117 research outputs found

    Periodic Properties of Interpolated Time Series

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    Although linearly interpolated series are often used in economics, little has been done to examine the effects of interpolation on time series properties and on statistical inference. We show that linear interpolation of a trend tationary series superimposes a ‘periodic’ structure on the moments of the series. Using conventional time series methods to make inference about the interpolated series may therefore be invalid. Also, the interpolated series may exhibit more shock persistence than the original trend stationary series.Linear Interpolation, Trend-Stationary Series, Shock Persistence, Periodic Properties of Time Series

    On the Typical Spectral Shape of an Economic Variable

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    In a classic article, Granger (1966) asserted that most economic time series measured in level have spectra that exhibit a smooth declining shape with considerable power at very low frequencies. There has been no systematic attempt to examine Granger,s assertion with international data. We estimate output level spectra for 58 countries, divided into developed, high-income developing, and low-income developing groups. We find the shapes of the estimated spectra to be strikingly similar to Granger"s typical shape, particularly for the developed countries.Spectral Analysis, Spectral Shape, Output Level, OECD, Developing Countries.

    Testing for speculative bubbles in stock prices

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    A modification of Kenneth West's method for investigating speculative bubbles in stock prices, in which a direct test of the "no bubble" hypothesis is applied to long-term annual U.S. stock-market data.Stock - Prices

    International Evidence on Output Fluctuation and Shock Persistence

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    We estimate output growth rate spectra for 58 countries. The spectra exhibit diverse shapes. To study the sources of this diversity, we estimate the short-run, business cycle, and long-run frequency components of the sampled series. For most OECD countries the bulk of the spectral mass is in the business cycle frequency band, and the magnitude of this cyclical component increases with income. For the developing countries, however, the spectral mass is not concentrated in the business cycle frequency band, and the income-cycle relationship is not as strong. We also estimate two frequency domain measures of shock persistence and find both measures to vary considerably across countries, with the U.S. having the lowest estimates. For the OECD countries most of the variation in the variance ratio statistic appears to be explained by the variation in the long-term growth component.Business Cycles, Developing Countries, OECD Countries, Output Fluctuation, Output Growth, Shock Persistence, Spectral Analysis, Frequency Domain, Short Run, Long Run, Frequency Component, Income-Cycle Relationship, Variance Ratio Statistic

    International Evidence on Output Fluctuation and Shock Persistence

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    We estimate output growth rate spectra for 58 countries. The spectra exhibit diverse shapes. To study the sources of this diversity, we estimate the short-run, business cycle, and long-run frequency components of the sampled series. For most OECD countries the bulk of the spectral mass is in the business cycle frequency band, and the magnitude of this cyclical component increases with income. For the developing countries, however, the spectral mass is not concentrated in the business cycle frequency band, and the income-cycle relationship is not as strong. We also estimate two frequency domain measures of shock persistence and find both measures to vary considerably across countries, with the U.S. having the lowest estimates. For the OECD countries most of the variation in the variance ratio statistic appears to be explained by the variation in the long-term growth component.-Business Cycles, Developing Countries, OECD Countries, Output Growth, Shock Persistence, and Spectral Analysis.

    Interpolation and Shock Persistence of Prewar U.S. Macroeconomic Time Series: A Reconsideration

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    The U.S. prewar output series exhibit smaller shock-persistence than postwar-series. Some studies suggest that this may be due to linear interpolation used to generate missing prewar data. Monte Carlo simulations that support this view generate large standard-errors, making such inference imprecise. We assess analytically the effect of linear interpolation on a nonstationary process. We find that interpolation indeed reduces shock-persistence, but the interpolated series can still exhibit greater shock-persistence than a pure random walk. Moreover, linear interpolation makes the series periodically nonstationary, with parameters of the data generating process and the length of the interpolation time-segments affecting shock-persistence in conflicting ways
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