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Journal articles on the topic 'Skill Biased Technological Change'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 March 2023

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1

Anagnostopoulos, Alexis, Orhan Erem Atesagaoglu, and Eva Carceles-Poveda. "Skill-biased technological change and homeownership." Journal of Economic Dynamics and Control 37, no. 12 (December 2013): 3012–33. http://dx.doi.org/10.1016/j.jedc.2013.08.007.

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2

Koch, Michael, and Marcel Smolka. "Foreign ownership and skill-biased technological change." Journal of International Economics 118 (May 2019): 84–104. http://dx.doi.org/10.1016/j.jinteco.2019.01.017.

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3

Li, Tailong, Shiyuan Pan, and Heng-fu Zou. "DIRECTED TECHNOLOGICAL CHANGE: A KNOWLEDGE-BASED MODEL." Macroeconomic Dynamics 19, no. 1 (July 24, 2013): 116–43. http://dx.doi.org/10.1017/s1365100513000308.

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In a knowledge-based growth model where skilled workers are used in innovation and production, skill-biased technological change may lower average R&D productivity via an innovation possibilities frontier effect that eliminates scale effects. We show that skill-biased technological change increases the skill premium even if the elasticity of substitution between skilled and unskilled workers is less than two. Trade between developed countries promotes skill-biased technological change, thus raising wage inequality. Trade between developed and developing countries has differing effects: it induces relatively skill-replacing technological change and lowers wage inequality in the developed country but has the opposite effects in the developing country. Finally, we show that trade can stimulate or hurt economic growth.

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4

Berman, Eli, John Bound, and Stephen Machin. "Implications of Skill-Biased Technological Change: International Evidence*." Quarterly Journal of Economics 113, no. 4 (November 1998): 1245–79. http://dx.doi.org/10.1162/003355398555892.

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5

Balleer, Almut, and Thijs van Rens. "Skill-Biased Technological Change and the Business Cycle." Review of Economics and Statistics 95, no. 4 (October 2013): 1222–37. http://dx.doi.org/10.1162/rest_a_00326.

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6

Fadinger, Harald, and Karin Mayr. "SKILL-BIASED TECHNOLOGICAL CHANGE, UNEMPLOYMENT, AND BRAIN DRAIN." Journal of the European Economic Association 12, no. 2 (January 28, 2014): 397–431. http://dx.doi.org/10.1111/jeea.12049.

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7

CONTE, Andrea, and Marco VIVARELLI. "IMPORTED SKILL-BIASED TECHNOLOGICAL CHANGE IN DEVELOPING COUNTRIES." Developing Economies 49, no. 1 (February 21, 2011): 36–65. http://dx.doi.org/10.1111/j.1746-1049.2010.00121.x.

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8

Zou, Wei, Lan Liu, and Ziyin Zhuang. "Skill Premium, Biased Technological Change and Income Differences." China & World Economy 17, no. 6 (November 13, 2009): 64–87. http://dx.doi.org/10.1111/j.1749-124x.2009.01174.x.

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9

Coelho, José. "Universal basic income and skill‑ biased technological change." Notas Económicas, no. 51 (December 11, 2020): 109–32. http://dx.doi.org/10.14195/2183-203x_51_6.

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In the last decades, income inequality has been on the rise in the U.S. The growing skill premium suggests the pivotal role of skill‑ biased technological change (SBTC) in promoting the observed increase in inequality levels. In this context, labor income tax structures have been central to the policy debate. We have developed an overlapping generations model to perform a welfare evaluation of Universal basic income (UBI) tax structures and verify how these interact with SBTC. I find that an UBI system would have improved social welfare in 2010 when compared to the existing tax system and determine that this result is primarily motivated by SBTC.

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10

Woods, Jeffrey G. "Pathways of Technological Change." International Journal of Social Ecology and Sustainable Development 5, no. 1 (January 2014): 1–11. http://dx.doi.org/10.4018/ijsesd.2014010101.

