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.     

Inattentive agents and disagreement about economic activity

This paper evaluates empirically the (in)consistency of disagreement in survey forecasts with the prediction of sticky information models à la Mankiw-Reis, in which only a fraction of agents update their information sets at every period. To address this issue, a dynamic stochastic general equilibrium (DSGE) model that features agents’ infrequent information updating as well as nominal rigidities is fit to U.S. data. We find that the survey disagreement shares two pivotal characteristics with its model-based counterparts: (i) disagreement can be predicted by agents’ average forecast revisions reflecting the arrival of shocks; and (ii) disagreement exhibits a U-shaped relationship against the deviation of output growth from its steady state. These features arise because the arrival of new information elevates disagreement among informed and uninformed agents. Our findings indicate a substantial degree of infrequent information updating in the survey disagreement. The existing literature often uses survey disagreement as a proxy for macroeconomic uncertainty, but our finding suggests that it is unlikely to be an appropriate measure.     

Macroeconomic expectations and time varying heterogeneity:evidence from individual survey data

ABSTRACT

The goal of this paper is to investigate forecast heterogeneity and time variability in the formation of expectations using disaggregated monthly survey data on macroeconomic indicators provided by Bloomberg from June 1998 to August 2017. We show that our panel of forecasters are not rational and are moderately heterogeneous and thus confirm that previously well-established results on asset prices hold for macroeconomic indicators. We propose a flexible hybrid forecast model defined at any time as a combination of the extrapolative, regressive, adaptive and interactive heuristics. Controlling for endogenous structural breaks, we find that experts adjust their forecast behaviour at any time with some inertia in extrapolative and adaptive profiles. Changes in the formation of expectations are triggered mostly by financial shocks, and uncertainty is dealt with by using complex processes in which the fundamentalist component overweighs chartist activity. Forecasters whose models combine different relevant rules and display high temporal flexibility provide the most accurate forecasts. Authorities can then stabilize the domestic markets by encouraging fundamentalists’ forecasts through increased transparency policy.     

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.     

Quantification and characteristics of household inflation expectations in Switzerland

Inflation expectations are a key variable in conducting monetary policy. However, these expectations are generally unobservable and only certain proxy variables exist, such as surveys on inflation expectations. This article offers guidance on the appropriate quantification of household inflation expectations in the Swiss Consumer Survey, where answers are qualitative in nature. We apply and evaluate different variants of the probability approach and the regression approach; we demonstrate that models that include answers on perceived inflation and allow for time-varying response thresholds yield the best results; and we show why the originally proposed approach of Fluri and Spörndli (1987) has resulted in heavily biased inflation expectations since the mid-1990s. Furthermore, we discuss some of the key features of Swiss household inflation expectations, i.e. the fact that there has been a shift in expectation formation since 2000 (expectations are better anchored and less adaptive, and there is lower disagreement of expectations). We suggest that this may be linked to the Swiss National Bank’s adjustment of its monetary policy framework around this time. In addition, we outline how expectation formation in Switzerland is in line with the sticky information model, where information disseminates slowly from professional forecasters to households.     

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.     

Has the economic crisis of 2007-2009 changed the expectation formation process in the Euro area?

We use the ECB's Survey of Professional Forecaster to show that euro area expectations are consistent with standard macroeconomic building blocks such as the Phillips curve, Okun's law, and the Taylor rule. Moreover, the paper finds that the financial and economic crisis of 2007-2009 did not change the expectation formation process as professional forecasters still adopt macroeconomic building blocks for their forecast. The skepticism that has recently been raised concerning macroeconomic building blocks has apparently not yet affected professional forecasts. On the contrary, we conclude that professional forecasters still have faith in macroeconomic building blocks.     

