Macroeconomic Forecasters Research Articles

Macroeconomic forecasting and macroeconomic forecasts

The specificity of macroeconomic forecasts is determined not so much by the list of predicted indicators or by mathematical tools used, but by the unavoidable human factor, which often generates great difference between forecasts made by various professionals. In Russian-language literature, this psychological aspect of macroeconomic forecasting has not received any attention; our work is designed to fill this gap. As a source of statistical data we used the forecasts extracted from the quarterly Poll of Professional Forecasters (PPF), which began in the first quarter of 2000. An analysis of real GDP and CPI forecasts made it possible to identify optimists and pessimists among independent experts, and also to show that the official forecasts by the Russian Ministry of Economic Development and the Bank of Russia are often too optimistic (with the possible exception of forecasts for a current year). It was also confirmed that the accuracy of consensus-forecasts exceeds (in the long run) not only that of official forecasts, but also forecasts made by the vast majority of independent experts. This asserts consensus-forecasts as a benchmark against which macroeconomic forecasts of other experts and organizations should be compared. An analysis of errors for different forecast horizons showed that in the medium term, the most significant ones are associated with underestimation of the resilience of the Russian economy to external shocks. This aspect of macroeconomic forecasting is closely related to forecasting cyclical dynamics (in particular, recessions, their beginning, depth and duration). Currently, this is just what requires additional attention by macroeconomic forecasters.

Will the last be the first? Ranking German macroeconomic forecasters based on different criteria

We rank the quality of German macroeconomic forecasts using various methods for 17 regular annual German economic forecasts from 14 different institutions for the period from 1993 to 2019. Using data for just one year, rankings based on different methods correlate only weakly with each other. Correlations of rankings calculated for two consecutive years and a given method are often relatively low and statistically insignificant. For the total sample, rank correlations between institutions are generally relatively high among different criteria. We report substantial long-run differences in forecasting quality, which are mostly due to distinct average forecast horizons. In the long-run, choosing the criterion to rank the forecasters is of minor importance. Rankings based on recession years and normal periods are similar. The same does hold for rankings based on real-time vs revised data.

Are macroeconomic forecasters optimists or pessimists? A reassessment of survey based forecasts

We examine the issue of macroeconomic uncertainty in the Eurozone Area using forecasts from the European Central Bank’s Survey of Professional Forecasters from the inception of the Euro in 1999Q1 to 2020Q2. We provide new insights concerning the optimism or pessimism of the distribution of forecasts by examining the 25th and 75th quartiles of the forecast distribution for each three key macro economic variables, GDP growth, inflation and unemployment. In addition, we examine the over- or under-confidence of forecasters in the survey by deriving the term structure of ex-ante uncertainty for up to 2 years ahead and compare it to ex-post uncertainty, enabling us to make some comparisons with existing US studies. Our results suggest that GDP growth forecasts tend towards optimism, while those for inflation and unemployment tend towards pessimism. In addition, ex-ante uncertainty in forecasts for the Eurozone Area is less than ex-post uncertainty at both the short and longer-term forecasting horizons, for all three variables. This suggests a tendency towards over-confidence on the part of Eurozone forecasters.

Do macroeconomic forecasters use macroeconomics to forecast?

Faced with an uncertain future, forecasters often rely on textbook relationships to build a coherent narrative for their macroeconomic forecasts. We focus on two cornerstones of modern macroeconomics – Okun’s law and the Phillips curve – and examine whether or not professionals forecast in a way that is consistent with these. Using microdata from the US, Euro Area, and UK surveys of professional forecasters, we examine forecasts over the period 1981-2017 at the level of the individual and across different time horizons. Our findings show that the majority of forecasters produce their forecasts in a manner that is consistent with macroeconomic theory.

Investor Protection, Aggregate Accounting Earnings and Forecasts of Growth in GDP: International Evidence.

