Belbute, José
(2013):
*Does final demand for energy in Portugal exhibit long memory?*

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## Abstract

The goal of this paper is to test for the presence of long memory in final energy demand in Portugal. Our findings suggest the presence of long memory in aggregate and disaggregate energy demand in Portugal. All fractional-difference parameters are positive and lower than 0.5 indicating that the series are both stationary and mean reverting. In addition, our findings also indicate that there are no clear seasonal effects over the degree of fractional integration. These results have important implication for the design of environmental policies. First positive policy shocks are likely to be more effective in moving energy consumption away from its predetermined target. Second, those policies may cause energy demand to revert to its (new) trend over a long period of time. Third, our results also suggest that switching between types of energy will be easier given that all components of aggregate final energy demand have long range dependency. Finally, given the strong connection of the energy sector with the rest of the economy, energy policies may be transmitted to other sectors of the economy and may also have impacts on the real economy. Moreover, positive shocks associated with permanent energy policies stimulating the switch to renewable energy sources may contribute to changing the energy consumption mix and to the reduction of carbon dioxide emissions.

Item Type: | MPRA Paper |
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Original Title: | Does final demand for energy in Portugal exhibit long memory? |

English Title: | Does final demand for energy in Portugal exhibit long memory? |

Language: | English |

Keywords: | Long memory, final energy demand, environmental policy, ARFIMA model, Portugal. |

Subjects: | C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes O - Economic Development, Innovation, Technological Change, and Growth > O1 - Economic Development > O13 - Agriculture ; Natural Resources ; Energy ; Environment ; Other Primary Products Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q41 - Demand and Supply ; Prices |

