ON THE ECONOMIC INTERPRETATION OF THE BRÓDY CONJECTURE

The aim of the paper is to study the economic aspects of the Bródy conjecture: an increase in the size of a (random) input matrix causes a decline in the ratio of its subdominant and dominant eigenvalues and implies faster convergence to equilibrium [Bródy, A. (1997) The Second Eigenvalue of the Leontief Matrix. Economic Systems Research, 9, 253–258]. Simulation results provide evidence that this ratio depends inversely on the level of data aggregation and can therefore not be a good indicator of the speed of convergence of an economy to its equilibrium path. We show that this is consistent with findings based on actual input–output tables of EU member states. These results imply that theorems about the speed of convergence of random matrices are not useful in describing the cyclical dynamics of real economies.     

Proposal of a model to measure competitiveness through factor analysis

This article presents a proposal for a simultaneous competitiveness measurement model for the three geographical levels: country, states, and municipalities. For this, a multivariate factor analysis method is used to help identify five factors, seven sub-factors, and thirty variables, which will be used for the measurement and to present the results of an empirical study on eleven entities: the country, the State of Sonora, and nine municipalities, which represent 80% of the population and 80% of their TGP. The results indicate that, in 2010, the municipality of Hermosillo was the most competitive.     

Capturing zero‐trade values in gravity equations of trade: an analysis of protectionism in agro‐food sectors

With significant improvements in its theoretical underpinnings, the gravity model has gained renewed interest in the agro‐food trade literature. Notwithstanding, there is a dearth of literature examining the relative trade restrictiveness of tariff barriers across a broad range of agro‐food sectors. This represents an important research gap, which this study sets out to fill. Furthermore, this research reconciles the application of zero‐inflated models with a sectorally disaggregated analysis. More specifically, employing a fully specified gravity equation, a Poisson estimator and variants of the Poisson model (Negative Binomial, Zero‐Inflated Poisson, and Zero‐Inflated Negative Binomial) provide statistically significant and theoretically consistent estimates, while allowing for the inclusion of zero‐trade values. A panel data model with fixed effects is also employed to improve the estimation of the parameters of interest. Estimation results reveal that in the vast majority of sectors examined, import tariffs are found to be statistically significant, whereas export refunds exhibit a statistically smaller role due to the nonsystematic nature of their application in world food markets. Model simulations of tariff barrier eliminations reveal limited trade gains, although there is encouraging evidence of “low” and “lower middle” per capita income country trade gains in wheat, red meat, dairy, sugar, and (particularly) rice markets.     

The Use of a Retail Store Database for Brand Choice Analysis

This paper examines relationships between perceptions and behaviours of channel members in an industry embroiled in conflict. We scrutinize these relationships from the perspective of the retailers. We utilize realistic perceptual and behavioural constructs which are meaningful to retailers. Our results suggest that the relationships between perceptions and behaviours may be bi-directional. We review the pertinent literature on conflict and suggest directions for future research.     

Donor Segmentation: When Summary Statistics Don't Tell the Whole Story

Funding pressures amidst the slow economic recovery from the late-2000's recession have forced universities, as well as other not-for-profit organizations, to increase the volume and sophistication of their direct marketing activities. The efficiency of direct marketing strategies is linked to an organization's ability to effectively target individuals. In this paper, we present a finite-mixture model framework to segment the alumni population of a university in the midwestern United States.Much of the research on customer segmentation summarizes response data (e.g., purchase and contribution histories) via recency, frequency and monetary value (RFM) statistics. Individuals sharing similar RFM characteristics are grouped together; the rationale being that the best predictor of future behavior is past behavior. Summary statistics such as RFM, however, introduce aggregation bias that mask the dynamics of purchase/contribution behavior. Accordingly, we implement latent-class segmentation models where alumni are classified based on how an individual's contribution sequence compares to those of other individuals. The framework's capability to process contribution sequences, i.e., longitudinal data, provides fundamental new insights into donor contribution behavior, and provides a rigorous mechanism to infer and segment the population based on unobserved heterogeneities (as well as based on other observable characteristics). Specifically, we analyze Markov mixture models to segment alumni based on contribution-behavior patterns, under the assumption of serially-dependent contribution sequences. We use the expectation–maximization algorithm to obtain parameter estimates for each segment. Through an extensive empirical study, we highlight the substantive insights gained through the processing of the full contribution sequences, and establish the presence of three distinct classes of alumni in the population (each with a discernible contribution pattern). The proposed framework, collectively, provides a basis to tailor direct marketing policies to optimize specific performance criteria (e.g., profits).     

