Expert Forecasts Research Articles

Real-Time Forecasting Using Mixed-Frequency Vars with Time-Varying Parameters

This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models (VAR) that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying parameter VAR with stochastic volatility (MF-TVP-SV-VAR). Overall, the MF-TVP-SV-VAR delivers accurate now- and forecasts and, on average, outperforms its competitors. We assess the models’ accuracy relative to expert forecasts and show that the MF-TVP-SV-VAR delivers better inflation nowcasts in this regard. Using an optimal prediction pool, we moreover demonstrate that the MF-TVP-SV-VAR has gained importance since the Great Recession.

Risk Exposure and Acquisition of Macroeconomic Information

We conduct an experiment with a representative sample from the US to study households’ demand for macroeconomic information. Respondents who learn of a higher personal exposure to unemployment risk during recessions increase their demand for an expert forecast about the likelihood of a recession. This finding is consistent with macroeconomic models of endogenous information acquisition, according to which the demand for information depends on its expected benefits. Moreover, respondents’ updating about their personal unemployment risk suggests that households are imperfectly informed about their exposure to aggregate fluctuations, which may distort their beliefs about the benefits of acquiring macroeconomic information.

Latin American Reflections on Integration Processes: from Theory of Peripheral Capitalism to “Sudamexit”

Integration processes in Latin America and Caribbean basin have been traditionally provoking strong research interest. Over the past decades, Latin American integration has tested plethora of institutional designs, ranging from relatively uniform subregional trade blocs - CACM, LAFTA, etc. to multifunctional partnerships with an identity-forming component, like Unasur or CELAC. This paper is an attempt to show how the Latin American academic community itself analyzes the integration in the “domestic” region. Forming the literature review, the authors, firstly, show how Latin American integrationism has transformed with the successive change of the phases of the “old”, “open” and “post-liberal” regionalism. Despite the fact that the types of integration in each of the periods differ significantly, scientists approach them in quite a similar way. They have been engineering the region socially and have been using such basic concepts as globalización , soberanía and desarrollo . The theory and practice of Latin American integration has always been closely intertwined. Secondly, the authors distinguish three today’s Latin American “big discourses” about integration - political-economic, geopolitical and state-centered. Each of these discourses takes into account the internal and external conditions that led to the post-liberal phase of integration. Third, expert forecasts about the prospects of regional associations against the background of the crisis tendencies of recent years are presented in this paper. Latin American experts agree on the fact that regional integration has entered the new phase, the most important features of which are the globalization slowing down, the complication of inter-American relations due to the “Trump factor”, the decline of left-progressist forces in the region.

Improving expert forecasts in reliability: Application and evidence for structured elicitation protocols

AbstractQuantitative expert judgements are used in reliability assessments to inform critically important decisions. Structured elicitation protocols have been advocated to improve expert judgements, yet their application in reliability is challenged by a lack of examples or evidence that they improve judgements.This paper aims to overcome these barriers. We present a case study where two world‐leading protocols, the IDEA protocol and the Classical Model, were combined and applied by the Australian Department of Defence for a reliability assessment. We assess the practicality of the methods and the extent to which they improve judgements.The average expert was extremely overconfident, with 90% credible intervals containing the true realisation 36% of the time. However, steps contained in the protocols substantially improved judgements. In particular, an equal weighted aggregation of individual judgements and the inclusion of a discussion phase and revised estimate helped to improve calibration, statistical accuracy, and the Classical Model score. Further improvements in precision and information were made via performance weighted aggregation.This paper provides useful insights into the application of structured elicitation protocols for reliability and the extent to which judgements are improved. The findings raise concerns about existing practices for utilising experts in reliability assessments and suggest greater adoption of structured protocols is warranted. We encourage the reliability community to further develop examples and insights.

A leading macroeconomic indicators’ based framework to automatically generate tactical sales forecasts

Tactical sales forecasting is fundamental to production, transportation and personnel decisions at all levels of a supply chain. Traditional forecasting methods extrapolate historical sales information to predict future sales. As a result, these methods are not capable of anticipating macroeconomic changes in the business environment that often have a significant impact on the demand. To account for these macroeconomic changes, companies adjust either their statistical forecast manually or rely on an expert forecast. However, both approaches are notoriously biased and expensive. This paper investigates the use of leading macroeconomic indicators in the tactical sales forecasting process. A forecasting framework is established that automatically selects the relevant variables and predicts future sales. Next, the seasonal component is predicted by the seasonal naive method and the long-term trend using a LASSO regression method with macroeconomic indicators, while keeping the size of the indicator’s set as small as possible. Finally, the accuracy of the proposed framework is evaluated by quantifying the impact of each individual component. The carried out analysis has shown that the proposed framework achieves a reduction of 54.5% in mean absolute percentage error when compared to the naive forecasting method. Moreover, compared to the best performing conventional methods, a reduction of 25.6% is achieved in the tactical time window over three different real-life case studies from different geographical areas.

