Taylor & Francis Group
Browse
TEXT
AEI_L0_NORM.m (3.16 kB)
TEXT
AEI_L0_NORM.m (3.16 kB)
TEXT
ECPF.m (9.39 kB)
TEXT
FKM.m (7.37 kB)
TEXT
HEI_L0_NORM.m (1.91 kB)
TEXT
HEI_L0_NORM.m (1.91 kB)
TEXT
HEV_L0.m (1.9 kB)
TEXT
HEV_L0.m (1.9 kB)
TEXT
POWER.m (1.7 kB)
TEXT
POWER.m (1.7 kB)
TEXT
POWER_PS.m (0.97 kB)
TEXT
POWER_PS.m (0.97 kB)
DOCUMENT
README.pdf (464.07 kB)
TEXT
VEV.m (3.12 kB)
TEXT
VEV.m (3.12 kB)
TEXT
VEV_L0.m (3.17 kB)
TEXT
VEV_L0.m (3.17 kB)
TEXT
emax_AEI.m (0.99 kB)
TEXT
emax_AEI.m (0.99 kB)
TEXT
emax_HEI.m (0.98 kB)
1/0
31 files

Homothetic Efficiency: Theory and Applications

Version 2 2019-04-02, 07:56
Version 1 2017-04-27, 21:22
dataset
posted on 2017-04-27, 21:22 authored by Jan Heufer, Per Hjertstrand

We provide a nonparametric revealed preference approach to demand analysis based on homothetic efficiency. Homotheticity is widely assumed (often implicitly) because it is a convenient and often useful restriction. However, this assumption is rarely tested, and data rarely satisfy testable conditions. To overcome this, we provide a way to estimate homothetic efficiency of consumption choices. The method provides considerably higher discriminatory power against random behavior than the commonly used Afriat efficiency. We use experimental and household survey data to illustrate how our approach is useful for different empirical applications and can provide greater predictive success.

History