Forecasting growth cycle turning points using US and Japanese professional forecasters

This paper examines the forecasting of growth cycle turning points by comparing the performances of US and Japanese professional forecasters with those of a simple time-series model, using real-time data. The empirical results, obtained after performing contingency table analyses and visual inspections, indicate that the US professional forecasters considerably outperform the simple time-series model; however, the Japanese professional forecaster is comparable to the simple time-series model in the visual inspections of major turning points.      

Towards an Understanding of Some Business Cycle Characteristics

For many years economists have debated the 'causes' of business cycles. Very little of this analysis has been closely matched with business cycle characteristics as measured by NBER-type dating methods. After summarising data on business cycle characteristics for a wide variety of countries, the article shows that an extremely simple statistical model of output growth, viz. that it is uncorrelated from month to month or quarter to quarter, produces business cycles that are close to those seen in practice. The demonstration involves the analysis of data simulated from this simple statistical model as well as some analytical work using a standard definition of a recession as being two quarters of negative growth. As well as explaining the average length of a cycle this model also accounts for the asymmetry between the lengths of expansions and contractions through the relative magnitudes of the trend rate of growth of the economy and the standard deviation of the shocks that impinge upon it.     

Geography, skills or both: What explains Fed watchers’ forecast accuracy of US monetary policy?

The paper shows that there is a substantial degree of heterogeneity in the ability of Fed watchers to forecast US monetary policy decisions. Based on a novel database for 268 individual professional forecasters since 1999, the average absolute forecast error of FOMC decisions varies 5–10 basis points between the best and worst-performers across the sample. This heterogeneity is found to be related to both the skills of analysts – such as their educational and employment backgrounds – and to geography. In particular, forecasters located in regions which experience more idiosyncratic economic conditions perform worse in anticipating monetary policy. This evidence is indicative that limited attention and heterogeneous priors are present even for anticipating important events such as monetary policy decisions.     

A multivariate analysis of forecast disagreement: Confronting models of disagreement with survey data

This paper documents multivariate forecast disagreement among professional forecasters and discusses implications for models of heterogeneous expectation formation. Disagreement varies over time and is positively correlated with general (economic) uncertainty. The degree to which individual forecasters disagree with the average forecast tends to persist over time. Models of heterogeneous expectation formation can be modified by introducing heterogeneous signal-to-noise ratios to match this feature. Furthermore, disagreement about correlations of different macroeconomic variables is high on average. In general, multivariate forecast data can be used more effectively than it has been to estimate models with heterogeneous expectations and to test the mechanisms used to generate disagreement in these models.     

Anchoring of inflation expectations in the euro area: Recent evidence based on survey data

This article analyses the anchoring of inflation expectations of professional forecasters and consumers in the euro area. We study anchoring, defined as the central bank's ability to manage expectations, by paying special attention to the impact of the ECB inflation target and ECB inflation projections on inflation expectations. Our analysis indicates that in the post-crisis period longer-term inflation expectations have become somewhat more sensitive to shorter-term ones and to actual HICP inflation. We also find that the ECB inflation projections have recently become more important for short- and medium-term expectations of professional forecasters and at the same time the role of the ECB inflation target for those expectations has diminished. Overall, our analysis suggests that in recent years inflation expectations in the euro area have shown some signs of de-anchoring.     

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

Data 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.     

Credible enough? Forward guidance and perceived National Bank of Poland’s policy rule

Forward guidance effectiveness is conditional upon its credibility. This policy, when taken as credible, should reduce the perceived impact of macroeconomic variables on the interest rate. Using the Taylor rule framework and employing micro-level data set, we test the perception of monetary policy in Poland among professional forecasters. Our results show that the Taylor principle is violated in the forward guidance period, which provides evidence for forward guidance credibility.     

Mean absolute percentage error and bias in economic forecasting

This article develops a simple theoretical framework to show how forecasters may bias downward point predictions under the assumption that the asymmetric loss function is directly related to the (Mean) Absolute Percentage Error (M)APE.     

