848 resultados para Bootstrap DEA
Resumo:
Between 2001 and 2005, the US airline industry faced financial turmoil. At the same time, the European airline industry entered a period of substantive deregulation. This period witnessed opportunities for low-cost carriers to become more competitive in the market as a result of these combined events. To help assess airline performance in the aftermath of these events, this paper provides new evidence of technical efficiency for 42 national and international airlines in 2006 using the data envelopment analysis (DEA) bootstrap approach first proposed by Simar and Wilson (J Econ, 136:31-64, 2007). In the first stage, technical efficiency scores are estimated using a bootstrap DEA model. In the second stage, a truncated regression is employed to quantify the economic drivers underlying measured technical efficiency. The results highlight the key role played by non-discretionary inputs in measures of airline technical efficiency.
Resumo:
La ricerca intende analizzare l’efficacia della spesa pubblica, l’efficienza e le loro determinanti nei settori della Sanità, dell’Istruzione e della Ricerca per 33 paesi dell’area OCSE. L’analisi ha un duplice obiettivo: da un lato un confronto cross country e dall’altro un confronto temporale, prendendo in considerazione il periodo che va dal 1992 al 2011. Il tema della valutazione dell’efficacia e dell’efficienza della spesa pubblica è molto attuale, soprattutto in Europa, sia perché essa incide di quasi il 50% sul PIL, sia a causa della crisi finanziaria del 2008 che ha spinto i governi ad una riduzione dei bugdet e ad un loro uso più oculato. La scelta di concentrare il lavoro di analisi nei settori della Sanità, dell’Istruzione e della Ricerca e Sviluppo deriva da un lato dalla loro peculiarità di attività orientate al cliente (scuole, ospedali, tribunali) dall’altro dal ruolo strategico che essi rappresentano per lo sviluppo economico di un paese. Il lavoro è articolato in tre sezioni: 1. Rassegna dei principali strumenti metodologici utilizzati in letteratura per la misurazione della performance e dell’efficienza della spesa pubblica nei tre settori. 2. Valutazione e confronto dell’efficienza e della performance della spesa pubblica dal punto di vista sia temporale sia cross-country attraverso la costruzione di indicatori di performance e di efficienza della spesa pubblica (per approfondire l'indice dell'efficienza ho applicato la tecnica DEA "bootstrap output oriented" con indicatori di output ed input non simultanei mentre l’evoluzione dell’efficienza tra i periodi 2011-2002 e 2001-1992 è stata analizzata attraverso il calcolo dell’indice di Malmquist). 3. Analisi delle variabili esogene che influenzano l’efficienza della spesa pubblica nei settori Salute, Istruzione e Ricerca e Sviluppo attraverso una regressione Tobit avente come variabile dipendente i punteggi di efficienza DEA output oriented e come variabili esogene alcuni indicatori scelti tra quelli presenti in letteratura: l’Indicatore delle condizioni socioeconomiche delle famiglie (costruito e applicato da OCSE PISA per valutare l’impatto del background familiare nelle performance dell’apprendimento), l’Indicatore di fiducia nel sistema legislativo del paese, l’Indicatore di tutela dei diritti di proprietà, l’Indicatore delle azioni di controllo della corruzione, l’Indicatore di efficacia delle azioni di governo, l’Indicatore della qualità dei regolamenti, il PIL pro-capite. Da questo lavoro emergono risultati interessanti: non sempre alla quantità di risorse impiegate corrisponde il livello massimo di performance raggiungibile. I risultati della DEA evidenziano la media dei punteggi di efficienza corretti di 0,712 e quindi, impiegando la stessa quantità di risorse, si produrrebbe un potenziale miglioramento dell’output generato di circa il 29%. Svezia, Giappone, Finlandia e Germania risultano i paesi più efficienti, più vicini alla frontiera, mentre Slovacchia, Portogallo e Ungheria sono più distanti dalla frontiera con una misura di inefficienza di circa il 40%. Per quanto riguarda il confronto tra l’efficienza della spesa pubblica nei tre settori tra i periodi 1992-2001 e 2002-2011, l’indice di Malmquist mostra risultati interessanti: i paesi che hanno migliorato il loro livello di efficienza sono quelli dell’Est come l’Estonia, la Slovacchia, la Lituania mentre Paesi Bassi, Belgio e Stati Uniti hanno peggiorato la loro posizione. I paesi che risultano efficienti nella DEA come Finlandia, Germania e Svezia sono rimasti sostanzialmente fermi con un indice di Malmquist vicino al valore uno. In conclusione, i risultati della Tobit contengono indicazioni importanti per orientare le scelte dei Governi. Dall’analisi effettuata emerge che la fiducia nelle leggi, la lotta di contrasto alla corruzione, l’efficacia del governo, la tutela dei diritti di proprietà, le condizioni socioeconomiche delle famiglie degli studenti OECD PISA, influenzano positivamente l’efficienza della spesa pubblica nei tre settori indagati. Oltre alla spending review, per aumentare l’efficienza e migliorare la performance della spesa pubblica nei tre settori, è indispensabile per gli Stati la capacità di realizzare delle riforme che siano in grado di garantire il corretto funzionamento delle istituzioni.
