{"id":1036,"date":"2024-12-23T15:06:29","date_gmt":"2024-12-23T15:06:29","guid":{"rendered":"https:\/\/naujienosversle.lt\/index.php\/2024\/12\/23\/labour-market-transitions-in-a-greener-economy\/"},"modified":"2024-12-23T15:06:29","modified_gmt":"2024-12-23T15:06:29","slug":"labour-market-transitions-in-a-greener-economy","status":"publish","type":"post","link":"https:\/\/naujienosversle.lt\/index.php\/2024\/12\/23\/labour-market-transitions-in-a-greener-economy\/","title":{"rendered":"Labour market transitions in a greener economy"},"content":{"rendered":"<p> <br \/>\n<\/p>\n<div>\n<p>The transition to a greener economy is a necessity (Kanzig 2024). It will require significant shifts in the way goods and energy are produced and consumed (European Parliament 2024) as well as the reallocation of production factors, including workers. Although the overall effects in terms of aggregate economic output and employment could be relatively small, the effects are likely to be concentrated \u2013 by economic activity, geographical area, and workers\u2019 characteristics \u2013 with a risk of amplifying inequalities in outcomes and opportunities. In particular, the transition is expected to induce a contraction of jobs in high-polluting activities (often labelled \u2018brown\u2019 jobs) and an expansion of so-called \u2018green\u2019 jobs, or those involving green activities according to the O*NET classification (Valero et al. 2021, Vona et al. 2018, Vandeplas et al. 2022, Causa et al. 2024, Causa and Phillips 2024, O*NET\u00a0 2010). A just transition in the labour market should minimise costs for individuals and communities. Achieving this will require policies to improve the allocation of workers and support the re-employment of dismissed ones, especially towards greener occupations, while managing and minimising the scarring effects associated with job losses in polluting industries. In addition, given the marked differences in industrial specialisation across regions, policy interventions should be place-based.<\/p>\n<p>Workers in high-polluting occupations tend to have lower educational attainment (Causa et al. 2024). In cases of job dismissal, they often experience larger earnings losses compared with workers in non-energy-intensive and transport sectors (Barreto et al. 2024). Comprehensive labour market policies and effective educational systems and upskilling programmes can help mitigate such losses and the risk of scarring, while also accelerating the green transition. Recent empirical work on a large sample of EU countries (Causa et al. 2024) finds that the estimated risk of long-term unemployment for individuals displaced from high-polluting jobs is lower, after accounting for country-specific effects and individual characteristics, in countries where higher shares of the population have a tertiary education and more adults participate in training (Table 1, Panel A). To facilitate the matching of workers to new jobs, training and active labour market programmes should be complemented with balanced and adequate income support and unemployment benefits, which are associated with a higher probability of transitioning from unemployment to employment, particularly among the long-term unemployed (Table 1, Panel B).<\/p>\n<p>In addition, policies fostering access to quality education and training can help fulfil the increasing demand for workers in green jobs (as defined in Causa et al. 2024) since, net of other observable characteristics, the odds of getting a green job are twice as high for workers with high levels of education, especially in STEM fields (Figure 1). In fact, the transitions from unemployment to green jobs are more likely in countries with higher rates of adult proficiency in literacy and numeracy and a higher share of workers with formal training (Table 1, Panel A).