Stationarity Level Research Articles

The impact of financial development and globalization on environmental quality: evidence from South Asian economies.

Climate change resulting from the higher concentration of greenhouse gases in the atmosphere is a threat to the sustainability of life on earth. To ensure sustainable development, the study analyzed the impact of financial development, globalization, and energy use on the environmental quality of South Asian economies over the period 1990-2014. To account for cross-sectional dependence, Breusch-Pagan-Lagrange multiplier, Pesaran-scaled Lagrange multiplier, bias-corrected-scaled Lagrange multiplier, and Pesaran cross-sectional dependence tests are used. The second-generation tests are used to determine the stationarity level of the variables. Furthermore, the Westerlund panel cointegration test confirms cointegration among the variables. For long-run association, fully modified ordinary least squares, dynamic ordinary least squares, and pooled mean group estimators are used. The results suggest that financial development contributes to carbon emissions, whereas globalization has the potential to control emissions. The study also used Dumitrescu and Hurlin's (2012) panel causality test to explore the causal relationship among the variables. Unidirectional causality is observed from economic growth, globalization, and financial development to environmental degradation and from emissions to energy use, respectively. As financial development deteriorates environmental quality, therefore, the government should monitor the disbursement of loans for research and development, green financing, and efficient production that reduce resource consumption and improves environmental quality. Financial development should not compromise environmental quality and endanger sustainability. Furthermore, South Asian countries should promote globalization to support the inflow of green technologies to enhance environmental quality.

DETERMINANTS OF THE INFLOW OF FOREIGN DIRECT INVESTMENT: EMPIRICAL EVIDENCE FROM PAKISTAN

This study aims to investigate empirically the various factors which affect the inflow of Foreign Direct Investment (FDI) in Pakistan over the period of 1980 to 2018 and used in this study are population, GDP per capita represent market size, energy consumption, inflation rate and financial development as explanatory variables. The Augmented Dickey Fuller and Philips Perron tests were used to check stationarity level of the data series; the Autoregressive Distributed Lag (ARDL) approach was employed. The empirical results show that GDP, Inflation, Energy and population growth have positive and significant effect on FDI, while the financial development have negative and significant effect on FDI. Findings of the study suggest that the government should make suitable policies to attract more FDI into Pakistan in order to improve economic growth and thereby society welfare.

AN ANALYSIS OF THE RELATIONSHIP BETWEEN THE QUALITY OF CORPORATE GOVERNMENT ACTIVITIES AND THE FINANCIAL PERFORMANCE BY PANEL DATA ANALYSIS UNDER CROSS-SECTIONAL DEPENDENCY: AN INVESTIGATION ON THE COMPANIES LISTED IN THE BORSA ISTANBUL CORPORATE GOVERNANCE INDEX

In this study, the effects of corporate governance ratings on financial performance are investigated. For this purpose, a sample that include the annual data of the 27 listed companies in the Borsa Istanbul’s Corporate Governance Index for the 2012-2018 a period are used. The existence of cross-sectional dependence among the firms included in the sample is analyzed by Breusch and Pagan (1980) LM test, Pesaran (2004) LM test, Pesaran (2004) CD test and Baltagi, Feng and Kao (2012) LMBC test. According to test results, the cross-sectional dependence between firms is determined. Stationarity level of the series is examined by CADF panel unit root test developed by Pesaran (2007). According to the findings of the test, all series are determined as stationary. The causality relationship between the series are examined by Dumitrescu and Hurlin (2012) method and the causality relations are found from the corporate governance rating of the firms to the operating profits. The coefficients in the econometric model are estimated using Westerlund (2007) OLSAdj method and it is determined that the annual operating profits will increase by 110.74 Million TL when corporate governance quality (ratings) of the firms increase by 1 unit.

