Mortgage volume and macroeconomic factors: Evidence from Turkey

This paper investigates the impacts of several macroeconomic variables on Turkey's volume of mortgage loans. Johansen cointegration test, vector error correction model, Granger causality tests, variance decomposition, and impulse-response analysis is employed for the econometric analysis to show short and long-run relationships between the variables using time series monthly data from January 2010 to March 2020. Paper results demonstrate that growth of housing credit size negatively correlates with mortgage interest rates, US Dollar/Turkish Lira exchange rate and level of real estate supply. At the same time, there is a positive correlation with house prices. Causal relationships between mortgage volume and macroeconomic indicators are bidirectional for all variables, except for mortgage interest rates. There is a one-way causality relationship from mortgage rates to mortgage loan volume. Econometric analyses show that the recent steep depreciation in the Turkish Lira hurts the Turkish mortgage market. In conclusion, a stable economic environment is essential to build a robust mortgage market.

Turkish Exports Before and After the 2001 Financial Crisis: A Panel Gravity Model

Turkey was subjected to a number of financial shocks after the liberalisation movements in the 1980s. The most devastating of them was the consecutive political and financial crises in late 2000 and early 2001. The absence of political stability and depreciated Turkish Lira devastated the markets. The Turkish government immediately acted against the collapsed economic system and introduced a radical Economic Stability Programme under the supervision of Kemal Dervis¸. The programme has restructured the banking and financial system and improved economic discipline. In this study, we aim to investigate the impacts of the 2001 crisis and the structural changes on Turkish exports. To this end, we estimate a one-way gravity model, using panel data belonging to Turkish exports to 135 World Trade Organization (WTO) member countries, over the period between 1981 and 2015. The augmented model controls for the inter/intra-industry exports, competitiveness, trade agreements, trade unions and additional demographics. We utilised Poisson pseudo-maximum-likelihood (PPML) estimator to account for unobservable time-invariant effects, zero trade, possible heteroscedasticity, and cross-correlation. The results reveals that Turkey has become a free market economy after the liberalisation movements in the early 1980s, and its exports are determined by the same indicators that affect other similar economies; on the other hand, the 2001 crisis has an immediate positive effect on exports through weak Turkish Lira, but this effect turns to negative in the following year. In addition, we find that structural changes in the economic system has a significant effect on exports and help to mitigate the trade-distorting effects of the global financial crisis in 2008. JEL Codes: C33, F13, F14

The Evolutionary Feature of Turkey’s Soft Power in the Middle East, 2011-2020

Today, soft power plays an important role in advancing states’ foreign policy goals. As one of the world’s emerging economic powers, Turkey pays special attention to the development and maintenance of its soft power. This commentary uses a descriptive-analysis approach to address the components of Turkey’s soft power in the Middle East North Africa (MENA) region in the years 2011-2020, the second decade of AK Party governance. Turkey’s soft power during this time period has mainly targeted and become influential in the Muslim-majority countries of the Middle East and Asia. Although certain events, such as the 2016 failed coup, the Gezi Park protests, the Syrian crisis, restrictions on freedom of expression, fluctuations in the value of the Turkish lira, etc., have somewhat tarnished the country’s image, various indicators of Turkey’s soft power demonstrate that it has remained strong in the MENA region during the time span of the present research. Keywords: Turkey, Soft Power, MENA, AK Party

Comparison of plasmapheresis with medical apheresis in terms of efficacy and cost in the acute treatment of hypertriglyceridemia in children with lipoprotein lipase deficiency

Objectives We aimed to compare plasmapheresis and medical apheresis as lipid-lowering therapies in children with familial lipoprotein lipase (LPL) deficiency. Methods The data of 13 patients who were followed up after a diagnosis of LPL deficiency were retrospectively analyzed. Plasma triglyceride, cholesterol, amylase, and lipase values and complications were recorded before and after each patient underwent plasmapheresis or medical apheresis. Results The mean follow-up period of the patients was 99.64 ± 52.92 months in the medical apheresis group and 118 ± 16.97 months in the plasmapheresis group. While the mean triglyceride level before plasmapheresis was 1,875.38 ± 547.46 mg/dL, it was 617 ± 228.28 mg/dL after plasmapheresis. While the mean triglyceride level before medical apheresis was 1,756.86 ± 749.27 mg/dL, it was found to be 623.03 ± 51.36 mg/dL after medical apheresis. Triglyceride levels were decreased by 59.62% with medical apheresis and 65.57% with plasmapheresis. The cost of treatment for medical apheresis was found to be lower compared to plasmapheresis 296.93 ± 29.94 Turkish lira (USD 43.34 ± 4.01) vs. 3,845.42 ± 156.17 Turkish lira (USD 561.37 ± 20.93; p<0.001). Conclusions Although there is no standardized strategy for the acute treatment of hypertriglyceridemia due to LPL deficiency, medical apheresis is a safe and effective treatment with a low risk of side effects. Unlike plasmapheresis, medical apheresis can be performed in any center, which is another important advantage of the procedure.

