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A new approach to stochastic frontier estimation: DEA+
Gstach, Dieter - Vienna University of Economics and Business, Department … - 1996
The outcome of a production process might not only deviate from a theoretical maximum due to inefficiency, but also because of non-controllable influences. This raises the issue of reliability of Data Envelopment Analysis in noisy environments. I propose to assume an i.i.d. data generating...
Persistent link: https://www.econbiz.de/10005817156
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The effect of protest votes on the estimates of willingness to pay for use values of recreational sites
Strazzera, Elisabetta; Genius, Margarita; Scarpa, Riccardo - 2001
Selectivity bias caused by protest responses in Contingent Valuation studies can be detected and corrected by means of sample selection models. This paper compares two methods: the Heckman 2-steps method and the full ML, applied to data on forest recreation - where WTP is elicited as a...
Persistent link: https://www.econbiz.de/10011608859
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Estimating parameters of the three-parameter Weibull distribution using a neural network
Abbasi, B; Rabelo, L; Hosseinkouchack, M - 2008
procedures such as Maximum Likelihood Estimation (MLE) have become almost too complicated to implement. In this paper, we will … an MLE and two moment-based methods. …
Persistent link: https://www.econbiz.de/10009481810
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Estimation of regulatory credit risk models
Pérez Montes, Carlos - 2013
Incluye bibliografía ; This article estimates a general credit risk model with both macroeconomic and latent credit factors for Spanish banks during the period 2004-2010. The proposed framework allows to estimate with bank level data both the standard credit risk model of Basel II and...
Persistent link: https://www.econbiz.de/10012530413
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Marshall-Olkin Power Lomax distribution for modeling of wind speed data
Ul Haq, Muhammad Ahsan; Rao, G. Srinivasa; Albassam, … - In: Energy Reports 6 (2020), pp. 1118-1123
Accurate collection of wind speed records is significant for numerous wind power applications. The present investigation aims to highlight the use of the Marshall-Olkin Power Lomax (MOPLx) distribution for wind speed data. We examine the actual wind speed records gathered from three stations...
Persistent link: https://www.econbiz.de/10012652468
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Hidden Markov model for stock selection
Nguyen, Nguyet; Nguyen, Dung - In: Risks 3 (2015) 4, pp. 455-473
The hidden Markov model (HMM) is typically used to predict the hidden regimes of observation data. Therefore, this model finds applications in many different areas, such as speech recognition systems, computational molecular biology and financial market predictions. In this paper, we use HMM for...
Persistent link: https://www.econbiz.de/10011709535
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Heteroskedasticity of unknown form in spatial autoregressive models with a moving average disturbance term
Doğan, Osman - In: Econometrics 3 (2015) 1, pp. 101-127
In this study, I investigate the necessary condition for the consistency of the maximum likelihood estimator (MLE) of … spatial models with a spatial moving average process in the disturbance term. I show that the MLE of spatial autoregressive … estimation. I also show that the MLE of parameters of exogenous variables is inconsistent and determine its asymptotic bias. I …
Persistent link: https://www.econbiz.de/10011755273
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Estimation of parameters in weighted generalized beta distributions of the second kind
Ye, Yuan; Oluyede, Broderick O.; Pararai, Mavis - In: Journal of Statistical and Econometric Methods 1 (2012) 1, pp. 1-12
. WGB2 proved to be in the generalized beta-F family of distributions, and maximum likelihood estimation(MLE) is used to …
Persistent link: https://www.econbiz.de/10010281952
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Hedging strategy comparisons of volatility index options using diffusion models
Lin, Jun-Biao - In: The international journal of business and finance … 9 (2015) 3, pp. 59-69
Persistent link: https://www.econbiz.de/10011285427
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Modelling tail behavior of returns using the generalized extreme value distribution
Makhwiting, Monnye Rhoda; Sigauke, Caston; Lesaoana, Maseka - In: Economics, management and financial markets 9 (2014) 1, pp. 41-52
Persistent link: https://www.econbiz.de/10011543664