Forecasting Inflation with a Simple and Accurate Benchmark: A Cross-Country Analysis

Abstract

We explore the ability of several univariate models to predict inflation in a number of countries and at several forecasting horizons. We place special attention on forecasts coming from a family of ten seasonal models that we call the Driftless Extended Seasonal ARIMA (DESARIMA) family. Using out-of-sample Root Mean Squared Prediction Errors (RMSPE) we compare the forecasting accuracy of the DESARIMA models with that of traditional univariate time-series benchmarks available in the literature. Our results show that DESARIMA-based forecasts display lower RMSPE at short horizons for every single country, except one. We obtain mixed results at longer horizons. Roughly speaking, in half of the countries, DESARIMA-based forecasts outperform the benchmarks at long horizons. Remarkably, the forecasting accuracy of our DESARIMA models is surprisingly high in stable inflation countries, for which the RMSPE is barely higher than 100 basis points when the prediction is made 24-and even 36-months ahead. Resumen En este trabajo se explora la capacidad de varios modelos univariados para predecir la inflación de un conjunto de países a varios horizontes predictivos. Se pone especial atención en predicciones provenientes de una familia de diez modelos estacionales que es denominada Driftless Extended Seasonal ARIMA (DESARIMA). Mediante el cálculo de la raíz cuadrada del error cuadrático medio (RECM) fuera de muestra, se compara la capacidad predictiva de los modelos DESARIMA con la de modelos referenciales de series de tiempo tradicionalmente utilizados en la literatura. Los resultados indican que las predicciones basadas en modelos DESARIMA muestran una menor RECM para horizontes cortos en todos los países considerados, excepto en uno. Se obtienen resultados mixtos para horizontes mayores. Aproximadamente en la mitad de los países las predicciones basadas en modelos DESARIMA superan a los modelos referenciales en horizontes largos. Se destaca que la precisión predictiva de los modelos DESARIMA es sorprendentemente alta en países con inflación estable, para los cuales la RECM es algo mayor que 100 puntos base para predicciones realizadas a 24 y hasta 36 meses adelante. * We thank the comments of seminar participants at the Central Bank of Chile. Any errors or omissions are responsibility of the authors. The views and ideas expressed in this paper do not necessarily represent those of the Central Bank of Chile or its authorities.

The low predictive power of simple Phillips curves in Chile

“…Also interesting to highlight is that the difference in predictive accuracy between the models estimated with revised and real-time 9 The time series models considered are a random walk with constant and two sarima models similar to the airline model of Box and Jenkins (1970). These sarima models are described in great detail in Pincheira and García (2009) and in Pincheira and Medel (2015), with these studies also showing their excellent predictive capacity for inflation in Chile and a select group of countries. A brief summary with the sarima specifications used in this document can be found in the annex.…”

“…These sarima models are described in great detail in Pincheira and García (2009) and Pincheira and Medel (2015), with these articles also demonstrating their excellent predictive capacity for inflation in Chile and a select group of countries. In particular, the three models used here have the following specifications: …”

The Evasive Predictive Ability of Core Inflation

“…We notice that univariate versions of the models 3-5 were evaluated in their ability to predict headline inflation for a number of countries in Pincheira and Medel (2015). These models were extremely competitive at short horizons yet similar to the usual benchmarks available in the literature at longer horizons.…”

El escaso poder predictivo de simples curvas de Phillips en Chile

“…Estos modelos sarima son descritos con gran detalle en Pincheira y García (2009), así como en Pincheira y Medel (2015), trabajos en los que también se muestra su excelente capacidad predictiva para la inflación de Chile y de un selecto grupo de países. Un breve resumen con las especificaciones sarima usadas en este documento se encuentra en los anexos.…”