Does Banque de France control inflation and unemployment?

We re-estimate statistical properties and predictive power of a set of Phillips curves, which are expressed as linear and lagged relationships between the rates of inflation, unemployment, and change in labour force. For France, several relationships were estimated eight years ago. The change rate of labour force was used as a driving force of inflation and unemployment within the Phillips curve framework. The set of nested models starts with a simplistic version without autoregressive terms and one lagged term of explanatory variable. The lag is determined empirically together with all coefficients. The model is estimated using the Boundary Element Method (BEM) with the least squares method applied to the integral solutions of the differential equations. All models include one structural break might be associated with revisions to definitions and measurement procedures in the 1980s and 1990s as well as with the change in monetary policy in 1994-1995. For the GDP deflator, our original model provided a root mean squared forecast error (RMSFE) of 1.0% per year at a four-year horizon for the period between 1971 and 2004. The rate of CPI inflation is predicted with RMSFE=1.5% per year. For the naive (no change) forecast, RMSFE at the same time horizon is 2.95% and 3.3% per year, respectively. Our model outperforms the naive one by a factor of 2 to 3. The relationships for inflation were successfully tested for cointegration. We have formally estimated several vector error correction (VEC) models for two measures of inflation. At a four year horizon, the estimated VECMs provide significant statistical improvements on the results obtained by the BEM: RMSFE=0.8% per year for the GDP deflator and ~1.2% per year for CPI. For a two year horizon, the VECMs improve RMSFEs by a factor of 2, with the smallest RMSFE=0.5% per year for the GDP deflator.Comment: 25 pages, 12 figure

Global Liquidity and House Prices: A VAR Analysis for OECD Countries

Global monetary dynamics has been particularly strong in recent years. At the same time, house prices in many OECD countries increased sharply, significantly outpacing the relatively subdued development in consumer prices. In this paper we argue that different price elasticities on asset and consumer markets help to explain the observed relative price change between assets and consumer goods. Using a VAR analysis and aggregated data for the major OECD countries, our empirical results are supportive of this relationship. Both house and consumer prices are determined by global monetary conditions; however, while global liquidity shocks lead to relatively fast responses in global house prices, significant responses of the global CPI index to money shocks occur only after long time lags. In addition, we find subsequent spillovers from asset prices to consumer prices on a global scale

The Forward-Discount Puzzle in Central and Eastern Europe

This paper adds to evidence that the forward-discount puzzle is at least partly explained as a compensation for taking crash-risk. A number of Central and Eastern European exchange rates are compared. A Hidden Markov Model is used to identify two regimes for most of the exchange rates. These two regimes can be characterised as being either periods of stability or periods of instability. The level of international risk aversion and changes in US interest rates affect the probability of switching from one regime to the other. This model is then used to assess the way that these two factors affect the probability of a currency crisis. While the Czech Republic, Hungary and Bulgaria are very sensitive to international financial conditions, Poland and Romania are relatively immune. JEL classifications: C24, F31, F32; Key words: Exchange rates, uncovered interest parity, foreign exchange risk discount, hidden-Markov model, carry-trad

China’s market economy, shadow banking and the frequency of growth slowdown

The activity of the Shadow Banks in China has been the subject of considerable interest in recent years. Total shadow banking lending has reached over 60% of GDP and has grown faster than regular bank lending. It has been argued that unregulated shadow banking has fuelled a credit boom that poses a risk to the stability of the financial system. This paper estimates a model of the Chinese economy using a DSGE framework that accommodates a banking sector that isolates the effects of lending to the private sector including shadow bank lending. A refinement of the model allows for bank lending including lending by the shadow banks to affect the credit premium on private investment. The main finding is that while financial shocks are significant, it is real shocks that dominate. The model is used to simulate the frequency of growth slowdowns in China and concludes that these are more likely to be driven by real sector shocks rather than financial sector, including shadow bank shocks. This paper differs from other applications in its use of indirect inference to test the fitted model against a threeequation VAR of inflation, output gap and interest rate

FAIR environmental and health registry (FAIREHR)- supporting the science to policy interface and life science research, development and innovation

The environmental impact on health is an inevitable by-product of human activity. Environmental health sciences is a multidisciplinary field addressing complex issues on how people are exposed to hazardous chemicals that can potentially affect adversely the health of present and future generations. Exposure sciences and environmental epidemiology are becoming increasingly data-driven and their efficiency and effectiveness can significantly improve by implementing the FAIR (findable, accessible, interoperable, reusable) principles for scientific data management and stewardship. This will enable data integration, interoperability and (re)use while also facilitating the use of new and powerful analytical tools such as artificial intelligence and machine learning in the benefit of public health policy, and research, development and innovation (RDI). Early research planning is critical to ensuring data is FAIR at the outset. This entails a well-informed and planned strategy concerning the identification of appropriate data and metadata to be gathered, along with established procedures for their collection, documentation, and management. Furthermore, suitable approaches must be implemented to evaluate and ensure the quality of the data. Therefore, the 'Europe Regional Chapter of the International Society of Exposure Science' (ISES Europe) human biomonitoring working group (ISES Europe HBM WG) proposes the development of a FAIR Environment and health registry (FAIREHR) (hereafter FAIREHR). FAIR Environment and health registry offers preregistration of studies on exposure sciences and environmental epidemiology using HBM (as a starting point) across all areas of environmental and occupational health globally. The registry is proposed to receive a dedicated web-based interface, to be electronically searchable and to be available to all relevant data providers, users and stakeholders. Planned Human biomonitoring studies would ideally be registered before formal recruitment of study participants. The resulting FAIREHR would contain public records of metadata such as study design, data management, an audit trail of major changes to planned methods, details of when the study will be completed, and links to resulting publications and data repositories when provided by the authors. The FAIREHR would function as an integrated platform designed to cater to the needs of scientists, companies, publishers, and policymakers by providing user-friendly features. The implementation of FAIREHR is expected to yield significant benefits in terms of enabling more effective utilization of human biomonitoring (HBM) data.Most co-authors were financialy supported with their respective inistitution. Some of the co-authors were financialy supportrd by the Safe and Efficient Chemistry by Design (SafeChem) project (grant no. DIA 2018/11) funded by the Swedish Foundation for Strategic Environmental Research, and by the PARC project (grant no. 101057014) funded under the European Union's Horizon Europe Research and Innovation program

International Business Cycle Spillovers

We apply Diebold-Yilmaz spillover index methodology to monthly industrial production indices to study business cycle interdependence among G-6 industrialized countries since 1958. The business cycle spillover index fluctuates substantially over time, increasing especially after the 1973-75, 1981-82 and 2001 U.S. recessions. The band within which the spillover index fluctuates has widened since the start of the globalization process in the early 1990s. Our most important result, however, concerns the current state of the world economy: In a matter of four months from September to December 2008, the business cycle spillover index recorded the sharpest increase ever, reaching a record level as of December 2008 (See http://data.economicresearchforum.org/erf/bcspill.aspx?lang=en for updates of the spillover plot). Focusing on directional spillover measures, we show that in the current episode the shocks are mostly originating from the United States and spreading to other industrialized countries. We also show that, throughout the period of analysis, the U.S. (1980s and 2000s) and Japan (1970s and 2000s) have been the major transmitters of shocks among the industrialized countries