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Article
Publication date: 5 July 2022

António M. Cunha and Júlio Lobão

This paper studies the dynamics and elasticities of house prices in Spain and Portugal (Iberia) at the Metropolitan Statistical Area (MSA) level, addressing panel regression…

Abstract

Purpose

This paper studies the dynamics and elasticities of house prices in Spain and Portugal (Iberia) at the Metropolitan Statistical Area (MSA) level, addressing panel regression problems such as heterogeneity and cross-sectional dependence between MSA.

Design/methodology/approach

The authors develop a two steps study. First, five distinct estimation methodologies are applied to estimate the long-term house price equilibrium of the Iberian MSA house market: Mean Group (MG), Fully Modified Ordinary Least Square (FMOLS) MG (FMOLS-MG), FMOLS Augmented MG (FMOLS-AMG), Common Correlated Effects MG (CCEMG) and Dynamic CCEMG (DCCEMG). FMOLS-AMG is found to be the best estimator for the long-term model. Second, an additional five distinct estimation methodologies are applied to estimate the short-term house price dynamics using the long-term FMOLS-AMG estimated price in the error-correction term of the short-term dynamic house price model: OLS Fixed Effects (FE), OLS Random Effects (RE), MG, CCEMG and DCCEMG. DCCEMG is found to be the best estimator for the short-term model.

Findings

The results show that in the long run Iberian house prices are inelastic to aggregate income (0.227). This is a much lower elasticity than what was previously found in US MSA house price studies, suggesting that there are other factors explaining Iberian house prices. According to our study, coastal MSA presents an inelastic housing supply and a price to income elasticity close to one, whereas inland MSA are shown to have an elastic supply and a non-significant price to income elasticity. Spatial differences are important and cross-section dependence is prevalent, affecting estimates in conventional methodologies that do not account for these limitations, such as OLS-FE and OLS-RE. Momentum and mean reversion are the main determinants of short-term dynamics.

Practical implications

Recent econometric advances that account for slope heterogeneity and cross-section dependence produce more accurate estimates than conventional panel estimation methodologies. The results suggest that house markets should be analyzed at the metropolitan level, not at the national level and that there are significant differences between short-term and long-term house price determinants.

Originality/value

To the best of the authors' knowledge, this is the first study applying recent econometric advances to the Iberian MSA house market.

Details

Journal of European Real Estate Research, vol. 15 no. 3
Type: Research Article
ISSN: 1753-9269

Keywords

Article
Publication date: 26 December 2023

Mohd Arshad Ansari, Mohammad Rais Ahmad, Pushp Kumar, Arvind Kumar Yadav and Rajveer Kaur Ritu

This study aims to examine the impact of oil consumption on carbon dioxide (CO2) emissions and total factor productivity (TFP) in highly oil-consuming countries of the world from…

Abstract

Purpose

This study aims to examine the impact of oil consumption on carbon dioxide (CO2) emissions and total factor productivity (TFP) in highly oil-consuming countries of the world from 1995 to 2019.

Design/methodology/approach

For this purpose, fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) are applied.

Findings

FMOLS and DOLS models reveal that oil consumption, human capital, population, trade openness and nonrenewable energy have a significant positive effect on CO2 emissions. While information and communication technology (ICT), as proxied by mobile and natural resources, has a significant negative effect on CO2 emissions. In the case of TFP, oil consumption, ICT and natural resources have a significant positive effect on the TFP. On the other hand, trade openness, population, human capital and nonrenewable energy have a significant negative effect on TFP. The results of this study can help to provide policy recommendations to reduce CO2 emissions in studied highly oil-consuming countries of the world.

Originality/value

Due to the threat to sustainable development, climate change has become a major topic for debate around the world. The influence of oil consumption on CO2 emission and TFP is less known in the available literature. Another significance of this study is that many researchers considered aggregate energy consumption to study this relationship, but the authors have studied the effect of energy consumption, particularly from oil in the top oil-consuming countries, which is a significant shortcoming of the present research.