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While technological change benefits the U.S. service sector and the economy as a whole, the creation, design and production of innovations may favor highly-skilled over less-skilled workers. If skill-biased technical change creates more job vacancies for skilled, relative to less-skilled workers, less-skilled workers are at greater risk of becoming structurally unemployed. An epidemiological model is developed that describes the pathways to, and prevention of, structural unemployment (SU) of less-skilled workers. Less-skilled workers must protect themselves from being “infected” by the diffusion of skill-biased technical change in the service sector. They must choose to become “vaccinated” with “injections” of human capital to reduce the probability of contracting the “disease” of (SU) and to avoid permanently working in de-skilled jobs. By making less-skilled workers more productive, one can simultaneously improve the distribution of education and training, health and income inequality while providing the government more tax revenue.

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11

Ferreira, Ana. "Skill-Biased Technological Change and Inequality in the U.S." Notas Económicas, no. 51 (December 11, 2020): 91–107. http://dx.doi.org/10.14195/2183-203x_51_5.

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Since the 1980s, income inequality has increased markedly and has reached the highest level ever since it started being recorded in the U.S. This paper uses an overlapping generations model with incomplete markets that allows for household heterogeneity that is calibrated to match the U.S. economy with the purpose to study how skill-biased technological change (SBTC) and changes in taxation quantitatively account for the increase in inequality from 1980 to 2010. We find that SBTC and taxation decrease account for 48% of the total increase in the income Gini coefficient. In particular, we conclude that SBTC alone accounted for 42% of the overall increase in income inequality, while changes in the progressivity of the income tax schedule alone accounted for 5.7%.

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12

Røed, Knut. "Egalitarian wage policies, unemployment and skill-biased technological change." Research in Economics 59, no. 4 (December 2005): 375–87. http://dx.doi.org/10.1016/j.rie.2005.08.001.

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13

Caselli, Francesco. "Technological Revolutions." American Economic Review 89, no. 1 (March 1, 1999): 78–102. http://dx.doi.org/10.1257/aer.89.1.78.

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In skill-biased (de-skilling) technological revolutions learning investments required by new machines are greater (smaller) than those required by preexisting machines. Skill-biased (de-skilling) revolutions trigger reallocations of capital from slow- (fast- ) to fast- (slow- ) learning workers, thereby reducing the relative and absolute wages of the former. The model of skill-biased (de-skilling) revolutions provides insight into developments since the mid-1970's (in the 1910's). The empirical work documents a large increase in the interindustry dispersion of capital-labor ratios since 1975. Changes in industry capital intensity are related to the skill composition of the labor force. (JEL E23 J31 O33)

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14

Mnif, Sirine. "Skill-biased technological change: The case of the MENA region." Ekonomski anali 61, no. 210 (2016): 101–16. http://dx.doi.org/10.2298/eka1610101m.

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Our work treats the relationship between inequality and technological change. Specifically, we focus on the transmission mechanisms by which technological innovation affects inequality in access to employment. The objective of this article is to determine the effect of the diffusion of innovation on the demand for skilled and non-skilled labour. It focuses on the concept of technological bias and the role of inequality between skilled and unskilled workers. The empirical validation of this work is based on the technique of the dynamic panel. An estimate using the method of Arellano and Bond seems more relevant. There is a positive relationship between innovation and the demand for skilled labour but a negative relationship with unskilled labour. This result is confirmed in our sample of countries.

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15

Wang, Jun, Yong Hu, and Zhiming Zhang. "Skill-biased technological change and labor market polarization in China." Economic Modelling 100 (July 2021): 105507. http://dx.doi.org/10.1016/j.econmod.2021.105507.

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16

Pi, Jiancai, and Pengqing Zhang. "Skill-biased technological change and wage inequality in developing countries." International Review of Economics & Finance 56 (July 2018): 347–62. http://dx.doi.org/10.1016/j.iref.2017.11.004.

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17

Weiss, Matthias. "Skill-biased technological change: Is there hope for the unskilled?" Economics Letters 100, no. 3 (September 2008): 439–41. http://dx.doi.org/10.1016/j.econlet.2008.03.022.