<\/p>\n<p><strong>Figure 1<\/strong> Transitions from unemployment and inactivity to employment in green jobs<\/p>\n<p>A) Transitions from unemployment to green jobs<\/p>\n<p>B) Transitions from study-related inactivity to green jobs<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_84 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Turinys;<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><ul class='ez-toc-list-level-6' ><li class='ez-toc-heading-level-6'><ul class='ez-toc-list-level-6' ><li class='ez-toc-heading-level-6'><ul class='ez-toc-list-level-6' ><li class='ez-toc-heading-level-6'><ul class='ez-toc-list-level-6' ><li class='ez-toc-heading-level-6'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/naujienosversle.lt\/index.php\/2024\/12\/23\/labour-market-transitions-in-a-greener-economy\/#Note_The_term_%E2%80%98green_jobs_indicates_the_ISCO_three-digit_occupations_which_based_on_the_crosswalk_defined_in_Causa_et_al_2024_correspond_to_the_ONET_list_ONET_2010_of_green-enhanced_and_green-demand_occupations_Charts_report_the_estimated_odds-ratios_from_two-steps_logit_regression_estimations_for_a_large_panel_of_European_OECD_countries_over_the_period_2011%E2%80%932019_along_with_the_corresponding_95_confidence_intervals_For_Panel_A_the_estimation_sample_includes_individuals_who_are_unemployed_in_year_t-1_and_move_to_employment_in_any_kind_of_occupation_by_year_t_and_the_binary_dependent_variable_takes_value_one_if_the_employment_in_t_is_in_a_green_job_and_zero_otherwise_For_Panel_B_the_sample_includes_respondents_in_the_age_group_20%E2%80%9329_who_are_out_of_the_labour_force_and_studying_in_year_t-1_and_employed_in_year_t_The_dependent_variable_in_Panel_B_takes_value_one_if_the_individual_is_employed_in_a_green_job_in_year_t_and_zero_if_in_a_non-green_job_Beyond_the_independent_variables_shown_in_the_chart_the_regressions_include_controls_for_the_basic_individual_characteristics_macro-level_cyclical_indicators_regional_labour_market_conditions_and_economic_sector_region_and_country_fixed_effects_Further_details_in_Causa_et_al_2024_Source_Causa_et_al_2024\" >Note: The term \u2018green jobs\u2019 indicates the ISCO three-digit occupations which, based on the crosswalk defined in Causa et al. (2024), correspond to the O*NET list (O*NET 2010) of green-enhanced and green-demand occupations. Charts report the estimated odds-ratios from two-steps logit regression estimations for a large panel of European OECD countries over the period 2011\u20132019, along with the corresponding 95% confidence intervals. For Panel A, the estimation sample includes individuals who are unemployed in year t-1 and move to employment (in any kind of occupation) by year t, and the binary dependent variable takes value one if the employment in t is in a green job and zero otherwise. For Panel B, the sample includes respondents in the age group 20\u201329 who are out of the labour force and studying in year t-1 and employed in year t. The dependent variable in Panel B takes value one if the individual is employed in a green job in year t, and zero if in a non-green job. Beyond the independent variables shown in the chart, the regressions include controls for the basic individual characteristics, macro-level cyclical indicators, regional labour market conditions, and economic sector, region, and country fixed effects. Further details in Causa et al. (2024). Source: Causa et al. (2024).<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-6'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/naujienosversle.lt\/index.php\/2024\/12\/23\/labour-market-transitions-in-a-greener-economy\/#Note_In_the_table_the_expression_%E2%80%98green_jobs_indicates_the_ISCO_three-digit_occupations_which_based_on_the_crosswalk_defined_in_Causa_et_al_2024_correspond_to_the_ONET_list_ONET_2010_of_green-enhanced_and_green-demand_occupations_The_symbol_%E2%80%98%3E_indicates_a_positive_association_for_example_an_increase_in_the_mean_literacy_score_is_associated_with_an_increase_in_the_probability_of_getting_a_job_in_a_green-skill_occupation_%E2%80%98%3E_%E2%80%98\" >Note: In the table, the expression \u2018green jobs\u2019 indicates the ISCO three-digit occupations which, based on the crosswalk defined in Causa et al. (2024), correspond to the O*NET list (O*NET 2010) of green-enhanced and green-demand occupations. The symbol \u2018&gt;\u2019 indicates a positive association (for example: an increase in the mean literacy score is associated with an increase in the probability of getting a job in a green-skill occupation); \u2018&lt;\u2019 indicates a negative association (for example, stronger employment protection on regular contracts is associated with lower probabilities of getting any job); and \u2018-\u2018 indicates the absence of a statistically significant association between the policy and the outcome. When considering sub-populations, such as younger or older workers or women, the sign \u2018&gt;&gt;\u2019 (\u2018&lt;&lt;\u2019) indicates that the association is positive (negative) and significantly more so than the association found for the general population. All associations are computed ceteris paribus, i.e. holding fixed the observable characteristics of workers, the year of the survey, the country and the corresponding macro-economic conditions, and, when relevant, the industry of occupation. For details on the sample and estimation see Causa et al. (2024).