This study draws on the investor protection literature to examine differences in a country’s information environment that are likely to explain cross country variation in the extent to which macroeconomic forecasters take account of current earnings when forecasting future growth in GDP. Using a unique sample of analysts’ GDP forecasts from thirty countries, we find that economies with stronger levels of disclosure and enforcement regulation have a lower association between changes in aggregate earnings and errors in forecasts of GDP growth. The results are consistent with macroeconomic forecasters in countries with stronger investor protections taking greater account of changes in aggregate earnings when forecasting growth in GDP than analysts in countries with lower levels of investor protection.

To tell the truth or the perceived truth: Structural estimation of peer effects in China’s macroeconomic forecast

This study investigates the strategic interactions among China’s professional macroeconomic forecasters in the context of a static game with incomplete information. Professional forecasters attempt to be more precise than their peers when they are uncertain about others’ ability to forecast, given their own ability to forecast macroeconomy. We then empirically estimate the peer effects using the two-step method proposed by Bajari et al. (2010). The results identify a pronounced peer effect among professional forecasters and specify the asymmetric peer effect exerted by prominent professional forecasters. The results remain valid through several robustness checks. The forecast customers must thus address the peer effects due to competition among professional forecasters when they use forecasting reports.

Tilting the evidence: the role of firm-level earnings attributes in the relation between aggregated earnings and gross domestic product

We examine whether the contribution of firm-level accounting earnings to the informativeness of the aggregate is tilted towards earnings with specific financial reporting characteristics. Specifically, we investigate whether considering the smoothness of firm-level earnings increases the informativeness of aggregate earnings for future real GDP, and if so, whether macroeconomic forecasters use this information efficiently. Using recently-developed mixed data sampling methods, we find that the aggregate is tilted towards firms with smoother earnings and that this composition of aggregate earnings outperforms traditional weighting schemes. Further, this tilted aggregate has a stronger positive association with forecast revisions; in fact, analysts who utilize earnings the most in their forecasts appear to fully impound the informativeness of earnings smoothness. Our results synthesize and span parallel yet distinct streams of research on the role of accounting earnings in firm-level and macroeconomic outcomes and suggest an important role for financial reporting characteristics in the aggregate.

What’s the natural rate of unemployment? Answers from forecasters

ABSTRACTFor its panel survey of professional macroeconomic forecasters, the US Federal Reserve asks panelists whether they use the ‘natural rate of unemployment’ (NRU) or ‘non-accelerating inflation rate of unemployment’ (NAIRU) in formulating their forecasts and, also, to estimate the NRU/NAIRU. This paper studies responses and non-responses to those questions in order to interrogate forecasters’ views of the NRU/NAIRU. We find that most panelists in most years say they do not use the NRU/NAIRU, and they do not provide an estimate of it. Among those who do, their NRU/NAIRU estimates differ but usually do not differ significantly from the average of recent unemployment rates. We fail to find much evidence – in either their inflation and unemployment forecasts, NRU/NAIRU estimates, or revisions to those estimates over time – that panelists who use the NRU/NAIRU treat it as an unemployment rate below which inflation rises and above which inflation falls. Finally, we find that the NRU/NAIRU has no informational value for panelists who say they use it; they are no better at accurately forecasting inflation or unemployment.

Tilting the Evidence: The Role of Firm-Level Earnings Attributes in the Relation between Aggregated Earnings and Gross Domestic Product

We examine whether the contribution of firm-level accounting earnings to the informativeness of the aggregate is tilted towards earnings with specific financial reporting characteristics. Specifically, we investigate whether considering the volatility of earnings relative to the volatility of cash flows at the firm level (smoothness) increases the informativeness of aggregate earnings for future real GDP, and if so, whether macroeconomic forecasters use this information efficiently. This study innovates on recently developed mixed data sampling methods in the construction of an aggregate earnings growth measure by allowing each firm's contribution to the aggregate to vary as a function of earnings smoothness. We find that the aggregate is tilted towards firms with smoother earnings and that this composition of aggregate earnings outperforms traditional weighting schemes in the association with future GDP growth. Further, this tilted aggregate has a stronger positive association with forecast revisions; in fact, analysts who utilize earnings the most in their forecasts appear to fully impound the informativeness of earnings smoothness. Our results synthesize and span parallel yet distinct streams of research on the role of accounting earnings in firm-level and macroeconomic outcomes and suggest an important role for financial reporting characteristics in the aggregate.

