This manuscript has been published under the terms of Creative Commons Attribution 4.0 Internatio... more This manuscript has been published under the terms of Creative Commons Attribution 4.0 International License (CC-BY). JQM under this license lets others distribute, remix, tweak, and build upon the work it publishes, even commercially, as long as the authors of the original work are credited for the original creation and the contributions are distributed under the same license as original.
This study aims to analyze the ways women are empowered through Information and Communication Tec... more This study aims to analyze the ways women are empowered through Information and Communication Technology (ICT) and fostering the process of achieving the Sustainable Development Goals (SDGs). Women in developing countries face economic and social hurdles and have limited access to ICT, which transforms into their lack of skills, lower literacy rate, and limited social engagement. Therefore, this study explores the role of ICT on women empowerment in 51 developing countries by conducting panel data modeling throughout 2000-17. The study finds that ICT has a positive contribution to the female labor force participation rate by applying the Generalized Method of Moment (GMM). Control variables like GDP growth and government expenditure on education have a positive and statistically significant role in enhancing women's empowerment. The findings of this study explain that the ICT impacts women's empowerment and returns, beneficial for fostering the process of achieving SDGs 2030.
This study investigates the determinants of food insecurity for both general and farmer household... more This study investigates the determinants of food insecurity for both general and farmer households. It is based on Pakistan Social and Living standard Measurement (PSLM) 2007-08 survey conducted by the Federal Bureau of Statistics, Pakistan. After having descriptive analysis of the important determinants of food insecurity, we have used logit model to find the probability for being household secure or insecure. The model is initially fitted with 16 (for general) and 19 (for farmer households) variables, selected from factors identified by previous researchers that affect food insecurity. Twelve out of 19 variables for farmer households are found to be significant such as household size, household size square, household income, number of rooms, dependency ratio, electricity connection, irrigation facility, age and age square of household head. To our surprise female education variable is insignificant for general household model. The results obtained are further analyzed to compute partial effects on continuous variables and change in the probabilities on discrete variables for the significant factors in the logistic models. Household size, education of household head, annual income and agricultural income are some of the most important factors influencing the household's food insecurity status.
Accomplishing Sustainable Development Goals (SDGs) an innovative global agenda of inclusive devel... more Accomplishing Sustainable Development Goals (SDGs) an innovative global agenda of inclusive development, how much progress has been made in some areas and how large an effort is needed to meet the SDGs is the main spirit. This collective journey has at its heart a promise to "leave no one behind". If current trends persist and the cost of missing this opportunity is losing millions of lives that could have been saved. Are we likely to have enough and proper data to conduct an assessment in a meaningful way? To answer this question, we need to evaluate the current state of progress towards each SDG. To take stock of progress at the national and provincial level, SDG Index is incorporated and ranked to evaluate the best and worst performers. Furthermore, they are analyzed against each SDG and highlights from acute to mild challenges. The resulting SDG scorecard depicts that through business as usual, it is hard to achieve SDGs for Pakistan by 2030. Baluchistan rural is at the bottom while Urban Punjab and Urban KP are have done reasonably well though these regions are also behind the target. There is need to do a lot in the domain of health, education, poverty, water and sanitation and no hunger for all regions. The SDG heatmap makes clear that every province faces major challenges in health, education and gender equality that needs to cope with. A call to governments and stakeholders to recognize the gaps that have been identified in implementation, financing and political will to fulfil this vision and keep this promise. SDG Index can draw attention to the SDGs and their role as a tool for guiding national policies and long-term strategies for inclusive development.
In this article our objective is to evaluate the performance of different measures of association... more In this article our objective is to evaluate the performance of different measures of associations for hypothesis testing purposes. We have considered different measures of association (including some commonly used) in this study, one of which is parametric and others are non-parametric including three proposed modifications. Performance of these tests are compared under different symmetric, skewed and contaminated probability distributions that include Normal, Cauchy, Uniform, Laplace, Lognormal, Exponential, Weibull, Gamma, t, Chi-square, Half Normal, Mixed Weibull and Mixed Normal. Performances of these tests are measured in terms of power. We have suggested appropriate tests which may perform better under different situations based on their efficiency grading(s). It is expected that researchers will find these results useful in decision making.