Item ID: | 45717 |

Depositing User: | José Belbute |

Date Deposited: | 02 Apr 2013 10:07 |

Last Modified: | 04 Oct 2019 06:26 |

References: | Adenstedt R.K. (1974); “On Large Sample Estimation for the Mean of a Stationary Random Sequence”, Annals of Statistics, 2, pp. 1095-1107; Al-Iriani, M. (2006); “Energy-GDP relationship revisited: an example from GCC countries using panel causality,” Energy Policy, 34, 3342–3350; Altinay,G. e E. Karagol (2004); “Structural break, unit root and the causality between energy consumption and GDP in Turkey,” Energy Economics, 26, 985–994; Apergis, N. e C. Tsoumas (2012); “Long memory and disaggregated energy consumption: evidence from fossil fuels, coal and electricity retail in the US.” Energy Economics, 34, 1082-1087; Apergis, N. e C. Tsoumas (2011); “Integration properties of disaggregated solar, geothermal and biomass energy consumption in the US.” Energy Policy, 39: 5474-5479; Apergis, N. e J. Payne (2010); “Structural breaks and petroleum consumption in US states: are shocks transitory or permanent?” Energy Policy, 38: 6375-78; Aslan, A. e H. Kum (2011); “The stationarity of energy consumption for Turkish disaggregate data by employing linear and nonlinear unit root tests.” Energy, 36: 4256-58; Baillie R. T. (1996); “Long Memory and Fractional Integration in Econometrics,” Journal of Econometrics, 73, pp. 5-59; Baillie R., C Chung and M. Tieslau (1996); “Analyzing inflation by fractionally integrated ARFIMA-GARCH model,” Journal of Applied Econometrics, 11, 23-40; Barros, C., Gil-Alana e L. Payne (2012); “Evidence of long memory behavior in US renewable energy consumption.” Energy Policy, 41, 822-826; Breitung, J. and Hassler, U. (2002); “Inference on the cointegration rank infractionally integrated processes,” Journal of Econometrics, 110, 167-185; Caporale, G. and L. Gil-Alana (2008): ”Modelling the US, UK and Japanese unemployment rates: fractional integration and structural breaks,” Computational Statistics and Data Analysis, 52, 4998–5013; Chen, P. e C-C Lee (2007); “Is energy consumption per capita broken stationary? New evidence from regional based panels,” Energy Policy, 35, 3526–3540; Choi, C. e H. Moh (2007); “How useful are tests for unit roots in distinguishing unit root processes from stationary but nonlinear processes?,” Econometrics Journal, 10: 82-111; Dahlhaus R. (1989); “Efficient Parameter Estimation for Self-Similar Processes,” Annals of Statistics, 17, pp. 1749-1766; Diebold, F. , S. Husted and M. Rush (1991); “Real exchange rates under the gold standard,” Journal of Political Economy, 99, 1252–1271; Diebold,F. e G. Rudebusch (1989); “Long memory and persistence in aggregate output. Journal of Monetary Economics24,189–209; Dickey, DA., Fuller (1979); “Distribution of the estimators for autoregressive time series with a unit root,” Journal of the American Statistical Association, 74: 427–31; Elder, J. e A. Serletis (2008); “Long memory in energy futures prices,” Review of Financial Economics, 17, 146–155; Geweke, J. e S. Porter-Hudak (1983); “The estimation and application of long memory time series models,” Journal of Time Series Analysis, 4, 221–238; Gil-Alana L.A., D. Loomis e J. Payne (2010); “Does Energy Consumption by the US Electric Power Sector Exhibit Long Memory Behavior?,” Energy Policy, 38, pp. 7515-7518; Gil-Alana, L.A., (2003); “A fractional multivariate long memory model for the US and Canadian real output,” Economic Letters, 81, 355-359; Gil-Alana, L.A., (2002a); “Structural beaks and fractional integration in the US output and unemployment rate,” Economic Letters, 77, 79–84; Gil-Alana, L.A., (2002b); “Mean reversion in the real exchange rate,” Economic Letters, 69, 285-288; Gil-Alana L.A., Robinson P.M. (1997); “Testing of Unit Root and Other Non-stationary Hypotheses in Macroeconomic Time Series,” Journal of Econometrics, 80, pp. 241-268; Gil-Alana L.A., Robinson P.M. (2001); “Seasonal Fractional Integration in the UK and Japanese Consumption and Income,” Journal of Applied Econometrics, 16, pp. 95-114; Granger C.W.J. (1980); “ Long Memory Relationships and the Aggregation of Dynamic Models,” Journal of Econometrics, 14, pp. 227-238; Granger C.W.J. (1981); “Some Properties of Time Series Data and their Use in Econometric Model Specification,” Journal of Econometrics, 16, pp. 121-130; Granger C.W.J., Joyeux R. (1980); “An Introduction to Long Memory Time Series and Fractional Differencing,” Journal of Time Series Analysis, 1, pp. 15-29; Grau-Carles, P. (2005); “Tests of Long Memory: A Bootstrap Approach.” Computational Economics, 25, pp 103-113; Hansen, L. e Sargent, T. (1993); Seasonality and Approximation Errors in Rational Expectations Models. Journal of Econometrics. 