Parameter estimation by contrast minimization for noisy observations of a diffusion process

We consider the estimation of unknown parameters in the drift and diffusion coefficients of a one-dimensional ergodic diffusion X when the observation Y is a discrete sampling of X with an additive noise, at times i δ, i=1,?…?, N. Assuming that the sampling interval tends to 0 while the total length-time interval tends to infinity, we prove limit theorems for functionals associated with the observations, based on local means of the sample. We apply these results to obtain a contrast function. The associated minimum contrast estimators are shown to be consistent. Some examples are discussed with numerical simulations.     

Between Activation and Supporting Women – Alternative Operation of Welfare‐to‐work Programmes

With the emergence of activation policies, researchers are intrigued by the extent to which welfare‐to‐work (WTW) programmes reflect the ideological orientation of policymakers, while leaving the ideological orientation of their operators unexamined. This aspect may be of particular importance when women's non‐governmental organizations operate non‐coercive WTW programmes. Directing attention to the contribution of the operator, we ask how women who operate these programmes distinguish between the feminist goal of increasing women's independent access to material resources, and the activation rhetoric of ‘work first’. Moreover, as not enough is known about how participants benefit from the incongruence between the feminist discourse and the activation one, scholarship contemplating women's resistance to WTW programmes remains focused on specific welfare histories, and this form of feminist work remains neglected. The importance of the specific operators and the policy implications of the benefits of feminist operation of WTW programmes receive attention in the study reported on herein. We used a non‐coercive activation programme operated by a feminist organization in Israel (among other operators) as an opportunity to deepen our understanding of how programme trainers voice their position between feminism and activation discourse, and how their form of speech enables participants to insist on decent employment as a policy issue. Implications for policy are discussed.     

Markov Perfect Industry Dynamics With Many Firms

We propose an approximation method for analyzing Ericson and Pakes (1995)‐style dynamic models of imperfect competition. We define a new equilibrium concept that we call oblivious equilibrium, in which each firm is assumed to make decisions based only on its own state and knowledge of the long‐run average industry state, but where firms ignore current information about competitors' states. The great advantage of oblivious equilibria is that they are much easier to compute than are Markov perfect equilibria. Moreover, we show that, as the market becomes large, if the equilibrium distribution of firm states obeys a certain “light‐tail” condition, then oblivious equilibria closely approximate Markov perfect equilibria. This theorem justifies using oblivious equilibria to analyze Markov perfect industry dynamics in Ericson and Pakes (1995)‐style models with many firms.     

Personelle Unternehmensverflechtung und Vorstandsgehälter

Personal linkages between the biggest German corporations is subject to a special survey by the Monopolies Commission every two years. We use linkage data ranging from 2000–2006 to examine the impact of personal linkage on the compensation of management board members. The empirical analysis reveals a positive relation between compensation of management board members and the amount of corporation-linkages by additional supervisory board mandates of members of the management board. At the same time, the performance of the sending firms has no influence on the likelihood to receive further supervisory board seats.     

Combinatorially composing Chebyshev polynomials

We present a combinatorial proof of two fundamental composition identities associated with Chebyshev polynomials. Namely, for all m,n?0$m,n?0$, _Tm(_Tn(x))=_Tmn(x)$T_m(T_n(x))=T_{\mathit{mn}}(x)$ and _Um−1(_Tn(x))_Un−1(x)=_Umn−1(x).$U_{m-1}(T_n(x))U_{n-1}(x)=U_{\mathit{mn}-1}(x).$