Impact of Trade Openness and Human Capital on Economic Growth: A Comparative Investigation of Asian Countries

The aim of this study is to analyze the impact of trade openness and human capital on economic growth in 19 Asian countries from 1985 to 2017. We selected two geographically distributed regions (Western and Southern Asia) based on difference in their GDP per capita. We applied the unit root tests to examine the level of stationarity and found that all variables were integrated at first difference. Kao and Fisher cointegration tests were employed and the results revealed the presence of a long-run relationship. We applied fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models to check the magnitude of the long-run coefficients among trade openness, human capital and economic growth. To investigate the direction of causality, we used a Dumitrescu and Hurlin (DH) causality test. The results indicated that trade openness and human capital have a significant and positive relationship while labor force participation has a negative effect on economic growth in Southern Asia, and in the case of Western Asia, the impact is positive. Foreign direct investment (FDI) has a negative and significant impact on GDP per capita (GDPPC) in Western Asia while it is positive and significant in Southern Asia; Total population (TPOP) has a negative impact on GDPPC in both regions. Furthermore, human capital has a positive and significant impact on trade openness in both panels. Meanwhile, labor force participation (LFP) has a positive and significant impact on trade openness in Southern Asia and a negative impact in the case of Western Asia. Trade openness and economic growth have bidirectional causality in Western Asia and unidirectional causality in Southern Asia. It also shows that human capital and economic growth have unidirectional causality in both regions.

Do technology and structural changes favour environment in Malaysia: an ARDL-based evidence for environmental Kuznets curve

The current study is an effort to investigate the relationship between technological innovation, structural changes, and carbon dioxide emission (CO2) along with the energy use and economic growth in the context of environmental Kuznets curve (EKC) over a period from 1985 to 2016. The study adopted the Zivot Andrews unit root test to check for the level of stationarity of the study variables. Based on the stationarity level, the study adopted autoregressive distributed lag (ARDL) approach to cointegration to investigate the presence of long- and short-run associations, simultaneously. To confirm the outcome of the ARDL bounds test in the presence of structural breaks, the study further applied the Gregory Hansen test of cointegration. The results reveal that industry value added in Malaysia has no significant impact on CO2 emissions. The results further posit that improvement in technology can lead to a cleaner environment. Regardless of improvements in technology and insignificant pressure of industrial activities towards environment, the results are not in the favour of the EKC hypothesis neither under the conventional turning point formula nor under the new turning point formula. The results reveal that long-run CO2 emission is bidirectionally related to energy use, structural changes, and technological innovation. The short-run results indicate bidirectional causalities between energy consumption, structural change, and CO2 emissions. The study suggests that the government should overhaul the structure of the energy in Malaysia to overcome both the losses in the production process and to reduce carbon emissions by inspiring the induction of environment-friendly and efficient technologies in the production process and a shift towards more services sector economy. The outcomes of the study are according to the theory of ecological modernization.

Disorder indicator for nonstationary stochastic processes

The properties of a statistic called a self-consistent stationarity level of nonstationary time series are examined in this work. It is shown that a change in this statistic can be treated as a disorder in the nonstationarity properties of the series. The significance level of decision making is estimated, characteristic periods in a non-stationary stochastic process are detected, and an optimal sample size for constructing indicators in stochastic control problems is determined. A disorder indicator for electroencephalogram data from epilepsy patients is studied as a practical application.

Working Capital Financing and Corporate Profitability of Pakistan Manufacturing Firms: Evidence from FMCG, Cement & Chemical Sector

The aim of conducting research is to explore the dynamic relation of working capital financing with respect to profitability of the firm & for that purpose data has been gathered from three different sectors i.e. chemical, cement & FMCG. For analyzing the results panel least square method has been employed for which stationarity level of data series has been checked through panel unit root test & results shows data series were non-stationary on level 1 but it has been stationary on 1st difference. This study is also among very few of the researches which uses quadratic model and panel regression models to verify the results. Additionally, this study explore the working capital management effect on profitability along with liquidity and short-term obligation as a measure of working capital management through considering specifically manufacturing sector by using the fixed/random effect regression model, on which no previous research has been done. Finding indicate that there is an insignificant but negative relationship between Return on assets (ROA) and all the control variables of working capital except current assets and sales in pooled regression model and current assets & debt ratio in fixed/random effect model. In brief, study suggests that profitability of firm is not dependent on investment in working capital of chemical, cement and consumer sectors of Pakistan.

