The slowdown of economy and widening of domestic imbalances in China bothers economists and politicians across the globe. We estimate the influence of a negative output shock in China on a number of different economies. We concentrate on China's neighboring countries. We compare the results from the Global VAR model and from the Bayesian VAR models. Also using Bayesian model averaging we search for determinants of Chinese spillovers for the global economy. We find that spillovers are stronger to economies with less flexible exchange rates, a higher share of manufacturing in gross value added and to economies which are larger.
We analyse why loan rates in Poland have diverged from interbank interest rates since the beginning of the global financial crisis. Following Illes et al. (2015) we calculate a weighted average cost of liabilities, which might be considered as a more accurate proxy for a marginal cost of funding for banks than an interbank interest rate. Then, we investigate the interest rate pass-through on bank-level panel data using both measures. We find that an increase in the weighted average cost of liabilities, relative to interbank interest rates, explains some of the increase in credit spreads. However, deterioration of economic outlook, an increase in uncertainty and non-performing loans, as well as tightening of capital regulation have also been at play. That the cost of funding matters for loan rates has important implications for the current discussion on the potency of negative interest rates, as they rather cannot be transmitted to deposit rates, which are the main component of bank funding.
This study investigates whether the effects of monetary policy are amplified through its impact on bank balance sheet strength. Or, in other words, it tests whether the bank lending channel of the monetary transmission mechanism (as reformulated by Disyatat, 2011) works. To this end, panel vector autoregressions with high frequency identification and univariate panel regressions are applied to data for Poland. Counterfactual exercises show that the analysed channel accounts for about 23% of a decrease in lending following a monetary policy impulse. This is another piece of evidence showing that the financial accelerator works in both non-financial and financial sector. In some cases it can make the interplay between monetary and macroprudential policy non-trivial.
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