Is it possible to discriminate between different switching regressions models? An empirical investigation

In this paper we study, using the sup LR test, the possibility of discrimination between two classes of models: the Markov switching models of Hamilton (1989) and the Threshold Auto-Regressive Models (TAR) of Lim and Tong (1980). This work is motivated by the fact that generally practicians use, in applications, switching models without any statistical justification. Using experiment simulations, we show that it is very difficult to discriminate between the MSAR and the SETAR models specially using large samples. This means that when the null hypothesis is rejected, it appears that different switching models are significant. Moreover, the results show that the power of the sup LR test is sensitive to the mean, the noise variance and the delay parameter. Then, we apply this methodology to two time series: the US GNP growth rate and the US/UK exchange rate. We shall retain retain a Markov switching process for the US GNP growth rate and the US/UK exchange rate (monthly data). For the US/UK exchange rate (quarterly data), we accept the null hypothesis of a random walk.Switching Models, Sup LR test, Empirical power, Exchange rate

Income Smoothing and CEO Job Security

The purpose of this paper is to examine the link between income smoothing and CEO tenure on a sample of 271 U.S companies over the period 1993 to 2003. Moreover, in order to test the extent of income smoothing for job security and specifically for a lengthen tenure; we also have considered some CEOs characteristics such as age and tenure. Empirical results of Wilcoxon statistics and discriminating analysis show that when the current (future) performance is good, the CEOs find the sufficient margins to manage the earnings to leave in reserve for the future performance (or borrow for the current performance). In addition, the results of the multivariate model show that the CEO smooth the income by decreasing accruals, so they shift current earnings to future periods when current earnings is high and future earnings is low to lengthen their tenure

Breaks or long memory behaviour : an empirical investigation

A paraître dans Physica AAre structural breaks models true switching models or long memory processes ? The answer to this question remain ambiguous. A lot of papers, in recent years, have dealt with this problem. For instance, Diebold and Inoue (2001) and Granger and Hyung (2004) show, under specific conditions, that switching models and long memory processes can be easily confused. In this paper, using several generating models like the mean-plus-noise model, the STOchastic Permanent BREAK model, the Markov switching model, the TAR model, the sign model and the Structural CHange model (SCH) and several estimation techiques like the GPH technique, the Exact Local Whittle (ELW) and the Wavelet methods, we show that, if the answer is quite simple in some cases, it can be mitigate in other cases. Using French and American inflation rates, we show that these series cannot be characterized by the same class of models. The main result of this study suggests that estimating the long memory parameter without taking account existence of breaks in the data sets may lead to misspecification and to overestimate the true parameter.Comment classer les modèles avec breaks : dans la classe des processus avec changement d'état qui sont en général des processus à mémoire courte ou comme processus longue mémoire ? Récemment ce problème fut étudié par un grand nombre d'auteurs dont Diebold et Inoue (2001) et Granger et Hyung (2004). Dans ce papier, nous étudions le comportement possible de longue mémoire de plusieurs processus présentant des breaks. On estime les paramètres de longue mémoire à partir de différentes méthodes. Les résultats ne sont pas toujours convaincants. Nous proposons une approche qui permet de cerner ce qu'il convient de faire empiriquement

Breaks or Long Memory Behaviour : An empirical Investigation

Are structural breaks models true switching models or long memory processes ? The answer to this question remain ambiguous. A lot of papers, in recent years, have dealt with this problem. For instance, Diebold and Inoue (2001) and Granger and Hyung (2004) show, under specific conditions, that switching models and long memory processes can be easily confused. In this paper, using several generating models like the mean-plus-noise model, the STOchastic Permanent BREAK model, the Markov switching model, the TAR model, the sign model and the Structural CHange model (SCH) and several estimation techiques like the GPH technique, the Exact Local Whittle (ELW) and the Wavelet methods, we show that, if the answer is quite simple in some cases, it can be mitigate in other cases. Using French and American inflation rates, we show that these series cannot be characterized by the same class of models. The main result of this study suggests that estimating the long memory parameter without taking account existence of breaks in the data sets may lead to misspecification and to overestimate the true parameter.Structural breaks models; spurious long memory behavior; inflation series

Can the SupLR test discriminate between different switching

In recent years two classes of switching models have been proposed, the Markov switching models, Hamilton (1989) and the Threshold Auto- Regressive Models (TAR), Lim and Tong (1980). These two models have the advantage of being able to modelize and capture asymmetry, sudden changes and irreversibility time observed in many economic and financial time series. Despite these similarities and common points, these models have been envolved, in the literature, largely independently. In this paper, using the $SupLR$ test, we study the possibility of discrimination between these two models. This approach is motivated by the fact that the majority of authors, in applications, use switching models without any statistical justification. We show that when the null hypothesis is rejected it appears that different switching models are significant. Then, using simulation experiments we show that it is very difficult to differenciate between MSAR and SETAR models specially with large samples. The power of the $SupLR$ test seems to be sensitive to the mean, the noise variance and the delay parameter which appear in each model. Finally, we apply this methodology to the US GNP growth rate and the US/UK exchange rate.Switching Models, SETAR processes SupLR test, Empirical power, exchange rates

