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Luisa Scaccia

Personal Details

First Name:Luisa
Middle Name:
Last Name:Scaccia
Suffix:
RePEc Short-ID:psc557
http://docenti.unimc.it/docenti/luisa-scaccia/

Affiliation

Facoltà di Economia e Diritto
Università degli Studi di Macerata

Macerata, Italy
http://www.economia.unimc.it/

: +39 0733.258.2721
+39 0733.258.2737
Via Crescimbeni, 20 - 62100 Macerata
RePEc:edi:fsmacit (more details at EDIRC)

Research output

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Jump to: Working papers Articles

Working papers

  1. Valerio Gatta & Edoardo Marcucci & Luisa Scaccia, 2014. "Willingness To Pay Confidence Interval Estimation Methods: Comparisons And Extensions," Working Papers 0314, CREI Università degli Studi Roma Tre, revised 2014.
  2. Rosella Castellano & Luisa Scaccia, 2007. "Bayesian inference for Hidden Markov Model," Working Papers 43-2007, Macerata University, Department of Finance and Economic Sciences, revised Oct 2008.
  3. Bartolucci Francesco & Mira Antonietta & Scaccia Luisa, 2003. "Bayesian inference for Latent Class model via MCMC with application to capture-recapture data," Economics and Quantitative Methods qf0303, Department of Economics, University of Insubria.

Articles

  1. Francesco Bartolucci & Alessio Farcomeni & Luisa Scaccia, 2017. "A Nonparametric Multidimensional Latent Class IRT Model in a Bayesian Framework," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 952-978, December.
  2. Gatta, Valerio & Marcucci, Edoardo & Scaccia, Luisa, 2015. "On finite sample performance of confidence intervals methods for willingness to pay measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 169-192.
  3. Marcucci, Edoardo & Gatta, Valerio & Scaccia, Luisa, 2015. "Urban freight, parking and pricing policies: An evaluation from a transport providers’ perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 239-249.
  4. Rosella Castellano & Luisa Scaccia, 2014. "Can CDS indexes signal future turmoils in the stock market? A Markov switching perspective," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(2), pages 285-305, June.
  5. Bartolucci, Francesco & Scaccia, Luisa & Farcomeni, Alessio, 2012. "Bayesian inference through encompassing priors and importance sampling for a class of marginal models for categorical data," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4067-4080.
  6. Francesco Bartolucci & Luisa Scaccia & Antonietta Mira, 2006. "Efficient Bayes factor estimation from the reversible jump output," Biometrika, Biometrika Trust, vol. 93(1), pages 41-52, March.
  7. Bartolucci, F. & Scaccia, L., 2005. "The use of mixtures for dealing with non-normal regression errors," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 821-834, April.
  8. Marcucci, Edoardo & Scaccia, Luisa, 2004. "Mode choice models with attribute cutoffs analysis: the case of freight transport in the Marche region," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 25-26, pages 21-32.
  9. Bartolucci, F. & Scaccia, L., 2004. "Testing for positive association in contingency tables with fixed margins," Computational Statistics & Data Analysis, Elsevier, vol. 47(1), pages 195-210, 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. Valerio Gatta & Edoardo Marcucci & Luisa Scaccia, 2014. "Willingness To Pay Confidence Interval Estimation Methods: Comparisons And Extensions," Working Papers 0314, CREI Università degli Studi Roma Tre, revised 2014.

    Cited by:

    1. Gatta, Valerio & Marcucci, Edoardo & Scaccia, Luisa, 2015. "On finite sample performance of confidence intervals methods for willingness to pay measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 169-192.

Articles

  1. Gatta, Valerio & Marcucci, Edoardo & Scaccia, Luisa, 2015. "On finite sample performance of confidence intervals methods for willingness to pay measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 169-192.

    Cited by:

    1. Marcucci, Edoardo & Le Pira, Michela & Gatta, Valerio & Inturri, Giuseppe & Ignaccolo, Matteo & Pluchino, Alessandro, 2017. "Simulating participatory urban freight transport policy-making: Accounting for heterogeneous stakeholders’ preferences and interaction effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 69-86.
    2. Juan Gabriel Brida & Juan Carlos Martín & Concepción Román & Raffaele Scuderi, 2017. "Air and HST Multimodal Products. A Segmentation Analysis for Policy Makers," Networks and Spatial Economics, Springer, vol. 17(3), pages 911-934, September.
    3. Shams, Kollol & Asgari, Hamidreza & Jin, Xia, 2017. "Valuation of travel time reliability in freight transportation: A review and meta-analysis of stated preference studies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 228-243.
    4. Marcucci, Edoardo & Gatta, Valerio, 2017. "Investigating the potential for off-hour deliveries in the city of Rome: Retailers’ perceptions and stated reactions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 142-156.
    5. Yang, Chih-Wen & Liao, Pei-Han, 2016. "Modeling the joint choice of access modes and flight routes with parallel structure and random heterogeneity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 19-31.

