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Book part
Publication date: 21 November 2014

Alex Maynard and Dongmeng Ren

We compare the finite sample power of short- and long-horizon tests in nonlinear predictive regression models of regime switching between bull and bear markets, allowing for time…

Abstract

We compare the finite sample power of short- and long-horizon tests in nonlinear predictive regression models of regime switching between bull and bear markets, allowing for time varying transition probabilities. As a point of reference, we also provide a similar comparison in a linear predictive regression model without regime switching. Overall, our results do not support the contention of higher power in longer horizon tests in either the linear or nonlinear regime switching models. Nonetheless, it is possible that other plausible nonlinear models provide stronger justification for long-horizon tests.

Details

Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

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Article
Publication date: 4 January 2022

Khairul Anuar Kamarudin, Ainul Islam, Ahsan Habib and Wan Adibah Wan Ismail

This paper aims to investigate the effect of auditor switching and lowballing on conditional conservatism, particularly how different types of auditor switching, namely, upward…

Abstract

Purpose

This paper aims to investigate the effect of auditor switching and lowballing on conditional conservatism, particularly how different types of auditor switching, namely, upward, downward and lateral switching to/from Big 4 and industry specialists, affect earnings quality in the following selected Asian countries: Indonesia, Malaysia, the Philippines, South Korea and Thailand.

Design/methodology/approach

Using conditional conservatism as a proxy for earnings quality, this study hypothesises that upward switching from non-Big 4 to Big 4 auditors, or from non-specialist to specialist auditors, would result in high conditional conservatism, while downward switching would lead to low conditional conservatism. The study further tests whether lowballing provides a viable explanation for reduced earnings conservatism in firms that switch from Big 4 to non-Big 4 auditors, or from specialist to non-specialist auditors.

Findings

The analysis, on a sample of 28,073 firm-year observations from 2007 to 2016, shows that the decision to downgrade auditors leads to lower conditional conservatism in the year of switching, compared with other firms and the pre-switching year. The evidence further shows that, when firms downgrade their auditors, lowballing contributes to a decrease in conditional conservatism in the first year of audit switching. Further, this research finds that switching to specialist auditors will result in increased conditional conservatism, while switching from specialist auditors to non-specialist auditors will result in reduced conditional conservatism.

Practical implications

The findings of this study are useful to investors who are looking to diversify their investment portfolio in developing markets, as evidence about auditor switching and quality of financial reporting may be an important factor in their investment decisions. Downward auditor switches and lowballing could act as red flags to investors in the sense that these events could signal a decrease in conditional conservatism and, hence, quality of earnings.

Originality/value

This research offers new evidence to support the view that management decisions to switch to lower-quality auditors will force newly appointed auditors to acquiesce to clients’ demands for reporting low-quality earnings.

Details

Managerial Auditing Journal, vol. 37 no. 2
Type: Research Article
ISSN: 0268-6902

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Book part
Publication date: 13 December 2013

Kirstin Hubrich and Timo Teräsvirta

This survey focuses on two families of nonlinear vector time series models, the family of vector threshold regression (VTR) models and that of vector smooth transition regression

Abstract

This survey focuses on two families of nonlinear vector time series models, the family of vector threshold regression (VTR) models and that of vector smooth transition regression (VSTR) models. These two model classes contain incomplete models in the sense that strongly exogeneous variables are allowed in the equations. The emphasis is on stationary models, but the considerations also include nonstationary VTR and VSTR models with cointegrated variables. Model specification, estimation and evaluation is considered, and the use of the models illustrated by macroeconomic examples from the literature.

Details

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: 30 November 2011

Massimo Guidolin

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov…

Abstract

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

Details

Missing Data Methods: Time-Series Methods and Applications
Type: Book
ISBN: 978-1-78052-526-6

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Open Access
Article
Publication date: 16 June 2022

Fatma Mathlouthi and Slah Bahloul

This paper aims at examining the co-movement dependent regime and causality relationships between conventional and Islamic returns for emerging, frontier and developed markets…

Abstract

Purpose

This paper aims at examining the co-movement dependent regime and causality relationships between conventional and Islamic returns for emerging, frontier and developed markets from November 2008 to August 2020.

Design/methodology/approach

First, the authors used the Markov-switching autoregression (MS–AR) model to capture the regime-switching behavior in the stock market returns. Second, the authors applied the Markov-switching regression and vector autoregression (MS-VAR) models in order to study, respectively, the co-movement and causality relationship between returns of conventional and Islamic indexes across market states.

