46 Matching Annotations
  1. Last 7 days
  2. Local file Local file
    Project Name - Raw data quality check
    23
    1. chiliq 04 Sep 2025
      Individual is unemployed, employed at a large firm or employed at a small firm at time tDummy (1: Individual is unemployed, 2 if he is employed at a large firm, and 3 if he is employed at a small firm at time t)Employed, unemployed or inactive (individual)Dummy (0 or 1)16Individual is unemployed, employed at a large firm or employed at a small firm at time t+2 (the last year in each panel)Dummy (1: Individual is unemployed, 2 if he is employed at a large firm, and 3 if he is employed at a small firm at time t + 2)Employed, unemployed or inactive (individual)Dummy (0 or 1), interaction20Job to non-employmentDummy (Current job: 0, New job: 1, Nonemployment: 2)Employed, unemployed or inactive (individual)Dummy (0 or 1)14

      Anschauen um welche Effekte es hier genau geht

      Quirin_to-do
    2. chiliq 04 Sep 2025
      Transition to a larger size establishmentDummy (Current job: 0, New job (larger size establishment): 1, Nonemployment: 2)Employed, unemployed or inactive (individual)Dummy (0 or 1)14

      Anschauen um welche Effekte es hier genau geht

      Quirin_to-do
    3. chiliq 04 Sep 2025
      Differences and logEmployment (number of persons)Standard hours, log and differences

      Checken:

      1. Was sind logged differences?
      2. Wie liest man eine Regression der Form "logged differences" auf "logged differences", und kann man das vergleichbar machen?
      Quirin_to-do
    4. chiliq 04 Sep 2025
      dependent_variable_name_category == “Employment (growth)”

      Für alle Variablen ansehen was genau gemessen wird, + Formeln heraussuchen. Im Idealfall können wir alles mit Employment per person kombinieren.

      Quirin_to-do
    7. chiliq 04 Sep 2025
      Job-Job-TransitionDummy (Current job: 0, New job: 1, Nonemployment: 2)OtherDummy (0 or 1)28Staying at jobDummy (Current job: 0, New job: 1, Nonemployment: 2)OtherDummy (0 or 1)14

      Nochmal genauer anschauen

      Quirin_to-do
    10. chiliq 28 Aug 2025
      To-do Wir haben hier einen Fehleintrag von 20024 drinnen, der muss noch ausgebessert werden. 1937, 1939, 1980, 1982, 1985, 1986, 1987, 1990, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2002, 2003, 2004, 2005, 2006, 2007, 2012, 2013, 2017, 20024 Ist das eigentlich 2024?

      Dasselbe wie voher, 20024 checken

      Quirin_to-do
    11. chiliq 28 Aug 2025
      wtr_end

      Idee: Den Unterschied zwischen wtr_end und Jahr der jeweiligen Schätzung nehmen und als indep variable reinschmeißen - Idealerweise messen wir damit kurz-/mittel-/langfristige Effekte von AZV.

      Vorschlag: sample_end - wtr_end

      Achtung: in 26 Fällen ist sample_end -kleiner als wtr_end (in nur 20 Fällen davon ist before_policy_implementation = Yes - muss überprüft werden.

      Ludwig_to-do Quirin_to-do
    19. chiliq 28 Aug 2025
      wtr_begin 95 0.92 1989.73 11.64 1915.00 1985.00 1985.00 1997.00 2013.00 ▁▁▁▇▅ wtr_end 95 0.92 1990.93 12.38 1920.00 1985.00 1985.00 2000.00 2013.00 ▁▁▁▇▆ wtr_hours_old 130 0.89 41.75 3.09 39.00 40.00 40.00 44.00 59.00 ▇▂▂▁▁ wtr_hours_new 110 0.91 39.09 2.24 35.00 38.50 38.50 40.00 48.00 ▁▇▁▁▁ sample_begin 34 0.97 1988.14 10.97 1914.00 1985.00 1986.00 1994.00 2013.00 ▁▁▁▇▃ sample_end 34

      Bitte checken

      Quirin_to-do
    22. chiliq 28 Aug 2025
      "Individual" "Industry" [3] "Firm" "Establishment" [5] "Labor market" "Employment zone" [7] "Individual/Region" "Aggregate" [9] "Plant" "Aggregate (Business Sector)" [11] "Aggregate (One Sector)"

      Umcodieren auf micro/meso/macro:

      micro: "Individual", "Firm", "Establishment", "Plant" meso: "Industry", "Labor market", "Employment zone", "Aggregate (Business Sector)", "Aggregate (One Sector)" macro: "Aggregate"

      Aber was ist "Individual/Region"?

