Inflation dynamics: a cross-country investigation

We document that "persistent and lagged" inflation (with respect to output) is a world-wide phenomenon in that these short-run inflation dynamics are highly synchronized across countries. In particular, the average cross-country correlation of inflation is significantly and systematically stronger than that of output, while the cross-country correlation of money growth is essentially zero. We investigate whether standard monetary models driven by monetary shocks are consistent with the empirical facts. We find that neither the new Keynesian sticky-price model nor the sticky-information model can fully explain the data. An independent contribution of the paper is to provide a simple solution technique for solving general equilibrium models with sticky information. ; Earlier title: Inflation and money: a puzzleMoney ; Inflation (Finance)

Another look at sticky prices and output persistence

Price rigidity is the key mechanism for propagating business cycles in traditional Keynesian theory. Yet the New Keynesian literature has failed to show that sticky prices by themselves can effectively propagate business cycles in general equilibrium. We show that price rigidity in fact can (by itself) give rise to a strong propagation mechanism of the business cycle in standard New Keynesian models, provided that investment is also subject to a cash-in-advance constraint. In particular, we show that reasonable price stickiness can generate highly persistent, hump-shaped movements in output, investment and employment in response to either monetary or non-monetary shocks, even if investment is only partially cash-in-advance constrained. Hence, whether or not price rigidity is responsible for output persistence (and the business cycle in general) may not be a theoretical question, but an empirical one.Prices ; Business cycles

Solving linear difference systems with lagged expectations by a method of undetermined coefficients

This paper proposes a solution method to solve linear difference models with lagged expectations. Variables with lagged expectations expand the model's state space greatly when N is large; and getting the system into a canonical form solvable by the traditional methods involves substantial manual work (e.g., arranging the state vector and the associated coefficient matrices to accommodate variables with lagged expectations), which is prone to human errors. Our method avoids the need of expanding the state space of the system and shifts the burden of analysis from the individual economist/model solver toward the computer. Hence it can be a very useful tool in practice, especially in testing and estimating economics models with a high order of lagged expectations. Examples are provided to demonstrate the usefulness of the method. We also discuss the implications of lagged expectations on the equilibrium properties of indeterminate DSGE models, such as the serial correlation properties of sunspots shocks in these models.Monetary policy ; Macroeconomics

Another Look at Sticky Prices and Output Persistence

Price rigidity is the key mechanism for propagating business cycles in traditional Keynesian theory. Yet the New Keynesian literature has failed to show that sticky prices by itself can effectively propagate business cycles in general equilibrium. This situation may be a direct consequence of the notion that money-in-utility (MIU) and cash-in-advance (CIA) are equivalent mechanisms for generating money demand. They are not. We show that price rigidity in fact can (by itself) give rise to a powerful propagation mechanism of the business cycle under CIA constraint in standard New Keynesian general equilibrium models. In particular, we show that reasonable price stickiness can generate highly persistent, hump-shaped movements in output, investment and employment in response to either monetary or non-monetary shocks. Hence, whether or not price rigidity is responsible for output persistence (and the business cycle in general) is not a theoretical question, but an empirical one.

Komplementäre Tunnel Feldeffekttransistoren (CTFET) in CMOS-Technologie

The short channel effects (SCE) are becoming serious problems as MOSFET scales down to the deep sub-micron dimension. For this reason, a silicon tunneling transistor called TFET is investigated. The device and process simulations are carried out to investigate physical principle, optimized fabrication conditions, and future structure of TFET. With the improved technologies, the complementary TFETs are realized on the single silicon wafer. The room temperature gate-controlled tunneling is realized in this silicon device. Due to the low leakage current, TFET can be used in the low power circuits. In addition, TFET is suitable for microwave application because of the short electron transit time through its channel.Für zukünftige MOSFET-Generationen treten neben technologischen Problemen große Schwierigkeiten aufgrund parasitärer Leckströme auf. Als alternatives ULSI-Bauelement ist in dieser Arbeit ein MOS-gesteuerter Tunneltransistor (TFET) untersucht worden. In Simulationen sind die Herstellungssequenzen, verschiedene Bauelementgeometrien und die resultierenden elektrischen Eigenschaften optimiert worden. In CMOS-Technologie wurden auf einem Si-wafer komplementäre TFETs hergestellt und charakterisiert. Durch Ausnutzung des Tunneleffektes im Stromtransport weisen die TFETs erheblich geringere Leckströme gegenüber MOSFETs auf, steuern über 6 Größenordnungen und vereinen die Vorteile der verlustarmen CMOS-Steuerung mit dem exponentiellen Stromanstieg eines Bipolartransistors. Diese Eigenschaften lassen den TFET für ultra-low power-Schaltungen und Höchstfrequenzanwendungen geeignet erscheinen

Structural Deep Embedding for Hyper-Networks

Network embedding has recently attracted lots of attentions in data mining. Existing network embedding methods mainly focus on networks with pairwise relationships. In real world, however, the relationships among data points could go beyond pairwise, i.e., three or more objects are involved in each relationship represented by a hyperedge, thus forming hyper-networks. These hyper-networks pose great challenges to existing network embedding methods when the hyperedges are indecomposable, that is to say, any subset of nodes in a hyperedge cannot form another hyperedge. These indecomposable hyperedges are especially common in heterogeneous networks. In this paper, we propose a novel Deep Hyper-Network Embedding (DHNE) model to embed hyper-networks with indecomposable hyperedges. More specifically, we theoretically prove that any linear similarity metric in embedding space commonly used in existing methods cannot maintain the indecomposibility property in hyper-networks, and thus propose a new deep model to realize a non-linear tuplewise similarity function while preserving both local and global proximities in the formed embedding space. We conduct extensive experiments on four different types of hyper-networks, including a GPS network, an online social network, a drug network and a semantic network. The empirical results demonstrate that our method can significantly and consistently outperform the state-of-the-art algorithms.Comment: Accepted by AAAI 1