Details

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

Keywords

Article
Publication date: 25 March 2020

Oguzhan Dincer

This study aims to investigate if the level of economic freedom matters for how corruption affects per capita income in US states.

Abstract

Purpose

This study aims to investigate if the level of economic freedom matters for how corruption affects per capita income in US states.

Design/methodology/approach

Using a new (and novel) index of corruption, which is based on Associated Press news wires, the author estimates the long-run cointegrating relationship between corruption, economic freedom and per capita income with fully modified ordinary least squares (FMOLS) following Pedroni (2000).

Findings

The author finds that there is a threshold level of economic freedom that determines if corruption reduces the per capita income in a state. According to the FMOLS estimations, the negative effects of corruption on income decrease as economic freedom increases, and they eventually disappear.

Originality/value

This is the first study investigating the intricate relationship between corruption, economic freedom and economic performance using data from US states. The study uses a news-based measure of corruption constructed by Dincer and Johnston (2017), which has several advantages over the convictions-based measure used in previous studies analyzing the relationship between corruption and growth using US data. The study takes into account the integration and cointegration properties of the data and estimates the relationship among the cointegrated variables using FMOLS following Pedroni (2000).

Details

Journal of Economic Studies, vol. 47 no. 6
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 24 March 2022

Pushp Kumar, Neha Kumari and Naresh Chandra Sahu

The paper aims to examine the effects of floods on economic growth in India from 1980 to 2019, taking into account the role of foreign direct investment (FDI) inflows and foreign…

Abstract

Purpose

The paper aims to examine the effects of floods on economic growth in India from 1980 to 2019, taking into account the role of foreign direct investment (FDI) inflows and foreign aid.

Design/methodology/approach

The study uses augmented Dickey–Fuller (ADF) and Phillip–Perron (PP) tests to determine the stationarity of the variables. Several models, including autoregressive distributed lag (ARDL), fully modified ordinary least square (FMOLS), dynamic ordinary least square (DOLS) and canonical cointegration regression (CCR), are used to examine the impact of floods on economic growth.

Findings

The bounds test determines the long-term relationship between floods, FDI inflows, economic growth and foreign aid. According to the ARDL and FMOLS models, floods have a negative long-term and short-term impact on India’s economic growth. Furthermore, FDI inflows and foreign aid are beneficial to economic growth. The findings of the ARDL and FMOLS models are confirmed by the DOLS and CCR models. Granger causality establishes a unidirectional causality that extends from floods to economic growth. Further diagnostic tests show that the estimates are free of heteroskedasticity, serial correlation and parameter instability.

Practical implications

Indian government needs to invest more in research and development on flood management techniques. Institutional strengthening is also required to implement pre- and post-flood prevention measures properly. Sound disaster financing strategy and proper water bodies management should be prioritised. Foreign investment opportunities should be encouraged by strengthening international relations.

Originality/value

This is the first time-series study that analysed the effects of floods on economic growth in India. Moreover, the paper contributes to floods literature by applying several econometric models for robustness check.

Details

Management of Environmental Quality: An International Journal, vol. 33 no. 5
Type: Research Article
ISSN: 1477-7835

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 dividend…

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

Article
Publication date: 15 December 2021

Billie Ann Brotman and Brett Katzman

This paper aims to examine potential causes of bankruptcy as they relate to hurricane damage. Investigate whether hurricanes result in personal bankruptcy filings due to real…

Abstract

Purpose

This paper aims to examine potential causes of bankruptcy as they relate to hurricane damage. Investigate whether hurricanes result in personal bankruptcy filings due to real property damages. Strengthen existing descriptive results by using fully modified ordinary least squares (FMOLS).

Design/methodology/approach

Lagged FMOLS model is used with data from states that suffered hurricane damage between 2000 through 2020. FMOLS controls for various financial distresses that can cause bankruptcy filings.