Slice sampler algorithm for generalized Pareto distribution

In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. Two simulation studies have shown the performance of the peaks over given threshold (POT) and GPD density function on various simulated data sets. The results were compared with another commonly used Markov chain Monte Carlo (MCMC) technique called Metropolis-Hastings algorithm. Based on the results, the slice sampler algorithm provides closer posterior mean values and shorter $95\%$ quantile based credible intervals compared to the Metropolis-Hastings algorithm. Moreover, the slice sampler algorithm presents a higher level of stationarity in terms of the scale and shape parameters compared with the Metropolis-Hastings algorithm. Finally, the slice sampler algorithm was employed to estimate the return and risk values of investment in Malaysian gold market.

Impact of WTO on Pakistan and Indian Economies

The present study revealed the impact of WTO on Pakistan and Indian economies. Yearly data were used from 1980 to 2010 for estimation. The main objective of this study was to measure the impact of WTO on economies of Pakistan and India. GDP, production of agriculture, production of industry, services, per capita income and FDI were used as dependent variables. Exchange rate, terms of trade and financial liberalization were used as the explanatory variables. Dummy variable was used for WTO. Augmented Dickey Fuller (ADF) test was applied to check the stationarity level of each variable included in the model. Johansen Cointegration Test was applied to find empirical results. Some policies were suggested on the base of empirical findings.

Markov chains and entropy tests in genetic-based lithofacies analysis of deep-water clastic depositional systems

AbstractThe aim of this study was to examine the relationship between structural elements and the so-called genetic lithofacies in a clastic deep-water depositional system. Process-sedimentology has recently been gaining importance in the characterization of these systems. This way the recognized facies attributes can be associated with the depositional processes establishing the genetic lithofacies. In this paper this approach was presented through a case study of a Tertiary deep-water sequence of the Pannonian-basin.Of course it was necessary to interpret the stratigraphy of the sequences in terms of “general” sedimentology, focusing on the structural elements. For this purpose, well-logs and standard deep-water models were applied.The cyclicity of sedimentary sequences can be easily revealed by using Markov chains. Though Markov chain analysis has broad application in mainly fluvial depositional environments, its utilization is uncommon in deep-water systems. In this context genetic lithofacies was determined and analysed by embedded Markov chains. The randomness in the presence of a lithofacies within a cycle was estimated by entropy tests (entropy after depositional, before depositional, for the whole system). Subsequently the relationships between lithofacies were revealed and a depositional model (i.e. modal cycle) was produced with 90% confidence level of stationarity. The non-randomness of the latter was tested by chi-square test.The consequences coming from the comparison of “general” sequences (composed of architectural elements), the genetic-based sequences (showing the distributions of the genetic lithofacies) and the lithofacies relationships were discussed in details. This way main depositional channel has the best, channelized lobes have good potential hydrocarbon reservoir attributes, with symmetric alternation of persistent fine-grained sandstone (Facies D) and muddy fine-grained sandstone with traction structures (Facies F)

Impact of Petroleum on SMEs Growth in Nigeria.

The study undertakes an empirical research on the impact of petroleum on small and medium scale enterprises (SMEs) development in Nigeria. The log linear error correction model was adopted to examine how petroleum price (PP), Imported petroleum (IMP) and domestically produced petroleum (DPP) had impacted on Nigeria’s SMEs. Unit root test was carried out on each of the variables to determine their level of stationarity. They were however found stationary after first difference (that is, they are all integrated of order one (I(1)), then it was safe to proceed with Johansen Cointegration Test. The integrated variables were then used for the regression analysis. The cointegration result showed that the variables used in the model have a long term, or equilibrium relationship between them. It was observed that from the analysis that PP and IMP were found to be statistically insignificant and both had negative relationships with SMEs development Nigeria, while DPP had a positive impact and is statistically significant. Due to the underproduction of the Nigerian petroleum refineries, the government had to resort to importation of the shortfall which also has its cost implications on its sales and distribution. Local manufacturers and farmers had to pay more for transporting their goods and services to the markets. Incessant price hikes of petroleum products have led to crisis and industrial actions led by some pressure groups in Nigeria which has caused distortion in the SMEs activities of Nigeria overtime The study thus recommends that the down-stream oil need to be deregulated to allow private investors come in to build in more refineries so as to produce the petroleum at a relatively lower cost to propel the growth of SMEs in the country.

