05. Fakülteler

Permanent URI for this communityhttps://hdl.handle.net/20.500.11779/7

Browse

Now showing 1 - 20 of 127

Citation - WoS: 2
Citation - Scopus: 5
Increasing Procurement Efficiency Through Optimal E-Commerce Enablement Scheduling
(Emerald Group Publishing Ltd., 2019) Özlük, Özgür; Cholette, Susan; Clark, Andrew G
Purpose: This study aims to show how cost savings can be achieved through optimizing the scheduling of e-commerce enablements. The University of California is one of the largest, most prestigious public education and research systems in the world, yet diminished state support is driving the search for system-wide cost savings. Design/methodology/approach: This study documents the preparation for and rollout of an e-procurement system across a subset of campuses. A math programing tool was developed for prioritizing the gradual rollout to generate the greatest expected savings subject to resource constraints. Findings: The authors conclude by summarizing the results of the rollout, discussing lessons learned and their benefit to decision-makers at other public institutions. Originality/value: The pilot program comprising three campuses has been predicted to yield $1.2m in savings over a one-year period; additional sensitivity analysis with respect to savings, project timelines and other rollout decisions illustrate the robustness of these findings.
Citation - WoS: 16
Citation - Scopus: 20
Selecting Suicide Ideation Assessment Instruments: a Meta-Analytic Review
(SAGE Publications, 2017) Duncan, Kelly; Atalay, Zümra; Erford, Bradley T.; Jackson, Jessica; Bardhoshi, Gerta
Psychometric meta-analyses and reviews were provided for four commonly used suicidal ideation instruments: the Beck Scale for Suicide Ideation, the Suicide Ideation Questionnaire, the Suicide Probability Scale, and Columbia–Suicide Severity Rating Scale. Practical and technical issues and best use recommendations for screening and outcome research are offered.
Citation - WoS: 1
Citation - Scopus: 1
Estimated Probabilities of Positive, Vs. Negative, Events Show Separable Correlations With Covid-19 Preventive Behaviours
(Elsevier, 2022) Aksu, Ayça; Booth, Robert W.; Yavuz, Burak Baran; Peker, Müjde
Research has associated optimism with better health-protective behaviours, but few studies have measured optimism or pessimism directly, by asking participants to estimate probabilities of events. We used these probability estimates to examine how optimism and/or pessimism relate to protecting oneself from COVID-19. When COVID-19 first reached Turkey, we asked a snowball sample of 494 Istanbul adults how much they engaged in various COVID-protective behaviours. They also estimated the probabilities of their catching COVID-19, and of other positive and negative events happening to them. Estimated probability of general positive events (optimism) correlated positively with officially-recommended helpful behaviours (e.g. wearing masks), but not with less-helpful behaviours (e.g. sharing ‘alternative’ COVID-related information online). Estimated probabilities of general negative events (pessimism), or of catching COVID, did not correlate significantly with helpful COVID-related behaviours; but they did correlate with psychopathological symptoms, as did less-helpful COVID-related behaviours. This shows important nuances can be revealed by measuring optimism and pessimism, as separate variables, using probability estimates.
Citation - WoS: 2
Citation - Scopus: 2
Parental Predictors of Children’s Math Learning Behaviours in Different Cultures
(Springer, 2022) Selçuk, Bilge; Kisbu-Sakarya, Yasemin; Niehues, Wenke
Research indicates that parental schoolwork involvement is beneficial for students' academic functioning when parents facilitate their children's autonomy and refrain from psychological controlling practices. However, effects of the quality of parental involvement on child learning outcomes may vary due to cross-cultural differences in children's appraisal and reaction towards these practices. The current study aimed to investigate the link between the quality of parental schoolwork involvement and children's learning-related behaviours in math, and the mediating role of mother-child conflict around math schoolwork in this link in three cultural groups (i.e., German-Turkish, Turkish and German families). Data were collected from 107 German-Turkish, 426 Turkish and 140 German mothers with children in fifth to eighth grades. After testing measurement invariance of the scales across groups, multi-group structural equation modelling was used to examine the direct and indirect paths between the quality of parental involvement, mother-child conflict and child learning-related behaviours. Results showed that the level of mother-child conflict mediated the link between mothers' psychologically controlling practices and children's learning-related behaviours in math in all three groups. No mediation was found for the link between maternal autonomy support and children's learning-related behaviours in any group. However, the direct path from mothers' autonomy support to children's learning-related behaviours was significant in the Turkish and German-Turkish samples. These results suggest that the role of different forms of parental schoolwork involvement in children's academic functioning is more similar than different across cultural groups.
