Misspecified heteroskedasticity in the panel probit model: A small sample comparison of GMM and SML estimators

This paper compares generalized method of moments (GMM) and simulated maximum likelihood (SML) approaches to the estimation of the panel probit model. Both techniques circumvent multiple integration of joint density functions without the need to restrict the error term variance- covariance matrix of the latent normal regression model. Particular attention is paid to a three-stage GMM estimator based on nonparametric estimation of the optimal instruments for given conditional moment functions. Monte Carlo experiments are carried out which focus on the small sample consequences of misspecification of the error term variance-covariance matrix. The correctly specified experiment reveals the asymptotic efficiency advantages of SML. The GMM estimators outperform SML in the presence of misspecification in terms of multiplicative heteroskedasticity. This holds in particular for the three-stage GMM estimator. Allowing for heteroskedasticity over time increases the robustness with respect to misspecification in terms of ultiplicative heteroskedasticity. An application to the product innovation activities of German manufacturing firms is presented.

Horizontal and Vertical R&D Cooperation

This paper introduces a second, vertically related industry into the usual one-industry oligopoly framework of cooperative R&D investment between firms operating on the same product market. R&D efforts are affected by intra- and inter-industry R&D spillovers. Horizontal and vertical R&D cooperation scenarios are compared to R&D competition. It turns out that vertical R&D cooperation is usually the only stable equilibrium in the sense that no firm has an incentive to chose any other R&D scenario. Empirical implications concerning the relationship between R&D intensities and R&D spillovers are derived and empirical evi-dence is given using data of German manufacturing firms.

Finite Sample Properties of One-step, Two-step and Bootstrap Empirical Likelihood Approaches to Efficient GMM Estimation

This paper compares conventional GMM estimators to empirical likelihood based GMM estimators which employ a semiparametric efficient estimate of the unknown distribution function of the data. One-step, two-step and bootstrap empirical likelihood and conventional GMM estimators are considered which are efficient for a given set of moment conditions. The estimators are subject to a Monte Carlo investigation using a specification which exploits sequential conditional moment restrictions for binary panel data with multipli-cative latent effects. Among other findings the experiments show that the one-step and two-step estimators yield coverage rates of confidence intervals below their nominal coverage probabilities. The bootstrap methods improve upon this result.

Accounting for Nonresponse Heterogeneity in Panel Data

The paper proposes a technique for the estimation of possibly nonlinear panel data models in the presence of heterogeneous unit nonresponse. Attrition or unit nonresponse in panel data usually renders parameter estimators inconsistent unless the unavailable information is missing completely at random. For moment based estimators this problem can be expressed in terms of the impossibility to construct the sample equivalents of the population moments of interest. However, if the attrition process is conditionally mean independent of the variables of interest then the sample equivalents of the population moments can be recovered by weighting the moment functions with the conditional response probability (or propensity score). The latter is usually unknown and has to be estimated. In the presence of nonresponse heterogeneity the propensity score can be estimated by conventional parametric estimation methods like the multinomial logit or probit model. The technique proposed in this paper leads to a moment estimator which simultaneously exploits the weighted moment functions of interest and the score function of the multinomial choice model. The use of simulated moments is discussed for applications with many nonresponse reasons. An applications of the estimator to firm level data is presented where the variables of interest are R&D investments related to product and process innovations.

How Deep is the Annuity Market Participation Puzzle?

Using UK microeconomic data, we analyze the empirical determinants of voluntary annuity market demand. We find that annuity market participation increases with financial wealth, life expectancy and education and decreases with other pension income and a possible bequest motive for surviving spouses. We then show that these empirically-motivated determinants of annuity market participation have the same, quantitatively important, effects in a life-cycle model of annuity and life insurance demand, saving and portfolio choice. Moreover, reasonable preference parameters predict annuity demand levels comparable to the data. For stockholders, a relatively strong bequest motive is sufficient to simultaneously generate balanced portfolios and low annuity demand.Annuities, portfolio choice, life insurance, bequest motive

Young and Out in Germany: On the Youths' Chances of Labor Market Entrance in Germany

This paper deals with the labor market entrance of young people in the Federal Republic" of Germany. The main focus is on failures during this stage. First, an overview of the youth" labor market in Germany is given. Then, the transition from vocational training to work is" analyzed: The duration of the first spell of non-employment after completion of formal" vocational training is analyzed by means of a proportional hazard function approach. Besides the" strong influence of the human capital variables there is a striking effect of the family background" of the youths. The following section addresses the extent to which early failures in the work" history have long-lasting effects on future incomes. There is some evidence for a permanent" income reduction.

Norwegian School of Economics and Business Administration, Shifting Capital Markets and Performance conference at Yale University, Texas Finance Festival

Abstract Since World War II, direct stock ownership by households has largely been replaced by indirect stock ownership by financial institutions which manage pensions. We argue that tax policy is the driving force. Using long time-series from eight countries, we show that the fraction of household ownership decreases with measures of the tax benefits of holding stocks inside a pension plan. This finding is important for policy considerations on effective taxation and for financial economics research on the long-term effects of taxation on corporate finance and asset prices

Compensating wage differentials for defined benefit and defined contribution occupational pension scheme benefits

The theory of equalizing differences suggests that employer provided pension benefits should be compensated by reduced wage benefits for an employee’s given produc-tivity potential. This paper presents an empirical analysis of compensating wage differentials for occupational pension scheme benefits in the UK using the newly available English Longi-tudinal Study of Ageing. The data allows us to differentiate between Defined Benefit (DB) and Defined Contribution (DC) schemes and to consider different measures of pension bene-fits based on current contributions and changes in accrued pension benefit rights. In our pre-ferred specifications we find evidence for perfect compensating wage differentials for both occupational DB and DC pension scheme benefits