  2. Marcucci, Edoardo & Gatta, Valerio & Scaccia, Luisa, 2015. "Urban freight, parking and pricing policies: An evaluation from a transport providers’ perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 239-249.

    Cited by:

    1. Holguín-Veras, José & Wang, Xiaokun (Cara) & Sánchez-Díaz, Iván & Campbell, Shama & Hodge, Stacey D. & Jaller, Miguel & Wojtowicz, Jeffrey, 2017. "Fostering unassisted off-hour deliveries: The role of incentives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 172-187.
    2. Marcucci, Edoardo & Le Pira, Michela & Gatta, Valerio & Inturri, Giuseppe & Ignaccolo, Matteo & Pluchino, Alessandro, 2017. "Simulating participatory urban freight transport policy-making: Accounting for heterogeneous stakeholders’ preferences and interaction effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 69-86.
    3. dell’Olio, Luigi & Moura, Jose Luis & Ibeas, Angel & Cordera, Ruben & Holguin-Veras, Jose, 2017. "Receivers’ willingness-to-adopt novel urban goods distribution practices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 130-141.
    4. Nourinejad, Mehdi & Roorda, Matthew J., 2017. "Impact of hourly parking pricing on travel demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 98(C), pages 28-45.
    5. de Abreu e Silva, João & Alho, André Romano, 2017. "Using Structural Equations Modeling to explore perceived urban freight deliveries parking issues," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 18-32.
    6. Holguín-Veras, José & Amaya Leal, Johanna & Seruya, Barbara B., 2017. "Urban freight policymaking: The role of qualitative and quantitative research," Transport Policy, Elsevier, vol. 56(C), pages 75-85.
    7. Marcucci, Edoardo & Gatta, Valerio, 2017. "Investigating the potential for off-hour deliveries in the city of Rome: Retailers’ perceptions and stated reactions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 142-156.
    8. Amer, Ahmed & Chow, Joseph Y.J., 2017. "A downtown on-street parking model with urban truck delivery behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 51-67.
    9. Budak, Aysenur & Ustundag, Alp & Guloglu, Bulent, 2017. "A forecasting approach for truckload spot market pricing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 55-68.
    10. Francesco Russo & Antonio Comi, 2016. "Urban Freight Transport Planning towards Green Goals: Synthetic Environmental Evidence from Tested Results," Sustainability, MDPI, Open Access Journal, vol. 8(4), pages 1-18, April.
    11. Román, Concepción & Arencibia, Ana Isabel & Feo-Valero, María, 2017. "A latent class model with attribute cut-offs to analyze modal choice for freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 212-227.
    12. Gatta, Valerio & Marcucci, Edoardo & Scaccia, Luisa, 2015. "On finite sample performance of confidence intervals methods for willingness to pay measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 169-192.

  3. Rosella Castellano & Luisa Scaccia, 2014. "Can CDS indexes signal future turmoils in the stock market? A Markov switching perspective," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(2), pages 285-305, June.

    Cited by:

    1. Marcel Ausloos & Rosella Castellano & Roy Cerqueti, 2016. "Regularities and Discrepancies of Credit Default Swaps: a Data Science approach through Benford's Law," Papers 1603.01103, arXiv.org.
    2. Consiglio, Andrea & Tumminello, Michele & Zenios, Stavros A., 2016. "Pricing Sovereign Contingent Convertible Debt," Working Papers 16-05, University of Pennsylvania, Wharton School, Weiss Center.
    3. Sinan Esen & Feyyaz Zeren & Halil Şimdi, 2015. "CDS and Stock Market: Panel Evidence Under Cross-Section Dependency," South-Eastern Europe Journal of Economics, Association of Economic Universities of South and Eastern Europe and the Black Sea Region, vol. 13(1), pages 31-46.
    4. Shahzad, Syed Jawad Hussain & Mensi, Walid & Hammoudeh, Shawkat & Balcilar, Mehmet & Shahbaz, Muhammad, 2018. "Distribution specific dependence and causality between industry-level U.S. credit and stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 114-133.
    5. Andrea Consiglio & Michele Tumminello & Stavros A. Zenios, 2018. "Pricing sovereign contingent convertible debt," Papers 1804.01475, arXiv.org.

