Numerous tests designed to detect realized jumps over a fixed time span have been proposed and extensively studied in the financial econometrics literature. These tests differ from 'long time span tests' that detect jumps by examining the magnitude of the jump intensity parameter in the data...

This paper deals with instability in regression coefficients. We propose a Bayesian regression model with time-varying coefficients (TVC) that allows to jointly estimate the degree of instability and the time-path of the coefficients. Thanks to the computational tractability of the model and to...

We introduce conditional score residuals and provide a general framework for the diagnostic analysis of time series models. A key feature of conditional score residuals is that they account for the shape of the conditional distribution. These residuals offer reliable and powerful diagnostic...

This paper investigates the quality of preliminary figures in the Norwegian national accounts. To address the problem of few observations in such analyses, we use some recently developed system tests. Preliminary figures for gross fixed capital formation (investments) under-predict the final...

This paper analyses the stochastic properties of UK nominal and real wages over the period 1750-2015 using fractional integration techniques. Both the original series and logged ones are analysed. The results generally suggest that nominal wages exhibit a higher degree of persistence, which...

This work built on financial literature on rolling window Granger-causality testing (RWGCT) methodology, specifically expanding its early theme of speculative trading which emerged in 2009 following the food price crisis. Although many times driving the commodity prices in reality, the...

This paper finds that global temperature anomalies are characterised by (temporary) explosiveness, a statistical feature typically found in financial and commodity market data during episodes of extreme price increases. This finding dramatically illustrates the extent temperature changes have...

We develop methods to obtain optimal forecast under long memory in the presence of a discrete structural break based on different weighting schemes for the observations. We observe significant changes in the forecasts when long-range dependence is taken into account. Using Monte Carlo...

We investigate the information theoretic optimality properties of the score function of the predictive likelihood as a device to update parameters in observation driven time-varying parameter models. The results provide a new theoretical justification for the class of generalized autoregressive...

We develop a new parameter stability test against the alternative of observation driven generalized autoregressive score dynamics. The new test generalizes the ARCH-LM test of Engle (1982) to settings beyond time-varying volatility and exploits any autocorrelation in the likelihood scores under...