Bootstrap procedures for detecting multiple persistence shifts in heteroskedastic time series

This article proposes new bootstrap procedures for detecting multiple persistence shifts in a time series driven by non-stationary volatility. The assumed volatility process can accommodate discrete breaks, smooth transition variation as well as trending volatility. We develop wild bootstrap sup-Wald tests of the null hypothesis that the process is either stationary [I(0)] or has a unit root [I(1)] throughout the sample. We also propose a sequential procedure to estimate the number of persistence breaks based on ordering the regime-specific bootstrap p-values. The asymptotic validity of the advocated procedures is established both under the null of stability and a variety of persistence change alternatives. A comparison with existing tests that assume homoskedasticity illustrates the finite sample improvements offered by our methods. An application to OECD inflation rates highlights the empirical relevance of the proposed approach and weakens the case for persistence change relative to existing procedures.     

Repeated Price Search

Consumers check few sites in online purchases. Previous research and experiments we perform demonstrate that consumers can not calculate the optimal strategy for price search. They use heuristics whose performance is better than random and less than optimal. To investigate online price search performance we survey student online textbook purchases. Students achieve good performance because they start with a good strategy and online market organization of marketplace and meta-search sites. An important factor is that algorithms at sites searched perform calculations that reduce the computational complexity of the search.     

A sequential procedure to determine the number of breaks in trend with an integrated or stationary noise component

Perron and Yabu (2009a) consider the problem of testing for a break occurring at an unknown date in the trend function of a univariate time series when the noise component can be either stationary or integrated. This article extends their work by proposing a sequential test that allows one to test the null hypothesis of, say, l breaks versus the alternative hypothesis of (l + 1) breaks. The test enables consistent estimation of the number of breaks. In both stationary and integrated cases, it is shown that asymptotic critical values can be obtained from the relevant quantiles of the limit distribution of the test for a single break. Monte Carlo simulations suggest that the procedure works well in finite samples.     

Stable Hairpin Structures Formed by Xylose-Based Nucleic Acids

Xenobiology explores synthetic nucleic acid polymers as alternative carriers of genetic information to expand the central dogma. The xylo- and deoxyxylo-nucleic acids (XyNA and dXyNA), containing 3’ epimers of riboses and deoxyriboses, are considered to be potential candidates for an orthogonal system. In this study, thermal and spectroscopic analyses show that XyNA and dXyNA form stable hairpins. The dXyNA hairpin structure determined by NMR spectroscopy contains a flexible loop that locks the stem into a stable ladder-like duplex with marginal right-handed helicity. The reduced flexibility of the dXyNA duplex observed in the stem of the hairpin demonstrates that folding of dXyNA yields more stable structures described so far.