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Carlos Brunet Martins-Filho

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. Mynbayev, Kairat & Martins-Filho, Carlos, 2017. "Unified estimation of densities on bounded and unbounded domains," MPRA Paper 87044, University Library of Munich, Germany, revised Jan 2018.

    Cited by:

    1. Martins-Filho, Carlos & Xie, Sihong & Yao, Feng, 2022. "A new estimator of a jump discontinuity in regression," Economics Letters, Elsevier, vol. 218(C).

  2. Mynbaev, Kairat & Martins-Filho, Carlos & Aipenova, Aziza, 2015. "A class of nonparametric density derivative estimators based on global Lipschitz conditions," MPRA Paper 75909, University Library of Munich, Germany, revised 2014.

    Cited by:

    1. Mynbayev, Kairat & Martins-Filho, Carlos, 2017. "Unified estimation of densities on bounded and unbounded domains," MPRA Paper 87044, University Library of Munich, Germany, revised Jan 2018.

  3. Carlos Martins-Filho & Feng Yao & Maximo Torero, 2012. "Nonparametric estimation of conditional value-at-risk and expected shortfall based on extreme value theory," Working Papers 13-05, Department of Economics, West Virginia University.

    Cited by:

    1. Gery Geenens & Richard Dunn, 2017. "A nonparametric copula approach to conditional Value-at-Risk," Papers 1712.05527, arXiv.org, revised Oct 2019.
    2. Wilson Calmon & Eduardo Ferioli & Davi Lettieri & Johann Soares & Adrian Pizzinga, 2021. "An Extensive Comparison of Some Well‐Established Value at Risk Methods," International Statistical Review, International Statistical Institute, vol. 89(1), pages 148-166, April.
    3. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    4. Daouia, Abdelaati & Stupfler, Gilles & Usseglio-Carleve, Antoine, 2022. "Inference for extremal regression with dependent heavy-tailed data," TSE Working Papers 22-1324, Toulouse School of Economics (TSE), revised 29 Aug 2023.
    5. Carlos Martins-Filho & Feng Yao & Maximo Torero, 2012. "Nonparametric estimation of conditional value-at-risk and expected shortfall based on extreme value theory," Working Papers 13-05, Department of Economics, West Virginia University.
    6. Cui, Zhenyu & Kirkby, J. Lars & Nguyen, Duy, 2021. "A data-driven framework for consistent financial valuation and risk measurement," European Journal of Operational Research, Elsevier, vol. 289(1), pages 381-398.
    7. Katerina Rigana & Ernst C. Wit & Samantha Cook, 2024. "Navigating Market Turbulence: Insights from Causal Network Contagion Value at Risk," Papers 2402.06032, arXiv.org.
    8. Stéphane Girard & Gilles Claude Stupfler & Antoine Usseglio-Carleve, 2021. "Extreme Conditional Expectile Estimation in Heavy-Tailed Heteroscedastic Regression Models," Post-Print hal-03306230, HAL.
    9. Julia S. Mehlitz & Benjamin R. Auer, 2021. "Time‐varying dynamics of expected shortfall in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 895-925, June.
    10. Dingshi Tian & Zongwu Cai & Ying Fang, 2018. "Econometric Modeling of Risk Measures: A Selective Review of the Recent Literature," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201807, University of Kansas, Department of Economics, revised Oct 2018.
    11. Yuya Sasaki & Yulong Wang, 2022. "Fixed-k Inference for Conditional Extremal Quantiles," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(2), pages 829-837, April.
    12. Yannick Hoga, 2023. "The Estimation Risk in Extreme Systemic Risk Forecasts," Papers 2304.10349, arXiv.org.
    13. Nicola Loperfido & Tomer Shushi, 2023. "Optimal Portfolio Projections for Skew-Elliptically Distributed Portfolio Returns," Journal of Optimization Theory and Applications, Springer, vol. 199(1), pages 143-166, October.
    14. Alexander Heinemann & Sean Telg, 2018. "A Residual Bootstrap for Conditional Expected Shortfall," Papers 1811.11557, arXiv.org.
    15. Athanasios Triantafyllou & George Dotsis & Alexandros Sarris, 2020. "Assessing the Vulnerability to Price Spikes in Agricultural Commodity Markets," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 631-651, September.
    16. Emmanuel Torsen & Peter N. Mwita & Joseph K. Mungatu, 2018. "Nonparametric Estimation of the Error Functional of a Location-Scale Model," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 7(4), pages 1-1.
    17. Ji Hyung Lee & Yuya Sasaki & Alexis Akira Toda & Yulong Wang, 2021. "Fixed-k Tail Regression: New Evidence on Tax and Wealth Inequality from Forbes 400," Papers 2105.10007, arXiv.org, revised Sep 2022.
    18. Santos, Douglas G. & Candido, Osvaldo & Tófoli, Paula V., 2022. "Forecasting risk measures using intraday and overnight information," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    19. Emmanuel Torsen & Peter N. Mwita & Joseph K. Mung’atu, 2019. "A Three-Step Nonparametric Estimation of Conditional Value-At-Risk Admitting a Location-Scale Model," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 8(4), pages 1-1.
    20. Denis Chetverikov & Yukun Liu & Aleh Tsyvinski, 2022. "Weighted-average quantile regression," Papers 2203.03032, arXiv.org.
    21. Yan Fang & Jian Li & Yinglin Liu & Yunfan Zhao, 2023. "Semiparametric estimation of expected shortfall and its application in finance," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 835-851, July.

  4. R. Fare & C. Martins-Filho & M. Vardanyan, 2010. "On functional form representation of multi-output production technologies," Post-Print hal-00800130, HAL.

    Cited by:

    1. Zhao, Yu & Zhong, Honglin & Kong, Fanbin & Zhang, Ning, 2023. "Can China achieve carbon neutrality without power shortage? A substitutability perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    2. Ni, Jinlan & Wei, Chu & Du, Limin, 2015. "Revealing the political decision toward Chinese carbon abatement: Based on equity and efficiency criteria," Energy Economics, Elsevier, vol. 51(C), pages 609-621.
    3. Gary Ferrier & Herve Leleu & Vivian Valdmanis & Michael Vardanyan, 2017. "A directional distance function approach for identifying the input/output status of medical residents," Post-Print hal-01744641, HAL.
    4. Badau, Flavius & Färe, Rolf & Gopinath, Munisamy, 2016. "Global resilience to climate change: Examining global economic and environmental performance resulting from a global carbon dioxide market," Resource and Energy Economics, Elsevier, vol. 45(C), pages 46-64.
    5. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances II," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 9, pages 371-408, Springer.
    6. Kyohei Matsushita & Kota Asano, 2014. "Reducing CO 2 emissions of Japanese thermal power companies: a directional output distance function approach," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 16(1), pages 1-19, January.
    7. Jamasb, T. & Söderberg, M., 2009. "Yardstick and Ex-post Regulation by Norm Model: Empirical Equivalence, Pricing Effect, and Performance in Sweeden," Cambridge Working Papers in Economics 0908, Faculty of Economics, University of Cambridge.
    8. Géraldine Henningsen & Arne Henningsen & Uwe Jensen, 2013. "A Monte Carlo Study on Multiple Output Stochastic Frontiers: Comparison of Two Approaches," IFRO Working Paper 2013/7, University of Copenhagen, Department of Food and Resource Economics.
    9. Bostian, Moriah B. & Herlihy, Alan T., 2014. "Valuing tradeoffs between agricultural production and wetland condition in the U.S. Mid-Atlantic region," Ecological Economics, Elsevier, vol. 105(C), pages 284-291.
    10. Layer, Kevin & Johnson, Andrew L. & Sickles, Robin C. & Ferrier, Gary D., 2020. "Direction selection in stochastic directional distance functions," European Journal of Operational Research, Elsevier, vol. 280(1), pages 351-364.
    11. Sauer, J. & Walsh, J. & Zilberman, D., 2014. "Agri-Environmental Policy Effects at Producer Level – Identification and Measurement," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 49, March.
    12. Timo Kuosmanen & Sheng Dai, 2023. "Modeling economies of scope in joint production: Convex regression of input distance function," Papers 2311.11637, arXiv.org.
    13. Stern, David I., 2012. "Modeling international trends in energy efficiency," Energy Economics, Elsevier, vol. 34(6), pages 2200-2208.
    14. María Molinos-Senante & Simon Porcher & Alexandros Maziotis, 2018. "Productivity change and its drivers for the Chilean water companies: A comparison of full private and concessionary companies," Post-Print hal-02145824, HAL.
    15. Atakelty Hailu & Robert Chambers, 2012. "A Luenberger soil-quality indicator," Journal of Productivity Analysis, Springer, vol. 38(2), pages 145-154, October.
    16. Mydland, Ørjan & Kumbhakar, Subal C. & Lien, Gudbrand & Amundsveen, Roar & Kvile, Hilde Marit, 2020. "Economies of scope and scale in the Norwegian electricity industry," Economic Modelling, Elsevier, vol. 88(C), pages 39-46.
    17. Molinos-Senante, María & Porcher, Simon & Maziotis, Alexandros, 2017. "Impact of regulation on English and Welsh water-only companies: an input-distance function approach," LSE Research Online Documents on Economics 82972, London School of Economics and Political Science, LSE Library.
    18. Matsushita, Kyohei & Yamane, Fumihiro, 2012. "Pollution from the electric power sector in Japan and efficient pollution reduction," Energy Economics, Elsevier, vol. 34(4), pages 1124-1130.
    19. Nancy H. Chau & Rolf Färe & Shawna Grosskopf, 2013. "Trade Restrictiveness and Pollution," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 15(1), pages 25-52, February.
    20. Aparajita Singh & Haripriya Gundimeda, 2021. "Measuring technical efficiency and shadow price of water pollutants for the leather industry in India: a directional distance function approach," Journal of Regulatory Economics, Springer, vol. 59(1), pages 71-93, February.
    21. Färe, Rolf & Pasurka, Carl & Vardanyan, Michael, 2017. "On endogenizing direction vectors in parametric directional distance function-based models," European Journal of Operational Research, Elsevier, vol. 262(1), pages 361-369.
    22. Bonilla, Jorge & Coria, Jessica & Sterner, Thomas, 2012. "Synergies and Trade-offs between Climate and Local Air Pollution: Policies in Sweden," Working Papers in Economics 529, University of Gothenburg, Department of Economics.
    23. Vardanyan, Michael & Valdmanis, Vivian G. & Leleu, Hervé & Ferrier, Gary D., 2022. "Estimating technology characteristics of the U.S. hospital industry using directional distance functions with optimal directions," Omega, Elsevier, vol. 113(C).
    24. Surender Kumar & Rakesh Kumar Jain, 2018. "Shadow Price of CO 2 Emissions in Indian Thermal Power Sector," Working Papers id:12791, eSocialSciences.
    25. Sauer, Johannes & Walsh, John & Zilberman, David, 2012. "Behavioural Change through Agri-Environmental Policies ? – A Distance Function based Matching Approach," 86th Annual Conference, April 16-18, 2012, Warwick University, Coventry, UK 134783, Agricultural Economics Society.
    26. Surender Kumar & Hidemichi Fujii & Shunsuke Managi, 2014. "Substitute or complement? Assessing renewable and non-renewable energy in OCED countries," Working Papers SDES-2014-8, Kochi University of Technology, School of Economics and Management, revised Oct 2014.
    27. Paolo Guarda & Abdelaziz Rouabah & Michael Vardanyan, 2013. "Identifying bank outputs and inputs with a directional technology distance function," Journal of Productivity Analysis, Springer, vol. 40(2), pages 185-195, October.
    28. Czekaj, Tomasz G., 2015. "Measuring the Technical Efficiency of Farms Producing Environmental Output: Semiparametric Estimation of Multi-output Stochastic Ray Production Frontiers," 2015 Conference, August 9-14, 2015, Milan, Italy 211555, International Association of Agricultural Economists.
    29. Sauer, J. & Latacz-Lohmann, U., 2013. "Efficient Innovation in Dairy Production – Empirical Findings for Germany," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 48, March.
    30. Sauer, J. & Latacz-Lohmann, Uwe, 2013. "Efficient Innovation in Dairy Production - Empirical Findings for Germany," 87th Annual Conference, April 8-10, 2013, Warwick University, Coventry, UK 158865, Agricultural Economics Society.
    31. Badau, Flavius & Rada, Nicholas, 2016. "The Price of Inefficiency in Indian Agriculture," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235622, Agricultural and Applied Economics Association.
    32. Chambers, Robert & Färe, Rolf & Grosskopf, Shawna & Vardanyan, Michael, 2013. "Generalized quadratic revenue functions," Journal of Econometrics, Elsevier, vol. 173(1), pages 11-21.
    33. Huiming Xie & Xiaopeng Wang & Manhong Shen & Chu Wei, 2022. "Abatement costs of combatting industrial water pollution: convergence across Chinese provinces," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(9), pages 10752-10767, September.
    34. Färe, Rolf & Grosskopf, Shawna & Hayes, Kathy J. & Margaritis, Dimitris, 2008. "Estimating demand with distance functions: Parameterization in the primal and dual," Journal of Econometrics, Elsevier, vol. 147(2), pages 266-274, December.
    35. Yang, Jun & Cheng, Jixin & Zou, Ran & Geng, Zhifei, 2021. "Industrial SO2 technical efficiency, reduction potential and technology heterogeneities of China's prefecture-level cities: A multi-hierarchy meta-frontier parametric approach," Energy Economics, Elsevier, vol. 104(C).
    36. Lee, Sang-choon & Oh, Dong-hyun & Lee, Jeong-dong, 2014. "A new approach to measuring shadow price: Reconciling engineering and economic perspectives," Energy Economics, Elsevier, vol. 46(C), pages 66-77.
    37. Kumar, Surender & Jain, Rakesh Kumar, 2019. "Carbon-sensitive meta-productivity growth and technological gap: An empirical analysis of Indian thermal power sector," Energy Economics, Elsevier, vol. 81(C), pages 104-116.
    38. Wei, Chu & Löschel, Andreas & Liu, Bing, 2013. "An empirical analysis of the CO2 shadow price in Chinese thermal power enterprises," Energy Economics, Elsevier, vol. 40(C), pages 22-31.
    39. Chen, Bin & Jin, Yingmei, 2020. "Adjusting productivity measures for CO2 emissions control: Evidence from the provincial thermal power sector in China," Energy Economics, Elsevier, vol. 87(C).
    40. Tomasz Gerard Czekaj, 2013. "Measuring the Technical Efficiency of Farms Producing Environmental Output: Parametric and Semiparametric Estimation of Multi-output Stochastic Ray Production Frontiers," IFRO Working Paper 2013/21, University of Copenhagen, Department of Food and Resource Economics.
    41. Yuanjie Li & Zhuoying Zhang & Minjun Shi, 2019. "Restrictive Effects of Water Scarcity on Urban Economic Development in the Beijing-Tianjin-Hebei City Region," Sustainability, MDPI, vol. 11(8), pages 1-23, April.
    42. Zhou, Yi & Zhou, Wenji & Wei, Chu, 2023. "Environmental performance of the Chinese cement enterprise: An empirical analysis using a text-based directional vector," Energy Economics, Elsevier, vol. 125(C).
    43. Ang, Frederic & Kerstens, Pieter Jan, 2020. "A superlative indicator for the Luenberger-Hicks-Moorsteen productivity indicator: Theory and application," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1161-1173.
    44. Bert Balk & Rolf Färe & Giannis Karagiannis, 2015. "On directional scale elasticities," Journal of Productivity Analysis, Springer, vol. 43(1), pages 99-104, February.
    45. Jorge Bonilla & Jessica Coria & Thomas Sterner, 2018. "Technical Synergies and Trade-Offs Between Abatement of Global and Local Air Pollution," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 70(1), pages 191-221, May.
    46. Sauer, Johannes & Latacz-Lohmann, Uwe, 2012. "Efficient Innovation in Dairy Production - Empirical Findings for Germany," 52nd Annual Conference, Stuttgart, Germany, September 26-28, 2012 137386, German Association of Agricultural Economists (GEWISOLA).
    47. Mellah, Thuraya & Ben Amor, Tawfik, 2016. "Performance of the Tunisian Water Utility: An input-distance function approach," Utilities Policy, Elsevier, vol. 38(C), pages 18-32.
    48. Limin Du & Aoife Hanley & Chu Wei, 2015. "Marginal Abatement Costs of Carbon Dioxide Emissions in China: A Parametric Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 61(2), pages 191-216, June.
    49. Di Peng & Haibin Liu, 2023. "Marginal Carbon Dioxide Emission Reduction Cost and Influencing Factors in Chinese Industry Based on Bayes Bootstrap," Sustainability, MDPI, vol. 15(11), pages 1-19, May.
    50. Tang, Kai & Yang, Lin & Zhang, Jianwu, 2016. "Estimating the regional total factor efficiency and pollutants’ marginal abatement costs in China: A parametric approach," Applied Energy, Elsevier, vol. 184(C), pages 230-240.
    51. Rolf Färe & Shawna Grosskopf & William L. Weber, 2016. "Pricing Nonmarketed Outputs with an Application to Community Colleges," Public Finance Review, , vol. 44(2), pages 197-219, March.
    52. Nakaishi, Tomoaki, 2021. "Developing effective CO2 and SO2 mitigation strategy based on marginal abatement costs of coal-fired power plants in China," Applied Energy, Elsevier, vol. 294(C).
    53. Sauer, Johannes & Walsh, John & Zilberman, David, 2012. "Producer Behaviour and Agri-Environmental Policies: A Directional Distance based Matching Approach," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124877, Agricultural and Applied Economics Association.

