Animal disease outbreaks and food market price dynamics: Evidence from regime‐dependent modelling and connected scatterplots

The economic impacts of animal disease outbreaks have been widely discussed in the literature. Most authors have centred their attention on estimating the direct costs. Recent studies have shown that the indirect economic effects might lead to equal or even higher welfare losses. This study aims to contribute to this field of research by assessing the effect of an animal disease outbreak on food market price dynamics in Mexico, accounting for the potential effect of an antitrust intervention. We employ a regime‐dependent vector error correction model and a connected scatterplot analysis. The results show that both the outbreak and the antitrust intervention caused structural breaks in food market price dynamics between producers and consumers, reflected in an increase in the absolute component of the marketing margin, with serious food security implications.     

Assessing the economic impact of entrepreneurship on a regional economy using social accounting matrices: the case of Andalusia

This article analyses the impact that entrepreneurial activity has, from the economic point of view, on a regional economy (Andalusia), based on a Social Accounting Matrix linear model. Moreover, to measure entrepreneurship at regional level, it is defined what can be considered an entrepreneurial initiative company from a quantitative point of view. The results obtained, in terms of Production, GDP and job creation, show how entrepreneurship, in the case of Andalusia, contributes to the sustainability of the economy, its growth and, above all, the reduction of unemployment in the short term.     

CAPM and APT-like models with risk measures

The paper deals with optimal portfolio choice problems when risk levels are given by coherent risk measures, expectation bounded risk measures or general deviations. Both static and dynamic pricing models may be involved. Unbounded problems are characterized by new notions such as (strong) compatibility between prices and risks. Surprisingly, the lack of bounded optimal risk and/or return levels arises for important pricing models (Black and Scholes) and risk measures (VaR, CVaR, absolute deviation, etc.). Bounded problems present a Market Price of Risk and generate a pair of benchmarks. From these benchmarks we introduce APT and CAPM-like analyses, in the sense that the level of correlation between every available security and some economic factors explains the security expected return. The risk level non correlated with these factors has no influence on any return, despite the fact that we are dealing with risk functions beyond the standard deviation.     

Defining efficient policies in a general equilibrium model: a multi-objective approach

Macroeconomic policy makers are typically concerned with several indicators of economic performance. We thus propose to tackle the design of macroeconomic policy using Multicriteria Decision Making (MCDM) techniques. More specifically, we employ Multi-objective Programming (MP) to seek so-called efficient policies. The MP approach is combined with a computable general equilibrium (CGE) model. We chose use of a CGE model since it has the dual advantage of being consistent with standard economic theory while allowing one to measure the effect(s) of a specific policy with real data. Applying the proposed methodology to Spain (via the 1995 Social Accounting Matrix) we first quantified the trade-offs between two specific policy objectives: growth and inflation, when designing fiscal policy. We then constructed a frontier of efficient policies involving real growth and inflation. In doing so, we found that policy in 1995 Spain displayed some degree of inefficiency with respect to these two policy objectives. We then offer two sets of policy recommendations that, ostensibly, could have helped Spain at the time. The first deals with efficiency independent of the importance given to both growth and inflation by policy makers (we label this set: general policy recommendations). A second set depends on which policy objective is seen as more important by policy makers: increasing growth or controlling inflation (we label this one: objective-specific recommendations).     

The Early Careers Of Engineers And The Accumulation Of Skills In The Canadian Economy

In this paper we use world cycling records to study the pattern of technological development of the track bicycle. We find that there is a strong evidence of ‘contagious’ effects among cycling records which in turn provides indirect evidence of ‘contagious’ effects among technological innovations. Interestingly, the ‘contagiousness’ of records is not a salient characteristic of track and field competitions where, arguably, technology plays a smaller role.     

Comment on sustainability and innovation in staple crop production in the US Midwest

This comment highlight issues when comparing genetically modified (GM) crops to non-GM ones across countries. Ignoring structural differences between agricultural sectors and assuming common yield trajectories before the time of introduction of GM crops results on misestimating the effect of GM varieties. Further data collection and analyses should guide policy-makers to encourage diverse approaches to agriculture, rather than excluding specific technologies (like GM crops) from the onset.     

