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ÖgeIssues on labor market in Turkey(Graduate School, 2024-12-27)Education is widely recognized as a fundamental driver of economic development and an effective tool for shaping labor market outcomes and reducing inequalities. In recent years, Turkey has implemented significant educational reforms, such as the 2012 compulsory education reform, which extended mandatory schooling from eight to twelve years and lowered the school starting age. This dissertation examines the multifaceted impacts of this reform, investigating its implications for labor market participation, wage dynamics, and employment trajectories. The second and third chapters of the thesis examine the labor market outcomes of the 2012 reform from interconnected but distinct perspectives. Chapter 2 analyzes the impact of the reform's provision for earlier school enrollment, which implicitly offered mothers a form of public childcare, on maternal labor force participation. Chapter 3 focuses on the potential human capital effects of the reform, exploring how compulsory high school education affects a broad range of labor market variables, including individual wages, employment types, and participation in the formal sector. The fourth and final chapter examines the impact of education on wage inequality, investigating the heterogeneity in returns to education across different wage deciles. Chapter 2 provides the first causal evidence in Turkey on the role of public childcare services in enhancing maternal labor supply. Turkey's 2012 education reform reduced the compulsory school starting age from 72 to 66 months and allowed children aged 60–66 months to start school with parental consent. By lowering the starting age for primary education in public schools, the reform created an implicit form of public childcare that could influence maternal labor market participation. Using data from the Household Labor Force Surveys (HLFS) between 2004 and 2019, the analysis employs a difference-in-differences approach. The treatment group comprises mothers whose youngest child was aged 5–6 years (eligible to enroll due to the reform), while the control group includes mothers whose youngest child was 4 years old (ineligible). Key labor supply measures include labor force participation, employment, working hours, and part-time employment. The findings reveal that the implicit childcare option introduced by the reform is not strong enough to significantly increase maternal labor force participation. While minor increases were observed in some subgroups, these effects were not statistically significant. The limited impact is attributed to the prevalence of informal childcare options (e.g., family and community networks) in Turkey and cultural norms emphasizing parental care for young children, which may restrict the substitutability of public schools for other forms of childcare. These results highlight the need for complementary policies to enhance the effectiveness of educational reforms in reducing barriers to women's labor force participation. Such policies could include expanding access to affordable formal childcare services, addressing cultural norms, and providing targeted support for low-income and less-educated mothers. Chapter 3 examines the labor market impacts of Turkey's 2012 compulsory education reform, particularly its effects on human capital accumulation. By extending the duration of compulsory education to 12 years, the reform aimed to raise educational attainment and deliver long-term benefits for individuals and the economy. Using regression discontinuity design (RDD) with birth month and year as an assignment rule, this chapter analyzes the causal effects of the reform on variables such as high school graduation rates, university enrollment, employment status, formal sector participation, and hourly wages. The analysis draws on household survey data from the Turkish Statistical Institute, covering a wide range of variables. The findings indicate that the reform significantly increased high school graduation rates for women by 7–8%, particularly among cohorts born close to the eligibility cutoff, demonstrating its success in reducing early school dropout rates among girls. However, the reform had no comparable effect on male individuals, suggesting that women faced greater barriers to accessing education prior to the reform. Despite successfully narrowing the gender gap in education, the reform did not achieve similar improvements in women's labor market outcomes. Higher education levels did not translate into short-run gains in employment or wages for women. These results suggest structural barriers in the labor market that limit the absorption of highly educated women, such as limited job opportunities, cultural norms restricting female labor force participation, and mismatches between education curricula and labor market demands. The findings underscore the need for complementary policies to maximize the economic benefits of educational reforms, such as expanding childcare services and implementing targeted employment programs for women. Chapter 4 provides a comprehensive analysis of how education reshapes the wage structure in Turkey, with a particular focus on its effects on wage inequality. By examining the impacts of education on wages across different ability groups and over time, this chapter offers new insights into the dynamics of wage inequality. The analysis focuses on both between-group inequality (wage differences between individuals with varying education levels) and within-group inequality (wage disparities among individuals with the same education level). Using quantile regression (QR) and instrumental variable quantile regression (IVQR) methods with data from HLFS, the findings reveal that education exacerbates within-group wage inequality. Highly educated individuals disproportionately benefit from education, which is attributed to the complementarity between education and unobservable abilities. Individuals with higher ability levels derive greater returns from additional education, widening wage disparities among those with similar educational backgrounds. Furthermore, the effects of education on wage inequality have evolved over time. Since 2012, the degree of complementarity between education and unobservable abilities has increased, leading to higher returns for highly able individuals and relatively smaller benefits for lower-ability groups. The results highlight the need for policies that address structural barriers in the labor market and align education with labor market demands. Expanding access to childcare services, developing targeted employment programs for women, and aligning curricula with market needs are essential steps to ensure that increased educational attainment translates into reduced inequalities and improved economic outcomes.
