Government efficiency and fiscal rules

Barbier‐Gauchard, Amélie; Baret, Kéa; Debrun, Xavier

doi:10.4337/9781839109164.00014

Handbook on Public Sector Efficiency 2023

DOI: 10.4337/9781839109164.00014

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Government efficiency and fiscal rules

Amélie Barbier‐Gauchard¹,

Kéa Baret²,

Xavier Debrun³

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Cited by 3 publications

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“…7 See for instanceDebrun et al (2008) orWyplosz (2012) for a general overview of the main reasons for introducing fiscal rules. 8 See insteadForemny (2014),Sacchi and Salotti (2015),Bergman et al (2016),Barbier-Gauchard et al (2021) orBarbier-Gauchard et al (2023) for instance. 9 See papers on the second generation of fiscal rules by Eyraud et al (2018), Caselli et al (2018), Darvas et al (2018), Hauptmeier and Kamps (2020), Debrun and Jonung (2019) and Blanchard et al (2020).…”

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confidence: 99%

Forecasting stability and growth pact compliance using machine learning

Baret,

Barbier‐Gauchard,

Papadimitriou

2023

World Economy

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The 2011 reform of the Stability and Growth Pact (1996) strengthened the European Commission's monitoring of EU member states' public finance. Failure to comply with the 3% limit on public deficit triggers an audit. In this paper, we present a machine learning based forecasting model for compliance with the 3% limit. We use data from 2006 to 2018 (a turbulent period including the Global Financial Crisis and the Sovereign Debt Crisis) for the 28 EU member states. After identifying 8 features as predictors among 138 variables, forecasting is performed using a support vector machine (SVM) algorithm. The proposed model achieved a forecasting accuracy of nearly 92% and outperformed the logit model used as a benchmark.

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Forecasting stability and growth pact compliance using machine learning

Baret,

Barbier‐Gauchard,

Papadimitriou

2023

World Economy

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Regional economic growth, digital economy and tax competition in China: mechanism and spatial assessment

Lin,

Baskaran

2024

Journal of the Asia Pacific Economy

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Assessing the Drivers of Sustained Agricultural Economic Development in China: Agricultural Productivity and Poverty Reduction Efficiency

Wang,

Tong,

Fang

2024

Sustainability

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Poverty eradication is a crucial element of SDG 1. Whether the financial resources invested by the Government provide a critical impetus for deeply impoverished rural areas needs to be studied by quantitative analysis. Therefore, this study presents a theoretical analytical framework for agricultural production–government poverty reduction. It divides the poverty reduction process into two stages, agricultural production and poverty reduction, from the perspective of sustainable agricultural development. The comprehensive measurement and spatio-temporal evolution analysis of China’s agricultural production and poverty reduction efficiency are conducted using a novel dynamic two-stage DEA model, which incorporates non-expected factors. The study found that (1) China’s agricultural production and poverty reduction efficiency exhibit overall poor performance, characterized by two poles of differentiation. (2) The agricultural production efficiency score is higher in the northern region than in the southern region, while the poverty reduction efficiency score is higher in the eastern region compared to the western region. (3) The coupling and coordination between China’s production efficiency and poverty reduction efficiency are inadequate.

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Government efficiency and fiscal rules

Cited by 3 publications

References 0 publications

Forecasting stability and growth pact compliance using machine learning

Forecasting stability and growth pact compliance using machine learning

Regional economic growth, digital economy and tax competition in China: mechanism and spatial assessment

Assessing the Drivers of Sustained Agricultural Economic Development in China: Agricultural Productivity and Poverty Reduction Efficiency

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