Search results

1 – 10 of over 13000
To view the access options for this content please click here

Abstract

Details

New Directions in Macromodelling
Type: Book
ISBN: 978-1-84950-830-8

To view the access options for this content please click here

Abstract

Details

The Peace Dividend
Type: Book
ISBN: 978-0-44482-482-0

To view the access options for this content please click here
Article
Publication date: 1 March 2007

Dongsung Kong

This article seeks to (1) identify forecasting techniques used to estimate taxable sales in California counties; (2) analyze which of these produces the most accurate…

Abstract

This article seeks to (1) identify forecasting techniques used to estimate taxable sales in California counties; (2) analyze which of these produces the most accurate estimate; (3) document what prevented officials from using the most accurate forecasting technique in California counties; and (4) determine what forecasting approach would work best for individual counties. This research generally confirms previous research findings that judgmental approaches are the most commonly used method of revenue forecasting in smaller localities. In terms of accuracy, econometric models outperform other quantitative methods, particularly compared to trend line fitting and extrapolation-by-average approaches. The “not now but later” perception in the use of econometric models can be ascribed to California county forecasters’ discomfort and lack of preparation for using this sophisticated technique. Once the critical prerequisites for the use of econometric models are provided -- such as statewide training, timely inter-governmental data sharing, easy access to economic data, and user-friendly forecasting formats with automated procedures -- econometric models can serve the needs of California counties.

Details

Journal of Public Budgeting, Accounting & Financial Management, vol. 19 no. 2
Type: Research Article
ISSN: 1096-3367

To view the access options for this content please click here
Book part
Publication date: 30 January 1995

Abstract

Details

Economics, Econometrics and the LINK: Essays in Honor of Lawrence R.Klein
Type: Book
ISBN: 978-0-44481-787-7

To view the access options for this content please click here
Book part
Publication date: 1 January 2008

Arnold Zellner

After briefly reviewing the past history of Bayesian econometrics and Alan Greenspan's (2004) recent description of his use of Bayesian methods in managing policy-making…

Abstract

After briefly reviewing the past history of Bayesian econometrics and Alan Greenspan's (2004) recent description of his use of Bayesian methods in managing policy-making risk, some of the issues and needs that he mentions are discussed and linked to past and present Bayesian econometric research. Then a review of some recent Bayesian econometric research and needs is presented. Finally, some thoughts are presented that relate to the future of Bayesian econometrics.

Details

Bayesian Econometrics
Type: Book
ISBN: 978-1-84855-308-8

To view the access options for this content please click here
Article
Publication date: 22 May 2020

Mariusz Doszyń

The purpose of this paper is to present an algorithm of real estate mass appraisal in which the impact of attributes (real estate features) is estimated by inequality…

Abstract

Purpose

The purpose of this paper is to present an algorithm of real estate mass appraisal in which the impact of attributes (real estate features) is estimated by inequality restricted least squares (IRLS) model.

Design/methodology/approach

This paper presents the algorithm of real estate mass appraisal, which was also presented in the form of an econometric model. Vital problem related to econometric models of mass appraisal is multicollinearity. In this paper, a priori knowledge about parameters is used by imposing restrictions in the form of inequalities. IRLS model is therefore used to limit negative consequences of multicollinearity. In ordinary least squares (OLS) models, estimator variances might be inflated by multicollinearity, which could lead to wrong signs of estimates. In IRLS models, estimators efficiency is higher (estimator variances are lower), which could result in better appraisals.

Findings

The final effect of the analysis is a vector of the impact of real estate attributes on their value in the mass appraisal algorithm. After making expert corrections, the algorithm was used to evaluate 318 properties from the test set. Valuation errors were also discussed.

Originality/value

Restrictions in the form of inequalities were imposed on the parameters of the econometric model, ensuring the non-negativity and monotonicity of real estate attribute impact. In case of real estate, variables are usually correlated. OLS estimators are then inflated and inefficient. Imposing restrictions in form of inequalities could improve results because IRLS estimators are more efficient. In the case of results inconsistent with theoretical assumptions, the real estate mass appraisal algorithm enables having the obtained results adjusted by an expert. This can be important for low quality databases, which is often the case in underdeveloped real estate markets. Another reason for expert correction may be the low efficiency of a given real estate market.

Details

Journal of European Real Estate Research , vol. 13 no. 2
Type: Research Article
ISSN: 1753-9269

Keywords

To view the access options for this content please click here
Article
Publication date: 15 June 2010

Pieter C.M. Cornelis

Whereas investments in new attractions continue to rise within the theme park industry, knowledge regarding the effects of new attractions on theme park performance and…

Abstract

Purpose

Whereas investments in new attractions continue to rise within the theme park industry, knowledge regarding the effects of new attractions on theme park performance and attendance remains scarce. In order to isolate these effects, the purpose of this paper is to present the results of an econometric study explaining the variance in theme park visitor numbers and quantifying the effects of new attractions on theme park attendance.

Design/methodology/approach

The paper is based on an econometric study, in which models were produced for four European theme parks. No pooled modelling was used, meaning that four different models were created; one for each participating theme park. Various variables affecting theme park attendance were identified and quantified, and subsequently the effects of new attractions on visitor numbers were isolated.

Findings

Findings indicate that all new attractions opened at Park D during the research period have had a positive long‐term influence on attendance. This positive influence lasted for no more than two years. No significant short‐term influence was found. There were significant differences in effect between new attractions which could not yet be explained.

