Are the most productive regions necessarily the most successful? Local effects of productivity growth on employment and earnings

Abstract

Economists typically celebrate productivity growth as the chief way to improve living standards. They also advocate that particular cities and regions strive to be as productive as possible to attract business and increase employment. However, while productivity growth may reduce costs, improve quality, or lead to innovation and new products, if demand is insufficiently elastic, labor demand may decrease, reducing employment in that location. In other words, places experiencing the most productivity growth may face some unintended consequences, such as weakening of local labor markets. In this paper, we study countylevel effects of productivity growth and productivity levels in the computer and electronic product manufacturing industry (NAICS334), the goods sector (excluding NAICS334) and in the services sector on total employment growth, employment growth in major sectors, income and earnings growth. The results suggest that productivity growth generally suppresses job growth but has boosting effects on earnings and, to a lesser degree, on percapita income, although there is considerable variation across geographies and specific outcomes.

Propulsive forces of economic growth in Slovakia: the inference from the input-output table data

“…Listing the other results, Partridge et al (2021) shown on the negative link between productivity growth and employment growth. On the sample of industries, he has found a weak negative link between productivity growth and employment growth in the case of the computer industry, however, most of the other employmentproductivity results were insignificant.…”

Contradictory effects of technological change across developed countries

“…As a consequence, differences in product market conditions and industry composition across countries can explain differences in labor market performance of these countries. To illustrate this, we introduce a simple macro model following Appelbaum and Schettkat (2001) (see also Möller, 2001; Partridge et al, 2021), which is similar to Bessen's (2019) and is based on three equations: $$$$ {\pi}_j=\frac{Q_j}{L_j}, $$$$ $$$$ {P}_j=\frac{z_j{W}_j}{\pi_j}, $$$$ $$$$ {Q}_j=f\left({P}_j,y\right),\mathrm{with}\ \partial {Q}_j/\partial {P}_j<0,\kern0.5em \partial {Q}_j/\partial y>0, $$$$ where $$$ {\pi}_j $$$ is labor productivity (in industry j ) given by production quantity $$$ {Q}_j $$$ divided by the level of employment $$$ {L}_j $$$. Equation () is a price‐setting function based on a mark‐up calculation.…”

“…Calculating growth rates and rearranging the equations lead to expressions using elasticities (the price elasticity $$$ {\varepsilon}_j=\frac{P_j}{Q_j}\frac{\partial\ {Q}_j}{\partial\ {P}_j} $$$ and $$$ =\frac{y}{Q}\frac{\partial {Q}_j}{\partial y} $$$, the income elasticity). Inserting dynamic versions of Equations () and () into Equation () leads to (see especially Partridge et al, 2021): $$$$ {\hat{L}}_j={\eta}_j\cdot \hat{y}-\left({\varepsilon}_j+1\right)\cdot {\hat{\pi}}_j+{\varepsilon}_j\cdot {\hat{W}}_j. $$$$ …”

“…Frey and Osborne (2017) focus only on the expected substitution of specific categories of workers by (computer) technology and discuss no compensating effects for the US. Autor and Salomons (2018) for 19 developed countries, Partridge et al (2021) for the US, Acemoglu and Restrepo (2020) also for the US and Dauth et al (2017) for Germany analyze the net effects either of productivity changes or of special technologies, such as industrial robots. All these studies do not compare the employment effects for different countries.…”

“…As a consequence, differences in product market conditions and industry composition across countries can explain differences in labor market performance of these countries. To illustrate this, we introduce a simple macro model following Appelbaum and Schettkat (2001) (see also Möller, 2001;Partridge et al, 2021), which is similar to Bessen's (2019) and is based on three equations:…”