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Giovanni Mellace

Personal Details

First Name:Giovanni
Middle Name:
Last Name:Mellace
Suffix:
RePEc Short-ID:pme404
https://sites.google.com/site/giovannimellace/
Department of Business and Economics, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Denmark
+4565509294

Affiliation

(90%) Institut for Virksomhedsledelse og Økonomi
Syddansk Universitet

Odense, Denmark
http://www.sdu.dk/ivoe

: 65 50 32 33
65 50 32 37
Campusvej 55, 5230 Odense M
RePEc:edi:okioudk (more details at EDIRC)

(10%) Center for Sundhedsøkonomisk Forskning (COHERE)
Institut for Virksomhedsledelse og Økonomi
Syddansk Universitet

Odense, Denmark
http://www.cohere.dk/

: (+45) 6550 3081
(+45) 6550 3880
Campusvej 55, DK-5230 Odense M
RePEc:edi:hesdudk (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Mellace, Giovanni & Ventura, Marco, 2019. "Intended and unintended effects of public incentives for innovation. Quasi-experimental evidence from Italy," Discussion Papers of Business and Economics 9/2019, University of Southern Denmark, Department of Business and Economics.
  2. Mellace, Giovanni & Pasquini, Alessandra, 2019. "Identify More, Observe Less: Mediation Analysis: Mediation Analysis Synthetic Control," Discussion Papers of Business and Economics 12/2019, University of Southern Denmark, Department of Business and Economics.
  3. Federico Crudu & Giovanni Mellace & Zsolt Sandor, 2017. "Inference in instrumental variables models with heteroskedasticity and many instruments," Department of Economics University of Siena 761, Department of Economics, University of Siena.
  4. Dahl, Christian M. & Huber, Martin & Mellace, Giovanni, 2017. "It's never too LATE: A new look at local average treatment effects with or without defiers," Discussion Papers of Business and Economics 2/2017, University of Southern Denmark, Department of Business and Economics.
  5. Kongstad, L.P. & Mellace, G. & Olsen, K.R., 2016. "Can the use of Electronic Health Records in General Practice reduce hospitalizations for diabetes patients? Evidence from a natural experiment," Health, Econometrics and Data Group (HEDG) Working Papers 16/25, HEDG, c/o Department of Economics, University of York.
  6. Laffers, Lukas & Mellace, Giovanni, 2015. "A Note on Testing the LATE Assumptions," Discussion Papers of Business and Economics 4/2015, University of Southern Denmark, Department of Business and Economics.
  7. Huber, Martin & Mellace, Giovanni & Lechner, Michael, 2014. "The finite sample performance of estimators for mediation analysis under sequential conditional independence," Economics Working Paper Series 1415, University of St. Gallen, School of Economics and Political Science, revised Nov 2014.
  8. Huber, Martin & Mellace, Giovanni & Lechner, Michael, 2014. "Why do tougher caseworkers increase employment? The role of programme assignment as a causal mechanism," Economics Working Paper Series 1414, University of St. Gallen, School of Economics and Political Science.
  9. Huber, Martin & Mellace, Giovanni, 2012. "Relaxing monotonicity in the identification of local average treatment effects," Economics Working Paper Series 1212, University of St. Gallen, School of Economics and Political Science.
  10. Giovanni Mellace & Roberto Rocci, 2011. "Principal Stratification in sample selection problems with non normal error terms," CEIS Research Paper 194, Tor Vergata University, CEIS, revised 02 May 2011.
  11. Huber, Martin & Mellace, Giovanni, 2011. "Testing instrument validity in sample selection models," Economics Working Paper Series 1145, University of St. Gallen, School of Economics and Political Science.
  12. Huber, Martin & Mellace, Giovanni, 2011. "Sharp bounds on causal effects under sample selection," Economics Working Paper Series 1134, University of St. Gallen, School of Economics and Political Science.
  13. Huber, Martin & Mellace, Giovanni, 2011. "Testing instrument validity for LATE identification based on inequality moment constraints," Economics Working Paper Series 1143, University of St. Gallen, School of Economics and Political Science.
  14. Martin Huber & Giovanni Mellace, 2010. "Sharp IV bounds on average treatment effects under endogeneity and noncompliance," University of St. Gallen Department of Economics working paper series 2010 2010-31, Department of Economics, University of St. Gallen.

