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This study re-investigates the money supply determination process for Japan. The methodology of this study, which differs from previous studies, is constructed on the assumption of potential nonlinear (asymmetric) relations between money supply and monetary base via money multiplier. To this aim, the nonlinear autoregressive distributed lag (ARDL) model by Shin, Yu and Greenwood-Nimmo, (2014) is applied. This model allows us to examine the endogeneity and exogeneity of the money supply determination process via the linkage of the money multiplier under expansionary and contractionary monetary policies of the Bank of Japan (BOJ) separately in a nonlinear manner. The main findings of the study indicate that the money supply determination process is endogenous with an unstable money multiplier for Japan for M1. However, this endogeneity in the BOJ’s contractionary monetary policy is more than its expansionary policy. This can be interpreted that the BOJ’s expansionary monetary policy has more of a determining role on money supply determination than its contractionary monetary policy. Additionally, the same findings indicate that the BOJ has more power to determine M1 than M2. This result can be interpreted that when the measure of money broadens the BOJ’s controllability on money supply decreases. In contrast, in our Canadian study (Ongan and Gocer, 2019) with the same nonlinear ARDL model, we concluded that the Canadian central bank (BOC) was able to determine money supply exogenously for M1, unlike the Japanese central bank (BOJ), and the money multiplier was stable for Canada.

Cryptocurrencies, such as Bitcoin, are one of the most controversial and complex technological innovations in today's financial system. This study aims to forecast the movements of Bitcoin prices at a high degree of accuracy. To this aim, four different Machine Learning (ML) algorithms are applied, namely, the Support Vector Machines (SVM), the Artificial Neural Network (ANN), the Naive Bayes (NB) and the Random Forest (RF) besides the logistic regression (LR) as a benchmark model. In order to test these algorithms, besides existing continuous dataset, discrete dataset was also created and used. For the evaluations of algorithm performances, the F statistic, accuracy statistic, the Mean Absolute Error (MAE), the Root Mean Square Error (RMSE) and the Root Absolute Error (RAE) metrics were used. The t test was used to compare the performances of the SVM, ANN, NB and RF with the performance of the LR. Empirical findings reveal that, while the RF has the highest forecasting performance in the continuous dataset, the NB has the lowest. On the other hand, while the ANN has the highest and the NB the lowest performance in the discrete dataset. Furthermore, the discrete dataset improves the overall forecasting performance in all algorithms (models) estimated., Comment: 14 pages, 2 figures and 15 tables

This study examines whether trade policy-related uncertainties, scaled by TPU index, and the COVID-19 pandemic affect Japan’s bilateral commodity trade balance with the U.S concerning 60 industries. To this end, the nonlinear ARDL (autoregressive distributed lag) model is applied. Empirical findings of the disaggregated data model indicate that while changes in Japan’s TPU index have significant, either improving or worsening, impacts on this balance concerning 23 industries, changes in US TPU index have impact on only 32 industries. Additionally, based on the behaviors of Japanese and US consumers through their import demands, it can be interpreted that neither of them is uncertainty-sensitive to each other’s products and they continue to buy these products even if both countries’ TPU indexes keep rising. Another expected empirical finding is that the COVID-19 pandemic worsens the trade balances of Japan for different industries shown in the tables.

We investigate the validity of the environmental Kuznets curve (EKC) hypothesis for the NAFTA countries. In this investigation, we approach this hypothesis from a different methodology and propose employing the ARMEY curve hypothesis since the mathematical-functional propositions of both hypotheses were constructed on the same inverted U-shaped relationships. Thus, for the first time, it can be interpreted that the EKC hypothesis is empirically tested through a transmission mechanism of the ARMEY curve hypothesis in a single composite model. Therefore, this approach makes our study different from all empirical studies in the relevant literature. We apply the Augmented Mean Group (AMG) estimator to this aim. Empirical findings indicate that the ARMEY curve hypothesis was verified only for the USA. However, this new approach proposed in this study cannot test the EKC hypothesis through the ARMEY curve model for any NAFTA country since this approach requires verification of the ARMEY curve hypothesis and a significant composite model for the same NAFTA country. If our composite model was significant, it might make it possible to numerically determine a maximum real GDP per capita level that would minimize or maximize CO2 emission levels for the USA. Therefore, this study introduces-proposes this new methodology as an alternative way of testing the EKC hypothesis in the relevant literature for future empirical studies.

This study examines the asymmetric effects of uncertainties in monetary policy on the demand for money in Greece. In doing so, it introduces and uses the monetary policy uncertainty (MPU) index, which can probably be a very appropriate and robust explanatory variable in demand-for-money models. Therefore, this study with this index differs from previous empirical studies that use conventional uncertainty-based independent variables. Empirical findings of both models indicate that changes in the MPU index have significant effects on Greek money demand. Additionally, compendious inferences of the nonlinear model for the Greek people’s financial preferences are as follow as: (i): Greek people invest more in alternative financial instruments and/or spend their money rather than hold (demand) it when the MPU index rises, (ii): Greek people’s money demand in both increases and decreases in the MPU index is predominantly determined by longer-term bond rate changes.