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ÖgeSign predictability of intraday price returns to formulate appropriate trading strategies with optimum set of equities(Graduate School, 2024-02-08)The prediction of stock market returns has been a focused research area for computational finance, time-series econometrics, and computer science researchers. Typically, market participants rely on technical and fundamental analyses to make predictions, determining their buy or sell strategies based on these assessments. However, scholars in finance and economics have remained skeptical about the predictability of stock returns, particularly in efficient markets. Besides the stock market earnings, a literature on capital martket's direciton predcition has been emerged. Studies in the field of computer science also supported this research area with the help of machine lerning, deep lerning and artifical neural network techniques. Empirical studies in applied economics focuses on efficient market hypotesis whereas computer science studies mostly compares prediction performances of diffirent techniques. In this thesis, closing price direction of 26 stocks in 5 miutes intervals predictited. Only the higly liquid stocks existed in the BIST 30 index for the entire year of 2018 are examined. The data includes 251 trading days and 84 data nodes for each day. Transaction costs are considered to be 2.5 bps and 15 bps is determined as the treshold for a direction signal. If 5 minute closing price of an equity went up by 0.15 percent, it is tagged as "positive" and the opposite as "negative" and the inbetween in considered "steady" to achieve economically significant results. A significant data source—Borsa Istanbul's 'data analytics' information distributed through data vendors—is utilized. There are 39 analytics providing order book statistics regarding for last 1 minute, 5 minute and intraday periods. Initially, a specific method for extracting valuable insights from the complex raw data of Borsa Istanbul is described and implemented. Subsequently, standard scaling and dimension reduction methods, such as Principal Component Analysis, are employed to enhance efficiency. Seven different machine learning algorithms, Logistic Regression, K-Nearest Neighborhood, Support Vector Machines with radial and sigmoid kernels, Naïve Bayes, Decision Tree, Random Forest, are compared. All the methods trained with former 95 percent and tested using the last 5 percent of the complete dataset of the year 2018. The performance levels of each method for twenty-six highly liquid stocks are assessed in terms of Macro Averaged F-Measures. Furthermore, in this thesis, the effectiveness and significance of machine learning algorithms are compared using confidence intervals calculated from the confusion matrices for Macro Averaged F-Measures—an innovative approach within the economics and finance literature. Additionally, the use of three classes for stock price directions 'positive ,' 'negative" and 'steady' rather than just two is a rare aspect in academic studies, aligning more closely with data analytics practitioners' methodologies. Concerning the 5-minute lagged data, a statistically significant predictability is found in nine of the equities. K-Nearest Neighbors, Decision Tree and Random Forest yielded significant predictions. Naïve Bayes and SVM-sigmoid achieved better for a few equites while Logistic Regression and SVM-rbf not for any. However, for the 10 and 60-minute lagged data, predictability remains only in four and none of the equities, respectively. Essentially, markets assimilated Borsa Istanbul's data over time for those equities. Moreover, economic gains for the nine equities are analyzed with algorithms not allowing short selling and allowing short selling, based on these predictions. 'Positive", 'negative' and 'steady' signs treated as 'buy', 'sell' and 'keep the position' signals in the first scenerio while 'steady' allowed as the 'short-sell' signal in the second scenerio. Those scnerios are compared with passive buy and hold strategy and it has been revealed that determined trading strategies depending on the machine lerning algorithms performs higher earnings or less losses for KOZAA, KOZAL and KRDMD stocks when short selling is not allowed. If short selling is allowed TKFEN is also added to this list. Test period performances of the determined trading strategies and the stocks' own price performances are graphically illustrated in the thesis. Since four equities are observed to generate higher economic gains through machine learning-supported trading strategies compared to their own price performances, these findings for those wquities indicate, within the framework of the 'Efficient Market Hypothesis,' a lack of 'Semi-strong-form efficiency.' The methods and techniques used in this study such as creating tree dimensional confusion matrices, determining standard deviation and confidence intervals for MA F-Measures, and benchmarking them with a theorical MA F-Measure and developing trading strategies with three signals will support further research