Citation - WoS: 3
Citation - Scopus: 2
A Benchmark Dataset for Turkish Data-To Generation
(Elsevier, 2022) Demir, Şeniz; Öktem, Seza
In the last decades, data-to-text (D2T) systems that directly learn from data have gained a lot of attention in natural language generation. These systems need data with high quality and large volume, but unfortunately some natural languages suffer from the lack of readily available generation datasets. This article describes our efforts to create a new Turkish dataset (Tr-D2T) that consists of meaning representation and reference sentence pairs without fine-grained word alignments. We utilize Turkish web resources and existing datasets in other languages for producing meaning representations and collect reference sentences by crowdsourcing native speakers. We particularly focus on the generation of single-sentence biographies and dining venue descriptions. In order to motivate future Turkish D2T studies, we present detailed benchmarking results of different sequence-to-sequence neural models trained on this dataset. To the best of our knowledge, this work is the first of its kind that provides preliminary findings and lessons learned from the creation of a new Turkish D2T dataset. Moreover, our work is the first extensive study that presents generation performances of transformer and recurrent neural network models from meaning representations in this morphologically-rich language.
Comparing Humans and Deep Neural Networks on Face Recognition Under Various Distance and Rotation Viewing Conditions
(Journal of Vision, 2023) Fux, Michal; Arslan , Şuayb Şefik; Jang, Hojin; Boix, Xavier; Cooper, Avi; Groth, Matt J; Sinha, Pawan
Humans possess impressive skills for recognizing faces even when the viewing conditions are challenging, such as long ranges, non-frontal regard, variable lighting, and atmospheric turbulence. We sought to characterize the effects of such viewing conditions on the face recognition performance of humans, and compared the results to those of DNNs. In an online verification task study, we used a 100 identity face database, with images captured at five different distances (2m, 5m, 300m, 650m and 1000m) three pitch values (00 - straight ahead, +/- 30 degrees) and three levels of yaw (00, 45, and 90 degrees). Participants were presented with 175 trials (5 distances x 7 yaw and pitch combinations, with 5 repetitions). Each trial included a query image, from a certain combination of range x yaw x pitch, and five options, all frontal short range (2m) faces. One was of the same identity as the query, and the rest were the most similar identities, chosen according to a DNN-derived similarity matrix. Participants ranked the top three most similar target images to the query image. The collected data reveal the functional relationship between human performance and multiple viewing parameters. Nine state-of-the-art pre-trained DNNs were tested for their face recognition performance on precisely the same stimulus set. Strikingly, DNN performance was significantly diminished by variations in ranges and rotated viewpoints. Even the best-performing network reported below 65% accuracy at the closest distance with a profile view of faces, with results dropping to near chance for longer ranges. The confusion matrices of DNNs were generally consistent across the networks, indicating systematic errors induced by viewing parameters. Taken together, these data not only help characterize human performance as a function of key ecologically important viewing parameters, but also enable a direct comparison of humans and DNNs in this parameter regime
A Bayesian Allocation Model Based Approach To Mixed Membership Stochastic Blockmodels
(Taylor and Francis Ltd., 2022) Kırbız, Serap; Hızlı, Çağlar
Although detecting communities in networks has attracted considerable recent attention, estimating the number of communities is still an open problem. In this paper, we propose a model, which replicates the generative process of the mixed-membership stochastic block model (MMSB) within the generic allocation framework of Bayesian allocation model (BAM) and BAM-MMSB. In contrast to traditional blockmodels, BAM-MMSB considers the observations as Poisson counts generated by a base Poisson process and marks according to the generative process of MMSB. Moreover, the optimal number of communities for BAM-MMSB is estimated by computing the variational approximations of the marginal likelihood for each model order. Experiments on synthetic and real data sets show that the proposed approach promises a generalized model selection solution that can choose not only the model size but also the most appropriate decomposition.