Articles

  1. Martin Huber & Lukas Laffers & Giovanni Mellace, 2017. "Sharp IV Bounds on Average Treatment Effects on the Treated and Other Populations Under Endogeneity and Noncompliance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 56-79, January.
  2. Lukas Laffers & Giovanni Mellace, 2017. "A note on testing instrument validity for the identification of LATE," Empirical Economics, Springer, vol. 53(3), pages 1281-1286, November.
  3. Martin Huber & Michael Lechner & Giovanni Mellace, 2017. "Why Do Tougher Caseworkers Increase Employment? The Role of Program Assignment as a Causal Mechanism," The Review of Economics and Statistics, MIT Press, vol. 99(1), pages 180-183, March.
  4. Martin Huber & Michael Lechner & Giovanni Mellace, 2016. "The Finite Sample Performance of Estimators for Mediation Analysis Under Sequential Conditional Independence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 139-160, January.
  5. Martin Huber & Giovanni Mellace, 2015. "Sharp Bounds on Causal Effects under Sample Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(1), pages 129-151, February.
  6. Martin Huber & Giovanni Mellace, 2015. "Testing Instrument Validity for LATE Identification Based on Inequality Moment Constraints," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 398-411, May.
  7. Martin Huber & Giovanni Mellace, 2014. "Testing exclusion restrictions and additive separability in sample selection models," Empirical Economics, Springer, vol. 47(1), pages 75-92, August.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Kongstad, L.P. & Mellace, G. & Olsen, K.R., 2016. "Can the use of Electronic Health Records in General Practice reduce hospitalizations for diabetes patients? Evidence from a natural experiment," Health, Econometrics and Data Group (HEDG) Working Papers 16/25, HEDG, c/o Department of Economics, University of York.

    Cited by:

    1. Olsen, Kim Rose & Laudicella, Mauro, 2019. "Health care inequality in free access health systems: The impact of non-pecuniary incentives on diabetic patients in Danish general practices," Social Science & Medicine, Elsevier, vol. 230(C), pages 174-183.

  2. Huber, Martin & Mellace, Giovanni & Lechner, Michael, 2014. "The finite sample performance of estimators for mediation analysis under sequential conditional independence," Economics Working Paper Series 1415, University of St. Gallen, School of Economics and Political Science, revised Nov 2014.

    Cited by:

    1. Advani, Arun & Sloczynski, Tymon, 2013. "Mostly Harmless Simulations? On the Internal Validity of Empirical Monte Carlo Studies," IZA Discussion Papers 7874, Institute of Labor Economics (IZA).
    2. Frölich, Markus & Huber, Martin & Wiesenfarth, Manuel, 2015. "The finite sample performance of semi- and nonparametric estimators for treatment effects and policy evaluation," FSES Working Papers 454, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    3. Bodory, Hugo & Huber, Martin & Camponovo, Lorenzo & Lechner, Michael, 2016. "The finite sample performance of inference methods for propensity score matching and weighting estimators," FSES Working Papers 466, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    4. Arun Advani & Toru Kitagawa & Tymon Słoczyński, 2019. "Mostly harmless simulations? Using Monte Carlo studies for estimator selection," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 893-910, September.
    5. Stephen Whelan, 2017. "Does homeownership affect education outcomes?," IZA World of Labor, Institute of Labor Economics (IZA), pages 342-342, April.
    6. Bijwaard, Govert & Alessie, Rob & Angelini, Viola, 2018. "The Effect of Early Life Health on Later Life Home Care Use: The Mediating Role of Household Composition," IZA Discussion Papers 11729, Institute of Labor Economics (IZA).

  3. Huber, Martin & Mellace, Giovanni & Lechner, Michael, 2014. "Why do tougher caseworkers increase employment? The role of programme assignment as a causal mechanism," Economics Working Paper Series 1414, University of St. Gallen, School of Economics and Political Science.

