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The Chinese fund market has witnessed significant developments in recent years. However, although there has been a range of studies assessing fund performance in developed industries, the rapidly developing fund industry in China has received very little attention. This study aims to examine the performance of open-end securities investment funds investing in Chinese domestic equity during the period May 2003 to September 2020. Specifically, applying a non-parametric bootstrap methodology from the literature on fund performance, the authors investigate the role of skill versus luck in this rapidly evolving investment funds industry.

This study evaluates the performance of Chinese equity securities investment funds from 2003–2020 using a bootstrap methodology to distinguish skill from luck in performance. The authors consider unconditional and conditional performance models.

The bootstrap methodology incorporates non-normality in the idiosyncratic risk of fund returns, which is a major drawback in “conventional” performance statistics. The evidence does not support the existence of “genuine” skilled fund managers. In addition, it indicates that poor performance is mainly attributable to bad stock picking skills.

The authors find that the top-ranked funds with positive abnormal performance are attributed to “good luck” not “good skill” while the negative abnormal performance of bottom funds is mainly due to “bad skill.” Therefore, sensible advice for most Chinese equity investors would be against trying to “pick winners funds” among Chinese securities investment funds but it would be recommended to avoid holding “losers.” At the present time, investors should consider other types of funds, such as index/tracker funds with lower transactions. In addition, less risk-averse investors may consider Chinese hedge funds [Zhao (2012)] or exchange-traded fund [Han (2012)].

The paper makes several contributions to the literature. First, the authors examine a wide range (over 50) of risk-adjusted performance models, which account for both unconditional and conditional risk factors. The authors also control for the profitability and investment risks in Fama and French (2015). Second, the authors select the “best-fit” model across all risk-adjusted models examined and a single “best-fit” model from each of the three classes. Therefore, the bootstrap analysis, which is mainly based on the selected best-fit models, is more precise and robust. Third, the authors reduce the possibility that findings may be sample-period specific or may be a survivor (upward) biased. Fourth, the authors consider further analysis based on sub-periods and compare fund performance in different market conditions to provide more implications to investors and practitioners. Fifth, the authors carry out extensive robustness checks and show that the findings are robust in relation to different minimum fund histories and serial correlation and heteroscedasticity adjustments. Sixth, the authors use higher frequency weekly data to improve statistical estimation.

The main purpose of this paper is to determine the bias-corrected efficiencies and rankings of the selected hotels and restaurants (H&Rs) in India.

The data for the Indian H&R sector are collected from the Prowess database. The bootstrap data envelopment analysis (DEA) based on a constant return to scale (CRS), variable return to scale-input oriented (VRS-IP) and variable return to scale-output oriented (VRS-OP) are applied on H&Rs to obtain the bias-corrected efficiencies.

It is found that relative efficiencies using basic DEA methods of all the 45 H&Rs of India are overestimated. These efficiencies are corrected using bias correction through bootstrap DEA methods. The bounds for the efficiencies of each H&R are computed using all the adopted methods. All H&Rs are ranked using bias-corrected efficiencies, and the linear trend between ranks suggests that the H&Rs are ranked almost similarly by all the adopted methods.

To improve efficiency, Indian H&R companies must rethink their personnel needs by enhancing their workforce management capabilities. The government needs to extend more support to this sector by introducing a liberal legislation framework and supporting infrastructure policies.

There is a paucity of studies on H&Rs in India. The current study focused on measuring bias-corrected efficiencies of the selected H&Rs of India. This study is one of the few initiatives to explore bias-corrected efficiencies extensively using the bootstrap DEA method.

The purpose of this work is twofold: on the one hand, recent methodologies will be used to estimate efficiency and productivity in Spain's non‐specialized retail sector for the period of 1997‐2007. In particular, the order‐m approach proposed by Cazals et al., which is based on the concept of expected minimum input function. On the other hand, the results obtained applying the methods mentioned in the Spanish retail sector can contribute to opening up a new field of analysis since the results may be compared by means of the methodologies proposed as well as those which already exist in the literature.

