Non-minimization of source taxes on labor income: empirical evidence from Germany

The present paper analyzes the choice of tax classes by married couples under the German withholding tax on wage income. Making use of micro data from official tax returns for the year 1998 and conducting simulation analysis, it is shown that more than 20 percent of the observed households do not choose the tax class combination that minimizes withholding. In the second part of the paper, several explanations for this result are discussed. Among those explanations, transaction costs and Pareto-inefficient intrahousehold-decision-making are the most likely.     

Living Differences: Ethnicity and Fearless Girls in Public Spaces

Its strength (of the book of Jules Verne, Snr) comes precisely from knowing never to invent, but paying acute, almost hypnotic, attention to the real, so as to get it to yield up its secret and reveal its possibilities.(Writings on the City)     

Sequential Monte Carlo on large binary sampling spaces

A Monte Carlo algorithm is said to be adaptive if it automatically calibrates its current proposal distribution using past simulations. The choice of the parametric family that defines the set of proposal distributions is critical for good performance. In this paper, we present such a parametric family for adaptive sampling on high dimensional binary spaces. A practical motivation for this problem is variable selection in a linear regression context. We want to sample from a Bayesian posterior distribution on the model space using an appropriate version of Sequential Monte Carlo. Raw versions of Sequential Monte Carlo are easily implemented using binary vectors with independent components. For high dimensional problems, however, these simple proposals do not yield satisfactory results. The key to an efficient adaptive algorithm are binary parametric families which take correlations into account, analogously to the multivariate normal distribution on continuous spaces. We provide a review of models for binary data and make one of them work in the context of Sequential Monte Carlo sampling. Computational studies on real life data with about a hundred covariates suggest that, on difficult instances, our Sequential Monte Carlo approach clearly outperforms standard techniques based on Markov chain exploration.     

Cooperation governance mode: an extended transaction cost approach

This paper analyses the cooperation governance mode and possible factors affecting the choice between an equity joint venture and a contractual agreement. Although transaction cost economics (TCE) provides a workable and well-used framework within which to analyse this choice, it only captures the static transaction costs related to the two modes. This has lead to a discussion about dynamic governance costs and possible benefits related to the governance mode. The objective of this paper is to show how this extended framework differs from TCE when determining the appropriate governance mode. We use four factors related to nature of cooperation to contrast these two approaches. We collected empirical data about cooperation in the information and communications technology (ICT) sector in order to find support for these arguments. Estimates based on logistic regression analysis suggest that our dynamic governance cost and benefit perspective really provides valuable complementary insights into the traditional static transaction-cost framework when it is a question of the choice of alliance form.     

The impact of macroeconomic conditions on income inequality

This paper analyzes the relationship between macroeconomic factors and the income distribution using data on equivalized disposable household income from the United Kingdom for 1961–99. We argue in favour of fitting a parametric functional form to the income distribution for each year, and then modeling the time series of model parameters in terms of the macroeconomic factors, as this better allows us to take into account non-stationarity in the time series. Estimates from models that relate income distribution parameters to cyclical variables in first differences (to account for non-stationarity) suggest that neither inflation nor unemployment have significant effects on income inequality. Compared to the commonly-used method of modelling the income shares directly, our approach indicates that there was no clear cut relationship between macroeconomic factors and the UK income distribution during the last third of the twentieth century.     

Fitting probability distributions to economic growth: a maximum likelihood approach

The growth rate of the gross domestic product (GDP) usually carries heteroscedasticity, asymmetry and fat-tails. In this study three important and significantly heteroscedastic GDP series are examined. A Normal, normal-mixture, normal-asymmetric Laplace distribution and a Student's t-Asymmetric Laplace (TAL) distribution mixture are considered for distributional fit comparison of GDP growth series after removing heteroscedasticity. The parameters of the distributions have been estimated using maximum likelihood method. Based on the results of different accuracy measures, goodness-of-fit tests and plots, we find out that in the case of asymmetric, heteroscedastic and highly leptokurtic data the TAL-distribution fits better than the alternatives. In the case of asymmetric, heteroscedastic but less leptokurtic data the NM fit is superior. Furthermore, a simulation study has been carried out to obtain standard errors for the estimated parameters. The results of this study might be used in e.g. density forecasting of GDP growth series or to compare different economies.