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ÖgeMacro stress testing in Turkish banking sector and tail dependence in financial, energy and commodity markets(Graduate School, 2024-02-07)This dissertation is a collection of three chapters on the resilience of Turkish banking system, nonlinear tail dependence from U.S. agricultural markets to Turkish agricultural markets, and nonlinear tail dependence from energy commodities to agricultural commodities. Financial institutions and financial markets exert significant effect on economies due to their critical role. When operating efficiently, they ensure the growth and stability of economies. Nevertheless, inefficiencies or vulnerabilities to shocks in these institutions and markets can result in systemic crises. For instance, deteriorations in the indicators of banks not only affect the banking system but also have repercussions across the entire economy through a feedback mechanism. As emphasized in the literature, higher nonperforming loans impede the real economy by slowing economic activity and credit growth. Financial markets, on the other hand, inherently contain the risk of financial contagion or spillover effects. While offering investment opportunities and facilitating price discovery, which contributing to wealth accumulation and economic advancement, they possess the potential to trigger joint collapses and substantial financial losses in the event of a shock. Thus, examining the vulnerabilities of financial institutions and the interdependence among various financial markets is exceedingly crucial, particularly considering the complexity of this interdependence. Accordingly, this dissertation evaluates the resilience of the Turkish banking system, the nonlinear dependence from US agricultural markets to Turkish agricultural markets, and the nonlinear dependence from energy commodities to agricultural commodities in separate chapters. The first chapter focuses on stress testing applied to conventional and participation banks within the Turkish banking sector. It employs the nonperforming loan ratio (NPL) as a pivotal stress variable. To conduct stress testing, the study uses an innovative additive nonparametric quantile regression technique. The objective is to assess how macroeconomic variables—exchange rates, interest rates, unemployment rates, and the public debt to GDP ratio—affect the NPL. The analysis covers monthly observations spanning from January 2005 to February 2020. Additionally, the chapter conducts scenario analyses based on various distributions and examines adverse scenarios concerning extreme tail values of macroeconomic variables. The study reveals the substantial influence of these macroeconomic factors on NPL, emphasizing the importance of stable exchange rates, controlled unemployment rates, and managed public debt. Furthermore, it highlights the necessity for tailored policies concerning different bank types, given observed disparities. The second chapter examines the relationship between U.S. and Turkish agricultural commodity markets, and also investigates the nonlinear tail dependence from Brent oil, USD/TRY currency rate, and overnight interest rate to Turkish agricultural commodities. It employs a novel nonlinear measure of tail dependence to explore the connection between these markets. The study analyzes the mean and tail dependence between the markets, considering both lower and upper continuum of quantiles. Additionally, it evaluates significant events such as the Turkish Mercantile Exchange (TMEX) launch and the Ukraine war. The dataset set contains daily returns from January 5, 2016, to May 31, 2022. To ensure robustness, a nonparametric test for Granger causality in distribution is employed. The findings reveal significant and persistent tail and mean dependence from U.S. agricultural futures to Turkish spot markets. This emphasizes the necessity for enhanced information exchange between spot and derivatives markets to strengthen market efficiency. The chapter also addresses the importance of monitoring interconnections and contagion risks among markets, especially during challenging market conditions. The third chapter investigates the impact of energy commodities—Brent oil, natural gas, and gasoline—on agricultural commodities. It employs a nonlinear measure of tail dependence to analyze the relationship across three distinct periods: pre-Covid-19, during Covid-19, and post-Covid-19. The dataset comprises daily records from June 1, 2017, to June 9, 2023, covering different market periods. Additionally, the chapter utilizes cross-quantilogram analysis and the nonparametric test for Granger causality in distribution for robustness checks. The research reveals significant and persistent lower and upper tail dependence between energy and agricultural commodities across each period. The findings demonstrate nuanced and dynamic tail dependence patterns, indicating asymmetric risk transmissions under varying market conditions. These results have critical implications for effective market strategies, efficient portfolio management in agricultural commodity markets, and the need for resilient regulations during extreme events.