<\/a><\/li><\/ul><\/li><\/ul><\/li><\/ul><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/naujienosversle.lt\/index.php\/2024\/12\/23\/labour-market-transitions-in-a-greener-economy\/#References\" >References<\/a><\/li><\/ul><\/nav><\/div>\n<h6><span class=\"ez-toc-section\" id=\"Note_The_term_%E2%80%98green_jobs_indicates_the_ISCO_three-digit_occupations_which_based_on_the_crosswalk_defined_in_Causa_et_al_2024_correspond_to_the_ONET_list_ONET_2010_of_green-enhanced_and_green-demand_occupations_Charts_report_the_estimated_odds-ratios_from_two-steps_logit_regression_estimations_for_a_large_panel_of_European_OECD_countries_over_the_period_2011%E2%80%932019_along_with_the_corresponding_95_confidence_intervals_For_Panel_A_the_estimation_sample_includes_individuals_who_are_unemployed_in_year_t-1_and_move_to_employment_in_any_kind_of_occupation_by_year_t_and_the_binary_dependent_variable_takes_value_one_if_the_employment_in_t_is_in_a_green_job_and_zero_otherwise_For_Panel_B_the_sample_includes_respondents_in_the_age_group_20%E2%80%9329_who_are_out_of_the_labour_force_and_studying_in_year_t-1_and_employed_in_year_t_The_dependent_variable_in_Panel_B_takes_value_one_if_the_individual_is_employed_in_a_green_job_in_year_t_and_zero_if_in_a_non-green_job_Beyond_the_independent_variables_shown_in_the_chart_the_regressions_include_controls_for_the_basic_individual_characteristics_macro-level_cyclical_indicators_regional_labour_market_conditions_and_economic_sector_region_and_country_fixed_effects_Further_details_in_Causa_et_al_2024_Source_Causa_et_al_2024\"><\/span><em>Note<\/em>: The term \u2018green jobs\u2019 indicates the ISCO three-digit occupations which, based on the crosswalk defined in Causa et al. (2024), correspond to the O*NET list (O*NET 2010) of green-enhanced and green-demand occupations. Charts report the estimated odds-ratios from two-steps logit regression estimations for a large panel of European OECD countries over the period 2011\u20132019, along with the corresponding 95% confidence intervals. For Panel A, the estimation sample includes individuals who are unemployed in year t-1 and move to employment (in any kind of occupation) by year t, and the binary dependent variable takes value one if the employment in t is in a green job and zero otherwise. For Panel B, the sample includes respondents in the age group 20\u201329 who are out of the labour force and studying in year t-1 and employed in year t. The dependent variable in Panel B takes value one if the individual is employed in a green job in year t, and zero if in a non-green job. Beyond the independent variables shown in the chart, the regressions include controls for the basic individual characteristics, macro-level cyclical indicators, regional labour market conditions, and economic sector, region, and country fixed effects. Further details in Causa et al. (2024).<br \/><em>Source<\/em>: Causa et al. (2024).<span class=\"ez-toc-section-end\"><\/span><\/h6>\n<p>In terms of promoting transitions from joblessness to employment in green jobs, beyond the key role of education and training, labour market institutions are instrumental. These include active labour market policies, cash support to unemployed workers, and well-designed institutions to promote effective collective wage bargaining and social dialogue. Progress in this area is particularly beneficial for women, less-educated workers, and those living in rural areas (Table 1, Panel A). Policies like training, public employment services that support job searches (PES), and employment incentives are associated with higher chances of transitioning from non-employment to green jobs for higher-educated workers (Table 1, Panel B). While not causal, this association suggests the need to better design and target such policies for more exposed and vulnerable workers, especially those with lower education levels.