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We quantify the macroeconomic effects of COVID-19 for a small open economy by calibrating a SIR-multi-sector-macro model. We measure sectoral supply shocks utilizing teleworking and physical job proximity, and demand shocks with credit card purchases. Both shocks are also affected from changing infection rates under different lockdown scenarios. Being an open economy amplifies the economic costs through two main channels. First, the demand shock has domestic and external components. Second, the initial shock is magnified due to domestic and international input-output linkages.

Turkey

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Market liquidity is of value to both investors and issuers of securities, and is therefore a crucial factor in asset pricing. For the important asset class of Eurobonds, significant feedback from liquidity to pricing is established, and it is shown that bid-ask spreads (a proxy for market liquidity) and yields are closely related to bond characteristics such as issue volume, time to maturity, the inclusion of collective action clauses, and the jurisdiction of issuance. Debt management offices can choose these characteristics in a way that has economically significant and persistent effects on both liquidity and pricing.

Turkey

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We develop a framework to nowcast (and forecast) economic variables with machine learning techniques. We explain how machine learning methods can address common shortcomings of traditional OLS-based models and use several machine learning models to predict real output growth with lower forecast errors than traditional models. By combining multiple machine learning models into ensembles, we lower forecast errors even further. We also identify measures of variable importance to help improve the transparency of machine learning-based forecasts. Applying the framework to Turkey reduces forecast errors by at least 30 percent relative to traditional models. The framework also better predicts economic volatility, suggesting that machine learning techniques could be an important part of the macro forecasting toolkit of many countries.

Turkey

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Developing a systemic liquidity stress testing tool is challenging due to data constraints and hard-to-model behavioral factors. There has yet to be a uniformly accepted model partly because the nature of systemic liquidity risks differs significantly across countries. This paper offers a simple Excel-based tool to assess the high-level impact of aggregate liquidity stress on the whole economy and gauge its spillover across banks, non-bank financial institutions (NBFIs), and non-financial economic sectors. It primarily uses the balance sheet approach (BSA) data—a sector-aggregate matrix of financial exposure by counterpart—that have become increasingly available for various economies with all income levels. The results can identify systemically important financial linkages to be analyzed further and help calibrate macroprudential measures and a liquidity support framework. When liquidity stress stems from capital outflows, the tool can enrich policy discussion based on integrated policy framework (IPF) and international reserve adequacy perspectives.

Turkey

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OECD360, size temel OECD yayınlarından seçilen en yeni analizleri ve bilgileri sunan bir dergidir. Önemli güncel olaylar çok sayıda grafik ile açıklanmaktadır. Eğitim, istihdam, çevre ile uyumlu ekonomik kalkınma, bölgesel perspektifler, tarım, ekonomik kriz ve toplum ile toplumun gelişimi üzerindeki etkileri: İşte ülkenizin ve tüm uluslararası tablonun durumunu özetleyen 8 ana konu. Her makale, orijinal yayın organından alınan üç grafiğin içerdiği OECD bilgilerini özetleyen iki sayfalık grafikler içermektedir. Statlink’ler sayesinde her grafiğin kaynak verilerini indirebilirsiniz.

Economics --- Turkey