Rationality Of Forecasts Research Articles

A Note on Forecasting the Rate of Change of the Price of Oil: Asymmetric Loss and Forecast Rationality

We study whether forecasts of the rate of change of the price of oil are rational. To this end, we consider a model that allows the shape of forecasters’ loss function to be studied. The shape of forecasters’ loss function may be consistent with a symmetric or an asymmetric loss function. We find that an asymmetric loss function often (but not always) makes forecasts look rational, and we also report that forecast rationality may have changed over time.

Forecasting US housing starts under asymmetric loss

Survey data of forecasts of the housing market may provide a particularly rich data environment for researchers and policymakers to study developments in housing markets. Based on the approach advanced by Elliott et al. (2005), we studied the properties of a large set of survey data of housing starts in the United States. We document the heterogeneity of forecasts, analyse the shape of forecasters' loss function, study the rationality of forecasts and the temporal variation in forecasts.

Multivariate test for forecast rationality under asymmetric loss functions: Recent evidence from MMS survey of inflation–output forecasts

We propose a multivariate test for forecast rationality under asymmetric loss functions and test jointly the rationality of inflation–output forecasts of the MMS survey for the US. Our results indicate that even though the rationality of the forecasts individually may be rejected under two popular univariate asymmetric loss functions, Linlin and Linex, there is evidence that rationality of the joint forecasts of inflation and output cannot be rejected. We find that allowing for multivariate asymmetric loss functions does improve the evidence for rationality.

Evaluating state revenue forecasting under a flexible loss function

Abstract This paper examines the accuracy of state revenue forecasting under a flexible loss function. Previous research has focused on whether a forecast is rational, meaning that the forecasts are unbiased and the actual forecast errors are uncorrelated with information available at the time of the forecast. These traditional tests assumed that the forecast loss function is quadratic and symmetric. The literature has found that budget forecasts often under-predict revenue and use the available information inefficiently. Using Californian data, I reach the same conclusion using similar tests. However, the rejection of forecast rationality might be the result of an asymmetric loss function. Once the asymmetry of the loss function is taken into account using a flexible loss function, I find evidence that under-forecasting is less costly than over-forecasting California’s revenues. I also find that the forecast errors that take this asymmetry into account are independent of information available at the time of the forecast. These results indicate that a failure to control for possible asymmetry in the loss function in previous work may have produced misleading results.

Rationality of Direct Tax Revenue Forecasts under Asymmetric Losses: Evidence from Swiss Cantons

The current debt crisis has shed light on the importance of accurate fiscal forecasts. In particular, the accuracy of revenue forecasts is central since they set the limit within which expenditure should remain in order to reach fiscal balance. Therefore, forecasting tax revenue accurately is a key step in the implementation of sound fiscal policies. The current paper contributes to the empirical literature on budget predictions by providing new evidence about Swiss cantons. Using data from 26 Swiss cantons over 1944-2010, we apply the method developed by Elliott et al. (2005) to test the rationality of direct tax revenue forecasts. We mainly find that 1) when considering the percent forecast error, loss functions are asymmetric in a majority of cantons, 2) allowing for asymmetric losses, results of rationality tests are substantially altered in the sense that more cantons turn out to produce rational forecasts 3) when considering forecasts of growth rates, almost no evidence of asymmetric loss function is found and finally 4) forecasts of tax revenue growth rate turn out to be rational in a higher number of cantons than forecasts of levels of tax revenue.

The term structure of loss preferences and rationality in analyst earnings forecasts

We show there is a term-structure in analysts’ loss preferences on corporate earnings forecast errors. Using the full I/B/E/S database on US corporate earnings, we estimate the loss function of consensus forecasts of each company in four different horizons and forecast types. Analysts are on average prudent in short horizons and evolve to optimism for longer horizons. Also, robust testing shows that forecast rationality is more evident in short horizons and much less in longer horizons. These loss preferences are found to be associated to sector and firm characteristics such as the actual earnings distribution, company size, debt and price to earnings ratios thus revealing association with the structure of managerial incentives. Their relevance increases for shorter horizons and preferences closer to pessimism.