This study investigates the relations between COVID-19-related stay-at-home-tendencies and various health insurance coverages of people across US states. To this aim, the K-means clustering and panel regression analysis with cross-sectional dependence are applied. The main empirical finding reveals that various health insurance coverages have different level impacts on COVID-19-related stay-at-home-tendencies. People who are uninsured tend to stay at home the most as compared with people with private, Medicaid, Medicare and military health insurance coverages. As a result, it may be interpreted that uninsured people have serious concerns about affording healthcare costs associated with COVID-19 and, thereby, stay at home. However, people with private health insurance coverages tend to stay at home the least. This may also lead to the interpretation that people with private health insurance coverages feel safer and better protected against the rising risks of this pandemic outside their homes.

This study reconsiders the Fisher effect for the UK from a different methodological perspective. To this aim, the nonlinear ARDL model recently developed by Shin et al. (2014), is applied over the periods of 1995M1-2008M9 and 2008M10-2018M1. This model decomposes the changes in original inflation series as two new series: increases and decreases in inflation rates. Hence, it enables us to examine the Fisher effect in terms of increases and decreases in inflation separately. The empirical findings support asymmetrically partial Fisher effects for the UK in the long-run only for the first period. Additionally, this study attempts to describe and introduce a different version of the partial effect concept for the first time for the UK.

Bu çalışmada, İngiltere ve temel ticaret ortağı 17 ülke arasındaki ikili ticaret üzerinden J-eğrisi hipotezi araştırılmıştır. Bu amaçla, 1981Q1-2015Q1 dönemi verileri ve Doğrusal Olmayan Gecikmesi Dağıtılmış Otoregresif (NARDL) eş-bütünleşme yaklaşımı kullanılmıştır. Bu çalışmanın sonuçları, İngiltere ve 17 ticaret ortağı arasındaki ticaret için J-eğrisi hipotezinin geçerli olmadığını göstermektedir. Ayrıca, bu çalışma sonuçlarına göre, İngiliz sterlinin değerindeki azalış veya artış, İngiliz ticaret hadlerinde kısa dönemde asimetrik etkiler yaratmaktadır. Dolayısıyla bu çalışma, İngiltere’de yapılan 2016 Avrupa Birliği Üyeliği Referandumu sonrası, İngiliz sterlininin değerinde gerçekleşen dalgalanmaların kısa ve uzun dönemde İngiliz ticaret hadlerine etkisini ortaya koymaktadır., In this study, we investigate the validity of the J-curve hypothesis based on the bilateral trade models between the UK and its 17 main trading partner countries over the period of 1981Q1-2015Q1, by applying Nonlinear Autoregressive Distributed Lag (NARDL) cointegration approach. The results of this study suggest no evidence supporting the J-curve hypothesis between the UK and any of its 17 trading partners. We also find that depreciations and appreciations in value of the GBP have asymmetric effects on the UK’s trade balances in the short-run. Therefore, the results of this study have potential to shed light on both short run and long run consequences of the recent fluctuations of the GBP with respect to the trade balances after the UK’s EU membership referendum in 2016.

This study re-tests the EKC hypothesis for US states with a new methodology that differs from all previous empirical studies using traditional EKC models. To this aim, this methodology, for the first time, unifies two seemingly different but strongly interrelated hypotheses (models), namely the Armey curve (AC) and traditional EKC models, into one single composite model. The rationale for creating this composite model is twofold. First, the functional propositions of these two hypotheses are depicted with inverted U-shaped curves. Second, they also have economically interrelated-causal relationships. This means that rising government spending (through the AC hypothesis) increases real GDP per capita (RGDPPC) and, consequently, increases in RGDPPC (through the EKC hypothesis) increase CO2 emissions. The composite model created may also allow US state policymakers to determine a single maximum spending level that will maximize or minimize CO2 emissions. Empirical findings indicate that the composite model is capable of testing the EKC hypothesis for 7 US states. Additionally, for 7 US states, maximum spending level was calculated to be around 15% of their RGDPPCs. Hence, with this calculated spending level, policymakers of these states may be able to determine-adjust their golden spending levels so as not to cause environmental degradation and declines in GDP.

This paper analyzes the legitimacy of the Environmental Kuznets Curve (EKC) hypothesis for a group of seven (G7) countries over the period 1995&ndash, 2015. In addition to testing the EKC speculation, the authors also would like to understand the ways in which increases in renewable energy consumption and the international tourism receipt affect the CO2 emissions in G7 countries, because the energy and tourism sectors may have considerable direct impacts on CO2 emissions. In this investigation, a panel bootstrap cointegration test and an augmented mean group (AMG) estimator were applied. The empirical findings indicate that the tourism-induced EKC hypothesis is valid only for France. Additionally, it was detected that a rise in renewable energy consumption has a negative (reduction) impact on CO2 emissions in France, Italy, the UK, and the US. However, an increase in the receipt of international touristm has a positive (additional) impact on Italy&rsquo, s CO2 emissions. Hence, this country&rsquo, s decision-makers should re-review their tourism policy to adopt a renewable-inclusive one for sustainable tourism and the environment.