Research limitations/implications

The research by design only takes into account the economic effects of new attractions and disregards all environmental and socio‐cultural effects. Even though the research provides an accurate approximation of the effects of new attractions on attendance, this effect should, according to the author, not be perceived as a stand‐alone effect yet as a part of a complex system. A situational approach taking into account several other situational as well as qualitative factors would do the complex reality more justice than a, even though effective, simplified and general approach.

Practical implications

Industry operators can now use the econometric model presented in this paper to determine the effects of new attractions on their theme park's attendance and use this knowledge to further fine‐tune their investment policy.

Originality/value

The paper presents the first econometric model successful at isolating and quantifying a new attraction's effect on theme park attendance and can thus be a valuable tool in perfecting one's investment policy. The paper furthermore includes a brief introduction to a situational approach of determining a new attraction's effects on theme park performance.

Details

Worldwide Hospitality and Tourism Themes, vol. 2 no. 3
Type: Research Article
ISSN: 1755-4217

Keywords

To view the access options for this content please click here
Article
Publication date: 24 June 2021

Mariusz Doszyń

The purpose of this paper is to present how prior knowledge about the impact of real estate features on value might be utilised in the econometric models of real estate…

Abstract

Purpose

The purpose of this paper is to present how prior knowledge about the impact of real estate features on value might be utilised in the econometric models of real estate appraisal. In these models, price is a dependent variable and real estate features are explanatory variables. Moreover, these kinds of models might support individual and mass appraisals.

Design/methodology/approach

A mixed estimation procedure was discussed in the research. It enables using sample and prior information in an estimation process. Prior information was provided by real estate experts in the form of parameter intervals. Also, sample information about the prices and features of undeveloped land for low-residential purposes was used. Then, mixed estimation results were compared with ordinary least squares (OLS) outcomes. Finally, the estimated econometric models were assessed with regard to both formal criteria and valuation accuracy.

Findings

The OLS results were unacceptable, mostly because of the low quality of the database, which is often the case on local, undeveloped real estate markets. The mixed results are much more consistent with formal expectations and the real estate valuations are also better for a mixed model. In a mixed model, the impact of each real estate feature could be estimated, even if there is no variability in the sample information. Valuations are also more precise in terms of their consistency with market prices. The mean error (ME) and mean absolute percentage error (MAPE) are lower for a mixed model.

Originality/value

The crucial problem in econometric property valuation is that it involves the unreliability of databases, especially on undeveloped, local markets. The applied mixed estimation procedure might support sample information with prior knowledge, in the form of stochastic restrictions imposed on parameters. Thus, that kind of knowledge might be obtained from real estate experts, practitioners, etc.

Details

Journal of European Real Estate Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-9269

Keywords

To view the access options for this content please click here
Book part
Publication date: 1 January 2004

Stefan Kooths, Timo Mitze and Eric Ringhut

This paper compares the predictive power of linear econometric and non-linear computational models for forecasting the inflation rate in the European Monetary Union (EMU)…

Abstract

This paper compares the predictive power of linear econometric and non-linear computational models for forecasting the inflation rate in the European Monetary Union (EMU). Various models of both types are developed using different monetary and real activity indicators. They are compared according to a battery of parametric and non-parametric test statistics to measure their performance in one- and four-step ahead forecasts of quarterly data. Using genetic-neural fuzzy systems we find the computational approach superior to some degree and show how to combine both techniques successfully.

Details

Applications of Artificial Intelligence in Finance and Economics
Type: Book
ISBN: 978-1-84950-303-7

To view the access options for this content please click here
Article
Publication date: 28 September 2012

Bing Pan, Doris Chenguang Wu and Haiyan Song

The purpose of this paper is to investigate the usefulness of search query volume data in forecasting demand for hotel rooms and identify the best econometric forecasting model.

Abstract

Purpose

The purpose of this paper is to investigate the usefulness of search query volume data in forecasting demand for hotel rooms and identify the best econometric forecasting model.

Design/methodology/approach

The authors used search volume data on five related queries to predict demand for hotel rooms in a specific tourist city and employed three ARMA family models and their ARMAX counterparts to evaluate the usefulness of these data. The authors also evaluated three widely used causal econometric models – ADL, TVP, and VAR – for comparison.

Findings

All three ARMAX models consistently outperformed their ARMA counterparts, validating the value of search volume data in facilitating the accurate prediction of demand for hotel rooms. When the three causal econometric models were included for forecasting competition, the ARX model produced the most accurate forecasts, suggesting its usefulness in forecasting demand for hotel rooms.

Research limitations/implications

To demonstrate the usefulness of this data type, the authors focused on one tourist city with five specific tourist‐related queries. Future studies could focus on other aspects of tourist consumption and on more destinations, using a larger number of queries to increase accuracy.

Practical implications

Search volume data are an early indicator of travelers' interest and could be used to predict various types of tourist consumption and activities, such as hotel occupancy, spending, and event attendance.

Originality/value

The paper's findings validate the value of search query volume data in predicting hotel room demand, and the paper is the first of its kind in the field of tourism and hospitality research.

Details

Journal of Hospitality and Tourism Technology, vol. 3 no. 3
Type: Research Article
ISSN: 1757-9880

Keywords

1 – 10 of over 13000