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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

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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…

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.

Details

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

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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…

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. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1750-6220

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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

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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

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Article
Publication date: 2 December 2021

Pushp Kumar, Naresh Chandra Sahu, Mohd Arshad Ansari and Siddharth Kumar

The paper investigates the effects of climate change along with ecological and carbon footprint on rice crop production in India during 1982–2016.

Abstract

Purpose

The paper investigates the effects of climate change along with ecological and carbon footprint on rice crop production in India during 1982–2016.

Design/methodology/approach

The autoregressive distributed lag (ARDL), canonical cointegration regression (CCR) and fully modified ordinary least square (FMOLS) models are used in the paper.

Findings

A long-run relationship is found between climate change and rice production in India. Results report that ecological footprint and carbon footprint spur long-term rice production. While rainfall boosts rice crop productivity in the short term, it has a negative long-term impact. Further, the findings of ARDL models are validated by other cointegration models, i.e., the FMOLS and CCR models.

Research limitations/implications

This study provides insights into the role of ecological footprint and carbon footprint along with climate variables in relation to rice production.

Originality/value

In the literature, the effects of ecological and carbon footprint on rice production are missing. Therefore, this is the first study to empirically examine the impact of climate change along with ecological footprint and carbon footprint on rice production in India.

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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Article
Publication date: 26 July 2021

Billie Ann Brotman

Flood damage to uninsured single-family homes shifts the entire burden of costly repairs onto the homeowner. Homeowners in the United States and in much of Europe can…

Abstract

Purpose

Flood damage to uninsured single-family homes shifts the entire burden of costly repairs onto the homeowner. Homeowners in the United States and in much of Europe can purchase flood insurance. The Netherlands and Asian countries generally do not offer flood insurance protection to homeowners. Uninsured households incur the entire cost of repairing/replacing properties damaged due to flooding. Homeowners’ policies do not cover damage caused by flooding. The paper examines the link between personal bankruptcy and the severity of flooding events, property prices and financial condition levels.

Design/methodology/approach

A fully modified ordinary least squares (FMOLS) regression model is developed which uses personal bankruptcy filings as its dependent variable during the years 2000 through 2018. This time-series model considers the association between personal bankruptcy court filings and costly, widespread flooding events. Independent variables were selected that potentially act as mitigating factors reducing bankruptcy filings.

Findings

The FMOLS regression results found a significant, positive association between flooding events and the total number of personal bankruptcy filings. Higher flooding costs were associated with higher bankruptcy filings. The Home Price Index is inversely related to the bankruptcy dependent variable. The R-squared results indicate that 0.65% of the movement in the dependent variable personal bankruptcy filings is explained by the severity of a flooding event and other independent variables.

Research limitations/implications

The severity of the flooding event is measured using dollar losses incurred by the National Flood Insurance program. A macro-case study was undertaken, but the research results would have been enhanced by examining local areas and demographic factors that may have made bankruptcy filing following a flooding event more or less likely.

Practical implications

The paper considers the impact of the natural disaster flooding on bankruptcy rates filings. The findings may have implications for multi-family properties as well as single-family housing. Purchasing flood insurance generally mitigates the likelihood of severe financial risk to the property owner.

Social implications

Natural flood insurance is underwritten by the federal government and/or by private insurers. The financial health of private property insurers that underwrite flooding and their ability to meet losses incurred needs to be carefully scrutinized by the insured.

Originality/value

Prior studies analyzing the linkages existing between housing prices, natural disasters and bankruptcy used descriptive data, mostly percentages, when considering this association. The study herein posits the same questions as these prior studies but used regression analysis to analyze the linkages. The methodology enables additional independent variables to be added to the analysis.

Details

Property Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0263-7472

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Article
Publication date: 28 May 2021

Saffet Akdag, Hakan Yildirim and Andrew Adewale Alola

The recent dynamics of trade policy, especially that is associated with the United States of America (USA) and China, has not only triggered policy adjustments in two…

Abstract

Purpose

The recent dynamics of trade policy, especially that is associated with the United States of America (USA) and China, has not only triggered policy adjustments in two economies, it has also implied an uncertainty spillover to other economies across the globe. Consequently, the current study attempts to examine the effect of uncertainties in the USA–China trade policies on stock market indexes. In addition, the cointegration evidence between the USA–China trade policy uncertainty index and of the leading Global South fragile quintet (Brazil, Indonesia, South Africa, India and Turkey) stock market indices is investigated.

