THE COMPLEX DYNAMICS OF THE SIMPLE RICARDIAN SYSTEM: A NOTE

In a recent note, Bhaduri and Harris (1987) showed that a discrete-time dynamic version of the ‘simple’Ricardian system (i.e. Blaug's (1978) popular version of Kaldor's (1955-6) representation of Ricardian distribution theory, which includes linear agricultural productivity) can be endowed with an unstable stationary state, and that the system can also exhibit “chaotic” orbits (cfr. Collet and Eckmann, 1980), even if these phenomena cannot appear when the adjustment process is continuous. This stationary state does not necessarily have to be unstable. A slightly generalized version of the ‘simple’Ricardian system (we dispense with the linearity assumption) is used in this paper to analyse a number of meaningful special cases in which the stationary state is stable.     

Occupational and Job Mobility in the US*

We propose a new methodology to measure worker mobility across occupations and jobs in the US, building on the limited longitudinal dimension of monthly CPS data. For the period 1979–2006, we find that about 3.5% of male workers employed in two consecutive months report different three‐digit occupations. This rate is procyclical, mildly rising in the 1980s and falling after 1995. We also revise upward current estimates of aggregate job‐to‐job mobility since 1994, from 2.7% to 3.2% of employment per month. Despite extreme similarity of average levels and time‐series behavior, occupational and job mobility are only weakly correlated.     

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.     

Tax havens compliance with international standards: A temporal perspective

This paper contributes to the debate centering on the fight against aggressive tax avoidance practices through the release of international standards. We develop a model in which identical tax havens decide upon their compliance date while competing for onshore capital. The timing of these decisions depends on the effects of two opposing forces. One force is linked to the tax sensitivity of international capital and the other to the reaction of nearby potential capital. When the former force dominates, asynchronous compliance arises, which occurs even with identical tax havens and perfect information. However, when the latter force dominates, tax havens comply simultaneously. In any case, the loss of tax base within the onshore region is minimized when compliance is simultaneous and occurs at the earliest possible date. Surprisingly, compliance of just one tax haven is not necessarily better than no compliance at all.     

Knightian uncertainty and moral hazard

This paper presents a principal-agent model in which the agent has imprecise beliefs. We model this situation formally by assuming the agent?s preferences are incomplete as in Bewley (1986) [2]. In this setting, incentives must be robust to Knightian uncertainty. We study the implications of robustness for the form of the resulting optimal contracts. We give conditions under which there is a unique optimal contract, and show that it must have a simple flat payment plus bonus structure. That is, output levels are divided into two sets, and the optimal contract pays the same wage for all output levels in each set. We derive this result for the case in which the agent?s utility function is linear and then show it also holds if this utility function has some limited curvature.     

Asymmetric information and deal selection: evidence from the Italian venture capital market

International Entrepreneurship and Management Journal - The aim of this study is to show how information asymmetry affects the venture capital (VC) deal selection process in the Italian capital...     

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.     

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.