Environment Degradation and Economic Growth in the Qatar Economy: Evidence from a Markov Switching Equilibrium Correction Model

Air pollution, global greenhouse gases (GHG), water pollution and water resources degradation are among the most serious environmental concerns that encounter the Qatar country. In nowadays, it is commonly known that the effects of environment degradation exceed its direct negative impacts on climate changes to cover its impacts on Human health, nation livelihood and cultural integrity. So, we advocate that understanding and determining factors explaining environmental degradation remain an important question of research. Moreover, by determining factors that explain environment degradation, policymakers, researchers and international institutions can help on recommending the adequate economic policies that can improve the environment quality and the live standing of inhabitants. In the empirical literature, the Environmental Kuznets Curve (EKC) is the most powerful tool used to investigate the relationship between environment degradation and some macroeconomics and financial variables. Following the EKC hypothesis, the relationship between economic growth and environment degradation is inverted-U shaped. From the economic perspective, this means that initially economic growth increases environment degradation and then declines it after a threshold point of income per capita. More specifically, at initial level of economic growth, an increase in income is linked with an increase in energy consumption that raises environment degradation. After reaching a critical level of income, the spending on environment protection is increased, and hence environment degradation tend to decrease. From an econometrical or statistical perspectives, the EKC hypothesis have been firstly tested using the basic EKC equation which relies the environment degradation proxy to the real GDP and to a nonlinear term of the real GDP (the squared real GDP). If the EKC hypothesis holds then the real GDP and the squared real GDP have respectively a positive and negative signs. This EKC hypothesis has been firstly introduced by Kuznets (1955) when examining the relationship between economic growth and income inequality which shows that this relationship is inverted U-shaped. Grossman and Krueger (1995) are the first to examine this relationship between environment degradation and economic growth in their seminal paper published on the Quarterly Journal of Economics. They found that this relationship is inverted U-shaped which validates the EKC hypothesis. Empirically, until now no consensus has been reached about the true nature of the relation between real GDP and environment degradation. Evidence for the EKC hypothesis is very mixed. Overall, the results seem to depend in many factors including the specification, the pollutants and the econometrics technique used. First, empirical studies show that the results in term of positive and negative relationships as well as in term of magnitude differ significantly for the same country depend on the specification studied, linear, quadratic or cubic. Moreover, the inclusion of other factors in the right hand of the regression such as urbanization, trade openness, financial development and political stability have a significant impact on the magnitude of the income per capita variables coefficients. Second, the results differ significantly following the environment degradation proxy used. For instance, Horvath (1997) and Holtz-Eakin and Selden (1995) suggest that the use of global pollutants leads to continuously rise the levels of environment degradation or to a high levels of income per capita turning point, see also Esteve and Tamarit (2011). Third, the results also seem to depend in the econometric approach employed. In this paper, we investigate the case of the Qatar economy for several reasons. First, Qatar 2030 vision has given a high importance to questions related to air pollution, climate change and their impacts on economic sustainability. Second, the rapid increase of economic growth of the Qatar economy in the last two decades has been accompanied with an increase in energy consumption, urbanization and international trade. These factors are among the most important factors largely used in theoretical and empirical literature to explain environment degradation. Third, following the world health organization (WHO), local air pollution levels in Qatar has frequently exceeded recommended levels and are more time higher than the international standards. In fact, compared to the WHO's standards for PM10 for the 24-hour average and for the annual average concentration of 50 ug/m3 and 20 ug/m3 the Qatar's national air quality standards are far from these values. For instance, the values for PM10 is around 150 ug/m3 for 24 hours average concentration and to 50 ug/m3 for the annual average concentration. The data set used in this paper consists on macroeconomics and financial data, including CO2 emissions, ecological foot print, real GDP per capita, energy use, urbanization, financial development and openness trade, to investigate the EKC hypothesis for the Qatar economy. All the dataset except the ecological foot print variable are collected from the world Bank's development indicators (WDI). The ecological footprint data is obtained from the National Footprint Accounts (NFAs) of the Global Footprint Network. This variable is employed as second proxy of environment quality measures. This data set used is a quarterly data and covers the period 1975Q1 to 2007Q4 for variables used for ecological footprint equation and covers the periods 1980Q1 to 2010Q4 for the CO2 emissions equations variables. This paper contributes to the empirical literature of the EKC hypothesis in many ways. First, to our knowledge this paper is the first to consider the case of the Qatar economy as a single country to test the EKC hypothesis as well as the different directions of causality between variables. Second, in addition to the CO2 emissions largely employed in the empirical literature, in this paper we employ also the ecological footprint as a new proxy of environmental degradation. Third, we use recent development of cointegration approach with structural breaks which is also rarely used for the case of EKC hypothesis. As tests of cointegration with shifts in the cointegration vector, we use the Gregory and Hansen (1996), Hatemi-J (2008) and to investigate the causal relationship between all variables using standard Granger causality tests. Fourth, to our knowledge this paper is the first study that uses Markov Switching Equilibrium Correction Model with shifts in both the intercept and the income per capita coefficient for the long run relationship between environment degradation and its key determinants. The empirical findings of this paper are useful for Qatari policymakers and especially for the ministry of environment of the Qatar government. Moreover, economic implications and economic policy are proposed and discussed.qscienc