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18

HARASHIMA, Taiji. "WAGE INEQUALITY AND INNOVATIVE INTELLIGENCE-BIASED TECHNOLOGICAL CHANGE." Theoretical and Practical Research in the Economic Fields 9, no. 1 (June 30, 2018): 17. http://dx.doi.org/10.14505/tpref.v9.1(17).02.

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In this paper, “innovative intelligence–biased technological change” (IIBTC) is examined as an alternative to the traditional concept of skill-biased technological change (SBTC) as a source of increases in wage inequality. The innovative intelligence of ordinary or average workers is an important element in productivity and can be heterogeneous across workers. Because technologies are heterogeneous in that they have different characteristics and are used in different situations, some technologies are “innovative intelligence-biased” and are advantageous for workers with relatively high innovative intelligence. If IIBTC prevails over a certain period of time, these workers become additionally advantaged and thereby wage inequality will increase during the period.

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19

Afonso, Oscar, and Manuela Magalhäes. "HOW POWERFUL ARE NETWORK EFFECTS? A SKILL-BIASED TECHNOLOGICAL CHANGE APPROACH." Macroeconomic Dynamics 24, no. 4 (November 14, 2018): 882–919. http://dx.doi.org/10.1017/s1365100518000524.

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Even for the standard skill-biased technological change (SBTC) literature, the generic rise in the skill premium in the face of the relative increase in skilled workers since the 1980s seems a little puzzling. We develop a general equilibrium SBTC growth model that allows the dominance of either the price channel or the market-size channel mechanism through which network spillovers affect the technological-knowledge bias and, thus, the paths of intra-country wage inequality. The proposed mechanisms can accommodate facts not explained by the earlier literature.

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20

Neto, Antonio Soares Martins, and Rafael Saulo Marques Ribeiro. "A Neo-Kaleckian model of skill-biased technological change and income distribution." Review of Keynesian Economics 7, no. 3 (July 2019): 292–307. http://dx.doi.org/10.4337/roke.2019.03.02.

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This article proposes a macrodynamic model that takes into account the joint determination of intra-working-class income distribution and knowledge-intensive technological change. Our model highlights two opposing effects of technological change at play: (i) technological innovation promotes a positive structural change and hence boosts net exports and output growth; (ii) technological change, on the other hand, disproportionately affects unskilled workers, which worsens the intra-working-class income distribution and slows down economic growth. Therefore, our model demonstrates that the net impact of technological change on capital accumulation and output growth is ambiguous and hence is a parametric question. Lastly, we show that income transfer and public investments in higher education may be of paramount importance to alleviating the unwanted effects of a contractionary wave of technological change and so promoting a sustained economic recovery.

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21

Neto, Antonio, Oscar Afonso, and Sandra T. Silva. "HOW POWERFUL ARE TRADE UNIONS? A SKILL-BIASED TECHNOLOGICAL CHANGE APPROACH." Macroeconomic Dynamics 23, no. 2 (June 9, 2017): 730–74. http://dx.doi.org/10.1017/s1365100516001346.

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This paper proposes a new theoretical framework aimed at understanding the link between technological change, skill premium, and employment. We build an endogenous growth model of directed technological change with vertical research and development (R&D) in which low-skilled workers might be organized in a trade union. This union can act as a monopoly seller of labor and decide unilaterally the low-skilled wage, or as a managerial union that bargains wage and employment with the employers' federation, i.e., firms. Our results suggest that (i) the impacts of trade unions on technological-bias and on the level of (un)employment crucially depend on their type and preferences; and (ii) trade unions can actually increase low-skilled wages and employment if they have some bargaining power and are employment-oriented. Furthermore, our framework provides some highlights to explain the relationship between wage dispersion and the deunionization process that occurred in the United Kingdom and the United States during the 1980s.

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22

Thoenig, Mathias, and Thierry Verdier. "A Theory of Defensive Skill-Biased Innovation and Globalization." American Economic Review 93, no. 3 (May 1, 2003): 709–28. http://dx.doi.org/10.1257/000282803322157052.

