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Book part
Publication date: 9 August 2012

Dennis Togo

The reciprocal method for allocating support department costs is preferred over the direct and step-down methods because it captures all support services provided to other…

Abstract

The reciprocal method for allocating support department costs is preferred over the direct and step-down methods because it captures all support services provided to other departments. However, even as business organizations increase the number of support departments and their costs, the adoption of the reciprocal method has been hindered by mathematical difficulties in solving simultaneous equations. This paper illustrates spreadsheet matrix functions that remove the difficulties associated with the reciprocal method. The algebraic expressions for reciprocated costs commonly presented in accounting textbooks are used to form an equivalent matrix relationship. Then spreadsheet matrix functions easily compute reciprocated costs for support departments from the matrix relationship, and also allocate the reciprocated costs to other departments.

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Advances in Accounting Education: Teaching and Curriculum Innovations
Type: Book
ISBN: 978-1-78052-757-4

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Article
Publication date: 14 July 2021

Khandokar Istiak

Broker-dealer leverage volatility increases during booms and crisis periods, but its impact on stock prices is relatively unexplored. This paper aims to investigate…

Abstract

Purpose

Broker-dealer leverage volatility increases during booms and crisis periods, but its impact on stock prices is relatively unexplored. This paper aims to investigate whether broker-dealer leverage volatility is a key driver for stock prices.

Design/methodology/approach

This paper collects the US quarterly data of broker-dealer book leverage and three leading stock market indicators (S&P 500, DJIA and Nasdaq) for the period of 1967–2018. The research uses a multivariate GARCH-in-mean VAR to examine the impact of leverage volatility on each of the stock market indicators. A split-sample analysis (pre-1990 and post-1990) has also been performed to show the robustness of the result.

Findings

The research finds that broker-dealer leverage volatility does not have any significant impact on stock prices.

Originality/value

Broker-dealers are important financial intermediaries, and there is a huge literature exploring the relationship between their leverage and asset prices. But, the relationship between broker-dealer leverage volatility and asset prices is not explored yet. This study fills the gap and provides the first evidence that broker-dealer leverage volatility does not play any major role in the theory of stock pricing. The research proposes that the stock holding decisions of the investors should depend only on the first moment of leverage and not on the second moment of leverage. The study concludes that high broker-dealer leverage volatility is not a sinister signal for the US stock market.

Details

Studies in Economics and Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1086-7376

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Book part
Publication date: 19 November 2014

Miguel Belmonte and Gary Koop

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selection (DMS) or averaging (DMA) in time-varying…

Abstract

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selection (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact method for implementing DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an inflation forecasting application. We find strong evidence of model switching. We also compare different ways of implementing DMA/DMS and find forgetting factor approaches and approaches based on the switching Gaussian state space model to lead to similar results.

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Book part
Publication date: 20 November 2020

Levi van der Heijden and Tanya Bondarouk

This chapter aims to find out perceived value creation while engaging with the Airbnb business. Whilst values have been found leading to participation, values resulting…

Abstract

This chapter aims to find out perceived value creation while engaging with the Airbnb business. Whilst values have been found leading to participation, values resulting from actual participation are yet to be explored. By taking the approach of service-dominant logic and cocreation, topped with the discourse analysis of the written accounts of Airbnb guests, this study has discovered several values that result from cocreation during participation in Airbnb business models. Several avenues for the continuation of this study are suggested to build upon the acquired knowledge from this exploratory research.

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Sustainable Hospitality Management
Type: Book
ISBN: 978-1-83909-266-4

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Book part
Publication date: 13 December 2013

Claudia Foroni, Eric Ghysels and Massimiliano Marcellino

The development of models for variables sampled at different frequencies has attracted substantial interest in the recent literature. In this article, we discuss classical…

Abstract

The development of models for variables sampled at different frequencies has attracted substantial interest in the recent literature. In this article, we discuss classical and Bayesian methods of estimating mixed-frequency VARs, and use them for forecasting and structural analysis. We also compare mixed-frequency VARs with other approaches to handling mixed-frequency data.

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VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims
Type: Book
ISBN: 978-1-78190-752-8

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Book part
Publication date: 26 April 2014

Petri Kuosmanen and Juuso Vataja

This paper examines the predictive content of financial variables above and beyond past GDP growth in a small open economy in the Eurozone. We aim to clarify potential…

Abstract

Purpose

This paper examines the predictive content of financial variables above and beyond past GDP growth in a small open economy in the Eurozone. We aim to clarify potential differences in forecasting economic activity during periods of steady growth and economic turbulence.

Design/methodology/approach

The out-of-sample forecasting analysis is conducted recursively for two different time periods: the steady growth period from 2004:1 to 2007:4 and the financial crisis period from 2008:1 to 2011:2.

Findings

Our results from Finland suggest that the proper choice of forecasting variables relates to general economic conditions. During steady economic growth, the preferable financial indicator is the short-term interest rate combined with past growth. However, during economic turbulence, the traditional term spread and stock returns are more important in forecasting GDP growth.

Research limitations/implications

The results highlight the importance of long-term interest rates in determining the level of the term spread when the central bank implements a zero interest rate policy. Moreover, during economic turbulence, stock markets are able to signal the expected effects of unconventional monetary policy on GDP growth.

Details

Macroeconomic Analysis and International Finance
Type: Book
ISBN: 978-1-78350-756-6

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Article
Publication date: 29 April 2020

Hardik Marfatia

The objective of the paper is to explore the out-of-sample forecasting connections in income growth across the globe.

Abstract

Purpose

The objective of the paper is to explore the out-of-sample forecasting connections in income growth across the globe.

Design/methodology/approach

An autoregressive distributed lag (ARDL) framework is employed and the forecasting performance is analyzed across several horizons using different forecast combination techniques.

