This paper deals with the phenomenon of poverty-trap regimes in Mexico, that is, self-reinforcing mechanisms in which municipalities which start poor remain poor. We develop a coordination game of poverty traps driven by strategic interactions of economic agents: people choose to complete or not their education levels since it might be excessively costly and unprofitable. A one-shot game is constructed and then converted into a system of differential equations in which strategies that perform relatively better become more abundant in the population. Applying evolutionary games and symbolic-regimes dynamics (nonparametric and nonlinear techniques), we show that Mexican regions are in poverty-trap regimes (stable and dynamically evolving low-level equilibria) characterized by incomplete education and low income since initial conditions (education and income per capita) are such (very precarious) that poverty is the stable steady-state situation. We examine scenarios to show that to overcome the high-poverty regime by the year 2030, it is necessary to reduce incomplete education by 10% in the 5-year periods 2020–2025 and 2025–2030 and increase per-capita income by 10% in both periods.

Using the inter-regional economic inequality index and the gross state product per capita for the Mexican states over the period 1940-2015, we apply regime dynamics and hierarchical cluster analysis for segmenting the sample into regimes of Mexican states with similar performance.Robust econometric models are studied showing the direction of causality between economic inequality and income per capita, and the existence of a U-shaped curve for the interdependence between economic growth vs economic inequality, and threshold levels.We additionally demonstrate the existence of inequality traps.The education literacy rate as a control variable indicates an inverted U-shaped curve.

In the present study, a deterministic model is introduced to explain the stylized facts of financial data. The adaptation introduced by the labyrinth chaos model can reproduce phenomena such as heavy tails observed in financial returns, volatility clustering and jumps. The model is based on the assumption that many unstable stationary states arise from the interaction or feedback between financial prices. Model tests are performed, and the results show that the model generates series that reject a normal distribution of the returns and which can be represented by the GARCH model. An analysis applying symbolic dynamics shows similar behaviors in a system with three stock indices, three currency relations and three prices generated by the introduced model. We observe sequences that have not been produced by any of the three systems, suggesting that in a three-dimensional space, the paths traveled by the real series and those of the model may not be completely random.

Whether corruption can be conducive or not to income inequality has been the focus of interest in the last decades. To the best of our knowledge, however, none has investigated the possibility that income inequality may foster corruption. In this research note, we argue that corruption may be the response of a (perceived) unfair income inequality. Analyzing 34 OECD countries during the period 1995–2011, some tests suggest that causality between corruption and income inequality is country specific. Even more, we found that corruption increases income inequality, and income inequality affects positively corruption.

In the present chapter, we analyze the relation between tourism specialization, income distribution, and human capital in South America between 1995 and 2015. Causality is studied by applying different approaches. On one hand, the panel data Granger causality test and the test proposed by Dumitrescu and Hurlin are conducted. On the other hand, the individual causality test for each country is considered by applying the classical Granger causality and a novel symbolic causality test. The results suggest that tourism specialization measured as arrival/population (TSA) and receipts/exports (TSR) and human capital cause income distribution. The estimated regressions suggest the existence of a Kuznets curve between tourism specialization and income distribution in South America, presenting threshold for TSA equal to 53.20% and TSR equal to 19.98%. Under these thresholds, tourism specialization increases income inequality, but overpassing them the income distribution improves. In addition, human capital has also a positive effect on income distribution.

We present robust results on the empirical relationship among income inequality, innovation, and economic growth for a panel dataset of 74 countries over the period 1996-2014. We estimate pairwise causality tests to show that there is bidirectional causality between GDP per capita and R&D, while R&D causes the Gini index of income inequality, and it causes human capital. Allowing coefficients to be different across cross-sections of countries, we get in any case a pairwise bi-directionality. By dynamic panel data estimations, when regressing R&D on GDP per capita, we obtain a threshold value of 0.16% of R&D such that for values above it there is economic growth. While regressing R&D on the Gini index, we get a threshold of 0.10% of R&D above which, the income distribution begins to improve. Finally, we estimate a growth equation that depends on R&D, income inequality, and physical capital. We obtain two thresholds, one of 38.79 for the Gini (above which the economic growth decreases), and one of 0.06% for R&D such that above it, economic growth is rising.

