Money demand and the shadow economy: empirical evidence from OECD countries

Herwartz, Helmut; Sardà, Jordi; Theilen, Bernd

doi:10.1007/s00181-015-0970-7

Cited by 12 publications

(14 citation statements)

References 40 publications

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“…The quantification and detection of tax fraud is a top priority amongst the most important goals of tax offices in several countries. The estimates regarding tax fraud at the international level reveal that Spain is one of the developed countries with a high level of tax fraud, exceeding 20% of GDP [1][2][3]. Despite the measures implemented to curtail this, to date, there has been no reduction with respect to the trend [4,5].…”

Section: Introductionmentioning

confidence: 99%

Tax Fraud Detection through Neural Networks: An Application Using a Sample of Personal Income Taxpayers

2019

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The goal of the present research is to contribute to the detection of tax fraud concerning personal income tax returns (IRPF, in Spanish) filed in Spain, through the use of Machine Learning advanced predictive tools, by applying Multilayer Perceptron neural network (MLP) models. The possibilities springing from these techniques have been applied to a broad range of personal income return data supplied by the Institute of Fiscal Studies (IEF). The use of the neural networks enabled taxpayer segmentation as well as calculation of the probability concerning an individual taxpayer’s propensity to attempt to evade taxes. The results showed that the selected model has an efficiency rate of 84.3%, implying an improvement in relation to other models utilized in tax fraud detection. The proposal can be generalized to quantify an individual’s propensity to commit fraud with regards to other kinds of taxes. These models will support tax offices to help them arrive at the best decisions regarding action plans to combat tax fraud.

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Section: Introductionmentioning

confidence: 99%

Tax Fraud Detection through Neural Networks: An Application Using a Sample of Personal Income Taxpayers

2019

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“…The empirical literature on money demand has traditionally and consistently found a positive effect of income and a negative impact of interest rates over different measures of monetary aggregates (Knell and Stix (2006)). When attention is restricted to narrow definitions of money, as in the case of cash demand, estimations have confirmed these relations and the importance of other factors such as financial innovations and the shadow economy (Alvarez and Lippi (2009); Herwartz et al (2016)).…”

Section: Introductionmentioning

confidence: 94%

Digital Payments Adoption and the Demand for Cash: New International Evidence

Arango¹,

Suárez-Ariza²

2019

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Even though the levels and growth rates of adoption of digital payments have reached significant figures in the recent past, the demand for cash continues to grow in both developed and developing economies across the world. This puzzle has found only partial explanations in the previous empirical literature. We bring further and more conclusive evidence that the adoption of digital payments indeed reduces the demand for cash. Yet, economic growth and lower interest rates as well as positive trends in the demand for large denomination banknotes, not explained by traditional factors, still dominate the overall growth in the demand for cash.

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“…He finds no effects in the case of Norway, but a positive relationship for Sweden. Using the same methodology, Herwartz et al (2016)investigate whether shadow economic activities have a measurable influence on the demand for currency in a cross section of 11 OECD countries (including Germany, Italy, Norway, Spain and Switzerland) from 1970 to 2012. They find within an error-correction model based on pooled data that some of these variables have a significant influence on cash demand.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

“…First, we are the first to use net issues of cash of all national euro area central banks to analyze the relationship between cash demand and the shadow economy within a currency union. Up to now, these net issues are only investigated for individual countries (see Bartzsch et al, 2013;Rua, 2018), for other currency areas like the US (see Judson & Porter, 2000, ch 6.4) or, instead, currency (banknotes) in circulation is used (see Herwartz et al, 2016;Klovland, 1984). Second, we distinguish between large and small countries as well as between large, medium and small denominations.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

“…Third, we use estimates of the shadow economy which do not rely on the currency demand approach (see, e.g., Medina & Schneider, 2018, ch 3). 3 This is necessary to circumvent the circularity problem of estimating the shadow economy with cash figures, and in a subsequent step estimating cash demand functions that include as regressor the size of the shadow economy estimated in the first step (see also Herwartz et al, 2016 The paper is structured as follows: It starts with some theoretical reflections and our basic hypothesis in section 2.Section 3presents the data and explains the concept of net issues of banknotes and the selected estimation procedure for the shadow economy. Moreover, the econometric methodology is briefly described.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

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Cash in Circulation and the Shadow Economy: An Empirical Investigation for Euro Area Countries and Beyond

Seitz¹,

Reimers²,

Schneider³

2020

JBEP

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We analyze the net cash issues of the national euro area central banks in relation to the dynamics of the shadow economy within a panel cointegration framework. Besides the total net issues, we distinguish between large, medium and small euro banknotes and take due account of other determinants of cash demand as well as country-specific repercussions of the financial crisis of 2008. We find a significant and positive relationship between the net issues and the size of the shadow economy only for medium notes. And this result seems to be driven by the smaller euro area countries. The use of large and small denominations is obviously not driven by the shadow economy. For comparison purposes, we also present panel results for eight non-euro area countries (

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Money demand and the shadow economy: empirical evidence from OECD countries

Cited by 12 publications

References 40 publications

Tax Fraud Detection through Neural Networks: An Application Using a Sample of Personal Income Taxpayers

Tax Fraud Detection through Neural Networks: An Application Using a Sample of Personal Income Taxpayers

Digital Payments Adoption and the Demand for Cash: New International Evidence

Cash in Circulation and the Shadow Economy: An Empirical Investigation for Euro Area Countries and Beyond

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