This paper mainly studies the effect of deregulation on prices and quantity. For this aim, we employ cointegration methodology with structural breaks to empirically investigate the simultaneous relationship between deregulation, ticket prices, and the number of passengers in the Turkish airline...

This paper revisits inflation forecasting using reduced form Phillips curve forecasts, i.e., inflation forecasts using activity and expectations variables. We propose a Phillips curve-type model that results from averaging across different regression specifications selected from a set of...

This paper proposes a Bayesian estimation framework for a typical multi-factor model with time-varying risk exposures to macroeconomic risk factors and corresponding premia to price U.S. stocks and bonds. The model assumes that risk exposures and idiosynchratic volatility follow a break-point...

This paper examines the possibility of unit roots in the presence of endogenously determined multiple structural breaks in the total, female and male labour force participation rates (LFPR) for Australia, Canada and the USA. We extend the procedure of Gil-Alana (2008) for single structural break...

Instead of relying on descriptive statistics to evaluate the permanence of a fiscal contraction, this paper suggests that this issue should be studied using tests for structural breaks in cointegrating relationships between taxes and spending. We label a fiscal contraction as 'permanent' if a...

We test for state-dependent bias in the European Central Bank's inflation projections. We show that the ECB tends to underpredict when the observed inflation rate at the time of forecasting is higher than an estimated threshold of 1.8%. The bias is most pronounced at intermediate forecasting...

The transition to a cleaner energy mix, essential for achieving net-zero greenhouse gas emissions by 2050, will significantly increase demand for metals critical to renewable energy technologies. Energy Transition Metals (ETMs), including copper, lithium, nickel, cobalt, and rare earth elements,...

We develop metrics based on Shapley values for interpreting time-series forecasting models, including "black-box" models from machine learning. Our metrics are model agnostic, so that they are applicable to any model (linear or nonlinear, parametric or nonparametric). Two of the metrics,...

When alternatives are compared using an estimated criterion function, this may introduce a discrepancy between the true and the estimated criterion. In this paper, we consider a situation where a preordering (ranking) of stochastic sequences is defined from expected loss/gain, using a parametric...

In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric kernel estimators of the aforementioned...