  4. Bartolucci, Francesco & Scaccia, Luisa & Farcomeni, Alessio, 2012. "Bayesian inference through encompassing priors and importance sampling for a class of marginal models for categorical data," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4067-4080.

    Cited by:

    1. Alan Agresti, 2014. "Two Bayesian/frequentist challenges for categorical data analyses," METRON, Springer;Sapienza Università di Roma, vol. 72(2), pages 125-132, August.
    2. Guido Consonni & Roberta Paroli, 2017. "Objective Bayesian Comparison of Constrained Analysis of Variance Models," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 589-609, September.
    3. Linda J. Young & M. Kateri & A. Agresti, 2013. "Bayesian inference about odds ratio structure in ordinal contingency tables," Environmetrics, John Wiley & Sons, Ltd., vol. 24(5), pages 281-288, August.
    4. Ntzoufras, Ioannis & Tarantola, Claudia, 2013. "Conjugate and conditional conjugate Bayesian analysis of discrete graphical models of marginal independence," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 161-177.
    5. Andrea Boitani & Chiara Punzo, 2018. "Banks’ leverage behaviour in a two-agent New Keynesian model," DISCE - Working Papers del Dipartimento di Economia e Finanza def063, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    6. Lorenza Rossi & Emilio Zanetti Chini, 2017. "Firms' Dynamics and Business Cycle: New Disaggregated Data," DEM Working Papers Series 141, University of Pavia, Department of Economics and Management.
    7. Francesco Bartolucci & Alessio Farcomeni & Luisa Scaccia, 2017. "A Nonparametric Multidimensional Latent Class IRT Model in a Bayesian Framework," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 952-978, December.
    8. Gordon Anderson & Alessio Farcomeni & Maria Grazia Pittau & Roberto Zelli, 2018. "Multidimensional Nation Wellbeing, More Equal yet More Polarized: An Analysis of the Progress of Human Development since 1990," Working Papers tecipa-602, University of Toronto, Department of Economics.
    9. Ioannis Ntzoufras & Claudia Tarantola & Monia Lupparelli, 2018. "Probability Based Independence Sampler for Bayesian Quantitative Learning in Graphical Log-Linear Marginal Models," DEM Working Papers Series 149, University of Pavia, Department of Economics and Management.

  5. Francesco Bartolucci & Luisa Scaccia & Antonietta Mira, 2006. "Efficient Bayes factor estimation from the reversible jump output," Biometrika, Biometrika Trust, vol. 93(1), pages 41-52, March.

    Cited by:

    1. Rufo, M.J. & Martín, J. & Pérez, C.J., 2010. "New approaches to compute Bayes factor in finite mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3324-3335, December.
    2. David I. Hastie & Peter J. Green, 2012. "Model choice using reversible jump Markov chain Monte Carlo," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(3), pages 309-338, August.
    3. Pandolfi, Silvia & Bartolucci, Francesco & Friel, Nial, 2014. "A generalized multiple-try version of the Reversible Jump algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 298-314.
    4. Shotwell Matthew S & Slate Elizabeth H, 2010. "Bayesian Modeling of Footrace Finishing Times," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(3), pages 1-21, July.
    5. N. Friel & A. N. Pettitt, 2008. "Marginal likelihood estimation via power posteriors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(3), pages 589-607.
    6. Nicolas Chopin & Christian P. Robert, 2010. "Properties of nested sampling," Biometrika, Biometrika Trust, vol. 97(3), pages 741-755.

  6. Bartolucci, F. & Scaccia, L., 2005. "The use of mixtures for dealing with non-normal regression errors," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 821-834, April.

