Real option games with R&D and learning spillovers

We demonstrate to decision makers how to optimally make costly strategic pre-investment R&D decisions in the presence of spillover effects in an option pricing framework with analytic tractability. Decisions are modeled as impulse-type controls with random outcome. Two firms face two decisions that are solved interdependently in a two-stage game. The first-stage decision is: What is the optimal level of coordination (optimal policy/technology choice)? The second-stage decision is: What is the optimal effort for a given level of the spillover effects and the cost of information acquisition? The framework is extended to a two-period closed-loop stochastic game with (path-dependency inducing) switching costs that make strategy revisions harder. When conditions of learning-by-doing exist, we find that strategy shifts are easier to observe in market environments of high growth and high volatility.     

The effect of divorce costs on marriage formation and dissolution

Exploiting the theoretical parallels between the matching of workers to jobs in the labour market and the matching of individuals in the marriage market, we use a search theoretic model of marriage formation and dissolution to examine the effect of divorce costs on both decisions. By introducing learning at both stages of the marital decision process, we show that divorce costs not only affect the probability of divorce but also the probability of marriage. Interestingly, to what extent divorce costs affect the marital status distribution depends on the information regarding the quality of the potential marriage that individuals receive while encountering marital offers. Received: 30 July 1996/Accepted: 7 December 1998     

What’s in a Topic? Exploring the Interaction Between Test-taker Age and Item Content in High-Stakes Testing

The research reported in this article investigates differential item functioning (DIF) in a listening comprehension test. The study explores the relationship between test-taker age and the items’ language domains across multiple test forms. The data comprise test-taker responses (N = 2861) to a total of 133 unique items, 46 items of which were shared across two or more forms. Twenty-one items demonstrated DIF. However, there was no pattern by language domain. Eleven items showing DIF appeared in more than one test form but DIF for these items occurred only once.     

Early Career Mobility and Earnings Profiles of German Apprentices: Theory and Empirical Evidence

We investigate how apprenticeship training affects the early career mobility and earnings profiles of young apprentices in Germany. The heterogeneous quality and nature (whether general or firm specific) of training across firms is expected to be reflected in the post‐apprenticeship mobility and earning patterns of young workers. In this paper, we argue that a simple model of training and labour turnover can explain such patterns. Specifically, assuming that job changes are associated with a loss of accumulated firm‐specific skills, the model predicts that although movers initially experience a productivity loss, their earnings grow at a faster rate than those of stayers. As job changes become more costly the longer a worker stays with the training firm, later movers experience a larger reduction in their earnings compared with direct movers. Estimated selectivity‐corrected earnings equations for movers and stayers, based on data from the German Socioeconomic Panel (GSOEP), support the predictions of the model and highlight important differences in earnings profiles and mobility patterns by apprenticeship firm size.     

Distributions of patterns of two successes separated by a string of <Emphasis Type="Italic">k</Emphasis>-2 failures

Let Z ₁, Z ₂, . . . be a sequence of independent Bernoulli trials with constant success and failure probabilities p = Pr(Z _t  = 1) and q = Pr(Z _t  = 0) = 1 − p, respectively, t = 1, 2, . . . . For any given integer k ≥ 2 we consider the patterns E₁{\mathcal{E}_{1}}: two successes are separated by at most k−2 failures, E₂{\mathcal{E}_{2}}: two successes are separated by exactly k −2 failures, and E₃{\mathcal{E}_{3}} : two successes are separated by at least k − 2 failures. Denote by N_n,k⁽ⁱ⁾{ N_{n,k}^{(i)}} (respectively M_n,k⁽ⁱ⁾{M_{n,k}^{(i)}}) the number of occurrences of the pattern E_i{\mathcal{E}_{i}} , i = 1, 2, 3, in Z ₁, Z ₂, . . . , Z _n when the non-overlapping (respectively overlapping) counting scheme for runs and patterns is employed. Also, let T_r,k⁽ⁱ⁾{T_{r,k}^{(i)}} (resp. W_r,k⁽ⁱ⁾){W_{r,k}^{(i)})} be the waiting time for the r − th occurrence of the pattern E_i{\mathcal{E}_{i}}, i = 1, 2, 3, in Z ₁, Z ₂, . . . according to the non-overlapping (resp. overlapping) counting scheme. In this article we conduct a systematic study of N_n,k⁽ⁱ⁾{N_{n,k}^{(i)}}, M_n,k⁽ⁱ⁾{M_{n,k}^{(i)}}, T_r,k⁽ⁱ⁾{T_{r,k}^{(i)}} and W_r,k⁽ⁱ⁾{W_{r,k}^{(i)}} (i = 1, 2, 3) obtaining exact formulae, explicit or recursive, for their probability generating functions, probability mass functions and moments. An application is given.