Omay, Tolga

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Profile URL
https://hdl.handle.net/20.500.14411/7237
Name Variants
T.,Omay
Omay, Tolga
O., Tolga
Tolga, Omay
Omay,T.
O.,Tolga
T., Omay
Omay T.
Job Title
Profesor Doktor
Email Address
tolga.omay@atilim.edu.tr
Main Affiliation
Economics
Status
Website
ORCID ID
Scopus Author ID
23978235900
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
GDI-4259-2022

Sustainable Development Goals

2

ZERO HUNGER
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0

Research Products

14

LIFE BELOW WATER
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2

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17

PARTNERSHIPS FOR THE GOALS
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7

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5

GENDER EQUALITY
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0

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16

PEACE, JUSTICE AND STRONG INSTITUTIONS
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0

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8

DECENT WORK AND ECONOMIC GROWTH
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11

Research Products

4

QUALITY EDUCATION
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0

Research Products

6

CLEAN WATER AND SANITATION
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0

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7

AFFORDABLE AND CLEAN ENERGY
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3

Research Products

10

REDUCED INEQUALITIES
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2

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11

SUSTAINABLE CITIES AND COMMUNITIES
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1

Research Products

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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3

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1

NO POVERTY
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0

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3

GOOD HEALTH AND WELL-BEING
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2

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12

RESPONSIBLE CONSUMPTION AND PRODUCTION
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1

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13

CLIMATE ACTION
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7

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15

LIFE ON LAND
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1

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Documents

80

Citations

1218

h-index

20

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Documents

72

Citations

1070

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Scholarly Output

65

Articles

55

Views / Downloads

19/0

Supervised MSc Theses

4

Supervised PhD Theses

2

WoS Citation Count

431

Scopus Citation Count

500

WoS h-index

13

Scopus h-index

13

Patents

0

Projects

0

WoS Citations per Publication

6.63

Scopus Citations per Publication

7.69

Open Access Source

32

Supervised Theses

6

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JournalCount
Applied Economics5
Computational Economics5
Springer Proceedings in Business and Economics -- 4th International Conference on Banking and Fice Perspectives, ICBFP 2019 -- 2 May 2019 through 3 May 2019 -- Famagusta -- 2737293
Mathematics3
Environmental Science and Pollution Research2
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Subject: C12

Scholarly Output Search Results

Now showing 1 - 4 of 4
  • Thumbnail Image
    Article
    Citation - WoS: 6
    Citation - Scopus: 4
    Is real per capita state personal income stationary? New nonlinear, asymmetric panel-data evidence
    (Wiley, 2020) Emirmahmutoglu, Furkan; Gupta, Rangan; Miller, Stephen M.; Omay, Tolga
    This paper re-examines the stochastic properties of U.S. state real per capita personal income, using new panel unit-root procedures. The new developments incorporate non-linearity, asymmetry, and cross-sectional correlation within panel-data estimation. Including nonlinearity and asymmetry finds that 43 states exhibit stationary real per capita personal income whereas including only nonlinearity produces 42 states that exhibit stationarity. Stated differently, we find that two states exhibit nonstationary real per capita personal income when considering nonlinearity, asymmetry, and cross-sectional dependence.
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    Article
    Citation - WoS: 1
    Citation - Scopus: 1
    A Unit Root Test With Markov Switching Deterministic Components: A Special Emphasis on Nonlinear Optimization Algorithms
    (Springer, 2023) Omay, Tolga; Corakci, Aysegul
    In this study, we investigate the performance of different optimization algorithms in estimating the Markov switching (MS) deterministic components of the traditional ADF test. For this purpose, we consider Broyden, Fletcher, Goldfarb, and Shanno (BFGS), Berndt, Hall, Hall, Hausman (BHHH), Simplex, Genetic, and Expectation-Maximization (EM) algorithms. The simulation studies show that the Simplex method has significant advantages over the other commonly used hill-climbing methods and EM. It gives unbiased estimates of the MS deterministic components of the ADF unit root test and delivers good size and power properties. When Hamilton's (Econometrica 57:357-384, 1989) MS model is re-evaluated in conjunction with the alternative algorithms, we furthermore show that Simplex converges to the global optima in stationary MS models with remarkably high precision and even when convergence criterion is raised, or initial values are altered. These advantages of the Simplex routine in MS models allow us to contribute to the current literature. First, we produce the exact critical values of the generalized ADF unit root test with MS breaks in trends. Second, we derive the asymptotic distribution of this test and provide its invariance feature.
  • Thumbnail Image
    Article
    Citation - WoS: 2
    Citation - Scopus: 2
    Re-Examining the Real Interest Rate Parity Hypothesis Under Temporary Gradual Breaks and Nonlinear Convergence
    (Springer Heidelberg, 2023) Hasanov, Mubariz; Omay, Tolga; Abioglu, Vasif
    This paper investigates the real interest parity hypothesis by testing stationarity of real interest rate differentials for 52 countries with respect to the USA. Taking account of the fact that both asymmetric adjustment and gradual temporary breaks may better characterize the dynamics of real interest rate differentials, we propose a new test that allows for two temporary shifts together with asymmetric adjustment towards the equilibrium. We employ the newly proposed test procedure along with the conventional ADF test as well as nonlinear KSS and OSH tests to examine stationarity of real interest rate differentials. Among the main results, we find that the newly proposed unit root test procedure highly outperforms the existing unit root tests in terms of rejecting the null hypothesis of unit root. Our results suggest that real interest rate differentials can be characterized by a stationary process with asymmetric adjustment around gradual and temporary shifts of mean.
  • Thumbnail Image
    Article
    Citation - Scopus: 2
    The Refinement of a Common Correlated Effect Estimator in Panel Unit Root Testing: an Extensive Simulation Study
    (Mdpi, 2024) Omay, Tolga; Akdi, Yilmaz; Emirmahmutoglu, Furkan; Eryilmaz, Meltem
    The Common Correlated Effect (CCE) estimator is widely used in panel data models to address cross-sectional dependence, particularly in nonstationary panels. However, existing estimators have limitations, especially in small-sample settings. This study refines the CCE estimator by introducing new proxy variables and testing them through a comprehensive set of simulations. The proposed method is simple yet effective, aiming to improve the handling of cross-sectional dependence. Simulation results show that the refined estimator eliminates cross-sectional dependence more effectively than the original CCE, with improved power properties under both weak- and strong-dependence scenarios. The refined estimator performs particularly well in small sample sizes. These findings offer a more robust framework for panel unit root testing, enhancing the reliability of CCE estimators and contributing to further developments in addressing cross-sectional dependence in panel data models.