Citation - WoS: 23
Citation - Scopus: 23
Experimental Observation of Temperature and Pressure Induced Frequency Fluctuations in Silicon Mems Resonators
(IEEE, 2021) Zhao, Chun; Mustafazade, Arif; Pandit, Milind; Seshia A, Ashwin; Sobreviela, Guillermo; Zou, Xudong
Silicon MEMS resonators are increasingly being adopted for applications in timing and frequency control, as well as precision sensing. It is well established that a key limitation to performance is associated with sensitivity to environmental variables such as temperature and pressure. As a result, technical approaches to address these factors such as vacuum sealing and ovenization of the resonators in a temperature controlled system have been introduced. However, residual sensitivity to such effects can still serve as a significant source of frequency fluctuations and drift in precision devices. This is experimentally demonstrated in this paper for a precision oven-controlled and vacuum-sealed silicon resonators. The frequency fluctuations of oscillators constructed using two separate nearly-identical co-located resonators on the same chip are analysed and differential frequency fluctuations are examined as a means of reducing the impact of common-mode effects such as temperature and pressure. For this configuration, our results show that the mismatch of temperature and pressure coefficients between the resonators ultimately limits the frequency stability.
Citation - WoS: 3
Citation - Scopus: 3
When Are Minorities Worse Off? a Systematic Investigation of Size and Status
(2017) Thacker, Strom C.; Lu, Yuan; Gerring, John; Öncel, Erzen
Are smaller ethnic groups less advantaged than large groups? This question has not been systematically studied. Using two new datasets, we find that when group size and status are analyzed at national levels smaller groups are generally worse off than larger groups. By contrast, when group size and status are analyzed at subnational (regional or district) levels, smaller groups are better off than larger groups. National minorities are disadvantaged while local minorities are advantaged.We theorize that two factors are at work in generating this surprisingly consistent relationship. First, a synergy exists at national levels among three features of ethnic groups: size, power, and status. The second factor is based on social dynamics. Specifically, insofar as internal migration is characterized by positive selection, then migrants and their descendants should form the basis of small, privileged groups within the region that they migrate to. Insofar as distance enhances positive selection, this explains why smaller migrations are associated with more privileged groups and larger migrations with somewhat less privileged groups.
Citation - WoS: 3
Citation - Scopus: 4
Does Credit Composition Matter for Current Account Dynamics? Evidence From Turkey
(Taylor & Francis, 2016) Toraganlı, Nazlı; Ertuğrul, Hasan Murat
Based on a dynamic approach using the Kalman filter we depict effects of time-varying interactions between different components of credit stock on the current account in the Turkish Economy for the period 2002Q3–2014Q3. We decompose the credit stock into consumer and non-financial corporate sector credit and show empirically that both types of credit stock have negative effects on the current account dynamics
Citation - WoS: 5
Citation - Scopus: 5
The Pisa Tasks: Unveiling Prospective Elementary Mathematics Teachers’ Difficulties With Contextual, Conceptual, and Procedural Knowledge
(Taylor & Francis, 2019) Özgeldi, Meriç; Aydın, Utkun
The aim of this mixed methods study was to investigate the difficulties prospective elementary mathematics teachers have in solving the Programme for International Student Assessment (PISA) 2012 released items. A mathematics test consisting of 26 PISA items was administered, followed by interviews. Multiple data were utilized to provide rich insights into the types of mathematical knowledge that a particular item requires and prospective teachers’ difficulties in using these knowledge types. A sample of 52 prospective teachers worked the mathematics test, and 12 of them were interviewed afterwards. The data-sets were complementary: the quantitative data showed that PISA items could be categorized under contextual, conceptual, and procedural knowledge and indicated the most frequent difficulties in the combined contextual, conceptual, and procedural knowledge items. The qualitative data revealed that few prospective teachers could give mathematical explanations for conceptual knowledge items, and that their contextual knowledge was fragmented. Educational implications were discussed.
Citation - WoS: 1
Mechanochemical Synthesis and Characterization of Nanostructured Erb4 and Ndb4 Rare-Earth Tetraborides
(John Wiley and Sons Inc, 2024) Boztemur, B.; Kaya, F.; Derin, B.; Öveçoğlu, M.L.; Li, J.; Ağaoğulları, D.
