A growing literature uses changes in residual volatility for identifying structural shocks in vector autoregressive (VAR) analysis. A number of different models for heteroskedasticity or conditional heteroskedasticity are proposed and used in applications in this context. This study reviews the...

The paper considers the Markov-Switching GARCH(1,1)-model with time-varying transition probabilities. It derives sufficient conditions for the square of the process to display long memory and provides some additional intuition for the empirical observation that estimated GARCH-parameters often...

On 21 July 2005 China adopted an undisclosed basket exchange rate regime. We formally assess and envisage the gradual evolution of the renminbi over time. We utilize nonlinear dependencies in the renminbi exchange rate and describe the smooth transition of the renminbi/U.S. dollar (RMB/USD)...

This paper is concerned with carbon price volatility and the underlying causes of large price movements in the European emissions trading market. Based on the application of a combined jump-GARCH model the behavior of EUA prices is characterized. The jump-GARCH model explains the unsteady carbon...

This paper investigates the time-varying impact of oil price uncertainty on stock prices in China using weekly data on ten sectoral indices over the period January 1997-Febraury 2014. The estimation of a bivariate VAR-GARCH-in-mean model suggests that oil price volatility affects stock returns...

This paper estimates a time-varying AR-GARCH model of inflation producing measures of inflation uncertainty for the euro area, and investigates the linkages between them in a VAR framework, also allowing for the possible impact of the policy regime change associated with the start of EMU in...

This paper aims to select the best model or set of models for modelling volatility of the four most popular cryptocurrencies, i.e. Bitcoin, Ethereum, Ripple and Litecoin. More than 1,000 GARCH models are fitted to the log returns of the exchange rates of each of these cryptocurrencies to...

The paper explores the effect of measurement errors on the estimation of a linear panel data model. The conventional fixed effects estimator, which ignores measurement errors, is biased. By correcting for the bias one can construct consistent and asymptotically normal estimators. In addition, we...

This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial autoregressive disturbances, SARAR(R,S). We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM)...

This paper considers the estimation problem of structural models for which empirical restrictions are characterized by a fixed point constraint, such as structural dynamic discrete choice models or models of dynamic games. We analyze the conditions under which the nested pseudo-likelihood (NPL)...