Browsing by Author "Islam, M. Qamarul"

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Citation Count: Tiku, Moti L.; Islam, M. Qamarul; Sazak, Hakan S., "Estimation in bivariate nonnormal distributions with stochastic variance functions", Computational Statistics & Data Analysis, Vol.52, No.3-4, pp.1728-1745, (2008).
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.
Citation Count: Islam, M.Q. (2014). Estimation in multivariate nonnormal distributions with stochastic variance function. Journal of Computational and Applied Mathematics, 255, 698-714. http://dx.doi.org/10.1016/j.cam.2013.06.032
Estimation in multivariate nonnormal distributions with stochastic variance function
(Elsevier Science Bv, 2014) Islam, M. Qamarul
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.
Citation Count: Yazıcı, Mehmet; Islam, M. Qamarul (2014). "Exchange Rate And Bilateral Trade Balance Of Turkey With EU (15) Countries", Journal of Business Economics and Finance, Vol.3, No.3, pp.341-356.
Exchange Rate And Bilateral Trade Balance Of Turkey With EU (15) Countries
(2014) Yazıcı, Mehmet; Islam, M. Qamarul; 144084
This paper investigates the short-run and long-run impact of real exchange rate on the bilateral trade balance of Turkey with EU (15) countries. We’ve employed the bounds testing approach to the cointegration and the error correction modeling. Following Yazici and Islam (2011a, 2011b, 2012) and Yazici (2012), we select the optimal model from the set of those models that satisfy both diagnostic tests and cointegration. Thus, unlike the other studies, it is ensured that a statistically reliable and cointegrated model is picked up for estimation. Based on the quarterly data for 1982-I to 2001-IV period, estimation results indicate no evidence of J-curve in the short run in any of Turkey’s bilateral trade with EU(15) countries. In the long run, however, real depreciation of Turkish Lira improves the trade balance of Turkey with Austria, Denmark, France, Ireland, Italy, Sweden and UK.
Citation Count: Yazıcı, Mehmet; Islam, M. Qamarul (2012). "Exchange rate and Turkish agricultural trade balance with EU (15)", Agricultural Economics Review, Vol. 13, No. 2, pp. 35-47.
Exchange rate and Turkish agricultural trade balance with EU (15)
(2012) Yazıcı, Mehmet; Islam, M. Qamarul; 144084
This paper investigates the short-run and long-run impact of exchange rate on the trade balance of Turkish Agriculture with EU (15) countries. The bounds testing approach to the cointegration and the error correction modeling is employed. A new strategy in the model selection phase is adopted and the optimal model is selected from the set of those models that satisfy both diagnostic tests and cointegration. Thus, unlike the previous literature utilizing this approach, it is ensured that a statistically reliable and cointegrated model is picked up for estimation. Estimation results based on the data for 1988-I to 2008-IV period indicate that in the short-run real exchange rate variable affects agriculture trade balance in trade with EU(15) and depreciation of Turkish Lira improves the trade balance. As for the long-run impact of the exchange rate, depreciation of domestic currency has a statistically significant negative effect on trade balance of agriculture.
Citation Count: Doğan, E., İslam, M.Q., Yazıcı, M. (2017). Firm size and job creation: evidence from Turkey. Economic Research-Economska Istrazivanja, 30(1), 349-367. http://dx.doi.org/10.1080/1331677X.2017.1305804
Firm size and job creation: evidence from Turkey
(Routledge Journals, 2017) Doğan, Ergün; Islam, M. Qamarul; Yazıcı, Mehmet; 43080; 144084
This study examines the relationship between firm size and job creation by using an extensive data set covering all non-farm Turkish businesses with 20 or more employees from 2003 to 2010. We find that small firms (firms with employees between 20 and 100 employees) have higher mean job flow rates (job creation, job destruction and net job creation rates) than large firms. Firm size and job flow rates are inversely related, and this relationship is especially prominent for firms with 50 employees or more. Although the overall pattern observed is also observed in both sectors, job creation rates in services are higher than the ones in manufacturing. The magnitudes of job destruction rates are comparable across sectors. Higher job creation rate in services but comparable job destruction rate results in higher net job creation rate in services. As for shares, only for smaller firms (20-49 and 50-99 size categories), job creation shares are greater than their shares in employment. But these firms have disproportionate job destruction shares as well. We also find that only the 20-49 category firms contribute to net job creation more than their share in employment. The smaller firms have high disproportionate shares in job creation and destruction in manufacturing and services as well.
Citation Count: Yazıcı, M., Islam, M.Q. (2011). Impact of exchange rate and customs uinon on trade balance at commodity level of Turkey with EU (15). Ekonomska Istrazivanja-Economic Research, 24(3), 75-85.
Impact of exchange rate and customs uinon on trade balance at commodity level of Turkey with EU (15)
(Juraj Dobrila ,University Pula, 2011) Yazıcı, Mehmet; Islam, M. Qamarul; 144084
This paper investigates the short-run and long-run impact of exchange rate and customs union on the trade balance at commodity-group level of Turkey with EU (15). Bounds testing approach is employed where a new strategy in the model selection phase is odopted ensuring that optimal model is selected from those models satisfying both diagnostics and cointegration. Results indicate that in the short-run exchange rate matters in determination of trade balance of 13 commodity groups out of 21 and customs union in 8 cases. Pattern of response of trade balance to exchange rate does not suggest a J-curve effect in any of cases. As for the long-run effect, neither exchange rate nor customs union has a statistically significant effect on trade balance of any of commodity groups, suggesting that those significant short-run effects don't last into long-run
Citation Count: Islam, M.Q., Yıldırım, F., Yazıcı, M. (2014). Inference in multivariate linear regression models with elliptically distributed errors. Journal of Applied Statistics, 41(8), 1746-1766. http://dx.doi.org/10.1080/02664763.2014.890177
Inference in multivariate linear regression models with elliptically distributed errors
(Taylor&Francis Ltd, 2014) Islam, M. Qamarul; Yıldırım, Fetih; Yazıcı, Mehmet; 6772; 144084
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
Citation Count: Islam, Q. (2010). Mahalanobis distance under non-normality. Statistics: A Journal of Theoretical and Applied Statistics, 44(3), 275-290. http://dx.doi.org/10.1080/02331880903043223
Mahalanobis distance under non-normality
(Taylor&Francis LTD, 2010) Islam, M. Qamarul
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
Citation Count: İslam, M.Q., Yazıcı, M. (2012). Model selection uncertainties and model averaging in autoregressive time series models. Pakistan Journal Of Statistics, 28(2), 239-252.
