Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

In this paper, we perform an empirical analysis in order to estimate the adoption effect of the new lease accounting standard (IFRS 16) has had on the financial statements of quoted Spanish companies. Previous literature has not considered the final version of the new standard as it had not yet been issued. In this sense, our methodology design is more consistent with the final standard as regards aspects such as lease term, discount rate, and how lease asset and liability are measured. The adoption of IFRS 16 will have a significant impact on the financial statements of Spanish companies; in fact, it will have an even greater impact than on European firms in those sectors most affected, and said impact will also be greater than that demonstrated in previous literature. There will be an important impact on balance sheet: total assets and liabilities will increase, involving an increase in leverage ratios. Interest coverage ratio will experience an important decrease. The effects will be higher in those sectors with higher lease relative volume, such as retail, hotels, professional services and the media. As in previous studies, we do not find consistent results in relation to profitability. This paper will be of use to analysts since it improves the methodology for estimating the impact of lease capitalization.

Spatial and spatio-temporal data are not new. They have always been here. However, until fairly recently the scientific community had at its disposal neither the theory nor the technology to deal with them. It was thus unable to take advantage of the spatial or spatio-temporal dependencies existing in a large number of phenomena when it comes to estimating, predicting, mapping, experimental designing, etc. This article first addresses the adverse consequences of failing to account for such dependencies. Then, it traces the route travelled by geostatistics from its beginnings to the present day, providing the reader with the rudiments of kriging, the technique geostatistics uses for inferential purposes. However, this article is not only an overview. It poses a number of criticisms, alternatives, open questions and future avenues of research in its different phases: spatial-only, spatio-temporal and functional. Initially having arisen in the Earth sciences, and having been applied in many natural sciences, in recent years geostatistics has stepped into the sphere of social sciences and particularly applied economy.

The decision-making process on the behalf of a person and institutions has been considered, under the economic conventional assumption, as a rational process developed in a complete information context. However, reality has proved the excessive simplicity and the lack of realism of such assumption. This paper analyzes the decision-making process from a theoretical perspective and it asks if behavioral economics can help us to understand some recent events that suppose uncertainty in the European architecture and question some traditional instruments of economic policy.

Cyber threats affect all kinds of organisations with frequent and costly impacts worldwide. Cyber insurance products have recently emerged with the potential of lowering the impact of cyberspace risks. However, they have yet to mature. In this paper we present several risk analysis models that may facilitate the implementation and adoption of cyber insurance. These models, described in terms of influence diagrams and bi-agent influence diagrams, provide a framework for estimating the economic impact of cyber risks that may face insurers and insurees as well as calculating their optimal risk mitigation and transfer strategies.

Starting from a socio-cybernetic perspective, some questions are proposed to think about the social future of applied economics. First, it addresses the social and the economic considering the debate of 'embeddedness'. Second, there is the tension of the social sciences between describing and prescribing on the framework of the great transformation provoked by the digitization of social processes. Third, the influence of financial market regulators is discussed, where Draghi's 'oracle' in August 2017 serves as an example. Finally, some keys are posited to think about the future.

This essay seeks to rehabilitate the capital asset pricing model by splitting beta, the basic unit of systematic risk, into subatomic (or “baryonic”) components. By analogy to quantum chromodynamics and other aspects of the Standard Model of particle physics, this essay bifurcates beta on either side of mean returns and into distinct components reflecting relative volatility and correlation, as well as cash-flow and discount-rate effects. Splitting the atom of systematic risk answers some of the most troubling anomalies and puzzles in finance, including abnormal returns on small-cap and value stocks, the low-volatility anomaly, and the equity premium puzzle.

This paper leads to deliberate on economics as a science. One of the basic principles of the scientific method is the "reproducibility", so an experiment can be tested o repeat it. This is based on the publicity of its results and its potential verification by the scientific community. Nowadays, this basic rule of the scientific method seems to be in question in the economic analysis. Then, we find in the literature, more recently, numerous articles that discuss the need to impulse and promote the replication of empirical studies. Researchers should obtain the author’s dataset and codes that facilitate the replication or verification or reproducibility. This is an essential part of scientific progress, providing robustness and transparency to the results already obtained and published.

The paper emphasizes the recent use of spectral analysis for forecasting financial and economic time series which deserves consideration from econometricians. Time series of Spanish nominal and real GDPs are decomposed in simpler signals called approximations and details in the framework of the one-dimensional discrete wavelet analysis. The simplified signals are recomposed after Burg extension. 2017-2026 forecasts with spectral analysis are less optimistic than the ones of government agencies. Benchmarking spectral analysis to an ARIMA model show the pertinence of adding spectral analysis to the battery of tools used by econometricians and quantitative analysts for the forecast of economic time series.

Multi-winner voting is a way to select a subset of candidates, rather than just one, in a single election process. It is easy to carry out, and has become common, but its properties are not well understood. Because the voter must use a single ballot to indicate his or her preferences over all of the candidates, many nuances of preference are difficult or impossible to express. Many forms of ballot have been proposed for multi-winner voting; for some of them, there are multiple ways to determine the winning subset from a set of submitted ballots. Generally, these counting procedures balance two objectives - to elect only candidates who are well-supported individually, and to elect a subset of candidates with broad support. The breadth of multi-winner ballots and counting procedures is surveyed, and some properties that are desirable in multi-winner voting are described.

In this paper, the GDP comparisons over time and across space are analyzed in an integrated time-space approach, to highlight the duality of the topic that allows a comprehensive treatment of the issue. The properties of the real GDP ratios are discussed, including the deflation and the exchange rate use, as well as the GDP PPPs and the International Comparison Program (ICP) framework.