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Article
Publication date: 10 May 2019

Peterson Owusu Junior, George Tweneboah, Kola Ijasan and Nagaratnam Jeyasreedharan

This paper aims to contribute to knowledge by investigating the return behaviour of seven global real estate investment trusts (REITs) with respect to the appropriate…

Abstract

Purpose

This paper aims to contribute to knowledge by investigating the return behaviour of seven global real estate investment trusts (REITs) with respect to the appropriate distributional fit that captures tail and shape characteristics. The study adds to the knowledge of distributional properties of seven global REITs by using the generalised lambda distribution (GLD), which captures fairly well the higher moments of the returns.

Design/methodology/approach

This is an empirical study with GLD through three rival methods of fitting tail and shape properties of seven REIT return data from January 2008 to November 2017. A post-Global Financial Crisis (GFC) (from July 2009) period fits from the same methods are juxtaposed for comparison.

Findings

The maximum likelihood estimates outperform the methods of moment matching and quantile matching in terms of goodness-of-fit in line with extant literature; for the post-GFC period as against the full-sample period. All three methods fit better in full-sample period than post-GFC period for all seven countries for the Region 4 support dynamics. Further, USA and Singapore possess the strongest and stronger infinite supports for both time regimes.

Research limitations/implications

The REITs markets, however, developed, are of wide varied sizes. This makes comparison less than ideal. This is mitigated by a univariate analysis rather than multivariate one.

Practical implications

This paper is a reminder of the inadequacy of the normal distribution, as well as the mean, variance, skewness and kurtosis measures, in describing distributions of asset returns. Investors and policymakers may look at the location and scale of GLD for decision-making about REITs.

Originality/value

The novelty of this work lies with the data used and the detailed analysis and for the post-GFC sample.

Details

Journal of European Real Estate Research , vol. 12 no. 3
Type: Research Article
ISSN: 1753-9269

Keywords

Article
Publication date: 1 January 1997

R.W. Faff and S. Lau

Standard multivariate tests of mean variance efficiency (MVE) have been criticised on the grounds that they require regression residuals to have a multivariate normal…

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Abstract

Standard multivariate tests of mean variance efficiency (MVE) have been criticised on the grounds that they require regression residuals to have a multivariate normal distribution. Generally, the existing evidence suggests that the normality assumption is questionable, even for monthly returns. MacKinlay and Richardson (1991) developed a generalised method of moments (GMM) framework which provides tests which are valid under much weaker distributional assumptions. They examined monthly US data formed into size based portfolios, for mean‐variance efficiency relative to the Sharpe‐Lintner CAPM. They found that inferences regarding mean‐variance efficiency can be sensitive to the test considered. In this paper we further investigate their GMM tests using monthly Australian data over the period 1974 to 1994. We extend upon their analysis to consider an alternative version of their GMM test and also to examine a zero‐beta version of the CAPM. Similar to the US case, our results also indicate sensitivity of inferences to the tests used. Finally, while we find that the GMM tests generally provide rejection of mean‐variance efficiency, tests involving the zero‐beta CAPM, particularly when a value‐weighted market index is used, prove less prone to rejection.

Details

Pacific Accounting Review, vol. 9 no. 1
Type: Research Article
ISSN: 0114-0582

Book part
Publication date: 30 August 2019

Md. Nazmul Ahsan and Jean-Marie Dufour

Statistical inference (estimation and testing) for the stochastic volatility (SV) model Taylor (1982, 1986) is challenging, especially likelihood-based methods which are…

Abstract

Statistical inference (estimation and testing) for the stochastic volatility (SV) model Taylor (1982, 1986) is challenging, especially likelihood-based methods which are difficult to apply due to the presence of latent variables. The existing methods are either computationally costly and/or inefficient. In this paper, we propose computationally simple estimators for the SV model, which are at the same time highly efficient. The proposed class of estimators uses a small number of moment equations derived from an ARMA representation associated with the SV model, along with the possibility of using “winsorization” to improve stability and efficiency. We call these ARMA-SV estimators. Closed-form expressions for ARMA-SV estimators are obtained, and no numerical optimization procedure or choice of initial parameter values is required. The asymptotic distributional theory of the proposed estimators is studied. Due to their computational simplicity, the ARMA-SV estimators allow one to make reliable – even exact – simulation-based inference, through the application of Monte Carlo (MC) test or bootstrap methods. We compare them in a simulation experiment with a wide array of alternative estimation methods, in terms of bias, root mean square error and computation time. In addition to confirming the enormous computational advantage of the proposed estimators, the results show that ARMA-SV estimators match (or exceed) alternative estimators in terms of precision, including the widely used Bayesian estimator. The proposed methods are applied to daily observations on the returns for three major stock prices (Coca-Cola, Walmart, Ford) and the S&P Composite Price Index (2000–2017). The results confirm the presence of stochastic volatility with strong persistence.

