A proposal of a suspicion of tax fraud indicator based on Google trends to foresee Spanish tax revenues

Manuel Monge, Carlos Poza and Sofía Borgia

International Economics, 2022, issue 169, 1-12

Abstract: This article contributes to the relationship between fiscal fraud and tax collection in the Spanish economy, creating a composite suspicion tax fraud indicator (STFI) based on Google Trends searches to study the dynamics and foresee tax revenues evolution in Spain. Also, we expand knowledge in the field of fraud tax indicators, following the UNODC (2020) and OECD (2016) recommendations. To this purpose, we apply factor analysis to create the composite indicator and, next, we utilize techniques centered on fractional integration (ARFIMA) and fractional cointegration VAR (FCVAR) to assess the STFI behavior against tax collection and GDP. The outcomes indicate that the differencing parameter d is less than 1 in all the time series analyzed. The tax collection and the leading indicator have similar statistical behavior (d ?= ?0.49 and d ?= ?0.40, respectively), which implies mean reversion. On the other hand, GDP will behave similarly to the other two time series, with d ?= ?0.05, which means that the shocks will have a temporary effect on the GDP behavior, and these effects will disappear by themselves in the short term and in less time than the other two time series. FCVAR results indicate a short-lived shock duration due to the error correction term and their short-run stationary behavior. In the end, applying wavelet analysis, we determine that the composite suspicion tax fraud indicator maintains a negative association with tax collection, except in 2017 and 2018, when the high economic growth offsets the fiscal fraud.

Keywords: Fiscal fraud; Composite indicator; Google trends; Fractional integration; FCVAR model; Wavelets (search for similar items in EconPapers)
JEL-codes: C22 E37 E60 H26 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:cii:cepiie:2022-q2-169-1

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