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This paper considers a dynamic model of innovations in which firms can endogenously bias the direction of technological change. Both in a North–North and North–South context, we show that, when globalization triggers an increased threat of technological leapfrogging or imitation, firms tend to respond to that threat by biasing the direction of their innovations towards skilled-labor-intensive technologies. We show that this process of defensive skill-biased innovations generates an increase in wage inequalities in both regions. We then discuss suggestive empirical evidence of the existence of defensive skill-biased technical change.

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23

Marouani, Mohamed A., and Björn Nilsson. "The labor market effects of skill-biased technological change in Malaysia." Economic Modelling 57 (September 2016): 55–75. http://dx.doi.org/10.1016/j.econmod.2016.04.009.

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24

Sandulli, Francesco D., Paul M. A. Baker, and José I. López-Sánchez. "Can small and medium enterprises benefit from skill-biased technological change?" Journal of Business Research 66, no. 10 (October 2013): 1976–82. http://dx.doi.org/10.1016/j.jbusres.2013.02.021.

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25

Acemoglu, Daron, Gino Gancia, and Fabrizio Zilibotti. "Offshoring and Directed Technical Change." American Economic Journal: Macroeconomics 7, no. 3 (July 1, 2015): 84–122. http://dx.doi.org/10.1257/mac.20130302.

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We study the implications of offshoring on innovation, technology, and wage inequality in a Ricardian model with directed technical change. Profit maximization determines both the extent of offshoring and the direction of technological progress. A fall in the offshoring cost induces technical change with an ambiguous factor bias. When the initial cost of offshoring is high, an increase in offshoring opportunities causes a fall in the real wages of unskilled workers in industrial countries, skill-biased technical change and rising skill premia. When the offshoring cost is sufficiently low, instead, offshoring induces technical change biased in favor of the unskilled workers. (JEL J24, J31, L24, O33)

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26

Meyer, Brett. "Financialization, Technological Change, and Trade Union Decline." Socio-Economic Review 17, no. 3 (August 8, 2017): 477–502. http://dx.doi.org/10.1093/ser/mwx022.

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Abstract Recent research finds that financialization and technological change have had a variety of negative effects on labor, including reducing low-skill workers’ wages and increasing income inequality. In this article, I examine the effect on trade unions of one type of financialization, equity market development and one type of technological change, routine-biased technological change. I argue that we should conceptualize trade union strength in two dimensions: (a) the strength of their institutional structures, such as the degree of wage bargaining coordination and the degree to which firms can deviate from collective agreements; (b) the strength of their membership. Using data for 21 OECD countries from 1970 to 2010, I find a negative effect of equity market development on unions’ institutional structures, but not on union membership. Contrarily, I find that routine-biased technological change has a negative effect on union density, but an inconsistent relationship with the strength of unions’ institutional structures.

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27

Li, Huijuan, Weihong Cai, and Wenxiu Li. "Does global value chains participation improve skill premium? Mediating role of skill-biased technological change." Economic Modelling 99 (June 2021): 105489. http://dx.doi.org/10.1016/j.econmod.2021.03.008.

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28

Moore, Mark P., and Priya Ranjan. "Globalisation vs Skill‐Biased Technological Change: Implications for Unemployment and Wage Inequality." Economic Journal 115, no. 503 (April 1, 2005): 391–422. http://dx.doi.org/10.1111/j.1468-0297.2005.00994.x.

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29

Fernandez, Roberto M. "Skill‐Biased Technological Change and Wage Inequality: Evidence from a Plant Retooling." American Journal of Sociology 107, no. 2 (September 2001): 273–320. http://dx.doi.org/10.1086/324009.

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30

Decreuse, Bruno. "Can skill-biased technological change compress unemployment rate differentials across education groups?" Journal of Population Economics 14, no. 4 (December 1, 2001): 651–67. http://dx.doi.org/10.1007/s001480000056.

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31

Ábrahám, Árpád. "Earnings Inequality and Skill-Biased Technological Change with Endogenous Choice of Education." Journal of the European Economic Association 6, no. 2-3 (April 2008): 695–704. http://dx.doi.org/10.1162/jeea.2008.6.2-3.695.

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32

Card, David, and John E. DiNardo. "Skill‐Biased Technological Change and Rising Wage Inequality: Some Problems and Puzzles." Journal of Labor Economics 20, no. 4 (October 2002): 733–83. http://dx.doi.org/10.1086/342055.