  5. Mynbaev, Kairat & Martins-Filho, Carlos, 2009. "Bias reduction in kernel density estimation via Lipschitz condition," MPRA Paper 24904, University Library of Munich, Germany.

    Cited by:

    1. Kairat Mynbaev & Carlos Martins-Filho & Aziza Aipenova, 2016. "A Class of Nonparametric Density Derivative Estimators Based on Global Lipschitz Conditions," Advances in Econometrics, in: Essays in Honor of Aman Ullah, volume 36, pages 591-615, Emerald Group Publishing Limited.
    2. Martins-Filho, Carlos & Ziegelmann, Flávio Augusto & Torrent, Hudson da Silva, 2013. "Local Exponential Frontier Estimation," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 33(2), November.
    3. Henderson, Daniel J. & Parmeter, Christopher F., 2012. "Canonical higher-order kernels for density derivative estimation," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1383-1387.
    4. Mynbaev, Kairat & Martins-Filho, Carlos, 2015. "Consistency and asymptotic normality for a nonparametric prediction under measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 139(C), pages 166-188.
    5. Mynbayev, Kairat & Martins-Filho, Carlos, 2017. "Unified estimation of densities on bounded and unbounded domains," MPRA Paper 87044, University Library of Munich, Germany, revised Jan 2018.
    6. Sakhanenko, Lyudmila, 2017. "In search of an optimal kernel for a bias correction method for density estimators," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 42-50.
    7. Mynbaev, Kairat & Nadarajah, Saralees & Withers, Christopher & Aipenova, Aziza, 2014. "Improving bias in kernel density estimation," MPRA Paper 75846, University Library of Munich, Germany, revised 2014.
    8. Christopher Withers & Saralees Nadarajah, 2013. "Density estimates of low bias," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(3), pages 357-379, April.

  6. Martins-Filho, Carlos & yang, ke, 2007. "Finite sample performance of kernel-based regression methods for non-parametric additive models under common bandwidth selection criterion," MPRA Paper 39295, University Library of Munich, Germany.

    Cited by:

    1. Wang, Li & Wang, Suojin, 2011. "Nonparametric additive model-assisted estimation for survey data," Journal of Multivariate Analysis, Elsevier, vol. 102(7), pages 1126-1140, August.
    2. Song, Qiongxia & Yang, Lijian, 2010. "Oracally efficient spline smoothing of nonlinear additive autoregression models with simultaneous confidence band," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2008-2025, October.
    3. Xin Geng & Carlos Martins-Filho & Feng Yao, 2015. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 15-46, Department of Economics, West Virginia University.
    4. Ozabaci, Deniz & Henderson, Daniel J., 2014. "Additive Kernel Estimates of Returns to Schooling," IZA Discussion Papers 8736, Institute of Labor Economics (IZA).
    5. Guo, Zheng-Feng & Shintani, Mototsugu, 2011. "Nonparametric lag selection for nonlinear additive autoregressive models," Economics Letters, Elsevier, vol. 111(2), pages 131-134, May.
    6. Martins-Filho, Carlos & Yao, Feng, 2012. "Kernel-based estimation of semiparametric regression in triangular systems," Economics Letters, Elsevier, vol. 115(1), pages 24-27.
    7. Christopher F. Parmeter & Valentin Zelenyuk, 2016. "A Bridge Too Far? The State of the Art in Combining the Virtues of Stochastic Frontier Analysis and Data Envelopement Analysis," Working Papers 2016-10, University of Miami, Department of Economics.

  7. Martins Filho, Carlos & Mandy, David M., 1998. "Optimal IV estimation of systems with stochastic regressors and var disturbances with applications to dynamic systems," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 333, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

    Cited by:

    1. Martins-Filho Carlos & Yao Feng, 2006. "Estimation of Value-at-Risk and Expected Shortfall based on Nonlinear Models of Return Dynamics and Extreme Value Theory," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(2), pages 1-43, May.

  8. Okmyung Bin & Carlos Martins-Filho, "undated". "Estimation of Hedonic Price Functions via Additive Nonparametric Regression," Working Papers 0116, East Carolina University, Department of Economics.

    Cited by:

    1. Wolfgang Brunauer & Stefan Lang & Nikolaus Umlauf, 2010. "Modeling House Prices using Multilevel Structured Additive Regression," Working Papers 2010-19, Faculty of Economics and Statistics, Universität Innsbruck.
    2. Yiyang GU, 2018. "What are the most important factors that influence the changes in London Real Estate Prices? How to quantify them?," Journal of Economics Bibliography, KSP Journals, vol. 5(1), pages 18-24, March.
    3. Celia Bilbao & Amelia Bilbao & José Labeaga, 2010. "The welfare loss associated to characteristics of the goods: application to housing policy," Empirical Economics, Springer, vol. 38(2), pages 305-323, April.
    4. Antipov, Evgeny & Pokryshevskaya, Elena, 2010. "Applying a CART-based approach for the diagnostics of mass appraisal models," MPRA Paper 27646, University Library of Munich, Germany.
    5. Carlos Felipe Balcázar & Lidia Ceriani & Sergio Olivieri & Marco Ranzani, 2017. "Rent‐Imputation for Welfare Measurement: A Review of Methodologies and Empirical Findings," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(4), pages 881-898, December.
    6. Alan T. K. Wan & Jinhong You & Riquan Zhang, 2016. "A Seemingly Unrelated Nonparametric Additive Model with Autoregressive Errors," Econometric Reviews, Taylor & Francis Journals, vol. 35(5), pages 894-928, May.
    7. Wolfgang Brunauer & Stefan Lang & Peter Wechselberger & Sven Bienert, 2008. "Additive Hedonic Regression Models with Spatial Scaling Factors: An Application for Rents in Vienna," Working Papers 2008-17, Faculty of Economics and Statistics, Universität Innsbruck.
    8. Bontemps, Christophe & Simioni, Michel & Surry, Yves R., 2005. "Hedonic Housing Prices and Agricultural Pollution: An Empirical Investigation on Semiparametric Models," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24709, European Association of Agricultural Economists.
    9. Kagie, M. & van Wezel, M.C., 2006. "Hedonic price models and indices based on boosting applied to the Dutch housing market," Econometric Institute Research Papers EI 2006-17, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Sun, Tianyu & Chand, Satish & Sharpe, Keiran, 2018. "Effect of aging on housing prices: evidence from a panel data," MPRA Paper 94418, University Library of Munich, Germany, revised 01 Mar 2019.
    11. Martijn Kagie & Michiel Van Wezel, 2007. "Hedonic price models and indices based on boosting applied to the Dutch housing market," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 15(3‐4), pages 85-106, July.
    12. Fuess, Roland & Koller, Jan, 2015. "The Role of Spatial and Temporal Structure for Residential Rent Predictions," Working Papers on Finance 1523, University of St. Gallen, School of Finance.
    13. Alan T. K. Wan & Shangyu Xie & Yong Zhou, "undated". "A varying coefficient approach to estimating hedonic housing price functions and their quantiles," GRU Working Paper Series GRU_2016_003, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    14. März, Alexander & Klein, Nadja & Kneib, Thomas & Mußhoff, Oliver, 2014. "Analysing farmland rental rates using Bayesian geoadditive quantile regression," DARE Discussion Papers 1403, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
    15. Renigier-Biłozor Małgorzata & Wiśniewski Radosław, 2012. "The Impact of Macroeconomic Factors on Residential Property Price Indices in Europe," Folia Oeconomica Stetinensia, Sciendo, vol. 12(2), pages 103-125, December.
    16. Löchl, Michael & Axhausen, Kay W., 2010. "Modelling hedonic residential rents for land use and transport simulation while considering spatial effects," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 3(2), pages 39-63.
    17. Antipov, Evgeny & Pokryshevskaya, Elena, 2010. "Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics," MPRA Paper 27645, University Library of Munich, Germany.
    18. da Silva, Fernando A. Boeira Sabino, 2002. "Additive nonparametric regression estimation via backfitting and marginal integration: Small sample performance," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 22(2), November.
    19. W. Brunauer & S. Lang & P. Wechselberger & S. Bienert, 2010. "Additive Hedonic Regression Models with Spatial Scaling Factors: An Application for Rents in Vienna," The Journal of Real Estate Finance and Economics, Springer, vol. 41(4), pages 390-411, November.
    20. Manuel Landajo & Celia Bilbao & Amelia Bilbao, 2012. "Nonparametric neural network modeling of hedonic prices in the housing market," Empirical Economics, Springer, vol. 42(3), pages 987-1009, June.
    21. Yu, Peiyong, 2015. "The Effect of Eminent Domain on Private and Mixed Development on Property Values," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 45(2).
    22. Yiyang Gu, 2018. "What are the most important factors that influence the changes in London Real Estate Prices? How to quantify them?," Papers 1802.08238, arXiv.org.
    23. Robert J. Hill & Daniel Melser, 2007. "Comparing House Prices Across Regions and Time: An Hedonic Approach," Discussion Papers 2007-33, School of Economics, The University of New South Wales.