Findings

Results show the presence of two different regimes for the three studied markets, namely, stability and crisis periods. Also, the authors found evidence of a co-movement relationship between the conventional and Islamic indexes for the three studied markets whatever the regime. For the Granger causality, it is proved only for emerging and developed markets and only during the stability regime. Finally, the authors conclude that Islamic indexes can act as diversifiers, or safe-haven assets are not strongly supported.

Originality/value

This paper is the first study that examines the co-movement and the causal relationship between conventional and Islamic indexes not only across different financial markets' regimes but also during the COVID-19 period. The findings may help investors in making educated decisions about whether or not to add Islamic indexes to their portfolios especially during the recent outbreak.

Details

Journal of Capital Markets Studies, vol. 6 no. 2
Type: Research Article
ISSN: 2514-4774

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Article
Publication date: 4 May 2012

Glenn Pederson, Wonho Chung and Roelof Nel

The purpose of this paper is to determine if there are positive microeconomic effects from a state‐funded loan participation program on farm productivity and investment behavior.

Abstract

Purpose

The purpose of this paper is to determine if there are positive microeconomic effects from a state‐funded loan participation program on farm productivity and investment behavior.

Design/methodology/approach

The authors take the approach that access to credit solves a liquidity problem. If a credit constraint exists it results in a suboptimal allocation of resources and a reduction in farm output and profitability. A two‐stage regression model approach is used to analyze farmer survey and loan application data. In the first stage, a probit regression model is used to identify the farmers who are likely to be credit rationed. In the second stage, switching regression models are used to observe the effect of credit rationing on farm productivity and on farm investment behavior.

Findings

It is found that there are liquidity effects of credit constraints for a significant share of the beginning and low‐resource farmers who participated in the state‐funded farm loan program. After controlling for various farm and farmer characteristics, the estimated productivity and investment demand equations imply that a 1 percent increase in credit received by credit constrained farmers under the state program increased their gross income by about 0.49 percent, and their investments in depreciable assets by about 0.33 percent.

Originality/value

This paper is the first to apply the switching regression model to a state‐funded farm loan program for the purpose of evaluating the financial impacts on farmer participants.

Article
Publication date: 4 February 2019

Claudia Pigini and Stefano Staffolani

The purpose of this paper is to investigate the determinants of the probability of being a teleworker and the extent of earnings differentials between teleworkers and traditional…

Abstract

Purpose

The purpose of this paper is to investigate the determinants of the probability of being a teleworker and the extent of earnings differentials between teleworkers and traditional employees.

Design/methodology/approach

The analysis is grounded on a theoretical framework depicting endogenous telework assignment and wage variations based on individual bargaining. The empirical strategy allows for non-random telework assignment, generating from individual- and job-specific observed as well as unobserved factors.

Findings

Results are based on the Italian labor force survey and uncover a key role of gender, higher education and family composition as determinants of the probability of teleworking. Furthermore, teleworkers enjoy a wage premium ranging between 2.7 and 8 percent.

Originality/value

Accounting for observed individual and job-specific effects, by both standard linear regression and propensity score matching, largely reduces the extent of wage premium emerging from unconditional descriptives; the results of an endogenous switching regression model however suggest that failing to properly care for unobserved factors leads to the underestimation of returns to telework.

Details

International Journal of Manpower, vol. 40 no. 2
Type: Research Article
ISSN: 0143-7720

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Article
Publication date: 30 September 2014

Chihiro Shimizu, Koji Karato and Kiyohiko Nishimura

The purpose of this article, starting from linear regression, was to estimate a switching regression model, nonparametric model and generalized additive model as a semi-parametric…

Abstract

Purpose

The purpose of this article, starting from linear regression, was to estimate a switching regression model, nonparametric model and generalized additive model as a semi-parametric model, perform function estimation with multiple nonlinear estimation methods and conduct comparative analysis of their predictive accuracy. The theoretical importance of estimating hedonic functions using a nonlinear function form has been pointed out in ample previous research (e.g. Heckman et al. (2010).

Design/methodology/approach

The distinctive features of this study include not only our estimation of multiple nonlinear model function forms but also the method of verifying predictive accuracy. Using out-of-sample testing, we predicted and verified predictive accuracy by performing random sampling 500 times without replacement for 9,682 data items (the same number used in model estimation), based on data for the years before and after the year used for model estimation.