Analysis Of The Effect Of The European Debt Crisis On The Saudi Arabian Economy

This paper investigates the economic impact of the 2009 European debt crisis on Saudi Arabia’s real economy from 2004 Q2 to 2014 Q2 using a structural vector autoregressive model (SVAR). The results of the impulse response functions obtained from the aggregated data show that the shock to European imports from Saudi Arabia had a significant impact on the real effective exchange rate, inflation rate, and economic growth that lasted for three periods. Moreover, the variance decomposition analysis shows that Europe’s imports from Saudi Arabia explain approximately 20% of the variance of the Saudi real effective exchange rate and real economic growth, 10% of the interest rate variability, and only 5% of the inflation rate variance. The results of the individual country analysis show that the impact of shocks to imports from all European countries had an instantaneous impact, except for France and Spain, where the impact on the economic growth was significant in the second and sixth periods respectively. The results suggest that Saudi Arabian policymakers should continue the process of export diversification in order to reduce its dependence on this region

The Influence Of CEO Departure And Board Characteristics On Firm Performance

This paper uses panel data from 271 U.S. firms to empirically examine the relationship between the departure of a firms CEO and that firms performance. Results of our analysis reveal a significant relationship between CEO departure and firm performance. Specifically, we found that the departure of entrenched CEOs negatively affects current and future firm performance. Results also demonstrate that board size and the presence of independent administrators moderates the relationship between CEO departure and firm performance. This suggests that entrenched CEOs can have informal associations with independent administrators

Do information and communication technology and renewable energy use matter for carbon dioxide emissions reduction? Evidence from the Middle East and North Africa region

This study aims to investigate whether information and communication technologies (ICT) and renewable energy consumption can help improve environmental quality for a selected group of the Middle East and North Africa (MENA) region. By using the Panel Vector Autoregressive model over the period 1980-2019, the results show evidence for the first-order effects of ICTs on CO2 emissions, indicating that the use of ICT in the current economic development context of the MENA region lead to a deterioration of the environmental quality. The results also show that renewable energy consumption improves environmental quality whatever the sample and the proxy for ICT used. Overall, the results of the impulse responses functions (IRFs) show that the impact of shocks on ICT and renewable energy last between 1 and 7 years. The results of the IRFs are confirmed by the forecast error variance decomposition analysis, which shows that the contributions of ICT and renewable energy to the variability of CO2 emissions is not zero. Finally, in tests for causality, the results reveal evidence for bidirectional causality in most cases between CO2 emissions and ICT and renewable energy consumption. To benefit from the potential positive impact of ICT and renewable energy consumption on the quality of the environment, several ICT and renewable energy policies have been developed and discussed. 2021 The AuthorsThe first author would like to thank the financial support of QNRF under the grant number NPRP11C-1229-170007 from the Qatar National Research Fund (a member of Qatar foundation). The statements made herein are solely the responsibility of the author (s). Open Access funding provided by the Qatar National Library.Scopu

Blockchain-based Supply Chain Financing Solutions for Qatar

When it comes to trade, operations or expansion, access to finance from conventional sources such as financial institutions (FIs) can become a major hurdle for companies (International Chamber of Commerce [ICC], 2020). This is especially the case for firms that fall under the small, medium enterprise (SME) category due to either lacking financial strength or being relatively new to the market and therefore lacking credit history. Due to the smaller size of SMEs in comparison to larger corporate customers, FIs and banks alike do not seem to be addressing SME demand for more flexible financing options (Ash, 2018). According to a recent report by the Asian Development Bank, there exists a 1.5 trillion (US) dollar gap in terms of unmet trade financing requests worldwide (Asian Development Bank [ADB], 2017). Furthermore, the report adds that 74% of rejected trade finance requests come from SMEs and midcap firms. By 2025, the World Trade Organization (WTO) projects that the trade financing gap could increase to a whopping 2.5 trillion (US) dollars globally, further exacerbating the situation for SMEs in developing countries (MarcoPolo, 2020). This is also worsened by the recent COVID-19 pandemic.This white paper was made possible by NPRP Cluster grant # 11C-1229-170007 from the Qatar National Research Fund (a member of Qatar foundation). The opinions expressed and statements made in this paper are those of the authors(s) and are not intended to represent the positions or opinions of the Qatar Foundation or its members