The Role of Wealth Transformations: An Application to Estimating the Effect of Tax Incentives on Saving
By Karen Pence. 2006
370 citations recorded by the source corpus.
Subfields: Accounting, Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/a0d340a767bbbfd2720bd3276a7d74ee12ce914c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Accounting
- Anthony J. Nyberg
- B. Gerhart
- I. Fulmer
- Dimitris Georgarakos
- Arne Henningsen
- G. B. Aïhounton
- Giacomo Pasini
- Marc F. Bellemare
In Economics and Econometrics
- Dimitris Georgarakos
- Arne Henningsen
- G. B. Aïhounton
- Giacomo Pasini
- Marc F. Bellemare
- Michael Haliassos
- Mason A. Carpenter
- Anthony J. Nyberg
Citations in the corpus
- Agency Theory Revisited: CEO Return and Shareholder Interest Alignment (2010, methodology): “As does a logarithmic transformation, an IHS transformation provides a means of estimating a percentage change interpretation (Pence, 2006).”
- A two-step estimator for a spatial lag model of counts: Theory, small sample performance and an application☆ (2010, neutral): “Pence (2006) and El-Osta et al. (2007) provide recent applications.”
- Intergenerational Wealth Mobility and the Role of Inheritance: Evidence from Multiple Generations (2018, neutral): “An alternative that is sometimes used instead of logarithms is the inverse hyperbolic sine (IHS) transformation, which can be used in the presence of zero and negative observations (Pence, 2006).”
- Household Debt and Social Interactions (2012, methodology): “The advantage of this near-logarithmic transformation is that it is defined for zero and negative values (see also Pence, 2006).”
- Units of measurement and the inverse hyperbolic sine transformation (2020, methodology): “However, we do not consider this to be a distributional assumption. zero and even negative values without any arbitrary manipulations of the original variable and it allows a similar interpretation of the regression results as the log transformation (see, e.g., Carroll et al., 2003; Carboni, 2012; R”
- Elasticities and the Inverse Hyperbolic Sine Transformation (2019, positive): “(ii) it allows retaining zero-valued (and even negative-valued) observations (Burbidge, Magee and Robb, 1988; MacKinnon and Magee, 1990; Pence, 2006).1 For a random variable x, taking the inverse hyperbolic sine transformation yields a new variable x̃, such that x̃ = arcsinh(x)= ln(x +√x2 +1).”