Evaluating the joint efficiency of German trade forecasts - a nonparametric multivariate approach

ABSTRACT

I analyse the joint efficiency of export and import forecasts by leading economic research institutes for the years 1970 to 2017 for Germany in a multivariate setting. To this end, I compute, in a first step, multivariate random forests in order to model links between forecast errors and a forecaster’s information set, consisting of several trade and other macroeconomic predictor variables. I use the Mahalanobis distance as performance criterion and, in a second step, permutation tests to check whether the Mahalanobis distance between the predicted forecast errors for the trade forecasts and actual forecast errors is significantly smaller than under the null hypothesis of forecast efficiency. I find evidence for joint forecast inefficiency for two forecasters, however, for one forecaster I cannot reject joint forecast efficiency. For the other forecasters, joint forecast efficiency depends on the examined forecast horizon. I find evidence that real macroeconomic variables as opposed to trade variables are inefficiently included in the analysed trade forecasts. Finally, I compile a joint efficiency ranking of the forecasters.     

Can rational stubbornness explain forecast biases?

This paper examines whether the rational jumpiness/stubbornness hypothesis can explain forecast biases. Using a dataset of professional GDP forecasts for the G7 countries over the period 1989–2010, we find evidence supporting the rational stubbornness hypothesis. Specifically, forecasters underreact more when large forecast revisions are highly indicative of low forecast ability. Underreaction is less likely when the size of forecast revisions is unrelated to ability. These findings are consistent with the hypothesis that forecasters choose to smooth GDP forecasts to maximize their perceived ability.     

How sensitive are bargaining outcomes to changes in disagreement payoffs?

We use a human-subjects experiment to investigate how bargaining outcomes are affected by changes in bargainers’ disagreement payoffs. Subjects bargain against changing opponents, with randomly drawn asymmetric disagreement outcomes that vary over plays of the game, and with complete information about disagreement payoffs and the cake size. We find that subjects only respond about half as much as theoretically predicted to changes in their own disagreement payoff and to changes in their opponent’s disagreement payoff. This effect is observed in a standard Nash demand game and a related unstructured bargaining game, in both early and late rounds, and is robust to moderate changes in stake sizes. We show theoretically that standard models of expected utility maximisation are unable to account for this under-responsiveness, even when generalised to allow for risk aversion. We also show that quantal-response equilibrium has, at best, mixed success in characterising our results. However, a simple model of other-regarding preferences can explain our main results.     

A nonparametric approach to identifying a subset of forecasters that outperforms the simple average

Empirical studies in the forecast combination literature have shown that it is notoriously difficult to improve upon the simple average despite the availability of optimal combination weights. In particular, historical performance-based combination approaches do not select forecasters that improve upon the simple average going forward. This paper shows that this is due to the high correlation among forecasters, which only by chance causes some individuals to have lower root-mean-squared error (RMSE) than the simple average. We introduce a new nonparametric approach to eliminate forecasters who perform well based on chance as well as poor performers. This leaves a subset of forecasters with better performance in subsequent periods. The average of this group improves upon the simple average in the SPF particularly for bond yields where some forecasters may be more likely to have superior forecasting ability.     

Inflation forecast uncertainty

We study the inflation uncertainty reported by individual forecasters in the Survey of Professional Forecasters 1969-2001. Three popular measures of uncertainty built from survey data are analyzed in the context of models for forecasting and asset pricing, and improved estimation methods are suggested. Popular time series models are evaluated for their ability to reproduce survey measures of uncertainty. The results show that disagreement is a better proxy of inflation uncertainty than what previous literature has indicated, and that forecasters underestimate inflation uncertainty. We obtain similar results for output growth uncertainty.     

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.     

Group decision-making in the shadow of disagreement

A model of group decision-making is studied, in which one of two alternatives must be chosen. While agents differ in their preferences over alternatives, everybody prefers agreement to disagreement. Our model is distinguished by three features: private information regarding valuations, differing intensities in preferences, and the option to declare neutrality to avoid disagreement. There is always an equilibrium in which the majority is more aggressive in pushing its alternative, thus enforcing their will via both numbers and voice. However, under general conditions an aggressive minority equilibrium inevitably makes an appearance, provided that the group is large enough. Such equilibria invariably display a “tyranny of the minority”: the increased aggression of the minority always outweighs their smaller number, leading to the minority outcome being implemented with larger probability than the majority alternative. We fully characterize the asymptotic behavior of this model as group size becomes large, and show that all equilibria must converge to one of three possible limit outcomes.     