    Cited by:

    1. Maria Karlsson & Thomas Laitila, 2014. "Finite mixture modeling of censored regression models," Statistical Papers, Springer, vol. 55(3), pages 627-642, August.
    2. Hu, Hao & Yao, Weixin & Wu, Yichao, 2017. "The robust EM-type algorithms for log-concave mixtures of regression models," Computational Statistics & Data Analysis, Elsevier, vol. 111(C), pages 14-26.
    3. Galimberti, Giuliano & Soffritti, Gabriele, 2014. "A multivariate linear regression analysis using finite mixtures of t distributions," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 138-150.
    4. Wang, Shangshan & Xiang, Liming, 2017. "Two-layer EM algorithm for ALD mixture regression models: A new solution to composite quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 136-154.
    5. Usta, Ilhan & Kantar, Yeliz Mert, 2011. "On the performance of the flexible maximum entropy distributions within partially adaptive estimation," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2172-2182, June.
    6. Steven Caudill & James Long, 2010. "Do former athletes make better managers? Evidence from a partially adaptive grouped-data regression model," Empirical Economics, Springer, vol. 39(1), pages 275-290, August.
    7. Katherine G. Yewell & Steven B. Caudill & Franklin G. Mixon, Jr., 2014. "Referee Bias and Stoppage Time in Major League Soccer: A Partially Adaptive Approach," Econometrics, MDPI, Open Access Journal, vol. 2(1), pages 1-19, February.
    8. Steven Caudill, 2012. "A partially adaptive estimator for the censored regression model based on a mixture of normal distributions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(2), pages 121-137, June.
    9. 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.
    10. Islam, Tanweer ul, 2008. "Normality Testing- A New Direction," MPRA Paper 16452, University Library of Munich, Germany.

  7. Marcucci, Edoardo & Scaccia, Luisa, 2004. "Mode choice models with attribute cutoffs analysis: the case of freight transport in the Marche region," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 25-26, pages 21-32.

    Cited by:

    1. Shams, Kollol & Asgari, Hamidreza & Jin, Xia, 2017. "Valuation of travel time reliability in freight transportation: A review and meta-analysis of stated preference studies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 228-243.
    2. Zhang, Rong & Zhu, Lichao, 2016. "Curbside parking pricing in a city centre using a threshold," Transport Policy, Elsevier, vol. 52(C), pages 16-27.
    3. Marcucci, Edoardo & Gatta, Valerio, 2017. "Investigating the potential for off-hour deliveries in the city of Rome: Retailers’ perceptions and stated reactions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 142-156.
    4. Arencibia, Ana Isabel & Feo-Valero, María & García-Menéndez, Leandro & Román, Concepción, 2015. "Modelling mode choice for freight transport using advanced choice experiments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 252-267.
    5. María Feo-Valero & Leandro García-Menéndez & Salvador Saz-Salazar, 2016. "Rail freight transport and demand requirements: an analysis of attribute cut-offs through a stated preference experiment," Transportation, Springer, vol. 43(1), pages 101-122, January.
    6. Román, Concepción & Arencibia, Ana Isabel & Feo-Valero, María, 2017. "A latent class model with attribute cut-offs to analyze modal choice for freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 212-227.
    7. María Feo-Valero & Leandro García-Menéndez & Salvador del Saz-Salazar, 2016. "Rail freight transport and demand requirements: an analysis of attribute cut-offs through a stated preference experiment," Transportation, Springer, vol. 43(1), pages 101-122, January.

  8. Bartolucci, F. & Scaccia, L., 2004. "Testing for positive association in contingency tables with fixed margins," Computational Statistics & Data Analysis, Elsevier, vol. 47(1), pages 195-210, August.

    Cited by:

    1. Ivy Liu & Alan Agresti, 2005. "The analysis of ordered categorical data: An overview and a survey of recent developments," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 14(1), pages 1-73, June.
    2. Alan Agresti, 2014. "Two Bayesian/frequentist challenges for categorical data analyses," METRON, Springer;Sapienza Università di Roma, vol. 72(2), pages 125-132, August.
    3. Manuela Cazzaro & Roberto Colombi, 2006. "Maximum Likelihood Inference for Log-linear Models Subject to Constraints of Double Monotone Dependence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 15(2), pages 177-190, August.
    4. Manuela Cazzaro & Roberto Colombi, 2006. "Maximum Likelihood Inference for Log-linear Models Subject to Constraints of Double Monotone Dependence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 15(2), pages 177-190, August.
    5. Linda J. Young & M. Kateri & A. Agresti, 2013. "Bayesian inference about odds ratio structure in ordinal contingency tables," Environmetrics, John Wiley & Sons, Ltd., vol. 24(5), pages 281-288, August.
    6. Bartolucci, Francesco & Scaccia, Luisa & Farcomeni, Alessio, 2012. "Bayesian inference through encompassing priors and importance sampling for a class of marginal models for categorical data," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4067-4080.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

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 3 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 (3) 2003-05-12 2008-11-25 2015-05-02
  2. NEP-DCM: Discrete Choice Models (1) 2015-05-02

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