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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.

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.

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.

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.

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.

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

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.

This study is aimed to measure the intertemporal financial efficiency of 16 emerging economy countries (BRICS and N-11) and further to investigate the mechanisms of financial development on energy efficiency covering the period 2008–2020.

The dynamic data envelopment analysis model is used to measure financial efficiency dynamically. The generalized method of moments is used to investigate the effects of financial efficiency on energy efficiency. In the proposed approach, energy efficiency is the dependent variable, whereas financial efficiency, GDP per capita, industrial structure upgrade index, urbanization level and export trade structure are the regressors. Generalized moment estimation is performed.

There is heterogeneity in the level of financial development at different stages of economic development. The impact of financial efficiency on energy efficiency is related to the type of industries to which financial institutions are allocated. With the financial development of emerging economies, enterprises in technology-intensive industries are becoming the main contributors to higher profits for financial institutions, the products and results of these enterprises reduce energy consumption and increase energy efficiency. In addition, residents with rising levels of wealth holdings prefer low-carbon and environmentally friendly products, which indirectly improves energy efficiency. Per capita GDP and urbanization have no significant impact on the energy efficiency of emerging economies. The optimization and upgrading of the industrial structure of emerging economies has played a role in promoting energy efficiency. The export trade structure has a restraining effect on energy efficiency.

The findings contribute value by supporting a positive link between Financial Development and Energy Efficiency in the emerging economies. Enterprises in technology-intensive industries have gradually become the main force that brings higher profits to financial institutions. The products and achievements of these enterprises will reduce energy consumption and improve energy efficiency. The findings of this study provide emerging economies with an objective view of their financial development and energy efficiency, while also providing governments and policymakers with ways to improve energy efficiency and achieve sustainable development.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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).

The performance of financial markets is significantly influenced by the political environment during general elections. This study investigates the effect of general elections on stock market performance in selected African markets.

Prior studies have been inconsistent in determining whether electioneering events negatively or positively influence stock market performance. The study utilized panel data set with annual observations from 1990 to 2020. The generalized method of moments (GMM) is employed to investigate the effect of electioneering and change in government on key stock market performance indicators, including stock market capitalization, stock market turnover ratio and the value of stock traded.

The study finds that electioneering activities generally have a positive impact on the performance of the stock market, whereas a change in government has a negative impact. As a result, the study recommends that stakeholders of the stock market remain vigilant and actively monitor electioneering events to devise and implement effective policies aimed at mitigating political risks during general elections. By adopting these measures, investor confidence can be significantly enhanced, fostering a more robust and secure investment environment.

The study investigates a neglected section of the literature by highlighting not only the effect of elections on stock market indicators but also possible change in government during elections.

This study aims to find the relationship of stock market returns and selected financial market variables (market capitalization, earnings per share, price-earnings multiples, dividend yield and trading volume) of Malaysia grounded by the arbitrage pricing theories.

This study empirically examines the effects of selected financial market variables on stock market returns using 64 companies listed in Malaysia's stock market with data spanning from 2005 to 2018. A systematic empirical study based on the Generalized Method of Moments following Arellano and Bond (1991) has been taken to estimate the effect.

The regression result of the financial market variables and stock market return shows that, except for trading volume, all selected financial market variables play significant roles in the stock market returns. Furthermore, market capitalization, earnings per share, price-earnings ratio, dividend yield and trading volume have a positive impact on stock market returns.

The outcome of this study can contribute by helping domestic and global investors devise strategies to minimize their risks. Also, policy administrators can use the outcomes of this study to inform the micro- and macro-level policy formulation.

This study will contribute to filling the gap in knowledge concerning the new release of factors affecting the stock market returns of Malaysia.

The purpose of this paper is to explore the impact of social capital on happiness. The previous literature generally measures social capital using “generalized trust”, which is a narrow dimension of social capital. In this study, social capital is measured as a multidimensional concept consisting of generalized trust, institutional trust and trust on family, neighborhood and strangers.

This study explores the relationship between social capital and average happiness using a panel data of 89 countries from 1980 to 2017. The empirical analysis is done by employing pooled OLS (POLS), fixed effects method (FEM), random effects method (REM) and system generalized method of moments.

The findings demonstrate that all measures of social capital are positively associated with happiness while comparatively institutional trust and generalized trust appear more significant for happiness. The findings are robust to different robustness checks. The findings document the importance of social capital for average happiness.

The research has certain limitations. First, the objective of study was to cover global sample of countries, however, the data series were not available for all countries. Second, the empirical is restricted to global evidence instead of exploring separate estimates for developed and developing world.

The findings document the importance of social capital for average happiness. The awareness of the importance of social capital needs to be increased. Government can develop such organizations or institutions that are conducive for social capital development.

Some progress have been made over time in improving health conditions in Sub-Saharan Africa (SSA). There are, however, contradicting reports on the relationship between health outcomes and economic growth in the region. The paper aimed at assessing the effect of health outcome on economic growth in SSA.

Data for 41 countries from 2000 to 2018 were obtained from WDI and WGI and analyzed using system generalized method of moment (sGMM) which is appropriate for the present scenario. AR(1) and AR(2) tests were used to assess the validity of the model while Sargan and Hansen tests were adopted to examine the validity of the instrumental variables. The robustness of the estimation was confirmed using the pooled OLS and fixed effect regression.

Health outcome (proxied by life expectancy), lagged GDP per capita, capital formation, labor force (LF), health expenditure (HE), foreign direct investment (FDI) and trade openness (TOP) significantly affected economic growth emphasizing the importance of health in the process of economic growth in the region. AR(1) and AR(2) tests for serial correlation and Sargan/Hansen tests confirmed the validity of the estimated model and the instrumental variables respectively. Robustness of the GMM results was established from the pooled OLS and the fixed effect model results.

Improvement in the national health system possibly through the widespread adoption of National Health Insurance, increase government spending on healthcare alongside increased beneficial trade and ease of doing business to facilitate investment were recommended to enhance.

The study used up-to-date data with appropriate methodology.