Aggregation mechanisms for crowd predictions

When the information of many individuals is pooled, the resulting aggregate often is a good predictor of unknown quantities or facts. This aggregate predictor frequently outperforms the forecasts of experts or even the best individual forecast included in the aggregation process (“wisdom of crowds”). However, an appropriate aggregation mechanism is considered crucial to reaping the benefits of a “wise crowd”. Of the many possible ways to aggregate individual forecasts, we compare (uncensored and censored) arithmetic and geometric mean and median, continuous double auction market prices and sealed bid-offer call market prices in a controlled experiment. We use an asymmetric information structure, where participants know different sub-sets of the total information needed to exactly calculate the asset value to be estimated. We find that prices from continuous double auction markets clearly outperform all alternative approaches for aggregating dispersed information and that information lets only the best-informed participants generate excess returns.

Decomposing Long Bond Returns: A Decentralized Modeling Approach

This paper develops a decentralized theory that determines the fair value of the yield-to-maturity of a bond or bond portfolio based purely on the near-term dynamics of the yield itself. The theory decomposes the yield into three components: its expected change, its risk premium, and its convexity effects. The convexity effect can be constructed with a historical variance estimator. The expectation can come from statistical models or expert forecasts, leaving the remaining component of the yield as a risk premium estimate. Comparative yield analysis of different bonds can start with commonality assumptions on their risks, risk premiums, and expected change.

Experts forecasts on the demand for energy carriers in motor vehicle transport in Poland up to year 2035

Presentation of the number of passenger cars, vehicles other than passenger cars with GVM up to 3.5 tons and above 3.5 tons (trucks, buses and special vehicles), registered in Poland as at the end of 2015, with types of energy carriers. Forecasts of transport performance of the vehicle fleet and the forecast of the fleet volume in Poland by year 2035. Expert forecasts of energy carriers con-sumption (petrol, diesel oil, LPG, CNG, electric power, hydrogen) up to year 2035.

Main Trends and Conclusions of Socioeconomic Development of Russia for June 2019

The almost concurrent deterioration of both the official and expert forecasts of Russia’s economic growth in 2019 coincided with the deepening pessimism about the prospects for the world economy. As regards the former, analysts were disillusioned by the puny results of the year beginning, while as regards the latter, they became increasingly convinced that contradictions between the USA and China would intensify, no matter what the outcome of US-China trade talks might be.

Традиционные подходы и новые идеи в работах Марии Альфредовны Глазовской в области тематического картографирования

Professor Maria Glazovskaya (1912–2016) – an outstanding geographer, geochemist and soil scientist, made a prominent contribution to the formation and development of several aspects of thematic mapping both in conceptual and methodological issues. These aspects, namely, soil, landscape- and soil-geochemical, as well as ecological mapping, were derived from the knowledge on soils combined with the concepts of geochemical migrations facilities for certain chemical elements in soils and landscapes. Methodology of compilation of such maps presumes purposeful interpretation of diverse soil and landscape features, their expert evaluation and forecast of response reactions of soils and landscapes to certain technogenic loads. Maria Glazovskaya proposed innovative approaches to thematic mapping enabling her to compile original maps. She introduced the principle of “prognostic information capacity of natural factors”, which means that properties of landscape components contain information appropriate for evaluating the resilience of natural systems. The ideas and methods proposed by Maria Glazovskaya are now implemented in basic and applied thematic mapping.