    Cited by:

    1. Huber, Martin & Lechner, Michael & Strittmatter, Anthony, 2015. "Direct and Indirect Effects of Training Vouchers for the Unemployed," IZA Discussion Papers 9138, Institute of Labor Economics (IZA).
    2. Frölich, Markus & Huber, Martin & Wiesenfarth, Manuel, 2015. "The finite sample performance of semi- and nonparametric estimators for treatment effects and policy evaluation," FSES Working Papers 454, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    3. Martin Huber & Mark Schelker & Anthony Strittmatter, 2019. "Direct and Indirect Effects based on Changes-in-Changes," Papers 1909.04981, arXiv.org, revised Oct 2019.
    4. Prifti, Ervin & Daidone, Silvio & Davis, Benjamin, 2019. "Causal pathways of the productive impacts of cash transfers: Experimental evidence from Lesotho," World Development, Elsevier, vol. 115(C), pages 258-268.
    5. Wunsch, Conny & Strobl, Renate, 2018. "Identification of Causal Mechanisms Based on Between-Subject Double Randomization Designs," IZA Discussion Papers 11626, Institute of Labor Economics (IZA).
    6. Steinmayr, Andreas, 2014. "When a random sample is not random: Bounds on the effect of migration on household members left behind," Kiel Working Papers 1975, Kiel Institute for the World Economy (IfW).
    7. Lechner, Michael, 2019. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," CEPR Discussion Papers 13430, C.E.P.R. Discussion Papers.
    8. Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2017. "Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach," Economics Working Paper Series 1711, University of St. Gallen, School of Economics and Political Science.
    9. Michael C. Knaus & Michael Lechner & Anthony Strittmatter, 2018. "Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence," Papers 1810.13237, arXiv.org, revised Dec 2018.
    10. Martin Huber & Michael Lechner & Giovanni Mellace, 2016. "The Finite Sample Performance of Estimators for Mediation Analysis Under Sequential Conditional Independence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 139-160, January.
    11. N. N., 2017. "WIFO-Monatsberichte, Heft 6/2017," WIFO Monatsberichte (monthly reports), WIFO, vol. 90(6), June.
    12. Rainer Eppel & Helmut Mahringer & Petra Sauer, 2017. "Österreich 2025 – Arbeitslosigkeit und die Rolle der aktiven Arbeitsmarktpolitik," WIFO Monatsberichte (monthly reports), WIFO, vol. 90(6), pages 493-505, June.
    13. Schiprowski, Amelie, 2017. "The Role of Caseworkers in Unemployment Insurance: Evidence from Unplanned Absences," IZA Discussion Papers 11040, Institute of Labor Economics (IZA).

  4. Huber, Martin & Mellace, Giovanni, 2012. "Relaxing monotonicity in the identification of local average treatment effects," Economics Working Paper Series 1212, University of St. Gallen, School of Economics and Political Science.

    Cited by:

    1. Will Dobbie & Jae Song, 2015. "Debt Relief and Debtor Outcomes: Measuring the Effects of Consumer Bankruptcy Protection," American Economic Review, American Economic Association, vol. 105(3), pages 1272-1311, March.
    2. de Chaisemartin, Clement, 2013. "Defying the LATE? Identification of local treatment effects when the instrument violates monotonicity," The Warwick Economics Research Paper Series (TWERPS) 1020, University of Warwick, Department of Economics.
    3. Clément de Chaisemartin & Xavier d'Haultfoeuille, 2012. "Late Again with Defiers," Working Papers halshs-00699646, HAL.
    4. Fiorini, Mario & Katrien Stevens, 2014. "Assessing the Monotonicity Assumption in IV and fuzzy RD designs," Working Papers 2014-13, University of Sydney, School of Economics.
    5. de Chaisemartin, Clement, 2013. "Defying the LATE? Identication of local treatment eects when the instrument violates monotonicity," Economic Research Papers 270439, University of Warwick - Department of Economics.
    6. Clément de Chaisemartin, 2012. "Late again, whithout Monotonicity," Working Papers 2012-12, Center for Research in Economics and Statistics.
    7. Clément de Chaisemartin & Xavier d'Haultfoeuille, 2012. "Late Again with Defiers," PSE Working Papers halshs-00699646, HAL.

