We consider the extent to which different time-series models can generate simulated data with the same business cycle features that are evident in US real GDP. We focus our analysis on whether multivariate linear models can improve on the previously documented failure of univariate linear models to replicate certain key business cycle features. These results are robust to simulated data generated either using Normal disturbances or bootstrapped disturbances, as well as to allowing for a one-time structural break in the variance of shocks to real GDP growth. Ahmed, S. Levin, and B. Blanchard, O. Boivin, J. Boldin, M. Breunig, R. Najarian, and A.
International Business Cycle Dates
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Section 2 contains a description of an algorithm used for dating business cycles and a definition of the concordance statistic. In section 3, the properties of the.
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A comparison of two business cycle dating methods
RATS Version Please be sure to include instructions on using the procedure and detailed references where applicable. For quarterly data, it implements the Pagan-Harding version. Bry and Boschan Pagan and Harding “Dissecting the cycle: a methodological investigation”, Journal of Monetary Economics , Volume 49, Issue 2,
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Dating Business Cycles: A Methodological Contribution with an Application to the Euro Area
This paper discusses formal quantitative algorithms that can be used to identify business cycle turning points. An intuitive, graphical derivation of these algorithms is presented along with a description of how they can be implemented making very minimal distributional assumptions. We also provide the intuition and detailed description of these algorithms for both simple parametric univariate inference as well as latent-variable multiple-indicator inference using a state-space Markov-switching approach.
We illustrate the promise of this approach by reconstructing the inferences that would have been generated if parameters had to be estimated and inferences drawn based on data as they were originally released at each historical date. Waiting until one extra quarter of GDP growth is reported or one extra month of the monthly indicators released before making a call of a business cycle turning point helps reduce the risk of misclassification.
Both indexes perform quite well in simulation with real-time data bases.
Keyword: Business Cycles, Economic Growth, Stagnation, Markov Switching Models. JEL Codes: F43 Dating Algorithm and Business Cycle’s characteristics.
In all cases, cyclical ups and downs depend not only on internal system cyclical processes and their factors in countries but also on the consequences of intercountry interaction. The ability to measure and predict business cycles, taking into account their mutual influence, is a prerequisite for the development of an adequate business policy of countries and their associations. This chapter is devoted to the substantiation of methods of statistical assessment and modeling of macroeconomic business cycles on the basis of their understanding as an integrated effect of changing business phases in different sectors, as well as the impact of synchronization and harmonization of business cycles in both the economy of one country and the intercountry levels.
The main directions of quantitative research of business cycles based on the econometric approach, which are widely presented in the literature, fall into two main groups. The first of these is the identification of stable cyclic components in the dynamics of macroeconomic indicators. In most cases, the authors of scientific publications use the real GDP gross domestic product , as an indicator for investigation of macroeconomic business cycle.
The second direction is the definition and quantitative description of the cyclic components in the dynamics of indicators characterizing the processes in individual sectors or spheres of the economy. This chapter proposes a method for identifying and quantifying the common business cycle as a directly unmeasurable phenomenon, which manifests itself in fluctuations in the dynamics of the specific indicators of industries and economic systems, but has an objective and independent economic nature.
The chapter suggests methods and their applications for identifying and quantifying the macroeconomic business cycle as a latent system-wide phenomenon, as well as methods for estimating intercountry synchronization and harmonization of common cycles. At the same time, the author gives her own definition of these forms of the interaction of business cycles. This approach is different to the view expressed in many publications about the identity of the concepts of synchronization, harmonization, concordance, and correlation of business cycles.
The chapter in addition to this introduction includes two main sections and a conclusion. In the second section of the chapter, an algorithm for quantifying the overall business cycle based on the principal component method is proposed, and methods for estimating synchronization and harmonizing business cycles are substantiated. The proof of the concept proposed in this chapter and the approbation of the corresponding algorithm were realized on the basis of statistics of Eurostat and Rosstat.
Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: Artis and M. Marcellino and T.
CZECH BUSINESS CYCLE DATING. LENKA VRANÁ This paper describes non-parametric (Bry-Boschan algorithm) and parametric (Markov switching model).
How does the Committee Define a Business Cycle? See Methodology. What data does the Committee use? See Data Sources. How is the Committee’s membership determined? The financial press often states the definition of a recession as two consecutive quarters of decline in real GDP. How does that relate to your recession dating procedure? As an example, the Committee has identified the period from the first quarter in to the third quarter in as a recession, despite the fact that real GDP was growing in some quarters during that episode and that real GDP was higher at the end of the recession than at the beginning.
As another example, the Committee did not declare a recession for or , even though the data at the time appeared to show a decline in economic activity though not for two quarters. Subsequent data revisions have erased these declines. First, we do not identify economic activity solely with real GDP, but use a range of indicators, notably employment. Second, we consider the depth of the decline in economic activity.
The following period is an expansion.
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An Alternative Business Cycle Dating Procedure for South Africa. Adel Bosch and the BB procedure into an algorithm that could easily be applied. A variant of.
Journal of Economic Dynamics and Control , 27 9 , pp. View at publisher. We study the suggestion that Markov switching MS models should be used to determine cyclical turning points. A Kalman filter approximation is used to derive the dating rules implicit in such models. We compare these with dating rules in an algorithm that provides a good approximation to the chronology determined by the NBER. We find that there is very little that is attractive in the MS approach when compared with this algorithm.
The most important difference relates to robustness. The MS approach depends on the validity of that statistical model. Our approach is valid in a wider range of circumstances. These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different.
Brownian Bridge Excel
The program has been uniquely designed to calculate which phase the Moon is passing through on any particular day. The cycle of Golden Numbers is the period after which moon phases repeat approximately on the same calendar dates. The illuminated fraction of the moon can be calculated with moonAngle in the oce package, as illustrated graphically and in R code below. Some moon phases present better opportunities than others, with four significant moon events happening every day.
Dates of business cycle turning points are a critical input for aca- demic and policy tion of the dating algorithm by Bry and Boschan ().
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Wednesday, September 07, Dating the Indian business cycle. Most macroeconomics is about business cycle fluctuations. The ultimate dream of macroeconomic policy is to use monetary policy and fiscal policy to reduce the amplitude of business cycle fluctuations, without contaminating the process of trend GDP growth. From an Indian policy perspective, this agenda is sketched in Shah and Patnaik The starting point of all these glamorous things, however, is measurement. The major barrier to doing Indian macroeconomics is the lack of the foundations of business cycle measurement.
The first milestone in this journey is sound procedures for seasonal adjustment of a large number of macroeconomic time series.