55, 21–55; Hasanov, M. e Telatar (2011); “A re-examination of stationarity of energy consumption: evidence from new unit root tests,” Energy Policy 2011; 39: 7726-7738; Hassler U., Wolters J. (1995); “Long Memory in Inflation Rates: International Evidence,” Journal of Business and Economic Statistics, 19, pp. 37-45; Hauser M.A., Potscher B.M. and Reschenhofer E. (1998); “Measuring Persistence in Aggregate Output: ARMA Models, Fractionally Integrated ARMA Models and Non Parametric Procedures,” Empirical Economics, 24, pp. 243-269; Hosking J.R.M. (1984); “Modelling Persistence in Hydrological Time Series Using Fractional Differencing,” Water Resources Research, 20, pp. 1898-1908; Hosking J.R.M. (1981); “Fractional Differencing,” Biometrika, 68, pp. 165-176; Hsu, Y. e C-C Lee (2008); “Revisited: are shocks to energy consumption permanent or stationary? New evidence from a panel SURADF approach,” Energy Economics, 30, 2314–2330; Hurst, H. (1951); “Long-term storage capacity of reserviors,” Transactions of the American Society of Civil Engineers, 116, 770-799; Hurst, H. (1956); “Methods of using long term storage in reservoirs,” Proceedings of the Institute of Civil Engineers, 1, 519-543; Hurst, H. (1957); “A suggested statistical model of some time series that occur in nature,” Nature 180, 494; Joyeux,R. e R. Ripple (2007); “Household energy consumption versus income and relative standard of living: a panel approach,” Energy Policy, 35, 50–60; Kumar, M. e T. Okimoto (2007); “Dynamics of persistence in international inflation rates.” Journal of Money, Credit and Banking 39, 1457–1479; Lee, C.C. e J. Lee (2009); “Energy prices, multiple structural breaks and efficient market hypothesis,” Applied Energy, 86, 466–479; Lean, H. e R. Smyth (2009); “Long memory in US disaggregated petroleum consumption: Evidence from univariate and multivariate LM tests for fractional integration,” Energy Policy, 37, pp. 3205-3211; Lee, C e C. Chang (2008);” Energy consumption and economic growth in Asian economies: a more comprehensive analysis using panel data,“ Resource and Energy Economics, 30, 50-65; Lee, C. (2005); “Energy consumption and GDP in developing countries: a cointegrated panel analysis,” Energy Economics, 27, 415–427; Lee, C e C. Chang (2005);”Structural breaks, energy consumption and economic growth evisited: Evidence from Taiwan,“ Energy Economics, 27, 857–872; Lee, D. e P. Schmidt (1996); “On the power of the KPSS test of stationarity against fractionally integrated alternatives.” Journal of Econometrics, 73: 285-30; Lo, A. (1991); “Long term memory in stock markets prices,” Econometrica, 59, 451-474; Mandelbrot, B. and J. Willis (1968); “Noah, Joseph and operational hydrology,” Water Resources Research, 4, 909-918; Maslyuk, S. e R. Smyth (2009); “Non-linear unit root properties of crude oil production.” Energy Economics, 31: 109-118; Maslyuk,S. e R. Smyth (2008); “Unit root properties of crude oil spot and futures prices,” Energy Policy , 36, 2591–2600; Moosa, I.A. E Ripple, R.D. (2000); The Effects of Seasonal Adjustment on the Accuracy of Forecasting U.S. West coast oil imports. Journal of Economic Research, 5, 149–172; Narayan, P. S. Narayan e S. Popp (2010); “Energy consumption at the state level: the unit root null hypothesis from Australia,” Applied Energy, 87, 1953-1962; Narayan,P., S. Narayan e R. Smyth (2008); “Are oil shocks permanent or temporary? Panel data evidence from crude oil and NGL production in 60countries,” Energy Economics, 30, 919–936; Narayan,P. e R. Smyth (2005); “Electricity consumption, employment and real income in Australia: evidence from multivariate granger causality tests,” Energy Policy, 33, 1109–1116; Narayan,P. e R. Smyth (2007); “Are shocks to energy consumption permanent or temporary: evidence from 182 countries,” Energy Policy, 35, 333–341; Nielsen, O. (2005); “Multivariate lagrange multiplier tests for fractional integration,” Journal of Financial Econometrics 3, 372–398; Parke W.R. (1999); “What is Fractional Integration?,” Review of Economics and Statistics, 8, pp. 632-638; Palma, W. (2007); “Long-Memory Time Series: Theory and Methods, Hoboken, New Jersey, Wiley; Peng, C. S. Buldyrev, S. Havlin, M. Simons, H. Standley e A. Goldberger (1994); “Mosaic organization of DNA sequences.” Physical Review E, 49, 1684–1989; Pereira, AM., Belbute, JM. Final energy demand in Portugal: how persistent it is and why it matters for environmental policy. CEFAGE-UE Working Paper 2011/20; Robinson P.M. (1978); “Statistical Inference for a Random Coefficient Autoregressive Model,” Scandinavian Journal of Statistics, 5, pp. 163-168; Robinson P.M. (1994a); “Efficient Tests of Non-Stationary Hypotheses,” Journal of the American Statistical Association, 89, pp. 1420-1437; Robinson P.M. (1994b); “Semi-Parametric Analysis of Long Memory Time Series,” Annals of Statistic, 22, pp. 515-539. Serletis, A. (1992); “Unit root behavior in energy futures prices,” The Energy Journal 13, 119–128; Smyth, R. (2012); “Are Fluctuations in Energy Variables Permanent or Transitory? A Survey of the Literature on the Integration Properties of Energy Consumption and Production,” Discussion Paper 4/12, Department of Economics, Monash University, Australia; Sowell F. (1992a); “Modeling Long-run behavior with the fractional ARIMA model,” Journal of Monetary Economics, 29, pp. 277-302. |

URI: | https://mpra.ub.uni-muenchen.de/id/eprint/45717 |