Information or Institution?

2011 ◽  
Vol 231 (1) ◽  
Author(s):  
Roland Döhrn ◽  
Christoph M. Schmidt
Keyword(s):  
Personal Experience ◽  
Forecast Accuracy ◽  
Forecast Errors ◽  
Forecast Horizon ◽  
Good Investment ◽  
New Information ◽  
German Research ◽  
Macroeconomic Forecast ◽  
The Individual ◽  
The Impact

SummaryThe accuracy of macroeconomic forecast depends on various factors, most importantly the mix of analytical methods used by the individual forecasters, the way that their personal experience is shaping their identification strategies, but also their efficiency in translating new information into revised forecasts. In this paper we use a broad sample of forecasts of German GDP and its components to analyze the impact of institutions and information on forecast accuracy. We find that forecast errors are a linear function of the forecast horizon, which serves as an indicator of the information available at the time a forecast is produced. This result is robust over a variety of different specifications. As better information seems to be the key to achieving better forecasts, approaches for acquiring reliable information early seem to be a good investment. By contrast, the institutional factors tend to be small and statistically insignificant. It has to remain open, whether this is the consequence of the efficiency-enhancing competition among German research institutions or rather the reflection of an abundance of forecast suppliers.

scholarly journals Seeking Consensus: A New Approach

2010 ◽  
Vol 138 (12) ◽  
pp. 4402-4415 ◽  
Author(s):  
Paul J. Roebber
Keyword(s):  
Minimum Temperature ◽  
Forecast Accuracy ◽  
Cost Savings ◽  
Absolute Error ◽  
Electricity Production ◽  
Forecast Errors ◽  
Consensus Forecasts ◽  
Temperature Forecast ◽  
Model Output Statistics ◽  
The Individual

Abstract Simulated evolution is used to generate consensus forecasts of next-day minimum temperature for a site in Ohio. The evolved forecast algorithm logic is interpretable in terms of physics that might be accounted for by experienced forecasters, but the logic of the individual algorithms that form the consensus is unique. As a result, evolved program consensus forecasts produce substantial increases in forecast accuracy relative to forecast benchmarks such as model output statistics (MOS) and those from the National Weather Service (NWS). The best consensus produces a mean absolute error (MAE) of 2.98°F on an independent test dataset, representing a 27% improvement relative to MOS. These results translate to potential annual cost savings for electricity production in the state of Ohio of the order of $2 million relative to the NWS forecasts. Perfect forecasts provide nearly $6 million in additional annual electricity production cost savings relative to the evolved program consensus. The frequency of outlier events (forecast busts) falls from 24% using NWS to 16% using the evolved program consensus. Information on when busts are most likely can be provided through a logistic regression equation with two variables: forecast wind speed and the deviation of the NWS minimum temperature forecast from persistence. A forecast of a bust is 4 times more likely to be correct than wrong, suggesting some utility in anticipating the most egregious forecast errors. Discussion concerning the probabilistic applications of evolved programs, the application of this technique to other forecast problems, and the relevance of these findings to the future role of human forecasting is provided.

scholarly journals Tracing the Roots of Cognitive Linguistics in Hermann Paul’s “Principles of the History of Language”

2015 ◽  
Vol 28 (33) ◽  
pp. 81-88
Author(s):  
Tatyana V. Romanova
Keyword(s):  
Personal Experience ◽  
Cognitive Linguistics ◽  
Vantage Point ◽  
Important Work ◽  
Cognitive Approach ◽  
History Of ◽  
German Linguist ◽  
The Individual ◽  
The Impact

The paper examines the impact of Hermann Paul’s ideas on the development of anthropocentric cognitive linguistics in Russia and Europe. The anthropocentric and pragmatic approaches to the study of language, related, in particular, to the consideration of language as “the language of the individual” and a product of personal experience, were formulated by the German linguist Hermann Paul (1846-1921) in his Principles of the History of Language (1920). In this important work, Paul argues that language development is driven by subjective, psychological factors, acknowledging the Man’s central role in the learning process (anthropocentrism). Viewing Paul’s position from the vantage point of modern linguistics, the article seeks to establish the rightness of the cognitive school in linguistics, provides a brief overview of Paul’s key ideas and concludes that he anticipated and formulated the main principles of the cognitive approach to language, namely: language as a product of individual experience, the role of individual notions in forming a word’s meaning, analogy as a mechanism of language acquisition, metaphor as a mechanism of learning and the connection of language with other mental processes.

