İktisat Bölümü Yayın Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/402
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Article Citation - WoS: 1Citation - Scopus: 1Model 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.; İktisatSelecting 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.Article Multiple linear regression model under nonnormality(Taylor & Francis Inc, 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.Article Citation - WoS: 2Citation - Scopus: 1Impact of Exchange Rate and Customs Union on Trade Balance at Commodity Level of Turkey With Eu (15)(Routledge Journals, Taylor & Francis Ltd, 2011) Islam, M. Qamarul; Yazici, Mehmet; Qamarul Islam, M.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.Article Citation - Scopus: 1Real Exchange Rates and Job Flows: Evidence From Turkey(Routledge Journals, Taylor & Francis Ltd, 2018) Islam, M. Qamarul; Yazici, Mehmet; Dogan, ErgunThis 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.Article Citation - WoS: 8Citation - Scopus: 11Firm Size and Job Creation: Evidence From Turkey(Routledge Journals, Taylor & Francis Ltd, 2017) Islam, M. Qamarul; Yazici, Mehmet; Dogan, ErgunThis 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.Article Citation - WoS: 4Citation - Scopus: 4Inference in Multivariate Linear Regression Models With Elliptically Distributed Errors(Taylor & Francis Ltd, 2014) Yazici, Mehmet; Islam, M. Qamarul; Yildirim, FetihIn 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.Article Citation - WoS: 4Citation - Scopus: 4Estimation 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.Article Citation - WoS: 4Citation - Scopus: 6Mahalanobis 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.Article Citation - WoS: 13Citation - Scopus: 13Multiple Linear Regression Model With Stochastic Design Variables(Taylor & Francis Ltd, 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.