Articles

  1. Borri, Karine T. & Martins-Filho, Carlos & Kalatzis, Aquiles E.G., 2022. "Exploring nonlinearities between investment and internal funds: Evidence of the U-shaped investment curve," Economics Letters, Elsevier, vol. 218(C).

    Cited by:

    1. Kadzima, Marvelous & Machokoto, Michael, 2023. "A semi-parametric analysis of the cash flow sensitivity of cash," Finance Research Letters, Elsevier, vol. 56(C).

  2. Kairat Mynbaev & Carlos Martins-Filho, 2019. "Unified estimation of densities on bounded and unbounded domains," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(4), pages 853-887, August.
    See citations under working paper version above.
  3. Martins-Filho, Carlos & Yao, Feng & Torero, Maximo, 2018. "Nonparametric Estimation Of Conditional Value-At-Risk And Expected Shortfall Based On Extreme Value Theory," Econometric Theory, Cambridge University Press, vol. 34(1), pages 23-67, February.
    See citations under working paper version above.
  4. Tarcio Da Silva & Carlos Martins-filho & Eduardo Ribeiro, 2016. "A comparison of nonparametric efficiency estimators: DEA, FDH, DEAC, FDHC, order-m and quantile," Economics Bulletin, AccessEcon, vol. 36(1), pages 118-131.

    Cited by:

    1. Carlucci, Fabio & Corcione, Carlo & Mazzocchi, Paolo & Trincone, Barbara, 2021. "The role of logistics in promoting Italian agribusiness: The Belt and Road Initiative case study," Land Use Policy, Elsevier, vol. 108(C).
    2. Isabel Narbón-Perpiñá & Maria Balaguer-Coll & Emili Tortosa-Ausina, 2019. "Evaluating local government performance in times of crisis," Local Government Studies, Taylor & Francis Journals, vol. 45(1), pages 64-100, January.

  5. Castro, Fernanda & Kalatzis, Aquiles E.G. & Martins-Filho, Carlos, 2015. "Financing in an emerging economy: Does financial development or financial structure matter?," Emerging Markets Review, Elsevier, vol. 23(C), pages 96-123.

    Cited by:

    1. Liu, Chao & Fan, Yixin & Xie, Qiwei & Wang, Chao, 2022. "Market-based versus bank-based financial structure in China: From the perspective of financial risk," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 24-39.
    2. Jonathan A. Batten & Xuan Vinh Vo, 2016. "Bank risk shifting and diversification in an emerging market," Risk Management, Palgrave Macmillan, vol. 18(4), pages 217-235, December.
    3. Bilal Haider Subhani & Umar Farooq & M. Ishaq Bhatti & Muhammad Asif Khan, 2021. "Economic Policy Uncertainty, National Culture, and Corporate Debt Financing," Sustainability, MDPI, vol. 13(20), pages 1-15, October.
    4. Tang, Xiaobo & Yao, Xingyuan, 2018. "Do financial structures affect exchange rate and stock price interaction? Evidence from emerging markets," Emerging Markets Review, Elsevier, vol. 34(C), pages 64-76.
    5. Armando Lenin Támara Ayús & Lina María Eusse Ossa & Andrés Castellón Pérez, 2017. "Efectos del desarrollo financiero sobre el crecimiento económico de Colombia y Chile, 1982-2014," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 9(1), pages 57-67, February.
    6. Samargandi, Nahla & Kutan, Ali M. & Sohag, Kazi & Alqahtani, Faisal, 2020. "Equity market and money supply spillovers and economic growth in BRICS economies: A global vector autoregressive approach," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    7. Muhammad Kaleem Khan & Yixuan Qin & Chengsi Zhang, 2022. "Financial structure and earnings manipulation activities in China," The World Economy, Wiley Blackwell, vol. 45(8), pages 2593-2621, August.
    8. Muhammad Kaleem Khan & Ahmad Kaleem & Salman Zulfiqar & Umair Akram, 2019. "Innovation Investment: Behaviour Of Chinese Firms Towards Financing Sources," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 23(07), pages 1-29, October.
    9. Naeem, Kashif & Li, Matthew C., 2019. "Corporate investment efficiency: The role of financial development in firms with financing constraints and agency issues in OECD non-financial firms," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 53-68.
    10. Huang, Ke & Zhu, Ying, 2022. "China’s secondary privatization and corporate investment efficiency," Research in International Business and Finance, Elsevier, vol. 61(C).
    11. Nagano, Mamoru, 2016. "The bank–firm relationship during economic transition: The impacts on bank performance in emerging economies," Emerging Markets Review, Elsevier, vol. 28(C), pages 117-139.
    12. Sabahat Riaz & Mohamed Hisham Hanifa & Fauzi Zainir, 2021. "Does Foreign Institutional Equity Participation Instigate Sustainable Corporate Investment Efficiency? Evidence from Emerging Economies," Sustainability, MDPI, vol. 13(8), pages 1-17, April.
    13. Ammar Hussain & Minhas Akbar & Muhmmad Kaleem Khan & Marcela Sokolová & Ahsan Akbar, 2022. "The Interplay of Leverage, Financing Constraints and Real Earnings Management: A Panel Data Approach," Risks, MDPI, vol. 10(6), pages 1-21, May.
    14. Umar Farooq & Jaleel Ahmed & Shamshair Khan, 2021. "Do the macroeconomic factors influence the firm's investment decisions? A generalized method of moments (GMM) approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 790-801, January.
    15. Samargandi, Nahla & Kutan, Ali M., 2016. "Private credit spillovers and economic growth: Evidence from BRICS countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 56-84.
    16. Umar Farooq & Mosab I. Tabash & Basem Hamouri & Linda Nalini Daniel & Samir K. Safi, 2023. "Nexus between Macroeconomic Factors and Corporate Investment: Empirical Evidence from GCC Markets," IJFS, MDPI, vol. 11(1), pages 1-15, February.
    17. Liu, Guanchun & Zhang, Chengsi, 2020. "Does financial structure matter for economic growth in China," China Economic Review, Elsevier, vol. 61(C).
    18. Sanvicente, Antonio Zoratto & Bortoluzzo, Adriana & Bortoluzzo, Mauricio Mesquita, 2017. "Capital structure determinants of financially constrained and unconstrained firms," Textos para discussão 451, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).

  6. Carlos Martins-Filho & Feng Yao, 2015. "Semiparametric Stochastic Frontier Estimation via Profile Likelihood," Econometric Reviews, Taylor & Francis Journals, vol. 34(4), pages 413-451, April.

