The Effect of Working from Home on the Agglomeration Economies of Cities: Evidence from Advertised Wages

Liu, Sitian and Su, Yichen (2022): The Effect of Working from Home on the Agglomeration Economies of Cities: Evidence from Advertised Wages.

Abstract

We analyze the effect of working from home on the agglomeration economies of large cities and the aggregate productivity implications of such effect. Using advertised wages from job ads, we show that occupations with the highest work-from-home adoption during the COVID-19 pandemic saw a strong decrease in the urban wage premium. The decline in the urban wage premium is accompanied by an exodus of employment (based on firms' locations) from large cities to small cities. In contrast, occupations with low or moderate levels of work-from-home adoption saw little overall reduction in the urban wage premium. The empirical evidence in our paper points to weakened agglomeration economies in large cities among professions with the highest prevalence of working from home. A decomposition exercise reveals that a sizable portion of the decline in the urban wage premium is driven by the decline in the urban wage premium of relationship-building skills, suggesting the decreased agglomeration effect in large cities is at least partially a result of reduced occurrence of interactive activities.

• Item Type: MPRA Paper
• Language: English
• Keywords: Agglomeration; Productivity; Spillover; Urban Wage Premium; Working from Home; Remote; Virtual; WFH; Wages; Job Posting; COVID-19; Pandemic
• Subjects: J - Labor and Demographic Economics > J2 - Demand and Supply of Labor > J24 - Human Capital ; Skills ; Occupational Choice ; Labor Productivity; J - Labor and Demographic Economics > J3 - Wages, Compensation, and Labor Costs > J31 - Wage Level and Structure ; Wage Differentials; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R1 - General Regional Economics > R12 - Size and Spatial Distributions of Regional Economic Activity; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R2 - Household Analysis > R23 - Regional Migration ; Regional Labor Markets ; Population ; Neighborhood Characteristics

References

Akcigit, U., Caicedo, S., Miguelez, E., Stantcheva, S., and Sterzi, V. (2018). Dancing with the stars: Innovation through interactions. NBER Working Paper No.24466.

Althoff, L., Eckert, F., Ganapati, S., and Walsh, C. (2022). The geography of remote work. Regional Science and Urban Economics, 93(103770).

Barrero, J. M., Bloom, N., and Davis, S. (2021). Why working from home will stick. Working Paper.

Bartik, A., Cullen, Z., Glaeser, E., Luca, M., and Stanton, C. (2020). What jobs are being done at home during the COVID-19 crisis? Evidence from firm-level surveys. Harvard Business School Working Paper, 20:138.

Baum-Snow, N., Gendron-Carrier, N., and Pavan, R. (2021). Local productivity spillovers. Working Paper.

Baum-Snow, N. and Pavan, R. (2012). Understanding the city size wage gap. Review of Economic Studies, 79(1):88–127.

Bick, A., Blandin, A., and Mertens, K. (2022). Work from home after the COVID-19 outbreak. Federal Reserve Bank of Dallas Working Paper No. 2017.

Bleakley, H. and Lin, J. (2012). Thick-market effects and churning in the labor market: Evidence from us cities. Journal of Urban Economics, 72(2-3):87–103.

Bloom, N., Liang, J., Roberts, J., and Ying, Z. J. (2015). Does working from home work? evidence from a chinese experiment. Quarterly Journal of Economics, 130(1):165–218.

Brynjolfsson, Erik amd Horton, J., Ozimek, A., Rock, D., Sharma, G., and TuYe, H.-Y. (2020). Covid-19 and remote work: An early look at us data. NBER Working Paper, 27344.

Carnevale, A., Jayasundera, T., and Repnikov, D. (2014). Understanding online job ads data. Georgetown University, Center on Education and the Workforce, Technical Report (April).

Charlot, S. and Duranton, G. (2004). Communication externalities in cities. Journal of Urban Economics, 56(3):581–613.

Chen, J. and Chen, Z. (2008). Extended bayesian information criteria for model selection with large model spaces. Biometrika, 95(3):759–771.

Ciccone, A. and Hall, R. (1996). Productivity and the density of economic activity. American Economic Review, 86(1):54–70.

