Taking the temperature – forecasting GDP growth for mainland China

We present a new composite leading indicator of economic activity in mainland China, es-timated using a dynamic factor model. Our leading indicator is constructed from three se-ries: exports, a real estate climate index, and the Shanghai Stock Exchange index. These series are found to share a common, unobservable element from which our indicator can be identified. This indicator is then incorporated into out-of-sample one-step-ahead forecasts of Chinese GDP growth. Recursive out-of-sample accuracy tests indicate that the small-scale factor model approach leads to a successful representation of the sample data and provides an appropriate tool for forecasting Chinese business conditions.forecasting; China; leading indicator; factor model; growth cycles

Drifting Together or Falling Apart? The Empirics of Regional Economic Growth in Post-Unification Germany

The objective of this paper is to address the question of convergence across German districts in the first decade after German unification by drawing out and emphasising some stylised facts of regional per capita income dynamics. We achieve this by employing non-parametric techniques which focus on the evolution of the entire cross-sectional income distribution. In particular, we follow a distributional approach to convergence based on kernel density estimation and implement a number of tests to establish the statistical significance of our findings. This paper finds that the relative income distribution appears to be stratifying into a trimodal/bimodal distribution.regional economic growth, Germany, convergence clubs, density estimation, modality tests

Economic Growth across Space and Time: subprovincial Evidence from Mainland China

We present a new composite leading indicator of economic activity in mainland China, estimated using a dynamic factor model. Our leading indicator is constructed from three series: exports, a real estate climate index, and the Shanghai Stock Exchange index. These series are found to share a common, unobservable element from which our indicator can be identified. This indicator is then incorporated into out-of-sample one-step-ahead forecasts of Chinese GDP growth. Recursive out-of-sample accuracy tests indicate that the small scale factor model approach leads to successful representation of the sample data and provides an appropriate tool for forecasting Chinese business conditions.Regional Economic Growth, China

Investigating agglomeration economies in a panel of European cities and regions

This paper investigates agglomeration economies in an annual panel of NUTS 2 and NUTS 3 city regions across France, Germany, Ireland, Italy, Spain and the UK over 1980-2006 and comparing three sub-samples to see if the effects have changed over time. We uncover evidence of long run agglomeration effects of around 6% for NUTS 2 and NUTS 3 city regions for the full sample. The underlying pattern that this data reflects is changing sectoral composition in which manufacturing was declining, to be largely replaced by services; then more recently a period of city-based economic growth with the financial and business services-led boom at its heart

Der Lebensyzklus eines Kleidungsstücks aus Baumwolle

Der Lebensyzklus eines Kleidungsstücks aus Baumwolle

Partial synchronisation of stochastic oscillators through hydrodynamic coupling

Holographic optical tweezers are used to construct a static bistable optical potential energy landscape where a Brownian particle experiences restoring forces from two nearby optical traps and undergoes thermally activated transitions between the two energy minima. Hydrodynamic coupling between two such systems results in their partial synchronisation. This is interpreted as an emergence of higher mobility pathways, along which it is easier to overcome barriers to structural rearrangement.Comment: 4 pages, 4 figures, submitted to Phys. Rev. Let

Predicting Temporal Patterns In The Environment: Toward Primitive Mechanisms Of Learning, Memory, And Generalization

Across a wide range of cognitive tasks, recent experience influences subsequent behavior. For example, when individuals repeatedly perform a speeded two-alternative choice task, response latencies vary dramatically based on the immediately preceding sequence. These sequential dependencies (SDs) have been interpreted as adaptation to the statistical structure of an uncertain, changing environment (e.g., Jones & Sieck, 2003; Mozer, Kinoshita, & Shettel, 2007; Yu & Cohen, 2009), and can shed light on how individuals learn and represent structure in binary stimulus sequences. Heretofore, theories have posited that SDs arise from rapidly (exponentially) decaying memory traces of various environmental statistics (e.g., Cho et al., 2002; Yu & Cohen, 2009).

We present a series of experiments and a model that place SDs on a fundamentally different foundation. We show that: (1) decay of recent experience can follow a power function curve, not an exponential, linking the SD literature
to a rich literature on human declarative memory; (2) the simple trace-based mechanism underlying existing accounts is inadequate, but incremental memory adjustments may be explained via error correction, linking the SD literature to the rich literature on human associative learning; and (3) distinct but interacting subsystems are found in the brain that jointly predict upcoming environmental events. 

We conducted three behavioral studies with EEG recordings of individuals performing discrimination of spatial location and motion coherence. Identifying the onset of the lateralized readiness potential (LRP) in an event-related EEG analysis, we are able to decompose the total response latency into two intervals—pre and post LRP onset—and to examine SDs in stimulus and response processing separately. We find evidence for two distinct mechanisms, one reflecting incremental learning of stimulus repetition rate (i.e., the probability that successive
stimuli will match), and the other reflecting incremental learning of response baserates. The data cannot be explained by a model that assumes these rates are based on independent traces, and calls for an account in which the two rates jointly predict future stimuli via error-correction learning. 

By manipulating the autocorrelation structure of the sequences (from a positive to a negative autocorrelation, indicated on the graphs by blue and red lines, respectively), we obtained evidence for incremental learning occurring over hundreds of trials, which is parsimoniously explained by a memory with power function decay. Together, the results highlight a tension between the two broad and well established classes of trace-based memory models and learning models based on error correction. Two attempts at reconciling these approaches via modeling are discussed

Species diversity of bats along an altitudinal gradient on Mount Mulanje, southern Malawi

A climate model, based on effects of water availability and temperature, was recently proposed to explain global variation in bat species richness along altitudinal gradients. Yet such studies are sparse in the tropics and near-absent in Africa. Here we present results from an altitudinal study of bat diversity from Mount Mulanje, Malawi. Using ground nets, canopy nets and harp traps, we sampled eight sites across three habitat zones from 630 m to 2010 m asl. We assessed the influence of climatic, geographic and biotic variables on measures of estimated species richness, Fisher's α, and an unbiased index of compositional turnover. We recorded 723 individuals and 30 species along the gradient, revealing a ‘low plateau' pattern in estimated species richness, peaking at 1220 m, which is congruent with the global climate model. Measures of local habitat structure significantly explained a large degree of variation in species richness and compositional turnover between sites. Fisher's α was further significantly correlated to mean annual relative humidity, suggesting a background climatic influenc

Development of arcjet and ion propulsion for spacecraft stationkeeping

Near term flight applications of arc jet and ion thruster satellite station-keeping systems as well as development activities in Europe, Japan, and the United States are reviewed. At least two arc jet and three ion propulsion flights are scheduled during the 1992-1995 period. Ground demonstration technology programs are focusing on the development of kW-class hydrazine and ammonia arc jets and xenon ion thrusters. Recent work at NASA LeRC on electric thruster and system integration technologies relating to satellite station keeping and repositioning will also be summarized