Rare-earth borides have become very popular in recent decades with high mechanical strength, melting point, good corrosion, wear, and magnetic behavior. However, the production of these borides is very challenging and unique. The production of ErB4 and NdB4 nanopowders via mechanochemical synthesis (MCS) is reported in this study first time in the literature. Er2O3 or Nd2O3, B2O3, and Mg initial powders are mechanically alloyed for different milling times to optimize the process. Rare-earth borides with MgO phases are synthesized, then MgO is removed with HCl acid. The nanostructured rare-earth tetraboride powders are analyzed using X-ray diffraction (XRD). Based on the XRD, ErB4 powders are produced successfully at the end of the 5 h milling. However, the NdB4 phase does not occur as the stoichiometric ratio, so the B2O3 amount is decreased to nearly 35 wt%. When the amount of B2O3 is decreased to 20 wt%, NdB4 and NdB6 phases are 50:50 according to the Rietveld analysis. However, a homogenous NdB4 phase is obtained with 30 wt% loss of B2O3. The average particle sizes of ErB4 and NdB4 powders are nearly 100.4 and 85.6 nm, respectively. The rare-earth tetraborides exhibit antiferromagnetic-to-paramagnetic-like phase transitions at 18 and 8.53 K, respectively. © 2024 The Author(s). Advanced Engineering Materials published by Wiley-VCH GmbH.
Citation - WoS: 8
Citation - Scopus: 5
Second Language Motivational Self System of Sixth Graders in Turkey: a Correlational Study
(Wiley, 2021) Çiftçi, Hatime; Arslan, Tugba
Investigating the foreign and second language (L2) motivational self system (L2MSS) of Turkish sixth graders, this study reports relationships among three components (ideal L2 self, ought-to L2 self, and L2 learning experience) of the L2MSS and the variables of school type (public and private), gender, and intended effort. Data were collected from 170 students in two public and two private secondary schools in northwestern Turkey through a questionnaire. The results of correlation analysis indicate a strong positive correlation between ideal L2 self and L2 learning experience, and the variables of school type and gender did not make a difference. Intended effort was found to have a strong positive correlation with these L2MSS components. The results of multiple regression analysis provide further evidence for especially intended effort as a significant predictor of L2MSS, whereas the school type and gender did not contribute to the system. The major implications of the study and future research possibilities are discussed.
A New Benchmark Dataset for P300 Erp-Based Bci Applications
(Academic Press Inc Elsevier Science, 2023) Çakar, Tuna; Özkan, Hüseyin; Musellim, Serkan; Arslan, Suayb S.; Yağan, Mehmet; Alp, Nihan
Because of its non-invasive nature, one of the most commonly used event-related potentials in brain -computer interface (BCI) system designs is the P300 electroencephalogram (EEG) signal. The fact that the P300 response can easily be stimulated and measured is particularly important for participants with severe motor disabilities. In order to train and test P300-based BCI speller systems in more realistic high-speed settings, there is a pressing need for a large and challenging benchmark dataset. Various datasets already exist in the literature but most of them are not publicly available, and they either have a limited number of participants or utilize relatively long stimulus duration (SD) and inter-stimulus intervals (ISI). They are also typically based on a 36 target (6 x 6) character matrix. The use of long ISI, in particular, not only reduces the speed and the information transfer rates (ITRs) but also oversimplifies the P300 detection. This leaves a limited challenge to state-of-the-art machine learning and signal processing algorithms. In fact, near-perfect P300 classification accuracies are reported with the existing datasets. Therefore, one certainly needs a large-scale dataset with challenging settings to fully exploit the recent advancements in algorithm design (machine learning and signal processing) and achieve high-performance speller results. To this end, in this article we introduce a new freely-and publicly-accessible P300 dataset obtained using 32-channel EEG, in the hope that it will lead to new research findings and eventually more efficient BCI designs. The introduced dataset comprises 18 participants performing a 40 -target (5 x 8) cued-spelling task, with reduced SD (66.6 ms) and ISI (33.3 ms) for fast spelling. We have also processed, analyzed, and character-classified the introduced dataset and we presented the accuracy and ITR results as a benchmark. The introduced dataset and the codes of our experiments are publicly accessible at https://data .mendeley.com /datasets /vyczny2r4w.(c) 2023 Elsevier Inc. All rights reserved.
