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The Local Job Multipliers of Green Industrialization. (2025). Vona, Francesco ; Colantone, Italo ; Bontadini, Filippo ; Frattini, Federico Fabio.
In: FEEM Working Papers.
RePEc:ags:feemwp:358792.

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  27. Coefficient estimates Years Aggregate -.06 -.04 -.02 0 .02 -.02 0 .02 .04 -.05 0 .05 -.02 -.01 0 .01 -.05 0 .05 -.06 -.04 -.02 0 .02 2000 2001 2002 2003 2000 2001 2002 2003 2000 2001 2002 2003 Total Manufacturing Non-manufacturing Construction Services Agric. + Min.
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  28. Coefficient estimates Years NACE 20 -.04 -.02 0 .02 -.02 -.01 0 .01 .02 -.04 -.02 0 .02 -.01 -.005 0 .005 .01 -.04 -.02 0 .02 -.04 -.02 0 .02 .04 2000 2001 2002 2003 2000 2001 2002 2003 2000 2001 2002 2003 Total Manufacturing Non-manufacturing Construction Services Agric. + Min.
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  29. Coefficient estimates Years NACE 27 -.06 -.04 -.02 0 .02 -.02 0 .02 .04 -.05 0 .05 -.02 0 -.02 0 .02 .04 .06 -.08 -.06 -.04 -.02 0 2000 2001 2002 2003 2000 2001 2002 2003 2000 2001 2002 2003 Total Manufacturing Non-manufacturing Construction Services Agric. + Min.
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  30. Coefficient estimates Years NACE 28 -.1 -.05 0 -.02 0 .02 .04 -.1 -.05 0 .05 -.02 -.01 0 .01 -.1 -.05 0 .05 -.05 0 .05 2000 2001 2002 2003 2000 2001 2002 2003 2000 2001 2002 2003 Total Manufacturing Non-manufacturing Construction Services Agric. + Min.
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  31. Coefficient estimates Years NACE 29 -.06 -.04 -.02 0 .02 -.02 -.01 0 .01 .02 -.06 -.04 -.02 0 -.01 0 .01 .02 -.06 -.04 -.02 0 -.02 0 .02 .04 2000 2001 2002 2003 2000 2001 2002 2003 2000 2001 2002 2003 Total Manufacturing Non-manufacturing Construction Services Agric. + Min.
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  32. Columns (2), (4) and (6) report the Kleibergen-Paap (KP) and the Cragg-Donald (CD) F statistic for weak identification, as well as the first stage coefficient. Controls include the share of employment in manufacturing and the regional non-green penetration, interacted with year fixed effects. All the controls are taken at baseline, that is their average value between 2000 and 2003. We include country and year fixed effects. Estimates are weighted by the share of regional population over the EU one, at baseline. NUTS 1 clustered standard errors in parentheses. Number of regions: 278. Number of NUTS1: 100. * p<0.10, ** p<0.05, *** p<0.01.
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  33. Construction employment. Source: Eurostat - LFS (links: NACER 2 - 2008/2017; NACER 1.1 - 2000-2007). The data concerns construction employment levels by NUTS2 and year, from 2000 to 2017. The crosswalk between NACER 1.1 and NACER 2 is a simple one-to-one of the NACER 1.1 category F to NACER 2 category F. The rest of the data management is identical to that described for total employment.
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  41. Figure A5: Distribution of the first stage’s coefficients. Monte Carlo simulation. 0 5.0e-04 .001 .0015 Density 0 1000 2000 3000 First-stage coefficient Notes. This figure shows the distribution of the coefficient of the first stage drawn from 1000 different subsamples. The vertical dashed black line correspond to the first-stage coefficient of Table 1.