    Cited by:

    1. Parmeter, Christopher F. & Simar, Léopold & Van Keilegom, Ingrid & Zelenyuk, Valentin, 2021. "Inference in the Nonparametric Stochastic Frontier Model," LIDAM Discussion Papers ISBA 2021029, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Llorca, Manuel & Orea, Luis & Pollitt, Michael G., 2016. "Efficiency and environmental factors in the US electricity transmission industry," Energy Economics, Elsevier, vol. 55(C), pages 234-246.
    3. Taining Wang & Jinjing Tian & Feng Yao, 2021. "Does high debt ratio influence Chinese firms’ performance? A semiparametric stochastic frontier approach with zero inefficiency," Empirical Economics, Springer, vol. 61(2), pages 587-636, August.
    4. Christopher F. Parmeter & Hung-Jen Wang & Subal C. Kumbhakar, 2017. "Nonparametric estimation of the determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 47(3), pages 205-221, June.
    5. Maruyama, Eduardo & Schollard, Phoebe, 2021. "Geographic prioritization of agricultural investments: Prioritization of agricultural and nutrition investments," 2021 Conference, August 17-31, 2021, Virtual 315292, International Association of Agricultural Economists.
    6. Valentin Zelenyuk & Valentyn Panchenko, 2023. "Bayesian Artificial Neural Networks for Frontier Efficiency Analysis," CEPA Working Papers Series WP022023, School of Economics, University of Queensland, Australia.
    7. Marijn Verschelde & Michel Dumont & Glenn Rayp & Bruno Merlevede, 2015. "Semiparametric stochastic metafrontier efficiency of European manufacturing firms," Post-Print hal-01563023, HAL.
    8. Zhou, Jianhua & Parmeter, Christopher F. & Kumbhakar, Subal C., 2020. "Nonparametric estimation of the determinants of inefficiency in the presence of firm heterogeneity," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1142-1152.
    9. Chen, Zhongfei & Barros, Carlos Pestana & Borges, Maria Rosa, 2015. "A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies," Energy Economics, Elsevier, vol. 48(C), pages 136-144.
    10. William E. Griffiths & Gholamreza Hajargasht, 2015. "Welfare Consequences of Information Aggregation and Optimal Market Size," Department of Economics - Working Papers Series 1190, The University of Melbourne.
    11. Mike Tsionas & Valentin Zelenyuk, 2021. "Goodness-of-fit in Optimizing Models of Production: A Generalization with a Bayesian Perspective," CEPA Working Papers Series WP182021, School of Economics, University of Queensland, Australia.
    12. Lopez Gomez, Daniel & Parmeter, Christopher F., 2020. "Smooth coefficient estimation of stochastic frontier models," Economics Letters, Elsevier, vol. 193(C).
    13. Christopher F. Parmeter & Valentin Zelenyuk, 2019. "Combining the Virtues of Stochastic Frontier and Data Envelopment Analysis," Operations Research, INFORMS, vol. 67(6), pages 1628-1658, November.
    14. Ahmed S & Sonia Pérez-F & Carlos Carleos A & Norberto C & Pablo Martínez C, 2018. "Inference in Stochastic Frontier Models Based on Asymmetry," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 4(4), pages 99-108, January.
    15. Yao, Feng & Wang, Taining & Tian, Jinjing & Kumbhakar, Subal C., 2018. "Estimation of a smooth coefficient zero-inefficiency panel stochastic frontier model: A semiparametric approach," Economics Letters, Elsevier, vol. 166(C), pages 25-30.
    16. Mike Tsionas & Christopher F. Parmeter & Valentin Zelenyuk, 2021. "Bridging the Divide? Bayesian Artificial Neural Networks for Frontier Efficiency Analysis," CEPA Working Papers Series WP082021, School of Economics, University of Queensland, Australia.
    17. Kien C. Tran & Mike G. Tsionas, 2023. "Semiparametric estimation of a spatial autoregressive nonparametric stochastic frontier model," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-28, December.
    18. Maruyama, Eduardo & Torero, Maximo & Scollard, Phoebe & Elías, Maribel & Mulangu, Francis & Seck, Abdoulaye, 2018. "Frontier analysis and agricultural typologies," Discussion Papers 270849, University of Bonn, Center for Development Research (ZEF).
    19. Fan Zhang & Joshua Hall & Feng Yao, 2017. "Does Economic Freedom Affect The Production Frontier? A Semiparametric Approach With Panel Data," Working Papers 17-27, Department of Economics, West Virginia University.
    20. Christopher F. Parmeter & Valentin Zelenyuk, 2016. "A Bridge Too Far? The State of the Art in Combining the Virtues of Stochastic Frontier Analysis and Data Envelopement Analysis," Working Papers 2016-10, University of Miami, Department of Economics.
    21. Jun Cai & William C. Horrace & Christopher F. Parmeter, 2024. "Penalized sieve estimation of zero‐inefficiency stochastic frontiers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 41-65, January.
    22. Kien C. Tran & Mike G. Tsionas & Emmanuel Mamatzakis, 2020. "Why fully efficient banks matter? A nonparametric stochastic frontier approach in the presence of fully efficient banks," Empirical Economics, Springer, vol. 58(6), pages 2733-2760, June.

  7. Feng Yao & Carlos Martins-Filho, 2015. "An Asymptotic Characterization of Finite Degree U-statistics With Sample Size-Dependent Kernels: Applications to Nonparametric Estimators and Test Statistics," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(15), pages 3251-3265, August.

    Cited by:

    1. Xin Geng & Carlos Martins-Filho & Feng Yao, 2015. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 15-46, Department of Economics, West Virginia University.

  8. Carlos Martins-Filho & Feng Yao & Maximo Torero, 2015. "High-Order Conditional Quantile Estimation Based on Nonparametric Models of Regression," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 907-958, December.

    Cited by:

    1. Carlos Martins-Filho & Feng Yao & Maximo Torero, 2012. "Nonparametric estimation of conditional value-at-risk and expected shortfall based on extreme value theory," Working Papers 13-05, Department of Economics, West Virginia University.
    2. Matthias Kalkuhl & Lukas Kornher & Marta Kozicka & Pierre Boulanger & Maximo Torero, 2013. "Conceptual framework on price volatility and its impact on food and nutrition security in the short term," FOODSECURE Working papers 15, LEI Wageningen UR.
    3. Matthias Kalkuhl & Mekbib Haile & Lukas Kornher & Marta Kozicka, 2015. "Cost-benefit framework for policy action to navigate food price spikes. FOODSECURE Working Paper No 33," FOODSECURE Working papers 33, LEI Wageningen UR.
    4. Almanzar, Miguel & Torero, Maximo, 2017. "Media Coverage and Food Commodities: Agricultural Futures Prices and Volatility Effects," Discussion Papers 264781, University of Bonn, Center for Development Research (ZEF).
    5. Kalkuhl, Matthias & von Braun, Joachim & Torero, Maximo, 2016. "Food Price Volatility and Its Implications for Food Security and Policy," MPRA Paper 72164, University Library of Munich, Germany.

  9. Rolf Färe & Shawna Grosskopf & Carl Pasurka & Carlos Martins-Filho, 2013. "On Nonparametric Estimation: With a Focus on Agriculture," Annual Review of Resource Economics, Annual Reviews, vol. 5(1), pages 93-110, June.

    Cited by:

    1. Daraio, Cinzia & Kerstens, Kristiaan & Nepomuceno, Thyago & Sickles, Robin C., 2019. "Empirical Surveys of Frontier Applications: A Meta-Review," Working Papers 19-005, Rice University, Department of Economics.
    2. Luis Diaz-Balteiro & Carlos Iglesias-Merchan & Carlos Romero & Silvestre García de Jalón, 2020. "The Sustainable Management of Land and Fisheries Resources Using Multicriteria Techniques: A Meta-Analysis," Land, MDPI, vol. 9(10), pages 1-18, October.

  10. Martins-Filho, Carlos & Yao, Feng, 2012. "Kernel-based estimation of semiparametric regression in triangular systems," Economics Letters, Elsevier, vol. 115(1), pages 24-27.

    Cited by:

    1. Xin Geng & Carlos Martins-Filho & Feng Yao, 2015. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 15-46, Department of Economics, West Virginia University.
    2. Delgado, Michael S. & Parmeter, Christopher F., 2014. "A simple estimator for partial linear regression with endogenous nonparametric variables," Economics Letters, Elsevier, vol. 124(1), pages 100-103.
    3. Daniel J. Henderson & Christopher F. Parmeter, 2015. "Single-Step Estimation of a Partially Linear Model," Working Papers 2015-01, University of Miami, Department of Economics.

