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1 – 10 of over 2000

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Nonlinear Time Series Analysis of Business Cycles
Type: Book
ISBN: 978-0-44451-838-5

Article
Publication date: 7 August 2017

Zachary Alexander Smith and Muhammad Zubair Mumtaz

The purpose of this paper is to examine whether there is significant evidence that hedge fund managers engage in deceptive manipulation of their reported performance results.

Abstract

Purpose

The purpose of this paper is to examine whether there is significant evidence that hedge fund managers engage in deceptive manipulation of their reported performance results.

Design/methodology/approach

A model of hedge fund performance has been developed using standard regression analysis incorporating dependent lagged variables and an autoregressive process. In addition, the extreme bounds analysis technique has been used to examine the robustness and sensitivity of the explanatory variables. Finally, the conditional influence of the global stock market’s returns on hedge fund performance and the conditional return behavior of the Hedge Fund Index’s performance have been explored.

Findings

This paper begins by identifying a model of hedge fund performance using passive index funds that is well specified and robust. Next, the lag structure associated with hedge fund returns has been examined and it has been determined that it seems to take the hedge fund managers two months to integrate the global stock market’s returns into their reported performance; however, the lagged variables were reduced from the final model. The paper continues to explore the smoothing behavior by conditioning the dependent lagged variables on positive and negative returns and find that managers are conservative in their estimates of positive performance events, but, when experiencing a negative result, they seem to attempt to rapidly integrate that effect into the return series. The strength of their integration increases as the magnitude of the negative performance increases. Finally, the performance of returns for both the Hedge Fund Index and the passive indices were examined and no significant differences between the conditional returns were found.

Research limitations/implications

The results of this analysis illustrate that hedge fund performance is not all that different from the performance of passive indices included in this paper, although it does offer investors access to a unique return distribution. From a management perspective, we are reminded that we need to be cautious about hastily arriving at conclusions about something that looks different or feels different from everything else, because, at times, our preconceived notions will cause us to avoid participating in something that may add value to our organizations. From an investment perspective, sometimes having something that looks and behaves differently from everything else, improves our investment experience.

Originality/value

This paper provides a well-specified and robust model of hedge fund performance and uses extreme bounds analysis to test the robustness of this model. This paper also investigates the smoothing behavior of hedge fund performance by segmenting the returns into two cohorts, and it finds that the smoothing behavior is only significant after the hedge funds produce positive performance results, the strength of the relationship between the global stock market and hedge fund performance is more economically significant if the market has generated a negative performance result in the previous period, and that as the previous period’s performance becomes increasingly negative, the strength of the relationship between the Hedge Fund Index and the global stock market increases.

Details

Chinese Management Studies, vol. 11 no. 3
Type: Research Article
ISSN: 1750-614X

Keywords

Open Access
Article
Publication date: 5 August 2021

Anthanasius Fomum Tita and Pieter Opperman

Homeownership provides shelter and is a vital component of wealth, and house purchase signifies a lifetime achievement for many households. For South Africa confronted with social…

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Abstract

Purpose

Homeownership provides shelter and is a vital component of wealth, and house purchase signifies a lifetime achievement for many households. For South Africa confronted with social and structural challenges, homeownership by the low and lower middle-income household is pivotal for its structural transformation process. In spite of these potential benefits, research on the affordable housing market in the context of South Africa is limited. This study aims to contribute to this knowledge gap by answering the question “do changes in household income per capita have a symmetric or asymmetric effect on affordable house prices?”

Design/methodology/approach

A survey of the international literature on house prices and income revealed that linear modelling that assumes symmetric reaction of macroeconomic variables dominates the empirical strategy. This linearity assumption is restrictive and fails to capture possible asymmetric dynamics inherent in the housing market. The authors address this empirical limitation by using asymmetric non-linear autoregressive distributed lag models that can test and detect the existence of asymmetry in both the long and short run using data from 1985Q1 to 2016Q3.

Findings

The results revealed the presence of an asymmetric long-run relationship between affordable house prices and household income per capita. The estimated asymmetric long-run coefficients of logIncome[+] and logIncome[−] are 1.080 and −4.354, respectively, implying that a 1% increase/decrease in household income per capita induces a 1.08% rise/4.35% decline in affordable house prices everything being equal. The positive increase in affordable house prices creates wealth, helps low and middle-income household climb the property ladder and can reduce inequality, which provides support for the country’s structural transformation process. Conversely, a decline in affordable house prices tends to reduce wealth and widen inequality.