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33

Hershbein, Brad, and Lisa B. Kahn. "Do Recessions Accelerate Routine-Biased Technological Change? Evidence from Vacancy Postings." American Economic Review 108, no. 7 (July 1, 2018): 1737–72. http://dx.doi.org/10.1257/aer.20161570.

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We show that skill requirements in job vacancy postings differentially increased in MSAs that were hit hard by the Great Recession, relative to less hard-hit areas. These increases persist through at least the end of 2015 and are correlated with increases in capital investments, both at the MSA and firm levels. We also find that effects are most pronounced in routine-cognitive occupations, which exhibit relative wage growth as well. We argue that this evidence is consistent with the restructuring of production toward routine-biased technologies and the more-skilled workers that complement them, and that the Great Recession accelerated this process. (JEL E24, E32, J24, J31, J63, L23, O33)

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34

Autor, David, Claudia Goldin, and Lawrence F. Katz. "Extending the Race between Education and Technology." AEA Papers and Proceedings 110 (May 1, 2020): 347–51. http://dx.doi.org/10.1257/pandp.20201061.

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The race between education and technology provides a canonical framework that does a remarkable job of explaining US wage structure changes across the twentieth century. The framework involves secular increases in the demand for more-educated workers from skill-biased technological change, combined with variations in the supply of skills from changes in educational access. We expand the analysis backward and forward. The framework helps explain rising skill differentials in the nineteenth and twenty-first centuries but needs to be augmented to illuminate the recent convexification of education returns and implied slowdown in the growth of the relative demand for college workers.

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35

Piercy, Cameron, and Angela Gist-Mackey. "Automation Anxieties: Perceptions About Technological Automation and the Future of Pharmacy Work." Human-Machine Communication 2 (January 15, 2021): 191–208. http://dx.doi.org/10.30658/hmc.2.10.

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This study uses a sample of pharmacists and pharmacy technicians (N = 240) who differ in skill, education, and income to replicate and extend past findings about socioeconomic disparities in the perceptions of automation. Specifically, this study applies the skills-biased technical change hypothesis, an economic theory that low-skill jobs are the most likely to be affected by increased automation (Acemoglu & Restrepo, 2019), to the mental models of pharmacy workers. We formalize the hypothesis that anxiety about automation leads to perceptions that jobs will change in the future and automation will increase. We also posit anxiety about overpayment related to these outcomes. Results largely support the skillsbiased hypothesis as a mental model shared by pharmacy workers regardless of position, with few effects for overpayment anxiety.

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36

Gil, Pedro Mazeda, Susana Gabriel, and Oscar Afonso. "Is the skills mismatch important under skill-biased technological change and imperfect substitutability between immigrants and natives?" Economic Modelling 84 (January 2020): 38–54. http://dx.doi.org/10.1016/j.econmod.2019.03.006.

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37

Choi, Kang-Shik. "The Rising Returns to Education and Skill-Biased Technological Change in Korea: 1983-2000." International Economy 2004, no. 55 (2004): 340–60. http://dx.doi.org/10.5652/kokusaikeizai.2004.340.

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38

Weiss, Matthias, and Alfred Garloff. "Skill-biased technological change and endogenous benefits: the dynamics of unemployment and wage inequality." Applied Economics 43, no. 7 (March 2011): 811–21. http://dx.doi.org/10.1080/00036840802599933.

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39

Dadush, Uri. "Trade, Development, and Inequality." Current History 114, no. 775 (November 1, 2015): 298–304. http://dx.doi.org/10.1525/curh.2015.114.775.298.

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[T]he most powerful underlying force driving increased inequality is not trade by itself but skill-biased technological change—machines and methods that reduce the need for unskilled labor and boost demand for more specialized and skilled workers.

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40

Goos, Maarten, and Alan Manning. "Can a More Nuanced View of Skill Biased Technological Change Explain the Recent Changes in Wage Inequality ?" Reflets et perspectives de la vie économique XLIV, no. 2 (2005): 37. http://dx.doi.org/10.3917/rpve.442.0037.