This paper analyzes the renegotiation problem in the context of public-private partnership projects. Utilizing a game-theoretic approach, an equilibrium is found in which the government finds that accepting renegotiation can be efficient. A first indicator is proposed based the public sector comparator (PSC) that can be estimated by policymakers as an additional tool when deciding about renegotiation. A second more theoretical indicator is derived to analyze the economic and financial variables affecting renegotiation. This indicator is applied to four case studies in different countries (England, Taiwan, Portugal and China) and the results suggest that the model performs well.

The present chapter intents to present the symbolic time series analysis (STSA) reviewing the recent developments in sciences.Even if there are very few works applied to social sciences, STSA has a potential to be developed.In particular, due to the limitations about historical data, fields such as Economics and Finance need to develop statistical tests to prove their hypotheses.An independence test and a causality test based on STSA are reviewed.They seem to be more powerful, detecting different kinds of nonlinearities compared with the classical tests, usually applied in social sciences.However, there is much work to do with STSA, and social sciences are a fertile field for the development of new powerful tools.

This article analyzes the relationship between tourism and economic growth for a worldwide dataset of 179 countries during 1995–2016. Applying a panel data Granger causality test, bidirectional causality is found, supporting the feedback hypothesis at a worldwide level. The results show that a 100% increase in number of arrivals, tourism receipts, and tourism expenditure increases per capita GDP by 9%, 7%, and 10%, respectively. In contrast, a 100% increase in real per capita GDP increases number of arrivals, receipts, and expenditure by 54%, 91%, and 101%, respectively. Control variables such as human capital and gross capital formation as a percentage of GDP play an important role in tourism and economic growth.

La actividad turística se considera un sector clave en Uruguay, al igual que en el ámbito internacional, por su importancia en la generación de divisas, empleo y aporte al desarrollo local. Actores públicos y privados necesitan proyectar el número de turistas para poder realizar una planificación eficiente. A su vez, la rentabilidad de posibles oportunidades de inversión podría evaluarse mejor en base a proyecciones más precisas. Estas proyecciones también son necesarias a los efectos de posicionar un destino en relación a su competencia. Es por ello que el objetivo del presente trabajo es obtener un modelo que permita realizar proyecciones de corto plazo del número de turistas que ingresan al país. En particular, los argentinos y brasileños representan el 80% del total de turistas que ingresan a Uruguay, por ello se modela y proyecta su comportamiento para el año 2015 y 2016. Debido al comportamiento estacional de las series, se procede a realizar un análisis de series de tiempo mediante modelos SARIMA. Dicha metodología surge de la necesidad de elaborar modelos rigurosos pero parsimoniosos, que puedan ser fácilmente transmitidos y asimilados por las instituciones públicas y privadas, de modo que estos instrumentos sean de utilidad y se les pueda dar continuidad. Según los modelos ajustados a este caso, se prevé para el 2015 un aumento de la cantidad de turistas argentinos del 5,6% respecto al año 2014, mientras que para los brasileños se espera que crezcan un 5,1% en el mismo periodo.

The correlation between democracy and income inequality, as well as the direction of causation is still debated. In this paper, we conduct a dynamic panel data analysis for all 34 Organisation for Economic Co-operation and Development member states over the period 1960–2012 and illustrate a nonmonotonic relationship between inequality and democracy, as well as test the direction of causation by employing a noncausal homogeneity test in a panel Granger framework and the Dumitrescu and Hurlin noncausal heterogeneity test. We provide an explanation for the inverted U-shaped relation. In addition, we illustrate individual regression results for 12 exemplary Organisation for Economic Co-operation and Development countries and provide a concise illustration of the economic and political changes to which countries have been subjected while elaborating the effect of the underlying policies on democracy and income equality.

A novel non-causality test is developed based on the symbolic time series approach. The test is suggested to be complementary to the Granger non-causality test widely apply in empirical research. A statistic is constructed and its asymptotic distribution is derived. Size and power experiments are conducted comparing the results with the classical Granger non-causality. It is found that the symbolic test presents a good performance detecting nonlinear processes such as exponential, NLAR model and the chaotic Lorenz map.

In this document the Uruguayan departmental tourism GDP was estimated, disaggregating the results obtained in the first Tourism Satellite Accounts in 2008, using (Geary and Stark, 2002) methodology. Montevideo and Maldonado generate 62.92% of Tourism GDP in 2010 considering Hotels and restaurants activities only. The departmental distribution does not differ statistically from the latest official approaches dating from 2006. It is noted that more than 80% of the touristic GDP is concentrated in the southern coast of the country. Also noteworthy is the significant growth in production and participation of Rocha and may be related to tourism development in recent years.

