O33 – Regional Science Inquiry

Lena MALEŠEVIĆ PEROVIĆ

Full professor, University of Split, Faculty of Economics, Business and Tourism, Split, Croatia and CERGE-EI Teaching Fellow

lena@efst.hr

Abstract

The main aim of this paper is to investigate macroeconomic effects of teleworking during the COVID-19 pandemic, using an atypical approach. We apply stochastic frontier analysis to a Cobb-Douglas production function broadened with teleworkability variable, and analyse the level of (in)efficiency of EU27 countries in producing their GDPs. We find that increasing the percentage of jobs that can be done at home by 1 percentage point reduces the level of technical inefficiency by 3.5%. Additionally, we use a unique e-survey conducted in April and May of 2020, which provides the data on the share of people who started working from home as a results of a COVID-19 situation, and combine it with the teleworkability variable. Overall, our findings suggest that more developed EU countries have a higher share of teleworkable jobs, which in turn reduces their inefficiencies, and furthermore results in more people beginning to work from home in the pandemic.

Keywords: teleworking, production function, stochastic frontier analysis, EU, COVID-19

JEL classification: C21, O4, O33, O52

pp. 33-42

Shicong XU

PhD candidate, Department of Agricultural, Environmental and Development Economics, Suite 250 Ag. Administration Building, 2120 Fyffe Rd, The Ohio State University, Columbus OH 43210, USA

Shicong.x@gmail.com

Abdoul G. SAM

Professor, Department of Agricultural, Environmental and Development Economics, Suite 250 Ag. Administration Building, 2120 Fyffe Rd, The Ohio State University, Columbus OH 43210, USA, Corresponding author

Sam.7@osu.edu

Abstract

China’s rise to the top echelons of the world’s economies was accompanied by an expeditious growth in domestic patent applications. Not surprisingly, this phenomenon has spawned a growing literature trying to sort out the determinants of patented research in China. However, mostly due to data limitations, many of the papers on this topic use aggregated innovation data at the industry, prefecture, or province levels. In this paper, we examine the empirical validity of important theories of knowledge spillover in the context of China at a micro-level, using a firm-level panel dataset comprised of publicly traded companies listed in the Shanghai and ShenZhen Stock Exchanges during the 2006-2010 period. Our study sheds light on whether locating near innovative firms increases patenting activity in general, regardless of the industry membership of these neighboring firms. We also explore how industry makeup, measured by the number of firms in the same or different industries, affects firm-level patenting activity. Our econometric results show that the number of patent applications by firms in close geographic proximity of a firm of interest has a significant and positive impact on that firm’s successful patent applications. In addition, we find that proximity to firms in the same industry reduces innovation while locating near firms from different industries stimulates innovation.

Keywords: patents, knowledge diffusion, MAR spillover, Jacobs spillover, China

JEL classification: O31, O32, O33, R12, D22

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