  5. Giovanni Mellace & Roberto Rocci, 2011. "Principal Stratification in sample selection problems with non normal error terms," CEIS Research Paper 194, Tor Vergata University, CEIS, revised 02 May 2011.

    Cited by:

    1. Martin Huber & Giovanni Mellace, 2015. "Sharp Bounds on Causal Effects under Sample Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(1), pages 129-151, February.

  6. Huber, Martin & Mellace, Giovanni, 2011. "Sharp bounds on causal effects under sample selection," Economics Working Paper Series 1134, University of St. Gallen, School of Economics and Political Science.

    Cited by:

    1. Huber, Martin & Melly, Blaise, 2011. "Quantile Regression in the Presence of Sample Selection," Economics Working Paper Series 1109, University of St. Gallen, School of Economics and Political Science.
    2. Possebom, Vitor, 2018. "Sharp bounds on the MTE with sample selection," MPRA Paper 89785, University Library of Munich, Germany.
    3. Martin Huber & Giovanni Mellace, 2010. "Sharp IV bounds on average treatment effects under endogeneity and noncompliance," University of St. Gallen Department of Economics working paper series 2010 2010-31, Department of Economics, University of St. Gallen.
    4. Blanco, German & Chen, Xuan & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2018. "Bounds on Average and Quantile Treatment Effects on Duration Outcomes under Censoring, Selection, and Noncompliance," GLO Discussion Paper Series 288, Global Labor Organization (GLO).

  7. Huber, Martin & Mellace, Giovanni, 2011. "Testing instrument validity for LATE identification based on inequality moment constraints," Economics Working Paper Series 1143, University of St. Gallen, School of Economics and Political Science.

    Cited by:

    1. Guber, Raphael, 2018. "Instrument Validity Tests with Causal Trees: With an Application to the Same-sex Instrument," MEA discussion paper series 201805, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    2. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    3. Kline, Patrick & Walters, Christopher, 2014. "Evaluating Public Programs with Close Substitutes: The Case of Head Start," Institute for Research on Labor and Employment, Working Paper Series qt43s9211b, Institute of Industrial Relations, UC Berkeley.
    4. Ismael Mourifié & Yuanyuan Wan, 2017. "Testing Local Average Treatment Effect Assumptions," The Review of Economics and Statistics, MIT Press, vol. 99(2), pages 305-313, May.
    5. Darío Tortarolo, 2014. "Female Labor Supply and Fertility. Causal Evidence for Latin America," CEDLAS, Working Papers 0166, CEDLAS, Universidad Nacional de La Plata.
    6. Patrick Kline & Christopher R. Walters, 2018. "On Heckits, LATE, and Numerical Equivalence," CESifo Working Paper Series 6994, CESifo Group Munich.
    7. Frölich, Markus & Huber, Martin, 2014. "Direct and Indirect Treatment Effects: Causal Chains and Mediation Analysis with Instrumental Variables," IZA Discussion Papers 8280, Institute of Labor Economics (IZA).
    8. Francis DiTraglia & Camilo García-Jimeno, 2016. "A Framework for Eliciting, Incorporating, and Disciplining Identification Beliefs in Linear Models," NBER Working Papers 22621, National Bureau of Economic Research, Inc.
    9. Huber, Martin, 2019. "An introduction to flexible methods for policy evaluation," FSES Working Papers 504, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    10. Fricke, Hans & Frölich, Markus & Huber, Martin & Lechner, Michael, 2015. "Endogeneity and non-response bias in treatment evaluation - nonparametric identification of causal effects by instruments," FSES Working Papers 459, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    11. Bolzern, Benjamin & Huber, Martin, 2017. "Testing the validity of the compulsory schooling law instrument," FSES Working Papers 480, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    12. Markus Frölich & Martin Huber, 2014. "Treatment Evaluation With Multiple Outcome Periods Under Endogeneity and Attrition," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1697-1711, December.
    13. Martin Huber, 2019. "An introduction to flexible methods for policy evaluation," Papers 1910.00641, arXiv.org.
    14. Christina Felfe & Martin Huber, 2017. "Does preschool boost the development of minority children?: the case of Roma children," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 475-502, February.
    15. María Angelica Bautista & Felipe González & Luis R. Martínez & Pablo Muñoz & Mounu Prem, 2018. "The Geography of Repression and Support for Democracy: Evidence from the Pinochet Dictatorship," Working papers 5, Red Investigadores de Economía.
    16. James Bisbee & Rajeev Dehejia & Cristian Pop-Eleches & Cyrus Samii, 2015. "Local Instruments, Global Extrapolation: External Validity of the Labor Supply-Fertility Local Average Treatment Effect," NBER Working Papers 21663, National Bureau of Economic Research, Inc.
    17. Sarnetzki, Florian & Dzemski, Andreas, 2014. "Overidentification test in a nonparametric treatment model with unobserved heterogeneity," Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100620, Verein für Socialpolitik / German Economic Association.
    18. G. Brunello & M. Fort & G. Weber & C. T. Weiss, 2013. "Testing the Internal Validity of Compulsory School Reforms as Instrument for Years of Schooling," Working Papers wp911, Dipartimento Scienze Economiche, Universita' di Bologna.
    19. Huber, Martin & Mellace, Giovanni, 2011. "Testing instrument validity in sample selection models," Economics Working Paper Series 1145, University of St. Gallen, School of Economics and Political Science.
    20. Joeri Smits & Jeffrey S. Racine, 2013. "Testing Exclusion Restrictions in Nonseparable Triangular Models," Department of Economics Working Papers 2013-02, McMaster University.
    21. Machado, Cecilia & Shaikh, Azeem M. & Vytlacil, Edward J., 2019. "Instrumental variables and the sign of the average treatment effect," Journal of Econometrics, Elsevier, vol. 212(2), pages 522-555.
    22. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    23. Blaise Melly und Kaspar Wüthrich, 2016. "Local quantile treatment effects," Diskussionsschriften dp1605, Universitaet Bern, Departement Volkswirtschaft.
    24. Magne Mogstad & Andres Santos & Alexander Torgovitsky, 2017. "Using Instrumental Variables for Inference about Policy Relevant Treatment Effects," NBER Working Papers 23568, National Bureau of Economic Research, Inc.
    25. Martin Huber & Giovanni Mellace, 2014. "Testing exclusion restrictions and additive separability in sample selection models," Empirical Economics, Springer, vol. 47(1), pages 75-92, August.
    26. Linbo Wang & James M. Robins & Thomas S. Richardson, 2017. "On falsification of the binary instrumental variable model," Biometrika, Biometrika Trust, vol. 104(1), pages 229-236.
    27. Toru Kitagawa, 2013. "A bootstrap test for instrument validity in heterogeneous treatment effect models," CeMMAP working papers CWP53/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    28. Eckhoff Andresen, Martin & Huber, Martin, 2018. "Instrument-based estimation with binarized treatments: Issues and tests for the exclusion restriction," FSES Working Papers 492, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    29. Lukas Laffers & Giovanni Mellace, 2017. "A note on testing instrument validity for the identification of LATE," Empirical Economics, Springer, vol. 53(3), pages 1281-1286, November.
    30. Dahl, Christian M. & Huber, Martin & Mellace, Giovanni, 2017. "It's never too LATE: A new look at local average treatment effects with or without defiers," Discussion Papers of Business and Economics 2/2017, University of Southern Denmark, Department of Business and Economics.

  8. Martin Huber & Giovanni Mellace, 2010. "Sharp IV bounds on average treatment effects under endogeneity and noncompliance," University of St. Gallen Department of Economics working paper series 2010 2010-31, Department of Economics, University of St. Gallen.

