Business surveys modelling with Seasonal-Cyclical Long Memory models

نویسندگان

  • Laurent Ferrara
  • Dominique Guégan
چکیده

Business surveys are an important element in the analysis of the short-term economic situation because of the timeliness and nature of the information they convey. Especially, surveys are often involved in econometric models in order to provide an early assessment of the current state of the economy, which is of great interest for policy-makers. In this paper, we focus on non-seasonally adjusted business surveys released by the European Commission. We introduce an innovative way for modelling those series taking the persistence of the seasonal roots into account through seasonal-cyclical long memory models. We empirically prove that such models produce more accurate forecasts than classical seasonal linear models. The views expressed herein are those of the author and do not necessarily reflect those of the Banque de France. Citation: Ferrara, Laurent and Dominique Guégan, (2008) "Business surveys modelling with Seasonal-Cyclical Long Memory models." Economics Bulletin, Vol. 3, No. 29 pp. 1-10 Submitted: May 5, 2008. Accepted: May 22, 2008. URL: http://economicsbulletin.vanderbilt.edu/2008/volume3/EB-08C20041A.pdf

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Identification of Cyclical Banks in Iranian Banking System (Focus on Leverage Ratio)

T he cyclical banks have different behavior than other banks. The structure of the balance sheet in cyclical banks is different from anti-cyclical banks. The cyclical banks have a relationship between leverage growth and asset growth while the other banks have no relationship between asset growth and leverage growth in the banking system. This relationship depends on the structure of...

متن کامل

Estimating seasonal long-memory processes: a Monte Carlo study

This paper discusses extensions of the popular methods proposed by Geweke and Porter-Hudak [Geweke, J. and Porter-Hudak, S., 1983, The estimation and application of long memory times series models. Journal of Time Series Analysis, 4(4), 221–238.] and Fox and Taqqu [Fox, R. and Taqqu, M.S., 1986, Large-sample properties of parameter estimates for strongly dependent stationary Gaussian time serie...

متن کامل

Seasonal Adjustment and the Business Cycle in Unemployment

Several recent studies show that seasonal variation and cyclical variation in unemployment are correlated. A common nding is that seasonality tends to diier across the business cycle stages of recessions and expansions. Since seasonal adjustment methods assume that the two sources of variation can somehow be separated, the present study examines the impact of seasonal adjustment on the analysis...

متن کامل

Asymmetric Effects of Government Spending on Economic Growth Over the Business Cycle: Application of Markov Switching Models

This paper is  investigated four subject with uses iranian economic data and using the Markov-Switching model during the period (1369: 3-1393: 4), So that: (a) were Examined impact of  the positive and negative Fiscal  shocks on Iran economic growth ( B) the Hypothesis  impact of negative shocks is greater than a positive shock was tested. (C) were tested the impact of government expenditure (f...

متن کامل

Testing Fractional Order of Long Memory Processes: A Monte Carlo Study

Testing the fractionally integrated order of seasonal and non-seasonal unit roots is quite important for the economic and financial time series modelling. In this paper, Robinson test (1994) is applied to various well-known long memory models. Via Monte Carlo experiments, we study and compare the performances of this test using several sample sizes.

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008