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.     

The Impact of Bank Credit on Employment Formality: Evidence from Uruguay

This article examines the effect of bank credit on employment formalization in Uruguay. Using a difference-in-differences methodology the article finds that financial deepening decreases informality, especially in more financially dependent sectors. In addition, the effect is found to be greater among women and older workers. In the period under analysis the economy underwent a severe economic crisis and bank credit contracted sharply, but we find no evidence that the effect of bank credit on employment formality changed over time.     

An Active Asset Management Investment Process for Drawdown-Averse Investors

The contribution of this article is to present an investment process that allows the asset manager to limit risk exposure to macro-factors – including expectations on correlation dynamics – whilst allowing for selective exposure to risk factors using factor-portfolios that emulate the risk and return profile of market micro-factors. The design of the process provides the ability to explicitely limit risk exposures to macro-factors based on forward-looking narratives allowing the investor to reflect – in the resulting active allocation – expectations of financial or systemic crises by, say, restricting the overall exposure to the credit macro-factor that includes the risk factor exposures (micro-level) arising, for example, from corporate and supranational spreads whilst simultaneously increasing the exposure to flight-to-safety macro-factors under a local or global crisis. This process is better suited to drawdown-averse investors that are willing to forgo some upside in order to effectively limit significant portfolio losses from crises, systemic or otherwise. In order to improve the optimization over the rugged solution space resulting from superimposing macro-factors' risk envelopes on the factor-portfolios' tracking error allocation, a genetic-algorithm-based optimization is proposed. Copyright © 2015 John Wiley & Sons, Ltd.     

Risk aversion and inequity aversion in demand for unemployment benefits

This paper is an empirical study of what motivates net contributors to support redistributive policies. While studies in the area have tended to consider broad measures of inequality and support for redistribution in general, we focus on a single, salient relationship between local unemployment rates and demand for spending on unemployment benefits. Using a particularity of the Spanish labour market, we estimate how workers’ stated preferences for unemployment benefits spending respond to changes in the local unemployment rate. We then decompose this response into the part explained by risk aversion, and thus demand for insurance, and the part explained by inequity aversion. Our results suggest that increases in local unemployment rates lead to increased demand by workers for unemployment benefits spending. Moreover, our results are consistent with an insurance motive driving this relationship but provide little support for inequity aversion. Our results suggest that studies of the relationship between inequality and demand for redistribution might benefit from considering both the source and measure of the inequality and the instrument of redistribution.     

Modeling public transport corridors with aggregate and disaggregate demand

Microeconomic public transport models aimed at maximizing social benefits usually consider demand in an aggregate manner. In this paper we examine the effect of this approach on the optimal values of frequency and vehicle size by comparison with models where demand is described in detail as a matrix of flows between every station in a single line service. The theoretical analysis and the numerical examples suggest that the spatially aggregated model underestimates optimal frequency and overestimates vehicle size.     

International Technology Diffusion: Effects of Trade and FDI

There has been little analysis of the effect of inward FDI on international R&D diffusion, especially in LDCs, although FDI has become the core of international production and LDCs have been receiving an increasing share of world FDI over the past few decades. Using data from 57 countries from 1988 to 2001, we find that both FDI and trade serve as important channels of international technology diffusion. However, there exist heterogeneous effects of FDI in DCs and LDCs. For inward FDI to promote technology diffusion in LDCs, a certain threshold of human capital has to be reached.     

TAX DATA FOR WEALTH CONCENTRATION ANALYSIS: AN APPLICATION TO SPANISH WEALTH TAX

As recent studies in different countries show, tax data offer the opportunity to estimate income or wealth shares for the upper income groups. However, several critical points must be considered in order to avoid misleading conclusions: the interpolation technique used, legal amendments, and tax fraud. In this note we take Spanish wealth tax as a case study to assess the importance of these factors, and compare our results with those obtained by Alvaredo and Saez (2009 ). Although the results of the two analyses are very similar, our approach complements theirs by offering a more precise treatment of the correction of fiscal underassessment and tax fraud in real estate, which is the main asset in Spaniards' portfolios.     

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.     

Toward a conceptual framework of the harmonization of bank financial reporting standards in transition economies: The case of Mexico

In recent years banks in emerging and transition economies throughout the world have been compelled to change lending and financial reporting practices in response to the economic transition of their countries. Correspondingly, on the basis of the theory of soft budget constraints (SBC), economists have studied the relationship between economic development, banks' lending practices, and banks' penchant to overstate loans. However, very little research has been performed by accounting researchers regarding the nature of bank loan overstatement during times of financial crisis in emerging markets. Accordingly, this paper uses the theory of soft budget constraints to develop a four stage conceptual framework of the harmonization of bank financial reporting standards during times of economic transition. Emphasis is placed on using the theory of soft budget constraints to characterize the harmonization of standards and practices with respect to bank loan overstatement. The framework is applied to the harmonization of Mexican bank financial reporting during the country's economic transition of the late 1990s. The Mexican harmonization process during this period generally followed the framework.