<\/p>\n<p>On the other hand, the transition from unemployment to green jobs is less likely in countries with relatively high employment protection and product markets and occupational entry regulations that hinder business and labour market dynamism (Table 1, Panel C). Such an association is particularly strong for vulnerable groups, like lower-educated individuals and those just entering the labour force after completing their studies. These results are in line with the general literature on the effects of employment protection legislation on job-finding rates and labour market transitions (Bassanini and Garnero 2013, Causa et al. 2022, Scarpetta 2014).<\/p>\n<p><strong>Table 1<\/strong> Policies to support labour market transitions into a greener economy<\/p>\n<h6><span class=\"ez-toc-section\" id=\"Note_In_the_table_the_expression_%E2%80%98green_jobs_indicates_the_ISCO_three-digit_occupations_which_based_on_the_crosswalk_defined_in_Causa_et_al_2024_correspond_to_the_ONET_list_ONET_2010_of_green-enhanced_and_green-demand_occupations_The_symbol_%E2%80%98%3E_indicates_a_positive_association_for_example_an_increase_in_the_mean_literacy_score_is_associated_with_an_increase_in_the_probability_of_getting_a_job_in_a_green-skill_occupation_%E2%80%98%3E_%E2%80%98\"><\/span><em>Note<\/em>: In the table, the expression \u2018green jobs\u2019 indicates the ISCO three-digit occupations which, based on the crosswalk defined in Causa et al. (2024), correspond to the O*NET list (O*NET 2010) of green-enhanced and green-demand occupations. The symbol \u2018&gt;\u2019 indicates a positive association (for example: an increase in the mean literacy score is associated with an increase in the probability of getting a job in a green-skill occupation); \u2018&lt;\u2019 indicates a negative association (for example, stronger employment protection on regular contracts is associated with lower probabilities of getting any job); and \u2018-\u2018 indicates the absence of a statistically significant association between the policy and the outcome. When considering sub-populations, such as younger or older workers or women, the sign \u2018&gt;&gt;\u2019 (\u2018&lt;&lt;\u2019) indicates that the association is positive (negative) and significantly more so than the association found for the general population. All associations are computed ceteris paribus, i.e. holding fixed the observable characteristics of workers, the year of the survey, the country and the corresponding macro-economic conditions, and, when relevant, the industry of occupation. For details on the sample and estimation see Causa et al. (2024).<span class=\"ez-toc-section-end\"><\/span><\/h6>\n<p>The labour market literature shows that housing policies favouring residential mobility tend to facilitate the spatial reallocation of workers and promote business dynamism, enhancing the ability of workers to seize job opportunities (Causa et al. 2021, Causa et al. 2020, Andrews et al. 2011). This is also the case in the context of the green transition: for example, hirings from studies are hindered by strong house price dynamics, with higher house prices acting as possible barriers to geographical mobility. Social rental housing and the provision of housing allowances (i.e. housing-related monetary benefits) increase the odds of an individual moving from joblessness to a job, including a green job, with the benefits of housing allowances being more widespread than those of social housing. At the same time, these housing support policies are associated with significantly lower risks of long-term unemployment, especially for lower-educated individuals. Finally, reducing excessively rigid rental market regulations could also lift barriers to geographical mobility and enhance transitions from joblessness to employment (Table 1, Panel D).