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  60. Notes. These plots show the results of the event study specification for several outcomes employing a regression adjustment estimator from Callaway and Sant’Anna (2021). The positive spike in green regional penetration is defined as a change higher than the 90th percentile in the one-year change of green regional penetration. The first spike identifies the beginning of treatment. The analysis is split by brown exposure. Standard errors are clustered at the NUTS2 level.
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  61. Notes. These plots show the results of the event study specification for several outcomes employing both a two-way fixed effects estimator and the regression adjustment one from Callaway and Sant’Anna (2021). The positive spike in green regional penetration is defined as a change higher than the 90th percentile in the one-year change of green regional penetration. The first spike identifies the beginning of treatment. Standard errors are clustered at the NUTS2 level.
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  75. Table A12: Lee et al. (2022) valid t-ratio inference Panel A: Total Manufacturing Non-manufacturing Coefficient 0.166 0.053 0.126 Unadj SE 0.028 0.012 0.046 1% CV of |t| 3.138 3.138 3.138 Adj SE 0.034 0.015 0.056 Adj UB 0.255 0.091 0.269 Adj LB 0.078 0.015-0.017 FS F-stat 80.909 80.909 80.909 Panel B: Construction Services Agric. + Min.
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  76. Table A19: Positive and negative weights from the TWFE regression N ATTs Sum ofweights Positive Weights 1141 1.0614 Negative Weights 135 -.0614 Total 1276 1 Notes. This table shows the weights attached to the two-way fixed effects regressions computet as in De Chaisemartin and d’Haultfoeuille (2020).
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  78. Utilities employment. Source: Eurostat - SBS (links: NACER 2 - 2008/2017; NACER 1.1 - 2000 -2007). The data concerns utilities employment levels by NUTS2 and year, from 1995 to 2017. The crosswalk between NACER 1.1 and NACER 2 is a simple one-to-one of the NACER 1.1 category E to NACER 2 categories D and E, summed together. The rest of the data management is identical to that described for total employment. 29 For example, in the UK UKM3 was split into UKM8 and UKM9.
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  87. Wilson, D. J. (2012). Fiscal spending jobs multipliers: Evidence from the 2009 american recovery and reinvestment act. American Economic Journal: Economic Policy, 4(3), 251–282. A Appendix A.1 Descriptive statistics Figure A1: GRP and NGRP β = 9.690*** -5 0 5 10 ∆3 Non-green penetration -.5 0 .5 1 ∆3 Green penetration Notes. This graph shows the raw correlation between the average three-year change in regional non-green penetration and the average three-year change in regional green penetration. We weight the two variables by the share of regional population over the EU one. Table A1: Green and polluting production by 2-digit industries NACE2D Label Share Gp Tot. Gp Mean Gp SD Gp Max Gp GHG int.
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  29. The labour market impact of robotisation in Europe. (2020). Urzì Brancati, Maria Cesira ; Klenert, David ; Fernandez-Macias, Enrique ; Antón, José Ignacio ; Urzi, Maria Cesira ; Anton, Jose-Ignacio ; Alaveras, Georgios.
    In: JRC Working Papers on Labour, Education and Technology.
    RePEc:ipt:laedte:202006.

