Intro -- Contents -- I. INTRODUCTION -- II. THE NONACCELERATING INFLATION RATE OF FACTOR UTILIZATION -- III. FACTOR …

-looking specifications, especially when targeting core components of GDP and inflation, and combine the best parts of efficiency …

inflation than output growth. Our estimated dynamic policy coefficients characterize the style of policy as a ""bang …

Intro -- Contents -- I. INTRODUCTION -- II. TAXONOMY OF UNDERLYING INFLATION INDICATORS -- III. FEATURES OF THE …

Intro -- Contents -- I. INTRODUCTION -- II. INFLATION AND MONETARY POLICY IN THE KYRGYZ REPUBLIC -- III. SEASONAL … CHARACTERISTICS OF CONSUMER PRICES -- IV. MODELING AND FORECASTING INFLATION -- V. CONCLUDING REMARKS -- References -- Appendix …

the analysis, and demonstrates how to decompose the output gap into contributions of observed data on output, inflation …

This paper forecasts inflation in Sudan following two methodologies: the Autoregressive Moving Average (ARMA) model and … by looking at the leading indicators of inflation. The estimated ARMA model remarkably tracks the actual inflation during … indicators explaining inflation in Sudan. Inflation forecasts based on both approaches suggest that inflationary pressures for …

machine learning (ML) models to forecast near-term core inflation in Japan post-pandemic. Japan is a challenging case, because …Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and … inflation had been muted until 2022 and has now risen to a level not seen in four decades. Four machine learning models are …

We examine whether changes in the distribution of household inflation expectations contain information on future … inflation. We first discuss recent shifts in micro data from the US, UK, Germany, and Canada. We then zoom in on the US to … explore econometrically whether distributional characteristics help predict future inflation. We find that the shape of the …