Inflation is a process of continuous increase in the price goods or an economic situation that shows tendency to level general. One way control inflation use forecasting. Forecasting activity predict future events. Related forecasting, method can be used forecasting time series data Indonesia fuzzy Lee's logic. This study aims apply Fuzzy Time Series period January 2014 December 2022. The resul...

Standard macroeconomic forecasting indicators and techniques tend to perform poorly in predicting inflation in the short-run. The present paper shows that microeconomic price data placed in an empirical model rooted in (S,s) pricing theory convey extra information on inflation dynamics. The empirical model designed to capture the deviation between target and actual price, potentially applicable...

This paper presents out-of-sample inflation forecasting results based on relative price variability and skewness. It is demonstrated that forecasts on long horizons of 1.5-2 years are significantly improved if the forecast equation is augmented with skewness. JEL: E17, E31, C43

This paper compares three reduced-form models of heterogeneity in survey inflation expectations. On the one hand, we specify two models of forecasting inflation based on limited information flows of the type developed in Mankiw and Reis [2002. Sticky information versus sticky prices: a proposal to replace the new Keynesian Phillips curve. Quarterly Journal of Economics 117(4), 1295–1328]. We pr...

A longstanding feature of macroeconomic forecasting has been that a wide variety of multivariate models have struggled to out-predict univariate representations. We seek an explanation of this feature in terms of population properties. We show that if we know the univariate properties of a time-series yt these constrain tightly both the dimensions and the predictive power of the multivariate ma...

Wages and prices are closely related. Wages are an important part of businesses’ costs and are thus tied to their pricing decisions. Similarly, people take the general level of prices into account when figuring out how much pay they deserve for their work. It is intuitive, therefore, that wage data could contain important information about prices and, in particular, might be useful for forecast...

this paper investigates the forecasting performance of different time-varying bvar models for iranian inflation. forecast accuracy of a bvar model with litterman’s prior compared with a time-varying bvar model (a version introduced by doan et al., 1984); and a modified time-varying bvar model, where the autoregressive coefficients are held constant and only the deterministic components are allo...

This paper outlines the practical steps which need to be undertaken to use autoregressive integrated moving average (ARIMA) time series models for forecasting Irish inflation. A framework for ARIMA forecasting is drawn up. It considers two alternative approaches to the issue of identifying ARIMA models the Box Jenkins approach and the objective penalty function methods. The emphasis is on forec...