Are There Any Housing Bubbles in Turkey?

It is very important that the housing market, which meets the most basic need of people is needed for shelter from the past to the present, has a stable structure. The instability structure of the housing market is generally associated with the presence of housing bubbles. The deviation of housing prices from their basic value and not being able to be explained by economic fundamentals leads to the formation of housing bubbles. Housing bubbles can lead to permanent losses, as it may take a long time to return to normal prices. For Turkey as a developing country, it is important to identify an unstable structure in house prices discuss the basic economic factors related to this. After the global increases in housing prices, inflation, and depreciation in the Turkish lira, Turkey has become the country with the highest housing price increases globally in 2020. In the study, the presence of bubbles in the housing market for Ankara, Izmir, Istanbul, and Turkey in general, was investigated by SADF and GSADF unit root tests for the period 2010:01-2021:02. In this context, the study examines the presence of bubbles in housing prices for Ankara, Izmir, Istanbul, and Turkey in general, which are the three cities with the highest price increases. As a result of the study, the presence of bubbles in the housing market has been determined for Ankara, Istanbul, Izmir, and Turkey in general.

New Continuum of High Volatile Currency Spillover During EU-BREXIT

In this study, the researchers observed the impact of Brexit on the Pound and its spillover to other European countries, likely to be affected during that period. The intraday high-frequency hourly return data of chief monies as Great Britain Pound (GBP), Euro (EUR), Danish Krone (DDK), Hungarian Forint (HUF), Turkish Lira (TRY), Swiss Franc (CHF), Swedish Krona (SEK), and Polish Zloty (PLN), for two months and one day, was utilized. The Intraday volatility spillover index approach and a further rolling window technique applied. The analysis of high-frequency data revealed that four currency pairs as TRY/USD, DKK/USD, PLN/USD, and HUF/USD, are highly volatile currencies. However, three pair currencies as GBP/USD, EUR/USD, and SEK/USD, are comparatively lesser volatile. The results and managerial implications reflect preparedness dynamics and proactiveness for a new continuum project that regional transmission effects of volatility spread from one currency to other currencies in the EU during Brexit.

Determination of farmers’ willingness to pay for drought adaptation policies in Şanlıurfa, Turkey

In Şanlıurfa, Turkey, agriculture is the most important source of income. This study aimed to determine Şanlıurfa farmers’ willingness to pay for drought adaptation policies and the factors affecting their willingness. The data were obtained from face-to-face surveys with farmers, selected using a simple random sampling method. According to the results, 50.26% perceive a risk of drought, and 35.86% are willing to pay for adaptation policies. Among those willing to pay, the average amount was 22.63 $/ha (1$=5.676 Turkish Lira), while the average for all participants was 13.55 $/ha. This adds up to a total of 14.363 million $/year for Şanlıurfa. This amount is 1.47% of the annual average income of the participants and is thus within their ability to pay. Age, amount of land farmed, education level, experience, and income were factors affecting willingness to pay. Many respondents, however, were unaware of drought adaptation policies. Because there is concern that drought risk is increasing, awareness needs to be increased, for example through extension services. To the best of our knowledge, this is the first study of its kind, and the results may be useful for creating and applying drought adaptation policies in both Turkey and other regions with similar socio-economic characteristics.

Recent innovation in benchmark rates (BMR): evidence from influential factors on Turkish Lira Overnight Reference Interest Rate with machine learning algorithms

Some countries have announced national benchmark rates, while others have been working on the recent trend in which the London Interbank Offered Rate will be retired at the end of 2021. Considering that Turkey announced the Turkish Lira Overnight Reference Interest Rate (TLREF), this study examines the determinants of TLREF. In this context, three global determinants, five country-level macroeconomic determinants, and the COVID-19 pandemic are considered by using daily data between December 28, 2018, and December 31, 2020, by performing machine learning algorithms and Ordinary Least Square. The empirical results show that (1) the most significant determinant is the amount of securities bought by Central Banks; (2) country-level macroeconomic factors have a higher impact whereas global factors are less important, and the pandemic does not have a significant effect; (3) Random Forest is the most accurate prediction model. Taking action by considering the study’s findings can help support economic growth by achieving low-level benchmark rates.