The paper used data envelopment analysis stochastic (order‐m) and bootstrapping Malmquist index to measure productivity and efficiency in 12 sectors in Spanish retail trade 1997‐2007.

In order to illustrate the methodology proposed in this paper different phases involved; first, we have estimated the efficiency in 12 sectors of the retail sector four digits NACE, we found high levels of inefficiency in most of the sectors analyzed over the period of analysis. Next, we will deepen and simplify the analysis by concentrating on food‐predominant sectors in non‐specialised shops (5211). The evolution of the efficiency of firms belonging to this sector decreases over the period of analysis. Analyzing the relationship between firms and size, the results obtained in this work shows that the firm's size have a positive influence on efficiency that suggest that the management may have incentives to grow in order to improve their efficiency levels. Our second contribution has to do with the use of bootstrapping Malmquist productivity indices. Productivity decreased at an average rate of −4.1 percent over the entire period of 1997‐2007. On average, this deterioration was due to efficiency change −6.1 percent. Technical progress is increased at an average rate of 2.1 percent. All rates at global level are statistically significant at 95 percent.

The main contribution of this paper is to provide an efficiency analysis using a non‐parametric approach with a robust estimator that has been suggested recently by Cazals et al. This methodology is that the first time that is applied in the analysis of retail sector. In addition, we analyze productivity growth using bootstrapping Malmquist indices. This methodology allows for a more careful analysis of what happens at firm level. Differences in conclusions between the original estimates and the bootstrap results are more evident when we scrutinize the sample firms and individual levels.

The authors examine the performance of individual global equity funds in Central and Eastern Europe (CEE) and separate the skill of their fund managers from luck.

The authors use cross-sectional bootstrap simulations to study the monthly net and gross returns of 175 funds over the period September 2005 to December 2019. Simulations are applied to three, four, and five-factor asset pricing models, and to regressions run on fund-specific benchmark indexes. The authors also examine the value added by all funds and by fund size groups.

Using multifactor models, a majority of the individual funds fail to deliver alpha, both net and gross of fees; whereas, most of the negative alphas appear due to poor skills, not bad luck. Relative to benchmark indexes, about 5% of the sample shows skill only gross of fees, indicating that fund management fees absorb this skill. As a whole, global equity funds in CEE add more economic value than they destroy, gross of fees, which is largely driven by large funds.

Market-tracking passive indexes are the most reliable choice for investors who want to maximise their risk-adjusted returns at the lowest possible cost. However, investors with a high level of risk appetite might prefer small actively managed funds in CEE when market conditions are stable or growing. Investors who are less risk tolerant might prefer large actively managed funds.

This is the first study to shed light on the presence of skill in mutual fund returns in CEE.

The purpose of this paper is to assess the performance of Greek fossil fuel‐fired power stations employing a data envelopment analysis (DEA) model combined with bootstrapping.

DEA is used to derive aggregate performance indicators using data on inputs and desirable and undesirable outputs for a sample of fossil fuel‐fired power stations. The statistical significance of the derived aggregate performance indicators is assessed via the bootstrapping approach.

The results suggest that the power stations in the sample are considerably more inefficient than revealed by the initial point estimates of inefficiency. Moreover, the non‐lignite‐fired stations of the sample are on an average more efficient than the lignite‐fired stations.

DEA represents a useful framework for exploring the current state to derive aggregate performance indicators of power stations, and moreover, the statistical properties of these metrics can be assessed via the bootstrapping approach.

The bootstrapping approach in DEA shows its superiority over DEA models that do not address the uncertainty surrounding point estimates. The DEA bootstrapping model used in this study to model environmental performance in the power station electricity production setting provides bias correction and confidence intervals for the point estimates and it is therefore more preferable.

The derivation of aggregate performance indicators of Greek fossil fuel‐fired power stations is an important addition to the existing literature on energy economics. The paper is also innovated in providing the statistical properties of the derived performance metrics.

The main purpose of this study is to examine the possibility of prediction of Greek takeover targets that belong to the industrial sector, emphasizing the econometric methodology and the prediction test.

