Political Uncertainty, Public Expenditure and Growth

We focus on the link between political instability due to uncertain electoral outcomes and economic growth, through the impact on a government's decisions on how to allocate government expenditure between public consumption and investment. Using an endogenous growth model with partisan electoral effects, we demonstrate that political uncertainty will generate a steady-state equilibrium growth rate which is inefficient and too low. We also use a newly-constructed political data set to estimate panel regressions for several OECD economies over a period 1960-95. Our empirical evidence on the effects of political variables on tax and spending decisions supports our theoretical results.Endogenous growth, public consumption and investment, political uncertainty, panel regressions, OECD countries

PINK1 protects against oxidative stress by phosphorylating mitochondrial chaperone TRAP1.

Mutations in the PTEN induced putative kinase 1 (PINK1) gene cause an autosomal recessive form of Parkinson disease (PD). So far, no substrates of PINK1 have been reported, and the mechanism by which PINK1 mutations lead to neurodegeneration is unknown. Here we report the identification of TNF receptor-associated protein 1 (TRAP1), a mitochondrial molecular chaperone also known as heat shock protein 75 (Hsp75), as a cellular substrate for PINK1 kinase. PINK1 binds and colocalizes with TRAP1 in the mitochondria and phosphorylates TRAP1 both in vitro and in vivo. We show that PINK1 protects against oxidative-stress-induced cell death by suppressing cytochrome c release from mitochondria, and this protective action of PINK1 depends on its kinase activity to phosphorylate TRAP1. Moreover, we find that the ability of PINK1 to promote TRAP1 phosphorylation and cell survival is impaired by PD-linked PINK1 G309D, L347P, and W437X mutations. Our findings suggest a novel pathway by which PINK1 phosphorylates downstream effector TRAP1 to prevent oxidative-stress-induced apoptosis and implicate the dysregulation of this mitochondrial pathway in PD pathogenesis

Counting abelian varieties over finite fields via Frobenius densities

Let $[X,\lambda]$ be a principally polarized abelian variety over a finite field with commutative endomorphism ring; further suppose that either $X$ is ordinary or the field is prime. Motivated by an equidistribution heuristic, we introduce a factor $\nu_v([X,\lambda])$ for each place $v$ of $\mathbb Q$, and show that the product of these factors essentially computes the size of the isogeny class of $[X,\lambda]$. The derivation of this mass formula depends on a formula of Kottwitz and on analysis of measures on the group of symplectic similitudes, and in particular does not rely on a calculation of class numbers.Comment: Main text by Achter, Altug and Gordon; appendix by Li and Ru

A Polylogarithimic Approximation Algorithm for Edge-Disjoint Paths with Congestion 2

In the Edge-Disjoint Paths with Congestion problem (EDPwC), we are given an undirected n-vertex graph G, a collection M={(s_1,t_1),...,(s_k,t_k)} of demand pairs and an integer c. The goal is to connect the maximum possible number of the demand pairs by paths, so that the maximum edge congestion - the number of paths sharing any edge - is bounded by c. When the maximum allowed congestion is c=1, this is the classical Edge-Disjoint Paths problem (EDP). The best current approximation algorithm for EDP achieves an $O(\sqrt n)$-approximation, by rounding the standard multi-commodity flow relaxation of the problem. This matches the $\Omega(\sqrt n)$ lower bound on the integrality gap of this relaxation. We show an $O(poly log k)$-approximation algorithm for EDPwC with congestion c=2, by rounding the same multi-commodity flow relaxation. This gives the best possible congestion for a sub-polynomial approximation of EDPwC via this relaxation. Our results are also close to optimal in terms of the number of pairs routed, since EDPwC is known to be hard to approximate to within a factor of $\tilde{\Omega}((\log n)^{1/(c+1)})$ for any constant congestion c. Prior to our work, the best approximation factor for EDPwC with congestion 2 was $\tilde O(n^{3/7})$, and the best algorithm achieving a polylogarithmic approximation required congestion 14

Using Sentiment Induction to Understand Variation in Gendered Online Communities

We analyze gendered communities defined in three different ways: text, users, and sentiment. Differences across these representations reveal facets of communities\u27 distinctive identities, such as social group, topic, and attitudes. Two communities may have high text similarity but not user similarity or vice versa, and word usage also does not vary according to a clearcut, binary perspective of gender. Community-specific sentiment lexicons demonstrate that sentiment can be a useful indicator of words\u27 social meaning and community values, especially in the context of discussion content and user demographics. Our results show that social platforms such as Reddit are active settings for different constructions of gender