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Measurement error causes a bias towards zero when estimating a panel data linear regression model. The panel data context offers various opportunities to derive instrumental variables allowing for consistent estimation. We consider three sources of moment conditions: (i) restrictions on the covariance matrix of the errors in the equations, (ii) nonzero third moments of the regressors, and (iii) heteroskedasticity and nonlinearity in the relation between the error-ridden regressor and another, error-free, regressor. In simulations, these approaches appear to work well. (C) 2017 Elsevier B.V. All rights reserved.

We study the influence on firm risks of NASDAQ and NYSE firm payout initiations and omissions. These payout events can be interpreted as managerial signals of firm financial life-cycle maturation resulting in concomitant changes in firm risks. We remove confounding payout types and we match on the propensity to initiate or omit informed by determinants of payout known to investors in advance. For payout event and matched firms, we apply the difference-in-differences method to estimate the effect of the information content of actual initiations and omissions on firm risks. We find consistent significant declines in total, aggregate systematic, and idiosyncratic firm risks after cash dividend initiations and increases after dividend omissions, but only incidentally after share repurchase initiations and omissions. (C) 2014 Elsevier B.V. All rights reserved.

The objective of this paper is to extend the results on Pseudo Maximum Likelihood (PML) theory derived in Gourieroux, Monfort, and Trognon (GMT) (1984) to a situation where the first four conditional moments are specified. Such an extension is relevant in light of pervasive evidence that conditional distributions are non-Gaussian in many economic situations. The key statistical tool here is the quartic exponential family, which allows us to generalize the PML2 and QGPML1 methods proposed in GMT(1984) to PML4 and QGPML2 methods, respectively. An asymptotic theory is developed which shows, in particular, that the QGPML2 method reaches the semi-parametric bound. The key numerical tool that we use is the Gauss-Freud integration scheme which solves a computational problem that has previously been raised in several econometric fields. Simulation exercises show the feasibility and robustness of the methods.

We relate US portfolio returns, book-to-market values and excess stock returns to different dimensions of socially responsible performance. We find that socially responsible investing (SRI) impacts on stock returns by lowering the book-to-market ratio and not by generating positive alphas. Our result is consistent with the theoretical work suggesting that SRI is reflected in demand differences between SRI and non-SRI stock. It also explains why so few studies are able to establish a link between alpha's and SRI, We relate US portfolio returns, book-to-market values and excess stock returns to different dimensions of socially responsible performance. We find that socially responsible investing (SRI) impacts on stock returns by lowering the book-to-market ratio and not by generating positive alphas. Our result is consistent with the theoretical work suggesting that SRI is reflected in demand differences between SRI and non-SRI stock. It also explains why so few studies are able to establish a link between alpha’s and SRI.

This article employs the Structure–Conduct–Performance (SCP) paradigm to investigate the simultaneous relationship between industrial concentration, price rigidity, technical efficiency, and price-cost margin in the Indonesian food and beverages industry. This research extends the SCP framework by including price rigidity and technical efficiency as additional key variables. The results suggest that there is a simultaneous relationship between industrial concentration, price rigidity, technical efficiency, and price-cost margin with a positive bi-directional relationship between industrial concentration and price-cost margin. These findings imply that an appropriate course of action for the regulator in this highly concentrated industry is to reduce industrial concentration in order to increase competition, reduce upward price flexibility, and increase technical efficiency in the long run.

A present study addresses some cornerstones in designing high performance optical instruments. Very often the practical work starts via feasibility studies on whether something can be measured or not. Either lab or process instruments are used to find response in a given spectral range. Other specifications address signal-to-noise ratio, sensitivity, selectivity, application-related linearity as well as instrument related photometric linearity, accuracy, and repeatability. Much of the work focuses on establishing a correlation between primary lab method and secondary spectral method. Less attention is often paid to scattering and absorption properties of samples. At some later point in application development, all method developers pay attention to these issues at latest when calibrating spectral instruments with chemometric tools, either knowingly or unknowingly. In many industries, both near and mid infrared spectroscopy rely on sample chemistry and specific absorptions while down-weighting the physical interferences caused by packing density variations, particle size distribution differences, surface topography variations, and/or other optical path length variations. Chemometric tools such as standard normal variate (SNV), spectral interference subtraction (SIS), inverted signal correction (ISC), multiplicative signal correction (MSC), and their extensions (EISC and EMSC) correct for these physical interferences and greatly simplify calibrations. While these methods solve the problem for calibration, there are areas where this is not enough, namely, the design processes of optical instruments. This work illustrates some tools developed and used routinely in VTT Optical Instrumentation Center prior to designing new optical instruments. Particularly, these tools address the estimation of optical properties of sample materials representative to real processes. This work illustrates how experimental data can be collected using a specially designed hardware accessory and high performance double-beam lab UV-vis-NIR spectrometer and how tailored software tools can be used to study these data and compute optical properties of sample materials. Though these optical properties may not be exact estimates, they are very important and accurate enough for the design of tailored optical instruments for performance-critical customer applications. The study shown here presents results from near infrared (NIR) measurement made on industrial applications. The results and methods shown here are directly applicable both for studying sample properties and for designing appropriate sampling optics for existing commercial or tailor-made optical instruments whether the working range is in ultraviolet (UV), visible, fluorescence, Raman, NIR, or mid infrared (MIR). This study shows how the above methods can bring along significant benefits in the design phase of optical instruments. To conclude this presentation, we present also general guidelines how to design a high performance optical instrument

A present study addresses some cornerstones in designing high performance optical instruments. Very often the practical work starts via feasibility studies on whether something can be measured or not. Either lab or process instruments are used to find response in a given spectral range. Other specifications address signal-to-noise ratio, sensitivity, selectivity, application-related linearity as well as instrument related photometric linearity, accuracy, and repeatability. Much of the work focuses on establishing a correlation between primary lab method and secondary spectral method. Less attention is often paid to scattering and absorption properties of samples. At some later point in application development, all method developers pay attention to these issues at latest when calibrating spectral instruments with chemometric tools, either knowingly or unknowingly. In many industries, both near and mid infrared spectroscopy rely on sample chemistry and specific absorptions while down-weighting the physical interferences caused by packing density variations, particle size distribution differences, surface topography variations, and/or other optical path length variations. Chemometric tools such as standard normal variate (SNV), spectral interference subtraction (SIS), inverted signal correction (ISC), multiplicative signal correction (MSC), and their extensions (EISC and EMSC) correct for these physical interferences and greatly simplify calibrations. While these methods solve the problem for calibration, there are areas where this is not enough, namely, the design processes of optical instruments. This work illustrates some tools developed and used routinely in VTT Optical Instrumentation Center prior to designing new optical instruments. Particularly, these tools address the estimation of optical properties of sample materials representative to real processes. This work illustrates how experimental data can be collected using a specially designed hardware accessory and high performance double-beam lab UV-vis-NIR spectrometer and how tailored software tools can be used to study these data and compute optical properties of sample materials. Though these optical properties may not be exact estimates, they are very important and accurate enough for the design of tailored optical instruments for performance-critical customer applications. The study shown here presents results from near infrared (NIR) measurement made on industrial applications. The results and methods shown here are directly applicable both for studying sample properties and for designing appropriate sampling optics for existing commercial or tailor-made optical instruments whether the working range is in ultraviolet (UV), visible, fluorescence, Raman, NIR, or mid infrared (MIR). This study shows how the above methods can bring along significant benefits in the design phase of optical instruments. To conclude this presentation, we present also general guidelines how to design a high performance optical instrument