Assessing the Effect of Current Account and Currency Crises on Economic Growth

Several empirical studies are concerned with measuring the effect of currency and current account crises on economic growth. Using different empirical models this paper serves two aspects. It provides an explicit assessment of country specific factors influencing the costs of crises in terms of economic growth and controls via a treatment type model for possible sample selection governing the occurrence of crises in order to estimate the impact on economic growth correctly. The applied empirical models allow for rich intertemporal dependencies via serially correlated errors and capture latent country specific heterogeneity via random coe?cients. For accurate estimation of the treatment type model a simulated maximum likelihood approach employing efficient importance sampling is used. The results reveal significant costs in terms of economic growth for both crises. Costs for reversals are linked to country specific variables, while costs for currency crises are not. Furthermore, shocks explaining current account reversals and growth show strong significant positive correlation. --Currency crises,Current account reversals,Treatment Model,Discrete dependent variable,Efficient Importance Sampling,Panel Data

A bayesian approach to model-based clustering for panel probit models

Consideration of latent heterogeneity is of special importance in non linear models for gauging correctly the effect of explaining variables on the dependent variable. This paper adopts the stratified model-based clustering approach for modeling latent heterogeneity for panel probit models. Within a Bayesian framework an estimation algorithm dealing with the inherent label switching problem is provided. Determination of the number of clusters is based on the marginal likelihood and out-of-sample criteria. The ability to decide on the correct number of clusters is assessed within a simulation study indicating high accuracy for both approaches. Different concepts of marginal effects incorporating latent heterogeneity at different degrees arise within the considered model setup and are directly at hand within Bayesian estimation via MCMC methodology. An empirical illustration of the developed methodology indicates that consideration of latent heterogeneity via latent clusters provides the preferred model specification compared to a pooled and a random coefficient specification. --Bayesian Estimation,MCMC Methods,Panel Probit Model,Mixture Modelling

The Decline in German Output Volatility: A Bayesian Analysis

Empirical evidence suggests a sharp volatility decline of the growth in U.S. gross domestic product (GDP) in the mid-1980s. Using Bayesian methods, we analyze whether a volatility reduction can also be detected for the German GDP. Since statistical inference for volatility processes critically depends on the specification of the conditional mean we assume for our volatility analysis different time series models for GDP growth. We find across all specifications evidence for an output stabilization around 1993, after the downturn following the boom associated with the German reunification. However, the different GDP models lead to alternative characterizations of this stabilization : In a linear AR model it shows up as smaller shocks hitting the economy, while regime switching models reveal as further sources for a stabilization, a narrowing gap between growth rates during booms and recessions or flatter trajectories characterizing the GDP growth rates. Furthermore, it appears that the reunification interrupted an output stabilization emerging already around 1987. --business cycle models,Gibbs sampling,Markov Chain Monte Carlo,regime switching,structural breaks

Determinants and Costs of Current Account Reversals under Heterogeneity and Serial Correlation

Recent empirical evidence suggests that reversing current account balances imply costly adjustment processes leading to reduced economic growth. Using large panel data sets to analyze determinants and costs of reversals asks for controls of heterogeneity among countries. This paper contributes a Bayesian analysis, which allows a parsimonious yet flexible handling of country specific heterogeneity via random coeffcients. Furthermore, the analysis allows for serially correlated errors in order to capture persistence within the employed macroeconomic data. Bayesian specification tests provide evidence in favor of models incorporating heterogeneity and serial correlation. The results suggest that consideration of serial correlation and heterogeneity is necessary to assess correctly the determinants and costs of reversals. Results are checked for robustness against the underlying reversal definition. --Current account reversals,Bayesian Analysis,Panel Probit Model,Panel Treatment Model,Random Parameters,Serial Correlation

Chain Reversion for Detecting Associations in Interacting Variables-St. Nicolas House Analysis

(1) Background: We present a new statistical approach labeled as "St. Nicolas House Analysis" (SNHA) for detecting and visualizing extensive interactions among variables. (2) Method: We rank absolute bivariate correlation coefficients in descending order according to magnitude and create hierarchic "association chains" defined by sequences where reversing start and end point does not alter the ordering of elements. Association chains are used to characterize dependence structures of interacting variables by a graph. (3) Results: SNHA depicts association chains in highly, but also in weakly correlated data, and is robust towards spurious accidental associations. Overlapping association chains can be visualized as network graphs. Between independent variables significantly fewer associations are detected compared to standard correlation or linear model-based approaches. (4) Conclusion: We propose reversible association chains as a principle to detect dependencies among variables. The proposed method can be conceptualized as a non-parametric statistical method. It is especially suited for secondary data analysis as only aggregate information such as correlations matrices are required. The analysis provides an initial approach for clarifying potential associations that may be subject to subsequent hypothesis testing

Eine Empirische Analyse von Leistungsbilanzdaten

This thesis analyzes certain aspects of the current account balance and its relationship to economic growth. Employing recently developed statistical and econometric techniques for estimation of non linear models, crises phenomena connected to the balance of payments are focused. The analysis of crises phenomena has been subject to tremendous research efforts over the last decades. However, this thesis addresses several empirical and methodological issues, which have received less attention, namely the incorporation of latent heterogeneity and serial dependence structures in empirical models employed for explaining and assessing crises and their influence on economic growth

Nonlinear spectroscopy of exciton-polaritons in a GaAs-based microcavity

We present a systematic investigation of two-photon excitation processes in a GaAs-based microcavity in the strong-coupling regime. We observe second harmonic generation resonant to the upper and lower polariton level, which exhibits a strong dependence on the photonic fraction of the corresponding polariton. In addition we have performed two-photon excitation spectroscopy to identify $2p$ exciton states which are crucial for the operation as a terahertz lasing device, which was suggested recently [A. V. Kavokin et al., Phys. Rev. Lett. \textbf{108}, 197401 (2012)]. However, no distinct signatures of a $2p$ exciton state could be identified, which indicates a low two-photon pumping efficiency

Influence of interactions with non-condensed particles on the coherence of a 1D polariton condensate

One-dimensional polariton condensates (PoCos) in a photonic wire are generated through non-resonant laser excitation, by which also a reservoir of background carriers is created. Interaction with this reservoir may affect the coherence of the PoCo, which is studied here by injecting a condensate locally and monitoring the coherence along the wire. While the incoherent reservoir is mostly present within the excitation laser spot, the condensate can propagate ballistically through the wire. Photon correlation measurements show that far from the laser spot the second order correlation function approaches unity value, as expected for the coherent condensed state. When approaching the spot, however, the correlation function increases up to values of 1.2 showing the addition of noise to the emission due to interaction with the reservoir. This finding is substantiated by measuring the first order coherence by a double slit experiment, which shows a reduced visibility of interference at the excitation laser spot.Comment: 8 pages, 8 figure

A [email protected] Approach for Multi-objective Self-optimizing Software

This paper presents an approach to operate multi-objective self-optimizing software systems based on the [email protected] paradigm. In contrast to existing approaches, which are usually specific to a single or selected set of objectives (e.g., performance and/or reliability), the presented approach is generic in that it allows the software architect to model the relevant concerns of interest to self-optimization. At runtime, these models are interpreted and used to generate optimization problems. To evaluate the applicability of the approach, a scalability analysis is provided, showing the approach’s feasibility for at least two objectives