Details

Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A
Type: Book
ISBN: 978-1-78973-241-2

Keywords

Article
Publication date: 27 April 2020

Edmore Mahembe and Nicholas M. Odhiambo

This paper aims to assess whether official development assistance (ODA) or foreign aid has been effective in reducing extreme poverty; test whether the type and source of

Abstract

Purpose

This paper aims to assess whether official development assistance (ODA) or foreign aid has been effective in reducing extreme poverty; test whether the type and source of aid matter; and examine whether political or economic freedom enhances aid effectiveness in developing countries.

Design/methodology/approach

The study uses recent dynamic panel estimation techniques (system generalised method of moments), including those methods which deal with endogeneity by controlling for simultaneity and unobserved heterogeneity.

Findings

The main findings of the study are: firstly, foreign aid does have a statistically significant poverty reduction effect and the results are consistent across all the three extreme poverty proxies. Secondly, the disaggregation of aid by source and type shows that total aid, grant and bilateral aid are more likely to reduce poverty. Thirdly, political freedom might not be an effective channel through which aid impacts extreme poverty, but aid is more effective in an environment where there is respect for freedom of enterprise.

Research limitations/implications

As with most cross-country aid–growth–poverty dynamic panel data studies, the challenges of establishing robust causality and accounting for the unobserved country-specific heterogeneity remain apparent. However, given the data availability constraints, generalised method of moments is, to the best of the authors’ knowledge, the most robust empirical strategy when T < N. Future research could explore possibilities of individual country analysis, disaggregating countries by income and also examining the direction of causality between foreign aid, poverty and democracy.

Practical implications

The policy implications are that the development partners should continue to focus on poverty reduction as the main objective for ODA; aid allocation should be focused on channels which have more poverty-reduction effect, such as per capita income and economic freedom; and aid recipient countries should also focus on reducing inequality.

Social implications

The main social implications from this study is that it is possible to reduce poverty through ODA. Second, to enhance the effectiveness of foreign aid, ODA allocation should be focussed on channels, which have more poverty-reduction effect, and the host countries should have economic freedom.

Originality/value

This paper makes a further contribution to the aid effectiveness literature, especially the channels through which foreign aid affects poverty.

Details

International Journal of Development Issues, vol. 19 no. 2
Type: Research Article
ISSN: 1446-8956

Keywords

Book part
Publication date: 23 June 2016

Bao Yong, Fan Yanqin, Su Liangjun and Zinde-Walsh Victoria

This paper examines Aman Ullah’s contributions to robust inference, finite sample econometrics, nonparametrics and semiparametrics, and panel and spatial models. His early…

Abstract

This paper examines Aman Ullah’s contributions to robust inference, finite sample econometrics, nonparametrics and semiparametrics, and panel and spatial models. His early works on robust inference and finite sample theory were mostly motivated by his thesis advisor, Professor Anirudh Lal Nagar. They eventually led to his most original rethinking of many statistics and econometrics models that developed into the monograph Finite Sample Econometrics published in 2004. His desire to relax distributional and functional-form assumptions lead him in the direction of nonparametric estimation and he summarized his views in his most influential textbook Nonparametric Econometrics (with Adrian Pagan) published in 1999 that has influenced a whole generation of econometricians. His innovative contributions in the areas of seemingly unrelated regressions, parametric, semiparametric and nonparametric panel data models, and spatial models have also inspired a larger literature on nonparametric and semiparametric estimation and inference and spurred on research in robust estimation and inference in these and related areas.

Book part
Publication date: 29 March 2006

Jean-Marie Dufour and Pascale Valéry

In this paper, we consider the estimation of volatility parameters in the context of a linear regression where the disturbances follow a stochastic volatility (SV) model of

Abstract

In this paper, we consider the estimation of volatility parameters in the context of a linear regression where the disturbances follow a stochastic volatility (SV) model of order one with Gaussian log-volatility. The linear regression represents the conditional mean of the process and may have a fairly general form, including for example finite-order autoregressions. We provide a computationally simple two-step estimator available in closed form. Under general regularity conditions, we show that this two-step estimator is asymptotically normal. We study its statistical properties by simulation, compare it with alternative generalized method-of-moments (GMM) estimators, and present an application to the S&P composite index.

Details

Econometric Analysis of Financial and Economic Time Series
Type: Book
ISBN: 978-0-76231-274-0

Article
Publication date: 1 March 1991

David Blake

The different types of estimators of rational expectations modelsare surveyed. A key feature is that the model′s solution has to be takeninto account when it is estimated…

Abstract

The different types of estimators of rational expectations models are surveyed. A key feature is that the model′s solution has to be taken into account when it is estimated. The two ways of doing this, the substitution and errors‐in‐variables methods, give rise to different estimators. In the former case, a generalised least‐squares or maximum‐likelihood type estimator generally gives consistent and efficient estimates. In the latter case, a generalised instrumental variable (GIV) type estimator is needed. Because the substitution method involves more complicated restrictions and because it resolves the solution indeterminacy in a more arbitary fashion, when there are forward‐looking expectations, the errors‐in‐variables solution with the GIV estimator is the recommended combination.

