University of Leicester
Browse
- No file added yet -

Amenities and Wage Premiums: the Role of Services

Download (4.2 MB)
journal contribution
posted on 2022-11-22, 10:31 authored by Chung Yi Tse, Kangoh Lee

This paper studies amenities and wage premiums in a service economy where individuals with different skills choose cities with different amenities and choose occupations to produce different services, namely the high-quality service or the low-quality service. Workers with higher skills have stronger preferences for amenity and choose the high-amenity city. Within each city, workers with higher skills choose to produce the high-quality service, and workers with lower skills choose to produce the other. Workers with higher skills are willing to sacrifice more wages to live in the high-amenity city. As a result, the price of the high-quality service, relative to the price of the low-quality service, is lower in the high-amenity city, because the wage equals the price times skill or productivity. The wage of a worker with a given skill in the high-quality service sector, relative to the wage of a worker in the low-quality service sector, or the wage premium, is thus lower in the high-amenity city. A quantitative analysis shows that the wage premium is about 3% lower when amenity is 10% higher. However, the average wage of high-quality service workers over that of low-quality service workers may be lower or higher in the high-amenity city due to skill concentration in the high-amenity city.

History

Author affiliation

School of Business, University of Leicester

Version

  • AM (Accepted Manuscript)

Published in

The Annals of Regional Science: international journal of urban, regional and environmental research and policy

Volume

68

Publisher

Springer Verlag

issn

0570-1864

Copyright date

2022

Available date

2023-11-13

Language

en

Usage metrics

    University of Leicester Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC