Forecast combinations under structural break uncertainty

This paper proposes two new weighting schemes that average forecasts based on different estimation windows in order to account for possible structural change. The first scheme weights the forecasts according to the values of reversed ordered CUSUM (ROC) test statistics, while the second weighting method simply assigns heavier weights to forecasts that use more recent information. Simulation results show that, when structural breaks are present, forecasts based on the first weighting scheme outperform those based on a procedure that simply uses ROC tests to choose and forecast from a single post-break estimation window. Combination forecasts based on our second weighting scheme outperform equally weighted combination forecasts. An empirical application based on a NAIRU Phillips curve model for the G7 countries illustrates these findings, and also shows that combination forecasts can outperform the random walk forecasting model.     

How does issuing contingent convertible bonds improve bank's solvency? A Value-at-Risk and Expected Shortfall approach

This paper examines how issuing an innovative financial instrument called contingent convertible bond (CoCo) may enhance bank's solvency in comparison to issuing a conventional bond. CoCos convert automatically into common equity or have a principal write-down when bank's regulatory capital fails to meet a predetermined level. They have been invented and put into legislation with an objective to absorb losses thus preventing institutions from bankruptcy. From the standpoint of an issuer CoCos bring about two counter effects regarding his solvency: on one hand they recapitalize a bank approaching insolvency on the other hand CoCos pay much higher coupon comparing to conventional bonds. In our model a bank has two funding alternatives: either to issue CoCos or conventional bonds. We measure issuer's default risk using the concept of Value-at-Risk (VaR) and Expected Shortfall (ES). We conclude that CoCos have the potential to strengthen the resilience of the issuer on the condition that the probability of conversion triggering is higher than the VaR's significance level. Our findings can be helpful to the policymakers and banks to better understand the impact of CoCos on issuer's solvency.     

The (de-)anchoring of inflation expectations: New evidence from the euro area

Well-anchored inflation expectations are a key factor for achieving economic stability. This paper provides new empirical results on the anchoring of long-term inflation expectations in the euro area. In line with earlier evidence, we find that euro area inflation expectations have been anchored until fall 2011. Since then, however, they respond significantly to macroeconomic news. Our results obtained from multiple endogenous break point tests suggest that euro area inflation expectations have remained de-anchored ever since.     

Wheat variety yield data: Do commercial and public performance tests provide the same information?

Wheat yields from reported performance test results are of economic importance to wheat producers, since their profits depend on selecting the optimal variety for their location. However, our data shows differences in absolute and relative wheat yields between commercial and public wheat breeding program's performance test data in Kansas. Newly available data are used to test if the difference in yields arose from potential selectivity bias, and to determine the contribution of private and public wheat breeding programs to varietal yield improvement during 2007–2012. Both Heckman selection models and multiple regression showed no statistical evidence of the potential presence of selectivity bias rather, managerial practices, agronomic conditions, field location, and inherent genetic traits of the seed variety were identify as the source of yield differences.     

Generalized runs tests to detect randomness in hedge funds returns

The major contribution of this paper is to make use of generalized runs tests (Cho and White, 2011) to analyze the randomness, i.e. the lack of persistence, in both absolute and relative returns of hedge funds. We find that about 42% of the HFR universe exhibit iid absolute returns over the period spanning 2000 to 2012. These funds are mainly found in proportions within the Macro and Equity Hedge strategies. A similar result holds for relative returns. We also find that funds having non-iid returns often exhibit ARCH effects and structural breaks, with largest breaks located within financial crises. Also, only a small percentage displays persistence in their relative performance, 8.2% to 16.7% of the universe, mainly found in proportions within the Relative Value and Event-Driven strategies. The robustness of results is challenged by implementing the tests on a crisis-free period. We find similar results for absolute returns. For relative ones, differences appear across strategies and benchmarks, but still both ARCH and breaks are present. Our work contributes to the hedge fund literature in terms of methodology, portfolio allocation, and performance measurement.     

Tests of Normality of Functional Data

The paper is concerned with testing normality in samples of curves and error curves estimated from functional regression models. We propose a general paradigm based on the application of multivariate normality tests to vectors of functional principal components scores. We examine finite sample performance of a number of such tests and select the best performing tests. We apply them to several extensively used functional data sets and determine which can be treated as normal, possibly after a suitable transformation. We also offer practical guidance on software implementations of all tests we study and develop large sample justification for tests based on sample skewness and kurtosis of functional principal component scores.     

Asymmetry,Complementarities, and State Dependence in Federal Reserve Forecasts

Forecasts are a central component of policymaking; the Federal Reserve's forecasts are published in a document called the Greenbook. Previous studies of the Greenbook's inflation forecasts have found them to be rationalizable but asymmetric if considering particular subperiods, for example, before and after the Volcker appointment. In these papers, forecasts are analyzed in isolation, assuming policymakers value them independently. We analyze the Greenbook forecasts in a framework in which the forecast errors for different variables are allowed to interact. We find that allowing the losses to interact makes the unemployment forecasts virtually symmetric, the output forecasts symmetric prior to the Volcker appointment, and the inflation forecasts symmetric after the onset of the Great Moderation.     

Does economic policy uncertainty affect cryptocurrency markets? Evidence from Twitter-based uncertainty measures

Using daily data from August 9, 2015, to July 7, 2020, this study examines the effects of economic policy uncertainty (EPU) on the returns of four cryptocurrencies: Bitcoin, Ethereum, Litecoin, and Ripple. To this end, two new measures of EPU (Twitter-based economic uncertainty and Twitter-based market uncertainty) are considered. A Granger causality test using the recursive evolving window approach shows a significant causality between the Twitter-based EPU measures and the BTC/USD exchange rate from October 2016 to July 2017. Moreover, a significant causality was noted from the EPU measures to the ETH/USD exchange rate from June 2019 to February 2020 and from the EPU measures to the XRP/USD exchange rate from January 2020 to February 2020. The Twitter-based EPU measures primarily positively affect the returns of the related cryptocurrencies during these periods. These results are robust to different measures of Twitter-based EPU and different econometric techniques. Potential implications, including the COVID-19 era, are also discussed.     

Pension plan solvency and extreme market movements: a regime switching approach

We develop and test a new approach to assess defined benefit (DB) pension plan solvency risk in the presence of extreme market movements. Our method captures both the ‘fat-tailed’ nature of asset returns and their correlation with discount rate changes. We show that the standard assumption of constant discount rates leads to dramatic underestimation of future projections of pension plan solvency risk. Failing to incorporate leptokurtosis into asset returns also leads to downward biased estimates of risk, but this is less pronounced than the time-varying discount rate effect. Further modifying the model to capture the correlation between asset returns and the discount rate provides additional improvements in the projection of future pension plan solvency. This reduces the perceived future risk of underfunding because of the negative correlation between interest rate changes and asset returns. These results have important implications for those with responsibility for balancing risk against expected return when seeking to improve the current poor funding positions of DB pension schemes.     

Considerations in the diffusion of a public traffic app for Metro Manila

The proliferation of apps enabling motorists to access traffic information on the move introduces several intriguing possibilities for transportation authorities. In the expectation that public demand for these apps will increase as both road traffic and smartphone ownership rise, these tools invite consideration alongside other traffic management tools. Traffic app-specific considerations include increased motorist interactivity, consumer technology diffusion, and institutional factors affecting the rollout of e-government initiatives. This article uses the introduction of the MMDA Traffic Navigator—a Manila-based, publicly developed traffic app—to illustrate these considerations. Additionally, app usage among residents of nearby cities constituting Manila’s extended metropolitan region is considered. These considerations are subsequently classified using a 4E framework under economy, effectiveness, efficiency, and equity to inform other authorities’ efforts to either incorporate traffic apps into overall transport planning or even take the initiative in developing them.