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Ioana Marinescu - One of the best experts on this subject based on the ideXlab platform.
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the general equilibrium impacts of unemployment insurance evidence from a large online Job board
Journal of Public Economics, 2017Co-Authors: Ioana MarinescuAbstract:Abstract During the Great Recession, U.S. unemployment benefits were extended by up to 73 weeks. Theory predicts that extensions increase unemployment by discouraging Job search, a partial equilibrium effect. Using data from the large Job board CareerBuilder.com , I find that a 10% increase in benefit duration decreased state-level Job applications by 1%, but had no robust effect on Job Vacancies. Job seekers thus faced reduced competition for Jobs, a general equilibrium effect. Calibration implies that the general equilibrium effect reduces the impact of unemployment insurance on unemployment by 39%.
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the general equilibrium impacts of unemployment insurance evidence from a large online Job board
Research Papers in Economics, 2016Co-Authors: Ioana MarinescuAbstract:During the Great Recession, U.S. unemployment benefits were extended by up to 73 weeks. Theory predicts that extensions increase unemployment by discouraging Job search, a partial equilibrium effect. Using data from the large Job board CareerBuilder.com, this paper finds that a 10% increase in benefit duration decreased state-level Job applications by 1%, but had no robust effect on Job Vacancies. Job seekers thus faced reduced competition for Jobs, a general equilibrium effect. Calibration implies that the general equilibrium effect reduces the impact of unemployment insurance on unemployment by 40%: increasing benefit duration by 10% increases unemployment by only 0.6% in equilibrium. [Working Paper 22447]
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the general equilibrium impacts of unemployment insurance evidence from a large online Job board
Social Science Research Network, 2016Co-Authors: Ioana MarinescuAbstract:During the Great Recession, U.S. unemployment benefits were extended by up to 73 weeks. Theory predicts that extensions increase unemployment by discouraging Job search, a partial equilibrium effect. Using data from the large Job board CareerBuilder.com, I find that a 10% increase in benefit duration decreased state-level Job applications by 1%, but had no robust effect on Job Vacancies. Job seekers thus faced reduced competition for Jobs, a general equilibrium effect. Calibration implies that the general equilibrium effect reduces the impact of unemployment insurance on unemployment by 40%: increasing benefit duration by 10% increases unemployment by only 0.6% in equilibrium.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
James Thurgood - One of the best experts on this subject based on the ideXlab platform.
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is the uk s productivity puzzle mostly driven by occupational mismatch an analysis using big data on Job Vacancies
Labour Economics, 2021Co-Authors: David Copple, Arthur Turrell, Jyldyz Djumalieva, Bradley Speigner, James ThurgoodAbstract:Abstract Uncertainty still remains as to the cause of the UK’s dramatic productivity puzzle that began during the Great Financial Crisis. Occupational mismatch has been implicated as driving up to two thirds of it. However, obtaining the high quality time series data for Vacancies by Job occupation that are required to measure occupational mismatch is a significant challenge. We confront this issue by using a weighted dataset of 15 million Job adverts posted online that cover most of the post-crisis period and that enable us to test whether occupational mismatch still stands up as an explanation for the UK productivity puzzle. We find little evidence that it does, mainly because, relative to the data used in similar analysis by Patterson et al. (2016), our vacancy data imply greater heterogeneity in occupational matching frictions, a key determinant of the optimal distribution of labour across Job types.
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using online Job Vacancies to understand the uk labour market from the bottom up
Social Science Research Network, 2018Co-Authors: James Thurgood, Arthur Turrell, David Copple, Jyldyz Djumalieva, Bradley SpeignerAbstract:What type of disaggregation should be used to analyse heterogeneous labour markets? How granular should that disaggregation be? Economic theory does not currently tell us; perhaps data can. Analyses typically split labour markets according to top-down classification schema such as sector or occupation. But these may be slow-moving or inaccurate relative to the structure of the labour market as perceived by firms and workers. Using a dataset of 15 million Job adverts posted online between 2008 and 2016, we create an empirically driven, ‘bottom-up’ segmentation of the labour market which cuts across wage, sector, and occupation. Our segmentation is based upon applying machine learning techniques to the demand expressed in the text of Job descriptions. This segmentation automatically identifies traditional Job roles but also surfaces sub-markets not apparent in current classifications. We show that the segmentation has explanatory power for offered wages. The methodology developed could be deployed to create data-driven taxonomies in conditions of rapidly changing labour markets and demonstrates the potential of unsupervised machine learning in economics.
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using Job Vacancies to understand the effects of labour market mismatch on uk output and productivity
Social Science Research Network, 2018Co-Authors: Arthur Turrell, David Copple, Jyldyz Djumalieva, Bradley Speigner, James ThurgoodAbstract:Mismatch in the labour market has been implicated as a driver of the UK’s productivity ‘puzzle’, the phenomenon describing how the growth rate and level of UK productivity have fallen behind their respective pre-Great Financial Crisis trends. Using a new dataset of around 15 million Job adverts originally posted online, we examine the extent to which eliminating occupational or regional mismatch would have boosted productivity and output growth in the UK in the post-crisis period. To show how aggregate labour market data hide important heterogeneity, we map the naturally occurring vacancy data into official occupational classifications using a novel application of text analysis. The effects of mismatch on aggregate UK productivity and output are driven by dispersion in regional or occupational productivity, tightness, and matching efficiency. We find, contrary to previous work, that unwinding occupational mismatch would have had a weak effect on growth in the post-crisis period. However, unwinding regional mismatch would have substantially boosted output and productivity relative to their realised paths, bringing them in line with their pre-crisis trends.
Bradley Speigner - One of the best experts on this subject based on the ideXlab platform.