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41

GEMKOW, S. "AN AGENT-BASED LABOR MARKET SIMULATION WITH ENDOGENOUS SKILL-DEMAND." International Journal of Modern Physics C 19, no. 03 (March 2008): 495–508. http://dx.doi.org/10.1142/s0129183108012121.

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This paper considers an agent-based labor market simulation to examine the influence of skills on wages and unemployment rates. Therefore less and highly skilled workers as well as less and highly productive vacancies are implemented. The skill distribution is exogenous whereas the distribution of the less and highly productive vacancies is endogenous. The different opportunities of the skill groups on the labor market are established by skill requirements. This means that a highly productive vacancy can only be filled by a highly skilled unemployed. Different skill distributions, which can also be interpreted as skill-biased technological change, are simulated by incrementing the skill level of highly skilled persons exogenously. This simulation also provides a microeconomic foundation of the matching function often used in theoretical approaches.

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42

BERMAN, SOMANATHAN, and TAN. "Is Skill-Biased Technological Change Here Yet? Evidence from Indian Manufacturing in the 1990's." Annales d'Économie et de Statistique, no. 79/80 (2005): 299. http://dx.doi.org/10.2307/20777579.

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43

Li, Ben. "Multinational production and choice of technologies: New evidence on skill-biased technological change from China." Economics Letters 108, no. 2 (August 2010): 181–83. http://dx.doi.org/10.1016/j.econlet.2010.04.042.

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44

Krashinsky, Harry. "The Effect of Labor Market Institutions on Salaried and Self-Employed Less-Educated Men in the 1980S." ILR Review 62, no. 1 (October 2008): 73–91. http://dx.doi.org/10.1177/001979390806200104.

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Less-educated workers exhibited negative real wage growth from the late 1970s to the early 1990s. Frequently cited to explain this pattern are such labor market trends as union decline and the falling real value of the minimum wage, but also of concern is the possible contribution of decreased demand, caused by factors such as skill-biased technological change. To investigate the relative importance of these determinants, the author, using CPS data, compares the experiences of wage-and-salary workers with those of the self-employed. Wages apparently declined little for less-educated self-employed workers, but greatly for similar wage-and-salary workers. Because self-employed workers are affected by the same demand shocks as wage-and-salary workers but are not subject to labor market institutions such as the minimum wage or labor unions, the author concludes that the main source of the observed negative real wage growth was the decline of labor market institutions, not skill-biased technological change.

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45

Sanders, Mark. "SKILL BIAS IN AN ENDOGENOUS GROWTH MODEL: EVALUATING THE CASE FOR MARKET SIZE AND ACCELERATION EFFECTS." Macroeconomic Dynamics 17, no. 4 (March 7, 2013): 802–29. http://dx.doi.org/10.1017/s1365100511000691.

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Skill-biased technical change occupied empirical economists for much of the 1990s. The empirical literature firmly established a positive correlation between technology indicators and demand shifts. In the minds of many, that has established a causal relationship. This leap of faith, however, is at odds with Hicks's conventional wisdom that endogenous technological change will be biased toward using cheap and abundant resources. In addition, if the rate of technical change is considered to be endogenous, the assumption of an exogenous bias toward skilled labor should at least be questioned. Two hypotheses explaining endogenous skill bias in technical change have been suggested in the theoretical literature: the acceleration effect and the market size effect. In this paper these are studied in a single endogenous-growth model to derive the sufficient and necessary conditions for both hypotheses. After confronting these conditions with the evidence, the paper concludes that it strongly favors the acceleration hypothesis.

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46

Shen, Chunmiao, and Jianghuai Zheng. "Does global value chains participation really promote skill-biased technological change? Theory and evidence from China." Economic Modelling 86 (March 2020): 10–18. http://dx.doi.org/10.1016/j.econmod.2019.03.009.

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47

KIERZENKOWSKI, RAFAL, and ISABELL KOSKE. "THE DRIVERS OF LABOR INCOME INEQUALITY — A LITERATURE REVIEW." Journal of International Commerce, Economics and Policy 04, no. 01 (January 27, 2013): 1350004. http://dx.doi.org/10.1142/s179399331350004x.

