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Islam, M.Qamarul

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https://hdl.handle.net/20.500.12416/8997
Name Variants
Islam, M. Qamarul
Islam, MQ
Job Title
Prof. Dr.
Email Address
Main Affiliation
İktisadi ve İdari Birimler Fakültesi
Status
Former Staff
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Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

11

SUSTAINABLE CITIES AND COMMUNITIES
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0

Research Products

3

GOOD HEALTH AND WELL-BEING
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0

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9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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3

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6

CLEAN WATER AND SANITATION
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0

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14

LIFE BELOW WATER
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0

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12

RESPONSIBLE CONSUMPTION AND PRODUCTION
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0

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8

DECENT WORK AND ECONOMIC GROWTH
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3

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1

NO POVERTY
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0

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4

QUALITY EDUCATION
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5

GENDER EQUALITY
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10

REDUCED INEQUALITIES
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3

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16

PEACE, JUSTICE AND STRONG INSTITUTIONS
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15

LIFE ON LAND
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7

AFFORDABLE AND CLEAN ENERGY
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13

CLIMATE ACTION
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17

PARTNERSHIPS FOR THE GOALS
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2

ZERO HUNGER
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1

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This researcher does not have a Scopus ID.
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Scholarly Output

19

Articles

19

Views / Downloads

1324/295

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

208

Scopus Citation Count

225

WoS h-index

7

Scopus h-index

7

Patents

0

Projects

0

WoS Citations per Publication

10.95

Scopus Citations per Publication

11.84

Open Access Source

5

Supervised Theses

0

JournalCount
Communications in Statistics - Theory and Methods4
Economic Research-Ekonomska Istraživanja2
Journal of Applied Statistics2
International Statistical Review1
Journal of Business Economics and Finance1
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Now showing 1 - 10 of 19
  • Thumbnail Image
    Article
    Citation - WoS: 18
    Citation - Scopus: 18
    Estimation in Bivariate Nonnormal Distributions With Stochastic Variance Functions
    (Elsevier Science Bv, 2008) Tiku, Moti L.; Islam, M. Qamarul; Sazak, Hakan S.
    Data sets in numerous areas of application can be modelled by symmetric bivariate nonnormal distributions. Estimation of parameters in such situations is considered when the mean and variance of one variable is a linear and a positive function of the other variable. This is typically true of bivariate t distribution. The resulting estimators are found to be remarkably efficient. Hypothesis testing procedures are developed and shown to be robust and powerful. Real life examples are given. (C) 2007 Elsevier B.V. All rights reserved.
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    Article
    Citation - WoS: 4
    Citation - Scopus: 6
    Mahalanobis Distance Under Non-Normality
    (Taylor & Francis Ltd, 2010) Tiku, Moti L.; Islam, M. Qamarul; Qumsiyeh, Sahar B.
    We give a novel estimator of Mahalanobis distance D2 between two non-normal populations. We show that it is enormously more efficient and robust than the traditional estimator based on least squares estimators. We give a test statistic for testing that D2=0 and study its power and robustness properties.
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    Article
    Nonnormal Regression.I. Skew Distributions
    (2001) Islam, M. Qamarul; L. Tiku, Moti; Yildirim, F.
    In a linear regression model of the typey¼ Xþe, it is oftenassumed that the random erroreis normally distributed. Innumerous situations, e.g., whenymeasures life times or reac-tion times,etypically has a skew distribution. We considertwo important families of skew distributions, (a) Weibull withsupport IR:ð0,1Þon the real line, and (b) generalised logisticwit hsupport IR:ð 1,1Þ. Since the maximum likelihoodestimators are intractable in these situations, we derivemodified likelihood estimators which have explicit algebraicforms and are, therefore, easy to compute. We show that theseestimators are remarkably efficient, and robust. We develophypothesis testing procedures and give a real life example
  • Thumbnail Image
    Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Model Selection Uncertainties and Model Averaging in Autoregressive Time Series Models
    (Isoss Publ, 2012) Islam, M. Qamarul; Yazıcı, Mehmet; Yazici, Mehmet; Islam, M.Qamarul; Qamarul Islam, M.; İktisat
    Selecting the correct lag order is necessary in order to avoid model specification errors in autoregressive (AR) time series models. Here we explore the problem of lag order selection in such models. This study provides an in-depth but easy understanding of the model selection mechanism to the practitioners in various fields of applied research. Several interesting findings are reported and through these the pitfalls of the model selection procedures are exposed. In particular, we show that the whole exercise of model selection and subsequent statistical inference invariably depends upon unknown entities, namely the true values of parameters in the model. The model averaging technique is proposed as an alternative to the common practice of model selection and it is shown that, as a result, the properties of post-model-selection estimates substantially improve.
