Estimates and inferences in accounting panel data sets: comparing approaches

2017 ◽  
Vol 18 (3) ◽  
pp. 268-283
Author(s):  
Felix Canitz ◽  
Panagiotis Ballis-Papanastasiou ◽  
Christian Fieberg ◽  
Kerstin Lopatta ◽  
Armin Varmaz ◽  
...  
Keyword(s):  
Time Series ◽  
Monte Carlo ◽  
Cross Section ◽  
Design Methodology ◽  
Estimation Methods ◽  
Standard Errors ◽  
Data Sets ◽  
Content Type ◽  
The Mean ◽  
Robust Standard Errors

Purpose The purpose of this paper is to review and evaluate the methods commonly used in accounting literature to correct for cointegrated data and data that are neither stationary nor cointegrated. Design/methodology/approach The authors conducted Monte Carlo simulations according to Baltagi et al. (2011), Petersen (2009) and Gow et al. (2010), to analyze how regression results are affected by the possible nonstationarity of the variables of interest. Findings The results of this study suggest that biases in regression estimates can be reduced and valid inferences can be obtained by using robust standard errors clustered by firm, clustered by firm and time or Fama–MacBeth t-statistics based on the mean and standard errors of the cross section of coefficients from time-series regressions. Originality/value The findings of this study are suited to guide future researchers regarding which estimation methods are the most reliable given the possible nonstationarity of the variables of interest.

Rigorous time-domain analysis of statistically oriented graphene sheet fluctuations

2017 ◽  
Vol 36 (5) ◽  
pp. 1351-1363 ◽  
Author(s):  
Athanasios N. Papadimopoulos ◽  
Stamatios A. Amanatiadis ◽  
Nikolaos V. Kantartzis ◽  
Theodoros T. Zygiridis ◽  
Theodoros D. Tsiboukis
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Finite Difference ◽  
Surface Waves ◽  
Time Domain ◽  
Finite Difference Time Domain ◽  
Mean Value ◽  
Content Type ◽  
The Mean ◽  
Difference Time

Purpose Important statistical variations are likely to appear in the propagation of surface plasmon polariton waves atop the surface of graphene sheets, degrading the expected performance of real-life THz applications. This paper aims to introduce an efficient numerical algorithm that is able to accurately and rapidly predict the influence of material-based uncertainties for diverse graphene configurations. Design/methodology/approach Initially, the surface conductivity of graphene is described at the far infrared spectrum and the uncertainties of its main parameters, namely, the chemical potential and the relaxation time, on the propagation properties of the surface waves are investigated, unveiling a considerable impact. Furthermore, the demanding two-dimensional material is numerically modeled as a surface boundary through a frequency-dependent finite-difference time-domain scheme, while a robust stochastic realization is accordingly developed. Findings The mean value and standard deviation of the propagating surface waves are extracted through a single-pass simulation in contrast to the laborious Monte Carlo technique, proving the accomplished high efficiency. Moreover, numerical results, including graphene’s surface current density and electric field distribution, indicate the notable precision, stability and convergence of the new graphene-based stochastic time-domain method in terms of the mean value and the order of magnitude of the standard deviation. Originality/value The combined uncertainties of the main parameters in graphene layers are modeled through a high-performance stochastic numerical algorithm, based on the finite-difference time-domain method. The significant accuracy of the numerical results, compared to the cumbersome Monte Carlo analysis, renders the featured technique a flexible computational tool that is able to enhance the design of graphene THz devices due to the uncertainty prediction.

Improving recommender systems’ performance on cold-start users and controversial items by a new similarity model

2016 ◽  
Vol 12 (2) ◽  
pp. 126-149 ◽  
Author(s):  
Masoud Mansoury ◽  
Mehdi Shajari
Keyword(s):  
Real World ◽  
Design Methodology ◽  
Cold Start ◽  
Selection Function ◽  
Data Sets ◽  
Real World Data ◽  
Content Type ◽  
User Similarity ◽  
Active User ◽  
Similarity Model

