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I propose a novel approach to uncover business cycle reports’ priorities and relate them to economic fluctuations. To this end, I leverage quantitative business-cycle forecasts published by leading German economic research institutes since 1970 to estimate the proportions of latent topics in associated business cycle reports. I then employ a supervised approach to aggregate topics with similar themes, thus revealing the proportions of broader macroeconomic subjects. I obtain measures of forecasters’ subject priorities by extracting the subject proportions’ cyclic components. Correlating these priorities with key macroeconomic variables reveals consistent priority patterns throughout economic peaks and troughs. The forecasters prioritize inflation-related matters over recession-related considerations around peaks. This finding suggests that forecasters underestimate growth and overestimate inflation risks during contractive monetary policies, which might explain their failure to predict recessions. Around troughs, forecasters prioritize investment matters, potentially suggesting a better understanding of macroeconomic developments during those periods compared to peaks.

Post-2006 expert judgment data has been extended to 530 experts assessing 580 calibration variables from their fields. New analysis shows that point predictions as medians of combined expert distributions outperform combined medians, and medians of performance weighted combinations outperform medians of equal weighted combinations. Relative to the equal weight combination of medians, using the medians of performance weighted combinations yields a 65% improvement. Using the medians of equally weighted combinations yields a 46% improvement. The Random Expert Hypothesis underlying all performance-blind combination schemes, namely that differences in expert performance reflect random stressors and not persistent properties of the experts, is tested by randomly scrambling expert panels. Generating distributions for a full set of performance metrics, the hypotheses that the original panels’ performance measures are drawn from distributions produced by random scrambling are rejected at significance levels ranging from E−6 to E−12. Random stressors cannot produce the variations in performance seen in the original panels. In- and out-of-sample validation results are updated., Applied Probability

Post-2006 expert judgment data has been extended to 530 experts assessing 580 calibration variables from their fields. New analysis shows that point predictions as medians of combined expert distributions outperform combined medians, and medians of performance weighted combinations outperform medians of equal weighted combinations. Relative to the equal weight combination of medians, using the medians of performance weighted combinations yields a 65% improvement. Using the medians of equally weighted combinations yields a 46% improvement. The Random Expert Hypothesis underlying all performance-blind combination schemes, namely that differences in expert performance reflect random stressors and not persistent properties of the experts, is tested by randomly scrambling expert panels. Generating distributions for a full set of performance metrics, the hypotheses that the original panels’ performance measures are drawn from distributions produced by random scrambling are rejected at significance levels ranging from E−6 to E−12. Random stressors cannot produce the variations in performance seen in the original panels. In- and out-of-sample validation results are updated., Applied Probability

We investigate how the forecasting performance of the Federal Reserve Greenbooks has changed relative to commercial forecasters between 1974 and 2009. To this end, we analyze time-variation in the Greenbook coefficients in forecast encompassing regressions. Assuming that model coefficients change continuously, we estimate unobserved components models using Bayesian inference techniques. To verify that our results do not depend on the specific way change is modeled, we also allow the coefficients to change discretely rather than continuously and test for structural breaks using classical inference techniques. We find that the Greenbook forecasts have been consistently superior to the commercial forecasts at all horizons throughout our sample period. Although the forecasting performance gap has narrowed at more distant horizons after the early-to-mid 1980s, it remains significant.

We investigate how the forecasting performance of the Federal Reserve Greenbooks has changed relative to commercial forecasters between 1974 and 2009. To this end, we analyze time-variation in the Greenbook coefficients in forecast encompassing regressions. Assuming that model coefficients change continuously, we estimate unobserved components models using Bayesian inference techniques. To verify that our results do not depend on the specific way change is modeled, we also allow the coefficients to change discretely rather than continuously and test for structural breaks using classical inference techniques. We find that the Greenbook forecasts have been consistently superior to the commercial forecasts at all horizons throughout our sample period. Although the forecasting performance gap has narrowed at more distant horizons after the early-to-mid 1980s, it remains significant.