    Cited by:

    1. Huber, Martin, 2012. "Statistical verification of a natural "natural experiment": Tests and sensitivity checks for the sibling sex ratio instrument," Economics Working Paper Series 1219, University of St. Gallen, School of Economics and Political Science.
    2. Amanda E. Kowalski, 2016. "Doing More When You're Running LATE: Applying Marginal Treatment Effect Methods to Examine Treatment Effect Heterogeneity in Experiments," NBER Working Papers 22363, National Bureau of Economic Research, Inc.
    3. Steinmayr, Andreas, 2014. "When a random sample is not random: Bounds on the effect of migration on household members left behind," Kiel Working Papers 1975, Kiel Institute for the World Economy (IfW).
    4. Laffers, Lukas & Mellace, Giovanni, 2015. "A Note on Testing the LATE Assumptions," Discussion Papers of Business and Economics 4/2015, University of Southern Denmark, Department of Business and Economics.
    5. Huber, Martin & Mellace, Giovanni, 2012. "Relaxing monotonicity in the identification of local average treatment effects," Economics Working Paper Series 1212, University of St. Gallen, School of Economics and Political Science.
    6. Martin Huber & Giovanni Mellace, 2015. "Testing Instrument Validity for LATE Identification Based on Inequality Moment Constraints," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 398-411, May.
    7. Chen, Xuan & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2015. "Going Beyond LATE: Bounding Average Treatment Effects of Job Corps Training," IZA Discussion Papers 9511, Institute of Labor Economics (IZA).
    8. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    9. Amanda E. Kowalski, 2016. "Doing More When You're Running LATE: Applying Marginal Treatment Effect Methods to Examine Treatment Effect Heterogeneity in Experiments for the Young and Privately Insured?," Cowles Foundation Discussion Papers 2045, Cowles Foundation for Research in Economics, Yale University.

Articles

  1. Martin Huber & Lukas Laffers & Giovanni Mellace, 2017. "Sharp IV Bounds on Average Treatment Effects on the Treated and Other Populations Under Endogeneity and Noncompliance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 56-79, January.

    Cited by:

    1. Christelis, Dimitris & Messina, Julián, 2019. "Partial Identification of Population Average and Quantile Treatment Effects in Observational Data under Sample Selection," IDB Publications (Working Papers) 9520, Inter-American Development Bank.
    2. Huber Martin & Wüthrich Kaspar, 2019. "Local Average and Quantile Treatment Effects Under Endogeneity: A Review," Journal of Econometric Methods, De Gruyter, vol. 8(1), pages 1-27, January.
    3. Possebom, Vitor, 2018. "Sharp bounds on the MTE with sample selection," MPRA Paper 89785, University Library of Munich, Germany.
    4. Chen, Xuan & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2015. "Going Beyond LATE: Bounding Average Treatment Effects of Job Corps Training," IZA Discussion Papers 9511, Institute of Labor Economics (IZA).
    5. Amanda E. Kowalski, 2018. "Extrapolation using Selection and Moral Hazard Heterogeneity from within the Oregon Health Insurance Experiment," Cowles Foundation Discussion Papers 2135, Cowles Foundation for Research in Economics, Yale University.
    6. Lukáš Lafférs, 2019. "Identification in Models with Discrete Variables," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 657-696, February.

  2. Lukas Laffers & Giovanni Mellace, 2017. "A note on testing instrument validity for the identification of LATE," Empirical Economics, Springer, vol. 53(3), pages 1281-1286, November.

    Cited by:

    1. Guber, Raphael, 2018. "Instrument Validity Tests with Causal Trees: With an Application to the Same-sex Instrument," MEA discussion paper series 201805, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.

  3. Martin Huber & Michael Lechner & Giovanni Mellace, 2017. "Why Do Tougher Caseworkers Increase Employment? The Role of Program Assignment as a Causal Mechanism," The Review of Economics and Statistics, MIT Press, vol. 99(1), pages 180-183, March.
    See citations under working paper version above.
  4. Martin Huber & Michael Lechner & Giovanni Mellace, 2016. "The Finite Sample Performance of Estimators for Mediation Analysis Under Sequential Conditional Independence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 139-160, January.
    See citations under working paper version above.
  5. Martin Huber & Giovanni Mellace, 2015. "Sharp Bounds on Causal Effects under Sample Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(1), pages 129-151, February.
    See citations under working paper version above.
  6. Martin Huber & Giovanni Mellace, 2015. "Testing Instrument Validity for LATE Identification Based on Inequality Moment Constraints," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 398-411, May.
    See citations under working paper version above.
  7. Martin Huber & Giovanni Mellace, 2014. "Testing exclusion restrictions and additive separability in sample selection models," Empirical Economics, Springer, vol. 47(1), pages 75-92, August.