Practical implications

This paper recommends both supply- and demand-side policies to support affordable housing development. Supply-side stimulants should include incentives to attract developers to affordable markets such as municipal serviced land and tax credit. Demand-side policy should focus on asset-based welfare policy; for example, the current Finance Linked Income Subsidy Programme (FLISP). Efficient management and coordination of the FLISP are essential to enhance the affordability of first-time buyers. Given the enormous size of the affordable property market, the practice of mortgage securitization by financial institutions should be monitored, as a persistent decline in income can trigger a systemic risk to the economy.

Social implications

The study results illustrate the importance of homeownership by low- and middle-income households and that the development of the affordable market segment can boost wealth creation and reduce residential segregation. This, in turn, provides support to the country’s structural transformation process.

Originality/value

The affordable housing market in South Africa is of strategic importance to the economy, accounting for 71.4% of all residential properties. Homeownership by low and lower middle-income households creates wealth, reduces wealth inequality and improves revenue collection for local governments. This paper contributes to the empirical literature by modelling the asymmetric behaviour of affordable house prices to changes in household income per capita and other macroeconomic fundamentals. Based on available evidence, this is the first attempt to examine the dynamic asymmetry between affordable house prices and household income per capita in South Africa.

Details

International Journal of Housing Markets and Analysis, vol. 15 no. 3
Type: Research Article
ISSN: 1753-8270

Keywords

Book part
Publication date: 23 June 2016

Alexander Chudik, Kamiar Mohaddes, M. Hashem Pesaran and Mehdi Raissi

This paper develops a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in large dynamic heterogeneous panel data models with…

Abstract

This paper develops a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in large dynamic heterogeneous panel data models with cross-sectionally dependent errors. The asymptotic distribution of the CS-DL estimator is derived under coefficient heterogeneity in the case where the time dimension (T ) and the cross-section dimension (N ) are both large. The CS-DL approach is compared with more standard panel data estimators that are based on autoregressive distributed lag (ARDL) specifications. It is shown that unlike the ARDL-type estimator, the CS-DL estimator is robust to misspecification of dynamics and error serial correlation. The theoretical results are illustrated with small sample evidence obtained by means of Monte Carlo simulations, which suggest that the performance of the CS-DL approach is often superior to the alternative panel ARDL estimates, particularly when T is not too large and lies in the range of 30–50.

Article
Publication date: 5 July 2023

Fredrick Otieno Okuta, Titus Kivaa, Raphael Kieti and James Ouma Okaka

The housing market in Kenya continues to experience an excessive imbalance between supply and demand. This imbalance renders the housing market volatile, and stakeholders lose…

Abstract

Purpose

The housing market in Kenya continues to experience an excessive imbalance between supply and demand. This imbalance renders the housing market volatile, and stakeholders lose repeatedly. The purpose of the study was to forecast housing prices (HPs) in Kenya using simple and complex regression models to assess the best model for projecting the HPs in Kenya.

Design/methodology/approach

The study used time series data from 1975 to 2020 of the selected macroeconomic factors sourced from Kenya National Bureau of Statistics, Central Bank of Kenya and Hass Consult Limited. Linear regression, multiple regression, autoregressive integrated moving average (ARIMA) and autoregressive distributed lag (ARDL) models regression techniques were used to model HPs.

Findings

The study concludes that the performance of the housing market is very sensitive to changes in the economic indicators, and therefore, the key players in the housing market should consider the performance of the economy during the project feasibility studies and appraisals. From the results, it can be deduced that complex models outperform simple models in forecasting HPs in Kenya. The vector autoregressive (VAR) model performs the best in forecasting HPs considering its lowest root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and bias proportion coefficient. ARIMA models perform dismally in forecasting HPs, and therefore, we conclude that HP is not a self-projecting variable.

Practical implications

A model for projecting HPs could be a game changer if applied during the project appraisal stage by the developers and project managers. The study thoroughly compared the various regression models to ascertain the best model for forecasting the prices and revealed that complex models perform better than simple models in forecasting HPs. The study recommends a VAR model in forecasting HPs considering its lowest RMSE, MAE, MAPE and bias proportion coefficient compared to other models. The model, if used in collaboration with the already existing hedonic models, will ensure that the investments in the housing markets are well-informed, and hence, a reduction in economic losses arising from poor market forecasting techniques. However, these study findings are only applicable to the commercial housing market i.e. houses for sale and rent.

Originality/value

While more research has been done on HP projections, this study was based on a comparison of simple and complex regression models of projecting HPs. A total of five models were compared in the study: the simple regression model, multiple regression model, ARIMA model, ARDL model and VAR model. The findings reveal that complex models outperform simple models in projecting HPs. Nonetheless, the study also used nine macroeconomic indicators in the model-building process. Granger causality test reveals that only household income (HHI), gross domestic product, interest rate, exchange rates (EXCR) and private capital inflows have a significant effect on the changes in HPs. Nonetheless, the study adds two little-known indicators in the projection of HPs, which are the EXCR and HHI.