The study uses a sample of 51 targets and 290 non‐targets exclusively from Greek industry over the period 1997‐2005. In order to achieve a better predictive accuracy the paper uses a new econometric methodology, the bootstrap mixed logit and different (more advanced) techniques of prediction test and choice of cutoff values.

The results exhibit that bootstrap mixed logit has significant and valuable predictive ability with respect to the classical conditional logit model. Furthermore, the predictive accuracy is higher than the results of other studies (e.g Palepu and Espahbodi and Espahbodi).

The main contribution of this study is the application of the bootstrap mixed logit in analyzing Greek takeovers. The results change the prediction variables as well as the determinants of the takeover target characteristics for the Greek industry. This is meaningful, not only for the investors that seek to increase the value of their fortune through acquisitions, but also for the managers that can detect if their firm might be considered a takeover target.

The purpose of this paper is to measure the efficiency of UK airlines in light of all the recent industry challenges.

The study measured the technical efficiency of airlines through the innovative data envelopment analysis (DEA) bootstrap methodology.

Results based on a sample of recent input/output data indicated that the efficiency of UK airlines has continuously declined since 2004 to reach a value of 73.39 per cent in 2007. Factors which were found to be significantly and positively related to technical efficiency variations include airline size and load factor. The paper also highlights that factors such as increase in oil price and fierce market competition were also potential inefficiency determinants.

The findings of this paper provide a fresh link between airline performance and the current industry characteristics. UK airlines also have a major role in the European and international aviation sector, and thus a reflection on their efficiency could be of interest to private and public policy makers.

The paper focuses on a recent period and thus provide a fresh efficiency assessment of the airline industry. The study also extends the limited literature available on UK airlines.

The purpose of this paper is to estimate advertising efficiency in the Spanish beer industry and to analyse the effects of several environmental variables and brand portfolio scope on advertising efficiency scores.

A two-stage double bootstrap procedure is used. In the first stage, advertising efficiency is estimated using a bootstrapped data envelopment analysis on a multiple input-output model of advertising. In the second stage, a bootstrapped truncated regression model is estimated to identify the determinants of advertising efficiency. Both stages are estimated simultaneously. The empirical application is carried out on a sample of Spanish brewers between 2007 and 2014.

Results show low advertising efficiency scores and highlight the effects that environment and brand portfolio scope have on these estimates.

For the first time, this paper analyses the effect of environmental variables and the brand portfolio scope on advertising efficiency in the beer industry.

The purpose of this paper is to investigate the issue of efficiency in the Brazilian motor carrier industry, which has undergone significant transformations since the economy deregulation in the mid-1990s. The main research objective is to determine whether or not different types of cargoes and geographic regions serviced significantly impact trucking managerial efficiency levels.

Research objectives are accomplished by applying a two-stage data envelopment analysis model with bootstrapped estimates. Based on an unbalanced panel model, secondary data from the annual study published by Transporte Moderno (years 2002-2010) were collected and analyzed.

Results support anecdotal evidence regarding a heterogeneous impact of cargo mix and route mix on efficiency levels.

A major limitation of this work concerns the fact of working with secondary data instead of primary data, especially with respect to the set of inputs and outputs used in the analysis, which may not cover all aspects relevant to building an efficiency frontier. Despite this limitation, the study has made an important contribution in its use of panel data to demonstrate the impacts of different types of cargoes and geographic regions serviced on managerial efficiency levels in the trucking industry.

Managerial impacts in terms of mergers and acquisitions are addressed.

The contribution of this study is twofold. On the theoretical side, a valuable scale for the measurement of managerial efficiency was built and validated, representing an index toward the most productive cargo/route mix. On the other hand, the managerial implication of this possibility of measuring the efficiency levels is that motor carriers can use it as a basis for establishing future action plans.

Brazil, DEA, Longitudinal study, Efficiency drivers, Trucking industry, Unbalanced panel

 Research paper

El estudio investiga el tema de la eficiencia en la industria del transporte Brasileña, la cual ha experimentado cambios significativos desde la desregulación de la economía a mediados de los años noventa. El objetivo principal de la investigación es determinar si los diferentes tipos de cargas y regiones geográficas que han recibido los servicios impactan significativamente o no los niveles de eficiencia administrativa de las empresas de camiones.

