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on Forecasting |
| By: | Snowberg, Erik; Wolfers, Justin; Zitzewitz, Eric |
| Abstract: | Prediction markets--markets used to forecast future events--have been used to accurately forecast the outcome of political contests, sporting events, and, occasionally, economic outcomes. This chapter summarizes the latest research on prediction markets in order to further their utilization by economic forecasters. We show that prediction markets have a number of attractive features: they quickly incorporate new information, are largely efficient, and impervious to manipulation. Moreover, markets generally exhibit lower statistical errors than professional forecasters and polls. Finally, we show how markets can be used to both uncover the economic model behind forecasts, as well as test existing economic models. |
| Keywords: | forecasting; prediction markets |
| JEL: | C5 G14 |
| Date: | 2012–07 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:9059&r=for |
| By: | Wickens, Michael R. |
| Abstract: | We find that forecasts from DSGE models are not more accurate than either times series models or official forecasts, but neither are they any worse. We also find that all three types of forecast failed to predict the recession that started in 2007 and continued to forecast poorly even after the recession was known to have begun. We investigate why these results occur by examining the structure of the solution of DSGE models and compare this with pure time series models. We show that the main factor is the dynamic structure of DSGE models. Their backward-looking dynamics gives them a similar forecasting structure to time series models and their forward-looking dynamics, which consists of expected values of future exogenous variables, is difficult to forecast accurately. As a result we suggest that DSGE models should not be tested through their forecasting ability. |
| Keywords: | DSGE models; Forecasting; VAR models |
| JEL: | C5 E1 |
| Date: | 2012–07 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:9049&r=for |
| By: | Lutz Kilian; Robert J. Vigfusson |
| Abstract: | There is a long tradition of using oil prices to forecast U.S. real GDP. It has been suggested that the predictive relationship between the price of oil and one-quarter ahead U.S. real GDP is nonlinear in that (1) oil price increases matter only to the extent that they exceed the maximum oil price in recent years and that (2) oil price decreases do not matter at all. We examine, first, whether the evidence of in-sample predictability in support of this view extends to out-of-sample forecasts. Second, we discuss how to extend this forecasting approach to higher horizons. Third, we compare the resulting class of nonlinear models to alternative economically plausible nonlinear specifications and examine which aspect of the model is most useful for forecasting. We show that the asymmetry embodied in commonly used nonlinear transformations of the price of oil is not helpful for out-of-sample forecasting; more robust and more accurate real GDP forecasts are obtained from symmetric nonlinear models based on the three-year net oil price change. Finally, we quantify the extent to which the 2008 recession could have been forecast using the latter class of time-varying threshold models. |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgif:1050&r=for |
| By: | Erik Snowberg; Justin Wolfers; Eric Zitzewitz |
| Abstract: | Prediction markets--markets used to forecast future events--have been used to accurately forecast the outcome of political contests, sporting events, and, occasionally, economic outcomes. This chapter summarizes the latest research on prediction markets in order to further their utilization by economic forecasters. We show that prediction markets have a number of attractive features: they quickly incorporate new information, are largely efficient, and impervious to manipulation. Moreover, markets generally exhibit lower statistical errors than professional forecasters and polls. Finally, we show how markets can be used to both uncover the economic model behind forecasts, as well as test existing economic models. |
| JEL: | C53 G14 |
| Date: | 2012–07 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:18222&r=for |
| By: | Pierdzioch, Christian; Rülke, Jan Christoph; Stadtmann, Georg |