scholarly journals The Impact of Big Data on Firm Performance: An Empirical Investigation

2019 ◽  
Vol 109 ◽  
pp. 33-37 ◽  
Author(s):  
Patrick Bajari ◽  
Victor Chernozhukov ◽  
Ali Hortaçsu ◽  
Junichi Suzuki
Keyword(s):  
Big Data ◽  
Firm Performance ◽  
Empirical Investigation ◽  
Forecast Accuracy ◽  
Forecast Errors ◽  
Retail Sales ◽  
Sales Data ◽  
Empirical Results ◽  
Time Periods ◽  
The Impact

We examine the impact of “big data” on firm performance in the context of forecast accuracy using proprietary retail sales data obtained from Amazon. We measure the accuracy of forecasts in two relevant dimensions: the number of products (N), and the number of time periods for which a product is available for sale (T). Theory suggests diminishing returns to larger N and T, with relative forecast errors diminishing at rate 1/sqrt(N)+1/sqrt(T). Empirical results indicate gains in forecast improvement in the T dimension but essentially flat N effects.

The impact of employees’ well-being on performance in the workplace

2018 ◽  
Vol 17 (2) ◽  
pp. 72-75 ◽  
Author(s):  
Janice Haddon
Keyword(s):  
Mental Health ◽  
Personal Experience ◽  
Well Being ◽  
Content Type ◽  
Different Types ◽  
The Individual ◽  
Hr Managers ◽  
The Impact ◽  
Mental Well Being ◽  
Made In

Purpose The purpose of this paper is to look at the link between employee well-being in the workplace and its effect on productivity. Specifically, it looks at the different types of well-being (physical, nutritional and mental) and how organisations should be putting the welfare of staff at the heart of their workplace culture, to ensure their well-being and productivity. Design/methodology/approach Written as a viewpoint, the paper outlines the ways in which organisations traditionally offer employees incentives to look after their physical and nutritional well-being, such as gym memberships and healthy food options. It goes on to look at the impact of mental health on productivity and the symptoms employees may display if they are suffering with mental illness. Findings Mental health is one of the key contributors to productivity, and employers should do more to ensure the mental well-being of their staff. In addition, it outlines the impact a person’s mental well-being can have not only on themselves, but also on those around them, affecting, therefore, the productivity of a team/organisation as a whole, not just the individual. Originality/value The findings in the paper are based on personal experience, as well as recent statistics which are used to highlight the importance of the arguments made in the paper about the effect of mental health on and individual’s well-being and productivity. It is designed to advise HR managers and employers of the steps they can take to ensure the well-being of their employees and the benefits to themselves in doing so.

Absolute Forecast Errors of Earnings in Malaysian IPO Prospectuses: The Impact of Ethnic Diversity

2014 ◽  
Vol 68 (3) ◽  
Author(s):  
Mohammed Abdullah Ammer ◽  
Nurwati A. Ahmad-Zaluki
Keyword(s):  
Ethnic Diversity ◽  
Boards Of Directors ◽  
Forecast Error ◽  
Forecast Accuracy ◽  
Earnings Forecasts ◽  
Ordinary Least Squares ◽  
Audit Committees ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
The Impact

The main focus of this paper is the earnings forecast, a vital information included in IPO prospectus. Specifically, our paper examined the impact of ethnic diversity groups on the boards of directors and audit committees in terms of earnings forecast accuracy. We are motivated by the lack of prior studies related to investigating IPO earnings forecast. Cross-sectional Ordinary Least Squares (OLS) modeling was conducted on 190 Malaysian IPOs from 2002 to 2012. For the evaluation of earnings forecast accuracy, we mathematically used the metric of Absolute Forecast Error (AFER). Moreover, for the test of robustness, we used the metric of Squared Forecast Error (SQFER) as error measurement, as it mostly deals with large errors. The empirical results indicate that the ethnic diversity groups on boards and audit committees have an impact on the accuracy of earnings forecasts. However, the evidence is significant for Chinese and Malay serving on boards but insignificant in terms of Chinese and Malay serving on audit committee. The findings indicate that multi-ethnic groups in Malaysian IPO companies could hinder the capability of IPO companies to achieve accurate earnings forecasts in their prospectuses.