Current Expected Credit Loss: Lessons from 2007-2009

We use a top-down approach to estimate the amount of credit loss allowances under the current expected credit loss (CECL) methodology during the 2007-2009 financial crisis. The new standard will replace the incurred loss methodology that is used nowadays by banks. We find that CECL would have been highly procyclical had it been in place during the past crisis, amplifying the contraction in bank lending and the severity of the crisis. This procyclicality would have occurred because macroeconomic models (and macroeconomic forecasters) are generally unable to predict turning points in the business cycle. As a result, CECL allowances generated using real-time forecasts of the economy would not have increased significantly until the beginning of 2007. As the problems in the housing sector gained steam in early 2007, credit loss allowances under CECL would have started to rise rapidly and would have caused a sharp decline in banks’ regulatory capital ratios. In addition, the trough in banks’ regulatory capital ratios would have occurred around the time of the failure of Lehman Brothers. Lastly, we estimate bank lending would have fallen by an additional 9 percentage points during 2009 as it would have been very difficult for banks to raise capital.

The effectiveness of exchange-rate-based monetary policy: evidence from survey data

ABSTRACTSingapore’s monetary policy is centred on the management of the exchange rate. We examine how macroeconomic forecasters perceive the effectiveness of this unconventional policy. We provide empirical evidence that forecasters’ expectations are consistent with a forward-looking exchange-rate-based Taylor-type policy rule. They expect monetary authorities to actively manage the currency against expected future changes in inflation and output.

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 US 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.

Macroeconomics: Theories and Episodes in the U.S.

This is a short book for students who have taken an introductory course in macroeconomics. The book contains a chapter on each of the major competing macroeconomic theories - Keynesian, Monetarist, real business cycle, and Austrian. Then the book presents macroeconomic data on five episodes in the U.S, one chapter for each episode. These are World War I and postwar recession and recovery, the Great Depression, the period of stagflation in the 1970s, and Great Moderation of the 1980s and 1990s, and the decade of the recent financial crisis. A narrative describes the macroeconomic events for each episode, and then assesses how well the implications of each theory comport with the narrative. The final chapter presents the views of important public officials and macroeconomic forecasters who have expressed themselves clearly in book form.

Do US Macroeconomic Forecasters Exaggerate Their Differences?

Application of the Bernhardt, Campello and Kutsoati (2006) test of herding to the calendar-year annual output growth and inflation forecasts suggests forecasters tend to exaggerate their differences, except at the shortest horizon when they tend to herd. We consider whether these types of behaviour can help to explain the puzzle that professional forecasters sometimes make point predictions and histogram forecasts which are mutually inconsistent.

Do US Macroeconomic Forecasters Exaggerate their Differences?

Application of the Bernhardt et al. (Journal of Financial Economics 2006; 80(3): 657–675) test of herding to the calendar‐year annual output growth and inflation forecasts suggests forecasters tend to exaggerate their differences, except at the shortest horizon, when they tend to herd. We consider whether these types of behaviour can help to explain the puzzle that professional forecasters sometimes make point predictions and histogram forecasts which are mutually inconsistent. Copyright © 2015 John Wiley & Sons, Ltd.

Are Professional Macroeconomic Forecasters Able To Do Better Than Forecasting Trends?