    Cited by:

    1. Harry Anthony Patrinos & George Psacharopoulos & Aysit Tansel, 2019. "Returns to Investment in Education: The Case of Turkey," Koç University-TUSIAD Economic Research Forum Working Papers 1906, Koc University-TUSIAD Economic Research Forum.
    2. Maasoumi, Esfandiar & Wang, Le, 2017. "What can we learn about the racial gap in the presence of sample selection?," Journal of Econometrics, Elsevier, vol. 199(2), pages 117-130.
    3. Antonio Paolo & Aysit Tansel, 2019. "English skills, labour market status and earnings of Turkish women," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(4), pages 669-690, November.
    4. Töpfer, Marina & Castagnetti, Carolina & Rosti, Luisa, 2016. "Discriminate me - if you can! The Disappearance of the Gender Pay Gap among Public-Contest Selected Employees," Annual Conference 2016 (Augsburg): Demographic Change 145905, Verein für Socialpolitik / German Economic Association.
    5. Andrew Beauchamp & Geoffrey Sanzenbacher & Shannon Seitz & Meghan Skira, 2014. "Deadbeat Dads," Boston College Working Papers in Economics 859, Boston College Department of Economics.
    6. Frölich, Markus & Huber, Martin, 2014. "Direct and Indirect Treatment Effects: Causal Chains and Mediation Analysis with Instrumental Variables," IZA Discussion Papers 8280, Institute of Labor Economics (IZA).
    7. Jacobs, Josephine C. & Van Houtven, Courtney H. & Laporte, Audrey & Coyte, Peter C., 2015. "Baby Boomer caregivers in the workforce: Do they fare better or worse than their predecessors?," The Journal of the Economics of Ageing, Elsevier, vol. 6(C), pages 89-101.
    8. Biavaschi, Costanza, 2016. "Recovering the counterfactual wage distribution with selective return migration," Labour Economics, Elsevier, vol. 38(C), pages 59-80.
    9. Chunbei Wang & Le Wang, 2017. "Knot yet: minimum marriage age law, marriage delay, and earnings," Journal of Population Economics, Springer;European Society for Population Economics, vol. 30(3), pages 771-804, July.
    10. Harry Anthony Patrinos & George Psacharopoulos & Aysit Tansel, 2019. "GLOBALISATION AND GOVERNANCE: Returns to Investment in Education: The Case of Turkey," ERC Working Papers 1903, ERC - Economic Research Center, Middle East Technical University, revised Mar 2019.
    11. Dhamija, Gaurav & Roychowdhury, Punarjit, 2018. "The impact of women's age at marriage on own and spousal labor market outcomes in India: causation or selection?," MPRA Paper 86686, University Library of Munich, Germany.
    12. Dante Contreras & Roberto Gillmore & Esteban Puentes, 2017. "Self‐Employment and Queues for Wage Work: Evidence from Chile," Journal of International Development, John Wiley & Sons, Ltd., vol. 29(4), pages 473-499, May.

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 14 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (10) 2010-11-27 2011-05-14 2011-08-29 2011-11-14 2012-01-03 2012-05-22 2014-06-22 2015-03-13 2017-02-26 2018-01-15. Author is listed
  2. NEP-ORE: Operations Research (2) 2017-02-26 2018-01-15
  3. NEP-CMP: Computational Economics (1) 2014-06-22
  4. NEP-EEC: European Economics (1) 2019-10-28
  5. NEP-ENT: Entrepreneurship (1) 2019-09-09
  6. NEP-EUR: Microeconomic European Issues (1) 2019-09-09
  7. NEP-HEA: Health Economics (1) 2016-08-21
  8. NEP-INO: Innovation (1) 2019-09-09
  9. NEP-LAB: Labour Economics (1) 2014-06-14
  10. NEP-TID: Technology & Industrial Dynamics (1) 2019-09-09

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