Citation - WoS: 27
Citation - Scopus: 30
Service-Aware Multi-Resource Allocation in Software-Defined Next Generation Cellular Networks
(2018) Arslan, Şuayb Şefik; Zeydan, Engin; Narmanloğlu, Ömer
Network slicing is one of the major solutions needed to meet the requirements of next generation cellular networks, under one common network infrastructure, in supporting multiple vertical services provided by mobile network operators. Network slicing makes one shared physical network infrastructure appear as multiple logically isolated virtual networks dedicated to different service types where each Network Slice (NS) benefits from on-demand allocated resources. Typically, the available resources distributed among NSs are correlated and one needs to allocate them judiciously in order to guarantee the service, MNO, and overall system qualities. In this paper, we consider a joint resource allocation strategy that weights the significance of the resources per a given NS by leveraging the correlation structure of different quality-of-service (QoS) requirements of the services. After defining the joint resource allocation problem including the correlation structure, we propose three novel scheduling mechanisms that allocate available network resources to the generated NSs based on different type of services with different QoS requirements. Performance of the proposed schedulers are then investigated through Monte-Carlo simulations and compared with each other as well as against a traditional max-min fairness algorithm benchmark. The results reveal that our schedulers, which have different complexities, outperform the benchmark traditional method in terms of service-based and overall satisfaction ratios, while achieving different fairness index levels.
Citation - WoS: 3
Citation - Scopus: 5
Unraveling Neural Pathways of Political Engagement: Bridging Neuromarketing and Political Science for Understanding Voter Behavior and Political Leader Perception
(2023) Çakar, Tuna; Filiz, Gözde
Political neuromarketing is an interdisciplinary field that combines marketing, neuroscience, and psychology to understand voter behavior and political leader perception. This interdisciplinary field offers novel techniques to understand complex phenomena such as voter engagement, political leadership, and party branding. This study aims to understand the neural activation patterns of voters when they are exposed to political leaders using functional near-infrared spectroscopy (fNIRS) and machine learning methods. We recruited participants and recorded their brain activity using fNIRS when they were exposed to images of different political leaders. This neuroimaging method (fNIRS) reveals brain regions central to brand perception, including the dorsolateral prefrontal cortex (dlPFC), the dorsomedial prefrontal cortex (dmPFC), and the ventromedial prefrontal cortex (vmPFC). Machine learning methods were used to predict the participants' perceptions of leaders based on their brain activity. The study has identified the brain regions that are involved in processing political stimuli and making judgments about political leaders. Within this study, the best-performing machine learning model, LightGBM, achieved a highest accuracy score of 0.78, underscoring its efficacy in predicting voters' perceptions of political leaders based on the brain activity of the former. The findings from this study provide new insights into the neural basis of political decision-making and the development of effective political marketing campaigns while bridging neuromarketing, political science and machine learning, in turn enabling predictive insights into voter preferences and behavior
Citation - WoS: 5
Citation - Scopus: 6
A New Approach for Measuring Viscoelastic Properties of Soft Materials Using the Dynamic Response of a Spherical Object Placed at the Sample Interface
(Springer, 2023) Besli, Ayça; Koç,Ömer Hayati; Körük,Hasan; Yurdaer, Berk Salih
Background: There are several techniques to characterize the mechanical properties of soft materials, such as the indentation method and the method based on the application of a spherical object placed inside the sample. The indentation systems usually yield the elastic properties of materials and their mathematical models do not consider the inertia of the sample involved in motion and radiation damping, while placing an object inside the sample is not practical and this procedure can alter the mechanical properties of the sample for the method based on the application of a bubble/sphere placed inside the sample. Objective: A new approach for the identification of the viscoelastic properties of soft materials using the dynamic response of a spherical object placed at the sample interface was proposed. Methods: The spherical object placed at the sample interface was pressed using an electromagnet and the dynamic response of the spherical object was tracked using a high-speed camera, while the dynamic response of the spherical object placed at the sample interface was estimated using a comprehensive analytical model. The effects of the shear modulus, viscosity, Poisson’s ratio and density of the soft sample, the radius and density of the spherical object and the damping due to radiation were considered in this mathematical model. The shear modulus and viscosity of the soft sample were determined by matching the experimentally identified and theoretically estimated responses of the spherical object. Results: The shear moduli and viscosities of the three phantoms with the gelatin mass ratios of 0.20, 0.25 and 0.29 were measured to be 3450, 4300 and 4950 Pa and 12.5, 14.0 and 15.0 Pa⋅s, respectively. The shear modulus and viscosity of the phantom increases as the gelatin mass ratio increases. The frequency of oscillations of the hemisphere placed at the phantom interface increases as the gelatin mass ratio increases due to stiffness increase. Conclusions: After matching the experimental and theoretical steady-state displacements and amplitudes of oscillations of the hemisphere at the sample interface, the comparison of the experimentally identified and theoretically predicted frequency of oscillations further confirmed the identified material properties of the samples. The approach presented here is expected to provide valuable information on material properties in biomedical and industrial applications.