Stability of Experimental Results: Forecasts and Evidence

How robust are experimental results to changes in design? And can researchers anticipate which changes matter most? We consider a specific context, a real-effort task with multiple behavioral treatments, and examine the stability along six dimensions: (i) pure replication; (ii) demographics; (iii) geography and culture; (iv) the task; (v) the output measure; (vi) the presence of a consent form. We use rank-order correlation across the treatments as measure of stability, and compare the observed correlation to the one under a benchmark of full stability (which allows for noise), and to expert forecasts. The academic experts expect that the pure replication will be close to perfect, that the results will differ sizably across demographic groups (age/gender/education), and that changes to the task and output will make a further impact. We find near perfect replication of the experimental results, and full stability of the results across demographics, significantly higher than the experts expected. The results are quite different across task and output change, mostly because the task change adds noise to the findings. The results are also stable to the lack of consent. Overall, the full stability benchmark is an excellent predictor of the observed stability, while expert forecasts are not that informative. This suggests that researchers' predictions about external validity may not be as informative as they expect. We discuss the implications of both the methods and the results for conceptual replication. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Aggregation Mechanisms for Crowd Predictions

When the information of many individuals is pooled, the resulting aggregate often is a good predictor of unknown quantities or facts (“wisdom of crowds”). This aggregate predictor frequently outperforms the forecasts of experts or even the best individual forecast included in the aggregation process. However, an appropriate aggregation mechanism is considered crucial to reaping the benefits of a “wise crowd”. Of the many possible ways to aggregate individual forecasts, we compare (uncensored and censored) mean and median, continuous double auction market prices and sealed bid-offer call market prices in a controlled experiment. We use an asymmetric information structure where subjects know different subsets of the total information needed to exactly calculate the asset value to be estimated. We find that prices from continuous double auction markets clearly outperform all alternative approaches for aggregating dispersed information and that information is only useful to the best-informed subjects.

Do Thank-You Calls Increase Charitable Giving? Expert Forecasts and Field Experimental Evidence

Calling to thank donors is a key fundraising strategy in the non-profit sector. Yet the effectiveness of these calls remains untested. We report on field experiments with public television stations and a national non-profit in which new donors were randomized to receive a thank-you call or not. The experiments involved about 600,000 donors and 500,000 thank-you calls over 6 years. We found a precisely estimated null effect of calls on subsequent giving. This result is in stark contrast to the incentivized forecasts of fundraising professionals and the general public, who anticipated that calls would increase donor retention by about 80%.

Do forecasters of major exchange rates herd?

This paper uses forecast data from 1995 through 2014 to examine, whether the market consensus of exchange rate forecasts has an effect on the forecasts of individual experts. Such an effect could take the form of herding or anti-herding. We use a very comprehensive data set to study experts' forecasts of three of the most important exchange rates. The results indicate that anti-herding vis-à-vis the consensus of forecasts occurs more often than herding. We also show how the increase in the forecasting horizon and financial crises affect the intensity of anti-herding behavior. Moreover, we report that the (anti-)herding behavior does not affect the forcasting performnce.

Medium term growth forecasts: Experts vs. simple models

We compare the medium-term GDP growth forecasts generated by experts to those generated by simple models. This study analyzes a large set of forecasts that covers 48 countries from 1997 to 2016. Out-of-sample exercises indicate that no noticeable difference in performance is observed for advanced economies. In contrast, in the case of emerging economies, model forecasts perform better than expert forecasts. In addition, similar patterns are found for a collection of forecasts from a different set of experts, which suggests that the reported regularity is prevalent. Further analyses suggest that the documented difference in performance can be explained by an optimism bias, excessive reactions to innovations in growth trajectories, and insufficient responses to the information contained in the current account balance.

Forecasting Fertility Based on Economic Factors

The Object of the Study: Demographic situation, population reproduction. fertility, fertility factors by group: demographic factors directly included in the number of benefits, subsidies and other measures of state demographic policy, economic factors that have a direct or indirect impact on the demographic situation in General, and the birth rate of the populationThe Subject of Study: fertility Forecasting based on selected groups of factors, using statistical methods, in particular regression equations.The Puroose of the Puroose of the Study is : to Identify the dominant influence of GDP, per capita income, the level of specific budget expenditures and other economic indicators on the main indicators of fertility.The Main Provisions of the Article: according to the calculations of the coefficients of pair correlation, the main indicators of fertility, and the key indicator TFR in particular,- depend not only on the passage of "demographic waves", and the level of costs of the national project "Demography", but also on GDP and other socioeconomic indicators. Traditional fertility projections are based on models that link age-specific fertility rates and the total fertility rate to the number of female populations that vary with the passage of "demographic waves". The ideology of traditional forecasting is the theory of "demographic transition". This article proposes to expand the field of forecasting methods due to a more confident connection of demographic indicators with economic ones. In particular, it is assumed that economic growth, and the resulting increase in specific budget expenditures on social, including demographic, policy, income growth and housing security of the population, can "equalize" the demographic wave, lowering its height and reducing its amplitude. Economic factors, if they are positive, can mitigate the decline in fertility and increase its growth. This addition to the generally accepted, but almost "separated" from the economy theories of "demographic transition", allow to adjust the forecasts of the total fertility rate (TFR). For this correction, the article proposes to use regression equations. This group of equations is suitable when retrospective statistical series of economic indicators for a sufficiently long period of time are available for analysis, and there are official (or generally accepted expert forecasts) for the future. This is the difference between the equations used in the article and more complex mathematical constructions, which offer a certain explanation of the situation, but do not have a statistical base for forecasting. In addition, the proposed equations are simple and effective for use by practitioners, because they do not require complex mathematical programs and can be easily implemented in the Excel processor.

