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Journal articles on the topic 'Beveridge-Nelson-Decomposition'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

Proietti, Tommaso. "The Multistep Beveridge–Nelson Decomposition." Econometric Reviews 35, no. 3 (September 25, 2014): 373–95. http://dx.doi.org/10.1080/07474938.2014.966631.

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2

Morley, James C. "THE TWO INTERPRETATIONS OF THE BEVERIDGE–NELSON DECOMPOSITION." Macroeconomic Dynamics 15, no. 3 (June 10, 2010): 419–39. http://dx.doi.org/10.1017/s1365100510000118.

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The Beveridge–Nelson decomposition calculates trend and cycle for an integrated time series. However, there are two ways to interpret the results from the decomposition. One interpretation is that the optimal long-run forecast (minus any deterministic drift) used to calculate the Beveridge–Nelson trend corresponds to an estimate of an unobserved permanent component. The other interpretation is that the optimal long-run forecast defines an observable permanent component. This paper examines some issues surrounding these two interpretations and provides empirical support for interpreting the Beveridge–Nelson trend as an estimate when considering macroeconomic data.

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3

Proietti, Tommaso. "The beveridge-nelson decomposition: Properties and extensions." Journal of the Italian Statistical Society 4, no. 1 (February 1995): 101–24. http://dx.doi.org/10.1007/bf02589061.

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4

Cuddington, John T., and L. Alan Winters. "The Beveridge-Nelson decomposition of economic time series." Journal of Monetary Economics 19, no. 1 (January 1987): 125–27. http://dx.doi.org/10.1016/0304-3932(87)90032-8.

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5

Miller, Stephen M. "The Beveridge-Nelson decomposition of economic time series." Journal of Monetary Economics 21, no. 1 (January 1988): 141–42. http://dx.doi.org/10.1016/0304-3932(88)90051-7.

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6

de Silva, Ashton, Rob J. Hyndman, and Ralph Snyder. "A multivariate innovations state space Beveridge–Nelson decomposition." Economic Modelling 26, no. 5 (September 2009): 1067–74. http://dx.doi.org/10.1016/j.econmod.2009.04.004.

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7

Murasawa, Yasutomo. "The Beveridge–Nelson decomposition of mixed-frequency series." Empirical Economics 51, no. 4 (January 2, 2016): 1415–41. http://dx.doi.org/10.1007/s00181-015-1061-5.

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8

Chen, Chao-Chun, and Wen-Jen Tsay. "The Beveridge–Nelson decomposition of Markov-switching processes." Economics Letters 91, no. 1 (April 2006): 83–89. http://dx.doi.org/10.1016/j.econlet.2005.11.002.

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9

Nelson, Charles R. "The Beveridge–Nelson decomposition in retrospect and prospect." Journal of Econometrics 146, no. 2 (October 2008): 202–6. http://dx.doi.org/10.1016/j.jeconom.2008.08.008.

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10

Andrić, Vladimir, and Sanja Nenadović. "Laplace, Hansen-Sargent and Beveridge-Nelson a note towards unified business application." Serbian Journal of Management 16, no. 1 (2021): 39–47. http://dx.doi.org/10.5937/sjm16-30877.

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The paper derives the equivalence condition between the Beveridge-Nelson decomposition and the Hansen-Sargent prediction formula in continuous time using Laplace transforms. The results presented show how the Hansen-Sargent prediction formula is relevant not just for present value discounting but also for the trend-cycle decomposition of cash flow streams in corporate finance.

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11

Morley, James C. "A state–space approach to calculating the Beveridge–Nelson decomposition." Economics Letters 75, no. 1 (March 2002): 123–27. http://dx.doi.org/10.1016/s0165-1765(01)00581-x.

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12

Gomez, Victor, and Jorg Breitung. "The Beveridge-Nelson Decomposition: A Different Perspective with New Results." Journal of Time Series Analysis 20, no. 5 (September 1999): 527–35. http://dx.doi.org/10.1111/1467-9892.00154.

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13

Paulauskas, Vygantas. "On Beveridge–Nelson decomposition and limit theorems for linear random fields." Journal of Multivariate Analysis 101, no. 3 (March 2010): 621–39. http://dx.doi.org/10.1016/j.jmva.2009.10.001.

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14

Ariño, Miguel A., and Paul Newbold. "Computation of the Beveridge–Nelson decomposition for multivariate economic time series." Economics Letters 61, no. 1 (October 1998): 37–42. http://dx.doi.org/10.1016/s0165-1765(98)00131-1.

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15

Murasawa, Yasutomo. "The multivariate Beveridge–Nelson decomposition with I(1) and I(2) series." Economics Letters 137 (December 2015): 157–62. http://dx.doi.org/10.1016/j.econlet.2015.11.001.

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16

Anderson, Heather M., Chin Nam Low, and Ralph Snyder. "Single source of error state space approach to the Beveridge Nelson decomposition." Economics Letters 91, no. 1 (April 2006): 104–9. http://dx.doi.org/10.1016/j.econlet.2005.11.005.

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17

Dungey, Mardi, Jan P. A. M. Jacobs, Jing Tian, and Simon van Norden. "TREND IN CYCLE OR CYCLE IN TREND? NEW STRUCTURAL IDENTIFICATIONS FOR UNOBSERVED-COMPONENTS MODELS OF U.S. REAL GDP." Macroeconomic Dynamics 19, no. 4 (June 13, 2014): 776–90. http://dx.doi.org/10.1017/s1365100513000606.