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is the uk s productivity puzzle mostly driven by occupational mismatch an analysis using big data on Job Vacancies
Labour Economics, 2021Co-Authors: David Copple, Arthur Turrell, Jyldyz Djumalieva, Bradley Speigner, James ThurgoodAbstract:Abstract Uncertainty still remains as to the cause of the UK’s dramatic productivity puzzle that began during the Great Financial Crisis. Occupational mismatch has been implicated as driving up to two thirds of it. However, obtaining the high quality time series data for Vacancies by Job occupation that are required to measure occupational mismatch is a significant challenge. We confront this issue by using a weighted dataset of 15 million Job adverts posted online that cover most of the post-crisis period and that enable us to test whether occupational mismatch still stands up as an explanation for the UK productivity puzzle. We find little evidence that it does, mainly because, relative to the data used in similar analysis by Patterson et al. (2016), our vacancy data imply greater heterogeneity in occupational matching frictions, a key determinant of the optimal distribution of labour across Job types.
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using online Job Vacancies to understand the uk labour market from the bottom up
Social Science Research Network, 2018Co-Authors: James Thurgood, Arthur Turrell, David Copple, Jyldyz Djumalieva, Bradley SpeignerAbstract:What type of disaggregation should be used to analyse heterogeneous labour markets? How granular should that disaggregation be? Economic theory does not currently tell us; perhaps data can. Analyses typically split labour markets according to top-down classification schema such as sector or occupation. But these may be slow-moving or inaccurate relative to the structure of the labour market as perceived by firms and workers. Using a dataset of 15 million Job adverts posted online between 2008 and 2016, we create an empirically driven, ‘bottom-up’ segmentation of the labour market which cuts across wage, sector, and occupation. Our segmentation is based upon applying machine learning techniques to the demand expressed in the text of Job descriptions. This segmentation automatically identifies traditional Job roles but also surfaces sub-markets not apparent in current classifications. We show that the segmentation has explanatory power for offered wages. The methodology developed could be deployed to create data-driven taxonomies in conditions of rapidly changing labour markets and demonstrates the potential of unsupervised machine learning in economics.
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using Job Vacancies to understand the effects of labour market mismatch on uk output and productivity
Social Science Research Network, 2018Co-Authors: Arthur Turrell, David Copple, Jyldyz Djumalieva, Bradley Speigner, James ThurgoodAbstract:Mismatch in the labour market has been implicated as a driver of the UK’s productivity ‘puzzle’, the phenomenon describing how the growth rate and level of UK productivity have fallen behind their respective pre-Great Financial Crisis trends. Using a new dataset of around 15 million Job adverts originally posted online, we examine the extent to which eliminating occupational or regional mismatch would have boosted productivity and output growth in the UK in the post-crisis period. To show how aggregate labour market data hide important heterogeneity, we map the naturally occurring vacancy data into official occupational classifications using a novel application of text analysis. The effects of mismatch on aggregate UK productivity and output are driven by dispersion in regional or occupational productivity, tightness, and matching efficiency. We find, contrary to previous work, that unwinding occupational mismatch would have had a weak effect on growth in the post-crisis period. However, unwinding regional mismatch would have substantially boosted output and productivity relative to their realised paths, bringing them in line with their pre-crisis trends.
Iourii Manovskii - One of the best experts on this subject based on the ideXlab platform.
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the cyclical behavior of equilibrium unemployment and Vacancies revisited
The American Economic Review, 2008Co-Authors: Marcus Hagedorn, Iourii ManovskiiAbstract:Recently, a number of authors have argued that the standard search model cannot generate the observed business-cycle-frequency fluctuations in unemployment and Job Vacancies, given shocks of a plausible magnitude. We propose a new calibration strategy of the standard model that uses data on the cost of vacancy creation and cyclicality of wages to identify the two key parameters - the value of nonmarket activity and the bargaining weights. Our calibration implies that the model is consistent with the data.
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the cyclical behavior of equilibrium unemployment and Vacancies revisited
Social Science Research Network, 2008Co-Authors: Marcus Hagedorn, Iourii ManovskiiAbstract:Recently, a number of authors have argued that the standard search model cannot generate the observed business-cycle-frequency fluctuations in unemployment and Job Vacancies, given shocks of a plausible magnitude. We use data on the cost of vacancy creation and cyclicality of wages to identify the two key parameters of the model - the value of non-market activity and the bargaining weights. Our calibration implies that the model is, in fact, consistent with the data.
Marco Viviani - One of the best experts on this subject based on the ideXlab platform.
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WoLMIS: a labor market intelligence system for classifying web Job Vacancies
Journal of Intelligent Information Systems, 2018Co-Authors: Roberto Boselli, Mirko Cesarini, Stefania Marrara, Fabio Mercorio, Mario Mezzanzanica, Gabriella Pasi, Marco VivianiAbstract:In the last decades, an increasing number of employers and Job seekers have been relying on Web resources to get in touch and to find a Job. If appropriately retrieved and analyzed, the huge number of Job Vacancies available today on on-line Job portals can provide detailed and valuable information about the Web Labor Market dynamics and trends. In particular, this information can be useful to all actors, public and private, who play a role in the European Labor Market. This paper presents WoLMIS, a system aimed at collecting and automatically classifying multilingual Web Job Vacancies with respect to a standard taxonomy of occupations. The proposed system has been developed for the Cedefop European agency, which supports the development of European Vocational Education and Training (VET) policies and contributes to their implementation. In particular, WoLMIS allows analysts and Labor Market specialists to make sense of Labor Market dynamics and trends of several countries in Europe, by overcoming linguistic boundaries across national borders. A detailed experimental evaluation analysis is also provided for a set of about 2 million Job Vacancies, collected from a set of UK and Irish Web Job sites from June to September 2015.
