Politics,Evidence and the New Aid Agenda

Based on study of (a) the HIPC debt relief initiative, (b) the linking of aid to policy conditionality and (c) transactions‐cost arguments in favour of programme aid, this article argues that major elements in the new aid agenda may not be well‐based empirically. This is partly because of inadequate knowledge, but particularly because the evidence often conflicts with political preferences. As a result, it is likely that large amounts of aid resources are being misdirected. Ways are suggested of narrowing the gap between evidence‐based and ‘political’ decision‐making. In the meantime, donors should avoid diverting more aid into debt relief, should roll back their reliance on policy conditionality, and should exercise pragmatic caution in the expansion of programme assistance.     

Censorship and the Australian Public

Recently the authors with the assistance of a research grant from the Sebel Company of Australia, carried out a study of attitudes held by sub-groups within Australian society. One of the topical issues investigated was the desirability of censorship of the mass media. The results of this section of the inquiry, based on a questionnaire administered to 1,455 adults in Sydney and Melbourne, are presented in this article.     

Still Searching for Excellence? International Accounting and the World's Most Outstanding Companies

This paper measures the effect of accounting policy choices in the context of Davis, Flanders and Star's (DFS) (1991) league table of the world's most outstanding companies. Our study is an investigation of the robustness of the research underlying Kay (1993). The sensitivity of the rankings to the three major conventions that are used in calculating added value are examined: depreciation policy, the estimation of the cost of capital inputs and consistency of international generally accepted accounting principles. The key finding is that the degree of disruption caused by international accounting differences is likely to be the most material. It is equivalent, in this study, to a 60% increase in the cost of capital or an 80% change in the depreciation lives of fixed assets. After adjusting towards consistent international accounting, we now find that four Japanese companies appear in the top ten. Before adjustment there were none.     

Nonstationary regression models with a lagged dependent variable

This paper studies regression models with a lagged dependent variable when both the dependent and independent variables are nonstationary, and the regression model is misspecified in some dimension. In particular, we discuss the limiting properties of leastsquares estimates of the parameters in such regression models, and the limiting distributions of their test statistics. We show that the estimate of the lagged dependent variable tends to unity asymptotically independent of its true value, while the estimates of the independent variables tend to zero. The limiting distributions of their test statistics are shown to diverge with sample size.     

Accounting for dynamic selection bias in educational transitions: The Cameron-Heckman latent class estimator and its generalizations

The sequential logit model of educational transitions has long been the dominant modeling framework for the study of inequality of educational opportunity ever since the seminal works of [Mare, 1980] and [Mare, 1981]. But conventional applications of the model are known to be biased by the ubiquitous presence of unobserved heterogeneity. Cameron and Heckman (1998) propose a logit model that allows for two or three latent classes if the selection bias is solely generated by a person-specific component of stable unobserved heterogeneity. To evaluate the latent class logit regression estimator, this study makes use of simulated data to eliminate the influences of other problems of transition modeling. The simulation is based on five independent pairs of large samples generated from standard distributional assumptions of transition modeling. The new estimator appears to be an effective way to adjust for dynamic selection bias when family background effects are transition-invariant and sample size is in the order of ten thousand or above. By contrast, the conventional sequential logit model produces results that are very different from the data generating models. This study also considers two alternative ways to improve statistical efficiency: (1) incorporate a crude indicator of stable unobserved heterogeneity; (2) pool the effect estimates across transitions, background variables, and alternative estimators to smooth out noise under the null hypothesis of transition invariance. In addition, this study examines the impact of indicator reliability and sample size on the performance of the latent class regression models and suggests practical guidelines.     

Fractional integration and impulse responses: a bivariate application to real output in the USA and four Scandinavian countries

This article analyzes impulse response functions in the context of vector fractionally integrated time series. We derive analytically the restrictions required to identify the structural-form system. As an illustration of the recommended procedure, we carry out an empirical application based on a bivariate system including real output in the USA and, in turn, in one of the four Scandinavian countries (Denmark, Finland, Norway, and Sweden). The empirical results appear to be sensitive, to some extent, to the specification of the stochastic process driving the disturbances, but generally a positive shock to US output has a positive effect on the Scandinavian countries, which tend to disappear in the long run.