Evaluating Changes in the Monetary Transmission Mechanism in the Czech Republic

We investigate the evolution of the monetary policy transmission mechanism in the Czech Republic over the 1996-2010 period by employing a time-varying parameters Bayesian vector autoregression model with stochastic volatility. We evaluate whether the response of GDP and the price level to exchange rate or interest rate shocks changes over time, with a focus on the period of the recent financial crisis. Furthermore, we augment the estimated system with a lending rate and credit growth to shed light on the relative importance of financial shocks for the macroeconomic environment. Our results suggest that output and prices have become increasingly responsive to monetary policy shocks, probably reflecting financial sector deepening, more persistent monetary policy shocks, and overall economic development associated with disinflation. On the other hand, exchange rate pass-through has weakened somewhat over time, suggesting improved credibility of inflation targeting in the Czech Republic with anchored inflation expectations. We find that credit shocks had a more sizeable impact on output and prices during the period of bank restructuring with difficult access to credit. In general, our results show that financial shocks are less important for the aggregate economy in an environment of a stable financial system.Monetary policy transmission, sign restrictions, time-varying parameters.

How to Solve the Price Puzzle? A Meta-Analysis

The short-run increase in prices following an unexpected tightening of monetary policy represents a frequently reported puzzle. Yet the puzzle is surprisingly easy to explain away when all published models are quantitatively reviewed. We collect about 1,000 point estimates of impulse responses from 70 articles using vector autoregressive models and present a simple method of research synthesis for graphical results. We find some evidence of publication selection against the price puzzle. Our results suggest that the reported impulse responses depend systematically on the study design: when misspecifications are filtered out, the average impulse response shows that prices decrease soon after a tightening. The long-run response of prices to monetary policy shocks depends on the characteristics of the economy.Meta-analysis, monetary policy transmission, price puzzle, publication selection bias.

Dissent voting behavior of central bankers: what do we really know?

Abstract We examine the determinants of the dissent in central bank boards’ voting records about monetary policy rates in the Czech Republic, Hungary, Sweden, the U.K. and the U.S. In contrast to previous studies, we consider about 25 different macroeconomic, financial, institutional, psychological or preference-related factors jointly and deal formally with the attendant model uncertainty using Bayesian model averaging. We find that the rate of dissent is between 5% and 20% in these central banks. Our results suggest that most regressors, including those capturing the effect of inflation and output, are not robust determinants of voting dissent. The difference in central bankers’ preferences is likely to drive the dissent in the U.S. Fed and the Bank of England. For the Czech and Hungarian central banks, average dissent tends to be larger when policy rates are changed. Some evidence is also found that food price volatility tends to increase the voting dissent in the U.S. Fed and in Riksbank.monetary policy, voting record, dissent

Early Warning Indicators of Economic Crises: Evidence from a Panel of 40 Developed Countries

Using a panel of 40 EU and OECD countries for the period 1970-2010 we construct an early warning system. The system consists of a discrete and a continuous model. In the discrete model, we collect an extensive database of various types of economic crises called CDEC 40-40 and examine potential leading indicators. In the continuous model, we construct an index of real crisis incidence as the response variable. We determine the optimal lead employing panel vector autoregression for each potential indicator, and then select useful indicators employing Bayesian model averaging. We re-estimate the resulting specification by system GMM and, to allow for country heterogeneity, additionally evaluate the random coefficients estimator and divide countries into clusters. Our results suggest that global variables are among the most useful early warning indicators. In addition, housing prices emerge consistently as an important source of risk. Finally, we simulate the past effectiveness of several policy instruments and conclude that some central bank tools (for example, reserves) could be useful in mitigating crisis incidence.Bayesian model averaging, dynamic panel, early warning indicators, macroprudential policies, panel VAR.

Dissent voting behavior of central bankers: what do we really know?

Abstract We examine the determinants of the dissent in central bank boards’ voting records about monetary policy rates in the Czech Republic, Hungary, Sweden, the U.K. and the U.S. In contrast to previous studies, we consider about 25 different macroeconomic, financial, institutional, psychological or preference-related factors jointly and deal formally with the attendant model uncertainty using Bayesian model averaging. We find that the rate of dissent is between 5% and 20% in these central banks. Our results suggest that most regressors, including those capturing the effect of inflation and output, are not robust determinants of voting dissent. The difference in central bankers’ preferences is likely to drive the dissent in the U.S. Fed and the Bank of England. For the Czech and Hungarian central banks, average dissent tends to be larger when policy rates are changed. Some evidence is also found that food price volatility tends to increase the voting dissent in the U.S. Fed and in Riksbank

Dissent voting behavior of central bankers: what do we really know?