Findings

Bankruptcy is usually filed for within one year of a hurricane. Changes in house prices and hurricane severity were significant indicators of bankruptcy filings. However, the divorce rate, commonly thought of as a primary reason for bankruptcy, is insignificant.

Research limitations/implications

Data was available on a state level for the independent variables. Hurricane damage needed to be financially significant enough for inland flooding to be measurable and influential.

Practical implications

Establishes that financial distress comes from several sources, not just home damage. Financial distress is highly correlated with whether a home was insured. Divorce does not cause bankruptcy filings.

Social implications

Federal flood insurance programs should be reexamined. Having a broader all-risk homeowner policy could reduce the number of households that file for bankruptcy after a hurricane.

Originality/value

Existing research uses descriptive statistics and obtains mixed findings regarding the association between hurricane damage and bankruptcy filings. The FMOLS approach provides clarity about this association.

Article
Publication date: 21 April 2020

Nura Sani Yahaya, Mohd Razani Mohd‐Jali and Jimoh Olajide Raji

This study examines the role of financial development and its interaction with corruption in the environmental degradation of eight Sub-Saharan African countries from 2000–2014.

Abstract

Purpose

This study examines the role of financial development and its interaction with corruption in the environmental degradation of eight Sub-Saharan African countries from 2000–2014.

Design/methodology/approach

The study utilizes Pedroni cointegration and fully modified ordinary least squares (FMOLS) techniques for the estimation of the models.

Findings

The results of the cointegration test reveal that there exist long-run relationships among the variables in the model with the interaction of financial development and corruption, and in the model without interaction. The FMOLS estimates show that in the former model, the interaction of financial development with corruption is positively significant in determining the level of environmental degradation in those countries. Moreover, in the latter, financial development, trade openness, and corruption have a positive effect on their environmental degradation

Research limitations/implications

Unavailability of data, the study was limited to only eight Sub-Saharan African nations

Practical implications

The finding that financial development and its interaction with corruption have an adverse effect on the environments of the Sub-Saharan African countries implies the need to focus on how efficient credits are being allocated in those countries. For better management of environmental quality, this may require the implementation of policies that enhance credit allocation to users with energy-efficient technology and appliances that promote the quality of environments. In addition, stringent policies could be embarked upon to curtail all acts of corruption in the region for an efficient credit allocation and a better environment in the development of Sub-Saharan African society.

Originality/value

The dearth in empirical studies on the Sub-Saharan African countries motivates this study. In particular, little is known about the interaction effect of corruption and financial development on the environmental degradation of those countries, as the work on this is limited in the existing literature.

Details

Management of Environmental Quality: An International Journal, vol. 31 no. 4
Type: Research Article
ISSN: 1477-7835

Keywords

Article
Publication date: 30 November 2021

Mowshumi Sharmin

The purpose of this study is to investigate the synergy between sectoral output, energy use and CO2 emission with other factors for a panel of South Asian economies including…

Abstract

Purpose

The purpose of this study is to investigate the synergy between sectoral output, energy use and CO2 emission with other factors for a panel of South Asian economies including Afghanistan, Bangladesh, Bhutan, India, Pakistan, Maldives, Nepal and Sri Lanka.

Design/methodology/approach

The analysis is done using annual panel data from 1980–2019 using dynamic ordinary least squares (DOLS), fully modified OLS (FMOLS) and Toda-Yamamoto techniques.

Findings

Empirical findings reveal the existence of a statistically significant long-run cointegrating relationship between energy use, sectoral output such as agricultural, industry and service gross domestic product (GDP), globalization, urbanization and CO2 emission. DOLS and FMOLS result posits that in the case of the South Asian region agriculture GDP does not contribute to increasing CO2 emission while service and industrial GDP is responsible for increasing CO2 emission along with urban population, energy use and to some extent globalization. More remarkably, the contribution of the service GDP is greater than the other two sectoral outputs in increasing CO2 emission with a feedback hypothesis.

