Do the secondary markets believe in life after debt?

Using panel data econometric techniques to examine the case for external debt relief, this report explores the relations between measures of creditworthiness and debt discounts on the secondary markets. It finds, however, that secondary market values tend to reflect past difficulties, not anticipate future ones - so they can't be used to build a case for debt relief. The secondary markets, still in an early evolutionary stage, are quite"thin"and thus unable to exploit efficiently and quickly all available information on creditworthiness.Environmental Economics&Policies,Strategic Debt Management,Economic Theory&Research,Banks&Banking Reform,Financial Intermediation

The Multinomial Multiperiod Probit Model: Identification and Efficient Estimation

In this paper we discuss parameter identification and likelihood evaluation for multinomial multiperiod Probit models. It is shown in particular that the standard autoregressive specification used in the literature can be interpreted as a latent common factor model. However, this specification is not invariant with respect to the selection of the baseline category. Hence, we propose an alternative specification which is invariant with respect to such a selection and identifies coefficients characterizing the stationary covariance matrix which are not identified in the standard approach. For likelihood evaluation requiring high-dimensional truncated integration we propose to use a generic procedure known as Efficient Importance Sampling (EIS). A special case of our proposed EIS algorithm is the standard GHK probability simulator. To illustrate the relative performance of both procedures we perform a set Monte-Carlo experiments. Our results indicate substantial numerical e?ciency gains of the ML estimates based on GHK-EIS relative to ML estimates obtained by using GHK

Offsetting Versus Mitigation Activities to Reduce CO2 Emissions: A Theoretical and Empirical Analysis for the U.S. And Germany

This paper studies the voluntary provision of public goods that is partially driven by a desire to offset for individual polluting activities. We first extend existing theory and show that offsets allow a reduction in effective environmental pollution levels while not necessarily extending the consumption of a polluting good. We further show a nonmonotonic income-pollution relationship and derive comparative static results for the impact f an increasing environmental preference on purchases of offsets and mitigation activities. Several theoretical results are then econometrically tested using a novel data set on activities to reduce CO2 emissions for the case of vehicle purchases in the U.S. and Germany. We show that an increased environmental preference triggers the use of CO2 offsetting and mitigation channels in both countries. However, we find strong country differences for the purchase of CO2 offsets. While such activities are already triggered by a high general awareness of the climate change problem in the U.S., driver's license holders in Germany need to additionally perceive road traffic as being responsible for CO2 emissions to a large extent

Rapid and Accurate Multiple Testing Correction and Power Estimation for Millions of Correlated Markers

With the development of high-throughput sequencing and genotyping technologies, the number of markers collected in genetic association studies is growing rapidly, increasing the importance of methods for correcting for multiple hypothesis testing. The permutation test is widely considered the gold standard for accurate multiple testing correction, but it is often computationally impractical for these large datasets. Recently, several studies proposed efficient alternative approaches to the permutation test based on the multivariate normal distribution (MVN). However, they cannot accurately correct for multiple testing in genome-wide association studies for two reasons. First, these methods require partitioning of the genome into many disjoint blocks and ignore all correlations between markers from different blocks. Second, the true null distribution of the test statistic often fails to follow the asymptotic distribution at the tails of the distribution. We propose an accurate and efficient method for multiple testing correction in genome-wide association studies—SLIDE. Our method accounts for all correlation within a sliding window and corrects for the departure of the true null distribution of the statistic from the asymptotic distribution. In simulations using the Wellcome Trust Case Control Consortium data, the error rate of SLIDE's corrected p-values is more than 20 times smaller than the error rate of the previous MVN-based methods' corrected p-values, while SLIDE is orders of magnitude faster than the permutation test and other competing methods. We also extend the MVN framework to the problem of estimating the statistical power of an association study with correlated markers and propose an efficient and accurate power estimation method SLIP. SLIP and SLIDE are available at http://slide.cs.ucla.edu

The Necessity of Self-Employment Towards Retirement: Evidence from Labor Market Dynamics and Search Requirements for Unemployment Benefits

Hervorming Sociale Regelgevin