Expert forecast and realized outcomes in technology foresight

Contrary to what happens in forecasting, in which the repetitive nature of events lends itself to the ex post validation of expert judgments, it is usually very difficult to compare directly the forecast of technology foresight studies with realized outcomes. When the comparison is feasible, therefore, there is large opportunity for learning and methodological refinement. The authors of this study had the opportunity to re-examine the findings of a technology foresight exercise on the medical device industry with realized technological performance, five years later. Among the findings of the comparison exercise, intriguing false positive as well as false negative cases have been identified. The paper suggests that these cases are due to specific cognitive and motivational biases of experts and examines the way in which they are at work in the foresight process. It argues that these biases are due to the inability of experts to reason systematically in abstract (or “functional”) terms during the whole foresight process. It also suggests a methodology to mitigate the biases and to manage the emergence of false positives and false negatives.

Російська Федерація в умовах багатополярного транзиту

The state of formation of a new system of world order and international relations is outlined. It was found out that there is a transition from post-bipolar to multi-polar world order. At the moment, the world is in a state of transit or transitive order, since the old world-system, which took shape after the end of the Cold War, went back to the past, while the new paradigm of the world order is the subject of uncertainty. The new world order, whose outline is more and more clearly distinguished by a distortion, is to be understood rather as a global mess that is a hallmark of the present stage of globalization. Under these circumstances, large, medium and small states are trying to find their place in the future of a multipolar world, which, according to the forecasts of most experts, will be multipolar. The United States is gradually moving away from its role as a world leader trying to focus ondomestic issues. Among the new centers of power are traditionally China, which is increasingly expanding its influence by expanding its economic presence in different regions through investments in industrial and infrastructure projects. The Russian Federation is compelled to seek a compromise from the West in the sense of recognizing its Russian sphere of strategic interests at the regional and partly global level in order to affirm the status of one of the centers of influence comparable in its power with the USA and China. A major geostrategic task for Russia is the return of the world to the realities of the twentieth century, or during the rhetoric of classical realism, which prevailed such categories as "zones of influence", "buffer zones", "balance of power", "balance of interests". It has been found that the resources available in Russia do not serve as a full-fledged geopolitical basis for designing global influence. That is why the Russian Federation has resorted to aggression and destabilization of the transitive world order in order to support controlled chaos in different directions.

Predicting Experimental Results: Who Knows What?

We analyze how academic experts and nonexperts forecast the results of 15 piece-rate and behavioral treatments in a real-effort task. The average forecast of experts closely predicts the experimental results, with a strong wisdom-of-crowds effect: the average forecast outperforms 96 percent of individual forecasts. Citations, academic rank, field, and contextual experience do not correlate with accuracy. Experts as a group do better than nonexperts, but not if accuracy is defined as rank-ordering treatments. Measures of effort, confidence, and revealed ability are predictive of forecast accuracy to some extent and allow us to identify “superforecasters” among the nonexperts.

Probability Forecasts and Their Combination: A Research Perspective

We explore some recent, and not so recent, developments concerning the use of probability forecasts and their combination in decision making. Despite these advances, challenges still exist. We expand on some important challenges influencing the “goodness” of combined probability forecasts such as miscalibration, dependence among forecasters, and selection of an appropriate evaluation measure while connecting the processes of aggregating and evaluating forecasts to decision making. Through three important applications from the domains of meteorology, economics, and political science, we illustrate state-of-the-art usage of probability forecasts: how they are combined, evaluated, and communicated to stakeholders. We expect to see greater use and aggregation of probability forecasts, especially given developments in statistical modeling, machine learning, and expert forecasting; the popularity of forecasting competitions; and the increased reporting of probabilities in the media. Our vision is that increased exposure to and improved visualizations of probability forecasts will enhance the public’s understanding of probabilities and how they can contribute to better decisions.