This study attempts to estimate the rate of inflation in Pakistan by a stochastic approach to ind... more This study attempts to estimate the rate of inflation in Pakistan by a stochastic approach to index numbers which provides not only point estimate but also confidence interval for inflation estimate. There are two approaches to index number theory namely: the functional economic approach and the stochastic approach. The attraction of stochastic approach is that it estimates the rate of inflation in which uncertainty and statistical ideas play a major roll of screening index numbers. We have used extended stochastic approach to index numbers for measuring the Pakistan inflation by allowing for the systematic changes in the relative prices. We use CPI data covering the period July 2001-march 2008.
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2017
This paper give an insight on effect of education and socio economic factors on education on earn... more This paper give an insight on effect of education and socio economic factors on education on earning for Pakistan using data mining technique Regression tree and classification tree (CART). Labor force survey data used in this paper. Variables used as predictors in the study are Education, Gender, Status, Training, and Occupation, Location of working, Training, Experience, Age and Type of industry, where monthly income is used as an independent variable. In case of classification income is divided in Quintiles, which is used as a dependent variable for classification variable. Type of industry, education, age and occupation are found significant variables in both classification and regression tree. Regression trees shows that instead of education type of industry is the most important variable and sex and education are the least important variables. Classification tree also shows that Type of industry is the most significant variable which effects the earning of an individual, then age and occupation of an individual come and education is the least important variable where the rest of predictors play no role in earning of an individual.
The present study explores the impact of tax policy on economic growth using average marginal tax... more The present study explores the impact of tax policy on economic growth using average marginal tax rate and average tax rate for South Asian countries. The data for five developing countries: India, Maldives, Nepal, Pakistan, Sri-Lanka is used for the period of 1991-2010. This study uses Additive Mixed Models with penalized spline methodology. In this study we have constructed the average marginal tax rates using methodology of Seater (1982). It further identifies that the variables like average marginal tax rate (AMTRs), average tax rate (ATR), population growth rate, trade-openness, investment, human capital and real per capita GDP are the significant determinants of economic growth in the sample countries. On average, AMTRs and population growth rate reduce the performance of economic growth in the developing countries. The main findings further suggest that nonlinear effects are exerted by tax policy on economic growth. The increase in average marginal tax rate at the lower level...
The Singh-Maddala distribution is very popular to analyze the data on income, expenditure, actuar... more The Singh-Maddala distribution is very popular to analyze the data on income, expenditure, actuarial, environmental, and reliability related studies. To enhance its scope and application, we propose four parameters transmutedSingh-Maddala distribution, in this study. The proposed distribution is relatively more flexible than the parent distribution to model a variety of data sets. Its basic statistical properties, reliability function, and behaviors of the hazard function are derived. The hazard function showed the decreasing and an upside-down bathtub shape that is required in various survival analysis. The order statistics and generalized TL-moments with their special cases such as L-, TL-, LL-, and LH-moments are also explored. Furthermore, the maximum likelihood estimation is used to estimate the unknown parameters of the transmuted Singh-Maddala distribution. The real data sets are considered to illustrate the utility and potential of the proposed model. The results indicate th...
Due to complexities in measuring the impact of tax policy on economic growth, there is need to ex... more Due to complexities in measuring the impact of tax policy on economic growth, there is need to explore functional relationship between response and predictors. Semi-parametric approaches are often very handy in modeling relationships which are non-linear but cant be completely described either through parametric or non-parametric approaches. To determine the effects of tax policy on economic growthfunctional, cubic smoothing spline method is used along with cross validation test to control the smoothing parameter. To replace the functional form of smoothing coefficients into linear mixed model, maximum likelihood estimation is used. Results indicate that proposed methodology is robust in determining functional form and in achieving increasing average marginal tax rates has negative impact on economic growth results. Empirical results indicate that high AMTRs and population growth rate reduce the performance of economic growth in the developing countries. A reduction on dependence of...
In this paper, we develop a generator to propose new continuous lifetime distributions. Thanks to... more In this paper, we develop a generator to propose new continuous lifetime distributions. Thanks to a simple transformation involving one additional parameter, every existing lifetime distribution can be rendered more flexible with our construction. We derive stochastic properties of our models, and explain how to estimate their parameters by means of maximum likelihood for complete and censored data, where we focus, in particular, on Type-II, Type-I and random censoring. A Monte Carlo simulation study reveals that the estimators are consistent. To emphasize the suitability of the proposed generator in practice, the two-parameter Fré chet distribution is taken as baseline distribution. Three real life applications are carried out to check the suitability of our new approach, and it is shown that our extension of the Fré chet distribution outperforms existing extensions available in the literature.