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ÖgeThe digital divide in Turkey(Graduate School, 2023-04-05)Information and communication technologies (ICT), which broadly include telecommunications, mobile telephony, the Internet, and various Internet-enabled devices, have permeated most aspects of life by offering new and more efficient ways for people to communicate, access information, and learn. With applications in education, banking, e-commerce, health, and government services, among other areas, ICT are a major force behind economic growth and productivity, connecting people to essential services and jobs while enabling businesses to operate. The digital divide describes the uneven distribution of ICT in society. At a high level, the digital divide is the gap between those who have and do not have access to the Internet. However, the digital divide is not a binary but multifaceted and includes many factors such as connectivity, access to equipment, affordability, quality of service, motivation to use the technology, digital skills, and so on. Therefore, the digital divide encompasses various Internet-related challenges, which results in different types (levels) of digital inequality. The digital divide literature categorized those challenges as follows: differences in access (first-level digital divide), usage and digital skills (second level digital divide), and outcomes of Internet use (third level digital divide). These digital gaps exist at the international level as well as within a country. Often these gaps fall along other social inequalities in a country – that is, the different levels of the digital divide usually reflect the gaps between individuals from different demographic backgrounds and at different socioeconomic levels with regard to their opportunity and ability to access and utilize ICT. This thesis empirically examines the different aspects of the digital divide in Turkey. It explores the demographic and socioeconomic determinants of the first level and second level of digital divide in Turkey and analyzes the data that substantiates digital inequalities between years 2008-2020. Digital transformation and technological advancements in ICT offer tremendous opportunities for countries, especially for emerging economies. However, the full potential of digital advancements cannot be achieved by focusing solely on supply-side policies such as investing in infrastructure deployment. Despite increased Internet penetration rates, Turkey has failed to create a digitally inclusive society and risk missing out on the benefits of digitization. One of the leading factors contributing to this problem is the lack of effective demand-side solutions mitigating the digital divide. The results of this thesis suggest that significant disparities persist between different social groups in Turkey in terms of Internet access and Internet usage patterns. The findings of this thesis point out the target groups of first priority to address the first level and second level digital divide in Turkey. We can conclude from the results that special initiatives and programs are required to increase widespread adoption of the Internet. Those initiatives and programs should be designed and implemented with a participatory approach, targeting the high priority groups: women, older citizens, citizens with lower household income, citizens with low educational background, homemakers, and retired people, as well as citizens of the Northeast Anatolia, Central East Anatolia, Southeast Anatolia and West Black Sea regions of Turkey in particular, while considering the factors that make Internet access and use difficult.
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ÖgeNetwork neutrality in the internet as a two sided market constituted by congestion sensitive end users and content providers(Graduate School, 2023-03-01)In this paper, I envision a two-sided market mediated by a monopolistic internet service provider, ISP. The ISP provides end-users internet access and carries content providers' (CPs') data packages on its network. I compare the case where network neutrality is strictly practiced with the case where the ISP can "throttle" the traffic of certain content providers. In the model, for simplicity, a single CP is exposed to throttling, while the other CPs, which are part of a continuum, are not. I then study the implications of the violation of network neutrality on total data consumption, congestion, and capacity investment. Under network neutrality, the decision variables of the ISP are end-user price and network bandwidth. I found that, in equilibrium, because of the monopolistic nature of the market is greater than the price under competitive equilibrium, and is lower than its socially optimum value. Thus, under neutrality, the ISP undersupplies both the capacity and the data. Under discrimination, the ISP is allowed to charge an access fee on unit bandwidth to one of the content providers (the discriminated CP). To reflect a scenario of great practical value, I choose the discriminated CP from one of the big OTTs such as YouTube, Instagram, Facebook, Netflix, etc. In this setting, to access the network, the discriminated CP needs to buy bandwidth from the ISP. However, the bandwidth bought by the discriminated CP is not for exclusive usage of the discriminated CP. It rather acts as an upper bandwidth limit for the discriminated CP. Under discrimination, the decision variables of the ISP are the end-user price, the network bandwidth, and the bandwidth price. I found that when allowed the ISP always prefers to deviate from network neutrality by charging a positive price for bandwidth. Also, the ISP sets just enough to keep the discriminated CP in the market. Comparing the equilibrium outcomes, I show that under discrimination, the ISP charges a lower price to end-users. However, the discrimination also leads to less network bandwidth installed. Both the lower end-user price and the lower network bandwidth contribute to the congestion. Thus, under discrimination, the congestion is higher than under neutrality. Considering its adverse effects on the network bandwidth and congestion, although the end-user price is lower under discrimination, I recommend that the network neutrality principle should not be abolished.