nep-for New Economics Papers
on Forecasting
Issue of 2016‒02‒17
eight papers chosen by
Rob J Hyndman
Monash University

  1. Foreign PMIs: A reliable indicator for Swiss exports By Hanslin Grossmann, Sandra; Scheufele, Rolf
  2. Does Joint Modelling of the World Economy Pay Off? Evaluating Multivariate Forecasts from a Bayesian GVAR By Dovern, Jonas; Feldkircher, Martin; Huber, Florian
  3. Forecasting Euro Area Recessions in real-time with a mixed-frequency Bayesian VAR By Pirschel, Inske
  4. Survey-based indicators vs. hard data: What improves export forecasts in Europe? By Lehmann, Robert
  5. THE INFORMATION CONTENT OF MONEY AND CREDIT FOR US ACTIVITY By Seitz, Franz; Albuquerque, Bruno; Baumann, Ursel
  6. Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts By Krüger, Fabian; Clark, Todd E.; Ravazzolo, Francesco
  7. A Cross-Country Analysis of Unemployment and Bonds with Long-Memory Relations By Dimpfl, Thomas; Langen, Tobias
  8. The real-time predictive content of asset price bubbles for macro forecasts By Beckers, Benjamin

  1. By: Hanslin Grossmann, Sandra; Scheufele, Rolf
    Abstract: Foreign economic activity is a major determinant of export development. This paper presents an indicator for now- and forecasting exports, which is based on survey data that captures foreign economic performance. We construct an indicator by weighting foreign PMIs of Switzerland's main trading partners with their export shares and compare its forecasting performance with alternative indicators. The paper shows that the indicator based on foreign PMIs is strongly correlated with exports (total as well as goods exports). In an out-of-sample forecast comparison we employ standard ARDL models as well as MIDAS models to forecast different definitions of exports. We document that our export indicator outperforms many other previously used indicators for forecasting exports and an univariate benchmark. As manufacturing is an important pillar of the Swiss economy and is highly export intensive, improving export forecasts is also beneficial for forecasting Swiss GDP.
    JEL: F14 F17 C53
    Date: 2015
  2. By: Dovern, Jonas; Feldkircher, Martin; Huber, Florian
    Abstract: To assess the performance of multivariate density forecasts for the world economy based on a Bayesian global vector autoregressive (GVAR) model, we decompose the predictive joint density into its marginals and a copula term that captures the dependence structure among variables and countries. Moreover, we use the stochastic search variable selection prior (SSVS) on the coefficients in its conjugate form to account for model uncertainty at the national level and augment the GVAR framework to allow for stochastic volatility. Our results are as follows: First, the GVAR systematically outperforms forecasts based on country-specific models in terms of predictive joint density. Second, the good GVAR performance is driven by superior predictions for the dependence structure across variables, whereas the GVAR model does not yield better predictive marginal densities. Third, the relative performance gains of the GVAR model are particularly pronounced during the Great Recession. Finally, our results imply that for some countries a more parsimonious GVAR model can further improve the forecast quality.
    JEL: C53 E37 F41
    Date: 2015
  3. By: Pirschel, Inske
    Abstract: In this paper I use the predictive distribution of the back-, now- and forecasts obtained with a mixed-frequency Bayesian VAR (MF-BVAR) to provide a real-time assessment of the probability of a recession in the euro area for the period from 2003 until 2013. Using a dataset that consists of 135 monthly data vintages and covers 11 soft and hard monthly indicators as well as quarterly real GDP, I show that the MF-BVAR is able to capture current economic conditions extremely well. For both recession periods in the sample, the Great Recession of 2008/2009 and the European debt crisis 2011/2013, the MF-BVAR real-time recession probabilities soar right at the onset of the pending slump of GDP growth. By contrast a BVAR estimated on quarterly data detects both recessions with a substantial delay. While typically non-linear discrete-choice or regime switching models have to be used to predict rare events such as recessions, my results indicate that the MF-BVAR can not only compete with other nowcasting approaches in terms of the accuracy of point forecasts, but also reliably detect rare events through the corresponding predictive distribution which is easily available as a by-product of the estimation procedure.
    JEL: C53 E32 E37
    Date: 2015
  4. By: Lehmann, Robert
    Abstract: We evaluate whether survey-based indicators produce lower forecast errors for export growth than indicators obtained from hard data such as price and cost competitiveness measures. Our pseudo out-of-sample analyzes and forecast encompassing tests reveal that survey-based indicators outperform the benchmark model as well as the indicators from hard data for most of our 20 European states and the aggregates EA-18 and EU-28. The most accurate forecasts are on average produced by the confidence indicator in the manufacturing sector, the economic sentiment indicator and the production expectations. However, large country differences in the forecast accuracy of survey-based indicators emerge. These differences are mainly explained with country-specific export compositions. A larger share in raw material or oil exports worsens the accuracy of soft indicators. The accuracy of soft indicators improves if countries have a larger share in exports of machinery goods. For hard indicators, we find only weak evidence for the export composition to explain differences in forecast accuracy.
