This paper proposes the cross-quantilogram to measure the quantile dependence between two time series. We apply it to test the hypothesis that one time series has no directional predictability to another time series. We establish the asymptotic distribution of the cross-quantilogram and the corresponding test statistic. The limiting distributions depend on nuisance parameters. To construct consistent confidence intervals we employ a stationary bootstrap procedure; we establish consistency of this bootstrap. Also, we consider a self-normalized approach, which yields an asymptotically pivotal statistic under the null hypothesis of no predictability. We provide simulation studies and two empirical applications. First, we use the cross-quantilogram to detect predictability from stock variance to excess stock return. Compared to existing tools used in the literature of stock return predictability, our method provides a more complete relationship between a predictor and stock return. Second, we investigate the systemic risk of individual financial institutions, such as JP Morgan Chase, Morgan Stanley and AIG.

Galvanized by Greta Thunberg’s idea for Friday school strikes, “climate strikes” emerged in 2018 and 2019 as a form of youth social movement demanding far-reaching action on climate change. Youths have taken various actions to combat climate change, but academics have not paid sufficient attention to youth climate mobilization. This study thus examines the questions of what has motivated youth to mobilize and how they have shaped global climate politics and governance. This study focuses particularly on the narrative of youth activists to address their understanding of climate change and their ideas regarding how to respond to it. Youth collective action has succeeded in problematizing global climate inaction and inertia and in framing climate change from a justice perspective, but activists have faced limitations in converting their moral legitimacy into the power required for sweeping changes. Overall, this study demonstrates the emergence of young people as agents of change in the global climate change arena and the urgency of engaging them in climate change governance and policymaking.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may May 2013Abstract This paper investigates the asymptotic properties of the Gaussian quasi-maximum-likelihood estimators (QMLE's) of the GARCH model augmented by including an additional explanatory variable -the so-called GARCH-X model. The additional covariate is allowed to exhibit any degree of persistence as captured by its long-memory parameter d x ; in particular, we allow for both stationary and non-stationary covariates. We show that the QMLE's of the parameters entering the volatility equation are consistent and mixed-normally distributed in large samples. The convergence rates and limiting distributions of the QMLE's depend on whether the regressor is stationary or not. However, standard inferential tools for the parameters are robust to the level of persistence of the regressor with t-statistics following standard Normal distributions in large sample irrespective of whether the regressor is stationary or not.

This article employs the advocacy coalition framework (ACF), a set of concepts developed to account for policymaking primarily in the United States, to analyze factors that led China to downsize its latest big hydropower project, on the Nu River. The ACF helps us identify two conflicting coalitions based on their policy beliefs and the resources they mobilized to translate their beliefs into policy change, which the ACF also helps us explain. Conflict between state agencies contributed to the rise of a societally based environmental coalition to oppose a state-centered development coalition, and struggle and strategic learning between these coalitions led to interventions by the premier and a scaling down of the project from 13 dams to four.

The paper considers the GARCH-X process in which the covariate is generalized as a fractionally integrated process I (d) for 1=2 < d < 1=2 or 1=2 < d < 3=2: We investigate the asymptotic properties of this process, and show how it explains stylized facts of …nancial time series such as the long memory property in volatility, leptokurtosis and IGARCH. If the covariate is a long memory process, regardless that it is stationary or nonstationary, the autocorrelation of the squared process of the model generates the long memory property in volatility by following the trend commonly observed in real data. The asymptotic limit of the sample kurtosis of the GARCH-X process is larger than that of the GARCH(1,1) process unless the covariate is antipersistent. We also analyze the e¤ect of omitting the covariate that is nonstationary as well as persistent. Our analysis shows that, if the relevant covariate is omitted and the usual GARCH(1,1) model is …tted, then the model would be estimated approximately as the IGARCH. This may well explain the ubiquitous evidence of the IGARCH in empirical volatility analysis.