Practical implications

As CO2 emission is a global phenomenon with a cross-boundary effect, these empirical findings might contribute to formulating implementable energy and environmental policies to sustain growth, as well as to protect the environment in the regional context.

Originality/value

The study contributes to the literature by providing an empirical investigation of South Asia incorporating the contribution of sectoral output to understand the potential contribution of each sector on energy and emission. This is the first study on the South Asian context from the perspective of sectoral output, energy and emission.

Details

International Journal of Energy Sector Management, vol. 16 no. 4
Type: Research Article
ISSN: 1750-6220

Keywords

Open Access
Article
Publication date: 1 March 2024

Kavita Kanyan and Shveta Singh

This study aims to examine the impact and contribution of priority and non-priority sectors, as well as their sub-sectors, on the gross non-performing assets of public, private…

Abstract

Purpose

This study aims to examine the impact and contribution of priority and non-priority sectors, as well as their sub-sectors, on the gross non-performing assets of public, private and foreign sector banks.

Design/methodology/approach

The Reserve Bank of India's database on the Indian economy is used to retrieve data over 13 years (2008–2021). Public sector (12), private sector (22) and foreign sector (44) banks are represented in the sample. Two-way ANOVA, multiple regression and panel regression statistical techniques are used in SPSS and EViews to examine the data. Further, the results are also validated by using robustness testing by applying the fully modified ordinary least square (FMOLS) and dynamic least square (DOLS) regression.

Findings

The results showed that, for private and foreign banks, the non-priority sector makes up the majority of the total gross non-performing assets, although both the priority and non-priority sectors are substantial for public sector banks. The largest contributors to the total gross non-performing assets in public, private and foreign banks are industries, agriculture and micro and small businesses. The FMOLS displays robustness results that are qualitatively similar to the baseline result.

Practical implications

Based on the study's findings about the patterns of non-performing assets originating from these specific industries, banks might improve the way in which these advanced loans are managed.

Originality/value

There has not been much research done on the subject of sub-sector-specific non-performing assets and how they affect total gross non-performing assets across the three sector banks. The study's primary focus will be on the issue of non-performing assets in the priority’s and non-priority’s sub-sectors, namely, agricultural, micro and small businesses, food credit, industries, services, retail loans and other priority and non-priority sectors.

Details

Vilakshan - XIMB Journal of Management, vol. 21 no. 1
Type: Research Article
ISSN: 0973-1954

Keywords

Article
Publication date: 22 March 2023

Hafizah Hammad Ahmad Khan

The main purpose of this study is to investigate the impact of housing price on mortgage debt accumulation while considering the structural break effects associated with the…

Abstract

Purpose

The main purpose of this study is to investigate the impact of housing price on mortgage debt accumulation while considering the structural break effects associated with the Global Financial Crisis (GFC).

Design/methodology/approach

To determine the existence of a long run relationship among the variables, this study used a Johansen cointegration test. The long run model was then estimated using the fully modified ordinary least square method and reported for both the model with and without a structural break associated with the GFC.

Findings

The findings demonstrate a moderate positive relationship between housing price and mortgage debt, with the impact of the GFC is positive but insignificant. The household’s lack of responsiveness to the GFC may be attributed to their optimistic expectations and confidence in the Malaysian housing market.

Practical implications

Findings of this study provide some guidance to policymakers and the banking sector in predicting household borrowing behavior during future economic crises.

Originality/value

The increase in housing prices and mortgage debt after the GFC has been a concern for many countries, including Malaysia. This study contributes to the literature by investigating the relationship between housing prices and mortgage debt in Malaysia and sheds light on the impact of the GFC on household borrowing behavior. The study’s contributions include providing new evidence to the underexplored topic, enhancing the robustness and reliability of the empirical results and providing insights into the importance of testing for structural breaks in time series analysis.

Details

International Journal of Housing Markets and Analysis, vol. 17 no. 1
Type: Research Article
ISSN: 1753-8270

Keywords

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