A Consistent Approach to Cost Efficiency Measurement*

Consistent specifications of the allocative inefficiency function in ‘cost plus input share equations’ systems may be difficult, if not impossible, to find because most plausible ones violate certain reasonable a priori conditions. Moreover, the models to which they lead give rise to highly non‐linear likelihood functions that are very hard to estimate. In an effort to confront these difficulties, this paper adapts an idea first suggested by Greene (1993) that allocative inefficiency ought to be related to input prices and allocative distortions in the input share equations. The system of ‘cost plus input demand equations’ that emerges is estimated by standard seemingly unrelated regression (SUR) techniques using data from private and state firms that operated in Greek manufacturing during the 1979–88 period. Among other findings, the estimates show that overall inefficiency for private and state firms was 63.5% and 102.2%, respectively in comparison with the least inefficient firms in their class. In relative terms these figures imply that state firms were almost 61% less efficient than private firms were. Technical and allocative reasons amounting to 64% and 36%, respectively, accounted for this excess inefficiency of state firms, in addition to differences in the utilization of labour, capital and debt. Lastly, it is found that the magnitudes of technical and allocative inefficiencies depend critically upon a self‐consistent specification of the allocative inefficiency function.     

Missing in Asynchronicity: A Kalman‐em Approach for Multivariate Realized Covariance Estimation

Motivated by the need for a positive‐semidefinite estimator of multivariate realized covariance matrices, we model noisy and asynchronous ultra‐high‐frequency asset prices in a state‐space framework with missing data. We then estimate the covariance matrix of the latent states through a Kalman smoother and expectation maximization (KEM) algorithm. Iterating between the two EM steps, we obtain a covariance matrix estimate which is robust to both asynchronicity and microstructure noise, and positive‐semidefinite by construction. We show the performance of the KEM estimator using extensive Monte Carlo simulations that mimic the liquidity and market microstructure characteristics of the S&P 500 universe as well as in a high‐dimensional application on US stocks. KEM provides very accurate covariance matrix estimates and significantly outperforms alternative approaches recently introduced in the literature. Copyright © 2014 John Wiley & Sons, Ltd.     

Non‐Fundamentalness in Structural Econometric Models: A Review

Current economic theory typically assumes that all the macroeconomic variables belonging to a given economy are driven by a small number of structural shocks. As recently argued, apart from negligible cases, the structural shocks can be recovered if the information set contains current and past values of a large, potentially infinite, set of macroeconomic variables. However, the usual practice of estimating small size causal Vector AutoRegressions can be extremely misleading as in many cases such models could fully recover the structural shocks only if future values of the few variables considered were observable. In other words, the structural shocks may be non‐fundamental with respect to the small dimensional vector used in current macroeconomic practice. By reviewing a recent strand of econometric literature, we show that, as a solution, econometricians should enlarge the space of observations, and thus consider models able to handle very large panels of related time series. Among several alternatives, we review dynamic factor models together with their economic interpretation, and we show how non‐fundamentalness is non‐generic in this framework. Finally, using a factor model, we provide new empirical evidence on the effect of technology shocks on labour productivity and hours worked.     

Exact Skewness–Kurtosis Tests for Multivariate Normality and Goodness‐of‐Fit in Multivariate Regressions with Application to Asset Pricing Models*

We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross‐equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared with a simulation‐based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal and stable error distributions. In the Gaussian case, finite‐sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi‐stage Monte Carlo test methods. For non‐Gaussian distribution families involving nuisance parameters, confidence sets are derived for the nuisance parameters and the error distribution. The tests are applied to an asset pricing model with observable risk‐free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over 5‐year subperiods from 1926 to 1995.     

The Inforum Approach to Interindustry Modeling

Inforum models are described as internationally-linkable, dynamic, interindustry models which imitate as closely as possible the way the economy behaves. They models are contrasted with classical input–output models, pure econometric models, and CGE models. Their common elements are set out and the common software described. The rest of this issue of this Journal is introduced.     

A Welfare‐Based Approach to Aggregating Growth Rates across Countries*

Aggregating per capita gross domestic product growth across countries has always been a technical problem because of the complexities in the relative movements of exchange rates, economic output and populations. As such, the conventional approach to aggregating growth across countries suffers from sensitivity to exchange rates, as well as from the possibility of aggregate growth rates not being convex combinations of individual growth rates. This article introduces a new methodology in aggregating per capita growth rates that does not suffer from the drawbacks of the conventional approach. Using a welfare‐based approach, it is shown that the proposed methodology is robust w.r.t. exchange rates and generates weights that always add up to unity, thus avoiding the anomalies that are inherent in the conventional approach. The methodology proposed in the article is applied to calculate aggregate growth rates of 33 developing member countries as well as five regional groupings, and the results are compared with those arising from the conventional approach. A number of insights arise that were previously hidden or inaccessible.     

Semiparametric Regression Analysis of Panel Count Data: A Practical Review

Panel count data arise in many applications when the event history of a recurrent event process is only examined at a sequence of discrete time points. In spite of the recent methodological developments, the availability of their software implementations has been rather limited. Focusing on a practical setting where the effects of some time‐independent covariates on the recurrent events are of primary interest, we review semiparametric regression modelling approaches for panel count data that have been implemented in R package spef . The methods are grouped into two categories depending on whether the examination times are associated with the recurrent event process after conditioning on covariates. The reviewed methods are illustrated with a subset of the data from a skin cancer clinical trial.     