Details

Journal of Economic Studies, vol. 18 no. 3
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 23 October 2019

Rakesh Kumar Sharma and Apurva Bakshi

This paper aims to make an attempt to identify the determinants of dividend policy by analyzing 125 real estate companies, which are selected on the basis of consistent…

Abstract

Purpose

This paper aims to make an attempt to identify the determinants of dividend policy by analyzing 125 real estate companies, which are selected on the basis of consistent dividend distribution throughout the study period. Most of these companies either listed with Bombay Stock Exchange or National Stock Exchange.

Design/methodology/approach

This paper applies three alternative methods to verify and validate the results obtained from each other method, namely, fully modified ordinary least square (FMOLS), dynamic ordinary least square and generalized method of moments (GMM). Data collected of the selected companies’ post-recession period i.e. 2009-2017. The selected companies have age either 5 years old or more when data are retrieved from the above-mentioned sources. Due to much volatility in the recession period in the real estate firms at the global level, no data have been taken of the firms before March 2009. Moreover, for arriving at good analysis and an adequate number of observations for the study more recent data have been taken.

Findings

Empirical findings of this research paper depict that firm previous dividend, firm risk and liquidity are strong predictors of future dividend payout ratios (DPRs). The results indicate that firm risk as measured through price-earnings ratio (PE ratio) has a positive association with a DPR of selected real estate firms. Lagged DPR used in the GMM test as an exogenous variable is showing positive significant association with DPR. Firm’s growth is found significant in FMOLS and GMM techniques. On the other firm’s size is found significant according to cointegration techniques.

Practical implications

The present study shall be useful to different stakeholders of real estate companies. Various significant determinants as identified can be used by management for designing optimum dividend policy and providing maximum benefits to existing shareholders. Similarly existing and prospective shareholders may predict the future payment of dividend and accordingly they may take investment decisions in these firms, as the future fund’s requirement of a firm depends upon dividend payment and retention ratio.

Originality/value

As per the authors’ knowledge, there is no single study carried in the post-recession period to predict determinants of dividend policy of real estate sector using three alternatives of methods to verify and validate the results obtained from each other method. The study is carried out after exploring determinant from a diverse range of period of studies (oldest one to latest one).

Details

Journal of Financial Management of Property and Construction , vol. 24 no. 3
Type: Research Article
ISSN: 1366-4387

Keywords

Book part
Publication date: 16 December 2009

Zongwu Cai and Yongmiao Hong

This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of

Abstract

This paper gives a selective review on some recent developments of nonparametric methods in both continuous and discrete time finance, particularly in the areas of nonparametric estimation and testing of diffusion processes, nonparametric testing of parametric diffusion models, nonparametric pricing of derivatives, nonparametric estimation and hypothesis testing for nonlinear pricing kernel, and nonparametric predictability of asset returns. For each financial context, the paper discusses the suitable statistical concepts, models, and modeling procedures, as well as some of their applications to financial data. Their relative strengths and weaknesses are discussed. Much theoretical and empirical research is needed in this area, and more importantly, the paper points to several aspects that deserve further investigation.

Details

Nonparametric Econometric Methods
Type: Book
ISBN: 978-1-84950-624-3

Article
Publication date: 17 January 2022

Muhammad Mushafiq, Syed Ahmad Sami, Muhammad Khalid Sohail and Muzammal Ilyas Sindhu

The main purpose of this study is to evaluate the probability of default and examine the relationship between default risk and financial performance, with dynamic panel…

Abstract

Purpose

The main purpose of this study is to evaluate the probability of default and examine the relationship between default risk and financial performance, with dynamic panel moderation of firm size.

Design/methodology/approach

This study utilizes a total of 1,500 firm-year observations from 2013 to 2018 using dynamic panel data approach of generalized method of moments to test the relationship between default risk and financial performance with the moderation effect of the firm size.

Findings

This study establishes the findings that default risk significantly impacts the financial performance. The relationship between distance-to-default (DD) and financial performance is positive, which means the relationship of the independent and dependent variable is inverse. Moreover, this study finds that the firm size is a significant positive moderator between DD and financial performance.

Practical implications

This study provides new and useful insight into the literature on the relationship between default risk and financial performance. The results of this study provide investors and businesses related to nonfinancial firms in the Pakistan Stock Exchange (PSX) with significant default risk's impact on performance. This study finds, on average, the default probability in KSE ALL indexed companies is 6.12%.

Originality/value

The evidence of the default risk and financial performance on samples of nonfinancial firms has been minimal; mainly, it has been limited to the banking sector. Moreover, the existing studies have only catered the direct effect of only. This study fills that gap and evaluates this relationship in nonfinancial firms. This study also helps in the evaluation of Merton model's performance in the nonfinancial firms.

Details

Journal of Economic and Administrative Sciences, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1026-4116

Keywords

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