Prognosen von Metallpreisen: Asymmetrische Verlustfunktionen und Rationalität

Prognosen von Metallpreisen: Asymmetrische Verlustfunktionen und Rationalität Metalle sind ein wichtiger industrieller Roh- und Werkstoff. Aufgrund der sehr starken Schwankungen der Metallpreise stehen Prognosen der zukünftigen Preisentwicklung häufig im Fokus medialer Berichterstattung. In diesem Beitrag werden Prognosen sechs verschiedener Metallpreise untersucht. Dabei wird insbesondere auf die Form der Verlustfunktion der Prognostiker und die Rationalität der Prognosen eingegangen. Die von uns verwendeten Mikro-Daten zeigen in Bezug auf beide Aspekte eine ausgeprägte Heterogenität sowohl über die analysierten Metallpreise hinweg als auch für einige der betrachteten Metalle über die Prognostiker hinweg. (JEL G17, E37, Q47)

Testing rationality of foreign exchange forecasts under flexible loss: survey evidence from Brazil

This study asks whether the Brazilian exchange rate (R$/US$) survey forecasts are rational under flexible loss. For 2001–2011, the forecasts overpredict. The bias in shorter-horizon forecasts is due to an inefficient use of information, while the bias in longer-horizon forecasts seems to reflect asymmetric loss. Further evidence indicates that the shorter-horizon (longer-horizon) forecasts are significantly less accurate than (as accurate as) those of the random walk. These forecasts, however, are not directionally accurate and are thus of no value to a user. The backward-looking nature of the forecasts may be due to reliance on simple forecasting rules (heuristics) since experts have great difficulty understanding the complex market dynamics.

Do Current Account Forecasters Herd? Evidence from the Euro Area and the G7 Countries

AbstractData from the Consensus Economics Forecast Poll is used to analyze how current account forecasters form expectations. The results suggest that forecasts do not satisfy traditional unbiasedness and orthogonality criteria for forecast rationality. In addition, this paper finds anti‐herding behavior among forecasters for the euro area and G7 countries. It also shows that the cross‐sectional heterogeneity with regard to anti‐herding is associated with cross‐sectional heterogeneity in forecast accuracy. More specifically, this paper finds some evidence indicating that forecasters who tend to herd provide more accurate forecasts than their colleagues who follow an anti‐herding strategy.

Forecast Rationality Tests Based on Multi-Horizon Bounds

Forecast rationality under squared error loss implies various bounds on second moments of the data across forecast horizons. For example, the mean squared forecast error should be increasing in the horizon, and the mean squared forecast should be decreasing in the horizon. We propose rationality tests based on these restrictions, including new ones that can be conducted without data on the target variable, and implement them via tests of inequality constraints in a regression framework. A new test of optimal forecast revision based on a regression of the target variable on the long-horizon forecast and the sequence of interim forecast revisions is also proposed. The size and power of the new tests are compared with those of extant tests through Monte Carlo simulations. An empirical application to the Federal Reserve's Greenbook forecasts is presented.

On the loss function of the Bank of Canada: A note

Based on the approach advanced by Elliott et al. [Elliott, G., Komunjer, I., Timmermann, A., 2005. Estimation and testing of forecast rationality under flexible loss. Review of Economic Studies 72, 1107–1125], we studied whether the inflation and output growth projections published by the Bank of Canada are consistent with an asymmetric loss function. Current-year projections provide no signs of asymmetry, but next-year projections do. The hypothesis of rationality of the projections can be rejected under symmetric loss, but not under asymmetric loss.

Are professional forecasts of growth in US business investment rational?

Utilizing comparable time-series forecasts as benchmarks, we document the “weak” and “stronger” rationality of professional forecasts of growth in business investment for 1982–2009. Consistent with these findings, the forecasts are directionally accurate and imply symmetric loss.

Forecast rationality and monetary policy frameworks: Evidence from UK interest rate forecasts

We find evidence of heterogeneity and irrationality among professional forecasts for three-month inter-bank rates and ten-year gilt yields at both short and long forecast horizons over the period 1989–2006. The majority of biased forecasts overestimate the future spot rate, consistent with slow adjustment to the declining trend in inflation and interest rates. Furthermore, we produce evidence indicating that both monetary policy actions and elements of communication policy have information content regarding the rationality of forecasts. Changes in official bank rates and disagreement among the Monetary Policy Committee influence the rationality of forecasts. The publication of inflation reports has no effect.

