Falling Wage Shares in Europe and the United States: How Important is Aggregation Bias?

This paper sheds light on the importance of aggregation bias in the analysis of wage shares developments over time and across countries. We focus on five European countries and the United States and show that the trend decline in the aggregate wage share observed in these countries over much of the 1980s and 1990s partly reflects changes in the sectoral composition of the economy. The application of a fixed-weight aggregation method changes the profile of the observed wage share in a significant way: in particular there is no longer sign of an overshooting of the wage share levels of the early-1970s. Error-correction wage equations based on the adjusted wage shares generally have a better regression fit and show long-run elasticities of real wages to unemployment that vary less across countries and are substantially lower than those obtained with observed shares.     

Built environment diversities and activity–travel behaviour variations in Beijing, China

The association between built environment and travel behaviour has received considerable research attention in recent years. In an attempt to contribute to this growing literature, this paper investigates the connections between urban built environments and activity–travel patterns in Beijing, the capital city of China. We characterize the built environment in Beijing and establish associations between built environment and activity–travel behaviour in terms of car ownership, time spent for out-of-home activities, and daily trip frequencies and travel time. Activity diaries from 1119 respondents living in ten different neighbourhoods were collected by face-to-face interviews. A household-level structure equations model incorporating intra-household interactions is developed to analyse this data. The empirical results show that residents of different types of neighbourhoods in Beijing demonstrate significant differences in car ownership, time spent for out-of-home activities, trip rate, and travel time. Further, the characteristics of the built environment are found to have more significant impacts on the activity–travel behaviour of the male head than that of the female head.     

Optimal investment-reinsurance with dynamic risk constraint and regime switching

We study an optimal investment–reinsurance problem for an insurer who faces dynamic risk constraint in a Markovian regime-switching environment. The goal of the insurer is to maximize the expected utility of terminal wealth. Here the dynamic risk constraint is described by the maximal conditional Value at Risk over different economic states. The rationale is to provide a prudent investment–reinsurance strategy by taking into account the worst case scenario over different economic states. Using the dynamic programming approach, we obtain an analytical solution of the problem when the insurance business is modeled by either the classical Cramer–Lundberg model or its diffusion approximation. We document some important qualitative behaviors of the optimal investment–reinsurance strategies and investigate the impacts of switching regimes and risk constraint on the optimal strategies.     

Relevance weighted likelihood for dependent data

The relevance-weighted likelihood function weights individual contributions to the likelihood according to their relevance for the inferential problem of interest. Consistency and asymptotic normality of the weighted maximum likelihood estimator were previously proved for independent sequences of random variables. We extend these results to apply to dependent sequences, and, in so doing, provide a unified approach to a number of diverse problems in dependent data. In particular, we provide a heretofore unknown approach for dealing with heterogeneity in adaptive designs, and unify the smoothing approach that appears in many foundational papers for independent data. Applications are given in clinical trials, psychophysics experiments, time series models, transition models, and nonparametric regression. Received: April 2000     

Investment and the real exchange rate’s profitability channel in Mexico

The paper estimates different versions of an equation for private investment in Mexico during the post-liberalization period 1988–2013, with the aim of studying the operation of the recently discussed real exchange rate’s profitability channel. During this period, the real exchange rate (RER) was broadly positively correlated with the Mexican price/wage ratio and the Mexican/US relative profit margin in the manufacturing sector, particularly so when the RER experienced large fluctuations, before the end of disinflation in the early 2000s. In the estimations, the effect of the profit margin appears to be ‘deeper’, wiping out the effect of the RER when the two variables are included together in the investment equation. From this, the paper argues that the positive effect of the RER on investment, observed in previous studies that omitted the profit margin, reflects indirectly the positive link of the RER with the profit margin, supporting the existence of a profitability channel in Mexico.     

THE EIGENFUNCTION EXPANSION METHOD IN MULTI-FACTOR QUADRATIC TERM STRUCTURE MODELS

We propose the eigenfunction expansion method for pricing options in quadratic term structure models. The eigenvalues, eigenfunctions, and adjoint functions are calculated using elements of the representation theory of Lie algebras not only in the self-adjoint case, but in non-self-adjoint case as well; the eigenfunctions and adjoint functions are expressed in terms of Hermite polynomials. We demonstrate that the method is efficient for pricing caps, floors, and swaptions, if time to maturity is 1 year or more. We also consider subordination of the same class of models, and show that in the framework of the eigenfunction expansion approach, the subordinated models are (almost) as simple as pure Gaussian models. We study the dependence of Black implied volatilities and option prices on the type of non-Gaussian innovations.     

Statistical Analysis with Linked Data

Computerised Record Linkage methods help us combine multiple data sets from different sources when a single data set with all necessary information is unavailable or when data collection on additional variables is time consuming and extremely costly. Linkage errors are inevitable in the linked data set because of the unavailability of error‐free unique identifiers. A small amount of linkage errors can lead to substantial bias and increased variability in estimating parameters of a statistical model. In this paper, we propose a unified theory for statistical analysis with linked data. Our proposed method, unlike the ones available for secondary data analysis of linked data, exploits record linkage process data as an alternative to taking a costly sample to evaluate error rates from the record linkage procedure. A jackknife method is introduced to estimate bias, covariance matrix and mean squared error of our proposed estimators. Simulation results are presented to evaluate the performance of the proposed estimators that account for linkage errors.     

A PDE method for estimation of implied volatility

In this paper it is proved that the Black–Scholes implied volatility satisfies a second order non-linear partial differential equation. The obtained PDE is then used to construct an algorithm for fast and accurate polynomial approximation for Black–Scholes implied volatility that improves on the existing numerical schemes from literature, both in speed and parallelizability. We also show that the method is applicable to other problems, such as approximation of implied Bachelier volatility.