Resumo:
The influence of IT investment on hospital efficiency and quality are of great interest to healthcare executives as well as insurers. Few studies have examined how IT investments influence both efficiency and quality or whether there is an optimal IT investment level that influences both in the desired direction. Decision makers in healthcare wonder if there are tradeoffs between their pursuit of hospital operational efficiency and quality. Our study involving a 2-stage double bootstrap DEA analysis of 187 US hospitals over 2. years found direct effects of IT investment upon service quality and a moderating effect of quality upon operational efficiency. Further, our findings indicate a U-shaped relationship between IT investments and operational efficiency suggesting that IT investments have diminishing returns beyond a certain point.
Resumo:
In this article we examine sources of technical efficiency for rice farming in Bangladesh. The motivation for the analysis is the need to close the rice yield gap to enable food security. We employ the DEA double bootstrap of Simar and Wilson (2007) to estimate and explain technical efficiency. This technique overcomes severe limitations inherent in using the two-stage DEA approach commonly employed in the efficiency literature. From a policy perspective our results show that potential efficiency gains to reduce the yield gap are greater than previously found. Statistically positive influences on technical efficiency are education, extension and credit, with age being a negative influence.
Resumo:
This paper analyses the productivity growth of the SUMA tax offices located in Spain evolved between 2004 and 2006 by using Malmquist Index based on Data Envelopment Analysis (DEA) models. It goes a step forward by smoothed bootstrap procedure which improves the quality of the results by generalising the samples, so that the conclusions obtained from them can be applied in order to increase productivity levels. Additionally, the productivity effect is divided into two different components, efficiency and technological change, with the objective of helping to clarify the role played by either the managers or the level of technology in the final performance figures.
Resumo:
The purpose of this study is to provide a comparative analysis of the efficiency of Islamic and conventional banks in Gulf Cooperation Council (GCC) countries. In this study, we explain inefficiencies obtained by introducing firm-specific as well as macroeconomic variables. Our findings indicate that during the eight years of study, conventional banks largely outperform Islamic banks with an average technical efficiency score of 81% compared to 95.57%. However, it is clear that since 2008, efficiency of conventional banks was in a downward trend while the efficiency of their Islamic counterparts was in an upward trend since 2009. This indicates that Islamic banks have succeeded to maintain a level of efficiency during the subprime crisis period. Finally, for the whole sample, the analysis demonstrates the strong link of macroeconomic indicators with efficiency for GCC banks. Surprisingly, we have not found any significant relationship in the case of Islamic banks.
Resumo:
The motivation of the study stems from the results reported in the Excellence in Research for Australia (ERA) 2010 report. The report showed that only 12 universities performed research at or above international standards, of which, the Group of Eight (G8) universities filled the top eight spots. While performance of universities was based on number of research outputs, total amount of research income and other quantitative indicators, the measure of efficiency or productivity was not considered. The objectives of this paper are twofold. First, to provide a review of the research performance of 37 Australian universities using the data envelopment analysis (DEA) bootstrap approach of Simar and Wilson (2007). Second, to determine sources of productivity drivers by regressing the efficiency scores against a set of environmental variables.
