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on Forecasting |
| By: | Sophia Chen; Romain Ranciere |
| Abstract: | We study the forecasting power of financial variables for macroeconomic variables for 62 countries between 1980 and 2013. We find that financial variables such as credit growth, stock prices and house prices have considerable predictive power for macroeconomic variables at one to four quarters horizons. A forecasting model with financial variables outperforms the World Economic Outlook (WEO) forecasts in up to 85 percent of our sample countries at the four quarters horizon. We also find that cross-country panel models produce more accurate out-of-sample forecasts than individual country models. |
| Date: | 2016–12–23 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:16/251&r=for |
| By: | Jimenez Polanco, Miguel A.; Ramírez Escoboza, Merlym |
| Abstract: | Manufacturing Surveys conducted by central banks, serve as a support to monetary policy decisions. This research analyzes the predictive power of indicators from EOE manufacturing survey of the Central Bank of the Dominican Republic to predict the economic cycle and to the development of macroeconomic forecasts. Additionally, we made an analysis of the indicators built from the qualitative responses of the survey and how they are related to official data. This analysis is performed by extracting the cyclical component using the Bry-Boschan (1971) approach used by the NBER for the analysis of business cycles. By doing this, the turning points of the series are identified. We estimate bivariate Vector Autoregressive to test for Granger causality in order to see if there is predictive causality in the indicators from EOE. Finally, we develop some forecasting exercises that show evidence of substantial improvements in short-term forecasts of the Monthly Economic Activity Index (IMAE), when indicators from the manufacturing survey are included. We conclude that the indicators obtained from the surveys have predictive information that can be used to model economic activity and that can serve as a support for the monetary policy decisions. |
| Keywords: | Surveys, Diffusion Index, Cyclical Component. |
| JEL: | E32 |
| Date: | 2015–12–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:75861&r=for |
| By: | Fuchs, Johann (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany]); Söhnlein, Doris (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany]); Weber, Brigitte (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany]); Weber, Enzo (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany]) |
| Abstract: | "This paper presents a stochastic integrated model to forecast the German population and labour supply until 2060. Within a cohort-component approach, the population forecast applies principal components to birth, mortality, emigration and immigration rates. The labour force participation rates are estimated by means of an econometric time series approach. All time series are forecast by bootstrapping. This allows fully integrated simulations and the possibility to illustrate the uncertainties in the form of confidence intervals. Our new forecast confirms the results from former studies. We conclude that even rising birth rates and high levels of immigration cannot break the basic demographic trend in the long run." (Author's abstract, IAB-Doku) ((en)) |
| JEL: | C38 J11 J20 J21 J22 |
| Date: | 2017–01–03 |
| URL: | http://d.repec.org/n?u=RePEc:iab:iabdpa:201701&r=for |
| By: | Feldkircher, Martin; Huber, Florian |
| Abstract: | Vector autoregressive (VAR) models are frequently used for forecasting and impulse response analysis. For both applications, shrinkage priors can help improving inference. In this paper we derive the shrinkage prior of Griffin et al. (2010) for the VAR case and its relevant conditional posterior distributions. This framework imposes a set of normally distributed priors on the autoregressive coefficients and the covariances of the VAR along with Gamma priors on a set of local and global prior scaling parameters. This prior setup is then generalized by introducing another layer of shrinkage with scaling parameters that push certain regions of the parameter space to zero. A simulation exercise shows that the proposed framework yields more precise estimates of the model parameters and impulse response functions. In addition, a forecasting exercise applied to US data shows that the proposed prior outperforms other specifications in terms of point and density predictions. (authors' abstract) |
| Keywords: | Normal-Gamma prior; density predictions; hierarchical modeling |
| Date: | 2016–03 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wus005:4933&r=for |
| By: | Mariana BĂLAN (Institute for Economic Forecasting, Romanian Academy); Brînduşa-Mihaela RADU (Institute for Economic Forecasting, Romanian Academy) |
| Abstract: | Demographic ageing of population turned lately into an extremely sensible issue, even thorny at times, and with deep impact on all generations and on most fields of economic activity. Romania, like all other European countries, is faced currently with demographic decrease. Demographic changes in the next decades are susceptible of having significant impact on the development of the Romanian economy. Population ageing, as a whole, affects negatively the GDP increase, by diminishing factor entries. At the same time, this phenomenon has negative impact also on GDP per capita, in particular for the future, mainly because of the decline in the employed population segment. In this context, knowing about the future evolution of the population plays a determinant role in adopting the measures and policies of economic growth. The paper intends in this stage of research to analyse and forecast Romania’s population ageing by using non-linear models. |
| Keywords: | population ageing; indicators of natural population movement; non-linear models; forecasts |
| JEL: | C53 E20 E27 J10 J11 |
| Date: | 2015–08 |
| URL: | http://d.repec.org/n?u=RePEc:rjr:wpiecf:150820&r=for |
| By: | Gonzalo Cortazar; Cristobal Millard; Hector Ortega; Eduardo S. Schwartz |
| Abstract: | Even though commodity pricing models have been successful in fitting the term structure of futures prices and its dynamics, they do not generate accurate true distributions of spot prices. This paper develops a new approach to calibrate these models using not only observations of oil futures prices, but also analysts’ forecasts of oil spot prices. We conclude that to obtain reasonable expected spot curves, analysts’ forecasts should be used, either alone, or jointly with futures data. The use of both futures and forecasts, instead of using only forecasts, generates expected spot curves that do not differ considerably in the short/medium term, but long term estimations are significantly different. The inclusion of analysts’ forecasts, in addition to futures, instead of only futures prices, does not alter significantly the short/medium part of the futures curve, but does have a significant effect on long-term futures estimations. |
| JEL: | G13 G17 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:22991&r=for |