In this article we have evaluated the performance of different forecasters and tested association... more In this article we have evaluated the performance of different forecasters and tested association between their performances for different pairs of variables. We have used three data sets of track records of professional U.S. economic forecasters participating in the Blue Chip consensus forecasting service (the data sets contain the root mean square errors (RMSE) of different forecasters for different years). To evaluate the performance of forecasters we have covered three well known tests, namely the usual F test (cf. Fisher (1923)), Kruskal Wallis test (cf. Kruskal and Wallis (1952)) and Extension of Median test (cf. Daniel (1990)). To test the association between the forecaster's performances for different pairs of variables we have considered Gini mean correlation coefficient 1 g r (cf. Yitzhaki, S., and Olkin, I. (1991) and Yitzhaki (2003)), Modified rank correlation coefficient (cf. Zimmerman (1994)) and three modifications of Spearman rank correlation coefficient. We have observed that different forecasters don't necessarily offer same average performance. Moreover, an evidence of association between two criteria does not always lead us reaching at the same decision. The outcomes of the study may help the practitioners in selecting the best forecaster(s) for policy making purposes.
Communications in Statistics - Simulation and Computation, 2019
Classification of High-dimensional data, such as gene expression data having far more variables (... more Classification of High-dimensional data, such as gene expression data having far more variables (genes) than observations, is challenging. Classifiers aggregation known as ensemble method has proven improved classification accuracy in a wide range of applications. In this study, we propose an Ensemble of Penalized Logistic models (EPL) which utilizes Ridge regression, Lasso and Elastic net as base learners for ensemble generation. Classification is done on the basis of majority votes of the models. The EPL is assessed on both simulated data and bench mark microarray data sets. Its performance in terms of classification accuracy is compared with state-of-the-art classifiers, i.e., Support Vector Machines (SVM), K-Nearest Neighbors (KNN) and Random Forest (RF). The experimental comparisons show that the EPL has high classification accuracy as compared to the other classifiers considered here.
Communications in Statistics - Simulation and Computation, 2016
This study aims at exploring correct identification of seasonal outliers using most commonly appl... more This study aims at exploring correct identification of seasonal outliers using most commonly applied test statistics. We evaluate the performance of seasonal level shift (SLS) by means of empirical level of significance, power of the test for sensitivity in detecting changes and the vulnerability to masking of outliers by misspecification frequencies. We observe that the size of SLS affects the sampling distribution of (test statistics for SLS detection) in case of SAR (1) and SMA (1) model. The empirical critical values for 1%, 5% and 10% upper percentiles are higher than the usual cut off points and the empirical level of significance is inversely related to sample size and the model coefficients. The empirical power of the test statistics is not satisfactory at small sample size, and for large model coefficient. gets confused with IO. The potential list of types of outliers should retain both IO and SLS as a part of outlier detection procedure for most efficient results. We apply the method suggested by Kaiser and Maravall (2001) with five possible types of outliers i.e. AO, IO, LS, TC and SLS, to a number of quarterly and monthly time series data from Pakistan.
Communications in Statistics - Simulation and Computation, 2015
ABSTRACT Outlier detection has always been of interest for researchers and data miners. It has be... more ABSTRACT Outlier detection has always been of interest for researchers and data miners. It has been well researched in different knowledge and application domains. This study aims at exploring the correctly identifying outliers using most commonly applied statistics. We evaluate the performance of AO, IO, LS, and TC as vulnerability to spurious outliers by means of empirical level of significance (ELS), power of the test indicating the sensitivity of the statistical tests in detecting changes and the vulnerability to masking of outliers in terms of misspecification frequencies are determined. We have observed that the sampling distribution of test statistic ηtp; tp = AO, IO, LS, TC in case of AR(1) model is connected with the values of n and φ. The sampling distribution of ηTC is less concentrated than the sampling distribution of ηAO, ηIO, and ηLS. In AR(1) process, empirical critical values for 1%, 5%, and 10% upper percentiles are found to be higher than those generally used. We have also found the evidence that the test statistics for transient change (TC) needs to be revisited as the test statistics ηTC is found to be eclipsed by ηAO, ηLS and ηIO at different δ values. TC keeps on confusing with IO and AO, and at extreme δ values it just gets equal to AO and LS.
