Future orientation and taxes: Evidence from big data

Petutschnig, Matthias

doi:10.1016/j.intaccaudtax.2017.03.003

Cited by 18 publications

(15 citation statements)

References 47 publications

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“…All the results show a significant correlation (Pearson correlation coefficients were 0.53, 0.64, 0.78, respectively) (Preis et al, 2012). Other scholars investigated the relation between FOI and suicide statistics (Lee et al, 2016), tax-related indicators (Petutschnig, 2017) and welfare-related indicators (Shepard and Turner, 2019).…”

Section: Extended Abstractmentioning

confidence: 83%

“…Portföy çeşitlendirmesine internet aramaları tabanlı bir yaklaşım getiren çalışmada ise, hisse senedinin yüksek hacimlerde sorgulanması, hisse senedinin riskli olduğu ile ilişkilendirilmiştir. Bu sebeple, internet arama hacimlerinde popüler olan hisse senetlerine daha düşük portföy ağırlıkları atanarak, portföyün toplam riskinin azaltılması üzerine kurulu bir yaklaşım önerilmiştir (Kristoufek, 2013b (Lee vd., 2016), vergi (Petutschnig, 2017) ve refah seviyesi (Shepard ve Turner, 2019)…”

Section: Introductionunclassified

“…Bulgular, sermaye kazancının, temettü ve katma değer vergilerinin, gelecek yönelimini olumsuz yönde etkilediğini göstermiştir. Kurumlar vergisi ve kişisel gelir vergilerinin ise gelecek yönelimini olumlu yönde etkileyebileceği saptanmıştır(Petutschnig, 2017). ve Turner (2019) ise çalışmalarında, FOI ve refah (well-being) seviyesinin ilişkili olup olmadığını test etmek üzere, internet penetrasyonu %25'in üzerinde olan ülkeleri ele alarak, 64 ülke için 2013, 2014 ve 2015 yıllarına ait FOI'yi hesaplamıştır.…”

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YENİ BİR VERİ KAYNAĞI OLARAK GOOGLE TRENDS: GELECEK YÖNELİMİ ENDEKSİ İLE İLGİLİ BİR DEĞERLENDİRME / Google Trends As A New Data Source: An Evaluation Of The Future Orientation Index

Ayan

2020

Uluslararası Ekonomi İşletme Ve Politika Dergisi

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Web 2.0 ile birlikte oluşan etkileşimli ortam, yeni veri kaynaklarını beraberinde getirmiştir. Bu yeni veri kaynaklarından biri, Google arama motorunda yapılan sorgulara erişimi sağlayan Google Trends platformudur. Bu çalışmada, internet kullanıcılarının gelecek yıl hakkında geçmiş yıldan daha fazla bilgi arama derecesini ölçme amacı ile geliştirilen Gelecek Yönelimi Endeksi ele alınmıştır. Endeksi geliştiren araştırmacılar, bu endeks ile ekonomik veya sosyal göstergeler arasında saptanan anlamlı korelasyonları, ülkelerin gelişmişlik düzeyleri ile yapılan Google sorguları arasındaki olası bir ilişki şeklinde yorumlamıştır.

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Section: Extended Abstractmentioning

confidence: 83%

Section: Introductionunclassified

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YENİ BİR VERİ KAYNAĞI OLARAK GOOGLE TRENDS: GELECEK YÖNELİMİ ENDEKSİ İLE İLGİLİ BİR DEĞERLENDİRME / Google Trends As A New Data Source: An Evaluation Of The Future Orientation Index

Ayan

2020

Uluslararası Ekonomi İşletme Ve Politika Dergisi

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“…Taxes have been cited as a potential boost or deterrent to entrepreneurship at least since the 1940s (e.g., [2]). Therefore, an existing literature on the relationship between taxes and entrepreneurship is unclear [3]. According to Clingingsmith and Shane [4], while the deterrent effects are associated with risk taking explanation (i.e., the asymmetric taxation of profits and losses), the boosting effects are associated with the tax avoidance story.…”

Section: Introductionmentioning

confidence: 99%

Tax Progressivity and Entrepreneurial Dynamics

Nadirov

Dehning

2020

Sustainability

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This study examines how tax progressivity affects entrepreneurial dynamics in 18 countries. The results show that increased downside progressivity has a positive influence on the transition rate from nascent entrepreneurship to established business ownership. In addition, only downside progressivity calculated using marginal tax rates is related to the transition ratio, implying that it is marginal tax rates, and not average tax rates, that are used in the entrepreneurial decision-making process. This paper contributes to our understanding of entrepreneurial dynamics and the effect of tax progressivity on the transition from nascent entrepreneurship to established business ownership.

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“…Its accuracy and validity in forecastings [33][34][35][36][37], predictions [38,39], nowcasting [40], and in examining human behavior in general has been highlighted. Economics and finance are among the main fields where online search traffic data from Google have been employed to analyze and predict behavioral variations, mainly for examining behavioral changes in stock market related issues [15,[41][42][43][44][45][46][47], currencies [48,49], in general consumption [50] and sales [51][52][53], in general applications for advertising, marketing, and management [54,55], or even examining the effect of taxation in the public's view of the future [56].…”

mentioning

confidence: 99%

Predictability analysis of the Pound’s Brexit exchange rates based on Google Trends data

2020

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During the last decade, the use of online search traffic data is becoming popular in examining, analyzing, and predicting human behavior, with Google Trends being a popular tool in monitoring and analyzing the users' online search patterns in several research areas, like health, medicine, politics, economics, and finance. Towards the direction of exploring the Sterling Pound’s predictability, we employ Google Trends data from the last 5 years (March 1st, 2015 to February 29th, 2020) and perform predictability analysis on the Pound’s exchange rates to Euro and Dollar. The period selected includes the 2016 UK referendum as well as the actual Brexit day (January 31st, 2020), with the analysis aiming at analyzing the Pound’s relationships with Google query data on Pound-related keywords and topics. A quantile dependence method is employed, i.e., cross-quantilograms, to test for directional predictability from Google Trends data to the Pound’s exchange rates for lags from zero to 30 (in weeks). The results indicate that statistically significant quantile dependencies exist between Google query data and the Pound’s exchange rates, which point to the direction of one of the main implications in this field, that is to examine whether the movements in one economic variable can cause reactions in other economic variables.

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Future orientation and taxes: Evidence from big data

Cited by 18 publications

References 47 publications

YENİ BİR VERİ KAYNAĞI OLARAK GOOGLE TRENDS: GELECEK YÖNELİMİ ENDEKSİ İLE İLGİLİ BİR DEĞERLENDİRME / Google Trends As A New Data Source: An Evaluation Of The Future Orientation Index

YENİ BİR VERİ KAYNAĞI OLARAK GOOGLE TRENDS: GELECEK YÖNELİMİ ENDEKSİ İLE İLGİLİ BİR DEĞERLENDİRME / Google Trends As A New Data Source: An Evaluation Of The Future Orientation Index

Tax Progressivity and Entrepreneurial Dynamics

Predictability analysis of the Pound’s Brexit exchange rates based on Google Trends data

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