New Multilateralism in Action for Peace: A Case Study of the US-led Operation Unified Assistance in the Asian Tsunami Disaster1

Abstract

In the aftermath of the Indian Ocean earthquake and tsunami in December 2004, the ensuing multinational relief, humanitarian, and rebuilding efforts of the Operation United Assistance (OUA) are new examples of international cooperation to sustain and rebuild Asian communities in the post-9/11 security environment. An analysis of the cooperative efforts in light of differing theoretical perspectives provides a forum for debate on the nature of cooperation in the international arena and the implications for ethnic and civil wars in Indonesia and Sri Lanka. Once described and explained by multiple theories, the relief operations can then be used to predict and perhaps even prescribe future international cooperation in natural disasters and conflict resolution in civil war environments. As a case study, this paper also examines international security strategies and the implications for economic prosperity and political stability in sovereign but weak nation states.     

An agent-based model for the assessment of LTV caps

We assess the effects of regulatory caps in the loan-to-value (LTV) ratio for housing mortgages using an agent-based model. Sellers, buyers and banks interact within a computational framework that enables the application of LTV caps to a one-step housing market. We first conduct a simulation exercise; later, we calibrate the probability distributions based on actual European data from the Household Finance and Consumption Survey. In both cases, the application of an LTV cap results in a modified distribution of buyers in terms of property values, bidding prices and properties sold, depending on the probability distributions of the LTV ratio, wealth and debt-to-income ratios considered. The results are of similar magnitude to other studies in the literature embodying other analytical approaches, and they suggest that our methodology can potentially be used to gauge the impact of common macroprudential measures.     

Using Artificial Neural Networks to forecast Exchange Rate,including VAR‐VECM residual analysis and prediction linear combination

The Euro US Dollar rate is one of the most important exchange rates in the world, making the analysis of its behavior fundamental for the global economy and for different decision‐makers at both the public and private level. Furthermore, given the market efficiency of the EUR/USD exchange rate, being able to predict the rate's future short‐term variation represents a great challenge. This study proposes a new framework to improve the forecasting accuracy of EUR/USD exchange rate returns through the use of an Artificial Neural Network (ANN) together with a Vector Auto Regressive (VAR) model, Vector Error Corrective model (VECM), and post‐processing. The motivation lies in the integration of different approaches, which should improve the ability to forecast regarding each separate model. This is especially true given that Artificial Neural Networks are capable of capturing the short and long‐term non‐linear components of a time series, which VECM and VAR models are unable to do. Post‐processing seeks to combine the best forecasts to make one that is better than its components. Model predictive capacity is compared according to the Root Mean Square Error (RMSE) as a loss function and its significance is analyzed using the Model Confidence Set. The results obtained show that the proposed framework outperforms the benchmark models, decreasing the RMSE of the best econometric model by 32.5% and by 19.3% the best hybrid. Thus, it is determined that forecast post‐processing increases forecasting accuracy.     

Does Teacher Subject Knowledge Contribute to Student Academic Performance in Developing and Least Developed Countries?

Little is known about the causal impact of teacher knowledge on student performance. In this research paper we intend to approach the potential causal effect (i.e. going beyond correlation) of sixth grade teachers’ knowledge on their students’ academic achievement for three Sub-Saharan African countries. To achieve this, we have used the heterogeneity of teachers’ subject knowledge and students’ correspondent academic achievement within-student between-subjects using student fixed effects. Concretely, our work is based on previous research by Bietenbeck, Piopiunik and Wiederhold. Compared to them, we do not use countries that lack representative information after keeping only those students taught by the same teacher for the subjects under analysis. This enables us to obtain more reliable results on this issue. Our results indicate that teacher subject knowledge in reading and mathematics does not have a significant influence on student academic achievement in these subjects for the countries under scrutiny. Many robustness checks have corroborated this conclusion, which contrasts with the positive effect found by Bietenbeck, Piopiunik and Wiederhold.