This paper uses a unique and recently available dataset that contains detailed information on firms from around the world to investigate factors that affect under-reporting behaviour by firms. The empirical strategy employed exploits the nature of the dependent variable, which is interval coded, and uses interval regression which provides an asymptotically more efficient estimator than the ordered probit, provided that the classical linear model assumptions hold. These assumptions are investigated using standard diagnostic tests that have been modified for the interval regression model. Evidence is presented that shows that firms in all regions around the world engage in under-reporting. Regression results indicate that government corruption has the single largest causal effect on under-reporting, resulting in the percentage of sales not reported to the tax authority being 53.4 percent higher. Taxes have the second single largest causal effect on under-reporting, resulting in the percentage of sales not reported to the tax authority being 20.2 percent higher. Access to financing, organized crime, political instability and the fairness of the legal system were found to have no effect on under-reporting. It is also found that there is a significant correlation between under-reporting and the legal organization of the business, size, age, ownership, competition and audit controls.
Using new time-series data for the size of the Canadian underground economy, the relationship between unreported and measured GDP in that country is examined. Granger causality tests are conducted, with a proper allowance for the non-stationarity of the data. It is found that there is clear evidence of such causality from measured GDP to 'hidden' output, but only very mild evidence of Granger causality in the reverse direction. This result supports similar evidence for New Zealand reported by the first author, and has several interesting policy implications.
There is considerable interest in measuring the underground economy using microeconomic data. One such method estimates income under-reporting by households by assuming a known, parametric form of the Engel curve and making the further parametric assumption that households under-report their income by a constant fraction, independent of income. This paper proposes a nonparametric approach which avoids functional form restrictions and enables the reporting function to vary across income levels and household characteristics. I illustrate by estimating the effect of the Canadian Goods and Services Tax on income under-reporting.
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Congestion charges pose a policy dilemma due to the balance that must be made between the management of a quasi public good along with the correction of negative externalities against the needs of economic, demographic, and urban growth along with citizen acceptance. The literature provides detailed rationales for congestion charges but minimal consideration on how to implement such charges once the decision to proceed has been made. The purpose of this article is to expose some of the technical and administrative issues that come with enacting and implementing congestion charges. The Halifax Peninsula is used as a case study to illuminate the topic. Drawing on this case, we spell out eleven ex ante implementation criteria that can be used to assess implementation considerations in any given congestion charge context. In so doing, we argue that context-specific factors must also be recognized and accommodated by policy and decision makers if congestion charge policy is to present a feasible, and palatable, choice.
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