Bu çalışmaUluslararası Atletizm Federasyonu tarafından düzenlenen Dünya AtletizmŞampiyonasının ev sahibi şehirdeki lise öğrencileri üzerinde bu spora karşı birfarkındalık yaratıp yaratmadığını ortaya koymayı amaçlamaktadır. Bunun içinturnuva öncesi ve sonrası olmak kaydıyla toplam 5265 öğrenci ile bir anketçalışması gerçekleştirilmiştir. Sorular bu spora öğrencilerin aktif olarakkatılımcı ve izleyici olmaları durumuna göre iki grupta oluşturulmuştur. Çalışmanın en temel bulgularından birisiortaya koymaktadır ki öğrencilerin atletizm etkinliklerine katılmasına en büyükiki engel atletizme ilgilerinin ve zamanlarının olmayışıdır. Ayrıca, anketekatılan öğrencilerin %25’inden fazlası atletizm tesissilerinin eksikliğinden veatletizm etkinliklerine nasıl katılacaklarını bilmeyişinden dolayıkatılamadığını bildirmiştir. Bir diğer önemli bulgu ise atletizme ilgisi olankız öğrencilerin atletizmi öğrenme ve katılma isteklerinin erkek öğrencilerdençok daha fazla olmasıdır. Ayrıca söz konusu bu turnuvanın ankete katılanöğrenciler üzerinde bu spora ait farkındalıklarını arttırdığı gözlemlenmiştir.Dolayısıyla bu noktada yerel ve hükümet yöneticileri gençlerin sportiffaaliyetler katılımlarını arttırmak için bu tür turnuvaların bölgelerinde çokçadüzenlenmesini sağlamalıdırlar., Thisstudy aims to analyze the effect of theIAAF World Indoor Track and Field Championships on high school students’awareness of the sports of track and field in the host city, Istanbul Turkey.Descriptive statistics and logistic regression wereapplied to the data collected from total 5,262 high school studentsbefore and after the event. Two groups of questions were asked of the students as participants and spectators.The main empirical findings indicate that the most significant factors that inhibit high school students’ ability toparticipate in track and field activities are lack of interest and time. Also, morethan 25 percent of the students said that factors keep them from participating intrack and field are lack of knowledge of how to participate and lack of accessto a track/facility. Additionally, it wasobserved that female students who are interested in track and field would like to learn and participate in theseactivities more so than their male peers. Another significant finding is that this tournament considerably increasedawareness of both female and male students. At this point, this study tries todraw attention to the importance of sponsoring this kind of sports organizationfor students and encouraging local and governmental sports authorities to hostevents in their cities.

This paper aims to investigate the validity of the J-curve hypothesis between Brazil and the USA using quarterly data for the period of 1981Q1- 2015Q1. To achieve this aim, the vector error correction (VEC) with cointegration, NARX (non-linear autoregressive exogenous) and ANFIS (adaptive neuro-fuzzy inference system) models are separately applied to strengthen this investigation. NARX and ANFIS, as artificial neural networks (ANN) models, were used for the first time in this study to test the validity of the J-curve hypothesis. It was found that the real exchange rate and income, as the independent variables, and the trade balance between Brazil and the USA, as the dependent variable, are cointegrated in the long-run. The empirical findings of all testing models examined in this study indicate that the J-curve hypothesis is not valid between Brazil and the USA. The real depreciations of the Brazilian currency do not make a positive contribution to the trade balance for Brazil.

Far better and more efficient teaching and understanding of economics, which predominantly encompasses human behaviors, is of the utmost importance. Both the correctness of personal financial decisions that individuals will make and the success of economic policies implemented and to be implemented at the macro level, require a through knowledge of economics and its fundamental rules. This study is an attempt to attract attention to the importance of utilizing literature, theatre, cinema, and humor, which are matters as everyday as economics, rather than employing classical presentation methods in economics education, in order to render economics more enjoyable, understandable, and appealing to college students.

This study aims to investigate the causal relationships between the economic policy uncertainty (EPU) index and the US stock indices the S&P 500, Dow Jones and Nasdaq 100 over the period of 1985M10–2016M12. To this aim, it is applied both linear causality and the nonlinear rolling window causality tests. The long-run analyses are also applied to reveal the elasticities of the US stock indices. The empirical findings indicate that both the linear and the nonlinear approaches support the evidence of causal relationships from the US EPU index to all the US stock indices. Additionally, it is also found some evidences of causal relationships from these three US stock indices to the US EPU index especially between 2008–2013 in the latest financial crisis and in the late 2016. The results indicate that the Nasdaq 100 index is mostly affected from the US EPU index both in the short and long-runs.