Backtesting Value-at-Risk Using Forecasts for Multiple Horizons, a Comment on the Forecast Rationality Tests of A.J. Patton and A. Timmermann

textabstractPatton and Timmermann (2011, 'Forecast Rationality Tests Based on Multi-Horizon Bounds', Journal of Business & Economic Statistics, forthcoming) propose a set of useful tests for forecast rationality or optimality under squared error loss, including an easily implemented test based on a regression that only involves (long-horizon and short-horizon) forecasts and no observations on the target variable. We propose an extension, a simulation-based procedure that takes into account the presence of errors in parameter estimates. This procedure can also be applied in the field of 'backtesting' models for Value-at-Risk. Applications to simple AR and ARCH time series models show that its power in detecting certain misspecifications is larger than the power of well-known tests for correct Unconditional Coverage and Conditional Coverage.

Are revenue forecasts rational? Evidence surrounding Reg FD

I test the rationality of analysts' revenue forecasts for a sample of value and growth stocks, which have been shown to have different valuation properties in previous research. Using one-quarter-ahead revenue forecasts and actual sales figures in a firm-by-firm and panel setting in the period 1997 to 2007, I find that all revenue forecasts are rational and actually improved after the introduction of regulation fair disclosure, albeit in larger proportion for value stocks.

Sales forecast rationality and small business reorganisation

This research examines the rationality of the sales forecasts made by entrepreneurs and administrators of 23 small reorganisation companies during legal reorganisation processes in Finland in 2008–2009. The findings are consistent with previous research, where small company entrepreneurs were optimistic and overconfident. The most important results are that the administrators' sales forecasts tend to be as optimistic and overconfident as the entrepreneurs' sales forecasts. These findings may give new perspective for academics in legal reorganisation research where the reasons for failure of legal reorganisation have been investigated for a long period without clear findings.

Evaluating German Business Cycle Forecasts Under an Asymmetric Loss Function

Based on annual data for growth and inflation forecasts for Germany covering the 1970-2007 period and up to 17 different forecasts per year, we test for a possible asymmetry of the forecasters’ loss function and estimate the degree of asymmetry for each forecasting institution using the approach of Elliot et al. (2005). Furthermore, we test for the rationality of the forecasts under the assumption of a possibly asymmetric loss function and for the features of an optimal forecast under the assumption of a generalised loss function. We find evidence of the existence of an asymmetric loss function of German forecasters only in the case of pooled data and a quad-quad loss function. We can reject the hypothesis of rationality of the growth forecasts based on a pooled dataset, but not on data for single institutions. The rationality of inflation forecasts is frequently rejected in the case of single institutions, and also for pooled data.

Evaluating German business cycle forecasts under an asymmetric loss function

Based on annual data for growth and inflation forecasts for Germany covering the 1970-2007 period and up to 17 different forecasts per year, we test for a possible asymmetry of the forecasters’ loss function and estimate the degree of asymmetry for each forecasting institution using the approach of Elliot et al. (2005). Furthermore, we test for the rationality of the forecasts under the assumption of a possibly asymmetric loss function and for the features of an optimal forecast under the assumption of a generalised loss function. We find evidence of the existence of an asymmetric loss function of German forecasters only in the case of pooled data and a quad-quad loss function. We can reject the hypothesis of rationality of the growth forecasts based on a pooled dataset, but not on data for single institutions. The rationality of inflation forecasts is frequently rejected in the case of single institutions, and also for pooled data.

Evaluating German Business Cycle Forecasts Under an Asymmetric Loss Function

Based on annual data for growth and inflation forecasts for Germany covering the time span from 1970 to 2007 and up to 17 different forecasts per year, we test for a possible asymmetry of the forecasters' loss function and estimate the degree of asymmetry for each forecasting institution using the approach of Elliot et al. (2005). Furthermore, we test for the rationality of the forecasts under the assumption of a possibly asymmetric loss function and for the features of an optimal forecast under the assumption of a generalized loss function. We find evidence for the existence of an asymmetric loss function of German forecasters only in case of pooled data and a quad-quad loss function. We cannot reject the hypothesis of rationality of the growth forecasts based on data for single institutions, but based on a pooled data set. The rationality of inflation forecasts frequently is rejected in case of single institutions and also for pooled data.

Spreads versus professional forecasters as predictors of future output change

AbstractWe examine whether real output forecasts obtained from the Survey of Professional Forecasters efficiently embody information in the term structure spread. To this end, we employ revised data as well as real‐time vintage data, and we also allow for the possible impact of asymmetric loss functions. Assuming quadratic loss, our results suggest that the term structure spread does contain information useful for forecasting not reflected in the survey forecasts, at least over the longest forecast horizon. However, if we allow agents' loss functions to become more negatively skewed with the forecast horizon, then we cannot reject the rationality of the survey forecasts. Copyright © 2009 John Wiley & Sons, Ltd.