IAS 31 allowed firms to choose between proportionate consolidation and the equity method to record joint ventures in the consolidated accounts of the venturer. Moreover, this election implied a decision about including information in the primary financial statements or in the notes. This paper investigates if financial analysts perceive accounting information differently depending on the method chosen conditioned to the disclosure of the required information in the notes. We analysed a sample of Spanish firms during 2005–2010. We not only considered earnings forecasts, but also examined target prices and stock recommendations. Furthemore, we look at how this accounting choice affects analysts’ information environment. Our results suggest that the choice of accounting regime does not affect the bias and accuracy of earnings forecasts, nor target prices nor stock recommendations, no matter if firms provide or not information in the notes. While the proportionate method implies lower dispersion in analysts’ forecasts than the equity method, our tests do not allow us to confirm that the information environment depends on the accounting method. These results support the decision adopted in IFRS 11 to impose a unique method for the accounting of joint ventures., La NIC 31 permitía elegir entre integración proporcional y el método de la participación para la inclusión de los negocios conjuntos en las cuentas consolidadas de los partícipes. Además, esta elección conllevaba la inclusión de cierta información sobre los negocios conjuntos en los estados financieros primarios o en la memoria. Este trabajo investiga si los analistas financieros perciben la información contable de forma distinta dependiendo del método elegido, condicionado a que se divulgue la información requerida en la memoria. Se analiza una muestra de empresas españolas en el periodo 2005-2010, y se considera la influencia de la decisión contable sobre las predicciones de beneficios, precios objetivo y recomendaciones sobre acciones. Adicionalmente, se estudia si esta opción contable afecta al entorno informativo de los analistas. Nuestros resultados sugieren que la elección no afecta al sesgo ni a la precisión de las predicciones de beneficios, ni tampoco a precios objetivo ni a recomendaciones, al margen de que las empresas proporcionen o no información en la memoria. Pese a que la integración proporcional implica menor dispersión en las predicciones, los contrastes realizados no permiten confirmar que el entorno informativo se vea afectado por el uso de un método contable u otro. Estos resultados apoyan la decisión tomada en la NIIF 11 de imponer un único método para la contabilización de los negocios conjuntos.

IAS 31 allowed firms to choose between proportionate consolidation and the equity method to record joint ventures in the consolidated accounts of the venturer. Moreover, this election implied a decision about including information in the primary financial statements or in the notes. This paper investigates if financial analysts perceive accounting information differently depending on the method chosen conditioned to the disclosure of the required information in the notes. We analysed a sample of Spanish firms during 2005–2010. We not only considered earnings forecasts, but also examined target prices and stock recommendations. Furthemore, we look at how this accounting choice affects analysts’ information environment. Our results suggest that the choice of accounting regime does not affect the bias and accuracy of earnings forecasts, nor target prices nor stock recommendations, no matter if firms provide or not information in the notes. While the proportionate method implies lower dispersion in analysts’ forecasts than the equity method, our tests do not allow us to confirm that the information environment depends on the accounting method. These results support the decision adopted in IFRS 11 to impose a unique method for the accounting of joint ventures., La NIC 31 permitía elegir entre integración proporcional y el método de la participación para la inclusión de los negocios conjuntos en las cuentas consolidadas de los partícipes. Además, esta elección conllevaba la inclusión de cierta información sobre los negocios conjuntos en los estados financieros primarios o en la memoria. Este trabajo investiga si los analistas financieros perciben la información contable de forma distinta dependiendo del método elegido, condicionado a que se divulgue la información requerida en la memoria. Se analiza una muestra de empresas españolas en el periodo 2005-2010, y se considera la influencia de la decisión contable sobre las predicciones de beneficios, precios objetivo y recomendaciones sobre acciones. Adicionalmente, se estudia si esta opción contable afecta al entorno informativo de los analistas. Nuestros resultados sugieren que la elección no afecta al sesgo ni a la precisión de las predicciones de beneficios, ni tampoco a precios objetivo ni a recomendaciones, al margen de que las empresas proporcionen o no información en la memoria. Pese a que la integración proporcional implica menor dispersión en las predicciones, los contrastes realizados no permiten confirmar que el entorno informativo se vea afectado por el uso de un método contable u otro. Estos resultados apoyan la decisión tomada en la NIIF 11 de imponer un único método para la contabilización de los negocios conjuntos.

Techniques for evaluating and selecting multivariate volatility forecasts are not yet understood as well as their univariate counterparts. This paper considers the ability of different loss functions to discriminate between a set of competing forecasting models which are subsequently applied in a portfolio allocation context. It is found that a likelihood-based loss function outperforms its competitors, including those based on the given portfolio application. This result indicates that considering the particular application of forecasts is not necessarily the most effective basis on which to select models.

