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on Econometric Time Series |
| By: | George Kapetanios; M. Hashem Pesaran |
| Abstract: | This paper considers alternative approaches to the analysis of large panel data models in the presence of error cross section dependence. A popular method for modelling such dependence uses a factor error structure. Such models raise new problems for estimation and inference. This paper compares two alternative methods for carrying out estimation and inference in panels with a multifactor error structure. One uses the correlated common effects estimator that proxies the unobserved factors by cross section averages of the observed variables as suggested by Pesaran (2004), and the other uses principal components following the work of Stock and Watson (2002). The paper develops the principal component method and provides small sample evidence on the comparative properties of these estimators by means of extensive Monte Carlo experiments. An empirical application to company returns provides an illustration of the alternative estimation procedures. |
| Keywords: | cross section dependence, large panels, principal components, common correlated effects, return equations |
| JEL: | C12 C13 C33 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_1416&r=ets |
| By: | Stephane Dees; Filippo di Mauro; M. Hashem Pesaran; L. Vanessa Smith |
| Abstract: | This paper presents a global model linking individual country vector error-correcting models in which the domestic variables are related to the country-specific variables as an approximate solution to a global common factor model. This global VAR is estimated for 26 countries, the euro area being treated as a single economy. This paper proposes two important extensions of previous research (see Pesaran, Schuermann and Weiner, 2004). First, it provides a theoretical framework where the GVAR is derived as an approximation to a global unobserved common factor model. Also using average pair-wise cross-section error correlations, the GVAR approach is shown to be quite effective in dealing with the common factor interdependencies and international comovements of business cycles. Second, in addition to generalised impulse response functions, we propose an identification scheme to derive structural impulse responses. We focus on identification of shocks to the US economy, particularly the monetary policy shocks, and consider the time profiles of their effects on the euro area. To this end we include the US model as the first country model and consider alternative orderings of the US variables. Further to the US monetary policy shock, we also consider oil price, US equity and US real output shocks. |
| Keywords: | Global VAR (GVAR), global interdependencies, global macroeconomic modeling, impulse responses |
| JEL: | C32 E17 F47 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_1425&r=ets |
| By: | Ekaterini Panopoulou; |
| Abstract: | This paper attempts a resolution of the Fisher effect puzzle in terms of estimator choice. Using both short-term and long-term interest rates for 14 OECD countries, we find ample evidence supporting the existence of a long-run Fisher effect in which interest rates move oneto- one with inflation. Our results suggest that the reason why the Fisher effect has not found support internationally lies on the estimation method. When the hypothesis of a unit coefficient relating interest rates to expected inflation is tested within the Autoregressive Distributed Lag (ADL) framework, which is invariant to the integration properties of the data, the Fisher effect easily survives the empirical evidence. Similar, but less robust, results are reached on the grounds of the Pre-Whitened Fully Modified Least Squares (PW-FMLS) or the Johansen’s (JOH) estimators. |
| Keywords: | Cointegration Estimators; Fisher Effect; ADL; DOLS; Small-sample properties |
| Date: | 2005–04–20 |
| URL: | http://d.repec.org/n?u=RePEc:iis:dispap:iiisdp067&r=ets |
| By: | Takao Kobayashi (Faculty of Economics, University of Tokyo); Seisho Sato (Department of Prediction and Control, Institute of Statistical Mathematics); Akihiko Takahashi (Faculty of Economics, University of Tokyo) |
| Abstract: | This paper proposes a new approach to style analysis by utilizing a general state space model and Monte Carlo filter. In particular,We regard coefficients of style indices as state variables in the state space model and apply Monte Carlo filter as estimation method. Moreover, an empirical analysis using actual funds' data confirms the validity of our approach. |
| Date: | 2005–04 |
| URL: | http://d.repec.org/n?u=RePEc:tky:fseres:2005cf337&r=ets |