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on Econometrics |
| By: | Carlos Enrique Carrasco GutiÃÂÃÂÃÂérrez; Reinaldo Castro Souza; Osmani Teixeira de Carvalho GuillÃÂÃÂÃÂén |
| Abstract: | An important aspect of empirical research based on the vector autoregressive (VAR) model is the choice of the lag order, since all inference in the VAR model depends on the correct model specification. Literature has shown important studies of how to select the lag order of a nonstationary VAR model subject to cointegration restrictions. In this work, we consider an additional weak form (WF) restriction of common cyclical features in the model in order to analyze the appropriate way to select the correct lag order. Two methodologies have been used: the traditional information criteria (AIC, HQ and SC) and an alternative criterion (IC(p,s)) which select simultaneously the lag order p and the rank structure s due to the WF restriction. A Monte-Carlo simulation is used in the analysis. The results indicate that the cost of ignoring additional WF restrictions in vector autoregressive modeling can be high, especially when SC criterion is used. |
| Date: | 2007–06 |
| URL: | http://d.repec.org/n?u=RePEc:bcb:wpaper:139&r=ecm |
| By: | Flavio Cunha; James J. Heckman; Salvador Navarro |
| Abstract: | This paper extends the widely used ordered choice model by introducing stochastic thresholds and interval-specific outcomes. The model can be interpreted as a generalization of the GAFT (MPH) framework for discrete duration data that jointly models durations and outcomes associated with different stopping times. We establish conditions for nonparametric identification. We interpret the ordered choice model as a special case of a general discrete choice model and as a special case of a dynamic discrete choice model. |
| JEL: | C31 |
| Date: | 2007–07 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberte:0340&r=ecm |
| By: | Pesaran, B.; Pesaran, M.H. |
| Abstract: | This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and suggests the use of devolatized returns computed as returns standardized by realized volatilities rather than by GARCH type volatility estimates. The t-DCC estimation procedure is applied to a portfolio of daily returns on currency futures, government bonds and equity index futures. The results strongly reject the normal-DCC model in favour of a t-DCC specification. The t-DCC model also passes a number of VaR diagnostic tests over an evaluation sample. The estimation results suggest a general trend towards a lower level of return volatility, accompanied by a rising trend in conditional cross correlations in most markets; possibly reflecting the advent of euro in 1999 and increased interdependence of financial markets. |
| Keywords: | Volatilities and Correlations, Futures Market, Multivariate t, Financial Interdependence, VaR diagnostics. |
| JEL: | C51 C52 G11 |
| Date: | 2007–06 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:0734&r=ecm |
| By: | Yang, H.; Pollitt, M. |
| Abstract: | There are two difficulties in doing an objective evaluation of the performance of decision-making units (DMUs). The first one is how to treat undesirable outputs jointly produced with the desirable outputs, and the second one is how to treat uncontrollable variables, which often capture the impact of the operating environment. Given difficulties in both model construction and data availability, very few published papers simultaneously consider the above two problems. This article attempts to do so by proposing six DEA-based performance evaluation models based on a research sample of the Chinese coal-fired power plants. The finding of this paper not only contributes for the performance measurement methodology, but also has policy implications for the Chinese coal-fired power sector. |
| Keywords: | Data envelopment analysis, performance measurement, technical efficiency, electricity |
| Date: | 2007–07 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:0733&r=ecm |