  11. Kairat Mynbaev & Carlos Martins-Filho, 2010. "Bias reduction in kernel density estimation via Lipschitz condition," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(2), pages 219-235.
    See citations under working paper version above.
  12. Rolf Färe & Carlos Martins-Filho & Michael Vardanyan, 2010. "On functional form representation of multi-output production technologies," Journal of Productivity Analysis, Springer, vol. 33(2), pages 81-96, April.
    See citations under working paper version above.
  13. Martins-Filho, Carlos & Yao, Feng, 2009. "Nonparametric regression estimation with general parametric error covariance," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 309-333, March.

    Cited by:

    1. Ke Yang, 2012. "Multivariate Local Polynomial Regression With Autocorrelated Errors," Economics Bulletin, AccessEcon, vol. 32(4), pages 3298-3305.
    2. Christopher F. Parmeter & Jeffrey S. Racine, 2018. "Nonparametric Estimation and Inference for Panel Data Models," Department of Economics Working Papers 2018-02, McMaster University.
    3. Ke Yang, 2013. "An Improved Local-linear Estimator For Nonparametric Regression With Autoregressive Errors," Economics Bulletin, AccessEcon, vol. 33(1), pages 19-27.
    4. Su, Liangjun & Ullah, Aman, 2007. "More efficient estimation of nonparametric panel data models with random effects," Economics Letters, Elsevier, vol. 96(3), pages 375-380, September.
    5. Juliane Geller & Michael H. Neumann, 2018. "Improved local polynomial estimation in time series regression," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 1-27, January.
    6. Alan T. K. Wan & Jinhong You & Riquan Zhang, 2016. "A Seemingly Unrelated Nonparametric Additive Model with Autoregressive Errors," Econometric Reviews, Taylor & Francis Journals, vol. 35(5), pages 894-928, May.
    7. Artem Prokhorov & Kien C. Tran & Mike G. Tsionas, 2021. "Estimation of semi- and nonparametric stochastic frontier models with endogenous regressors," Empirical Economics, Springer, vol. 60(6), pages 3043-3068, June.
    8. Linton, O. & Xiao, Z., 2019. "Efficient Estimation of Nonparametric Regression in The Presence of Dynamic Heteroskedasticity," Cambridge Working Papers in Economics 1907, Faculty of Economics, University of Cambridge.
    9. Shujie Ma & Jeffrey S. Racine & Aman Ullah, 2015. "Nonparametric Regression-Spline Random Effects Models," Department of Economics Working Papers 2015-10, McMaster University.
    10. Rodriguez-Poo, Juan M. & Soberón, Alexandra, 2015. "Nonparametric estimation of fixed effects panel data varying coefficient models," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 95-122.
    11. Paul Evans & Ji Uk Kim, 2016. "Convergence analysis as spatial dynamic panel regression and distribution dynamics of $$\hbox {CO}_{2}$$ CO 2 emissions in Asian countries," Empirical Economics, Springer, vol. 50(3), pages 729-751, May.
    12. Tanujit Dey & Kun Ho Kim & Chae Young Lim, 2018. "Bayesian time series regression with nonparametric modeling of autocorrelation," Computational Statistics, Springer, vol. 33(4), pages 1715-1731, December.
    13. Charnigo, Richard & Feng, Limin & Srinivasan, Cidambi, 2015. "Nonparametric and semiparametric compound estimation in multiple covariates," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 179-196.
    14. Sun, Yiguo & Malikov, Emir, 2017. "Estimation and Inference in Functional-Coefficient Spatial Autoregressive Panel Data Models with Fixed Effects," MPRA Paper 83671, University Library of Munich, Germany.
    15. Eduardo A. Souza-Rodrigues, 2016. "Nonparametric Regression with Common Shocks," Econometrics, MDPI, vol. 4(3), pages 1-17, September.
    16. Liangjun Su & Aman Ullah & Yun Wang, 2013. "Nonparametric regression estimation with general parametric error covariance: a more efficient two-step estimator," Empirical Economics, Springer, vol. 45(2), pages 1009-1024, October.

  14. Martins-Filho, Carlos & Yao, Feng, 2008. "A smooth nonparametric conditional quantile frontier estimator," Journal of Econometrics, Elsevier, vol. 143(2), pages 317-333, April.

    Cited by:

    1. Carlos Martins-Filho & Feng Yao & Maximo Torero, 2015. "High-Order Conditional Quantile Estimation Based on Nonparametric Models of Regression," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 907-958, December.
    2. Tsionas, Mike G., 2020. "Quantile Stochastic Frontiers," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1177-1184.
    3. Chumpitaz, Ruben & Kerstens, Kristiaan & Paparoidamis, Nicholas & Staat, Matthias, 2010. "Comparing efficiency across markets: An extension and critique of the methodology," European Journal of Operational Research, Elsevier, vol. 205(3), pages 719-728, September.
    4. Martins-Filho, Carlos & Ziegelmann, Flávio Augusto & Torrent, Hudson da Silva, 2013. "Local Exponential Frontier Estimation," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 33(2), November.
    5. Kortelainen, Mika, 2008. "Estimation of semiparametric stochastic frontiers under shape constraints with application to pollution generating technologies," MPRA Paper 9257, University Library of Munich, Germany.
    6. Wang, Yongqiao & Wang, Shouyang & Dang, Chuangyin & Ge, Wenxiu, 2014. "Nonparametric quantile frontier estimation under shape restriction," European Journal of Operational Research, Elsevier, vol. 232(3), pages 671-678.
    7. Henderson, Daniel J. & List, John A. & Millimet, Daniel L. & Parmeter, Christopher F. & Price, Michael K., 2012. "Empirical implementation of nonparametric first-price auction models," Journal of Econometrics, Elsevier, vol. 168(1), pages 17-28.
    8. Maria Teresa Balaguer-Coll & Diego Prior & Emili Tortosa-Ausina, 2010. "Devolution Dynamics of Spanish Local Government," Environment and Planning A, , vol. 42(6), pages 1476-1495, June.
    9. Maria Balaguer-Coll & Diego Prior & Emili Tortosa-Ausina, 2010. "Decentralization and efficiency of local government," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 45(3), pages 571-601, December.
    10. Dai, Sheng & Kuosmanen, Timo & Zhou, Xun, 2023. "Generalized quantile and expectile properties for shape constrained nonparametric estimation," European Journal of Operational Research, Elsevier, vol. 310(2), pages 914-927.
    11. Henderson, Daniel J. & List, John A. & Millimet, Daniel L. & Parmeter, Christopher F. & Price, Michael K., 2008. "Imposing Monotonicity Nonparametrically in First-Price Auctions," MPRA Paper 8769, University Library of Munich, Germany.

  15. Carlos Martins-Filho & Santosh Mishra & Aman Ullah, 2008. "A Class of Improved Parametrically Guided Nonparametric Regression Estimators," Econometric Reviews, Taylor & Francis Journals, vol. 27(4-6), pages 542-573.

    Cited by:

    1. Tae-Hwy Lee & Yundong Tu & Aman Ullah, 2014. "Nonparametric and Semiparametric Regressions Subject to Monotonicity Constraints: Estimation and Forecasting," Working Papers 201404, University of California at Riverside, Department of Economics.
    2. T. Senga Kiessé & M. Rivoire, 2011. "Discrete semiparametric regression models with associated kernel and applications," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(4), pages 927-941.
    3. Gao, Jiti, 2012. "Identification, Estimation and Specification in a Class of Semi-Linear Time Series Models," MPRA Paper 39256, University Library of Munich, Germany, revised 14 May 2012.
    4. Aman Ullah & Mardi Dungey & Xiangdong Long & Yun Wang, 2014. "A Semiparametric Conditional Duration Model," Working Papers 201408, University of California at Riverside, Department of Economics.
    5. Majda Talamakrouni & Anouar El Ghouch & Ingrid Van Keilegom, 2015. "Guided Censored Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 214-233, March.
    6. Yoshida, Takuma, 2018. "Semiparametric method for model structure discovery in additive regression models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 124-136.
    7. George Athanasopoulos & Minfeng Deng & Gang Li & Haiyan Song, 2013. "Domestic and outbound tourism demand in Australia: a System-of-Equations Approach," Monash Econometrics and Business Statistics Working Papers 6/13, Monash University, Department of Econometrics and Business Statistics.
    8. Yan Li & Liangjun Su & Yuewu Xu, 2015. "A Combined Approach to the Inference of Conditional Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 203-220, April.
    9. Pablo Guerróon‐Quintana & Molin Zhong, 2023. "Macroeconomic forecasting in times of crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 295-320, April.
    10. Talamakrouni, Majda & El Ghouch, Anouar & Van Keilegom, Ingrid, 2012. "Guided censored regression," LIDAM Discussion Papers ISBA 2012023, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    11. Li, Shuo & Tu, Yundong, 2016. "n-consistent density estimation in semiparametric regression models," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 91-109.
    12. Clemontina A. Davenport & Arnab Maity & Yichao Wu, 2015. "Parametrically guided estimation in nonparametric varying coefficient models with quasi-likelihood," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 27(2), pages 195-213, June.
    13. Jiti Gao, 2012. "Identification, Estimation and Specification in a Class of Semiparametic Time Series Models," Monash Econometrics and Business Statistics Working Papers 6/12, Monash University, Department of Econometrics and Business Statistics.
    14. Talamakrouni, Majda & Van Keilegom, Ingrid & El Ghouch, Anouar, 2016. "Parametrically guided nonparametric density and hazard estimation with censored data," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 308-323.