Out‐of‐Sample Return Predictability: A Quantile Combination Approach

This paper develops a novel forecasting method that minimizes the effects of weak predictors and estimation errors on the accuracy of equity premium forecasts. The proposed method is based on an averaging scheme applied to quantiles conditional on predictors selected by LASSO. The resulting forecasts outperform the historical average, and other existing models, by statistically and economically meaningful margins. Copyright © 2016 John Wiley & Sons, Ltd.     

The Distributional Effects of Tax‐benefit Policies under New Labour: A Decomposition Approach*

I revisit the distributional effects of tax‐benefit policy reforms under New Labour using counterfactual microsimulations embedded in a Shapley decomposition of time change in inequality and poverty indices. This makes it possible to quantify the relative effect of policy changes compared to all other changes, and to check the sensitivity of this policy effect to the use of (i) income vs. price indexation, and (ii) base vs. end period data. Inequality and poverty depth would have increased, and the sharp fall in child poverty would not have occurred, had the reforms of income support and tax credits not been implemented.     

A Two‐Step Procedure to Measure Representativeness of Internet Data Sources

So far, statistics has mainly relied on information collected from censuses and sample surveys, which are used to produce statistics about selected characteristics of the population. However, because of cost cuts and increasing non‐response in sample surveys, statisticians have started to search for new sources of information, such as registers, Internet data sources (IDSs, i.e. web portals) or big data. Administrative sources are already used for purposes of official statistics, while the suitability of the latter two sources is currently being discussed in the literature. Unfortunately, only a few papers devoted to statistical theory point out methodological problems related to the use of IDSs, particularly in the context of survey methodology. The unknown generation mechanism and the complexity of such data are often neglected in view of their size. Hence, before IDSs can be used for statistical purposes, especially for official statistics, they need to be assessed in terms of such fundamental issues as representativeness, non‐sampling errors or bias. The paper attempts to fill the first gap by proposing a two‐step procedure to measure representativeness of IDSs. The procedure will be exemplified using data about the secondary real estate market in Poland.     

成本管理新模式——Kaizen成本制度

Kaizen成本制度是日本的Kaizen企业文化在成本管理上的具体体现。本文对Kaizen成本制度的涵义、主要特点、基本步骤、目标确定和业绩评价进行了系统的介绍,对半生命周期模型在成本改进中的运用进行了探讨,分析比较了Kaizen成本制度与标准成本管理、成本企画之间的关系,并就这种成本制度实施过程中可能遇到的适用范围、组织文化等问题进行了讨论。     

New approaches to funding not‐for‐profit organisations

This paper seeks to record and to explain the enormous growth in interest over the last few years in the provision of loans and other investment to not‐for‐profit organisations. It argues that this funding development fills a gap in the market. It describes the following new approaches: social investment, the provision of ‘patient capital’, and an ‘investment’ or ‘venture philanthropy’ approach to grant making. The factors driving the growth in use of these approaches are examined and their relevance to fundraising charities considered. Finally, the paper discusses how key stakeholders including the government and charitable trusts are adapting to this new environment. Copyright © 2004 Henry Stewart Publications     

A Hidden Markov Model Approach to Information‐Based Trading: Theory and Applications

This paper develops a novel approach to information‐based securities trading by characterizing the hidden state of the market, which varies following a Markov process. Extensive simulation demonstrates that the approach can successfully identify market states and generate dynamic measures of information‐based trading that outperform prevailing models. A sample of 120 NYSE stocks further verifies that it can better depict trading dynamics. With this sample, we characterize the features of information asymmetry and belief dispersion around earnings announcements. The sample is also applied to the study of the co‐movements of trading activities due to private information or disputable public information. Copyright © 2014 John Wiley & Sons, Ltd.     

Reassembling Lesseps Square,Rethinking Barcelona: A More‐than‐Human Approach

This article discusses the great paradox of the planning of public spaces in Barcelona. While for years the city's residents, politicians and experts have been steeped in democratizing, participatory discourses, the interminable controversies almost all the council's initiatives in the streets and squares of Barcelona have aroused are evidence of a clear short‐circuit. Somehow this participatory‐democratic consensus has run up against a collective discord which, in my view, indicates the incapacity of the current channels and mechanisms of citizen participation to truly give shape to a more democratic city, one which does not block dissent or stand in the way of the possible. I discuss this short‐circuit through a case study, the Lesseps Square controversy, including a methodological and epistemological debate which, in order to study how the square was reassembled in practice after the participatory remodeling process, puts forward an actor‐network‐theory‐inspired approach to the study of public space. I argue that Barcelona, a city whose public institutions are deeply committed to creating channels for residents to participate in public processes, is at the same time enacting a closure of its public spaces. My contention here is that the urban environment is already distributed (in Rancière's sense) before it is given over to participation, and that this prevents the emergence of a (more‐than‐human) demos that could redistribute public space by taking account of innumerable unrepresented parties.