Resumo:
This article explores how data envelopment analysis (DEA), along with a smoothed bootstrap method, can be used in applied analysis to obtain more reliable efficiency rankings for farms. The main focus is the smoothed homogeneous bootstrap procedure introduced by Simar and Wilson (1998) to implement statistical inference for the original efficiency point estimates. Two main model specifications, constant and variable returns to scale, are investigated along with various choices regarding data aggregation. The coefficient of separation (CoS), a statistic that indicates the degree of statistical differentiation within the sample, is used to demonstrate the findings. The CoS suggests a substantive dependency of the results on the methodology and assumptions employed. Accordingly, some observations are made on how to conduct DEA in order to get more reliable efficiency rankings, depending on the purpose for which they are to be used. In addition, attention is drawn to the ability of the SLICE MODEL, implemented in GAMS, to enable researchers to overcome the computational burdens of conducting DEA (with bootstrapping).
Resumo:
The Data Envelopment Analysis (DEA) efficiency score obtained for an individual firm is a point estimate without any confidence interval around it. In recent years, researchers have resorted to bootstrapping in order to generate empirical distributions of efficiency scores. This procedure assumes that all firms have the same probability of getting an efficiency score from any specified interval within the [0,1] range. We propose a bootstrap procedure that empirically generates the conditional distribution of efficiency for each individual firm given systematic factors that influence its efficiency. Instead of resampling directly from the pooled DEA scores, we first regress these scores on a set of explanatory variables not included at the DEA stage and bootstrap the residuals from this regression. These pseudo-efficiency scores incorporate the systematic effects of unit-specific factors along with the contribution of the randomly drawn residual. Data from the U.S. airline industry are utilized in an empirical application.
Resumo:
Performance analysis has become a vital part of the management practices in the banking industry. There are numerous applications using DEA models to estimate efficiency in banking, and most of them assume that inputs and outputs are known with absolute precision. Here, we propose new Fuzzy-DEA α-level models to assess underlying uncertainty. Further, bootstrap truncated regressions with fixed factors are used to measure the impact of each model on the efficiency scores and to identify the most relevant contextual variables on efficiency. The proposed models have been demonstrated using an application in Mozambican banks to handle the underlying uncertainty. Findings reveal that fuzziness is predominant over randomness in interpreting the results. In addition, fuzziness can be used by decision-makers to identify missing variables to help in interpreting the results. Price of labor, price of capital, and market-share were found to be the significant factors in measuring bank efficiency. Managerial implications are addressed.
Resumo:
In this work, we investigate an alternative bootstrap approach based on a result of Ramsey [F.L. Ramsey, Characterization of the partial autocorrelation function, Ann. Statist. 2 (1974), pp. 1296-1301] and on the Durbin-Levinson algorithm to obtain a surrogate series from linear Gaussian processes with long range dependence. We compare this bootstrap method with other existing procedures in a wide Monte Carlo experiment by estimating, parametrically and semi-parametrically, the memory parameter d. We consider Gaussian and non-Gaussian processes to prove the robustness of the method to deviations from normality. The approach is also useful to estimate confidence intervals for the memory parameter d by improving the coverage level of the interval.
Resumo:
Between 2001 and 2005, the US airline industry faced financial turmoil while the European airline industry entered a period of substantive deregulation. Consequently, this opened up opportunities for low-cost carriers to become more competitive in the market. To assess airline performance and identify the sources of efficiency in the immediate aftermath of these events, we employ a bootstrap data envelopment analysis truncated regression approach. The results suggest that at the time the mainstream airlines needed to significantly reorganize and rescale their operations to remain competitive. In the second-stage analysis, the results indicate that private ownership, status as a low-cost carrier, and improvements in weight load contributed to better organizational efficiency.
Resumo:
The motivation for this analysis is the recently developed Excellence in Research for Australia (ERA) program developed to assess the quality of research in Australia. The objective is to develop an appropriate empirical model that better represents the underlying production of higher education research. In general, past studies on university research performance have used standard DEA models with some quantifiable research outputs. However, these suffer from the twin maladies of an inappropriate production specification and a lack of consideration of the quality of output. By including the qualitative attributes of peer-reviewed journals, we develop a procedure that captures both quality and quantity, and apply it using a network DEA model. Our main finding is that standard DEA models tend to overstate the research efficiency of most Australian universities.