| Abstract: | Recent price trends in housing markets may reflect herding of market participants. A natural question is whether such herding, to the extent that it occurred, reflects herding in forecasts of professional forecasters. Using survey data for Canada, Japan, and the United States, we did not find evidence of forecaster herding. On the contrary, forecasters anti-herd and, thereby, tend to intentionally scatter their forecasts around the consensus forecast. The extent of anti-herding seems to vary over time. For Canada and the United States, we found that more pronounced anti-herding leads to lower forecast accuracy. -- |
| Keywords: | Housing starts,Forecasting,Herding |
| JEL: | E37 D84 C33 |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:euvwdp:320&r=for |
| By: | Makram El-Shagi; Sebastian Giesen; A. Jung |
| Abstract: | In the tradition of Romer and Romer (2000), this paper compares staff forecasts of the Federal Reserve (Fed) and the European Central Bank (ECB) for inflation and output with corresponding private forecasts. Standard tests show that the Fed and less so the ECB have a considerable information advantage about inflation and output. Using novel tests for conditional predictive ability and forecast stability for the US, we identify the driving forces of the narrowing of the information advantage of Greenbook forecasts coinciding with the Great Moderation. |
| Keywords: | relative forecast performance, forecast stability, staff forecasts, private forecasts, real-time data |
| JEL: | C53 E37 E52 E58 |
| Date: | 2012–07 |
| URL: | http://d.repec.org/n?u=RePEc:iwh:dispap:5-12&r=for |
| By: | Korte, Niko (BOFIT) |
| Abstract: | This study examines the forecasting power of confidence indicators for the Russian economy. ARX models are fitted to the six confidence or composite indicators, which were then compared to a simple benchmark AR-model. The study used the output of the five main branches as the reference series. Empirical evidence suggests that confidence indicators do have forecasting power. The power is strongly influenced by the way which the indicator is constructed from the component series. The HSBC Purchasing Managers' Index (PMI), the OECD Composite Leading Indicator (CLI) and the OECD Business Confidence Indicator (BCI) were the best performers in terms of both the information criterion and forecasting accuracy. |
| Keywords: | confidence indicators; forecasting; Russia |
| JEL: | E37 P27 |
| Date: | 2012–07–12 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:bofitp:2012_015&r=for |
| By: | Martin-Rodriguez, Gloria; Caceres-Hernandez, Jose Juan |
| Abstract: | Sea shipping is the main transport mode used by Canary farmers to export tomatoes to the European markets. Provincial associations of Canary growers negotiate charter fees with the shipping companies for the whole exporting period and, therefore, provide a unified sea transport service. When such a negotiation takes place each year, the individual growers’ decisions about planting surface are usually known. However, the forecasting of the distribution of tomato exports over the whole harvesting period would help Canary associations make more timely and effective decisions. In this paper, a model is proposed to forecast weekly Canary tomato exports conditioned on a given total planting surface. A seasonal model is formulated to deal with the weekly seasonal pattern of Canary tomato yields per hectare by means of evolving splines. Such a model is a useful tool to forecast weekly yields. From these forecasts, weekly tomato exports beyond the end of the sample are also forecast by taking the total planting surface into account. To illustrate the aptness of this framework, the proposed methodology is applied to a weekly series of tomatoes exported to the European markets from 1995/1996 to 2010/2011 harvests. |
| Keywords: | tomato exports, surface, weekly data, seasonal splines, Research Methods/ Statistical Methods, C22, Q17, |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:ags:iaae12:126364&r=for |
| By: | Lorenzo Bencivelli (Bank of Italy); Massimiliano Marcellino (European University Institute, Bocconi University and CEPR); Gianluca Moretti (UBS Global asset management) |
| Abstract: | This paper proposes the use of Bayesian model averaging (BMA) as a tool to select the predictors' set for bridge models. BMA is a computationally feasible method that allows us to explore the model space even in the presence of a large set of candidate predictors. We test the performance of BMA in now-casting by means of a recursive experiment for the euro area and the three largest countries. This method allows flexibility in selecting the information set month by month. We find that BMA based bridge models produce smaller forecast error than fixed composition bridges. In an application to the euro area they perform at least as well as medium-scale factor models. |
