OECD Journal: Journal of Business Cycle Measurement and Analysis

Frequency :
3 times a year
ISSN :
1995-2899 (online)
ISSN :
1995-2880 (print)
DOI :
10.1787/19952899
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OECD Journal: Journal of Business Cycle Measurement and Analysis is jointly published by the OECD and the Centre for International Research on Economic Tendency Surveys (CIRET) to promote the exchange of knowledge and information on theoretical and operational aspects of economic cycle research, involving both measurement and analysis (see www.ciret.org/jbcma). Published as a part of the OECD Journal package.

 
 
 

Volume 2009, Issue 2 You do not have access to this content

Publication Date :
03 May 2010
DOI :
10.1787/jbcma-v2009-2-en

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Mark Mark Date TitleClick to Access
  03 May 2010 Click to Access: 
    http://oecd.metastore.ingenta.com/content/3309021ec001.pdf
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  • http://www.keepeek.com/Digital-Asset-Management/oecd/economics/the-dutch-business-cycle_jbcma-2009-5ks9zc0t7rg2
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The Dutch business cycle
Ard H. J. den Reijer

In this study we construct a business cycle indicator for the Netherlands. The Christiano-Fitzgerald band-pass filtter is employed to isolate the cycle using the definition of business cycle frequencies as waves with lengths longer than 3 years and shorter than 11 years. The coincident business cycle index is based on industrial production, household consumption and staffing employment. These three variables represent key macroeconomic developments, which are also analysed by both the CEPR and NBER dating committees. The composite leading index consists of eleven indicators representing different sectors in the economy: three financial series, four business and consumer surveys and four real activity variables, of which two supply - and two demand-related. The pseudo real-time performance of the composite indicator is analyzed by the extent to which the indicator gets revised as more data becomes available. Finally, the composite leading indicator is employed in a bivariate Vector Autoregressive model to forecast GDP growth rates.

  03 May 2010 Click to Access: 
    http://oecd.metastore.ingenta.com/content/3309021ec002.pdf
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  • http://www.keepeek.com/Digital-Asset-Management/oecd/economics/constructing-a-markov-switching-turning-point-index-using-mixed-frequencies-with-an-application-to-french-business-survey-data_jbcma-2009-5ks9v49q3swc
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Constructing a Markov-switching turning point index using mixed frequencies with an application to French business survey data
José Bardaji, Laurent Clavel, Frédéric Tallet

This paper proposes an indicator for detecting business cycles turning points incorporating mixed frequency business survey data. It is based on a hidden Markow-Switching model and allows for the detection of regime changes in a given economy where information is displayed monthly, bimonthly and quarterly. Adapting existing indicators such as Hamilton (1989) and Gregoir and Lenglart (2000) to this frequency mix constitutes the main contribution of the present work. The proposed methodology is applied to the French economy. Using balances from different business surveys, this indicator measures the probability of being in an accelerating or a decelerating phase. The indicator is compared over the past with a reference dating established upon the business cycle component of GDP e xtracted by a Christiano-Fitzerald filter. It exhibits quite clearly and timely regimes changes of the French outlook. In this case the mixed frequency methodology adapted from Gregoir and Lengart yields better performance than the Hamilton-based indicator. Considering the adequacy with the reference dating over the past, the French turning point index (TPI) provdies an accurate signal on the current outlook.

  03 May 2010 Click to Access: 
    http://oecd.metastore.ingenta.com/content/3309021ec003.pdf
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  • http://www.keepeek.com/Digital-Asset-Management/oecd/economics/measurement-error-in-estimating-inflation-expectations-from-survey-data_jbcma-2009-5ks9v45bggd5
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Measurement error in estimating inflation expectations from survey data
Akira Terai

This paper discusses the measurement error of conversion methods used to convert survey data to a quantitative index, especially the Carlson and Parkin (1975) method. When we want to summarise economic conditions using a numerical value, we often have to depend on survey data and convert them to a quantitative index. However, because survey research restricts responses into specific classifications and respondent’s response density may not be uniform, survey data surely include a specific error. In addition, because the distribution assumed in the Carlson–Parkin method may not fit the respondent’s distribution, this may also produce measurement error. This paper computes the measurement error of the Carlson and Parkin method in order to clarify its properties by Monte Carlo simulation. First, this paper finds that the "balance approach" contains significant error. Second, the error is large when true inflation expectations are large. Third, the error can be decreased by increasing the number of respondents. Fourth, changes in the response classification do not bring about dramatic changes compared with an increase in the number of respondents.

  03 May 2010 Click to Access: 
    http://oecd.metastore.ingenta.com/content/3309021ec004.pdf
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  • http://www.keepeek.com/Digital-Asset-Management/oecd/economics/forecasting-international-trade_jbcma-2009-5ks9v44bdj32
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Forecasting international trade
Alexander Keck, Alexander Raubold, Alessandro Truppia

This paper develops a time series model to forecast the growth in imports by major advanced economies in the current and following year (two to six quarters ahead). Both pure time series analysis and structural approaches that include additional predictors based on economic theory are used. Our results compare favourably with other trade forecasts, as measured by standard evaluation statistics and can serve as a benchmark for more complex macroeconomic models.

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