Findings

Results show that the foreign country's income provides superior forecasts beyond what is provided by the country's own past income movements. Superior forecasting power is particularly held by Belgium, Korea, New Zealand, the UK and the US, while these countries' income is rather difficult to predict by global counterparts. Contrary to conventional wisdom, improved forecasts of income can be obtained even for longer horizons using our approach. Results also show that the forecast combination techniques yield higher forecasting gains relative to individual model forecasts, both in magnitude and the number of countries.

Research limitations/implications

The forecasting paths of income movement across the globe reveal that predictive power greatly differs across countries, regions and forecast horizons. The countries that are difficult to predict in the short run are often seen to be predictable by global income movements in the long run.

Practical implications

Even while it is difficult to predict the income movements at an individual country level, combining information from the income growth of several countries is likely to provide superior forecasting gains. And these gains are higher for long-horizon forecasts as compared to the short-horizon forecast.

Social implications

In evaluating the forward-looking social implications of economic policy changes, the policymakers should also consider the possible global forecasting connections revealed in the study.

Originality/value

Employing an ARDL model to explore global income forecasting connections across several forecast horizons using different forecast combination techniques.

Details

Journal of Economic Studies, vol. 47 no. 5
Type: Research Article
ISSN: 0144-3585

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Article
Publication date: 14 January 2020

Pierre Rostan and Alexandra Rostan

The purpose of this paper is to present forecasts of fossil fuels prices until 2030 with spectral analysis to provide a clearer picture of this energy sector.

Abstract

Purpose

The purpose of this paper is to present forecasts of fossil fuels prices until 2030 with spectral analysis to provide a clearer picture of this energy sector.

Design/methodology/approach

Fossil fuels prices time series are decomposed in simpler signals called approximations and details in the framework of the one-dimensional discrete wavelet analysis. The simplified signals are recomposed after Burg extension.

Findings

In 2019-2030 average price forecasts of: West Texas intermediate (WTI) oil ($58.67) is above its 1986-2030 long-term mean of $47.83; and coal ($81.01) is above its 1980-2030 long-term mean of $60.98. On the contrary, 2019-2030 average of price forecasts of: Henry Hub natural gas ($3.66) is below its 1997-2030 long-term mean of $4; heating oil ($0.64) is below its 1986-2030 long-term mean of $1.16; propane ($0.26) is below its 1992-2030 long-term mean of $0.66; and regular gasoline ($1.45) is below its 2003-2030 long-term mean of $1.87.

Originality/value

Fossil fuels prices projections may relieve participants of WTI oil and coal markets but worry participants of Henry Hub, heating oil, propane and regular gasoline markets including countries whose economy is tied to energy prices.

Details

International Journal of Energy Sector Management, vol. 15 no. 2
Type: Research Article
ISSN: 1750-6220

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Article
Publication date: 4 March 2019

Rodolfo Nicolay and Ana Jordânia de Oliveira

Studies about the determinants of the clarity of central bank communication are still scarce. To the authors’ knowledge, there are no studies regarding emerging economies…

Abstract

Purpose

Studies about the determinants of the clarity of central bank communication are still scarce. To the authors’ knowledge, there are no studies regarding emerging economies. The purpose of this paper is to contribute to the literature in the following aspects: to analyze the determinants of the clarity of the central bank communication in an inflation targeting emerging economy; observe the influence of inflation volatility over the clarity; and observe the effect of the monetary policy signaling over the clarity.

Design/methodology/approach

The work uses readability indexes to measure the clarity of central bank communication. The empirical analysis uses ordinary least squares and the Generalized Method of Moments with one- and two-step estimations.

Findings

The findings suggest the inflation volatility reduces the clarity of central bank communication. Moreover, the monetary policy signaling also affects the clarity, but the effect depends on the direction of the signal.

Practical implications

This paper observes the determinants of the clarity considering an emerging economy environment. The clarity of central bank communications is an important tool to access transparency. Hence, the analysis of what determines the clarity of central bank communication is a debate about the level of transparency accessed by the central bank.

Originality/value

There are no studies about the determinants of the clarity of central bank communication in emerging economies. Moreover, the novelty are the effects of inflation volatility and monetary policy signaling over the clarity.

Details

Journal of Economic Studies, vol. 46 no. 2
Type: Research Article
ISSN: 0144-3585

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Article
Publication date: 8 June 2012

Zhuo Zhang and Yanyu Wang

The purpose of this paper is to establish a three‐dimensional service house of quality (HOQ). The new service HOQ adds a dimension of quality economics to solve the…

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Abstract

Purpose

The purpose of this paper is to establish a three‐dimensional service house of quality (HOQ). The new service HOQ adds a dimension of quality economics to solve the problems of economic evaluation in the process of transferring customer requirements into service characteristics by traditional HOQ.

Design/methodology/approach

Based on the traditional two‐dimensional HOQ, this paper constructs a three‐dimension service HOQ by adding an economic dimension into the traditional structure, so that the transformation process from customer requirements into service characteristics can be evaluated with quality economic perspective. The key concern of this new model is to balance the quality improvement and economic gain of a service. The other improvement of this paper is that it uses structural equations to present the coefficient matrix in the new HOQ model to avoid human errors in the evaluation. A case study is used to verify the effectiveness of the new model.

Findings

Quality gains and costs should be considered in service design and quality improvement. The three‐dimensional service HOQ uses the dimension of quality economics to balance customer requirements and service characteristics, which is more effective than the traditional one.

Practical implications

The method exposed in the paper can be used by service companies for decision making in service design and quality improvement.

Originality/value

This paper establishes a new three‐dimensional HOQ, by which quality economics can be effectively analyzed in service design and quality improvement.

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