The Exporter Productivity Premium along the Productivity Distribution: First Evidence from a Quantile Regression Approach for Fixed Effects Panel Data Models

An emerging literature on international activities of heterogeneous firms documents that exporting firms are more productive than firms that only sell on the national market. This positive exporter productivity premium shows up in a large number of empirical studies after controlling for observed and unobserved firm characteristics in regression models including firm fixed effects. These studies test for a difference in productivity between exporters and non-exporters at the conditional mean of the productivity distribution. However, if firms are heterogeneous, it is possible that the size of the premium varies over the productivity distribution. In this paper we apply a newly developed estimator for fixed-effects quantile regression models to estimate the exporter productivity premium at quantiles of the productivity distribution for manufacturing enterprises in Germany, one of the leading actors in the world market for goods. We show that the premium decreases over the quantiles – a dimension of firm heterogeneity that cannot be detected through mean regression.Exporter productivity premium, quantile regression, fixed effects

The Exporter Productivity Premium along the Productivity Distribution: First Evidence from a Quantile Regression Approach for Fixed Effects Panel Data Models

An emerging literature on international activities of heterogeneous firms documents that exporting firms are more productive than firms that only sell on the national market. This positive exporter productivity premium shows up in a large number of empirical studies after controlling for observed and unobserved firm characteristics in regression models including firm fixed effects. These studies test for a difference in productivity between exporters and non-exporters at the conditional mean of the productivity distribution. However, if firms are heterogeneous, it is possible that the size of the premium varies over the productivity distribution. In this paper we apply a newly developed estimator for fixed-effects quantile regression models to estimate the exporter productivity premium at quantiles of the productivity distribution for manufacturing enterprises in Germany, one of the leading actors in the world market for goods. We show that the premium decreases over the quantiles – a dimension of firm heterogeneity that cannot be detected through mean regression.exporter productivity premium, quantile regression, fixed effects

Minimum thrust levels for spinning drag-free satellites = Niveaux minimums de la force motrice pour des satellites rotatoires sans résistance = Minimum triebkraftniveaus für rotierende wiederstandsfreie satelliten

A drag-free satellite, which contains an internal unsupported proof mass, is shielded from external forces such as solar pressure. Thrustors force the satellite to follow the proof mass and hence the satellite follows an almost purely gravitational orbit. The dominant internal disturbing force is the mass attraction of the satellite on the proof mass. Spinning the satellite reduces this force and it has been investigated what the size of the thrustors must be in this case. This size is much smaller than originally thought. Its impact on some other features is shown

Accurate metasurface synthesis incorporating near-field coupling effects

One of the most promising metasurface architectures for the microwave and terahertz frequency ranges consists of three patterned metallic layers separated by dielectrics. Such metasurfaces are well suited to planar fabrication techniques and their synthesis is facilitated by modelling them as impedance sheets separated by transmission lines. We show that this model can be significantly inaccurate in some cases, due to near-field coupling between metallic layers. This problem is particularly severe for higher frequency designs, where fabrication tolerances prevent the patterns from being highly-subwavelength in size. Since the near-field coupling is difficult to describe analytically, correcting for it in a design typically requires numerical optimization. We propose an extension of the widely used equivalent-circuit model to incorporate near-field coupling and show that the extended model can predict the scattering parameters of a metasurface accurately. Based on our extended model, we introduce an improved metasurface synthesis algorithm that gives physical insight to the problem and efficiently compensates for the perturbations induced by near-field coupling. Using the proposed algorithm, a Huygens metasurface for beam refraction is synthesized showing a performance close to the theoretical efficiency limit despite the presence of strong near-field coupling

Industry Market Value at Risk in Australia

Value at Risk (VaR) is an important issue for banks since its adoption as a primary risk metric in the Basel Accords and the requirement that it is calculated on a daily basis. Relative industry risk measurement is also very important to Banks in their management of risk, such as for setting risk concentration limits and developing investment and credit policy. This paper examines market Value at Risk (VaR) and Conditional VaR (CVaR) in Australia from an industry perspective using a set of Australian industries. VaR and CVaR are compared between these industries over time, and a variety of metrics are used including diversified and undiversified VaR, as well as parametric and nonparametric CVaR methods. There has been no prior investigation of industry based VaR metrics in Australia to the authorsÌ knowledge. The relative riskiness of different industry sectors is examined and using diversified VaR, the study .nds the highest risk is in the Technology Sectors, whilst the lowest risk is found in the Finance and Utilities Sectors. Composite riskiness is also explored and the existence of correlation between industry risk rankings over time is found to depend on the number of years of data used. There is evidence of rank correlation over time using a 7 year window approach, but not when using 1 year data tranches. This highlights the importance of using both short and long time frames in order to cover different economic cycles as well as consider current conditions. It is important to note that there is found to be no significant difference between diversified and undiversified industry VaR rankings, or between parametric and nonparametric CVaR approaches. This means that bankers can be reasonably confident of the robustness of any one of these metrics when calculating and applying them, not only for the purposes of Basel compliance, but also for the determination of relative industry risk.Conditional value at risk (CVaR), Industry risk, Basel compliance

CVaR and Credit Risk Measurement

The link between credit risk and the current financial crisis accentuates the importance of measuring and predicting extreme credit risk. Conditional Value at Risk (CVaR) has become an increasingly popular method for measuring extreme market risk. We apply these CVaR techniques to the measurement of credit risk and compare the probability of default among Australian sectors prior to and during the financial crisis. An in depth understanding of sectoral risk is vital to Banks to ensure that there is not an overconcentration of credit risk in any sector. This paper demonstrates how CVaR methodology can be applied in different economic circumstances and provides Australian Banks with important insights into extreme sectoral credit risk leading up to and during the financial crisis.Conditional Value at Risk (CVaR), Banks, Structural modelling, Probability of default (PD)

Credit Risk and Real Capital: An Examination of Swiss Banking Sector Default Risk Using CVaR

The global financial crisis (GFC) has placed the creditworthiness of banks under intense scrutiny. In particular, capital adequacy has been called into question. Current capital requirements make no allowance for capital erosion caused by movements in the market value of assets. This paper examines default probabilities of Swiss banks under extreme conditions using structural modeling techniques. Conditional Value at Risk (CVaR) and conditional probability of default (CPD) techniques are used to measure capital erosion. Significant increase in probability of default (PD) is found during the GFC period. The market asset value based approach indicates a much higher PD than external ratings indicate. Capital adequacy recommendations are formulated which distinguish between real and nominal capital based on asset fluctuations.Real capital; Financial crisis; Conditional value at risk; Credit risk; Banks; Probability of default; Capital adequacy