Eliciting Consumer Preferences for Certified Animal‐Friendly Foods: Can Elements of the Theory of Planned Behavior Improve Choice Experiment Analysis?

Models used in neoclassical economics assume human behavior to be purely rational. On the other hand, models adopted in social and behavioral psychology are founded on the “black box” of human cognition. In view of these observations, this paper aims at bridging this gap by introducing psychological constructs in the well‐established microeconomic framework of choice behavior based on random utility theory. In particular, it combines constructs developed employing Ajzen's theory of planned behavior with Lancaster's theory of consumer demand for product characteristics to explain stated preferences over certified animal‐friendly foods (AFF). To reach this objective, a Web survey was administered in the largest five EU‐25 countries: France, Germany, Italy, Spain, and the United Kingdom. Findings identify some salient cross‐cultural differences between northern and southern Europe and suggest that psychological constructs developed using the Ajzen model are useful in explaining heterogeneity of preferences. Implications for policymakers and marketers involved with certified AFF are discussed.     

Indebted state versus intermediary state: who owes what to whom?

Ratios of public debt to GDP are much discussed these days and questions concerning debt relative to taxation have long been explored by fiscal scholars. With respect to monarchical regimes, it seems reasonable to treat public debt as similar to personal debt, recognizing that a monarch is not an ordinary person. When public debt arises through parliamentary assemblies, however, the similarity of form between public and personal debt vanishes because a parliamentary assembly does not trade on its own account; to the contrary, it is a type of intermediary that brings together people who buy bonds and people who later pay the bondholders. In a republic there is no sovereign who is indebted to ruled subjects. The institutional framework of republican governance transforms public borrowing into a process of intermediation among citizens, which leads in turn to the alternative orientation toward public debt that this paper explores.     

Reforming the reform: changing roles for accounting and management in the Italian health care sector

This paper examines the ways in which accounting has intervened in the process of reforming the original ‘reform’ of the Italian health care system. By stepping into an ongoing process accounting has been asked not only to foster efficiency, effectiveness and value for money, but to correct as well the ‘degeneration’ of the original reform, which subjected health care delivery to ‘democratic’ scrutiny and political control. The call for a greater accountability in the use of public resources has been thus interpreted as both a mechanism of surveillance and control and a way to resist the ‘over-politicization’ of health sector management together with the abuses, scandals and fraudulent behaviour it induced. In seeking to interpret the specificity of the Italian experience, the paper suggests that the range of ‘the contexts in which accounting operates’ should be broadened in order to gain a deeper understanding of its roles in those institutions, such as health care systems, which play a crucial role in modern societies. In order to move in this direction systematic and empirically grounded cross-national comparisons are called for, since, although accounting and management are involved in virtually all attempts to redesign health care services, consequences are likely to be different when conditions of possibility differ at the outset.     

Post Keynesian Approaches to Endogenous Money: A time framework explanation

Over the last two decades, work on the Post Keynesian theory of endogenous money has been flourishing, and has prompted a rethinking of the complex nature of money in modern economies. At the heart of the debate between what have now been labelled the accommodationist (or horizontalist) approach and the structuralist approach to endogenous money are the issues of the slope of the supply curves of reserves and of credit money, respectively. Using the distinction between a single period analysis and a continuation analysis, similarities and differences between those approaches are explained, and the suggestion is then made for retaining and re-interpreting them into a more general theory.     

A Comparison of Sequential and Information‐based Methods for Determining the Co‐integration Rank in Heteroskedastic VAR Models

In this article, we investigate the behaviour of a number of methods for estimating the co‐integration rank in VAR systems characterized by heteroskedastic innovation processes. In particular, we compare the efficacy of the most widely used information criteria, such as Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) , with the commonly used sequential approach of Johansen [Likelihood‐based Inference in Cointegrated Vector Autoregressive Models (1996)] based around the use of either asymptotic or wild bootstrap‐based likelihood ratio type tests. Complementing recent work done for the latter in Cavaliere, Rahbek and Taylor [Econometric Reviews (2014) forthcoming], we establish the asymptotic properties of the procedures based on information criteria in the presence of heteroskedasticity (conditional or unconditional) of a quite general and unknown form. The relative finite‐sample properties of the different methods are investigated by means of a Monte Carlo simulation study. For the simulation DGPs considered in the analysis, we find that the BIC‐based procedure and the bootstrap sequential test procedure deliver the best overall performance in terms of their frequency of selecting the correct co‐integration rank across different values of the co‐integration rank, sample size, stationary dynamics and models of heteroskedasticity. Of these, the wild bootstrap procedure is perhaps the more reliable overall as it avoids a significant tendency seen in the BIC‐based method to over‐estimate the co‐integration rank in relatively small sample sizes.     

Random Recursive Partitioning: a matching method for the estimation of the average treatment effect

In this paper we introduce the Random Recursive Partitioning (RRP) matching method. RRP generates a proximity matrix which might be useful in econometric applications like average treatment effect estimation. RRP is a Monte Carlo method that randomly generates non‐empty recursive partitions of the data and evaluates the proximity between two observations as the empirical frequency they fall in a same cell of these random partitions over all Monte Carlo replications. From the proximity matrix it is possible to derive both graphical and analytical tools to evaluate the extent of the common support between data sets. The RRP method is “honest” in that it does not match observations “at any cost”: if data sets are separated, the method clearly states it. The match obtained with RRP is invariant under monotonic transformation of the data. Average treatment effect estimators derived from the proximity matrix seem to be competitive compared to more commonly used estimators. RRP method does not require a particular structure of the data and for this reason it can be applied when distances like Mahalanobis or Euclidean are not suitable, in the presence of missing data or when the estimated propensity score is too sensitive to model specifications. Copyright © 2008 John Wiley & Sons, Ltd.     

The intraday multivariate structure of the Eurofutures markets

We investigate the multivariate intraday structure in interest rates, focusing on implied forward rates from Eurofutures contracts. Since futures markets are the most liquid for interest rate instruments and they yield high-quality intraday data, it is somehow surprising that their intraday behavior has not been thoroughly studied in the literature.We find interesting similarities with the foreign exchange market: scaling law, intraday patterns, all of which point to the heterogeneity of market participants. Other properties like asymmetric causal information flow between fine and coarse volatilities for the same time series are present in our data. There are also lead–lag correlations across the term structure of implied forward rates, but they tend to disappear as markets mature.A principal component analysis of the short end of the yield curve allows us to determine the most important components and to reduce the number of time series needed to describe the term structure. We find the decomposition rather stable over time. The first component, which describes the curve level, shows an asymmetry in the information flow between volatilities of different time resolution, i.e., the coarse-grained volatility predicts the fine-grained volatility better than the other way around, as observed in the foreign exchange market. The remaining components do not show such an effect, having instead significant negative autocorrelations for the time series themselves. A heterogeneous autoregressive conditional heteroskedasticity (HARCH) model is estimated for the first component and the impact of different market agents is discussed.     

Model‐Assisted Estimation of a Spatial Population Mean

This paper deals with the estimation of the mean of a spatial population. Under a design‐based approach to inference, an estimator assisted by a penalized spline regression model is proposed and studied. Proof that the estimator is design‐consistent and has a normal limiting distribution is provided. A simulation study is carried out to investigate the performance of the new estimator and its variance estimator, in terms of relative bias, efficiency, and confidence interval coverage rate. The results show that gains in efficiency over standard estimators in classical sampling theory may be impressive.