<\/p>\n<p>Our findings demonstrate that structural policies known to support labour market inclusiveness and efficiency are also likely to support a green transition that is both smooth and fair. Yet, they also highlight that the impact of the transition to a greener economy and climate mitigation policies is uneven across socioeconomic groups characterised by different educational and skill background as well as geographical areas, such as territories and regions characterised by different industrial specialisation structures. Successful policy experiences in the past can help national and sub-national governments build tailored approaches to support an efficient and fair labour market transition process.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"References\"><\/span>References<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Adalet McGowan, M and D Andrews (2017), \u201cSkills mismatch, productivity and policies: Evidence from the second wave of PIAAC\u201d, OECD Economics Department Working Papers, no. 1403.<\/p>\n<p>Andre, C and P Gal (2024), Reviving productivity growth: A review of policies, forthcoming.<\/p>\n<p>Andrews, D, A Caldera S\u00e1nchez and \u00c5 Johansson (2011), \u201cHousing Markets and Structural Policies in OECD Countries\u201d, OECD Economics Department Working Papers, no. 836.<\/p>\n<p>Barreto, C et al. (2024), \u201cThe \u2018clean energy transition\u2019 and the cost of job displacement in energy-intensive industries\u201d, OECD Social, Employment and Migration Working Papers, no. 310.<\/p>\n<p>Bassanini, A and A Garnero (2013), \u201cDismissal protection and worker flows in OECD countries: Evidence from cross-country\/cross-industry data\u201d, <em>Labour Economics<\/em>\u00a021, 25\u201341.<\/p>\n<p>Bilal, A and D K\u00e4nzig (2024), \u201cWhy Global Temperature Matters\u201d, VoxEU.org, 21 July.<\/p>\n<p>Boal, W and M Ransom (1997), \u201cMonopsony in the Labor Market\u201d, <em>Journal of Economic Literature <\/em>35(1).<\/p>\n<p>Boeri, T and M Burda (1996), \u201cActive labor market policies, job matching and the Czech miracle\u201d, <em>European Economic Review<\/em>\u00a040(3\u20135).<\/p>\n<p>Borgonovi, F et al. (2023), \u201cThe effects of the EU Fit for 55 package on labour markets and the demand for skills\u201d, OECD Social, Employment and Migration Working Papers, no. 297.<\/p>\n<p>Bowen, A, K Kuralbayeva and E Tipoe (2018), \u201cCharacterising green employment: The impacts of \u2018greening\u2019 on workforce composition\u201d, <em>Energy Economics<\/em>\u00a072: 263\u201375.<\/p>\n<p>Card, D, J Kluve and A Weber (2015), \u201cWhat Works? A Meta Analysis of Recent Active Labor Market Program Evaluations\u201d, NBER Working Paper 21431.<\/p>\n<p>Causa, O, M Abendschein and M Cavalleri (2021), \u201cThe laws of attraction: Economic drivers of inter-regional migration, housing costs and the role of policies\u201d, OECD Economics Department Working Papers, no. 1679.<\/p>\n<p>Causa, O et al. (2022), \u201cGetting on the job ladder: The policy drivers of hiring transitions\u201d, OECD Economics Department Working Papers, no. 1710.<\/p>\n<p>Causa, O, N Luu and M Abendschein (2021), \u201cLabour Market Transitions across the OECD: Stylised Facts\u201d, OECD Economics Department Working Papers, no. 1692.<\/p>\n<p>Causa, O, M Nguyen and E Soldani (2024), <em>A new measurement approach for indentifying high-polluting jobs across European countries<\/em>.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0<\/p>\n<p>Causa, O, M Nguyen and E Soldani (2024), <em>Lost in the green transition: Measurement and stylised facts.<\/em><\/p>\n<p>Causa, O and T Phillips (2024), \u201cIt\u2019s a dirty job\u201d, VoxTalk, 21 June.<\/p>\n<p>Causa, O and J Pichelmann (2020), \u201cShould I stay or should I go? Housing and residential mobility across OECD countries\u201d, OECD Economics Department Working Papers, no. 1626.<\/p>\n<p>Causa, O, E Soldani and M Nguyen (2024), \u201cLost in the green transition? Measurement and stylized facts\u201d, VoxEU.org, 28 May.<\/p>\n<p>Causa, O et al. (2024), \u201cLabour markets transitions in the greening economy: Structural drivers and the role of policies\u201d, OECD Economics Department Working Papers, no. 1803.<\/p>\n<p>Chateau, J, R Bibas and E Lanzi (2018), \u201cImpacts of Green Growth Policies on Labour Markets and Wage Income Distribution: A General Equilibrium Application to Climate and Energy Policies\u201d, OECD Environment Working Papers, no. 137.<\/p>\n<p>Consoli, D et al. (2016), \u201cDo green jobs differ from non-green jobs in terms of skills and human capital?