Innovation policy configuration – a comparative study of Russia and China

This paper presents a study of innovation policy configurations in two BRICS countries, Russia and China; the fastest growing and most innovative countries in recent years. Employing a three-dimensional framework which maps policy objectives, policy instruments and policy implementation, the research analyzes a database of 485 policy items issued between 1990 and 2013. Twenty-five innovation policy variables have been scrutinized vis-à-vis the three policy dimensions. The paper compares the experiences of Russia with China, across these three policy dimension areas, revealing the similarities and differences in innovation policy configurations. The research identifies how innovation management in both Russia and China has been shaped by contrasting histories, state institutions and economies. The paper offers an alternative perspective to the debate on the effective management of innovation, a debate currently dominated by the experiences of the USA, Japan and Western Europe.     

以弱胜强思想在当代社会中的反思

我国优良的传统伦理文化和传统美德有很多,诸如尊老爱幼、助人为乐等。这些优良的传统文化是值得骄傲和自豪的,因为它们是使我们中华民族悠久历史连接在一起的纽带。可以说没有这些传统的凝聚,就没有中华民族的今天。但是,这些传统文化、传统思想,应该有选择的继承和发展。选择那些利于当今社会发展的传统文化,而抛弃那些阻碍社会进步的传统思想,弃其糟粕,取其精华。     

One-shot exchange networks and the shadow of the future

From the Prisoner's Dilemma and other games, it is well known that strategy selection in one-shot games can be very different from that in iterated games. Because exchange structures were studied only as iterated games, whether one-shot structures differ was not known. Nor have exchange theories previously considered whether events in structures would be different if studied as one-shot games. This paper offers new theory to predict one-shot exchange structures and one-shot experiments to test that theory. As predicted, the experiments found that processes and outcomes of one-shot exchange structures are quite different from those of iterated exchange structures. For example, certain relations that are strategically used as threats in iterated exchange structures occur very rarely in one-shot structures. It follows that power differences in one-shot structures regress from those observed for repeated structures.     

Testing,One, Two,Three, Testing: An Attorney Perspective

SUMMARY

This article addresses the attorney perspective on the use of psychometric testing in the context of family law child custody evaluations. Although attorneys, judicial officers and child custody evaluators “use” psychometric testing in family law matters, the ways in which each discipline uses the information gleaned from the results of these tests as administered to child custody litigants can differ substantially. This article distinguishes the attorney perspective from the mental health perspective in the use of the results of such tests.     

Statistical inference in dynamic panel data models

Anderson and his collaborators have made seminal contributions to inference with instrumental variables and to dynamic panel data models. We review these contributions and the extensive economic and statistical literature that these contributions spawned. We describe our recent work in these two areas, presenting new approaches to (a) making valid inferences in the presence of weak instruments and (b) instrument and model selection for dynamic panel data models. Both approaches use empirical likelihood and resampling. For inference in the presence of weak instruments, our approach uses model averaging to achieve asymptotic efficiency with strong instruments but maintain valid inferences with weak instruments. For instrument and model selection, our approach aims at choosing valid instruments that are strong enough to be useful.     

Count Data Models with Correlated Unobserved Heterogeneity

Abstract. As previously argued, the correlation between included and omitted regressors generally causes inconsistency of standard estimators for count data models. Non‐linear instrumental variables estimation of an exponential model under conditional moment restrictions is one of the proposed remedies. This approach is extended here by fully exploiting the model assumptions and thereby improving efficiency of the resulting estimator. Empirical likelihood in particular has favourable properties in this setting compared with the two‐step generalized method of moments, as demonstrated in a Monte Carlo experiment. The proposed method is applied to the estimation of a cigarette demand function.     

Measuring serial dependence in categorical time series

The analysis of time-indexed categorical data is important in many fields, e.g., in telecommunication network monitoring, manufacturing process control, ecology, etc. Primary interest is in detecting and measuring serial associations and dependencies in such data. For cardinal time series analysis, autocorrelation is a convenient and informative measure of serial association. Yet, for categorical time series analysis an analogous convenient measure and corresponding concepts of weak stationarity have not been provided. For two categorical variables, several ways of measuring association have been suggested. This paper reviews such measures and investigates their properties in a serial context. We discuss concepts of weak stationarity of a categorical time series, in particular of stationarity in association measures. Serial association and weak stationarity are studied in the class of discrete ARMA processes introduced by Jacobs and Lewis (J. Time Ser. Anal. 4(1):19–36, 1983). An intrinsic feature of a time series is that, typically, adjacent observations are dependent. The nature of this dependence among observations of a time series is of considerable practical interest. Time series analysis is concerned with techniques for the analysis of this dependence. (Box et al. 1994p. 1)     

GMM with Many Moment Conditions

This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimators when the number of moment conditions is allowed to increase with the sample size and the moment conditions may be weak. Examples in which these asymptotics are relevant include instrumental variable (IV) estimation with many (possibly weak or uninformed) instruments and some panel data models that cover moderate time spans and have correspondingly large numbers of instruments. Under certain regularity conditions, the GMM estimators are shown to converge in probability but not necessarily to the true parameter, and conditions for consistent GMM estimation are given. A general framework for the GMM limit distribution theory is developed based on epiconvergence methods. Some illustrations are provided, including consistent GMM estimation of a panel model with time varying individual effects, consistent limited information maximum likelihood estimation as a continuously updated GMM estimator, and consistent IV structural estimation using large numbers of weak or irrelevant instruments. Some simulations are reported.     

On Error Rates in Normal Approximations and Simulation Schemes for Lévy Processes

Let X=(X(t) : t≥0) be a Lévy process. In simulation, one often wants to know at what size it is possible to truncate the small jumps while retaining enough accuracy. A useful tool here is the Edgeworth expansion. We provide a third order expansion together with a uniform error bound, assuming third Lévy moment is 0. We next discuss approximating X in the finite variation case. Truncating the small jumps, we show that, adding their expected value, and further, including their variability by approximating by a Brownian motion, gives successively better results in general. Finally, some numerical illustrations involving a normal inverse Gaussian Lévy process are given.     

A Note on the Relations Between Some Concepts of Positive Dependence

In this article, we provide some explicit examples showing that weak association in sequence is strictly weaker than weak association and strictly stronger than positive supermodular dependence. Furthermore, we show that strongly positive orthant dependence is strictly weaker than weakly association and strictly stronger than positive orthant dependence. Finally, we also show that positive supermodular dependence is not stronger than strongly positive orthant dependence.