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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).

This study aims to determine how changes in macroeconomic indicators and the housing prices index (HPI) are related. These factors can cause short-term and long-term changes in the housing market in Spain.

The study used cointegrating regression, fully modified ordinary least squares and dynamic ordinary least squares methodologies. The models are trained using quarterly time series data for these parameters from 2010 to 2022. A comprehensive examination is conducted to explore the relationship between macroeconomic issues and fluctuations in the HPI.

The results indicate statistically significant short-run effects (p < 0.05) of economic growth, inflation, Spanish stock indices, foreign trade and the interest rate on HPI. The inflation variables, Spain’s stock indices, interest rate and monetary rate, have statistically significant long-run effects (p < 0.05) on HPI. The exchange rate, unemployment and money supply have no substantial impact on HPI in Spain.

The study’s findings significantly contribute to increased information concerning the level of investing activity in the Spanish housing sector. After conducting an in-depth study of both the long-run and short-run connections with HPI, the study proved to be highly effective in formulating appropriate policies.

This study aims to examine the linkage between bankruptcy filings and hurricane events. Several independent variables related to local district court bankruptcy filings are examined. The primary question posed is whether Category 3,4 and 5 hurricanes result in personal bankruptcy filings due to the real property and other damage that ensures.

Landfall hurricanes in Florida from 2001 through 2018 were examined by using the fully modified least square regression model. Descriptive statistics include elasticity measures that show statistics prior and post the passage of the Bankruptcy Abuse and Prevent and Consumer Protection Act of 2005 (BAPCPA).

The elasticity of housing prices was a useful statistic in explaining bankruptcy filings. Regression results indicate that bankruptcy filing occur within one year of a serious hurricane. The regression model found hurricane events and housing price trends were significant variable when predicting district court bankruptcy filings.

BAPCPA targets fraud under Chapter 7 bankruptcy filings. Unfortunately, this also had the unintended consequence of discouraging legitimated filings due to the lowering of the marginal benefit associated with filing when the “means test” is applied.

Lack of flood insurance coverage and stagnant real estate prices could limit the desirability of filing under Chapter 13 resulting in an inventory of damaged properties being foreclosed.

Prior researchers relied on a descriptive approach by using percentage rates to quantify the association between hurricane damage and bankruptcy filings. By using the fully modified regression-based approach, the study herein establishes that filings occur approximately a year after the household experiences the real property loss and identifies other casual factors that influence the decision to file.

The purpose of this paper is to attempts to explore the relationship between population ageing, income growth and CO₂ emission in 25 high-income Organization for Economic Cooperation and Development (OECD) countries in the framework of environmental Kuznets curve (EKC).

Following Zagheni (2011) and using a relatively new cointegration technique and fully modified ordinary least square in a panel data over 1980-2009 the empirical results find evidence of inverted-U shaped EKC in these OECD countries.

The empirical results demonstrate that per capita CO₂ emission (PCCO₂) increases initially with economic growth; however, after reaching a per capita income level of US$ 24,657 it starts falling. With regard to ageing, the cointegrating vector indicates that a one percent increase in the share of aged population will reduce PCCO₂ by 1.55 percent in the long run.

This is one of the first studies that examine the effect of population ageing on CO₂ emission in a panel setting. The paper consider the cross-sectional dependence and use unit root test suitable for cross-sectional-dependent variables. The paper also examine short-run and long-run dynamics of EKC with panel cointegration and panel error correction methods.

Infrastructure deficiency in Southeast Asian countries is ever growing and touched to a level where it harms the local economy as well as the international sector of the country. The gap between demand and supply for infrastructure is constantly on the upswing. The purpose of this study to investigate the effect of infrastructure on exports and foreign direct investment (FDI) inflow in selected Southeast Asian economies.

This study employs the pooled mean group (PMG) technique to velaborate that how the infrastructure affects export and FDI in the short run and long run during 1990–2018. For cointegration, Pedroni and Kao tests are used. Dynamic ordinary least square (DOLS) and the fully modified least squares (FMOLSs) estimators are employed for robustness check.

The findings support that aggregate and sub-indices of infrastructure significantly promote the export and FDI inflow in the long run. Also infrastructure, export and FDI inflow are cointegrated in the long run. FMOLS and DOLS found the most robust results.

Infrastructure development in determining trade and FDI has established a significant deal of attention in the modern era where a plethora of research studies encourage the opinion that better infrastructure attracts FDI and enhances export. However, this study uses a global infrastructure index, which comprises the sub-indices like transport, telecommunication, energy and financial sector, which gives us a clear picture regarding how Southeast Asia can catch up FDI and export benefits through infrastructure.

This study aims to analyse the intellectual property rights (INPR), foreign direct investment (FDI) inflows and technological exports of 32 developing and developed countries for the period of 2006–2020.

Diagnostic tests were used to confirm the panel least squares, fixed effect, random effect, feasible general least squares, dynamic ordinary least squares and fully modified ordinary least squares estimator results as well as to increase the robustness.

According to the findings for the developing countries, trademark, patent and industrial design applications, each had a significant positive long-run effect on FDI inflows. In addition, there was a significant positive long-run relationship between patent applications and medium- and high-technology exports. Meanwhile, trademark and industrial design applications had a significant negative long-term effect on medium- and high-technology exports. In developed countries, patent and industrial design applications each have a significant negative long-term on medium- and high-technology exports. Furthermore, patent and trademark applications each had a significant negative long-run effect on FDI inflows.