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A well-documented property of the Beveridge–Nelson trend–cycle decomposition is the perfect negative correlation between trend and cycle innovations. We show how this may be consistent with a structural model where permanent innovations enter the cycle or transitory innovations enter the trend, and that identification restrictions are necessary to make this structural distinction. A reduced-form unrestricted version is compatible with either option, but cannot distinguish which is relevant. We discuss economic interpretations and implications using U.S. real GDP data.

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18

Sbrana, Giacomo. "The exact linkage between the Beveridge–Nelson decomposition and other permanent-transitory decompositions." Economic Modelling 30 (January 2013): 311–16. http://dx.doi.org/10.1016/j.econmod.2012.09.039.

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19

Newbold, Paul. "Precise and efficient computation of the Beveridge-Nelson decomposition of economic time series." Journal of Monetary Economics 26, no. 3 (December 1990): 453–57. http://dx.doi.org/10.1016/0304-3932(90)90007-q.

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20

Kim, Chang-Jin. "Markov-switching and the Beveridge–Nelson decomposition: Has US output persistence changed since 1984?" Journal of Econometrics 146, no. 2 (October 2008): 227–40. http://dx.doi.org/10.1016/j.jeconom.2008.08.014.

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21

Beyaert, Arielle, and Alfonso J. Quesada Medina. "Computation of the Beveridge–Nelson decomposition in the case of cointegrated systems with I(0) variables." Economics Letters 72, no. 3 (September 2001): 283–89. http://dx.doi.org/10.1016/s0165-1765(01)00455-4.

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22

Oh, Kum Hwa, Eric Zivot, and Drew Creal. "The relationship between the Beveridge–Nelson decomposition and other permanent–transitory decompositions that are popular in economics." Journal of Econometrics 146, no. 2 (October 2008): 207–19. http://dx.doi.org/10.1016/j.jeconom.2008.08.021.

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23

Guo, Sen, Haoran Zhao, and Huiru Zhao. "A New Hybrid Wind Power Forecaster Using the Beveridge-Nelson Decomposition Method and a Relevance Vector Machine Optimized by the Ant Lion Optimizer." Energies 10, no. 7 (July 4, 2017): 922. http://dx.doi.org/10.3390/en10070922.

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24

Kawka, Rafael. "Limit theorems for locally stationary processes." Statistical Papers, October 1, 2020. http://dx.doi.org/10.1007/s00362-020-01204-1.

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Abstract We present limit theorems for locally stationary processes that have a one sided time-varying moving average representation. In particular, we prove a central limit theorem (CLT), a weak and a strong law of large numbers (WLLN, SLLN) and a law of the iterated logarithm (LIL) under mild assumptions using a time-varying Beveridge–Nelson decomposition.

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25

Coronado, Roberto. "Business Cycles and Remittances: Can the Beveridge-Nelson Decomposition Provide New Evidence?" Federal Reserve Bank of Dallas, Globalization and Monetary Policy Institute Working Papers 2009, no. 40 (2009). http://dx.doi.org/10.24149/gwp40.

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26

Murasawa, Yasutomo. "Bayesian multivariate Beveridge–Nelson decomposition of I(1) and I(2) series with cointegration." Studies in Nonlinear Dynamics & Econometrics, June 2, 2021. http://dx.doi.org/10.1515/snde-2020-0049.

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Abstract The dynamic IS equation implies that if the real interest rate is I(1), then so is the output growth rate with possible cointegration, and log output is I(2). This paper extends the Beveridge–Nelson decomposition to such a case, and develops a Bayesian method to obtain error bands. The method is valid whether log output is I(1) or I(2). The paper applies the method to US data to estimate the natural rates (or their permanent components) and gaps of output, inflation, interest, and unemployment jointly, and finds that allowing for cointegration gives much bigger estimates of the gaps for all variables.

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27

Lücke, Bernd. "Analysis of West German Macroeconomic Data Using Common Trends and Common Cycles / Eine Analyse westdeutscher Makrodaten anhand gemeinsamer Trends und gemeinsamer Zyklen." Jahrbücher für Nationalökonomie und Statistik 214, no. 6 (January 1, 1995). http://dx.doi.org/10.1515/jbnst-1995-0604.

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SummaryThis paper is intended to explore a new way of analyzing macroeconomic datasets. For a dataset of twenty-one West German variables a common-trends-common-cycle representation is aimed at which allows for a multivariate Beveridge-Nelson decomposition of the data. However, standard F-tests reveal that the number of linearly independent cointegrating vectors plus the number of linearly independent serial correlation cofeature vectors do not add up to the dimension of the system. A slightly weaker notion of cofeature is used to derive an approximate trend-cycle decomposition. For most of the variables, this approximation seems to work quite well. Analysis of the cyclical components indicates that interest rates are procyclical with a lead and anticyclical with a lag. The real wage is at most very weakly procyclical and definitely not anticyclical, while the price level is procyclical.

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28

Cavicchioli, Maddalena. "A matrix approach to the Beveridge-Nelson decomposition of Markov-switching processes with applications to business cycle." Applied Economics Letters, November 3, 2020, 1–8. http://dx.doi.org/10.1080/13504851.2020.1841882.

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