Impact of Petroleum on Smes Growth in Nigeria

ABSTRACT The study undertakes an empirical research on the impact of petroleum on small and medium scale enterprises (SMEs) development in Nigeria. The log linear error correction model was adopted to examine how petroleum price (PP), Imported petroleum (IMP) and domestically produced petroleum (DPP) had impacted on Nigeria’s SMEs. Unit root test was carried out on each of the variables to determine their level of stationarity. They were however found stationary after first difference (that is, they are all integrated of order one (I(1)), then it was safe to proceed with Johansen Cointegration Test. The integrated variables were then used for the regression analysis. The cointegration result showed that the variables used in the model have a long term, or equilibrium relationship between them. It was observed that from the analysis that PP and IMP were found to be statistically insignificant and both had negative relationships with SMEs development Nigeria, while DPP had a positive impact and is statistically significant. Due to the underproduction of the Nigerian petroleum refineries, the government had to resort to importation of the shortfall which also has its cost implications on its sales and distribution. Local manufacturers and farmers had to pay more for transporting their goods and services to the markets. Incessant price hikes of petroleum products have led to crisis and industrial actions led by some pressure groups in Nigeria which has caused distortion in the SMEs activities of Nigeria overtime The study thus recommends that the down-stream oil need to be deregulated to allow private investors come in to build in more refineries so as to produce the petroleum at a relatively lower cost to propel the growth of SMEs in the country.

Entropy-based multichannel measure of stationarity for characterization of motor imagery patterns.

We propose a novel approach for measuring the stationarity level of multichannel time-series. This measure is based on stationarity definition over time-varying spectra and aims to quantify the relationship between local (single-channel dynamics) and global (multichannel dynamics) stationarity. With the purpose of separate among several motor/imagery tasks, we asssume that movement imagination implies an increase on the EEG variability, consequently, as discriminant features, we first compute the non-stationary components of input signals, and we further obtain its stationary level throughout the proposed measure. To assess the separability level of the proposed features, we employ the t-student test. Obtained results evidence that our measure is able to accurately detect brain areas projected on the scalp where motor tasks are performed.

Detrending moving-average cross-correlation coefficient: Measuring cross-correlations between non-stationary series

In the paper, we introduce a new measure of correlation between possibly non-stationary series. As the measure is based on the detrending moving-average cross-correlation analysis (DMCA), we label it as the DMCA coefficient ρDMCA(λ) with a moving average window length λ. We analytically show that the coefficient ranges between −1 and 1 as a standard correlation does. In the simulation study, we show that the values of ρDMCA(λ) very well correspond to the true correlation between the analyzed series regardless the (non-)stationarity level. Dependence of the newly proposed measure on other parameters–correlation level, moving average window length and time series length–is discussed as well.

Impact of Trade Liberalization and Corruption on Environmental Degradation in Pakistan

The present study revealed the impact of trade liberalization and corruption on environmental degradation. Yearly data were used from 1980 to 2011 for estimation. Air and water pollution were used as the environmental indicators. First model confirmed the evidence of the EKC. Trade liberalization and corruption index were used as the explanatory variables. Income per capita, square of income per capita, industrial value added, secondary school enrollment, law and order index and fertilizer use were used as control variables. Augmented Dickey Fuller (ADF) test was applied to check the stationarity level of each variable included in the model. Autoregressive Distributed Lag (ARDL) was applied to find empirical results. Some policies were suggested on the base of empirical findings.

Performance of an ensemble of ordinary, universal, non-stationary and limit Kriging predictors

The selection of stationary or non-stationary Kriging to create a surrogate model of a black box function requires apriori knowledge of the nature of response of the function as these techniques are better at representing some types of responses than others. While an adaptive technique has been previously proposed to adjust the level of stationarity within the surrogate model such a model can be prohibitively expensive to construct for high dimensional problems. An alternative approach is to employ a surrogate model constructed from an ensemble of stationary and non-stationary Kriging models. The following paper assesses the accuracy and optimization performance of such a modelling strategy using a number of analytical functions and engineering design problems.

Modified frequency domain kurtosis for signal processing

An operator sensitive to signal probability distribution is obtained, by integrating ideas from higher-order statistics and a frequency approach to signal processing. This function, based on a modified frequency domain kurtosis, assigns a level of stationarity to each signal spectrum component and enhances unsteady components over stationary sinusoids embedded in noise.