Car ownership and use in Britain: a comparison of the empirical results of alternative cointegration estimation methods and forecasts

This paper addresses two problems faced by many forecasters in the transport sector, namely how to use a relatively small sample to forecast car ownership over a long period of time and avoid the difficulties caused by spurious or nonsense regressions. Five alternative estimation methods are used to test for cointegrating relationships between per capita car ownership (and use) and real per capita personable disposable income, real motoring costs and real bus fares. These are the Engle-Granger two-stage, the Phillips-Hansen fully modified, the Wickens-Breusch one-stage, the autoregressive distributed lag, and the Johansen maximum likelihood methods. The corresponding error correction models are estimated, and a comparison made between the derived short- and long-run demand elasticities for car ownership and use. The ex-post forecasting performance of the error correction models, together with an ARIMA model specification, is evaluated using a number of performance criteria. The long-range time series forecasts obtained from the cointegrating regressions are compared with those from the cross-sectional approach used by the UK Department of the Environment, Transport and the Regions, and the policy implications discussed.     

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.     

Forecaster Overconfidence and Market Survey Performance

The authors document using the ZEW panel of German stock market forecasters that weak forecasters tend to be overconfident in the sense that they provide extreme forecasts and their confidence intervals are less likely to contain eventual realizations. They further show that moderate filters based on forecast accuracy of past performance over short rolling windows, which delicately balance ignoring relevant information and noise reduction, are somewhat successful in improving predictability. While poor performance can be due to various factors, a filter based on forecaster overconfidence, a prior tendency to have high forecast standard deviations, also improves the performance of market survey forecasts.     

Central bank forecasts and private expectations: An empirical assessment from three emerging economies

As part of their monetary policy strategy, many central banks are attempting to manage private sector expectations about key macroeconomic variables. In this article, we investigate whether forecasts provided by central banks in three inflation targeting emerging economies (Brazil, Mexico, and Poland) affect the expectations of private forecasters. In particular, we analyze whether the disagreement between the central bank and private sector forecasts applies to explain changes in private sector expectations regarding inflation and economic growth. The findings show that while central bank forecasts are higher than those made by private sector forecasters, the result is an update upwards of private forecasts and that this effect is stronger for GDP growth forecasts than for inflation forecasts.     

Forecasting UK consumer price inflation using inflation forecasts

The inflation rate is a key economic indicator for which forecasters are constantly seeking to improve the accuracy of predictions, so as to enable better macroeconomic decision making. Presented in this paper is a novel approach which seeks to exploit auxiliary information contained within inflation forecasts for developing a new and improved forecast for inflation by modeling with Multivariate Singular Spectrum Analysis (MSSA). Unlike other forecast combination techniques, the key feature of the proposed approach is its use of forecasts, i.e. data into the future, within the modeling process and extracting auxiliary information for generating a new and improved forecast. We consider real data on consumer price inflation in UK, obtained via the Office for National Statistics. A variety of parametric and nonparametric models are then used to generate univariate forecasts of inflation. Thereafter, the best univariate forecast is considered as auxiliary information within the MSSA model alongside historical data for UK consumer price inflation, and a new multivariate forecast is generated. We find compelling evidence which shows the benefits of the proposed approach at generating more accurate medium to long term inflation forecasts for UK in relation to the competing models. Finally, through the discussion, we also consider Google Trends forecasts for inflation within the proposed framework.     

Expectation formation and regime switches

Economic agents often have to make decisions in environments affected by regime switches but expectation formation has hardly been explored in this context. We report about a laboratory experiment whose participants judgmentally forecast three time series subject to regime switches. The participants make forecasts without context knowledge and without support from statistical software. Their forecasts are only based on the previous realizations of the time series. Our interest is the explanation of the average forecasts with a simple model, the bounds & likelihood heuristic. In previous studies it was shown that this model can explain average forecasting behavior very well given stable and stationary time series. We find that the forecasts after a structural break are characterized by a higher variance and less accuracy over several periods. Considering this transition phase in the model, the heuristic performs even slightly better than the Rational Expectations Hypothesis.