The Routine Content Of Occupations

Marcolin, Luca; Miroudot, Sébastien; Squicciarini, Mariagrazia

doi:10.1787/5jm0mq86fljg-en

Cited by 11 publications

(9 citation statements)

References 14 publications

(32 reference statements)

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“…Similar to O*NET, the PIAAC data have been used by researchers in many different ways to construct routine intensity measures. One example is Marcolin, Miroudot and Squicciarini (2016). Based on PIAAC data the authors construct an index measuring the routine content of occupations for 20 OECD countries.…”

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confidence: 99%

“…The composite index increases in its four components (low frequency and low extent are coded to take on high values), and is highest for Elementary Occupations and lowest for high-skilled occupations such as Managers and Professionals. One limitation of Marcolin, Miroudot and Squicciarini's (2016) routine measure is that it is based on four ad-hoc variables. The index is furthermore negatively correlated with the skill-level of occupations, which may suggest that it does not purely measures the routine content of occupations, but may partially captures the skill-level of occupations as well.…”

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confidence: 99%

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Measuring the Routine and Non-Routine Task Content of 427 Four-Digit ISCO-08 Occupations

Mihaylov

Tijdens

2019

SSRN Journal

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This paper develops new measures of the task content of occupations that are based on the International Standard Classification of Occupations 2008 (ISCO-08). Using a detailed set of 3,264 occupation-specific tasks, we construct five measures of non-routine analytic, non-routine interactive, routine cognitive, routine manual and non-routine manual tasks for 427 four-digit occupations. To generate these measures, first we assign each of the 3,264 tasks to one or more of the five task categories. The decision to classify tasks as routine or nonroutine, and as cognitive or manual, depends on whether the tasks can be replaced by computer-controlled technology and whether the performance of the tasks requires cognitive or manual skills. We judge the automation potential of tasks on a case-by-case basis and classify tasks to one or more of the five task categories. Because the classification of 3,264 tasks can be prone to errors, we devote substantial attention to the possibility of misclassifying tasks. We discuss three particular types of task misclassifications and provide examples of tasks that could be potentially misclassified. In line with the previous literature, we find that non-routine analytic and interactive tasks are most prevalent in the work of Managers and Professionals, routine cognitive tasks are mainly concentrated in the work of Clerical Support Workers, and routine and non-routine manual tasks are most common in the work of Plant and Machine Operators and Assemblers and Elementary Occupations, respectively. We compare the newly developed task measures with three previous studies (Acemoglu and Autor, 2011; Dengler, Matthes and Paulus, 2014; Frey and Osborne, 2017) and demonstrate that our measures are moderately to strongly positively correlated with the previous papers' indexes. Based on our task content measures, we provide an end of the envelop estimation of the number of occupations that might be at risk of automation. We find that approximately 16 percent of the 427 ISCO-08 occupations fall into the so-called high risk of automation category-they contain 70 percent or more routine tasks. The 16 percent of automatable occupations correspond roughly to 11 percent of total employment in the Netherlands.

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confidence: 99%

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confidence: 99%

Measuring the Routine and Non-Routine Task Content of 427 Four-Digit ISCO-08 Occupations

Mihaylov

Tijdens

2019

SSRN Journal

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“…Including the initial values of the dependent variable allows controlling for unobserved firm characteristics in the absence of firm fixed effects (Angrist and Pischke, 2009[29]). [32]) show that during the Asian Financial Crisis, a firm's vulnerability to financial market imperfections increased the higher its short-term debt to asset ratio. Current liabilities include loans, liabilities to credit Institutions, trade payables and any other liabilities due within one year, as well as accruals and deferred income.…”

Section: Box 1 the Response Of Firm-level Labour Shares To Relative mentioning

confidence: 99%

“…a A decline in offshoring costs triggers a decline in the capital share of output if the elasticity of substitution between capital and routine labour is higher than 1. 32 b The ratio between domestic value added and the value of domestic output declines as some routine labour tasks are offshored, thereby counteracting the effect of (a) and pushing up the capital share of value added. Without additional assumptions, the overall effect of (a) and (b) on the capital share is ambiguous.…”

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confidence: 99%

Labour share developments over the past two decades

Schwellnus¹,

Pak²,

Pionnier³

et al. 2018

OECD Economics Department Working Papers

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“…Especially in manufacturing industries, the digital transformation has in fact led to the substitution of many workers carrying out repetitive and codifiable tasks, the so called "routine" tasks (see Marcolin et al, 2016a). As digital technologies develop and get adopted in different sectors, fears about further tasks being automated also grow.…”

Section: Introductionmentioning

confidence: 99%