Audit quality and attributes of management earnings forecasts

2017 ◽  
Vol 16 (4) ◽  
pp. 406-423 ◽  
Author(s):  
Yu-Ho Chi ◽  
David A. Ziebart
Keyword(s):  
Corporate Governance ◽  
Audit Quality ◽  
Forecast Accuracy ◽  
Academic Community ◽  
Forecast Errors ◽  
Management Earnings Forecasts ◽  
Control Variables ◽  
Content Type ◽  
Time Period ◽  
The Impact

Purpose The purpose of this study is to examine the impact of auditor type on management’s choice of forecast precision and management forecast errors, including the effects of corporate governance. The authors use a different sample and a larger period of years to determine whether prior inferences are robust across these dimensions as well as various corporate governance and other control variables. Design/methodology/approach This quasi-experimental study uses archival data in regression-based analyses. Findings The authors find firms with Big 5 auditors issue forecasts that have larger forecast errors are biased downward and are less precise. The inferences of this study are robust to the inclusion of corporate governance variables, along with an extensive number of control variables found important in prior studies. Research limitations/implications While the sample and time period may be limited, the authors have no evidence this biases the results. Practical implications More stringent auditing may have an unintended consequence of reducing the informativeness of management forecasts, as managers act strategically in regards to forecast accuracy, bias and precision. Social implications The inferences of this study indicate that while higher quality audits could constrain earnings management, higher quality audits may induce management to provide forecasts that have greater errors, may be biased and may be less informative. Originality/value The results and inferences of this study suggest that the inferences in prior studies hold across a different sample and a different time period. This is important given concerns in the academic community regarding the extent to which prior studies can be replicated.

scholarly journals Synergy in fertility forecasting: improving forecast accuracy through model averaging

Genus ◽  
2020 ◽  
Vol 76 (1) ◽  
Author(s):  
Han Lin Shang ◽  
Heather Booth
Keyword(s):  
Forecast Accuracy ◽  
Model Averaging ◽  
Confidence Set ◽  
Forecast Horizon ◽  
Average Accuracy ◽  
Improve Accuracy ◽  
Using Data ◽  
The Individual ◽  
Model Confidence Set ◽  
First Time

Abstract Accuracy in fertility forecasting has proved challenging and warrants renewed attention. One way to improve accuracy is to combine the strengths of a set of existing models through model averaging. The model-averaged forecast is derived using empirical model weights that optimise forecast accuracy at each forecast horizon based on historical data. We apply model averaging to fertility forecasting for the first time, using data for 17 countries and six models. Four model-averaging methods are compared: frequentist, Bayesian, model confidence set, and equal weights. We compute individual-model and model-averaged point and interval forecasts at horizons of one to 20 years. We demonstrate gains in average accuracy of 4–23% for point forecasts and 3–24% for interval forecasts, with greater gains from the frequentist and equal weights approaches at longer horizons. Data for England and Wales are used to illustrate model averaging in forecasting age-specific fertility to 2036. The advantages and further potential of model averaging for fertility forecasting are discussed. As the accuracy of model-averaged forecasts depends on the accuracy of the individual models, there is ongoing need to develop better models of fertility for use in forecasting and model averaging. We conclude that model averaging holds considerable promise for the improvement of fertility forecasting in a systematic way using existing models and warrants further investigation.

scholarly journals The Impact of Integrated Reporting on Analysts’ Forecasts

2019 ◽  
Vol 12 (1) ◽  
pp. 76 ◽  
Author(s):  
Romy Bakker ◽  
Georgios Georgakopoulos ◽  
Virginia - Athanasia Sotiropoulou ◽  
Kanellos S. Tountas
Keyword(s):  
Positive Impact ◽  
Forecast Accuracy ◽  
Analyst Forecast ◽  
Forecast Errors ◽  
Integrated Reporting ◽  
Big 4 ◽  
Audit Firms ◽  
Sustainability Disclosure ◽  
The Impact ◽  
The Relationship