Abstract We examine the determinants of the dissent in central bank boards’ voting records about monetary policy rates in the Czech Republic, Hungary, Sweden, the U.K. and the U.S. In contrast to previous studies, we consider about 25 different macroeconomic, financial, institutional, psychological or preference-related factors jointly and deal formally with the attendant model uncertainty using Bayesian model averaging. We find that the rate of dissent is between 5% and 20% in these central banks. Our results suggest that most regressors, including those capturing the effect of inflation and output, are not robust determinants of voting dissent. The difference in central bankers’ preferences is likely to drive the dissent in the U.S. Fed and the Bank of England. For the Czech and Hungarian central banks, average dissent tends to be larger when policy rates are changed. Some evidence is also found that food price volatility tends to increase the voting dissent in the U.S. Fed and in Riksbank

Efficient Online Surface Correction for Real-time Large-Scale 3D Reconstruction

State-of-the-art methods for large-scale 3D reconstruction from RGB-D sensors usually reduce drift in camera tracking by globally optimizing the estimated camera poses in real-time without simultaneously updating the reconstructed surface on pose changes. We propose an efficient on-the-fly surface correction method for globally consistent dense 3D reconstruction of large-scale scenes. Our approach uses a dense Visual RGB-D SLAM system that estimates the camera motion in real-time on a CPU and refines it in a global pose graph optimization. Consecutive RGB-D frames are locally fused into keyframes, which are incorporated into a sparse voxel hashed Signed Distance Field (SDF) on the GPU. On pose graph updates, the SDF volume is corrected on-the-fly using a novel keyframe re-integration strategy with reduced GPU-host streaming. We demonstrate in an extensive quantitative evaluation that our method is up to 93% more runtime efficient compared to the state-of-the-art and requires significantly less memory, with only negligible loss of surface quality. Overall, our system requires only a single GPU and allows for real-time surface correction of large environments.Comment: British Machine Vision Conference (BMVC), London, September 201

Investigating feasibility of 2021 WHO protocol for cervical cancer screening in underscreened populations:PREvention and SCReening Innovation Project Toward Elimination of Cervical Cancer (PRESCRIP-TEC)

Abstract Background High-risk human papillomavirus (hrHPV) testing has been recommended by the World Health Organization as the primary screening test in cervical screening programs. The option of self-sampling for this screening method can potentially increase women’s participation. Designing screening programs to implement this method among underscreened populations will require contextualized evidence. Methods PREvention and SCReening Innovation Project Toward Elimination of Cervical Cancer (PRESCRIP-TEC) will use a multi-method approach to investigate the feasibility of implementing a cervical cancer screening strategy with hrHPV self-testing as the primary screening test in Bangladesh, India, Slovak Republic and Uganda. The primary outcomes of study include uptake and coverage of the screening program and adherence to follow-up. These outcomes will be evaluated through a pre-post quasi-experimental study design. Secondary objectives of the study include the analysis of client-related factors and health system factors related to cervical cancer screening, a validation study of an artificial intelligence decision support system and an economic evaluation of the screening strategy. Discussion PRESCRIP-TEC aims to provide evidence regarding hrHPV self-testing and the World Health Organization’s recommendations for cervical cancer screening in a variety of settings, targeting vulnerable groups. The main quantitative findings of the project related to the impact on uptake and coverage of screening will be complemented by qualitative analyses of various determinants of successful implementation of screening. The study will also provide decision-makers with insights into economic aspects of implementing hrHPV self-testing, as well as evaluate the feasibility of using artificial intelligence for task-shifting in visual inspection with acetic acid. Trial registration ClinicalTrials.gov, NCT05234112 . Registered 10 February 202

Comparing different early warning systems: Results from a horse race competition among members of the Macro-prudential Research Network

Over the recent decades researchers in academia and central banks have developed early warning systems (EWS) designed to warn policy makers of potential future economic and financial crises. These EWS are based on diverse approaches and empirical models. In this paper we compare the performance of nine distinct models for predicting banking crises resulting from the work of the Macroprudential Research Network (MaRs) initiated by the European System of Central Banks. In order to ensure comparability, all models use the same database of crises created by MaRs and comparable sets of potential early warning indicators. We evaluate the models’ relative usefulness by comparing the ratios of false alarms and missed crises and discuss implications for pratical use and future research. We find that multivariate models, in their many appearances, have great potential added value over simple signalling models. One of the main policy recommendations coming from this exercise is that policy makers can benefit from taking a broad methodological approach when they develop models to set macro-prudential instruments

Comparing different early warning systems: Results from a horse race competition among members of the Macro-prudential Research Network

Over the recent decades researchers in academia and central banks have developed early warning systems (EWS) designed to warn policy makers of potential future economic and financial crises. These EWS are based on diverse approaches and empirical models. In this paper we compare the performance of nine distinct models for predicting banking crises resulting from the work of the Macroprudential Research Network (MaRs) initiated by the European System of Central Banks. In order to ensure comparability, all models use the same database of crises created by MaRs and comparable sets of potential early warning indicators. We evaluate the models’ relative usefulness by comparing the ratios of false alarms and missed crises and discuss implications for pratical use and future research. We find that multivariate models, in their many appearances, have great potential added value over simple signalling models. One of the main policy recommendations coming from this exercise is that policy makers can benefit from taking a broad methodological approach when they develop models to set macro-prudential instruments