This study contributes significantly to the focus that host countries evaluate the technology gaps between domestic and foreign investors at different industry levels to select the best INPR rules and innovation process by increasing international cooperation. Furthermore, the host countries should follow the structure–conduct–performance paradigm based on analysis of the market structure, strategic firms and industrial dynamics systems.

First, the current study contributes to the available debate by reinvestigating the impact of economic growth (EG), foreign direct investment (FDI), technological innovation (TI) and inflation (INF) on trade openness (TO). Second, the study tests the moderating role of institutional quality (INS) on the relationship among EG, FDI, TI and TO. Third, the study tests how TO contributes to EG efficiency.

The study collects the data from the group of twenty (G20) economies for the period of 1998–2020. The study applied the Kao (1999), Pedroni (2001), and Palamuleni (2017) cointegration tests to test the long-run association between variables. The study applied fully modified least square (FMOLS) and dynamic least square (DOLS) models to test the hypotheses.

Findings of the study showed the positive impact of EG, FDI and TI on TO, which becomes more positive in the presence of institutional quality. Results indicate that INS plays an enhancing role in the relationship between FDI and TO, EG and TO and TI and TO. The study showed a negative relationship between INF and TO, and institutional quality plays a buffering role in the relationship between INF and TO.

First, the study reinvestigates the empirical association among EG, FDI, TI, INF and TO. Second, the study tests the moderating role of INS on the relationship between the proposed variables by developing an index of all the indicators of INS. Third, the study tests the contributions of TO in economic efficiency (ECE). The contributions of the present study will increase the available literature of TO and help the policy makers of G20 nations to suggest important policies to promote TO and ECE.

The main goal of the study is to explore the long run relationship between public debt and domestic investment in West Africa. Essentially, a study of this nature is to proffer major inroads into addressing low investment levels plaguing the region and securing critical fiscal policy measures.

The study examines the long-run relationship between public debt and domestic investment in 13 West African countries between 1986 and 2018 with the use of Panel Dynamic Least Squares (DOLS) and Panel Fully Modified Least Squares (FMOLS), and causality test based on Toda and Yamamoto.

Public debt (% of GDP) and external debt stocks have an insignificant effect on domestic investment in the long run, suggesting the negligible effect of public debt on the level of investments in the region. Further evidence shows that domestic investment Granger causes public debt indicators, implying that there is unidirectional causality. This suggests that any investment-generation policy could engender a rise in public borrowing, although such public loans might not be effective when there is pervasive mismanagement of public funds, as public debts need to be well managed for ensuring improved investment.

The study suggests that maintaining a strong and effective debt-investment nexus requires fiscal consolidation efforts across countries, as such could lead to enhanced institutional capacity and sustainable investment-generation policy.

Since panel regression techniques used by the previous studies (Fixed and Random effects) could be susceptible to possible statistical errors due to endogeneity issue and might not be well suited for explaining long-run effect or capturing the part of investment sustainability, their conclusions could be misleading and remain untenable in West Africa' s context. Hence, the study adopts techniques (DOLS and FMOLS) which could account for endogeneity issue and provide better elucidations for long-term effects.

Due to their limited capacity for adaptation and dependence on natural resources for economic growth, developing countries (DCs) tend to be more prone to climate change. It is argued that climate finance (CF) is a significant financial innovation to mitigate the negative effects of climate variation. However, the heterogeneous impacts of CF on environmental sustainability (ES) and social welfare (SW) have been masked. Thus, this study aims to investigate the heterogeneous effects of CF on ES and SW in 80 CF receipt DCs from 2002 to 2018. This study also aims to investigate the effects of CF on ES and SW based on population size, income heterogeneity and the type of CF.

The method of moments quantile regression (MMQR) with fixed effects is utilized. Alternatively, the fully modified least square (FMOLS) and dynamic least square (DOLS) estimators are used for the robustness test.

The findings revealed that DCs with the lowest and middle quantiles of EF, carbon dioxide (CO₂) emissions and human development exhibit large beneficial impacts of CF on ES and SW. In contrast, the positive effects of CF on ES breakdown for countries with the largest distributions of EF and CO₂ emissions. Besides, the impacts of CF on ES and SW depend on income heterogeneity, population size and the type of CF.

This study calls for a framework to integrate CF into all economic development decisions to strengthen climate-resilient SW and ES in DCs.

To the best of the authors’ knowledge, this is the first study to investigate the effects of CF on ES and SW in a wide range of DCs. Thus, it complements existing related literature focusing on the effects of CF on ES and SW.

This paper aims to examine the relationship between Indian rupee-US dollar exchange rate and the macroeconomic fundamentals for the post-economic reform period.

The authors have used an empirical model which includes a range of important macroeconomic variables based on the basic monetary theories of exchange rate determination. At the first stage of the analysis, they have tested structural break in the data. Subsequently, they have employed the fully modified ordinary least square, Wald’s coefficient restriction and impulse response functions (IRF) to estimate the monetary model in the long- and short-run horizons.

Results of analyses indicate that the macroeconomic fundamentals determine exchange rate in a significant way, but their effect varies sizably across the periods. The IRF illustrate the importance of interest rate in controlling exchange rate volatility.

The analysis of the behavior of inter-relationship among macroeconomic variables will help policymakers in a deep-rooted understanding of this complex and time-varying relationship.

Most of the existing studies have tested the impact of a single or a few macroeconomic fundamentals on exchange rate. But in the present study, we have tested the impact of a range of important variables, i.e. money supply, real income or output, price level and trade balance. Further, considering the importance of structural breaks in data, they authors have employed standard tests of structural break and incorporated the issue in the cointegration analysis.