nep-ets New Economics Papers
on Econometric Time Series
Issue of 2006‒11‒04
eight papers chosen by
Yong Yin
SUNY at Buffalo

  1. Conditioning Information and Variance Bounds on Pricing Kernels with Higher-Order Moments: Theory and Evidence By Fousseni Chabi-Yo
  2. Log Periodogram Regression: The Nonstationary Case By Chang Sik Kim; Peter C. B. Phillips
  3. A Complete Asymptotic Series for the Autocovariance Function of a Long Memory Process By Offer Lieberman; Peter C.B. Phillips
  4. Adaptive Estimation of Autoregressive Models with Time-Varying Variances By Ke-Li Xu; Peter C. B. Phillips
  5. Factor-GMM Estimation with Large Sets of Possibly Weak Instruments By George Kapetanios; Massimiliano Marcellino
  6. Comparing alternative predictors based on large-panel factor models By Antonello D'Agostino; Domenico Giannone
  7. Is reversion to PPP in euro exchange rates non-linear? By Bernd Schnatz
  8. The Long Wave of Conditional Convergence By Tong, Jian

  1. By: Fousseni Chabi-Yo
    Abstract: The author develops a strategy for utilizing higher moments and conditioning information efficiently, and hence improves on the variance bounds computed by Hansen and Jagannathan (1991, the HJ bound) and Gallant, Hansen, and Tauchen (1990, the GHT bound). The author's bound incorporates variance risk premia. It reaches the GHT bound when non-linearities in returns are not priced. The author also provides an optimally scaled bound with conditioning information, higher moments, and variance risk premia that improves on the Bekaert and Liu (2004, the BL bound) optimally scaled bound. This bound reaches the BL bound when nonlinearities in returns are not priced. When the conditional first four moments are misspecified, the author's optimally scaled bound remains a lower bound to the variance on pricing kernels, whereas the BL bound does not. The author empirically illustrates the behaviour of the bounds using Bekaert and Liu's (2004) econometric models. He also uses higher moments and conditioning information to provide distance measures that improve on the Hansen and Jagannathan distance measures. The author uses these distance measures to evaluate the performance of asset-pricing models. Some existing pricing kernels are able to describe returns ignoring the impact of higher moments and variance risk premia. When accounting for the impact of higher moments and variance risk premia, these same pricing kernels have difficulty in explaining returns on the assets and are unable to price non-linearities or higher moments.
    Keywords: Financial markets; Market structure and pricing
    JEL: G12 G13 C61
    Date: 2006
  2. By: Chang Sik Kim; Peter C. B. Phillips
    Date: 2006–10–27
  3. By: Offer Lieberman; Peter C.B. Phillips
    Date: 2006–10–27
  4. By: Ke-Li Xu; Peter C. B. Phillips
    Date: 2006–10–27
  5. By: George Kapetanios (Queen Mary, University of London); Massimiliano Marcellino (IEP-Bocconi University, IGIER and CEPR)
    Abstract: This paper analyses the use of factor analysis for instrumental variable estimation when the number of instruments tends to infinity. We consider cases where the unobserved factors are the optimal instruments but also cases where the factors are not necessarily the optimal instruments but can provide a summary of a large set of instruments. Further, the situation where many weak instruments exist is also considered in the context of factor models. Theoretical results, simulation experiments and empirical applications highlight the relevance and simplicity of Factor-GMM estimation.
    Keywords: Factor models, Principal components, Instrumental variables, GMM, Weak instruments, DSGE models
    JEL: C32 C51 E52
    Date: 2006–10
  6. By: Antonello D'Agostino (Central Bank and Financial Services Authority of Ireland - Economic Analysis and Research Department, PO Box 559 - Dame Street, Dublin 2, Ireland.); Domenico Giannone (ECARES, Universit Libre de Bruxelles - CP 114 - av. Jeanne, 44, B-1050, Brussels, Belgium.)
    Abstract: This paper compares the predictive ability of the factor models of Stock and Watson (2002) and Forni, Hallin, Lippi, and Reichlin (2005) using a "large" panel of US macroeconomic variables. We propose a nesting procedure of comparison that clarifies and partially overturns the results of similar exercises in the literature. As in Stock and Watson (2002), we find that efficiency improvements due to the weighting of the idiosyncratic components do not lead to significant more accurate forecasts. In contrast to Boivin and Ng (2005), we show that the dynamic restrictions imposed by the procedure of Forni, Hallin, Lippi, and Reichlin (2005) are not harmful for predictability. Our main conclusion is that for the dataset at hand the two methods have a similar performance and produce highly collinear forecasts. JEL Classification: C31, C52, C53.
    Keywords: Factor Models, Forecasting, Large Cross-Section.
    Date: 2006–10
  7. By: Bernd Schnatz (European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.)
    Abstract: The paper tests for nonlinearities in the adjustment of the euro exchange rate towards purchasing power parity (PPP). It presents new survey based evidence consistent with non-linear patterns in euro exchange rate dynamics. Moreover, based on an exponential smooth transition autoregressive (ESTAR-) model, it finds strong evidence that the speed of mean reversion in euro exchange rates increases non-linearly with the magnitude of the PPP deviation. Accordingly, while the euro real exchange rate can be well approximated by a random walk if PPP deviations are small, in periods of significant deviations, gravitational forces are set to take root and bring the exchange rate back towards its long-term trend. Consistent with higher euro-dollar volatility, deviations from the PPP equilibrium for this pair need to be stronger in order to reach the same adjustment intensity as for other currencies. JEL Classification: F31.
    Keywords: Purchasing power parity, real exchange rate, non-linearities, STAR models.
    Date: 2006–10
  8. By: Tong, Jian
    Abstract: We calculate the time series of the speed of convergence for 21 high-income countries over the period: 1953-1996, using low-pass filtered time series of per-capita GDP which are thus isolated from the influence of the short-run business cycle components. The observed patterns contradict the conventional ‘time-invariant speed of convergence’ hypothesis. Furthermore, dynamic panel data analysis provides strong evidence of the existence of stationary long cycles in the per capita GDP time series. We develop and estimate a technology-diffusion-based endogenous growth model, which shows that the endogenous growth of the domestic knowledge stock can account for the long cycles observed in the data. Keywords; trend reversion, speed of convergence, growth cycles

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