Local corruption and income underreporting

2019 ◽  
Author(s):  
Christian Zünd
Keyword(s):  
Income Underreporting

scholarly journals Do Most U.S. Farms Really Lose Money? Taxation and Farm Income Underreporting

2019 ◽  
Vol 51 (04) ◽  
pp. 646-663 ◽  
Author(s):  
Nigel Key
Keyword(s):  
Farm Households ◽  
Farm Income ◽  
Small Scale ◽  
Department Of Agriculture ◽  
Farm Level ◽  
Substantial Discrepancy ◽  
Level Data ◽  
Large Farms ◽  
Income Underreporting

AbstractThis article explores whether income underreporting for tax purposes can explain why the majority of U.S. farmers earn low or negative net farm income. Using 10 years of U.S. Department of Agriculture farm-level data, the extent of underreporting is estimated by exploiting the fact that farm households face an incentive to underreport farm income that varies with their reported off-farm income. Results indicate that 39% of total farm income is underreported. For large farms, the results imply a substantial discrepancy between reported and earned farm income. For small-scale operations, underreporting reduces but does not eliminate the gap between farm and off-farm wages.

Income Underreporting and Tax Evasion in Italy: Estimates and Distributional Effects

2019 ◽  
Vol 66 (4) ◽  
pp. 904-930 ◽  
Author(s):  
Andrea Albarea ◽  
Michele Bernasconi ◽  
Anna Marenzi ◽  
Dino Rizzi
Keyword(s):  
Tax Evasion ◽  
Distributional Effects ◽  
Income Underreporting

Identification of Households Prone to Income Underreporting

2015 ◽  
Vol 45 (5) ◽  
pp. 599-627 ◽  
Author(s):  
Merike Kukk ◽  
Karsten Staehr
Keyword(s):  
Food Consumption ◽  
Employment Status ◽  
The Self ◽  
Identification Methods ◽  
Business Income ◽  
Household Budget ◽  
Using Data ◽  
Income Underreporting ◽  
The Way

Pissarides and Weber propose using data on income and food consumption for estimating the extent of income underreporting by the self-employed, a group seen to be prone to income underreporting. This paper is the first to investigate the importance of the way in which these households are identified in such analyses. Using household budget data from Estonia, different ways are used to identify households prone to income underreporting and to estimate the extent of the underreporting. The share of unreported income is estimated to be substantially larger when underreporting households are identified using their share of reported business income than when they are identified using their employment status. Further analysis combines the different identification methods and reveals that the employment status provides no information on underreporting when the share of business income is taken into account. The share of reported business income is the most informative indicator of underreporting.

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