This manuscript has been published under the terms of Creative Commons Attribution 4.0 Internatio... more This manuscript has been published under the terms of Creative Commons Attribution 4.0 International License (CC-BY). JQM under this license lets others distribute, remix, tweak, and build upon the work it publishes, even commercially, as long as the authors of the original work are credited for the original creation and the contributions are distributed under the same license as original.
This study aims to analyze the ways women are empowered through Information and Communication Tec... more This study aims to analyze the ways women are empowered through Information and Communication Technology (ICT) and fostering the process of achieving the Sustainable Development Goals (SDGs). Women in developing countries face economic and social hurdles and have limited access to ICT, which transforms into their lack of skills, lower literacy rate, and limited social engagement. Therefore, this study explores the role of ICT on women empowerment in 51 developing countries by conducting panel data modeling throughout 2000-17. The study finds that ICT has a positive contribution to the female labor force participation rate by applying the Generalized Method of Moment (GMM). Control variables like GDP growth and government expenditure on education have a positive and statistically significant role in enhancing women's empowerment. The findings of this study explain that the ICT impacts women's empowerment and returns, beneficial for fostering the process of achieving SDGs 2030.
This study investigates the determinants of food insecurity for both general and farmer household... more This study investigates the determinants of food insecurity for both general and farmer households. It is based on Pakistan Social and Living standard Measurement (PSLM) 2007-08 survey conducted by the Federal Bureau of Statistics, Pakistan. After having descriptive analysis of the important determinants of food insecurity, we have used logit model to find the probability for being household secure or insecure. The model is initially fitted with 16 (for general) and 19 (for farmer households) variables, selected from factors identified by previous researchers that affect food insecurity. Twelve out of 19 variables for farmer households are found to be significant such as household size, household size square, household income, number of rooms, dependency ratio, electricity connection, irrigation facility, age and age square of household head. To our surprise female education variable is insignificant for general household model. The results obtained are further analyzed to compute partial effects on continuous variables and change in the probabilities on discrete variables for the significant factors in the logistic models. Household size, education of household head, annual income and agricultural income are some of the most important factors influencing the household's food insecurity status.
Accomplishing Sustainable Development Goals (SDGs) an innovative global agenda of inclusive devel... more Accomplishing Sustainable Development Goals (SDGs) an innovative global agenda of inclusive development, how much progress has been made in some areas and how large an effort is needed to meet the SDGs is the main spirit. This collective journey has at its heart a promise to "leave no one behind". If current trends persist and the cost of missing this opportunity is losing millions of lives that could have been saved. Are we likely to have enough and proper data to conduct an assessment in a meaningful way? To answer this question, we need to evaluate the current state of progress towards each SDG. To take stock of progress at the national and provincial level, SDG Index is incorporated and ranked to evaluate the best and worst performers. Furthermore, they are analyzed against each SDG and highlights from acute to mild challenges. The resulting SDG scorecard depicts that through business as usual, it is hard to achieve SDGs for Pakistan by 2030. Baluchistan rural is at the bottom while Urban Punjab and Urban KP are have done reasonably well though these regions are also behind the target. There is need to do a lot in the domain of health, education, poverty, water and sanitation and no hunger for all regions. The SDG heatmap makes clear that every province faces major challenges in health, education and gender equality that needs to cope with. A call to governments and stakeholders to recognize the gaps that have been identified in implementation, financing and political will to fulfil this vision and keep this promise. SDG Index can draw attention to the SDGs and their role as a tool for guiding national policies and long-term strategies for inclusive development.
In this article our objective is to evaluate the performance of different measures of association... more In this article our objective is to evaluate the performance of different measures of associations for hypothesis testing purposes. We have considered different measures of association (including some commonly used) in this study, one of which is parametric and others are non-parametric including three proposed modifications. Performance of these tests are compared under different symmetric, skewed and contaminated probability distributions that include Normal, Cauchy, Uniform, Laplace, Lognormal, Exponential, Weibull, Gamma, t, Chi-square, Half Normal, Mixed Weibull and Mixed Normal. Performances of these tests are measured in terms of power. We have suggested appropriate tests which may perform better under different situations based on their efficiency grading(s). It is expected that researchers will find these results useful in decision making.
