Externally funded research projects
Internally funded research projects
Evaluation of macroeconomic uncertainty
OPUS 8 project No. 2014/15/B/HS4/04263, UMO-2014/15/B/HS4/04263
(NCN, National Council of Science, Poland)
Duration: 04.08.2015 – 03.08.2018
Wojciech Charemza, Vistula University (Principal Investigator)
Svetlana Makarova, Vistula University
Anna Zamojska, University of Gdańsk, Poland
Main output and conference presentations so far:
Makarova, S. ‘European central bank’s footprints on the inflation forecast uncertainty’, Economic Inquiry (forthcoming). Presented at 4th International Symposium in Computational Economics and Finance, Paris, April 2016
The finding of the paper shows the relative effectiveness of the ‘one size fits all’ policy of the European Central Bank. The paper provides strong evidence in favour of this by testing whether the monetary policy effects (footprints), found in inflation uncertainty converge to a common level. These footprints are measured as the fraction of the estimated policy-induced reduction in this uncertainty. The testing was conducted by applying a bootstrap-type test in a regression of the rate of growth of these fractions on their initial values, computed for 16 euro area countries.
Charemza, W., C Díaz and S. Makarova, ‘Quasi ex-ante inflation forecast uncertainty’, presented at the Econometric Research in Finance Workshop, SGH, Warsaw, September 2017; 10th International Conference on Computational and Financial Econometrics (CFE 2016) Seville, December 2016.
We argue that the ex-post measure of forecast uncertainty developed from the distribution of inflation forecast errors differs from the corresponding ex-ante measure because of the impact of monetary policy decisions. We derive a proxy for inflation uncertainty, called quasi ex-ante forecast uncertainty, which is to an extent free from the effects of monetary policy decisions. This proxy is computed using the parameters of a weighted skew normal distribution fitted to forecast errors. This in turn leads to the development of the measure of the compound strength of monetary policy and the uncertainty ratio, which shows the relative impact of monetary policy on reducing inflation forecast uncertainty. A nonlinear relationship is found between compound strength and the measures of the independence and transparency of central banks for 38 countries. The quasi ex-ante forecast uncertainty is used for computing the inflation forecast term structure for the BRICS countries (Brazil, Russia, India, China and South Africa), the UK and the US. It is concluded that the greatest policy effect in reducing inflation forecast uncertainty is for countries which conduct either well-established and relatively pure inflation targeting policy, like South Africa and the UK, or clandestine inflation targeting, like India and the US. The smallest reduction is for countries like China and Russia that mix inflation targeting with exchange rate stabilisation.
Charemza, W. S. Makarova and Y. Wu, ‘Probability of short-term deflation episodes and their expected duration: the case of China’, 4th International Symposium in Computational Economics and Finance in Paris, April, 2016.
The paper proposes a simulation-based approach to multi-step probabilistic forecasting, applied for predicting the probability and duration of negative inflation. The essence of this approach is in counting runs simulated from a multivariate distribution representing the probabilistic forecasts, which enters the negative inflation regime. The marginal distributions of forecasts are estimated using the series of past forecast errors, and the joint distribution is obtained by a multivariate copula approach. This technique is applied for estimating the probability of negative inflation in China and its expected duration, with the marginal distributions computed by fitting weighted skew-normal and two-piece normal distributions to ARMA ex-post forecast errors and using the multivariate Student-t copula.