Stocks,bonds, money markets and exchange rates: measuring international financial transmission

Understanding the complexity of the financial transmission process across various assets—domestically as well as within and across asset classes—requires the simultaneous modeling of the various transmission channels in a single, comprehensive empirical framework. The paper estimates the financial transmission between money, bond and equity markets and exchange rates within and between the USA and the euro area. We find that asset prices react strongest to other domestic asset price shocks, but that there are also substantial international spillovers, both within and across asset classes. The results underline the dominance of US markets as the main driver of global financial markets: US financial markets explain, on average, around 30% of movements in euro area financial markets, whereas euro area markets account only for about 6% of US asset price changes. Moreover, the methodology allows us to identify indirect spillovers through other asset prices, which are found to increase substantially the international transmission of shocks within asset classes. Copyright © 2010 John Wiley & Sons, Ltd.     

Growth in transition countries

This study analyzes the impact of the speed of transition reforms on economic growth in transition countries in the context of the debate on ‘big‐bang vs. gradualist approach’. It builds a new indicator for the speed of transition reforms based on a three‐way principal component analysis. It shows that: (i) the speed of transition reforms Granger‐causes economic growth and there is no reverse causation; (ii) the impact of contemporaneous speed of transition reforms on economic growth is negative, but becomes positive in the longer horizon; and (iii) other factors, such as initial conditions and macroeconomic stabilization programmes, also drive economic growth. Although the first two results are robust to different estimators, the impact of control variables depends on the econometric specification.     

Bayesian Graphical Models for STructural Vector Autoregressive Processes

This paper proposes a Bayesian, graph‐based approach to identification in vector autoregressive (VAR) models. In our Bayesian graphical VAR (BGVAR) model, the contemporaneous and temporal causal structures of the structural VAR model are represented by two different graphs. We also provide an efficient Markov chain Monte Carlo algorithm to estimate jointly the two causal structures and the parameters of the reduced‐form VAR model. The BGVAR approach is shown to be quite effective in dealing with model identification and selection in multivariate time series of moderate dimension, as those considered in the economic literature. In the macroeconomic application the BGVAR identifies the relevant structural relationships among 20 US economic variables, thus providing a useful tool for policy analysis. The financial application contributes to the recent econometric literature on financial interconnectedness. The BGVAR approach provides evidence of a strong unidirectional linkage from financial to non‐financial super‐sectors during the 2007–2009 financial crisis and a strong bidirectional linkage between the two sectors during the 2010–2013 European sovereign debt crisis. Copyright © 2015 John Wiley & Sons, Ltd.     

Fitting and Forecasting Sovereign Defaults using Multiple Risk Signals

In this article, we try to realize the best compromise between in‐sample goodness of fit and out‐of‐sample predictability of sovereign defaults. To do this, we use a new regression‐tree based approach that signals impending sovereign debt crises whenever pre‐selected indicators exceed specific thresholds. Using data from emerging markets and Greece, Ireland, Portugal and Spain (GIPS) over the period 1975–2010, we show that our model significantly outperforms existing competing approaches (logit, stepwise logit, noise‐to‐signal ratio and regression trees), while balancing in‐ and out‐of‐sample performance. Our results indicate that illiquidity (high short‐term debt to reserves) and default history, together with real GDP growth and US interest rates, are the main determinants of both emerging market country defaults and the recent European sovereign debt crisis.     

On the Magnet Effect of Price Limits

The ‘magnet’ or ‘gravitational’ effect hypothesis asserts that, when trading halts are rule‐based, investors concerned with a likely impediment to trade advance trades in time. This behaviour actually pushes prices further towards the limit. Empirical studies about the magnet effect are scarce, most likely because of the unavailability of data on rule‐based halts. In this paper, we use a large database from the Spanish Stock Exchange (SSE), which combines intraday stock specific price limits and short‐lived rule‐based call auctions to stabilise prices, to test this hypothesis. The SSE is particularly well suited to test the magnet effect hypothesis since trading halts are price‐triggered and, therefore, predictable to some extent. Still, the SSE microstructure presents two particularities: (i) a limit‐hit triggers an automatic switch to an alternative trading mechanism, a call auction, rather than a pure halt; (ii) the trading halt only lasts 5 minutes. We find that, even when prices are within a very short distance to the price limits, the probability of observing a limit‐hit is unexpectedly low. Additionally, prices either initiate reversion (non limit‐hit days) or slow down gradually (limit‐hit days) as they come near the intraday limits. Finally, the most aggressive traders progressively become more patient as prices approach the limits. Therefore, both the price patterns and the trading behaviour reported near the limits do not agree with the price limits acting as magnetic fields. Consequently, we conclude that the switching mechanism implemented in the SSE does not induce traders to advance their trading programs in time.     

Industry and time specific deviations from fundamental values in a random coefficient model

The paper analyzes the relationship between stock prices and fundamentals for a large sample of US stocks in the last 10 years using a random coefficient model. Heterogeneity and omitted variable bias are properly taken into account with model coefficients being allowed to vary across time and industries. The random coefficient model allows to track waves of reliance on analysts’ forecasts and nonfundamental stock price components across time and clearly identifies the growth of the nonfundamental component in the long 1991–2000 swing.      

R&D intensity of investment across Europe before and after the crisis

In this paper we investigate the comovements between the R&D intensity of private investment and GDP growth in different European Union (EU) areas over the period 1999–2014. Our empirical analysis shows that only core countries display a common countercyclical mechanism leading to an increased intensity of R&D over prolonged downturns. The lack of an effective countercyclical pattern of R&D intensity over the evolution of GDP growth in periphery countries makes this area highly vulnerable to persistent recessions, with potentially harmful consequences for long‐term growth. For recent EU members the evidence of acyclicality should be evaluated in the light of the catching‐up process still at work in this area. Our analysis suggests that any successful EU innovation policy should not disregard the potential divergence in R&D performance due to the dispersion of the countercyclical properties of the investment intensity in productivity enhancing activities in the different EU areas.     

The heterogeneous effect of oil discoveries on democracy

This paper evaluates the existence of a resource curse on political regimes using the Synthetic Control Method. Focusing on 12 countries, we compare their democracy level with the weighted democracy level of countries that have not experienced oil shocks and have similar pre‐event characteristics. We find that the exogenous variation in oil endowment does not have the same effect on all countries. In most cases, the event has a negative effect in the long run, but countries with a pre‐existing high level of democracy are not negatively affected.     

Entry‐Timing Advantages in Renewable Natural Resources Industries

In this paper, we explore the conditions of entry‐timing advantages in renewable natural resource industries. Drawing from behavioural theory of the firm, we classify firms in two groups depending on the different heuristics used to make entry decisions when facing the cyclical endogenous nature of these industries: crowd firms are procyclical, making decisions based on the current phase of the industry cycle, whereas anti‐crowd firms follow a countercyclical strategy, making uncertain, and risky decisions by estimation of the next phase of the cycle. Therefore, anti‐crowd firms anticipate the deployment of resources each cycle, potentially gaining entry‐timing advantages beyond those provided by traditional competitive isolating mechanisms. Through a mathematical simulation of a performance feedback model, we reveal that the entry‐timing advantage of the anti‐crowd group becomes possible when the rivalry in the industry and the price sensitivity of competitors are high, and when the time required to deploy the resources is short.