This study attempts to estimate the rate of inflation in Pakistan by a stochastic approach to ind... more This study attempts to estimate the rate of inflation in Pakistan by a stochastic approach to index numbers which provides not only point estimate but also confidence interval for inflation estimate. There are two approaches to index number theory namely: the functional economic approach and the stochastic approach. The attraction of stochastic approach is that it estimates the rate of inflation in which uncertainty and statistical ideas play a major roll of screening index numbers. We have used extended stochastic approach to index numbers for measuring the Pakistan inflation by allowing for the systematic changes in the relative prices. We use CPI data covering the period July 2001-march 2008.
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2017
This paper give an insight on effect of education and socio economic factors on education on earn... more This paper give an insight on effect of education and socio economic factors on education on earning for Pakistan using data mining technique Regression tree and classification tree (CART). Labor force survey data used in this paper. Variables used as predictors in the study are Education, Gender, Status, Training, and Occupation, Location of working, Training, Experience, Age and Type of industry, where monthly income is used as an independent variable. In case of classification income is divided in Quintiles, which is used as a dependent variable for classification variable. Type of industry, education, age and occupation are found significant variables in both classification and regression tree. Regression trees shows that instead of education type of industry is the most important variable and sex and education are the least important variables. Classification tree also shows that Type of industry is the most significant variable which effects the earning of an individual, then age and occupation of an individual come and education is the least important variable where the rest of predictors play no role in earning of an individual.
The present study explores the impact of tax policy on economic growth using average marginal tax... more The present study explores the impact of tax policy on economic growth using average marginal tax rate and average tax rate for South Asian countries. The data for five developing countries: India, Maldives, Nepal, Pakistan, Sri-Lanka is used for the period of 1991-2010. This study uses Additive Mixed Models with penalized spline methodology. In this study we have constructed the average marginal tax rates using methodology of Seater (1982). It further identifies that the variables like average marginal tax rate (AMTRs), average tax rate (ATR), population growth rate, trade-openness, investment, human capital and real per capita GDP are the significant determinants of economic growth in the sample countries. On average, AMTRs and population growth rate reduce the performance of economic growth in the developing countries. The main findings further suggest that nonlinear effects are exerted by tax policy on economic growth. The increase in average marginal tax rate at the lower level...
The Singh-Maddala distribution is very popular to analyze the data on income, expenditure, actuar... more The Singh-Maddala distribution is very popular to analyze the data on income, expenditure, actuarial, environmental, and reliability related studies. To enhance its scope and application, we propose four parameters transmutedSingh-Maddala distribution, in this study. The proposed distribution is relatively more flexible than the parent distribution to model a variety of data sets. Its basic statistical properties, reliability function, and behaviors of the hazard function are derived. The hazard function showed the decreasing and an upside-down bathtub shape that is required in various survival analysis. The order statistics and generalized TL-moments with their special cases such as L-, TL-, LL-, and LH-moments are also explored. Furthermore, the maximum likelihood estimation is used to estimate the unknown parameters of the transmuted Singh-Maddala distribution. The real data sets are considered to illustrate the utility and potential of the proposed model. The results indicate th...
Due to complexities in measuring the impact of tax policy on economic growth, there is need to ex... more Due to complexities in measuring the impact of tax policy on economic growth, there is need to explore functional relationship between response and predictors. Semi-parametric approaches are often very handy in modeling relationships which are non-linear but cant be completely described either through parametric or non-parametric approaches. To determine the effects of tax policy on economic growthfunctional, cubic smoothing spline method is used along with cross validation test to control the smoothing parameter. To replace the functional form of smoothing coefficients into linear mixed model, maximum likelihood estimation is used. Results indicate that proposed methodology is robust in determining functional form and in achieving increasing average marginal tax rates has negative impact on economic growth results. Empirical results indicate that high AMTRs and population growth rate reduce the performance of economic growth in the developing countries. A reduction on dependence of...
In this paper, we develop a generator to propose new continuous lifetime distributions. Thanks to... more In this paper, we develop a generator to propose new continuous lifetime distributions. Thanks to a simple transformation involving one additional parameter, every existing lifetime distribution can be rendered more flexible with our construction. We derive stochastic properties of our models, and explain how to estimate their parameters by means of maximum likelihood for complete and censored data, where we focus, in particular, on Type-II, Type-I and random censoring. A Monte Carlo simulation study reveals that the estimators are consistent. To emphasize the suitability of the proposed generator in practice, the two-parameter Fré chet distribution is taken as baseline distribution. Three real life applications are carried out to check the suitability of our new approach, and it is shown that our extension of the Fré chet distribution outperforms existing extensions available in the literature.