Exchange rate determination and inter-market order flow effects

The dependence of foreign exchange rates on order flow is investigated for four major exchange rate pairs, EUR/USD, EUR/GBP, GBP/USD and USD/JPY, across sampling frequencies ranging from 5 min to 1 week. Strong explanatory power is discovered for all sampling frequencies. We also uncover cross-market order flow effects, e.g. GBP exchange rates are very strongly influenced by EUR/USD order flow. We proceed to investigate the predictive power of order flow for exchange rate changes, and it is shown that the order flow specifications reduce RMSEs relative to a random walk for all exchange rates at high-frequencies and for EUR/USD and USD/JPY at lower sampling frequencies.     

E‐corporate social responsibility in small non‐profit organisations: the case of Spanish ‘Non Government Organisations’

The image and the reputation of small NGOs have direct bearing on the capacity of these entities to retain and attract members, volunteers and donors. These attributes have been linked to the concept of Social Responsibility. Therefore, for NGOs to be socially responsible and to make this fact known is a key factor that will have a positive influence on their image and reputation and will contribute to their being recognised and to strengthening social confidence in them. This article analyses the e‐corporate social responsibility in Spanish NGOs. It shows the infra‐use that NGOs make of the Internet as an information medium to communicate their Corporate Social Responsibility (CSR) practices. In terms of transparency, this implies that the CSR transparency on their websites is very poor, although it grows as the size of the organisation increases.     

Epstein–Zin Utility in DICE: Is Risk Aversion Irrelevant to Climate Policy?

Climate change involves uncertain probabilities of catastrophic risks, and very longterm consequences of current actions. Climate economics, therefore, is centrally concerned with the treatment of risk and time. Yet conventional assumptions about utility and optimal economic growth create a perverse connection between risk aversion and time preference, such that more aversion to current risks implies less concern for future outcomes, and vice versa. The same conflation of risk aversion and time preference leads to the equity premium puzzle in finance. A promising response to the equity premium puzzle, the recursive utility of Epstein and Zin, allows separation of risk aversion and time preference—at the cost of considerable analytic complexity. We introduce an accessible implementation of Epstein–Zin utility into the DICE model of climate economics, creating a hybrid “EZ-DICE” model. Using Epstein–Zin parameters from the finance literature and climate uncertainty parameters from the science literature, we find that the optimal climate policy in EZ-DICE calls for rapid abatement of carbon emissions; it is similar to standard DICE results with the discount rate set to equal the risk-free rate of return. EZ-DICE solutions are sensitive to the intertemporal elasticity of substitution, but remarkably insensitive to risk aversion. Insensitivity to risk aversion may reflect the difficulty of modeling catastrophic risks within DICE. Implicit in DICE are strong assumptions about the cost of climate stabilization and the certainty and speed of success; under these assumptions, risk aversion would in fact be unimportant. A more realistic analysis will require a subtler treatment of catastrophic climate risk.     

Investing in mutual funds: the determinants of implied and actual net cash flows

Estimating the fund investors’ demand plays an important role in the mutual fund management. In this line, mutual fund demand can be measured as the total net cash flows experienced by the fund during a period. Due to a lack of the data for inflows and outflows in some countries and databases, many authors estimate the net cash flows using fund size and return information. This rough measure, although being a good approximation, implicitly assumes an error in its calculation. For a sample of 2985 US open-end funds, we find evidence that estimating this implied fund flows, the error generated is higher for smaller funds, funds with higher returns, and for those experiencing higher levels of inflows or outflows. This lack of precision leads to a distortion in the estimation of the effect of some determinants on the mutual fund demand, especially when longer periods are considered when constructing the net cash flows.