This paper investigates whether survey forecasters are able to make more accurate forecasts than simply supposing that the future values of the variable will move monotonically to the long‐run expectation. We consider the forecasts individually, and the consensus forecasts. Consensus survey forecasts are able to do so to varying degrees depending on the variable, but this ability is largely limited to forecasts of the current quarter.

Introduction

Economic forecasting is a well-recognized field of study in economists. However, the ability of economists to make forecast has often been questioned. Recently, Lahiry (2011) summarizes this idea, saying that ‘There is skepticism not only by laymen but by most academic economists regarding the true capability of macroeconomic forecasters. The conventional wisdom is that economic forecasters are mere charlatans.’ Despite such negative opinions residing in part of the professional and academic domains of economics, businesses and policymakers need predictions, especially when the world economy is experiencing the Great Recession. In this sense, Kennedy (2003, p. 364) asserted that ‘even if forecasts are poor, there are none better, and perhaps a poor forecast is better than none at all.’ The accuracy of economic forecasting depends on many factors, such as the quality of the data, the adequacy of the chosen method, and computational limitations. When it comes to predictions for (small) geographical/georeferenced entities, the scarcity of disaggregated data has limited the development of methods and the consequent interest in this particular empirical exercise for a long time. In contrast, forecasts at the regional/local level are a necessary complement to forecasts at the national level, allowing, for example, policymakers to allocate public expenditure between regions more efficiently. This idea reinforces the need for econometric techniques for obtaining local predictions, and in particular those where the information on each spatial unit is considered together with the one on its neighbouring units, as the latter ones are most likely to influence the former’s socioeconomic outcomes with their policies due to spatial proximity (e.g., think of interregional commuting) (see, e.g., Baltagi et al., 2012, 2014). Moreover, emerging empirical evidence suggests that, depending on the data set-up available (e.g., in terms of the cross-sectional and time dimensions) different methodological approaches may be desirable (Mayor and Patuelli, 2012, 2014). The aim of this special issue is to provide an outlet for some recent advances in regional forecasting, showing, at the same time, future research directions. Both methodological and applied contributions have been selected, varying methodologically from traditional, timeseries-based panel econometrics to spatial econometrics. The special issue contains nine

Forecasting Errors of New Venture Survival

This article studies entrepreneurs' forecast errors around market entry. Using data on nascent entrepreneurs in the U.S. and start‐ups in Finland, we find that besides being overoptimistic on average in both countries, entrepreneurs' survival expectations can barely distinguish survival from exits. Moreover, about one fourth of the entrepreneurs do not provide an estimate for the survival of a typical venture. However, among those that do provide it, the estimates are less overoptimistic. We also compare the forecast accuracy of entrepreneurs to those of macroeconomic forecasters. Our findings provide guidance for the development of positive theories of entrepreneurial belief formation and overoptimism. Copyright © 2014 Strategic Management Society.

Assessing the Evidence of Macro-Forecaster Herding: Forecasts of Inflation and Output Growth

We consider a number of ways of testing whether macroeconomic forecasters herd or anti-herd, i.e., whether they shade their forecasts towards those of others or purposefully exaggerate their differences. When applied to survey respondents' expectations of inflation and output growth the tests indicate conflicting behaviour. We show that this can be explained in terms of a simple model in which differences between forecasters are primarily due to idiosyncratic factors or reporting errors rather than imitative behaviour. Models of forecaster heterogeneity that stress informational rigidities will also falsely indicate imitative behaviour.

Uncertainty of Macroeconomic Forecasters and the Prediction of Stock Market Bubbles

We assess the contribution of macroeconomic uncertainty - approximated by the dispersion of the real GDP survey forecasts - to the ex post and ex ante prediction of stock price bubbles. For a panel of six OECD economies covering 24 years, two alternative binary chronologies of bubble periods are determined and subjected to panel logit regressions conditioning on macroeconomic indicators and expectation uncertainty. Measures of macroeconomic uncertainty improve the ex ante signalling of stock price booms and bubbles.