation of empirical models. Transportation Research Part A, 44(1), 16–38.
   Google Scholar
• Lippi, M., & Zaffaroni, P. (1999). Contemporaneous aggregation of linear dynamic models in large economies (manuscript). Research Department, Bank of Italy, Rome.
   Google Scholar
• Lobato, I. N., & Savin, N. E. (1998). Real and spurious long memory processes of stock market prices. Journal of Business and Economic Statistics, 16, 261–268.
   Web of Science ®Google Scholar
• Marazzo, M., Scherre, R., & Fernandes, E. (2010). Air transport demand and economic growth in Brazil: A time series analysis. Transportation Research Part E, 46, 261–269.
   Google Scholar
• Mckinsey & Company. (2010). Estudo do Setor de Transporte Aéreo do Brasil: Relatório Consolidado, Brasilia, McKinsey & Co.
   Google Scholar
• Mikosch, T., & Starica, C. (2004). Nonstationarities in financial time series, the long range dependence and the IGARCH effects. Review of Economics and Statistics, 86, 378–390.
   Web of Science ®Google Scholar
• Min, J. C. H., Kung, H. H., & Liu, H. H. (2010). Interventions affectin air transport passenger demand in Taiwan. African Journal of Business Management, 40, 2121–2131.
   Google Scholar
• Müller, C., & Santana, E. S. M. (2008). Analysis of flight-operating costs and delays: The Sao Paulo terminal maneuvering area. Journal of Air Transport Management, 14(6), 293–296.
   Web of Science ®Google Scholar
• Nam, K., & Schaefer, T. (1995). Forecasting international airline passenger traffic using neural networks. Logistics and Transportation Review, 31(3), 239–251.
   Web of Science ®Google Scholar
• Narayan, P. K. (2008). Examining the behaviour of visitors arrivals to Australia from 28 different countries. Transportation Research Part A, 42, 751–761.
   Google Scholar
• Narayan, P. K., & Popp, S. (2013). Size and power properties of structural break unit root tests. Applied Economics, 45(6), 721–728.
   Web of Science ®Google Scholar
• Njegovan, N. (2006). Are shocks to air passenger traffic permanent or transitory? Journal of Transport Economics and Policy, 40, 315–328.
   Web of Science ®Google Scholar
• Nelson, C. R., & Plosser, C. I. (1982). Trends and random walks in macroeconomic time series. Journal of Monetary Economics, 10, 139–162.
   Web of Science ®Google Scholar
• Ohanissian, A., Rusell, J. R., and Tsay, R. S. (2008). True or spurious long memory? A new test. Journal of Business and Economic Statistics, 26(2), 161–175.
   Web of Science ®Google Scholar
• Oliveira, A. V. M., & Huse, C. (2009). Localized competitive advantage and price reactions to entry: Full-service vs. low-cost airli`nes in recently liberalized emerging markets. Transportation Research Part E, 45(2), 307–320.
   Google Scholar
• Pacheco, R. R., Fernandes, E., & Santos, M. P. S. (2006). Management style and airport performance in Brazil. Journal of Air Transport Management, 12(6), 324–330.
   Web of Science ®Google Scholar
• Parke, W. R. (1999). What is fractional integration? Review of Economics and Statistics, 81, 632–638.
   Web of Science ®Google Scholar
• Ramanathan, R. (2001). The long-run behaviour of transport performance in India: A cointegration approach. Transportation Research Part A, 35, 309–320.
   Google Scholar
• Robinson, P. M. (1978). Statistical inference for a random coefficient autoregressive model. Scandinavian Journal of Statistics, 5, 163–168.
   Web of Science ®Google Scholar
• Robinson, P. M. (1994). Efficient tests of nonstationary hypotheses. Journal of the American Statistical Association, 89, 1420–1437.
   Web of Science ®Google Scholar
• Schmidt, P., & Phillips, P. C. B. (1992). LM tests for a unit root in the presence of deterministic trends. Oxford Bulletin of Economics and Statistics, 54, 257–287.
   Web of Science ®Google Scholar
• Tadeu, H. F. B., & Silva, J. T. M. (2012). A theoretical framework for the Brazilian airline competitive marketing environment. Review of Economics and Finance, 2, 97–106.
   Google Scholar
• Taqqu, M. S., Willinger, W., & Sherman, R. (1997). Proof of a fundamental result in self-similar traffic modelling. Computer Communication Review, 27, 5–23.
   Google Scholar
• Taylor, M. P., & Sarno, L. (2001). Real exchange rate dynamics in transition economies: A nonlinear analysis. Studies in Nonlinear Dynamics and Econometrics, 5, 153–177.
   Web of Science ®Google Scholar
• Weatherford, L. R., Gentry, T. W., & Wilamowski, B. (2003). Neural network forecasting for airlines: A comparative analysis. Journal of Revenue and Pricing Management, 1(4), 319–331.
   Google Scholar