Details

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

Keywords

Book part
Publication date: 1 January 2008

Michiel de Pooter, Francesco Ravazzolo, Rene Segers and Herman K. van Dijk

Several lessons learnt from a Bayesian analysis of basic macroeconomic time-series models are presented for the situation where some model parameters have substantial posterior…

Abstract

Several lessons learnt from a Bayesian analysis of basic macroeconomic time-series models are presented for the situation where some model parameters have substantial posterior probability near the boundary of the parameter region. This feature refers to near-instability within dynamic models, to forecasting with near-random walk models and to clustering of several economic series in a small number of groups within a data panel. Two canonical models are used: a linear regression model with autocorrelation and a simple variance components model. Several well-known time-series models like unit root and error correction models and further state space and panel data models are shown to be simple generalizations of these two canonical models for the purpose of posterior inference. A Bayesian model averaging procedure is presented in order to deal with models with substantial probability both near and at the boundary of the parameter region. Analytical, graphical, and empirical results using U.S. macroeconomic data, in particular on GDP growth, are presented.

Details

Bayesian Econometrics
Type: Book
ISBN: 978-1-84855-308-8

Article
Publication date: 28 August 2020

Iffat Zehra, Muhammad Kashif and Imran Umer Chhapra

This paper aims to examine association of money demand with key macroeconomic variables in Pakistan. The paper also investigates the asymmetric effect of real effective exchange…

Abstract

Purpose

This paper aims to examine association of money demand with key macroeconomic variables in Pakistan. The paper also investigates the asymmetric effect of real effective exchange rate (REER) on money demand.

Design/methodology/approach

The study employs both linear autoregressive distributed lag (ARDL) and non-linear autoregressive distributed lag (NARDL) model. Annual data from 1970 to 2018 is used which is subjected to non-linearity through partial sum concept. Empirical analysis is conducted to prove if money demand is influenced by currency appreciation or depreciation, for long and short run.

Findings

Cointegration test indicates existence of a long-run relationship between money demand and its determinants. Results from NARDL model suggest negative relation between money demand and inflation in long and short run. Real income shows positive but a very minimal and insignificant effect on money demand in long and short run. Impact of call money rates is statistically significant and negative on M1 and M2. Wald tests and differing coefficient sign confirm presence of asymmetric relation of REER in long run with M2, whereas in short run we observe a linear, symmetrical relation of REER with M1 and M2. Stability diagnostic tests (CUSUM and CUSUMSQ) verify stability of M2 demand model in Pakistan.

Practical implications

Results signify that role of money demand is imperative as a monetary policy tool and it can be utilized to achieve objective of price stability. Additionally, exchange rate movements should be critically examined by monetary authorities to avoid inflationary pressures resulting from an increase in demand for broad monetary aggregate.

Originality/value

The paper contributes to scarce monetary literature on asymmetrical effects of exchange rate in Pakistan. Impact of variables has been studied through linear approach, but this paper is unique since it attempts to explore non-linear relationships.

Details

International Journal of Emerging Markets, vol. 16 no. 8
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 7 December 2021

Gideon Ntim-Amo, Yin Qi, Ernest Ankrah-Kwarko, Martinson Ankrah Twumasi, Stephen Ansah, Linda Boateng Kissiwa and Ran Ruiping

The purpose of this research is to examine the validity of the agriculture-induced environmental Kuznets curve (EKC) hypothesis with evidence from an autoregressive distributed…

Abstract

Purpose

The purpose of this research is to examine the validity of the agriculture-induced environmental Kuznets curve (EKC) hypothesis with evidence from an autoregressive distributed lag (ARDL) approach with a structural break including real income and energy consumption in the model for Ghana over the period 1980–2014.

Design/methodology/approach

The ARDL approach with a structural break was used to analyze the agriculture-induced EKC model which has not been studied in Ghana. The dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) econometric methods were further used to validate the robustness of the estimates, and the direction of the relationship between the study variables was also clarified using the Toda–Yamamoto Granger causality test.

Findings

The ARDL results revealed that GDP, energy consumption and agricultural value added have significant positive effects on CO2 emissions, while GDP2 reduces CO2 emissions. The Toda-Yamamoto causality test results show a bidirectional causality running from GDP and energy consumption to CO2 emissions whereas a unidirectional long-term causality runs from GDP2 and agriculture value-added to CO2 emissions.

Practical implications

This finding validated the presence of the agriculture-induced EKC hypothesis in Ghana in both the short run and long run, and the important role of agriculture and energy consumption in economic growth was confirmed by the respective bidirectional and unidirectional causal relationships between the two variables and GDP. Thus, a reduction in unsustainable agricultural practices is recommended through specific policies to strengthen institutional quality in Ghana for a paradigm shift from rudimentary technology to modern sustainable agrarian technologies.

