Comment on ``Analytic Structure of One-Dimensional Localization Theory: Re-Examining Mott's Law''

The low-frequency conductivity of a disordered Fermi gas in one spatial dimension is governed by the Mott-Berezinskii law $\sigma(\omega) \propto \omega^2 \ln \omega^2$. In a recent Letter [Phys. Rev. Lett. 84, 1760 (2000)] A. O. Gogolin claimed that this law is invalid, challenging our basic understanding of disordered systems and a massive amount of previous theoretical work. We point out two calculational errors in Gogolin's paper. Once we correct them, the Mott-Berezinskii formula is fully recovered. We also present numerical results supporting the Mott-Berezinskii formula but ruling out that of Gogolin.Comment: 1 page, 1 figure, RevTeX

Endogenous Health Care, Life Expectancy, and Economic Development

We study the endogenous relationship between health care, life expectancy and output in a modified neoclassical growth model. While health care competes resources away from goods production, it prolongs life expectancy which in turn leads to higher capital accumulation. We show that savings and health care are complements in equilibrium, with both rising with economic development. Our model is therefore consistent with several stylized facts, namely, (i) countries spend more on health care as they prosper, (ii) individuals in rich countries tend to live longer, and (iii) population aging is more pronounced in rich countries. Moreover, through simulation, health care and health production technology are found to be growth and welfare enhancing.life expectancy, health care, economic growth, population aging

Single-image measurements of monochromatic subdiffraction dimolecular separations

Measuring subdiffraction separations between single fluorescent particles is important for biological, nano-, and medical-technology studies. Major challenges include (i) measuring changing molecular separations with high temporal resolution while (ii) using identical fluorescent labels. Here we report a method that measures subdiffraction separations between two identical fluorophores by using a single image of milliseconds exposure time and a standard single-molecule fluorescent imaging setup. The fluorophores do not need to be bleached and the separations can be measured down to 40 nm with nanometer precision. The method is called single-molecule image deconvolution -- SMID, and in this article it measures the standard deviation (SD) of Gaussian-approximated combined fluorescent intensity profiles of the two subdiffraction-separated fluorophores. This study enables measurements of (i) subdiffraction dimolecular separations using a single image, lifting the temporal resolution of seconds to milliseconds, while (ii) using identical fluorophores. The single-image nature of this dimer separation study makes it a single-image molecular analysis (SIMA) study.Comment: 16 pages, 5 figure

Fiscal and Monetary Policies and the Cost of Sudden Stops

This article investigates the effects of macroeconomic policy (monetary and fiscal) on output growth during financial crises characterized by a “sudden stop” in net capital inflows in developing and emerging market economies. We investigate 83 sudden stop crises in 77 countries over 1982-2003 using a baseline empirical model to control for the various determinants of output losses during sudden stop crises. Extending the baseline model to account for policies-- contractionary as well as expansionary-- we measure the marginal effects of policy on output losses. Simple descriptive statistics indicate no apparent correlation between the costs of financial crises and the economic policies pursed at the time. Once controlling for various pre-conditions and other factors, however, we find that monetary and fiscal tightening at the time of a sudden stop crisis significantly worsens output losses.Output losses, financial crises, sudden stops, fiscal policy, financial policy

Nested Hierarchical Dirichlet Processes

We develop a nested hierarchical Dirichlet process (nHDP) for hierarchical topic modeling. The nHDP is a generalization of the nested Chinese restaurant process (nCRP) that allows each word to follow its own path to a topic node according to a document-specific distribution on a shared tree. This alleviates the rigid, single-path formulation of the nCRP, allowing a document to more easily express thematic borrowings as a random effect. We derive a stochastic variational inference algorithm for the model, in addition to a greedy subtree selection method for each document, which allows for efficient inference using massive collections of text documents. We demonstrate our algorithm on 1.8 million documents from The New York Times and 3.3 million documents from Wikipedia.Comment: To appear in IEEE Transactions on Pattern Analysis and Machine Intelligence, Special Issue on Bayesian Nonparametric