| Keywords: | business cycle analysis, forecasting, Bayesian model averaging, bridge models. |
| JEL: | C22 C52 C53 |
| Date: | 2012–07 |
| URL: | http://d.repec.org/n?u=RePEc:bdi:wptemi:td_872_12&r=for |
| By: | Wong, Shirly Siew-Ling; Puah, Chin-Hong; Abu Mansor, Shazali; Liew , Venus Khim-Sen |
| Abstract: | The initiative to capture the information content behind the rise and fall of the business cycle has popularized the study of leading indicators. Many of the foreign experiences shared by economically advanced countries reveal that the leading indicator approach works well as a short-term forecasting tool. Thus, exploring an indicator-based forecasting tool for business cycle analysis and economic risk monitoring would provide insight into the Malaysian economy as well as that of other emerging countries. By extending the ideology of indicator construction from the US National Bureau of Economic Research (NBER), the present study demonstrated the strong potential of the leading indicator approach to be a good gauge of the business cycle movement in addition to being a practical and functional early warning indicator for economic vulnerability prediction. |
| Keywords: | Business Cycle; Composite Leading Indicator; Early Warning Indicator |
| JEL: | E32 C82 E37 |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:39944&r=for |
| By: | A. Debòn; S. Haberman; F. Montes; Edoardo Otranto |
| Abstract: | The parametric model introduced by Lee and Carter in 1992 for projecting mortality rates in the US has been a seminal development and has been widely used since then. Different versions of the model, incorporating constraints on the data, and different adjustment methods have led to improvement. All of these changes have increased the complexity of the model with a corresponding improvement in goodness of fit, however, there is little change in the accuracy of forecasts of life expectancy in comparison with the original Lee-Carter model, according to some authors. To evaluate to what point the increments in the complexity and computational cost of the models are reflected in the forecast of such indices as life expectancy and modal age at death, among others, we have compared three different models - the original Lee-Carter with one parameter and the Lee-Carter model with two temporal parameters forecasted by means of two independent time series or by means of a bivariate one. The three sets of predictions so obtained are compared using a mixture of block-bootstrap techniques and functional data analysis. |
| Keywords: | mortality indicators; block-bootstrap; functional data analysis |
| JEL: | C53 |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:cns:cnscwp:201215&r=for |
| By: | Nektarios Aslanidis (Department of Economics, FCEE, University Rovira Virgili); Charlotte Christiansen (Aarhus University and CREATES) |
| Abstract: | This paper adopts quantile regressions to scrutinize the realized stock-bond correlation based upon high frequency returns. The paper provides in-sample and out-of-sample analysis and considers a large number of macro-?nance predictors well-know from the return predictability literature. Strong in-sample predictability is obtained from quantile models with factor-augmented predictors, particularly at the lower to median quantiles. Out-of-sample the quantile factor model works best at the median to upper quantiles. |
| Keywords: | Realized stock-bond correlation, Quantile regressions, Macro?nance variables, Factor analysis. |
| JEL: | C22 G11 G12 |
| Date: | 2012–07–06 |
| URL: | http://d.repec.org/n?u=RePEc:aah:create:2012-34&r=for |
| By: | Crescenzio Gallo; Michelangelo De Bonis; Pierpaolo Palazzo |
| Abstract: | Prediction of various market indicators is an important issue in finance. This can be accomplished through computer models and related applications to finance, and in particular through Artificial Neural Networks (ANNs) which have been used in stock market prediction and exchange rates during the last decade. The prediction of financial values (such as stock/exchange rate index as well as daily direction of change in the index) with neural networks has been investigated and, in some applications, it turned out that artificial neural networks have both great advantages and some limitations for learning the data patterns and predicting future values of the financial phenomenon under analysis. In this paper we analyze the particular financial market called FOREX and the way ANNs can make affordable predictions on the evolution of exchange rates between currencies. |
| Date: | 2012–05 |
| URL: | http://d.repec.org/n?u=RePEc:ufg:qdsems:02-2012&r=for |