Forecast performance,disagreement, and heterogeneous signal-to-noise ratios

We propose an imperfect information model for the expectations of macroeconomic forecasters that explains differences in average disagreement levels across forecasters by means of cross-sectional heterogeneity in the variance of private noise signals. We show that the forecaster-specific signal-to-noise ratios determine both the average individual disagreement level and an individuals’ forecast performance: Forecasters with very noisy signals deviate strongly from the average forecasts and report forecasts with low accuracy. We take the model to the data by empirically testing for this implied correlation. Evidence based on data from the Surveys of Professional Forecasters for the USA and for the Euro Area supports the model for short- and medium-run forecasts but rejects it based on its implications for long-run forecasts.     

上市公司财务困境的串联和并联组合预测

利用单一判别分析方法对上市公司财务困境进行预测具有片面性和不稳定性。本文尝试通过多种判别分析方法的串联和并联组合来提高预测效果。以我国上市公司为对象的实证研究表明：在预测公司财务困境方面,串联组合的平均预测准确率最高,预测准确率最稳定。但是并联组合预测效果不够理想,有待改进以提高预测效果。     

State dependent asymmetric loss and the consensus forecast of real U.S. GDP growth

It has been well documented that the consensus forecast from surveys of professional forecasters shows a bias that varies over time. In this paper, we examine whether this bias may be due to forecasters having an asymmetric loss function. In contrast to previous research, we account for the time variation in the bias by making the loss function depend on the state of the economy. The asymmetry parameter in the loss function is specified to depend on set state variables which may cause forecaster to intentionally bias their forecasts. We consider both the Lin–Ex and asymmetric power loss functions. For the commonly used Lin–Ex and Lin–Lin loss functions, we show the model can be easily estimated by least squares. We apply our methodology to the consensus forecast of real U.S. GDP growth from the Survey of Professional Forecasters. We find that forecast uncertainty has an asymmetric effect on the asymmetry parameter in the loss function dependent upon whether the economy is in expansion or contraction. When the economy is in expansion, forecaster uncertainty is related to an overprediction in the median forecast of real GDP growth. In contrast, when the economy is in contraction, forecaster uncertainty is related to an underprediction in the median forecast of real GDP growth. Our results are robust to the particular loss function that is employed in the analysis.     

Forecaster Rationality and Expectation Formation in Foreign Exchange Markets: Do Emerging Countries Differ from Industrialized Economies?

ABSTRACT

This paper uses the Consensus Economic Forecast poll to investigate how forecasters in the foreign exchange market form expectations and whether the expectation formation process differs between industrialized and emerging countries. In order to explain the expectation formation of forecasters in countries and country groups, we analyze around 50,000 forecasts for 22 OECD member currencies. We find that differences between the way forecasters in industrialized countries and emerging countries form exchange rate expectations. However, we show that one important difference is due to a difference in forecasting behavior of emerging countries. Controlling for this feature lets the forecasting behavior in emerging countries resemble more the ones found for industrialized countries, but not for all forecast horizons.     

Forecasting ECB monetary policy: Accuracy is a matter of geography

Monetary policy in the euro area is conducted within a multi-country, multi-cultural, and multi-lingual context. How does this heterogeneity affect the ability of economic agents to understand and to anticipate monetary policy by the European Central Bank (ECB)? Using a database of surveys of professional ECB policy forecasters in 24 countries, we find remarkable differences in forecast accuracy, and show that these have important repercussions on market behaviour. Explaining the differences in forecast accuracy, we provide evidence that they are partly related to geography and clustering around informational hubs, as well as to country-specific economic conditions. In large part this heterogeneity can be traced to differences in forecasting models.     

Forecast combination when outcomes are difficult to predict

We show that when outcomes are difficult to forecast in the sense that forecast errors have a large common component that (a) optimal weights are not affected by this common component, and may well be far from equal to each other but (b) the relative mean square error loss from averaging over optimal combination can be small. Hence, researchers could well estimate combining weights that indicate that correlations could be exploited for better forecasts only to find that the difference in terms of loss is negligible. The results then provide an additional explanation for the commonly encountered practical situation of the averaging of forecasts being difficult to improve upon.     

