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The purpose of this paper is to assess the informational efficiency of Arabica (other milds) and Robusta coffee futures markets in terms of predicting future coffee spot prices.

Futures market efficiency is associated with the existence of a long-run equilibrium relationship between spot and future prices such that coffee futures prices are unbiased predictors of future spot prices. This study applies unit root testing to daily data for futures-spot price differentials. A range of maturities for futures contracts are considered, and the study also uses a recursive approach to consider time variation in futures market efficiency.

The other milds and Robusta futures prices tend to be unbiased predictors for their own respective spot prices. The paper further finds that other milds and Robusta futures prices are unbiased predictors of the respective Robusta and other milds spot prices. Recursive estimation suggests that the futures market efficiency associated with these cross cases has increased, though with no clear link to the implementation of the 2007 International Coffee Agreement.

The paper draws new insights into futures market efficiency by examining the two key types of coffee and analyses the potential interactions between them. Hitherto, no attention has been paid to futures contracts of the Robusta variety. The employment of unit root testing of spot futures coffee price differentials can be viewed as more stringent than an approach based on non-cointegration testing.

Speculative bubbles have been occurring periodically in local or global real-estate markets and are considered a potential cause of economic crises. In this context, the detection of explosive behaviors in the financial market and the implementation of early warning diagnosis tests are of critical importance. The recent increase in Brazilian housing prices has risen concerns that the Brazilian economy may have a speculative housing bubble. In the present chapter, we employ a recently proposed recursive unit root test in order to identify possible speculative bubbles in data from the Brazilian residential real-estate market. The empirical results show evidence for speculative price bubbles both in Rio de Janeiro and São Paulo, the two main Brazilian cities.

This paper aims to analyze the dynamics of the Spanish public debt–gross domestic product ratio during the period 1850–2020.

This study uses a recent procedure to test for recurrent explosive behavior (Phillips et al., 2011; Phillips et al., 2015a, 2015b) to identify episodes of explosive public debt dynamics and also the episodes of fiscal adjustments over this long period.

The identified episodes of explosive behavior of public debt coincided with fiscal stress events, whereas fiscal adjustments and changes in economic policies stabilized public finances after periods of explosive dynamics of public debt.

The longer than usual span of the data should allow the authors to obtain some more robust results than in most of previous analyses of long-run sustainability.

Housing prices in Brazil have displayed an impressive growth in recent years, raising some concerns about the existence of a bubble in housing markets. In this paper, the authors implement an empirical methodology to identify whether or not there is a bubble in housing markets in Brazil.

Based on a theoretical model that establish that, in the absence of a bubble, a long-run equilibrium relationship should be observed between the market price of an asset and its dividends. The authors implement two methodologies. First, the authors assess whether there is a cointegration relationship between housing prices and housing rental prices. Second, the authors test whether the price-to-rent ratio is stationary.

The authors’ results show that there is evidence of a bubble in housing prices in Brazil. However, given the short span of the data, the authors perform a Monte Carlo simulation and show that the cointegration tests may be biased in small samples. Therefore, the authors should be caution when assessing the results.

The results obtained from the cointegration analysis can be biased for small samples.

The information on the excessive increase of the prices of the properties in relation to their fundamental value can help in the decision-making on investment of the economic agents.

These results corroborate the hypothesis that Brazil has an excessive appreciation in housing prices, and, as Silva and Besarria (2018) have suggested, this behavior explains, in part, the fact that the central bank has taken this issue into account when deciding about the stance of monetary policy of Brazil.

The originality is linked to the use of the Gregory-Hansen method of cointegration in the identification of bubbles and discussion of the limitations of the research through Monte Carlo simulation.

Greece, Ireland, Portugal and Spain have been in the spotlight of the recent economic crisis in Europe. With their economy strongly reliant on the construction industry, these countries have become widely exposed to the downturn in the property sector. This paper aims to examine residential property bubble dynamics in the period from 2003 to 2014 and investigate the role of financing conditions in the formation of these bubbles.

Building on the present value model in conjunction with the rational bubble assumption, the study applies the discounted cash flow (DCF) approach and applies weighted average cost of capital (WACC) to capture real estate bubble dynamics in the four countries. Reduced form vector autoregression models are used to examine the relationship between financing conditions and the bubble indicator.

The bubble indicator suggests that Spain and Ireland experienced a large rise in the bubble relative to moderate increases in Portugal and Greece in the period from 2003 up to the collapse in 2008. Our findings from the empirical analysis indicate that central bank policy shifts that impact interest rates and lending volumes on the domestic level have a significant and leading effect on the formation of residential property bubbles.

Only little research on real estate bubbles takes financial leverage into account. This paper bridges this gap by applying the WACC in the DCF model to identify real estate bubbles. While using a distinct bubble indicator, this analysis provides new insights into the linkage between financing conditions and real estate bubbles.

Financial markets have experienced considerable turbulence over the past two decades. The recent subprime and sovereign debt crises in the United States and Europe, respectively, have resulted in significant new regulatory responses. They also prompted the re-evaluation of how best to manage and measure financial risk. The 20 chapters in this volume provide a number of different perspectives on financial risk in the post-crisis period where monetary easing has become a predominant monetary policy. While asset price volatility has now returned to levels experienced in the mid-2000s many lessons remain. Among the most important is the need to accurately measure and manage the complex risks that exist in financial markets. Our hope is that the chapters presented here provide a better understanding of how best to do this, while also giving insights for next suitable steps and further developments.

This chapter investigates the predictability of the European monetary policy through the eyes of the professional forecasters from a large investment bank. The analysis is based on forward-looking Actual and Perceived Taylor Rules for the European Central Bank which are estimated in real-time using a newly constructed database for the period April 2000–November 2009. The former policy rule is based on the actual refi rate set by the Governing Council, while the latter is estimated for the bank’s economists using their main point forecast for the upcoming refi rate decision as a dependent variable. The empirical evidence shows that the pattern of the refi rate is broadly well predicted by the professional forecasters even though the latter have foreseen more accurately the increases rather than the policy rate cuts. Second, the results point to an increasing responsiveness of the ECB to macroeconomic fundamentals along the forecast horizon. Third, the rolling window regressions suggest that the estimated coefficients have changed after the bankruptcy of Lehman Brothers in October 2008; the ECB has responded less strongly to macroeconomic fundamentals and the degree of policy inertia has decreased. A sensitivity analysis shows that the baseline results are robust to applying a recursive window methodology and some of the findings are qualitatively unaltered from using Consensus Economics forecasts in the regressions.

This article investigates the robustness of impulse response estimators to near unit roots and near cointegration in vector autoregressive (VAR) models. We compare estimators based on VAR specifications determined by pretests for unit roots and cointegration as well as unrestricted VAR specifications in levels. Our main finding is that the impulse response estimators obtained from the levels specification tend to be most robust when the magnitude of the roots is not known. The pretest specification works well only when the restrictions imposed by the model are satisfied. Its performance deteriorates even for small deviations from the exact unit root for one or more model variables. We illustrate the practical relevance of our results through simulation examples and an empirical application.