Citation - Scopus: 8
Patterns of Treatment and Correction of Hyponatremia in Intensive Care Unit Patients
(W.B. Saunders, 2015) Badawi, Omar; Chiodo, Joseph; Waikar, Sushrut S.; Boklage, Susan; Dasta, Joseph; Xie, Lin; Başer, Onur
Purpose: The goal of this study was to examine the real-world patterns of care and interventions among intensive care unit (ICU) patients with hypervolemic and euvolemic hyponatremia using a large clinical database. Materials and Methods: The Phillips eICU Research Institute database was used to investigate hyponatremia treatment patterns and trends, mortality, and ICU and hospital length of stay. Demographics, clinical characteristics, and outcome variables were compared in patients corrected for hyponatremia using both a more strict and a less strict definition. Results: At admission, 35%, 55%, and 10% of patients had mild, moderate, and severe hyponatremia, respectively. At the end of an ICU stay, the percentage of patients who did not have corrected serum sodium concentration was 48% (using a more strict definition) and 24% (using a less strict definition). Using either definition of correction, patients with serum sodium correction had lower mortality and longer survival than did patients without corrected serum sodium concentration. Conclusions: A significant proportion of hyponatremia is not corrected during an ICU stay. Critically ill patients with hyponatremia who have their serum sodium corrected have lower mortality and longer survival, highlighting the need for more attention to hyponatremia and its correction in critically ill patients. © 2015 Elsevier Inc.
Citation - WoS: 17
Citation - Scopus: 23
Benefit of Early Discharge Among Patients With Low-Risk Pulmonary Embolism
(2017) Wang, Li; Wells, Phil; Fermann, Gregory J; Peacock, W. Frank; Schein, Jeff; Coleman, Craig I; Crivera, Concetta; Başer, Onur
Clinical guidelines recommend early discharge of patients with low-risk pulmonary embolism (LRPE). This study measured the overall impact of early discharge of LRPE patients on clinical outcomes and costs in the Veterans Health Administration population. Adult patients with >= 1 inpatient diagnosis for pulmonary embolism (PE) (index date) between 10/2011-06/2015, continuous enrollment for >= 12 months pre-and 3 months post-index date were included. PE risk stratification was performed using the simplified Pulmonary Embolism Stratification Index. Propensity score matching (PSM) was used to compare 90-day adverse PE events (APEs) [recurrent venous thromboembolism, major bleed and death], hospital-acquired complications (HACs), healthcare utilization, and costs among short (<= 2 days) versus long length of stay (LOS). Net clinical benefit was defined as 1 minus the combined rate of APE and HAC. Among 6,746 PE patients, 95.4% were men, 22.0% were African American, and 1,918 had LRPE. Among LRPE patients, only 688 had a short LOS. After 1:1 PSM, there were no differences in APE, but short LOS had fewer HAC (1.5% vs 13.3%, 95% CI: 3.77-19.94) and bacterial pneumonias (5.9% vs 11.7%, 95% CI: 1.24-3.23), resulting in better net clinical benefit (86.9% vs 78.3%, 95% CI: 0.84-0.96). Among long LOS patients, HACs (52) exceeded APEs (14 recurrent DVT, 5 bleeds). Short LOS incurred lower inpatient ($2,164 vs $5,100, 95% CI: $646.8-$5225.0) and total costs ($9,056 vs $12,544, 95% CI: $636.6-$6337.7). LRPE patients with short LOS had better net clinical outcomes at lower costs than matched LRPE patients with long LOS.
Citation - WoS: 7
Citation - Scopus: 7
Market Access and Regional Dispersion of Human Capital Accumulation in Turkey
(Wiley, 2020) Karahasan, Burhan Can; Bilgel, Fırat
Building on early advances in development economics, the theoretical construct of new economic geography asserts that geography plays a crucial role in educational human capital accumulation. Based on this expectation, this study investigates the impact of market access on provincial human capital accumulation in Turkey. Results indicate that market access matters for understanding why some regions lag behind others in terms of average years of schooling. Our results are robust to the inclusion of spatial mechanisms, different specifications of the spatial weight matrix, endogeneity and alternative measurements of market access and to a host of other factors that affect regional human capital accumulation.

Browse

Browsing 05. Fakülteler by WoS Q "Q2"