Do professional forecasters behave as if they believed in the New Keynesian Phillips Curve for the euro area?

This paper finds that participants in the European Central Bank’s Survey of Professional Forecasters have submitted forecasts that are consistent with a (mostly forward-looking) empirical version of the New Keynesian Phillips Curve for the euro area. The estimation technique takes advantage of the panel nature of the Survey of Professional Forecasters’ dataset to exploit both its time series and cross-section dimensions, and to control for unobservable individual heterogeneity across forecasters. The estimation results suggest that euro-area inflation forecasts have reacted less to unemployment forecasts after the start of the financial crisis but another cost measure (energy inflation) remains significant. This finding is consistent with a flatter Phillips Curve in the euro area after 2007. However, the reasons suggested by the International Monetary Fund for this finding, namely a better anchoring of inflation expectations and increases in structural unemployment do not seem to find support in the survey data. Instead, the expectations for compensation per employee submitted by professional forecasters are consistent with the existence of downward real-wage rigidities in euro-area labour markets.     

Expert Judgments: Financial Analysts Versus Weather Forecasters

Two groups of experts, financial analysts and weather forecasters, were asked to predict corresponding events (the value of the Warsaw Stock Exchange Index and the average temperature of the next month). When accounting for inaccurate judgments, we find that weather forecasters attach more importance to probability than financial analysts. Although both groups revealed the overconfidence effect, it was significantly higher among financial analysts. These results are discussed from the perspective of learning from experience.     

Economic Forecasts and Their Assessment*

This paper looks at the accuracy of economic forecasts in general and by examining a subset of 12 Australian, forecasters over a five-year period. It also address the question of whether it is possible to rank forecasters in order of merit. The paper concludes that the problem are sufficiently large for it to be highly unlikely that a meaningful and stable ranking could be obtained.     

Explaining Disagreement on Interest Rates in a Taylor‐Rule Setting

Most studies on disagreement focus on one specific variable, thereby neglecting the fact that disagreement can be co‐moving with disagreement on other variables. In this paper, we explore to what extent disagreement regarding the interest rate is driven by disagreement on inflation and unemployment. This relationship can be motivated by the theoretical concept of the Taylor rule. Using survey microdata for both professional forecasters and consumers, we provide evidence that disagreement on the interest rate is mainly driven by disagreement on inflation. We further show that disagreement is significantly influenced by central bank transparency, as well as news on money and credit conditions.     

Growth and inflation forecasts for Germany a panel-based assessment of accuracy and efficiency

We analyse forecasts of professional forecasters for Germany regarding the time span from 1970 to 2004. This novel panel data set renders it possible to assess the accuracy and efficiency of growth and inflation forecasts more efficiently than in previous studies. We argue that the forecasts are, on average, unbiased and weakly—but not strongly—efficient. Using model confidence sets suggested by Hansen et al. (2004), we find that, besides the effect of diverging forecasting dates, no other substantial differences in forecasting quality among forecasters exist. Nevertheless, on the basis of a direction-of-change analysis we argue that it is not always advisable to listen to the majority of forecasters.

Endogenous order and information aggregation

Privately informed experts with heterogeneous expertise decide when to give advice and what advice to give. Each expert’s utility depends upon that expert’s own message as well as those of the other experts. Under different forms of payoff externalities, we find varying results for the optimal order in which messages are sent and the existence of herd behavior. Under negative payoff externalities, all experts send a message together without any delay and a herd never arises. This leads to truthful revealing of all private information. Without forcing any order of speech, we obtain a result similar to the ‘anti-seniority rule’. This, however, goes in the opposite direction when positive payoff externalities are induced. An incentive structure with positive payoff externalities gives rise to a herd led by the most precise expert with a delay in the disclosure of information. Next, we test for the nature of payoff externalities in the remuneration of forecasters listed with I/B/E/S. We find that the underlying payoff externalities are negative, i.e. the benefit from making dissimilar forecasts is higher than that from making similar ones.