Purpose This paper aims to improve the recommendations performance for cold-start users and controversial items. Collaborative filtering (CF) generates recommendations on the basis of similarity between users. It uses the opinions of similar users to generate the recommendation for an active user. As a similarity model or a neighbor selection function is the key element for effectiveness of CF, many variations of CF are proposed. However, these methods are not very effective, especially for users who provide few ratings (i.e. cold-start users). Design/methodology/approach A new user similarity model is proposed that focuses on improving recommendations performance for cold-start users and controversial items. To show the validity of the authors’ similarity model, they conducted some experiments and showed the effectiveness of this model in calculating similarity values between users even when only few ratings are available. In addition, the authors applied their user similarity model to a recommender system and analyzed its results. Findings Experiments on two real-world data sets are implemented and compared with some other CF techniques. The results show that the authors’ approach outperforms previous CF techniques in coverage metric while preserves accuracy for cold-start users and controversial items. Originality/value In the proposed approach, the conditions in which CF is unable to generate accurate recommendations are addressed. These conditions affect CF performance adversely, especially in the cold-start users’ condition. The authors show that their similarity model overcomes CF weaknesses effectively and improve its performance even in the cold users’ condition.

A new weighted fraction Monte Carlo method for particle coagulation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiao Jiang ◽  
Tat Leung Chan
Keyword(s):  
Monte Carlo ◽  
Design Methodology ◽  
Computational Cost ◽  
Particle Coagulation ◽  
Content Type ◽  
Aerosol Dynamics ◽  
Stochastic Error ◽  
Adjustable Weight ◽  
Initial Distributions ◽  
Coagulation Kernel

Purpose The purpose of this study is to investigate the aerosol dynamics of the particle coagulation process using a newly developed weighted fraction Monte Carlo (WFMC) method. Design/methodology/approach The weighted numerical particles are adopted in a similar manner to the multi-Monte Carlo (MMC) method, with the addition of a new fraction function (α). Probabilistic removal is also introduced to maintain a constant number scheme. Findings Three typical cases with constant kernel, free-molecular coagulation kernel and different initial distributions for particle coagulation are simulated and validated. The results show an excellent agreement between the Monte Carlo (MC) method and the corresponding analytical solutions or sectional method results. Further numerical results show that the critical stochastic error in the newly proposed WFMC method is significantly reduced when compared with the traditional MMC method for higher-order moments with only a slight increase in computational cost. The particle size distribution is also found to extend for the larger size regime with the WFMC method, which is traditionally insufficient in the classical direct simulation MC and MMC methods. The effects of different fraction functions on the weight function are also investigated. Originality Value Stochastic error is inevitable in MC simulations of aerosol dynamics. To minimize this critical stochastic error, many algorithms, such as MMC method, have been proposed. However, the weight of the numerical particles is not adjustable. This newly developed algorithm with an adjustable weight of the numerical particles can provide improved stochastic error reduction.

Website traffic measurement and rankings: competitive intelligence tools examination

2018 ◽  
Vol 14 (4) ◽  
pp. 423-437 ◽  
Author(s):  
David Prantl ◽  
Martin Prantl
Keyword(s):  
Design Methodology ◽  
State Of The Art ◽  
Competitive Intelligence ◽  
Data Sets ◽  
Traffic Data ◽  
Content Type ◽  
Traffic Measurement ◽  
Data Estimation ◽  
Research Studies

PurposeThe purpose of this paper is to examine and verify the competitive intelligence tools Alexa and SimilarWeb, which are broadly used for website traffic data estimation. Tested tools belong to the state of the art in this area.Design/methodology/approachThe authors use quantitative approach. Research was conducted on a sample of Czech websites for which there are accurate traffic data values, against which the other data sets (less accurate) provided by Alexa and SimilarWeb will be compared.FindingsThe results show that neither tool can accurately determine the ranking of websites on the internet. However, it is possible to approximately determine the significance of a particular website. These results are useful for another research studies which use data from Alexa or SimilarWeb. Moreover, the results show that it is still not possible to accurately estimate website traffic of any website in the world.Research limitations/implicationsThe limitation of the research lies in the fact that it was conducted solely in the Czech market.Originality/valueSignificant amount of research studies use data sets provided by Alexa and SimilarWeb. However, none of these research studies focus on the quality of the website traffic data acquired by Alexa or SimilarWeb, nor do any of them refer to other studies that would deal with this issue. Furthermore, authors describe approaches to measuring website traffic and based on the analysis, the possible usability of these methods is discussed.

scholarly journals Fractional differencing in stock market price and online presence of global tourist corporations

