Get discount factor

This function calculates the discount factor based on discount rate.

Usage

get_discount_factor(discount_rate, n_years, discount_shape = "exponential")

Arguments

discount_rate: Numeric value showing the discount rate for future years.
n_years: Numeric value referring to number of years in the future to be considered in the discounting and/or inflation. Be aware that the year 0 (without discounting/inflation, i.e. the present) is not be counted here. If a vector is entered in the argument impact, n_years does not need to be entered (length of impact = n_years + 1).
discount_shape: String referring to the assumed equation for the discount factor. By default: "exponential". Otherwise: "hyperbolic_harvey_1986" or "hyperbolic_mazur_1987".

Value

This function returns the numeric discount factor.

Details

Methodology

This function is called inside monetize().

One of the following three discount shapes can be selected:

Exponential (Frederick et al. 2002)
Hyperbolic as Harvey (1986)
Hyperbolic as Mazur (1987)

Detailed information about the methodology (including equations) is available in the package vignette. More specifically, see chapters:

Monetization

References

Frederick S, Loewenstein G, O'Donoghue T (2002). “Time Discounting and Time Preference: A Critical Review.” Journal of Economic Literature, 40(2), 351–401. doi:10.1257/002205102320161311 .

Harvey CM (1986). “Value Functions for Infinite-Period Planning.” Management Science, 32(9), 1123–1139. doi:10.1287/mnsc.32.9.1123 .

Mazur JE (1987). “An adjusting procedure for studying delayed reinforcement.” In Commons ML, Mazur JE, Nevin JA, Rachlin H (eds.), Quantitative Analyses of Behavior: Volume V. The Effect of Delay and of Intervening Events on Reinforcement Value, 55–73. Lawrence Erlbaum Associates, Hillsdale, NJ. ISBN 0-89859-800-1.

Author

Alberto Castro & Axel Luyten

Examples

get_discount_factor(
  discount_rate = 0.07,
  n_years = 5
 )
#> [1] 0.7129862