The CDS-bond basis quantifies the difference in risk premia between credit default swap (CDS) and bond markets. It is hard to measure at the individual firm level given substantial missing-value problems (30%-100%) in either or both markets, even for highly liquid blue-chip financial firms. We...

Aim of this study is to examine the coherence of consumer price indices (CPI) variants in Pakistan using time series data. The techniques of data analysis are descriptive statistics and wavelet analysis. Plots of CPI variants show more frequent changes as compared to the base year / month from...

This paper introduces a novel approach to simulation smoothing for nonlinear and non-Gaussian state space models. It allows for computing smoothed estimates of the states and nonlinear functions of the states, as well as visualizing the joint smoothing distribution. The approach combines...

The natural rate of interest, often interpreted as the equilibrium real interest rate, serves as a critical benchmark for evaluating the stance of monetary policy. This paper investigates the natural rate of interest in Uzbekistan using three econometric approaches: the HLW-type model1 , a...

This paper studies the effects of key underlying macroeconomic variables on the trend inflation rate in the USA. To do so, we consider eight structural shocks that incorporate a broad set of information for the US economy and that can be regarded as the main structural determinants of the...

Wavelet coherence analysis (WCA) examines the dynamic interactions between economic policy uncertainty (EPU) in Brazil, Chile, Colombia, and Mexico and key external variables, using monthly data from 2010 to 2022. The findings reveal the following: (i) medium-term co-movements (4-16 months)...

This paper addresses the challenge of inflation forecasting by adopting a thick modeling approach that integrates forecasts from time- and frequency-domain models. Frequency-domain models excel at capturing long-term trends while also accounting for short-term fluctuations. Combining these...

Standard nowcasting frameworks commonly use weekly or monthly variables to monitor quarterly gross domestic product (GDP). However, this method is not suitable for economies that track GDP annually. We modify the state-space representation of an otherwise standard dynamic factor model to...

The COVID-19 pandemic and the implementation of strict lockdown measures have significantly impacted various dimensions of the global economy. This study examines the impact of COVID-19 and lockdown stringency on exchange rate volatility in India using three core variables, i.e., COVID-19 cases,...

We estimate a New Keynesian model that allows endogenous transitions between a target equilibrium, with inflation fluctuating around the central bank's target and interest rates typically positive, and a low-inflation equilibrium, where the effective lower bound binds and de-anchored...

The energy-intensive nature of urban transport systems plays a major role in environmental decline, emphasizing the urgent need to foster sustainable energy adoption. This study takes Macao as an example and uses wavelet coherence to analyze the relationship between transportation and energy...

The paper compares two forecasts of Slovak GDP, the first with high-frequency data and the second without them. We utilize the last observation from the economic activity index acting as a short-term GDP forecast. We use data from 2000 to 2024 in weekly frequencies and have 27 variables related...

The return of high inflation in Latin America (and worldwide) since 2021 has renewed concerns about the persistence of above-target inflation and a potential de-anchoring of inflation expectations. This paper shows that trend inflation estimation using forward-looking information can offer...

We used daily return series for three pairs of datasets from the crude oil markets (WTI and Brent), stock indices (the Dow Jones Industrial Average and S&P 500), and benchmark cryptocurrencies (Bitcoin and Ethereum) to examine the connections between various data during the COVID-19 pandemic. We...

The study applies the wavelet local multiple correlations to investigate the level of comovements among the tail risks of US and emerging Asian stock markets in both time and frequency domains. Through this empirical investigation, we address the question of how the transmission of tail risk...

This paper makes a twofold contribution. First, it develops the dynamic factor model of by allowing for fractional integration instead of imposing the classical dichotomy between I(0) stationary and I(1) non-stationary series. This more general setup provides valuable information on the degree...

Purpose - This study aims to reassess the dynamics of major cryptocurrencies sur-rounding recent economic and geopolitical events. By employing wavelet analysis and quantile regression methods, it seeks to understand the behavior of cryptocurrencies before, during, and after the COVID-19...