    JEL: F01 F10 F17
    Date: 2015
  5. By: Seitz, Franz; Albuquerque, Bruno; Baumann, Ursel
    Abstract: We analyse the forecasting power of different monetary aggregates and credit variables for US GDP. Special attention is paid to the influence of the recent financial market crisis. For that purpose, in the first step we use a three-variable single-equation framework with real GDP, an interest rate spread and a monetary or credit variable, in forecasting horizons of one to eight quarters. This first stage thus serves to pre-select the variables with the highest forecasting content. In a second step, we use the selected monetary and credit variables within different VAR models, and compare their forecasting properties against a benchmark VAR model with GDP and the term spread. Our findings suggest that narrow monetary aggregates, as well as different credit variables, comprise useful predictive information for economic dynamics beyond that contained in the term spread. However, this finding only holds true in a sample that includes the most recent financial crisis. Looking forward, an open question is whether this change in the relationship between money, credit, the term spread and economic activity has been the result of a permanent structural break or whether we might go back to the previous relationships.
    JEL: E41 E52 E58
    Date: 2015
  6. By: Krüger, Fabian; Clark, Todd E.; Ravazzolo, Francesco
    Abstract: This paper shows entropic tilting to be a flexible and powerful tool for combining medium-term forecasts from BVARs with short-term forecasts from other sources (nowcasts from either surveys or other models). Tilting systematically improves the accuracy of both point and density forecasts, and tilting the BVAR forecasts based on nowcast means and variances yields slightly greater gains in density accuracy than does just tilting based on the nowcast means. Hence entropic tilting can offer -- more so for persistent variables than not-persistent variables -- some benefits for accurately estimating the uncertainty of multi-step forecasts that incorporate nowcast information.
    JEL: E17 C11 C53
    Date: 2015
  7. By: Dimpfl, Thomas; Langen, Tobias
    Abstract: We analyze the relationship between unemployment rate changes and government bond yields during and after the most recent financial crisis across nine industrialized countries. The study is conducted on a weekly basis and we therefore nowcast unemployment data, which are only available once a month, on a weekly frequency using Google search query data. In order to account for the time series' long-memory components during the first-stage nowcasting and the second-stage modeling, we draw on Corsi's (2009, JEF) heterogeneous autoregressive time series model. In particular, we adapt this idea to a setting of mixed-frequency nowcasting. Our results indicate that Google searches greatly increase the nowcasting accuracy of unemployment rate changes. The impact of an idiosyncratic rise in unemployment on bond yields turns out to be positive for European countries while it is negative for the United States and Australia. The speed of the response also varies. Not unexpectedly, bond yields do not have an impact on unemployment. Our findings have interesting implications for the way shocks are absorbed in economic systems that differ, in particular, with respect to the central bank's core tasks.
    JEL: G12 C53 D53
    Date: 2015
  8. By: Beckers, Benjamin
    Abstract: In light of the recent large swings in stock and housing prices accompanied by ample global liquidity, the role of monetary policy in the build-up of asset price bubbles has been questioned. This paper will contribute to the debate whether central banks can and should stronger "lean against the wind" of emerging bubbles. Against this background, the paper will reevaluate if new advances in real-time bubble detection, as brought forward by Phillips et al. (2011), can timely detect bubble emergences and collapses. Here, the paper suggests a combination approach of different bubble indicators to account for the uncertainty around start and end dates of asset price bubbles. Additionally, the paper will then investigate if these indicators carry predictive content for inflation, output growth and recession events when the real-time availability of all variables is considered. It finds that a combination approach of asset price bubbles is well suited to detect the most common stock and house price bubbles in the U.S. and shows that this indicator can improve output forecasts, however, only when the real-time availability of real variables is respected.
    JEL: C53 E44 G12
    Date: 2015

This nep-for issue is ©2016 by Rob J Hyndman. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.