In this article we have evaluated the performance of different forecasters and tested association... more In this article we have evaluated the performance of different forecasters and tested association between their performances for different pairs of variables. We have used three data sets of track records of professional U.S. economic forecasters participating in the Blue Chip consensus forecasting service (the data sets contain the root mean square errors (RMSE) of different forecasters for different years). To evaluate the performance of forecasters we have covered three well known tests, namely the usual F test (cf. Fisher (1923)), Kruskal Wallis test (cf. Kruskal and Wallis (1952)) and Extension of Median test (cf. Daniel (1990)). To test the association between the forecaster's performances for different pairs of variables we have considered Gini mean correlation coefficient 1 g r (cf. Yitzhaki, S., and Olkin, I. (1991) and Yitzhaki (2003)), Modified rank correlation coefficient (cf. Zimmerman (1994)) and three modifications of Spearman rank correlation coefficient. We have observed that different forecasters don't necessarily offer same average performance. Moreover, an evidence of association between two criteria does not always lead us reaching at the same decision. The outcomes of the study may help the practitioners in selecting the best forecaster(s) for policy making purposes.
Communications in Statistics - Simulation and Computation, 2019
Classification of High-dimensional data, such as gene expression data having far more variables (... more Classification of High-dimensional data, such as gene expression data having far more variables (genes) than observations, is challenging. Classifiers aggregation known as ensemble method has proven improved classification accuracy in a wide range of applications. In this study, we propose an Ensemble of Penalized Logistic models (EPL) which utilizes Ridge regression, Lasso and Elastic net as base learners for ensemble generation. Classification is done on the basis of majority votes of the models. The EPL is assessed on both simulated data and bench mark microarray data sets. Its performance in terms of classification accuracy is compared with state-of-the-art classifiers, i.e., Support Vector Machines (SVM), K-Nearest Neighbors (KNN) and Random Forest (RF). The experimental comparisons show that the EPL has high classification accuracy as compared to the other classifiers considered here.
Communications in Statistics - Simulation and Computation, 2016
This study aims at exploring correct identification of seasonal outliers using most commonly appl... more This study aims at exploring correct identification of seasonal outliers using most commonly applied test statistics. We evaluate the performance of seasonal level shift (SLS) by means of empirical level of significance, power of the test for sensitivity in detecting changes and the vulnerability to masking of outliers by misspecification frequencies. We observe that the size of SLS affects the sampling distribution of (test statistics for SLS detection) in case of SAR (1) and SMA (1) model. The empirical critical values for 1%, 5% and 10% upper percentiles are higher than the usual cut off points and the empirical level of significance is inversely related to sample size and the model coefficients. The empirical power of the test statistics is not satisfactory at small sample size, and for large model coefficient. gets confused with IO. The potential list of types of outliers should retain both IO and SLS as a part of outlier detection procedure for most efficient results. We apply the method suggested by Kaiser and Maravall (2001) with five possible types of outliers i.e. AO, IO, LS, TC and SLS, to a number of quarterly and monthly time series data from Pakistan.
Communications in Statistics - Simulation and Computation, 2015
ABSTRACT Outlier detection has always been of interest for researchers and data miners. It has be... more ABSTRACT Outlier detection has always been of interest for researchers and data miners. It has been well researched in different knowledge and application domains. This study aims at exploring the correctly identifying outliers using most commonly applied statistics. We evaluate the performance of AO, IO, LS, and TC as vulnerability to spurious outliers by means of empirical level of significance (ELS), power of the test indicating the sensitivity of the statistical tests in detecting changes and the vulnerability to masking of outliers in terms of misspecification frequencies are determined. We have observed that the sampling distribution of test statistic ηtp; tp = AO, IO, LS, TC in case of AR(1) model is connected with the values of n and φ. The sampling distribution of ηTC is less concentrated than the sampling distribution of ηAO, ηIO, and ηLS. In AR(1) process, empirical critical values for 1%, 5%, and 10% upper percentiles are found to be higher than those generally used. We have also found the evidence that the test statistics for transient change (TC) needs to be revisited as the test statistics ηTC is found to be eclipsed by ηAO, ηLS and ηIO at different δ values. TC keeps on confusing with IO and AO, and at extreme δ values it just gets equal to AO and LS.
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