Findings

As a result of estimating multiple models, we believe that when it comes to hedonic function estimation, nonlinear models are superior based on the strength of predictive accuracy viewed in statistical terms and on graphic comparisons. However, when we examined predictive accuracy using out-of-sample testing, we found that the predictive accuracy was inferior to linear models for all nonlinear models.

Research limitations/implications

In terms of the reason why the predictive accuracy was inferior, it is possible that there was an overfitting in the function estimation. Because this research was conducted for a specific period of time, it needs to be developed by expanding it to multiple periods over which the market fluctuates dynamically and conducting further analysis.

Practical implications

Many studies compare predictive accuracy by separating the estimation model and verification model using data at the same point in time. However, when attempting practical application for auto-appraisal systems and the like, it is necessary to estimate a model using past data and make predictions with respect to current transactions. It is possible to apply this study to auto-appraisal systems.

Social implications

It is recognized that housing price fluctuations caused by the subprime crisis had a massive impact on the financial system. The findings of this study are expected to serve as a tool for measuring housing price fluctuation risks in the financial system.

Originality/value

While the importance of nonlinear estimation when estimating hedonic functions has been pointed out in theoretical terms, there is a noticeable lag when it comes to testing based on actual data. Given this, we believe that our verification of nonlinear estimation’s validity using multiple nonlinear models is significant not just from an academic perspective – it may also have practical applications.

Details

International Journal of Housing Markets and Analysis, vol. 7 no. 4
Type: Research Article
ISSN: 1753-8270

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Article
Publication date: 9 July 2020

Michael T. Dugan

The purpose of this paper is to provide a literature review of elasticity-based techniques for the estimation of the degree of operating leverage (DOL) and the degree of financial…

Abstract

Purpose

The purpose of this paper is to provide a literature review of elasticity-based techniques for the estimation of the degree of operating leverage (DOL) and the degree of financial leverage (DFL) in empirical corporate finance research.

Design/methodology/approach

This paper describes the specific details of the estimation of DOL and DFL coefficients under both of the primary estimation techniques and documents the econometric properties of the estimates derived from each techniques.

Findings

There are tradeoffs between the two techniques, as each technique has both appealing and limiting features.

Originality/value

This paper indicates how each of the two techniques possesses limitations and suggests that future research should attempt to develop estimation techniques that overcome those limitations.

Article
Publication date: 19 December 2022

Patrick Owiredu, Camillus Abawiera Wongnaa, Patricia Pinamang Acheampong, Monica Addison, Kwaku Agyei Adu and Dadson Awunyo-Vitor

Various models and approaches are implemented to provide technical assistance and support to improve cocoa farmers' welfare in Ghana. The Farmer Business School (FBS), which is…

Abstract

Purpose

Various models and approaches are implemented to provide technical assistance and support to improve cocoa farmers' welfare in Ghana. The Farmer Business School (FBS), which is analogous to Farmer Field School (FFS), is one of the few initiatives of GIZ (Deutsche Gesellschaft für Internationale Zusammenarbeit) and Ghana Cocoa Board (COCOBOD). The main aim of the initiative is to train smallholder cocoa farmers to perceive cocoa production as a business. However, there is limited or conflicting evidence as to the effect of FBS on productivity and food security, especially in Ghana. This study assessed FBS participation and the participation's impact on productivity and food security of cocoa farmers.

Design/methodology/approach

The study used primary data collected from 542 cocoa farmers in Central and Western North regions of Ghana and employed descriptive statistics, perception index and Endogenous Switching Regression (ESR) as analytical tools.

Findings

The results, which reported an overall perception index of 0.7, indicated that the farmers had a strong positive perception on the FBS program. The results also showed that sex of a farmer, number of years of formal education, farm size, extension contact, perception, distance to extension outlet and membership of farmer-based organizations (FBOs) significantly influenced the decision to participate in FBS program. Also off-farm income, years of education and household size significantly influenced farm productivity and household food security. The results further showed that participation in FBS improved productivity and food security of cocoa farmers.

Research limitations/implications

The study used data from two regions of Ghana, namely the Central region and the Western North region. Findings from studies using data covering all cocoa growing areas of Ghana could be more informative in formulating policies aimed at encouraging participation in FBS and consequently help improve cocoa productivity and food security.

Originality/value

This article offers insights into the welfare effects of FBS on cocoa farmers as previous similar studies are without this information.

Details

Journal of Agribusiness in Developing and Emerging Economies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-0839

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1 – 10 of over 10000