  16. Okmyung Bin & Carlos Martins-Filho, 2008. "Vehicle price and hydrocarbon emissions: evidence from the used-vehicle markets," Applied Economics Letters, Taylor & Francis Journals, vol. 15(12), pages 939-943.

    Cited by:

    1. Giuliano Rolle, 2022. "Between and within vehicle models hedonic analyses of environmental attributes: the case of the Italian used-car market," SEEDS Working Papers 0822, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Aug 2022.
    2. Girma Kassie & Awudu Abdulai & Clemens Wollny, 2011. "Heteroscedastic hedonic price model for cattle in the rural markets of central Ethiopia," Applied Economics, Taylor & Francis Journals, vol. 43(24), pages 3459-3464.
    3. Yasser A. Al-Rawi & Mohammed Harith Imlus & Yusri Yusup & Sofri Bin Yahya, 2021. "Factors affecting vehicle exhaust emissions, driver motivations as a mediator," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 23(2), pages 361-407, April.

  17. Martins-Filho, Carlos & Yao, Feng, 2007. "Nonparametric frontier estimation via local linear regression," Journal of Econometrics, Elsevier, vol. 141(1), pages 283-319, November.

    Cited by:

    1. Eduardo Fé & Richard Hofler, 2013. "Count data stochastic frontier models, with an application to the patents–R&D relationship," Journal of Productivity Analysis, Springer, vol. 39(3), pages 271-284, June.
    2. Martins-Filho, Carlos & Ziegelmann, Flávio Augusto & Torrent, Hudson da Silva, 2013. "Local Exponential Frontier Estimation," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 33(2), November.
    3. Martins-Filho, Carlos & Yao, Feng, 2008. "A smooth nonparametric conditional quantile frontier estimator," Journal of Econometrics, Elsevier, vol. 143(2), pages 317-333, April.
    4. Bouali Guesmi & Teresa Serra & Amr Radwan & José María Gil, 2018. "Efficiency of Egyptian organic agriculture: A local maximum likelihood approach," Agribusiness, John Wiley & Sons, Ltd., vol. 34(2), pages 441-455, March.
    5. Xu, Ke-Li & Phillips, Peter C. B., 2011. "Tilted Nonparametric Estimation of Volatility Functions With Empirical Applications," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 518-528.
    6. Kortelainen, Mika, 2008. "Estimation of semiparametric stochastic frontiers under shape constraints with application to pollution generating technologies," MPRA Paper 9257, University Library of Munich, Germany.
    7. Marijn Verschelde & Michel Dumont & Glenn Rayp & Bruno Merlevede, 2015. "Semiparametric stochastic metafrontier efficiency of European manufacturing firms," Post-Print hal-01563023, HAL.
    8. Artem Prokhorov & Kien C. Tran & Mike G. Tsionas, 2021. "Estimation of semi- and nonparametric stochastic frontier models with endogenous regressors," Empirical Economics, Springer, vol. 60(6), pages 3043-3068, June.
    9. Feng Yao & Junsen Zhang, 2013. "Efficient Kernel-Based Semiparametric IV Estimation with an Application to Resolving a Puzzle on the Estimates of the Return to Schooling," Working Papers 13-01, Department of Economics, West Virginia University.
    10. Bouali Guesmi & Teresa Serra & Allen Featherstone, 2015. "Technical efficiency of Kansas arable crop farms: a local maximum likelihood approach," Agricultural Economics, International Association of Agricultural Economists, vol. 46(6), pages 703-713, November.
    11. Peter C.B. Phillips & Ke-Li Xu, 2007. "Tilted Nonparametric Estimation of Volatility Functions," Cowles Foundation Discussion Papers 1612, Cowles Foundation for Research in Economics, Yale University, revised Jul 2010.
    12. Ray, Subhash C. & Das, Abhiman, 2010. "Distribution of cost and profit efficiency: Evidence from Indian banking," European Journal of Operational Research, Elsevier, vol. 201(1), pages 297-307, February.
    13. Teresa Serra & Barry Goodwin, 2009. "The efficiency of Spanish arable crop organic farms, a local maximum likelihood approach," Journal of Productivity Analysis, Springer, vol. 31(2), pages 113-124, April.
    14. Kien C. Tran & Mike G. Tsionas, 2023. "Semiparametric estimation of a spatial autoregressive nonparametric stochastic frontier model," Journal of Spatial Econometrics, Springer, vol. 4(1), pages 1-28, December.
    15. Daniel J. Henderson & Léopold Simar & Le Wang, 2017. "The three s of public schools: irrelevant inputs, insufficient resources and inefficiency," Applied Economics, Taylor & Francis Journals, vol. 49(12), pages 1164-1184, March.
    16. Maria Balaguer-Coll & Diego Prior & Emili Tortosa-Ausina, 2010. "Decentralization and efficiency of local government," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 45(3), pages 571-601, December.
    17. Guesmi, Bouali & Serra, Teresa & Radwan, Amr & Gil, José María, 2014. "Efficiency of Egyptian Organic Agriculture: a Local Maximum Likelihood Approach," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 183023, European Association of Agricultural Economists.
    18. Bellio, Ruggero & Grassetti, Luca, 2011. "Semiparametric stochastic frontier models for clustered data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 71-83, January.

  18. Carlos Martins-Filho & Feng Yao, 2006. "A Note on the Use of V and U Statistics in Nonparametric Models of Regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 58(2), pages 389-406, June.

    Cited by:

    1. Carlos Martins-Filho & Feng Yao & Maximo Torero, 2015. "High-Order Conditional Quantile Estimation Based on Nonparametric Models of Regression," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 907-958, December.
    2. Majda Talamakrouni & Anouar El Ghouch & Ingrid Van Keilegom, 2015. "Guided Censored Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 214-233, March.
    3. De Backer, Mickael & El Ghouch, Anouar & Van Keilegom, Ingrid, 2016. "Semiparametric Copula Quantile Regression for Complete or Censored Data," LIDAM Discussion Papers ISBA 2016009, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Talamakrouni, Majda & El Ghouch, Anouar & Van Keilegom, Ingrid, 2012. "Guided censored regression," LIDAM Discussion Papers ISBA 2012023, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  19. Martins-Filho Carlos & Yao Feng, 2006. "Estimation of Value-at-Risk and Expected Shortfall based on Nonlinear Models of Return Dynamics and Extreme Value Theory," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(2), pages 1-43, May.