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  30. Technology, Labour Market Institutions and Early Retirement: Evidence from Finland. (2020). Yashiro, Naomitsu ; Kyyrä, Tomi ; Kyyra, Tomi ; Tuomala, Juha ; Hwang, Hyunjeong.
    In: Working Papers.
    RePEc:fer:wpaper:136.

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  31. Heterogeneous Relationships between Automation Technologies and Skilled Labor: Evidence from a Firm Survey. (2020). MORIKAWA, MASAYUKI.
    In: Discussion papers.
    RePEc:eti:dpaper:20004.

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  32. Place-based policies and spatial disparities across European cities. (2020). von Ehrlich, Maximilian ; Overman, Henry.
    In: LSE Research Online Documents on Economics.
    RePEc:ehl:lserod:105168.

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  33. The rise of robots and the fall of routine jobs. (2020). Wacker, Konstantin ; Miroudot, Sébastien ; de Vries, Gaaitzen ; Gentile, Elisabetta.
    In: Labour Economics.
    RePEc:eee:labeco:v:66:y:2020:i:c:s0927537120300890.

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  34. Digitization-based automation and occupational dynamics. (2020). Persson, Lars ; Norbäck, Pehr-Johan ; Heyman, Fredrik ; Gardberg, Malin ; Norback, Pehr-Johan.
    In: Economics Letters.
    RePEc:eee:ecolet:v:189:y:2020:i:c:s0165176520300501.

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  35. Virtually everywhere? Digitalisation and the euro area and EU economies. (2020). Vivian, Lara ; Petroulakis, Filippos ; Morgan, Julian ; Labhard, Vincent ; Jarvis, Valerie ; Anderton, Robert.
    In: Occasional Paper Series.
    RePEc:ecb:ecbops:2020244.

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  36. Twisting the Demand Curve: Digitalization and the Older Workforce. (2020). Freeman, Richard ; Davis, James ; Barth, Erling ; McElheran, Kristina.
    In: Working Papers.
    RePEc:cen:wpaper:20-37.

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  37. Place-Based Policies and Spatial Disparities across European Cities. (2020). von Ehrlich, Maximilian ; Overman, Henry.
    In: Journal of Economic Perspectives.
    RePEc:aea:jecper:v:34:y:2020:i:3:p:128-49.

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  38. Does automation lead to de-industrialization in emerging economies? Evidence from Brazil. (2019). Stemmler, Henry.
    In: University of Göttingen Working Papers in Economics.
    RePEc:zbw:cegedp:382.

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  39. OK Computer: The Creation and Integration of AI in Europe. (2019). Kogler, Dieter ; Hynes, Ryan ; Davies, Ronald ; Buarque, Bernardo S.
    In: Working Papers.
    RePEc:ucn:wpaper:201911.

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  40. Fewer babies and more robots: economic growth in a new era of demographic and technological changes. (2019). Jimeno, Juan F.
    In: SERIEs: Journal of the Spanish Economic Association.
    RePEc:spr:series:v:10:y:2019:i:2:d:10.1007_s13209-019-0190-z.

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  41. Explaining the labor share: automation vs labor market institutions. (2019). Gil, Pedro ; Guimares, Lus.
    In: Economics Working Papers.
    RePEc:qub:wpaper:1901.

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  42. Looking ahead at the effects of automation in an economy with matching frictions. (2019). Gil, Pedro ; Guimares, Luis.
    In: MPRA Paper.
    RePEc:pra:mprapa:96238.

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  43. Explaining the labor share: automation vs labor market institutions. (2019). Gil, Pedro ; Guimares, Lus.
    In: CEF.UP Working Papers.
    RePEc:por:cetedp:1901.

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  44. Effort: The Unrecognized Contributor to US Income Inequality. (2019). Leamer, Edward ; Fuentes, Rodrigo.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:26421.

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  45. The Wrong Kind of AI? Artificial Intelligence and the Future of Labor Demand. (2019). Restrepo, Pascual ; Acemoglu, Daron.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:25682.

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  46. Behind the headline number: Why not to rely on Frey and Osborne’s predictions of potential job loss from automation. (2019). Coelli, Michael ; Borland, Jeff.
    In: Melbourne Institute Working Paper Series.
    RePEc:iae:iaewps:wp2019n10.

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  47. Recent Employment Growth in Cities, Suburbs, and Rural Communities. (2019). Foote, Christopher ; Couillard, Benjamin.
    In: Working Papers.
    RePEc:fip:fedbwp:87417.

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  48. Digitising Agrifood: Pathways and Challenges. (2019). Reynolds, Nicole ; Laurer, Moritz ; Cohen, Gal ; Renda, Andrea.
    In: CEPS Papers.
    RePEc:eps:cepswp:25701.

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  49. High-Quality Versus Low-Quality Growth in Turkey - Causes and Consequences. (2019). Acemoglu, Daron ; Uer, Murat.
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:14070.

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  50. Automation and labor demand in European countries: A task-based approach to wage bill decomposition. (2019). Lábaj, Martin ; Vitalos, Materj ; Labaj, Martin.
    In: Department of Economic Policy Working Paper Series.
    RePEc:brt:depwps:021.

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