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Macroeconomic Time Series (macroeconomic + time_series)
Selected AbstractsTesting Stochastic Cycles in Macroeconomic Time SeriesJOURNAL OF TIME SERIES ANALYSIS, Issue 4 2001L. A. Gil-Alana A particular version of the tests of Robinson (1994) for testing stochastic cycles in macroeconomic time series is proposed in this article. The tests have a standard limit distribution and are easy to implement in raw time series. A Monte Carlo experiment is conducted, studying the size and the power of the tests against different alternatives, and the results are compared with those based on other tests. An empirical application using historical US annual data is also carried out at the end of the article. [source] Measuring predictability: theory and macroeconomic applicationsJOURNAL OF APPLIED ECONOMETRICS, Issue 6 2001Francis X. Diebold We propose a measure of predictability based on the ratio of the expected loss of a short-run forecast to the expected loss of a long-run forecast. This predictability measure can be tailored to the forecast horizons of interest, and it allows for general loss functions, univariate or multivariate information sets, and covariance stationary or difference stationary processes. We propose a simple estimator, and we suggest resampling methods for inference. We then provide several macroeconomic applications. First, we illustrate the implementation of predictability measures based on fitted parametric models for several US macroeconomic time series. Second, we analyze the internal propagation mechanism of a standard dynamic macroeconomic model by comparing the predictability of model inputs and model outputs. Third, we use predictability as a metric for assessing the similarity of data simulated from the model and actual data. Finally, we outline several non-parametric extensions of our approach. Copyright © 2001 John Wiley & Sons, Ltd. [source] A simultaneous test of unit root and level changeJOURNAL OF FORECASTING, Issue 3 2010Duk Bin Jun Abstract Testing the existence of unit root and/or level change is necessary in order to understand the underlying processes of time series. In many studies carried out so far, the focus was only on a single aspect of unit root and level change, therefore limiting a full assessment of the given problems. Our study aims to find a solution to the given problems by testing the two hypotheses simultaneously. We derive the likelihood ratio test statistic based on the state space model, and their distributions are created by the simulation method. The performance of the proposed method is validated by simulated time series and also applied to two Korean macroeconomic time series to confirm its practical application. This analysis can provide a solution to determine the underlying structure of arguable time series. Copyright © 2009 John Wiley & Sons, Ltd. [source] Forecast accuracy and economic gains from Bayesian model averaging using time-varying weightsJOURNAL OF FORECASTING, Issue 1-2 2010Lennart Hoogerheide Abstract Several Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time-varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time series. The results indicate that the proposed time-varying model weight schemes outperform other combination schemes in terms of predictive and economic gains. In an empirical application using returns on the S&P 500 index, time-varying model weights provide improved forecasts with substantial economic gains in an investment strategy including transaction costs. Another empirical example refers to forecasting US economic growth over the business cycle. It suggests that time-varying combination schemes may be very useful in business cycle analysis and forecasting, as these may provide an early indicator for recessions. Copyright © 2009 John Wiley & Sons, Ltd. [source] Stochastic Volatility in a Macro-Finance Model of the U.S. Term Structure of Interest Rates 1961,2004JOURNAL OF MONEY, CREDIT AND BANKING, Issue 6 2008PETER D. SPENCER affine term structure model; macro finance; unit root; stochastic volatility This paper generalizes the standard homoscedastic macro-finance model by allowing for stochastic volatility, using the "square root" specification of the mainstream finance literature. Empirically, this specification dominates the standard model because it is consistent with the square root volatility found in macroeconomic time series. Thus it establishes an important connection between the stochastic volatility of the mainstream finance model and macro-economic volatility of the Okun,Friedman type. This research opens the way to a richer specification of both macro-economic and term structure models, incorporating the best features of both macro-finance and mainstream finance models. [source] Pooling-Based Data Interpolation and BackdatingJOURNAL OF TIME SERIES ANALYSIS, Issue 1 2007Massimiliano Marcellino C32; C43; C82 Abstract., Pooling forecasts obtained from different procedures typically reduces the mean square forecast error and more generally improve the quality of the forecast. In this paper, we evaluate whether pooling-interpolated or-backdated time series obtained from different procedures can also improve the quality of the generated data. Both simulation results and empirical analyses with macroeconomic time series indicate that pooling plays a positive and important role in this context also. [source] Testing Stochastic Cycles in Macroeconomic Time SeriesJOURNAL OF TIME SERIES ANALYSIS, Issue 4 2001L. A. Gil-Alana A particular version of the tests of Robinson (1994) for testing stochastic cycles in macroeconomic time series is proposed in this article. The tests have a standard limit distribution and are easy to implement in raw time series. A Monte Carlo experiment is conducted, studying the size and the power of the tests against different alternatives, and the results are compared with those based on other tests. An empirical application using historical US annual data is also carried out at the end of the article. [source] Some Preliminary Findings on Hong Kong Business CyclesPACIFIC ECONOMIC REVIEW, Issue 1 2001Chi Fai Leung This paper presents some preliminary quantitative findings on the characteristics of business cycles in Hong Kong. The recently developed "approximate bandpass filter" is used to extract the fluctuations at business cycle frequencies (8 to 32 quarters) of macroeconomic time series. Based on the filtered time series, the paper identifies the cyclical turning points, describes the pattern of output fluctuations, and examines the co-movement of various macroeconomic variables. [source] AN ANALYSIS OF MONETARY POLICY SHOCKS IN JAPAN: A FACTOR AUGMENTED VECTOR AUTOREGRESSIVE APPROACH,THE JAPANESE ECONOMIC REVIEW, Issue 4 2007MASAHIKO SHIBAMOTO This paper analyses monetary policy shocks in Japan using a factor augmented vector autoregressive approach. There are three main findings. First, the time lags with which the monetary policy shocks are transmitted vary between the various macroeconomic time series. These include several series that have not been included thus far in standard vector autoregressive analysis, including housing starts and employment indices. Second, a coherent picture of monetary policy effects on the economy is obtained. Third, it is found that monetary policy shocks have a stronger impact on real variables, such as employment and housing starts, than industrial production. [source] | ||||||||||