Business and consumer expectations and macroeconomic forecasts

Abstract

Abstract:Business and consumer surveys have become an essential tool for gathering information about different economic variables. While the fast availability of the results and the wide range of variables covered made them very useful for monitoring the current status of the economy, there is no consensus on their utility for forecasting macroeconomic developments.The objective of the paper is to analyse the possibility of improving forecasts for selected macroeconomic variables for the euro area using the information provided by these surveys. After analyzing the potential presence of seasonality and the issue of quantification, we have tested if these indicators provide useful information to improve forecasts of the macroeconomic variables. With this aim, different sets of models have been considered (AR, ARIMA, SETAR, Markov switching regime models and VAR) to obtain forecasts for the selected macroeconomic variables. Then, information from surveys has been considered to forecast these variables in the context of the following models: autoregressive, VAR models, Markov Switching Regime models and leading indicators models. In both cases, the Root Mean Square Error (RMSE) has been computed for different forecast horizons.The comparison of the forecasting performance of the two sets of models permit to conclude that in most cases, models that include information from the survey obtain lower RMSE than the best model without survey information. However, this reduction is only significant in a limited number of cases. In this sense, the obtained results extend the results of previous research that have considered information from business and consumer surveys to explain the behaviour of macroeconomic variables, but are not conclusive about its role.

A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms

“…Balances have also been used as explanatory variables in economic models (Altug and Çakmakli 2016;Guizzardi and Stacchini 2015;Martinsen et al 2014;Ghonghadze and Lux 2012;Robinzonov et al 2012;Lui et al 2011aLui et al , 2011bSchmeling and Schrimpf 2011;Franses et al 2011;Klein and Özmucur 2010;Graff 2010;Claveria et al 2007;Abberger 2007;Mitchell et al 2005a;Hansson et al 2005;Mittnik and Zadrozny 2005;Batchelor and Dua 1998;Kauppi et al 1996;Parigi and Schlitzer 1995;Bergström 1995;Rahiala and Teräsvirta 1993;Biart and Praet 1987).…”

Quantifying survey expectations: What’s wrong with the probability approach?

“…Berk, 1999, Maag, 2010, and conclude that quantified qualitative survey expectations do not necessarily forecast the target variable better than simple time-series models (e.g. Claveria et al, 2007, Nolte and Pohlmeier, 2007, Breitung 2008, or directly suggested improvements and extensions of the CP approach to alleviate other problems of the method (e.g. Fishe and Lahiri, 1982, Löffler, 1999, Mitchell et al, 2007, or Müller, 2010.…”

Forecasting Employment in Europe: Are Survey Results Helpful?

“…Firms may want to fill a vacancy, but are not able to get suitable candidates due to their low matching efficiency, for instance. Fourthly, a discussion of the aggregation of firm's responses, e.g., balances, exists in the literature (Croux/Dekimpe/Lemmens, 2005;Claveria/Pons/Ramos, 2007). Alongside this discussion of the sheer aggregation of the raw data, several methods exist to transform qualitative indicators into quantitative information.…”

“…Alongside this discussion of the sheer aggregation of the raw data, several methods exist to transform qualitative indicators into quantitative information. Rather than using the direction of employment change, a quantitative measure extracted from employment expectations may have predictive power for the magnitude of employment change (Claveria/Pons/Ramos, 2007). However, our paper gives initial insights into the forecasting performance of survey-based indicators for predicting labor market variables.…”

“…Most of the studies either analyzed the Euro area as an aggregate (see Claveria/Pons/Ramos, 2007) or just one single state (see Hansson/Jansson/Löf, 2005;Österholm, 2010;Martinsen/Ravazzolo/Wulfsberg, 2014: for Sweden or Norway). Only the study of Croux/Dekimpe/Lemmens (2005) analyzed the capability of production expectations in forecasting industrial production for 12 European states.…”