6533b821fe1ef96bd127bebb
RESEARCH PRODUCT
Productivity analysis of Latvian companies using ORBIS database
Olegs KrasnopjorovsKonstantins Kovalovssubject
JEL: C - Mathematical and Quantitative Methods/C.C3 - Multiple or Simultaneous Equation Models • Multiple Variables/C.C3.C31 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions • Social Interaction Modelsproductivitycompany agemicro dataJEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R3 - Real Estate Markets Spatial Production Analysis and Firm Location/R.R3.R32 - Other Spatial Production and Pricing Analysiscompany size[SHS.ECO]Humanities and Social Sciences/Economics and FinanceORBIScompany location:SOCIAL SCIENCES [Research Subject Categories]JEL: L - Industrial Organization/L.L6 - Industry Studies: Manufacturing/L.L6.L60 - Generaldescription
International audience; This research study uses ORBIS microdata at the company level to analyse productivity of 167 thousand economically active Latvian companies over 2011-2018. The aim of the study is twofold-to find factors consistently associated with productivity at the company level; and to recommend possible criteria for companies to receive a state support (from the view of enhancing aggregate productivity in the long term). Our research results show that productivity of Latvian companies is positively related to their size, age, as well as location closer to Riga and other big cities. However, there is a substantial within-group variation in productivity between companies. Multivariate regression results show that location, size, age and economic sector explain only up to 19% of productivity differences between companies. In addition, distribution of companies by productivity has a positive skewness. This suggests that there is a small number of highly productive companies, while for most companies the productivity is lower than the average. Finally, we propose three criteria for companies to receive a state support: (1) high relative productivity given size, age, sector and location; (2) belonging to a group of companies with a higher probability of survival; (3) carrying out a significant part of economic activity in areas with a high unemployment rate.
year | journal | country | edition | language |
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2021-05-14 |