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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only On the past, present, and future of the Diebold-Yilmaz approach to dynamic network connectedness(Elsevier Science Sa, 2023) Diebold, Francis X.; Department of Economics; Yılmaz, Kamil; Department of Economics; College of Administrative Sciences and EconomicsWe offer retrospective and prospective assessments of the Diebold-Yilmaz connected-ness research program, combined with personal recollections of its development. Its centerpiece in many respects is Diebold and Yilmaz (2014), around which our discussion is organized.Publication Metadata only On the network topology of variance decompositions: measuring the connectedness of financial firms (Reprinted from Journal of Econometrics, Vol 182, Issue 1, September 2014, Pages 119-134)(Elsevier Science Sa, 2023) Diebold, Francis X.; Department of Economics; Yılmaz, Kamil; Department of Economics; College of Administrative Sciences and EconomicsWe propose several connectedness measures built from pieces of variance decomposi-tions, and we argue that they provide natural and insightful measures of connectedness. We also show that variance decompositions define weighted, directed networks, so that our connectedness measures are intimately related to key measures of connectedness used in the network literature. Building on these insights, we track daily time-varying connectedness of major U.S. financial institutions' stock return volatilities in recent years, with emphasis on the financial crisis of 2007-2008.Publication Metadata only Bridging the Covid-19 data and the epidemiological model using the time-varying parameter SIRD model(Elsevier Sci Ltd, 2024) Şimşek, Yasin; Department of Economics; Çakmaklı, Cem; Department of Economics; College of Administrative Sciences and EconomicsThis paper extends the canonical model of epidemiology, the SIRD model, to allow for timevarying parameters for real-time measurement and prediction of the trajectory of the Covid-19 pandemic. Time variation in model parameters is captured using the score -driven modeling structure designed for the typical daily count data related to the pandemic. The resulting specification permits a flexible yet parsimonious model with a low computational cost. The model is extended to allow for unreported cases using a mixed -frequency setting. Results suggest that these cases' effects on the parameter estimates might be sizeable. Full sample results show that the flexible framework accurately captures the successive waves of the pandemic. A realtime exercise indicates that the proposed structure delivers timely and precise information on the pandemic's current stance. This superior performance, in turn, transforms into accurate predictions of the death cases and cases treated in Intensive Care Units (ICUs).Publication Metadata only Long-run equilibrium and short-run dynamics between risk exposure and highway safety(Physica-Verlag Gmbh & Co, 2012) McCarthy, Patrick; Department of Economics; Kılıç, Rehim; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; N/ABased upon monthly California data, this exploratory analysis uses vector error correction methods and associated statistical tests to identify the long-run relationship and the short-run dynamics between highway exposure and crashes. The analysis finds that there is a cointegrating relationship between exposure and crashes, and for fatal, serious injury, and materials crashes, could not reject the hypothesis that crash exposure and frequency move proportionately. The analysis indicates that vector error correction models may be an important tool for improving our understanding of highway crashes and the near and longer term impacts of alternative safety policies.Publication Metadata only Testing for a unit root in a stationary ESTAR process(Taylor & Francis Inc, 2011) N/A; Department of Economics; Kılıç, Rehim; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; N/AThis article develops a statistic for testing the null of a linear unit root process against the alternative of a stationary exponential smooth transition autoregressive model. The asymptotic distribution of the test is shown to be nonstandard but nuisance parameter-free and hence critical values are obtained by simulations. Simulations show that the proposed statistic has considerable power under various data generating scenarios. Applications to real exchange rates also illustrate the ability of our test to reject null of unit root when some of the alternative tests do not.Publication Metadata only On the past, present, and future of the Diebold–Yilmaz approach to dynamic network connectedness(Elsevier Ltd, 2023) Diebold, F. X.; Department of Economics; Yılmaz, Kamil; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; 6111We offer retrospective and prospective assessments of the Diebold–Yilmaz connectedness research program, combined with personal recollections of its development. Its centerpiece in many respects is Diebold and Yilmaz (2014), around which our discussion is organized.Publication Metadata only Weak convergence to a matrix stochastic integral with stable processes(Cambridge Univ Press, 1997) Department of Economics; Caner, Mehmet; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; N/AThis paper generalizes the univariate results of Chan and Tran (1989, Econometric Theory 5, 354-362) and Phillips (1990, Econometric Theory 6, 44-62) to multivariate time series. We develop the limit theory for the least-squares estimate of a VAR(1) for a random walk with independent and identically distributed errors and for I(1) processes with weakly dependent errors whose distributions are in the domain of attraction of a stable law. The limit laws are represented by functionals of a stable process. A semiparametric correction is used in order to asymptotically eliminate the ''bias'' term in the limit law. These results are also an extension of the multivariate limit theory for square-integrable disturbances derived by Phillips and Durlauf (1986, Review of Economic Studies 53, 473-495). Potential applications include tests for multivariate unit roots and cointegration.Publication Metadata only Parameter estimation in nonlinear AR-GARCH models(Cambridge Univ Press, 2011) Saikkonen, Pentti; Department of Economics; Meitz, Mika; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; N/AThis paper develops an asymptotic estimation theory for nonlinear autoregressive models with conditionally heteroskedastic errors. We consider a general nonlinear autoregression of order p (AR(p)) with the conditional variance specified as a general nonlinear first-order generalized autoregressive conditional heteroskedasticity (GARCH(1,1)) model. We do not require the rescaled errors to be independent, but instead only to form a stationary and ergodic martingale difference sequence. Strong consistency and asymptotic normality of the global Gaussian quasi-maximum likelihood (QML) estimator are established under conditions comparable to those recently used in the corresponding linear case. To the best of our knowledge, this paper provides the first results on consistency and asymptotic normality of the QML estimator in nonlinear autoregressive models with GARCH errors.Publication Metadata only Reprint of: on the network topology of variance decompositions: measuring the connectedness of financial firms(Elsevier Ltd, 2023) Diebold, F. X.; Department of Economics; Yılmaz, Kamil; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; 6111We propose several connectedness measures built from pieces of variance decompositions, and we argue that they provide natural and insightful measures of connectedness. We also show that variance decompositions define weighted, directed networks, so that our connectedness measures are intimately related to key measures of connectedness used in the network literature. Building on these insights, we track daily time-varying connectedness of major U.S. financial institutions’ stock return volatilities in recent years, with emphasis on the financial crisis of 2007–2008.Publication Metadata only Partial derivatives, comparative risk behavior and concavity of utility functions(Elsevier, 2003) N/A; Department of Economics; Lajeri-Chaherli, Fatma; Faculty Member; Department of Economics; College of Administrative Sciences and Economics; N/AWe use the comparative risk behavior of the partial derivatives to address a long standing problem in mean-variance analysis: What does the concavity of utility functions mean? It is well known that, when mean-variance preferences are derived from expected utility and normal distributions, concavity is equivalent to decreasing prudence. In this paper, we derive conditions that link concavity to prudence in a general mean-standard deviation case.