      Ludwig_to-do Quirin_to-do
    23. chiliq 28 Aug 2025
      estimated_variables 4 1.00 14.00 26.84 1.00 2.00 3.00 17.00 255.00 ▇▁▁▁▁ estimated_fixed_effects 8 0.99 1617.31 14574.57 0.00 0.00 0.00 0.00 168265.00 ▇▁▁▁▁ sample_size 18

      Bitte checken

      Quirin_to-do

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  3. Local file Local file
    Project Name - Raw data quality check
    23
    2. Ludwig_List 03 Sep 2025
      "Individual" "Industry" [3] "Firm" "Establishment" [5] "Labor market" "Employment zone" [7] "Individual/Region" "Aggregate" [9] "Plant" "Aggregate (Business Sector)" [11] "Aggregate (One Sector)"

      Umcodieren auf micro/meso/macro:

      micro: "Individual", "Firm", "Establishment", "Plant" meso: "Industry", "Labor market", "Employment zone", "Aggregate (Business Sector)", "Aggregate (One Sector)" macro: "Aggregate"

      Aber was ist "Individual/Region"?

      Ludwig_to-do Quirin_to-do
    5. Ludwig_List 03 Sep 2025
      wtr_begin 95 0.92 1989.73 11.64 1915.00 1985.00 1985.00 1997.00 2013.00 ▁▁▁▇▅ wtr_end 95 0.92 1990.93 12.38 1920.00 1985.00 1985.00 2000.00 2013.00 ▁▁▁▇▆ wtr_hours_old 130 0.89 41.75 3.09 39.00 40.00 40.00 44.00 59.00 ▇▂▂▁▁ wtr_hours_new 110 0.91 39.09 2.24 35.00 38.50 38.50 40.00 48.00 ▁▇▁▁▁ sample_begin 34 0.97 1988.14 10.97 1914.00 1985.00 1986.00 1994.00 2013.00 ▁▁▁▇▃ sample_end 34

      Bitte checken

      Quirin_to-do
    11. Ludwig_List 03 Sep 2025
      wtr_end

      Idee: Den Unterschied zwischen wtr_end und Jahr der jeweiligen Schätzung nehmen und als indep variable reinschmeißen - Idealerweise messen wir damit kurz-/mittel-/langfristige Effekte von AZV.

      Vorschlag: sample_end - wtr_end

      Achtung: in 26 Fällen ist sample_end -kleiner als wtr_end (in nur 20 Fällen davon ist before_policy_implementation = Yes - muss überprüft werden.

      Ludwig_to-do Quirin_to-do
    14. Ludwig_List 03 Sep 2025
      To-do Wir haben hier einen Fehleintrag von 20024 drinnen, der muss noch ausgebessert werden. 1937, 1939, 1980, 1982, 1985, 1986, 1987, 1990, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2002, 2003, 2004, 2005, 2006, 2007, 2012, 2013, 2017, 20024 Ist das eigentlich 2024?

      Dasselbe wie voher, 20024 checken

      Quirin_to-do
    17. Ludwig_List 03 Sep 2025
      Transition to a larger size establishmentDummy (Current job: 0, New job (larger size establishment): 1, Nonemployment: 2)Employed, unemployed or inactive (individual)Dummy (0 or 1)14

      Anschauen um welche Effekte es hier genau geht

      Quirin_to-do
    18. Ludwig_List 03 Sep 2025
      Individual is unemployed, employed at a large firm or employed at a small firm at time tDummy (1: Individual is unemployed, 2 if he is employed at a large firm, and 3 if he is employed at a small firm at time t)Employed, unemployed or inactive (individual)Dummy (0 or 1)16Individual is unemployed, employed at a large firm or employed at a small firm at time t+2 (the last year in each panel)Dummy (1: Individual is unemployed, 2 if he is employed at a large firm, and 3 if he is employed at a small firm at time t + 2)Employed, unemployed or inactive (individual)Dummy (0 or 1), interaction20Job to non-employmentDummy (Current job: 0, New job: 1, Nonemployment: 2)Employed, unemployed or inactive (individual)Dummy (0 or 1)14

      Anschauen um welche Effekte es hier genau geht

      Quirin_to-do
    22. Ludwig_List 03 Sep 2025
      Differences and logEmployment (number of persons)Standard hours, log and differences

      Checken:

      1. Was sind logged differences?
      2. Wie liest man eine Regression der Form "logged differences" auf "logged differences", und kann man das vergleichbar machen?
      Quirin_to-do

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