It is common practice to evaluate fixed-event forecast revisions in macroeconomics by regressing current forecast revisions on one-period lagged forecast revisions. Under weak-form (forecast) efficiency, the correlation between the current and one-period lagged revisions should be zero. The empirical findings in the literature suggest that this null hypothesis of zero correlation is rejected frequently, where the correlation can be either positive (which is widely interpreted in the literature as “smoothing”) or negative (which is widely interpreted as “over-reacting”). We propose a methodology to in

The world is interconnected and powered by a number of global energy systems using fossil, nuclear, or renewable energy. This study reviews historical time series of energy production and growth for various energy sources. It compiles a theoretical and empirical foundation for understanding the behaviour underlying global energy systems' growth. The most extreme growth rates are found in fossil fuels. The presence of scaling behaviour, i.e. proportionality between growth rate and size, is established. The findings are used to investigate the consistency of several long-range scenarios expecting rapid growth for future energy systems. The validity of such projections is questioned, based on past experience. Finally, it is found that even if new energy systems undergo a rapid "oil boom"-development - i.e. they mimic the most extreme historical events - their contribution to global energy supply by 2050 will be marginal., STandUP for energy

It is common practice to evaluate fixed-event forecast revisions in macroeconomics by regressing current revisions on one-period lagged revisions. Under weak-form efficiency, the correlation between the current and one-period lagged revisions should be zero. The empirical findings in the literature suggest that the null hypothesis of zero correlation between the current and one-period lagged revisions is rejected quite frequently, where the correlation can be either positive or negative. In this paper we propose a methodology to be able to interpret such non-zero correlations in a straightforward manner. Our approach is based on the assumption that forecasts can be decomposed into both an econometric model and expert intuition. The interpretation of the sign of the correlation between the current and one-period lagged revisions depends on the process governing intuition, and the correlation between intuition and news.

This paper deals with the analysis and evaluation of sales forecasts of managers, given that it is unknown how they constructed their forecasts. Our goal is to find out whether these forecasts are rational. To examine deviations from rationality, we argue that one has to approximate how the managers could have generated the forecasts. We describe several ways to construct these approximate expressions. The analysis of a large set of a single manager's forecasts for sales of pharmaceutical products illustrates the practical usefulness of our methodology.

This paper deals with the analysis and evaluation of sales forecasts of managers, given that it is unknown how they constructed their forecasts. Our goal is to find out whether these forecasts are rational. To examine deviations from rationality, we argue that one has to approximate how the managers could have generated the forecasts. We describe several ways to construct these approximate expressions. The analysis of a large set of a single manager's forecasts for sales of pharmaceutical products illustrates the practical usefulness of our methodology.

It is common practice to evaluate fixed-event forecast revisions in macroeconomics by regressing current revisions on one-period lagged revisions. Under weak-form efficiency, the correlation between the current and one-period lagged revisions should be zero. The empirical findings in the literature suggest that the null hypothesis of zero correlation between the current and one-period lagged revisions is rejected quite frequently, where the correlation can be either positive or negative. In this paper we propose a methodology to be able to interpret such non-zero correlations in a straightforward manner. Our approach is based on the assumption that forecasts can be decomposed into both an econometric model and expert intuition. The interpretation of the sign of the correlation between the current and one-period lagged revisions depends on the process governing intuition, and the correlation between intuition and news.

The paper compares the information contents of two of the most widely used sets of macroeconomic forecasts, namely, the macroeconomic forecasts produced by the International Monetary Fund (IMF) and the Organization for Economic Cooperation and Development (OECD). By testing whether the release of public sector forecasts had systematic impact on subsequent revisions in Consensus (private sector) forecasts, the paper finds that, for the period 1994?2003, private forecasters reacted to the information provided by the IMF on regions (such as non?G7 Europe and Latin America) for which the IMF’s forecasts are known to be more accurate or about which information is less available. What determines the information value of public sector forecasts, however, appears complex. The OECD’s impact was limited in influencing private sector forecasts for the G7 countries, though it had a superior forecast performance than the IMF. Some herding behavior was observed among private sector forecasters.

Experts often add domain knowledge to model-based forecasts while aiming to reduce forecast errors. Indeed, there is some empirical evidence that expert-adjusted forecasts improve forecast quality. However, surprisingly little is known about what experts actually do. Based on a large and detailed databas