Originality/value

This study is novel in the EKC literature in Ghana, as no study has yet been done on agriculture-induced EKC in Ghana, and the other EKC studies also failed to account for structural breaks which have been done by this study. This study further includes a causality analysis to examine the direction of the relationship which the few EKC studies in Ghana failed to address. Finally, dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) methods are used for robustness check, unlike other studies with single methodologies.

Details

Management of Environmental Quality: An International Journal, vol. 33 no. 2
Type: Research Article
ISSN: 1477-7835

Keywords

Article
Publication date: 6 August 2020

Monica Singhania and Neha Saini

The paper attempts to revisit the nexus between economic growth, carbon emissions, trade openness, financial effectiveness and FDI for a sample of seven developed and developing…

Abstract

Purpose

The paper attempts to revisit the nexus between economic growth, carbon emissions, trade openness, financial effectiveness and FDI for a sample of seven developed and developing countries using curvilinear relationship as per environmental Kuznets curve (EKC) hypothesis over long term.

Design/methodology/approach

The authors determine the unit root properties of variables (using Clemente–Montañés–Reyes unit root test with double mean shifts and AO model and augmented Dickey–Fuller test) for structural breaks at different levels. Autoregressive distributed lag (ARDL) and error correction model (ECM) methodology was used to estimate long- and short-run parameters among the selected variables in sample countries from 1965 to 2016. Vector error correction (VEC) and Granger causality approach was used to determine the direction of causality.

Findings

The authors confirmed long-run relationship among the variables and highlighted high economic growth and energy consumption as the main causes of environmental degradation. While in India financial development and FDI inflows depict a negative association with environmental sustainability, however, such relationship was positive in the United Kingdom (UK), which is often considered as a benchmark for policymakers. The authors’ findings were in agreement with existing research insights in reporting FDI and financial development as the major contributors towards (unsustainable) sustainable environment through emissions in case of (developing country like India) developed country like UK. For other sample countries (China, Brazil, Japan, South Africa, United States of America (USA)), the authors’ model failed to capture financial development and FDI as significant contributors of carbon emissions. However, unidirectional causality running from energy to carbon emission was observed leading to the policy adoption of incentivizing alternative energy-based resources to increase energy efficiency across the energy value chain.

Research limitations/implications

Manufacturing with renewable energy, in collaboration with private and foreign players, under an institutional framework is desirable. Policy instruments including mandatory administrative controls, economic incentives and voluntary schemes that promote energy efficiency building blocks need to be established. A sound legal system for implementing technological innovation, financial subsidy incentives, interest-free loan programmes and development of financial sector supports creation and thriving of energy efficient units, often a perquisite for accelerated development.

Originality/value

By undertaking a comparative analysis, the authors address the research gap through revisiting EKC hypothesis with different set of trade policy and financial development framework. To the best of the authors’ knowledge, earlier studies were limited to one-country data analysis and did not consider the comparative data set of developed and developing countries with reference to financial development and FDI components.

Details

International Journal of Productivity and Performance Management, vol. 69 no. 8
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 22 May 2009

M. Shabri Abd. Majid and Rosylin Mohd. Yusof

The purpose of this paper is to explore the extent to which macroeconomic variables affect the Islamic stock market behavior in Malaysia in the post 1997 financial crisis period.

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Abstract

Purpose

The purpose of this paper is to explore the extent to which macroeconomic variables affect the Islamic stock market behavior in Malaysia in the post 1997 financial crisis period.

Design/methodology/approach

The paper employs the latest estimation technique of autoregressive distributed lag (ARDL) model approach to cointegration.

Findings

The results suggest that real effective exchange rate, money supply M3, treasury bill rate (TBR) and federal fund rate (FFR) seem to be suitable targets for the government to focus on, in order to stabilize the Islamic stock market and to encourage more capital flows into the market. As for the interest rates and stock returns relationship, the paper finds that when interest rates rise either domestically (TBR) or internationally (FFR), the Muslim investors will buy more Shari'ah compliant stocks; thereby escalating the Islamic stock prices.

Research limitations/implications

The results of this study are limited to the post 1997 financial crisis period until the beginning of the year 2006 for a small open economy, Malaysia.

Practical implications

The paper reveals that both changes in the local monetary policy variables and in the US monetary policy as measured by the changes in the FFR have a significant direct impact on the Islamic stock market behavior in Malaysia.

Originality/value

The paper adopts the latest time series econometrics technique to test for cointegration, ARDL. And it is among the earliest attempts to investigate the long‐run effects of the macroeconomic variables changes either domestically or internationally on the Islamic stock market.

Details

Humanomics, vol. 25 no. 2
Type: Research Article
ISSN: 0828-8666

Keywords

1 – 10 of over 2000