2019 ◽  
Vol 24 (48) ◽  
pp. 194-204 ◽  
Author(s):  
Francisco Flores-Muñoz ◽  
Alberto Javier Báez-García ◽  
Josué Gutiérrez-Barroso
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Market Price ◽  
Google Trends ◽  
Data Sets ◽  
Market Prices ◽  
Content Type ◽  
Search Results ◽  
Online Presence ◽  
Fractional Differencing

Purpose This work aims to explore the behavior of stock market prices according to the autoregressive fractional differencing integrated moving average model. This behavior will be compared with a measure of online presence, search engine results as measured by Google Trends. Design/methodology/approach The study sample is comprised by the companies listed at the STOXX® Global 3000 Travel and Leisure. Google Finance and Yahoo Finance, along with Google Trends, were used, respectively, to obtain the data of stock prices and search results, for a period of five years (October 2012 to October 2017). To guarantee certain comparability between the two data sets, weekly observations were collected, with a total figure of 118 firms, two time series each (price and search results), around 61,000 observations. Findings Relationships between the two data sets are explored, with theoretical implications for the fields of economics, finance and management. Tourist corporations were analyzed owing to their growing economic impact. The estimations are initially consistent with long memory; so, they suggest that both stock market prices and online search trends deserve further exploration for modeling and forecasting. Significant differences owing to country and sector effects are also shown. Originality/value This research contributes in two different ways: it demonstrate the potential of a new tool for the analysis of relevant time series to monitor the behavior of firms and markets, and it suggests several theoretical pathways for further research in the specific topics of asymmetry of information and corporate transparency, proposing pertinent bridges between the two fields.

Professional trilemma of students with family business experience

Kybernetes ◽  
2016 ◽  
Vol 45 (3) ◽  
pp. 446-460 ◽  
Author(s):  
Jaka Vadnjal ◽  
Predrag Ljubotina
Keyword(s):  
Family Business ◽  
Design Methodology ◽  
Future Research ◽  
Related Factors ◽  
Senior Student ◽  
Content Type ◽  
East European ◽  
Educational Backgrounds ◽  
The Mean

Purpose – Family businesses represent the largest share of small-sized firms in majority of economies around the world. Having in mind the global economic situation this trend is expected to be continued. With the goal of better understanding of the process of transferring the business to the next generation, which ensures a long-term success, the purpose of this paper is to investigate expectations of student’s with family business background. Design/methodology/approach – The research addresses the issue of an individual’s perception of entrepreneurship and the related factors that influence individual’s decision on whether to build a career as an employee, become a successor of family business or start own business as an independent entrepreneur. The authors separately analyzed West European (data from another study), East European and Slovenian senior student population for the purpose of comparative study. Students were surveyed and binominal regression was used for statistics. Findings – The results show differences between investigated populations and positions Slovenian students in the mean. The authors anticipate that differences are caused by historical, cultural and educational backgrounds. This challenging area is raising a lot of sub-questions for possible future research. Originality/value – The value of the study is in the replication of the existing methodology from the benchmarking study and result comparison.

scholarly journals Why do some people search for their files much more than others? A preliminary study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ofer Bergman ◽  
Tamar Israeli ◽  
Yael Benn
Keyword(s):  
Verbal Memory ◽  
Design Methodology ◽  
Demographic Data ◽  
Future Research ◽  
Visuospatial Memory ◽  
Content Type ◽  
Logical Memory ◽  
The Mean ◽  
Preliminary Study ◽  
People Search

PurposePrevious research has repeatedly shown that people only search for files in a small minority of cases when they do not remember the file's location. The current study aimed to examine whether there is a group of hyper-searchers who search significantly more than others. Based on previous neurocognitive studies, this study aims to hypothesize that if such a group exists, they will have superior verbal memory and reduced visuospatial memory.Design/methodology/approachIn total, 65 participants completed a questionnaire estimating their search percentages, as well as reporting demographic data. Verbal memory was measured using the Wechsler logical memory test, and visuospatial memory was assessed using an online card memory game.FindingsHyper-searchers were defined as participants with search percentage of over one standard deviation (SD) above the mean. The average search percentage of the seven participants who met this criterion was 51% (SD = 14%), over five times more than the other participants (M = 10%, SD = 9%). Similar results were obtained by re-analyzing data from four previous papers (N = 1,252). The results further confirmed the hypothesis that hyper-searchers have significantly better verbal memory than other participants, possibly making searching easier and more successful for them. Lastly, the search percentage was positively predicted by verbal memory scores and negatively predicted by visuospatial memory scores. Explanations and future research are discussed.Originality/valueThis preliminary study is the first to introduce the concept of hyper-searchers, demonstrate its existence and study its causes.