An independence test based on symbolic time series analysis (STSA) is developed. Considering an independent symbolic time series there is a statistic asymptotically distributed as a CHI-2 withn-1degrees of freedom. Size and power experiments for small samples were conducted applying Monte Carlo simulations and comparing the results with BDS and runs test. The introduced test shows a good performance detecting independence in nonlinear and chaotic systems.

En el presente estudio se estima el PIB turístico (PIBT) departamental de Uruguay, regionalizando los resultados obtenidos en el ejercicio piloto de Cuentas Satélite de Turismo en el año 2008, usando la metodología de (Geary y Stark, 2002). Se encuentra que los departamentos de Montevideo y Maldonado generan el 62,92% del PIBT cuando se consideran sólo las actividades Hoteles y Restaurantes en 2010. La distribución departamental parece no diferir estadísticamente de las últimas aproximaciones oficiales que datan de 2006. Se aprecia que más del 80% del PIBT se concentra en la costa sur del país. Cabe destacar el gran crecimiento, tanto en la producción como en participación, que presenta el departamento de Rocha y que puede estar relacionada al desarrollo turístico que ha tenido en los últimos años.

Routinely, practitioners and academics alike propose the use of trading strategies with an alleged improvement on the risk-return relation, typically entailing a considerably higher return for the given level of risk. A very popular example is "A quantitative approach to tactical asset allocation" by the fund manager M. Faber, a real hit in the SSRN online library. Is this paper a counterexample to market efficiency? We reject this conclusion, showing that a lot of caution should be used in this field, and we indicate a series of bootstrapping experiments which can be easily implemented to evaluate the performance of trading strategies.

This paper describes the dynamics of economic performance for the sub-national Mexican states from 1970 to 2006; the state variables used are the levels and the growth rates of per capita gdp. The authors situate this approach in a conceptual and methodological panorama of the existent literature. Starting from the regime concept, the paper introduces a distance notion to compare the observed paths and the clustering of the economies whose evolution is studied. The analysis shows that two fundamental clusters have existed: one of high and another of low performance, in addition to other transitory groups. In the high performance cluster the member's number increases, while in the low performance cluster this number diminishes. At the same time, the article shows that the sub-national states that belong to the first cluster have had an increasingly similar performance. Also, it confirms that the sub-national states move from the low to the high performance cluster, and that the distance between both clusters has increased. The interpretation of these facts is based on the dual economy concept proposed by the development theory.

The empirical evidence on the relationship between income inequality and economic growth is widely recognized and, now, there are rich databases for carry on panel-data type of analyses. However, time series studies for specific countries may be more attractive and yield revealing results. For this reason, we study hereafter the long-run relationship between economic growth and income inequality in the case of Mexico. To this end, a time series of data for the Gini coefficients from Solt (2011) is used over the period 1968–2010, within a cointegration exercise. Being related to a single country, our results are suffering less from problems of heterogeneity, endogeneity, and measurement errors, which are commonly encountered in cross-country growth regressions. We first investigate (and confirm) that the two series of per capita GDP and Gini index are cointegrated. Five different methodologies are implemented in our analysis, so that the robustness of cointegration results is guaranteed. We consistently also find that the relationship between those variables is negative. Moreover, results show the per capita GDP to be weakly exogenous. According to tests for Granger causality, unidirectional causality runs from per capita GDP to the Gini index.

En este trabajo estudiamos la estructura jerárquica y la dinámica de las relaciones existentes entre los tipos de cambio reales en los principales mercados latinoamericanos. Con este fin, introducimos una metodología que combina el análisis de series temporales simbólicas (STSA) de Daw et al. (2003) con el algoritmo de agrupación de asociación al vecino más cercano (nearest neighbor single linkage clustering algorithm, NSLCA; véase Mantegna y Stanley, 2000). A partir de la simbolización de los datos podemos obtener distancias métricas entre series temporales que pueden ser usadas para construir un árbol de expansión mínima (MST), y distancias ultramétricas que permiten construir un árbol jerárquico (HT). Estos árboles permiten detectar conexiones dinámicas y organización jerárquica de los mercados cambiarios de Latinoamerica a partir de la construcción de distintos grupos de acuerdo a su proximidad.