Government spending shocks and the multiplier: New evidence from the U.S. based on natural disasters

The literature on estimating macroeconomic effects of fiscal policy requires suitable instruments to identify exogenous and unanticipated spending shocks. So far, the instrument of choice has been military build-ups. This instrument, however, largely limits the analysis to the US as few other countries have been involved in mainly extraterritorial conflicts. Moreover, the expenditure associated with military build-ups affects primarily the defense sector so that the resulting multiplier does not necessarily approximate the effects of changes to general government spending. We propose an alternative instrument: government relief expenditure in the wake of natural disasters which is more similar in its scope to general government spending. We construct a rich data set of natural disasters and the corresponding government responses at the US state level. We apply this methodology both at the state as well as national levels and show that natural disasters serve as a powerful instrument for identifying government spending shocks. Furthermore, we show that the multiplier pertaining to non-defense government spending is higher than the defense-spending multiplier estimated in the literature using military build-ups

Spintronic signatures of Klein tunneling in topological insulators

Klein tunneling, the perfect transmission of normally incident Dirac electrons across a potential barrier, has been widely studied in graphene and explored to design switches, albeit indirectly. We show that Klein tunneling maybe easier to detect for spin-momentum locked electrons crossing a PN junction along a three-dimensional topological insulator surface. In these topological insulator PN junctions (TIPNJs), the spin texture and momentum distribution of transmitted electrons can be measured electrically using a ferromagnetic probe for varying gate voltages and angles of current injection. Based on transport models across a TIPNJ, we show that the asymmetry in the potentiometric signal between PP and PN junctions and its overall angular dependence serve as a direct signature of Klein tunneling

A Parameterized Centrality Metric for Network Analysis

A variety of metrics have been proposed to measure the relative importance of nodes in a network. One of these, alpha-centrality [Bonacich, 2001], measures the number of attenuated paths that exist between nodes. We introduce a normalized version of this metric and use it to study network structure, specifically, to rank nodes and find community structure of the network. Specifically, we extend the modularity-maximization method [Newman and Girvan, 2004] for community detection to use this metric as the measure of node connectivity. Normalized alpha-centrality is a powerful tool for network analysis, since it contains a tunable parameter that sets the length scale of interactions. By studying how rankings and discovered communities change when this parameter is varied allows us to identify locally and globally important nodes and structures. We apply the proposed method to several benchmark networks and show that it leads to better insight into network structure than alternative methods.Comment: 11 pages, submitted to Physical Review

A quasi-analytical model for energy-delay-reliability tradeoff studies during write operations in perpendicular STT-RAM cell

One of the biggest challenges the current STT-RAM industry faces is maintaining a high thermal stability while trying to switch within a given voltage pulse and energy cost. In this paper, we present a physics based analytical model that uses a modified Simmons' tunneling expression to capture the spin dependent tunneling in a magnetic tunnel junction(MTJ). Coupled with an analytical derivation of the critical switching current based on the Landau-Lifshitz-Gilbert equation, and the write error rate derived from a solution to the Fokker-Planck equation, this model provides us a quick estimate of the energydelay- reliability tradeoffs in perpendicular STTRAMs due to thermal fluctuations. In other words, the model provides a simple way to calculate the energy consumed during a write operation that ensures a certain error rate and delay time, while being numerically far less intensive than a full-fledged stochastic calculation. We calculate the worst case energy consumption during anti-parallel (AP) to parallel (P) and P to AP switchings and quantify how increasing the anisotropy field HK and lowering the saturation magnetization MS, can significantly reduce the energy consumption. A case study on how manufacturing variations of the MTJ cell can affect the energy consumption and delay is also reported.Comment: 6 pages, 9 figure