The role of salesperson brand selling confidence in enhancing important sales management outcomes: a social identity approach

2018 ◽  
Vol 33 (3) ◽  
pp. 277-290 ◽  
Author(s):  
Bashar S. Gammoh ◽  
Michael L. Mallin ◽  
Ellen Bolman Pullins ◽  
Catherine M. Johnson
Keyword(s):  
Job Satisfaction ◽  
Cross Section ◽  
Design Methodology ◽  
Sales Management ◽  
Measurement Model ◽  
Content Type ◽  
The Impact ◽  
The Relationship ◽  
Social Identity Approach

Purpose The purpose of the study is to address the gap in understanding how the brand influences sales outcomes by focusing one’s attention on the salesperson perceptions of the brand and the salesperson brand selling confidence. Design/methodology/approach The study uses a cross-section survey of professional salespeople. SmartPLS was used to estimate the measurement model and test the hypothesized path relationships. Findings The study’s results indicate that salespeople who believe in the strength of the brands they represent are more likely to identify with the brand, are more confident in selling the brand and, overall, tend to perform better, have higher job satisfaction and are more committed to their companies. Originality/value This paper contributes to the sales literature by further exploring the relationship between the brand and sales function in the firm. This area has recently received academic attention but has not yet considered the mediating processes that connect the two areas. This study identifies perceptions of brand strength and brand selling confidence as mechanisms that mediate the impact of brand on sales outcomes.

TESTING TIME-SERIES STATIONARITY AGAINST AN ALTERNATIVE WHOSE MEAN IS PERIODIC

2001 ◽  
Vol 5 (3) ◽  
pp. 380-412 ◽  
Author(s):  
Melvin A. Hinich ◽  
Phillip Wild
Keyword(s):  
Time Series ◽  
Fourier Transform ◽  
Real World ◽  
Null Hypothesis ◽  
Data Sets ◽  
Testing Time ◽  
Economic Data ◽  
The Mean ◽  
Important Form ◽  
Real World Problems

We develop a test of the null hypothesis that an observed time series is a realization of a strictly stationary random process. Our test is based on the result that the kth value of the discrete Fourier transform of a sample frame has a zero mean under the null hypothesis. The test that we develop will have considerable power against an important form of nonstationarity hitherto not considered in the mainstream econometric time-series literature, that is, where the mean of a time series is periodic with random variation in its periodic structure. The size and power properties of the test are investigated and its applicability to real-world problems is demonstrated by application to three economic data sets.

Factors affecting desire to negotiate again

2017 ◽  
Vol 32 (1) ◽  
pp. 16-29 ◽  
Author(s):  
Denise Fleck ◽  
Roger Volkema ◽  
Sergio Pereira ◽  
Lara Vaccari
Keyword(s):  
Outcome Measures ◽  
Design Methodology ◽  
Negotiation Process ◽  
Content Type ◽  
Factors Affecting ◽  
Negatively Associated ◽  
Process And Outcome ◽  
The Mean ◽  
Personality Process ◽  
E Mail

Purpose The purpose of this paper is to investigate the effects of negotiation process and outcome on an individual’s desire to negotiate again with the same counterpart. Design/methodology/approach Data were collected from 115 dyads representing two companies negotiating an eight-issue property leasing agreement via e-mail. Desire to negotiate again was regressed on demographic/personality, process, and outcome measures. Findings Reaching an agreement was found to be significantly related to desire to negotiate again, while the number of messages exchanged and the mean number of competitive tactics employed were positively and negatively associated with reaching an agreement, respectively. Further, perceived honesty of self and counterpart were also associated with an individual’s desire to negotiate again. Originality/value This study focuses on an aspect of real negotiations often overlooked by researchers – the likelihood of future encounters with the same party – and examines three categories of factors that could affect a party’s desire to negotiate with a counterpart again – demographic/personality, process, and outcome (actual and perceived).

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