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Despite a general trend of increasing labor income inequality, there have been differences in the timing, intensity and even direction of these changes across OECD countries. These stylized facts have led to numerous studies about the main determinants of labor income inequality and, as a result, a significant revision of the previous consensus about the key drivers. The most researched channels include skill-biased technological change, international trade, immigration, education as well as the role of labor market policies and institutions.

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48

Bode, Eckhardt, Ingrid Ott, Stephan Brunow, and Alina Sorgner. "Worker Personality: Another Skill Bias beyond Education in the Digital Age." German Economic Review 20, no. 4 (December 1, 2019): e254-e294. http://dx.doi.org/10.1111/geer.12165.

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Abstract We present empirical evidence suggesting that technological progress in the digital age will be biased not only with respect to skills acquired through education but additionally with respect to non-cognitive skills (personality). We measure the direction of technological change by estimated future digitalization probabilities of occupations, and non-cognitive skills by the Big Five personality traits from four German worker surveys. Even though we control for education and work experience, we find that workers who are more open to experience, emotionally more stable and less agreeable will tend to be less susceptible to digitalization. We also find that future technological progress may not continue to hollow out the middle class as much as it did in the recent past. These results suggest that education and labor market policies should put more emphasis on children’s and workers’ personalities to strengthen their labor market resilience in the digital age.

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Lentini, Valeria, and Gregorio Gimenez. "Depreciation of human capital: a sectoral analysis in OECD countries." International Journal of Manpower 40, no. 7 (October 7, 2019): 1254–72. http://dx.doi.org/10.1108/ijm-07-2018-0207.

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Purpose The purpose of this paper is to investigate which sectors are more vulnerable to human capital depreciation, with an emphasis on potential differences in skills and in ICT intensities. Design/methodology/approach The authors estimate an extended Mincerian earnings equation based on Neuman and Weiss’s (1995) model using the EU-KLEMS international database for 15 sectors for the period from 1980 to 2005. The authors also test structural ruptures in earnings and human capital depreciation in the labor market per decade controlling by technological intensity. Findings Human capital depreciation ranges from 1 to 6 percent. It is mainly significant in skill-intensive sectors regardless of the sector’s technological intensity. The analysis of structural breaks shows that human capital value indeed changed from decade to decade. It even appreciated in low skill-intensive sectors in the 1980s and in the high skill-intensive during the 1990s. Appreciation though, was mainly skill-biased. Research limitations/implications Information about on-the-job-training and non-cognitive skills that can also affect human capital depreciation are not included due to lack of data. Practical implications To prevent human capital from depreciating in particular sectors and periods educational systems should provide the tools for ongoing lifelong learning at all skills levels. Education is subject to dynamic effects that should be addressed to increase the potential benefits of technological change. Originality/value First, instead of using cross-section analysis which is considered to be a pitfall in studying the depreciation of knowledge, the authors observe its dynamic on a longitudinal basis. Second, the international macro-sectoral approach goes beyond limited micro-sectoral analysis in certain countries.

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Akerman, Anders, Ingvil Gaarder, and Magne Mogstad. "The Skill Complementarity of Broadband Internet *." Quarterly Journal of Economics 130, no. 4 (July 16, 2015): 1781–824. http://dx.doi.org/10.1093/qje/qjv028.

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Abstract Does adoption of broadband internet in firms enhance labor productivity and increase wages? Is this technological change skill biased or factor neutral? We combine several Norwegian data sets to answer these questions. A public program with limited funding rolled out broadband access points and provides plausibly exogenous variation in the availability and adoption of broadband internet in firms. Our results suggest that broadband internet improves (worsens) the labor market outcomes and productivity of skilled (unskilled) workers. We explore several possible explanations for the skill complementarity of broadband internet. We find suggestive evidence that broadband adoption in firms complements skilled workers in executing nonroutine abstract tasks, and substitutes for unskilled workers in performing routine tasks. Taken together, our findings have important implications for the ongoing policy debate over government investment in broadband infrastructure to encourage productivity and wage growth.

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