    Cited by:

    1. Sofiane Aboura, 2014. "When the U.S. Stock Market Becomes Extreme?," Risks, MDPI, vol. 2(2), pages 1-15, May.
    2. Gery Geenens & Richard Dunn, 2017. "A nonparametric copula approach to conditional Value-at-Risk," Papers 1712.05527, arXiv.org, revised Oct 2019.
    3. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
    4. Carlos Martins-Filho & Feng Yao & Maximo Torero, 2012. "Nonparametric estimation of conditional value-at-risk and expected shortfall based on extreme value theory," Working Papers 13-05, Department of Economics, West Virginia University.
    5. Geenens, Gery & Dunn, Richard, 2022. "A nonparametric copula approach to conditional Value-at-Risk," Econometrics and Statistics, Elsevier, vol. 21(C), pages 19-37.
    6. Escanciano, J. Carlos & Olmo, Jose, 2010. "Backtesting Parametric Value-at-Risk With Estimation Risk," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 36-51.
    7. Martins-Filho, Carlos & Yao, Feng, 2009. "Nonparametric regression estimation with general parametric error covariance," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 309-333, March.
    8. d’Addona, Stefano & Khanom, Najrin, 2022. "Estimating tail-risk using semiparametric conditional variance with an application to meme stocks," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 241-260.
    9. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    10. John G. Galbraith & Serguei Zernov, 2006. "Extreme Dependence In The Nasdaq And S&P Composite Indexes," Departmental Working Papers 2006-14, McGill University, Department of Economics.
    11. Giannopoulos, Kostas & Tunaru, Radu, 2005. "Coherent risk measures under filtered historical simulation," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 979-996, April.
    12. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    13. Nieto, María Rosa & Ruiz Ortega, Esther, 2008. "Measuring financial risk : comparison of alternative procedures to estimate VaR and ES," DES - Working Papers. Statistics and Econometrics. WS ws087326, Universidad Carlos III de Madrid. Departamento de Estadística.
    14. Bertrand B. Maillet & Jean-Philippe R. M�decin, 2010. "Extreme Volatilities, Financial Crises and L-moment Estimations of Tail-indexes," Working Papers 2010_10, Department of Economics, University of Venice "Ca' Foscari".
    15. Emmanuel Jurczenko & Bertrand Maillet & Paul Merlin, 2008. "Efficient Frontier for Robust Higher-order Moment Portfolio Selection," Post-Print halshs-00336475, HAL.

  20. Carlos Martins-Filho & Okmyung Bin, 2005. "Estimation of hedonic price functions via additive nonparametric regression," Empirical Economics, Springer, vol. 30(1), pages 93-114, January.
    See citations under working paper version above.
  21. David Mandy & Carlos Martins-Filho, 2001. "Optimal Iv Estimation Of Systems With Stochastic Regressors And Var Disturbances With Applications To Dynamic Systems," Econometric Reviews, Taylor & Francis Journals, vol. 20(4), pages 485-505.
    See citations under working paper version above.
  22. Mandy, David M & Martins-Filho, Carlos, 1997. "A Note on a Unified Approach to Asymptotic Equivalence of Aitken and Feasible Aitken Instrumental Variables Estimators," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(2), pages 479-479, May.

    Cited by:

    1. David Mandy & Sandor Fridli, 2004. "Exact FGLS Asymptotics for MA Errors," Working Papers 0405, Department of Economics, University of Missouri, revised 16 Dec 2004.

  23. Mandy, David M & Martins-Filho, Carlos, 1994. "A Unified Approach to Asymptotic Equivalence of Aitken and Feasible Aitken Instrumental Variables Estimators," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(4), pages 957-979, November.

    Cited by:

    1. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    2. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    3. Martins-Filho, Carlos & Yao, Feng, 2009. "Nonparametric regression estimation with general parametric error covariance," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 309-333, March.
    4. David Mandy & Sandor Fridli, 2004. "Exact FGLS Asymptotics for MA Errors," Working Papers 0405, Department of Economics, University of Missouri, revised 16 Dec 2004.
    5. Marco Avarucci & Paolo Zaffaroni, 2019. "Robust Nearly-Efficient Estimation of Large Panels with Factor Structures," Papers 1902.11181, arXiv.org.

  24. Mandy, David M. & Martins-Filho, Carlos, 1993. "Seemingly unrelated regressions under additive heteroscedasticity : Theory and share equation applications," Journal of Econometrics, Elsevier, vol. 58(3), pages 315-346, August.

    Cited by:

    1. Alexandre Manoel Angelo da Silva, 2001. "Setor Aéreo Doméstico Brasileiro: uma Função Custo," Anais do XXIX Encontro Nacional de Economia [Proceedings of the 29th Brazilian Economics Meeting] 069, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    2. Smith, M. & Kohn, R., 1998. "Nonparametric Seemingly Unrelated Regression," Monash Econometrics and Business Statistics Working Papers 7/98, Monash University, Department of Econometrics and Business Statistics.
    3. Surajit Ray & B. Ravikumar & N. Eugene Savin, 1998. "Robust Wald Tests in SUR Systems with Adding Up Restrictions: An Algebraic Approach to Proofs of Invariance," Econometrics 9802002, University Library of Munich, Germany.
    4. Xu, Qinfeng & You, Jinhong & Zhou, Bin, 2008. "Seemingly unrelated nonparametric models with positive correlation and constrained error variances," Economics Letters, Elsevier, vol. 99(2), pages 223-227, May.
    5. Haupt, Harry & Oberhofer, Walter, 2006. "Generalized adding-up in systems of regression equations," Economics Letters, Elsevier, vol. 92(2), pages 263-269, August.
    6. Zellner, Arnold & Ando, Tomohiro, 2010. "A direct Monte Carlo approach for Bayesian analysis of the seemingly unrelated regression model," Journal of Econometrics, Elsevier, vol. 159(1), pages 33-45, November.
    7. Jinhong You & Xian Zhou, 2010. "Statistical inference on seemingly unrelated varying coefficient partially linear models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(2), pages 227-253, May.
    8. Creel, Michael & Farell, Montserrat, 1996. "SUR estimation of multiple time-series models with heteroscedasticity and serial correlation of unknown form," Economics Letters, Elsevier, vol. 53(3), pages 239-245, December.

  25. Carlos Martins-Filho & John W. Mayo, 1993. "Demand and Pricing of Telecommunications Services: Evidence and Welfare Implications," RAND Journal of Economics, The RAND Corporation, vol. 24(3), pages 439-454, Autumn.

    Cited by:

    1. Gianni De Fraja & Fabio M. Manenti, "undated". "How Long Is A Piece Of Wire? Equilibrium Determination Of Local Telephone Areas," Discussion Papers 00/03, Department of Economics, University of York.
    2. Boonsaeng, Tullaya & Carpio, Carlos E., 2017. "Budget Allocation Patterns of American Household across Income Level in the 21 Century," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258245, Agricultural and Applied Economics Association.
    3. Jean-Michel Guldmann, 1998. "Competing destinations and intervening opportunities interaction models of inter-city telecommunication flows," ERSA conference papers ersa98p120, European Regional Science Association.
    4. Kridel, Donald J. & Rappoport, Paul N. & Taylor, Lester D., 2002. "IntraLATA long-distance demand: carrier choice, usage demand and price elasticities," International Journal of Forecasting, Elsevier, vol. 18(4), pages 545-559.
    5. Eric P. Chiang & Janice A. Hauge, 2007. "Funding Universal Service: The Effect of Telecommunications Subsidy Programs on Competition and Retail Prices," Working Papers 07-08, NET Institute, revised Aug 2007.
    6. Agiakloglou, Christos & Karkalakos, Sotiris, 2006. "Estimating Diffusion Rates for Telecommunications: Evidence from European Union," MPRA Paper 45788, University Library of Munich, Germany.
    7. Martin Gaynor & Yunfeng Shi & Rahul Telang & William Vogt, 2005. "Cell Phone Demand and Consumer Learning – An Empirical Analysis," Working Papers 05-28, NET Institute, revised Oct 2005.
    8. Rahul Telang, 2004. "An Empirical Analysis of Cellular Voice and Data services," Working Papers 04-10, NET Institute.
    9. Sergio Da Silva & Gustavo Manfrim, 2007. "Estimating demand elasticities of fixed telephony in Brazil," Economics Bulletin, AccessEcon, vol. 12(5), pages 1-9.
    10. Eriksson, Ross C & Kaserman, David L & Mayo, John W, 1998. "Targeted and Untargeted Subsidy Schemes: Evidence from Postdivestiture Efforts to Promote Universal Telephone Service," Journal of Law and Economics, University of Chicago Press, vol. 41(2), pages 477-502, October.
    11. Guldmann, Jean-Michel, 1998. "Intersectoral point-to-point telecommunication flows: theoretical framework and empirical results," Regional Science and Urban Economics, Elsevier, vol. 28(5), pages 585-609, September.
    12. Agiakloglou, Christos & Karkalakos, Sotiris, 2006. "Estimating Diffusion Rates for Telecommunications: Evidence from European Union," MPRA Paper 45862, University Library of Munich, Germany.

Chapters

  1. Kairat Mynbaev & Carlos Martins-Filho & Aziza Aipenova, 2016. "A Class of Nonparametric Density Derivative Estimators Based on Global Lipschitz Conditions," Advances in Econometrics, in: Essays in Honor of Aman Ullah, volume 36, pages 591-615, Emerald Group Publishing Limited.
    See citations under working paper version above.Sorry, no citations of chapters recorded.
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