Combes, P.-P., Duranton, G., and Gobillon, L. (2008). Spatial wage disparities: Sorting matters! Journal of Urban Economics, 63(2):723–742.

Davis, D. and Dingel, J. (2019). A spatial knowledge economy. American Economic Review, 109(1):153–170.

Davis, M., Ghent, A., and Gregory, J. (2021). The work-from-home technology boon and its consequences. NBER Working Paper, 28461.

D’Costa, S. and Overman, H. (2014). The urban wage growth premium: Sorting or learning? Regional Science and Urban Economics, 48:168–179.

De La Roca, J. and Puga, D. (2017). Learning by working in big cities. Review of Economic Studies, 84(1):106–142.

Delventhal, M. and Parkhomenko, A. (2022). Spatial implications of telecommuting. Working Paper.

Diamond, R. (2016). The determinants and welfare implications of us workers’ diverging location choices by skill: 1980-2000. American Economic Review, 106(3):479–524.

Dingel, J. and Neiman, B. (2020). How many jobs can be done at home? Journal of Public Economics, 189.

Duranton, G. and Puga, D. (2004). Micro-foundations of urban agglomeration economies. Handbook of Regional and Urban Economics, 4(48):2063–2117.

Eckert, F., Hejlesen, M., and Walsh, C. (2022). The return to big city experience: Evidence from refugees in denmark. Journal of Urban Economics, (103454).

Ellison, G., Glaeser, E., and Kerr, W. (2010). What causes industry agglomeration? evidence from coagglomeration patterns. American Economic Review, 100(3):1195–1213.

Flood, S., King, M., Rodgers, R., Ruggles, S., Warren, R., and Westberry, M. (2022). IPUMS CPS: Version 9.0 [dataset]. Minneapolis, MN: IPUMS.

Gaubert, C. (2018). Firm sorting and agglomeration. American Economic Review, 108(11):3117–3153.

Gelbach, J. (2016). When do covariates matter? and which ones, and how much? Journal of Labor Economics, 34(2):509–543.

Glaeser, E. (1999). Learning in cities. Journal of Urban Economics, 46(2):254–277.

Glaeser, E. and Mare, D. (2001). Cities and skills. Journal of Labor Economics, 19(2):316–342.

Gupta, A., Mittal, V., Peeters, J., and Van Nieuwerburgh, S. (2021). Flattening the curve: Pandemic-induced revaluation of urban real estate. Journal of Financial Economics, Forthcoming.

Hazell, J., Patterson, C., Sarsons, H., and Taska, B. (2022). National wage setting. Working Paper.

Hofferth, S., Flood, S., Sobek, M., and Backman, D. (2020). American time use survey data extract builder: Version 2.8 [dataset]. college park, md: University of maryland and minneapolis, mn.

Jaffe, A., Trajtenberg, M., and Henderson, R. (2003). Geographic localization of knowledge spillovers as evidenced by patent citations. Quarterly Journal of Economics, 108(3):1–28.

Jarosch, G., Oberfield, E., and Rossi-Hansberg, E. (2021). “learning from coworkers. Econometrica, 89(2):647–676.

Li, W. and Su, Y. (2022). The great reshuffle: Residential sorting during the covid-19 pandemic and its welfare implications. Working Paper.

Liu, S. and Su, Y. (2021). The impact of the covid-19 pandemic on the demand for density: Evidence from the u.s. housing market. Economics Letters, 207(110010).

Martellini, P. (2022). Local labor markets and aggregate productivity. Working Paper.

Moretti, E. (2013). Real wage inequality. American Economic Journal: Applied Economics, 5(1):65–103.

Ramani, A. and Bloom, N. (2021). The donut effect: How covid-19 shapes real estate. SIEPR Policy Brief.

Rosenthal, S. and Strange, W. (2003). Geography, industrial organization, and agglomeration. Review of Economics and Statistics, 85(2):377–393.

Ruggles, S., Flood, S., Goeken, R., Schouweiler, M., and Sobek, M. (2022). IPUMS USA: Version 12.0 [dataset]. Minneapolis, MN: IPUMS.

Wheaton, W. and Lewis, M. (2002). Urban wages and labor market agglomeration. Journal of Urban Economics, 51(3):542–562.