A new perspective on the exporter productivity premium: online trade

We use a unique firm-level data set including 9000 companies from 26 European Union countries covering four different sectors to take a close look at the relationship between online exports and productivity. The online exporter productivity premium is estimated using different techniques (ordinary least squares, quantile regressions and robust estimation). Results consistently indicate that the estimated online exporter productivity premium is statistically different from zero, positive and significant from an economic point of view. European online exporters, according to these results, are approximately 2% more productive than non-online exporters. Productivity differences between firms could be related to variables that are not included in the empirical model. More research would be needed to address this issue in the future.     

MODELING SOVEREIGN RISKS: FROM A HYBRID MODEL TO THE GENERALIZED DENSITY APPROACH

Motivated by the European sovereign debt crisis, we propose a hybrid sovereign default model that combines an accessible part taking into account the evolution of the sovereign solvency and the impact of critical political events, and a totally inaccessible part for the idiosyncratic credit risk. We obtain closed‐form formulas for the probability that the default occurs at critical political dates in a Markovian setting. Moreover, we introduce a generalized density framework for the hybrid default time and deduce the compensator process of default. Finally, we apply the hybrid model and the generalized density to the valuation of sovereign bonds and explain the significant jumps in long‐term government bond yields during the sovereign crisis.     

Advertising to the masses: the effects of crowding on the attention to place-based advertising

Advertising situated in environments where people congregate or pass through on their way to somewhere else benefit from being placed in such high traffic areas. However, these strategically placed ads also suffer from conditions of human crowding that prevents them from being noticed and processed. We undertake a study of place-based advertising in a shopping mall using facial recognition software to determine the effect of human density on the attention directed to advertising. We find that as human density increases, attention to advertising decreases, but only to a point where it begins to increase again. Our research also finds that human density plays a moderating role on the motivation to process advertising.     

The Local Whittle Estimator of Long-Memory Stochastic Volatility

We propose a new semiparametric estimator of the degree of persistencein volatility for long memory stochastic volatility (LMSV) models.The estimator uses the periodogram of the log squared returnsin a local Whittle criterion which explicitly accounts for thenoise term in the LMSV model. Finite-sample and asymptotic standarderrors for the estimator are provided. An extensive simulationstudy reveals that the local Whittle estimator is much lessbiased and that the finite-sample standard errors yield moreaccurate confidence intervals than the widely-used GPH estimator.The estimator is also found to be robust against possible leverageeffects. In an empirical analysis of the daily Deutsche Mark/USDollar exchange rate, the new estimator indicates stronger persistencein volatility than the GPH estimator, provided that a largenumber of frequencies is used.     

Time Inhomogeneous Multiple Volatility Modeling

Price variations at speculative markets exhibit positive autocorrelationand cross correlation. Due to large parameter spaces necessaryfor joint modeling of variances and covariances, multivariateparametric volatility models become easily intractable in practice.We propose an adaptive procedure that identifies periods ofsecond-order homogeneity for each moment in time. To overcomethe high dimensionality of the problem we transform the multivariateseries into a set of univariate processes. We discuss thoroughlythe implementation of the adaptive technique. Theoretical andMonte Carlo results are given. We provide two applications ofthe new method. For a bivariate exchange rate series we comparethe multivariate GARCH approach with our method and find thelatter to be more in line with the underlying assumption ofindependently distributed innovations. Analyzing a 23-dimensionalvector of asset returns we underscore the case for adaptivemodeling in high-dimensional systems.     

Beyond Single-Factor Affine Term Structure Models

This article proposes a new approach to testing for the hypothesisof a single priced risk factor driving the term structure ofinterest rates. The method does not rely on any parametric specificationof the state variable dynamics or the market price of risk.It simply exploits the constraint imposed by the no-arbitragecondition on instantaneous expected bond returns. In order toachieve our goal, we develop a Kolmogorov-Smirnov test and applyit to data on Treasury bills and bonds for both the United Statesand Spain. We find that the single risk factor hypothesis cannotbe rejected for either dataset.     

部分石化项目专利费的分析和测算

介绍了专利费的特点和测算原则，并对引进的部分专利技术的专利费作了分析和预测。     

Option Trading and the Intervalling Effect Bias in Beta

Prior studies show that the beta coefficient of a security changes systematically as the length of measurement interval is varied. This phenomenon, which is called the intervalling effect bias in beta, has been attributed to the friction in the trading system that causes the delays in the price-adjustment process. This study shows that option listing is associated with a decline in the beta intervalling effect bias. The decline is most pronounced for small firms. We also find that our sample firms grow significantly after option listing. Since prior research indicates that market value is a major determinant of the magnitude of the intervalling effect, we re-examine our results using a subsample that controls for market value. The results indicate that the decline in the beta bias from the pre-listing to post-listing period is still prevalent after we control for the change in firm size. Overall, the evidence is consistent with the notion that option trading reduces the delays in the price-adjustment process, which in turn reduces the intervalling effect bias in beta.     

LABOUR SUPPLY ESTIMATION AND PUBLIC POLICY

Abstract. Economists devote considerable energies towards refining their econometric techniques to overcome difficulties connected with conducting empirical research. Despite advances in technique. it is not clear whether further refinement in this direction is worthwhile for policy purposes. It may be that no further amount of statistical adjustment of inadequate data will increase understanding, and that better data is simply necessary to add to our knowledge. But rarely is sufficient credit paid to new forms of data. In short, econometric technique is emphasized to the neglect of data innovation, as if new data were merely lying about waiting for an ingenious suggestion for use. This paper surveys advances of the last twenty five years in estimating labour supply for policy purposes with a view towards appreciating the relative contribution of both improvements in econometric technique as well as developments of new data.
After briefly detailing the key parameters which economists have sought to estimate, we describe the early 'first generation' research (circa 1970), which is plagued by problems of unobservable variables, measurement errors, truncation and selectivity bias, and non linear budget constraints. 'Second generation' research constitute attempts to resolve one or more of these difficulties, and the respective contribution of econometric technique and new data is acknowledged and assessed, including the contribution of data generated by large scale social experiments in which participants are randomly assigned to different guaranteed income plans and their labour supply behaviour measured.