\u201d, <em>Research Policy<\/em>\u00a045(5): 1046\u201360.<\/p>\n<p>Demetriades, S, J Cabrita and K F\u00f3ti (2021), \u201cDistributional impacts of climate policies in Europe\u201d, Eurofound.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0<\/p>\n<p>European Parliament (2024), <em>Social and labour market impact of the green transition.\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0<\/em><\/p>\n<p>K\u00e4nzig, D (2023), \u201cThe Unequal Economic Consequences of Carbon Pricing\u201d, SSRN Electronic Journal.<\/p>\n<p>Lopez-Garcia, P (2009), \u201cBusiness Environment and Labor Market Outcomes in European and Central Asian Countries\u201d, <em>Journal of Entrepreneurial Finance<\/em>\u00a012(4).<\/p>\n<p>OECD (2023), <em>Economic Policy Reforms 2023: Going for Growth<\/em>, Paris: OECD Publishing.<\/p>\n<p>OECD (2023), <em>Education at a Glance 2023: OECD Indicators<\/em>, Paris: OECD Publishing.<\/p>\n<p>OECD (2023), <em>Job Creation and Local Economic Development 2023: Bridging the Great Green Divide<\/em>, Paris: OECD Publishing.<\/p>\n<p>OECD (2023), <em>Joining Forces for Gender Equality: What is Holding us Back?<\/em>, Paris: OECD Publishing.<\/p>\n<p>OECD (2017), <em>The Pursuit of Gender Equality: An Uphill Battle<\/em>, Paris: OECD Publishing.<\/p>\n<p>Pisani-Ferry, J (2021), \u201cClimate policy is macroeconomic policy, and the implications will be significant\u201d, PIIE Policy Brief, no. 21\u201320.\u00a0\u00a0<\/p>\n<p>Scarpetta, S (2014), \u201cEmployment protection\u201d, The IZA World of Labor.<\/p>\n<p>Soldani, E et al. (2024), Policy approaches to reduce inequalities while boosting productivity growth, Paris: OECD Publishing.\u00a0\u00a0\u00a0\u00a0<\/p>\n<p>Valero, A et al. (2021), \u201cAre \u2018green\u2019 jobs good jobs? How lessons from the experience to-date can inform labour market transitions of the future\u201d, Grantham Research Institute, London School of Economics.<\/p>\n<p>Vandeplas, A et al. (2022),<em> The possible implications of the green transition for the EU labour market<\/em>, European Commission.<\/p>\n<p>Vandyck, T et al. (2021), \u201cClimate policy design, competitiveness and income distribution: A macro-micro assessment for 11 EU countries\u201d, <em>Energy Economics\u00a0<\/em>103, 105538.<\/p>\n<p>Vona, F, G Marin and D Consoli (2018), \u201cGreen employment: What, where and how much?\u201d, Sciences Po publications.\u00a0\u00a0\u00a0\u00a0<\/p>\n<\/p><\/div>\n<p><br \/>\n<br \/><a href=\"https:\/\/cepr.org\/voxeu\/columns\/labour-market-transitions-greener-economy\">Source link <\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The transition to a greener economy is a necessity (Kanzig 2024). It will require significant shifts in the way goods and energy are produced and consumed (European Parliament 2024) as well as the reallocation of production factors, including workers. Although the overall effects in terms of aggregate economic output and employment could be relatively small,&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[5],"tags":[2260,2259,2257,1340,2258],"class_list":["post-1036","post","type-post","status-publish","format-standard","hentry","category-pasaulio-ekonomikos-naujienos","tag-economy","tag-greener","tag-labour","tag-market","tag-transitions"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/naujienosversle.lt\/index.php\/wp-json\/wp\/v2\/posts\/1036","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/naujienosversle.lt\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/naujienosversle.lt\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/naujienosversle.lt\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/naujienosversle.lt\/index.php\/wp-json\/wp\/v2\/comments?post=1036"}],"version-history":[{"count":0,"href":"https:\/\/naujienosversle.lt\/index.php\/wp-json\/wp\/v2\/posts\/1036\/revisions"}],"wp:attachment":[{"href":"https:\/\/naujienosversle.lt\/index.php\/wp-json\/wp\/v2\/media?parent=1036"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/naujienosversle.lt\/index.php\/wp-json\/wp\/v2\/categories?post=1036"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/naujienosversle.lt\/index.php\/wp-json\/wp\/v2\/tags?post=1036"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}