Shareholders are very interested in the relationship between Integrated Reporting and analyst forecast accuracy. Integrated Reporting is deemed to reduce information asymmetry between the company and shareholders. The purpose of this paper is to provide evidence on the relationship between Integrated Reporting and analyst forecast accuracy. Analyst forecast accuracy is examined for a global sample of companies that adopted Integrated Reporting, companies that get assurance on Integrated Reporting, companies that receive assurance on their integrated reports by one of the Big 4, and for a south african sample, companies that are mandated to use Integrated Reporting. Information for analysts’ forecasts is retrieved from the I/B/E/S database and information for Integrated Reporting is retrieved from the GRI Sustainability Disclosure Database. We do not find a significant impact of Integrated Reporting on analyst forecast errors. Similarly, attestation of the reports by bigger or smaller audit firms does not seem to affect analysts’ forecast accuracy. In South Africa however, a positive impact on analysts’ forecast accuracy is observed suggesting that the effect of mandatory integrated disclosures is important for analysts’ forecasts.

scholarly journals COMPLIANCE WITH IFRS REQUIRED DISCLOSURE AND ANALYSTS’ FORECAST ERRORS: EVIDENCE FROM BRAZIL

2018 ◽  
Vol 29 (1) ◽  
pp. 77-100 ◽  
Author(s):  
Edilene Santana Santos ◽  
Flávia Almeida Morato da Silva ◽  
Hsia Hua Sheng ◽  
Mayra Ivanoff Lora
Keyword(s):  
Financial Reporting ◽  
Negative Relationship ◽  
Forecast Accuracy ◽  
Economic Benefits ◽  
Earnings Forecast ◽  
Forecast Errors ◽  
Ifrs Adoption ◽  
Compliance Level ◽  
Before And After ◽  
The Impact

We analyze the relationship between analysts' earnings forecast errors and Brazilian listed firms’ compliance with International Financial Reporting Standards (IFRS) required disclosure. Through analysis of a panel data, we examine whether the variance in the Brazilian firms’ disclosure compliance levels in the Notes to Financial Statements for 2010 and 2012 affects analysts’ earnings forecast errors for 2011 and 2013, respectively, finding a significant negative relationship between these variables. By performing a compliance level analysis per firm, our study considers whether and to what extent firms effectively disclose as required by IFRS (as “IFRS serious adopters”), distinguishing them from firms that mere formally adopt IFRS (as “IFRS label adopters”), without effectively complying with it. Following other studies, we use four alternative models to measure the disclosure compliance level per firm, and we do not find significant improvement in the firms’ disclosure levels from 2010 to 2012, except if we use the most tolerant model.  By this approach, our research contributes to clarify the impact of IFRS adoption on analysts’ forecast accuracy, as other studies that use only binary variables (analysts’ forecasts before and after IFRS adoption) have found contradictory results. Our findings confirm other studies on the international accounting convergence in other countries, emphasizing that compliance is at least as important as the simply formal IFRS adoption. This corroborates the relevance of enforcement mechanisms to induce firms to better comply with IFRS, thus to better attain the economic benefits expected from its adoption.

Audit Quality and Analyst Forecast Accuracy: The Impact of Forecast Horizon and Other Modeling Choices

2015 ◽  
Vol 35 (2) ◽  
pp. 167-185 ◽  
Author(s):  
Yi (Ava) Wu ◽  
Mark Wilson
Keyword(s):  
Audit Quality ◽  
Forecast Accuracy ◽  
Earnings Forecasts ◽  
Analyst Forecasts ◽  
Data Availability ◽  
Analyst Forecast ◽  
Forecast Horizon ◽  
Financial Reports ◽  
Decision Usefulness ◽  
The Impact

SUMMARY The accuracy and other properties of analyst earnings forecasts represent potentially useful proxies for the impact of audit quality on client financial reports. Extant research in the auditing literature, however, is characterized by diametrically opposite predictions and inconsistent findings regarding the relationship between audit quality and analyst forecast accuracy. We argue that a potential reason for the inconsistency in the literature reflects these studies' focus on end-of-year forecast accuracy, which is subject to competing effects of audit quality. High-quality auditors may simultaneously improve forecast accuracy through their impact on the decision usefulness of clients' prior period reports, and reduce forecast accuracy by constraining client attempts to manage earnings in the direction of the consensus forecast. We argue and present evidence in support of the conjecture that analysts' beginning-of-year forecasts are a superior metric for identifying the impact of audit quality on the properties of analyst forecasts because the decision usefulness effect of audit quality should be dominant with respect to those forecasts. Data Availability: Data are available from sources identified in the article.

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