  • Thumbnail Image
    Article
    Citation - WoS: 4
    Citation - Scopus: 4
    Estimation in Multivariate Nonnormal Distributions With Stochastic Variance Function
    (Elsevier Science Bv, 2014) Islam, M. Qamarul; Qamarul Islam, M.
    In this paper the problem of estimation of location and scatter of multivariate nonnormal distributions is considered. Estimators are derived under a maximum likelihood setup by expressing the non-linear likelihood equations in the linear form. The resulting estimators are analytical expressions in terms of sample values and, hence, are easily computable and can also be manipulated analytically. These estimators are found to be remarkably more efficient and robust as compared to the least square estimators. They also provide more powerful tests in testing various relevant statistical hypotheses. (C) 2013 Elsevier B.V. All rights reserved.
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    Article
    Citation - WoS: 20
    Citation - Scopus: 22
    Regression Analysis With a Dtochastic Design Variable
    (Wiley, 2006) Sazak, HS; Tiku, ML; Islam, MQ
    In regression models, the design variable has primarily been treated as a nonstochastic variable. In numerous situations, however, the design variable is stochastic. The estimation and hypothesis testing problems in such situations are considered. Real life examples are given.
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    Article
    Citation - WoS: 4
    Citation - Scopus: 4
    Inference in Multivariate Linear Regression Models With Elliptically Distributed Errors
    (Taylor & Francis Ltd, 2014) Yazici, Mehmet; Islam, M. Qamarul; Yildirim, Fetih
    In this study we investigate the problem of estimation and testing of hypotheses in multivariate linear regression models when the errors involved are assumed to be non-normally distributed. We consider the class of heavy-tailed distributions for this purpose. Although our method is applicable for any distribution in this class, we take the multivariate t-distribution for illustration. This distribution has applications in many fields of applied research such as Economics, Business, and Finance. For estimation purpose, we use the modified maximum likelihood method in order to get the so-called modified maximum likelihood estimates that are obtained in a closed form. We show that these estimates are substantially more efficient than least-square estimates. They are also found to be robust to reasonable deviations from the assumed distribution and also many data anomalies such as the presence of outliers in the sample, etc. We further provide test statistics for testing the relevant hypothesis regarding the regression coefficients.
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    Article
    Citation - Scopus: 1
    Real Exchange Rates and Job Flows: Evidence From Turkey
    (Routledge Journals, Taylor & Francis Ltd, 2018) Islam, M. Qamarul; Yazici, Mehmet; Dogan, Ergun
    This study investigates the effects of the real exchange rate on job flows in Turkish manufacturing industries between 2006 and 2015 using data at the four-digit NACE Revision 2 level. Using dynamic panel data models, we find that a real appreciation increases gross and net job creation rates, and that the effect of appreciation is magnified as the exposure to international competitiveness of industries increases. We think that this is because Turkish manufacturing firms import a greater share of their inputs compared to the firms in developed countries. Hence, an appreciation creates more jobs because lower imported input costs enable firms to outcompete foreign producers.
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    Article
    Citation - WoS: 1
    Citation - Scopus: 2
    Sample Design and Allocation for Random Digit Dialling
    (Springer, 2005) Ayhan, HO; Islam, MQ
    Sample design and sample allocation methods are developed for random digit dialling in household telephone surveys. The proposed method is based on a two-way stratification of telephone numbers. A weighted probability proportional to size sample allocation technique is used, with auxiliary variables about the telephone coverage rates, within local telephone exchanges of each substrata. This makes the sampling design nearly "self-weighting" in residential numbers when the prior information is well assigned. A computer program generates random numbers for the local areas within the existing phone capacities. A simulation study has shown greater sample allocation gain by the weighted probabilities proportional to size measures over other sample allocation methods. The amount of dialling required to obtain the sample is less than for proportional allocation. A decrease is also observed on the gain in sample allocation for some methods through the increasing sample sizes.
  • Thumbnail Image
    Article
    Citation - WoS: 2
    Citation - Scopus: 2
    Job Flow Patterns and Productivity Dynamics in Turkish Manufacturing
    (World Scientific Publ Co Pte Ltd, 2024) Dogan, Ergun; Islam, M. Qamarul; Yazici, Mehmet
    In this paper, we analyze the job creation and destruction process, and the productivity dynamics in Turkish manufacturing by size, export status, import status and ownership by using a comprehensive firm-level dataset for the period of 2010-2015. Our focus is on the effect of turnover, which is due to the entry and exit of firms, on both job flows and industrial productivity growth. Our results show that while small firms contribute most to job creation, it is the large firms that contribute most to productivity growth. Regarding ownership, domestic private firms perform better than foreign firms in both job creation and productivity growth. With respect to export status, even though non-exporters outperform exporters in job creation, exporters dominate the productivity growth. As for import status, in job creation, like in the case of export status, non-importers do better but in productivity growth, unlike in the export status, no group of firms dominate, more specifically importers' and non-importers' contributions are close to each other. Another interesting finding is that, turnover effect on industry productivity is positive but very low. The role of incumbent firms in generating productivity growth is much higher than that of entering and exiting firms.