Model selection uncertainties and model averaging in autoregressive time series models
(ISOSS Publication, 2012) Islam, M. Qamarul; Yazıcı, Mehmet; 144084
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
Citation Count: Islam, M. Qamarul; Tiku, Moti L. (2004). "Multiple linear regression model under nonnormality", Communications in Statistics - Theory and Methods, Vol.33, No.10, pp.2443-2467.
Multiple linear regression model under nonnormality
(2004) Islam, M. Qamarul; Tiku, Moti L.
We consider multiple linear regression models under nonnormality. We derive modified maximum likelihood estimators (MMLEs) of the parameters and show that they are efficient and robust. We show that the least squares esimators are considerably less efficient. We compare the efficiencies of the MMLEs and the M estimators for symmetric distributions and show that, for plausible alternatives to an assumed distribution, the former are more efficient. We provide real-life examples.
Citation Count: Islam, M.Q., Tiku, M.L. (2010). Multiple linear regression model with stochastic design variables. Journal of Applied Statistics, 37(6), 923-943. http://dx.doi.org/10.1080/02664760902939612
Multiple linear regression model with stochastic design variables
(Routledge Journals, 2010) Islam, M. Qamarul; Tiku, Moti L.
In a simple multiple linear regression model, the design variables have traditionally been assumed to be non-stochastic. In numerous real-life situations, however, they are stochastic and non-normal. Estimators of parameters applicable to such situations are developed. It is shown that these estimators are efficient and robust. A real-life example is given
Citation Count: Islam, MQ; Tiku, ML; Yıldırım F., "Nonnormal regression. i. skew distributions" Communications In Statistics-Theory And Methods, Vol.30, No.6, pp.993-1020, (2001).
Nonnormal regression. i. skew distributions
(Marcel Dekker Inc, 2001) Islam, M. Qamarul; Tiku, M. L.; Yıldırım, F.
In a linear regression model of the type y = thetaX + e, it is often assumed that the random error e is normally distributed. In numerous situations, e.g., when y measures life times or reaction times, e typically has a skew distribution. We consider two important families of skew distributions, (a) Weibull with support IR: (0, infinity) on the real line, and (b) generalised logistic with support IR: (-infinity, infinity). Since the maximum likelihood estimators are intractable in these situations, we derive modified likelihood estimators which have explicit algebraic forms and are, therefore, easy to compute. We show that these estimators are remarkably efficient, and robust. We develop hypothesis testing procedures and give a real life example.
Citation Count: Tiku, ML; Islam, MQ; Selcuk, AS, "Nonnormal regression. II. Symmetric distributions", Communications in Statistics-Theory and Methods, Vol. 30, No. 6, pp. 1021-1045, (2001).
Nonnormal regression. II. Symmetric distributions
(Taylor&Francis INC, 2001) Tiku, M. L.; Islam, M. Qamarul; Selçuk, A. S.
Salient features of a family of short-tailed symmetric distributions, introduced recently by Tiku and Vaughan [1], are enunciated. Assuming the error distribution to be one of this family, the methodology of modified likelihood is used to derive MML estimators of parameters in a linear regression model. The estimators are shown to be efficient, and robust to inliers. This paper is essentially the first to achieve robustness to infers. The methodology is extended to long-tailed symmetric distributions and the resulting estimators are shown to be efficient, and robust to outliers. This paper should be read in conjunction with Islam et al. [2] who develop modified likelihood methodology for skew distributions in the context of linear regression.
Citation Count: Islam,M. Qamarul; L. Tiku,Moti; Yıldırım, F." Nonnormal Regression.I. Skew Distributions", Commun. Statist.—Theory Meth., Vol.30, No.6, pp.993-1020.
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
Citation Count: Doğan, E., Islam, M.Q., Yazıcı, M. (2018). Real exchange rates and job flows: evidence from Turkey. Applied Economics, 50(42), 4489-4499. http://dx.doi.org/ 10.1080/00036846.2018.1458190
Real exchange rates and job flows: evidence from Turkey
(Routledge Journals, 2018) Doğan, Ergün; Islam, M. Qamarul; Yazıcı, Mehmet; 43080; 14480
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.
Citation Count: Sazak, H., Tiko, ML., Islam, MQ. (2006). Regression analysis with a dtochastic design variable. International Statistical Review, 74(1), 77-88.
Regression analysis with a dtochastic design variable
(In Statistical Inst, 2006) Sazak, Hakan; Tiku, Moti L.; S., Hakan; Islam, M. Qamarul
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
Citation Count: Ayhan, H.Ö.; Islam, M.Q., "Sample design and allocation for random digit dialling", Quality&Quantity, Vol.39, No.5, pp.625-641, (2005).
Sample design and allocation for random digit dialling
(Springer, 2005) Ayhan, H. Öztaş; Islam, M. Qamarul
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.