Design/methodology/approach

Mainly, the FMOLS and DOLS Granger causality analysis with cointegration coefficient estimators were employed for the dataset over the monthly data period of March 2003 and July 2019.

Findings

Accordingly, the study found a long-term relationship between the USA–China Trade Policy Uncertainty index and the stock exchange indexes. In addition, a causal relationship was established from the change in the USA–China Trade Policy Uncertainty index to the change in the stock market indexes of almost all of the examined countries (Brazil, Indonesia, South Africa, India and Turkey). In addition, the nonlinear Autoregressive Distributed Lag approach further offers evidence of asymmetric relationship among the examined indicators.

Originality/value

Moreover, this study contributed to the existing literature because it employed the indexes of BIST100, BOVESPA, BSE Sensex 30, IDX Composite and South Africa 40 in a novel approach. Thus, the study posited a useful policy guideline for associated economic uncertainties arising from the trade dispute, such as the case of the world’s two largest trading giants or partners (i.e. the USA and China).

Details

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

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Article
Publication date: 26 August 2020

Nitin Koshta, Hajam Abid Bashir and Taab Ahmad Samad

The main purpose of this study is to explore the presence of the EKC hypothesis in emerging economies. Additionally, the present study also explores the existence of the…

Abstract

Purpose

The main purpose of this study is to explore the presence of the EKC hypothesis in emerging economies. Additionally, the present study also explores the existence of the “resource curse hypothesis” (RCH), and the causal relationship among the variables that are considered for testing the presence of EKC and RCH hypothesis for a panel of selected emerging economies for the time period between 1990 and 2014.

Design/methodology/approach

The authors performed unit root test followed by cointegration test to test the existence of cointegrating relationship among the variables. Dynamic ordinary least square (DOLS) and fully modified ordinary least square (FMOLS) methods are used to obtain long-run estimates of considered variables, and the Granger causality test is performed to test the directional causality.

Findings

The long-run estimates obtained from DOLS and FMOLS techniques support the presence of the EKC (inverted U-shape) and the RCH.

Originality/value

To the best of the authors’ knowledge, the present work is the pioneer study for EKC and RCH investigation in the context of emerging economies. The policy implication is that these economies should look forward to drafting new policies to reduce environmental degradation and promote sustainable development.

Details

Indian Growth and Development Review, vol. 14 no. 1
Type: Research Article
ISSN: 1753-8254

Keywords

Open Access
Article
Publication date: 11 September 2020

Yousra Trichilli, Mouna Boujelbène Abbes and Sabrine Zouari

This paper examines the impact of political instability on the investors' behavior, measured by Google search queries, and on the dynamics of stock market returns.

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Abstract

Purpose

This paper examines the impact of political instability on the investors' behavior, measured by Google search queries, and on the dynamics of stock market returns.

Design/methodology/approach

First, by using the DCC-GARCH model, the authors examine the effect of investor sentiment on the Tunisian stock market return. Second, the authors employ the fully modified dynamic ordinary least square method (FMOL) to estimate the long-term relationship between investor sentiment and Tunisian stock market return. Finally, the authors use the wavelet coherence model to test the co-movement between investor sentiment measured by Google Trends and Tunisian stock market return.

Findings

Using the dynamic conditional correlation (DCC), the authors find that Google search queries index has the ability to reflect political events especially the Tunisian revolution. In addition, empirical results of fully modified ordinary least square (FMOLS) method reveal that Google search queries index has a slightly higher effect on Tunindex return after the Tunisian revolution than before this revolution. Furthermore, by employing wavelet coherence model, the authors find strong comovement between Google search queries index and return index during the period of the Tunisian revolution political instability. Moreover, in the frequency domain, strong coherence can be found in less than four months and in 16–32 months during the Tunisian revolution which show that the Google search queries measure was leading over Tunindex return. In fact, wavelet coherence analysis confirms the result of DCC that Google search queries index has the ability to detect the behavior of Tunisian investors especially during the period of political instability.

Research limitations/implications

This study provides empirical evidence to portfolio managers that may use Google search queries index as a robust measure of investor's sentiment to select a suitable investment and to make an optimal investments decisions.

Originality/value

The important research question of how political instability affects stock market dynamics has been neglected by scholars. This paper attempts principally to fill this void by investigating the time-varying interactions between market returns, volatility and Google search based index, especially during Tunisian revolution.

Details

Journal of Capital Markets Studies, vol. 4 no. 1
Type: Research Article
ISSN: 2514-4774

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