Manuel Landajo

Determinants of fiscal decentralization: a neural network approach for OECD countries

Francisco J. Delgado, Manuel Landajo

Fiscal decentralization is a complex phenomenon driven by several forces, including socioeconomic, institutional, and historical issues. We analyze the determinants of fiscal decentralization through the percentage of expenditure or revenue of the subcentral governments – over the total – in 30 OECD …

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Stationarity and cycles in the energy consumption in the United States

María José Presno, Manuel Landajo

The purpose of this paper is twofold: analyzing stationarity of energy consumption by source in the United States and studying their cycles and pairwise synchronization. We study a panel of nine time series of monthly energy consumption for the period 1973-2022. Four …

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GHG Emissions in the Eu-28: A Multilevel Club Convergence Study of the Emission Trading System and Effort Sharing Decision Mechanisms

María José Presno, Manuel Landajo, Paula Fernández González

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Tax avoidance and earnings management: a neural network approach for the largest European economies

Francisco J. Delgado, Elena Fernández Rodríguez, Roberto García Fernández, Manuel Landajo et autres

Abstract In this study, we investigate the relationship between tax avoidance and earnings management in the largest five European Union economies by using artificial neural network regressions. This methodology allows us to deal with nonlinearities detected in the data, which is the …

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Tracking the change in Spanish greenhouse gas emissions through an LMDI decomposition model: A global and sectoral approach

Paula Fernández González, María José Presno, Manuel Landajo

The reduction of GHG emissions to reverse the greenhouse effect is one of the main challenges in this century. In this paper we pursue two objectives. First, we analyze the evolution of GHG emissions in Spain in 2008-2018, at both the global …

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The prices of renewable commodities: a robust stationarity analysis*

Manuel Landajo, María José Presno

This paper addresses the problem of testing for persistence in the effects of the shocks affecting the prices of renewable commodities, which have potential implications on stabilisation policies and economic forecasting, among other areas. A robust methodology is employed that enables the …

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EU-28’s progress toward the 2020 renewable energy share: a club convergence analysis

María José Presno, Manuel Landajo

This paper assesses the convergence of the EU-28 countries toward their common goal of 20% in the renewable energy share indicator by year 2020. The potential presence of clubs of convergence toward different steady-state equilibria is also analyzed from both the standpoints …

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Stationarity in the Prices of Energy Commodities. A Nonparametric Approach

Manuel Landajo, María José Presno, Paula Fernández González

In this paper, we address the classical problem of testing for stationarity in the prices of energy-related commodities. A panel of fourteen time series of monthly prices is analyzed for the 1980–2020 period. Nine of the series are classical nonrenewable, GHG-emissions-intensive resources …

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GHG emissions in the EU-28. A multilevel club convergence study of the Emission Trading System and Effort Sharing Decision mechanisms

María José Presno, Manuel Landajo, Paula Fernández González

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Nonparametric panel stationarity testing with an application to crude oil production

María José Presno, Manuel Landajo, Paula Fernández González

A nonparametric panel stationarity test is proposed which offers the advantage of not requiring prior specification of the trend function for each of the series in the panel. A bootstrap implementation of the test is outlined and its finite sample performance is …

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Using Nonlinear Quantile Regression for the Estimation of Software Cost

Javier de Andrés Suárez, Manuel Landajo, Pedro Tedde de Lorca

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The Shocks To Crude Oil Production. Nonparametric Stationarity Analysis For 20 OPEC And Non-OPEC Countries

Presno M.J., Manuel Landajo, Fernandez Gonzalez P.

Introduction: With recent breakthroughs in organized and amorphous data and rapid growth in analysis methodologies, Artificial Intelligence (AI) is causing a revolution in the health care industry. The value of Artificial Intelligence in health care is becoming recognized at the same time …