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.     

EQUALITY OF OPPORTUNITY: POLICY AND MEASUREMENT PARADIGMS

Abstract Equality of opportunity is a widely accepted principle of distributive justice and it is the leading idea of most political platforms in several countries. According to this principle, a society might institute policies that secure an equal distribution of the means to reach a valuable outcome among its members. Once the set of opportunities have been equalized, which particular opportunity, the individual chooses from those open to her, is outside the scope of justice. Ex ante inequalities, and only those inequalities, should be eliminated or compensated for by public intervention. The recent literature on the opportunity egalitarianism often merges these questions introducing two different economic issues. On one side the design of a public policy intended to implement the equality of opportunity view and on the other side the problem of measuring the degree of opportunity inequality in a society. We describe the basic setting and assumptions of some different approaches derived by Roemer’s algorithm for public policy and then we discuss some theoretical and empirical studies to separate and test alternative paradigms on the measurement of inequality of opportunity. Accordingly, an extended critique on the causality issue on policies and measurements is taken into account.     

A GIS-based tool for the management of industrial accidents triggered by volcanic ash fallouts

In this last decade, worldwide attention has been focused on the hazards derived from the interaction between extreme natural phenomena and critical infrastructures and/or chemical and process industry (natural–technological hazards or Na-Tech). Due to the recent occurrence of significant events, great attention has also been given to Na-Tech hazards triggered by volcanic eruptions; in particular, the eruption of the Icelandic volcano alarmed the European community due to the ash fallout over the continent, which caused significant problems for the population, road, rail and air traffic and production activities. This study aims at defining a procedure for the representation of the vulnerability of industrial facilities to potential volcanic ash fallouts. Its implementation on a Geographical Information System has also been executed and a semi-automatic procedure for the vulnerability mapping has been constructed.     

HUMAN CAPITAL MEASUREMENT: A SURVEY

Abstract After a short history of the concept of human capital (henceforth HC) in economic thought ( Section 1 ), this study presents the two main methods for estimating the value of the stock of HC – the retrospective and prospective one – with a review of the models proposed ( Section 2 ). These methods are linked both to the theory of HC investment as a rational choice ( Section 3 ), the literature analysing the contribution of HC investment to economic growth and the HC estimating method through educational attainment ( Section 4 ). The more recent literature on HC as a latent variable is also assessed ( Section 5 ) and a new method of estimation where HC is seen both as an unknown function of formative indicators and as a ‘latent effect’ underlying earned income is proposed ( Section 6 ). Section 7 concludes.