Los objetivos de la investigación se lograron usando un modelo DEA de dos etapas con estimaciones bootstrap. Basado en un modelo de panel no balanceado, se obtuvieron y analizaron datos secundarios del estudio anual publicados por Transporte Moderno (años 2002-2010).

Los resultados apoyan la evidencia anécdota en lo relacionado con el impacto heterogéneo de mezcla de cargas y una combinación de rutas en los niveles de eficiencia.

La limitación más grande de este trabajo es el hecho de trabajar con datos secundarios en vez de usar datos primarios, especialmente en relación con el set de inputs y outputs usados en este análisis, que podrían no cubrir todos los aspectos relevantes en la construcción de una frontera eficiente. A pesar de esta limitación, este estudio hace una importante contribución al usar datos de panel para demostrar los impactos de los diferentes tipos de cargas y regiones geográficas atendidas, en los niveles de eficiencia de la administración de la industria de transporte de camiones.

Se discuten los impactos de administración en términos fusiones y adquisiciones.

La contribución de este estudio es doble. Por el lado teórico, una escala relevante para medir la eficiencia de la administración fue construida y validada, que representa un índice hacia la combinación carga/ruta más efectiva. Por otro lado, las implicaciones administrativas de la posibilidad de medir niveles de eficiencia es que las empresas de transportes pueden usarloa como base para establecer planes futuros de acción.

Estudio longitudinal, Industria camionera, Brasil, DEA, Promotores de eficiencia, Panel no balanceado

 Trabajo de investigación

A pesquisa investiga o tema da eficiência na indústria brasileira de transporte rodoviário, a qual tem experimentado mudanças significativas desde a desregulamentação da economia em meados dos anos noventa. O objetivo principal da pesquisa é determinar se os diferentes tipos de cargas e de regiões geográficas atendidas impactam significativamente ou não nos níveis de eficiência na gestão de cargas rodoviárias.

Os objetivos da pesquisa foram atingidos usando um modelo DEA de dois estágios com estimativas bootstrap. Baseados em um modelo de painel, foram recolhidos e analisados dados secundários publicados no estudo anual da publicação Transporte Moderno (anos 2002-2010).

Os resultados apoiam a evidência baseada no senso comum relacionada ao impacto heterogêneo do mix de cargas e do mix de rotas nos níveis de eficiência.

A maior limitação de esta pesquisa concerne ao fato de trabalhar com dados secundários em vez de dados primários, especialmente em relação com a série de inputs e outputs utilizados na análise, que não puderam cobrir todos os aspectos relevantes para definição da fronteira de eficiência. Apesar dessa limitação, esta pesquisa traz uma importante contribuição ao utilizar dados de painel para demonstrar os impactos dos diferentes tipos de cargas e de regiões geográficas atendidas sobre os níveis de eficiência na gestão do transporte de cargas rodoviárias.

Os impactos da gestão em termos de fusão e aquisição são abordados.

A contribuição deste estudo é dupla. Pelo lado teórico, foi construída e validada uma escala relevante para medir a eficiência de gestão de cargas rodoviárias, que indica um índice para a combinação mais efetiva da combinação entre cargas e rotas. Por outro lado, quanto às implicações gerenciais, a possibilidade de medir os níveis de eficiência criam a possibilidade das empresas de transportes utilizá-los como base para futuros planos de ação.

Estudo longitudinal, Setor de transporte rodoviário, Brasil, DEA, Condutores de eficiência, Dados em painel

 Trabalhos de pesquisa

The purpose of this paper is to estimate and analyse the technical efficiency (TE) component of productivity for a sample of winegrowers from the Douro Demarcated Region in Portugal.

The data were collected through face-to-face surveys and includes a sample of 110 farmers’ vineyards with specific input-output information and other data about production systems during the year of 2017. The authors use a two-stage data envelopment analysis using bootstrap techniques to obtain TE scores in the farmers’ vineyards and to examine the determinants of its efficiency.

The results show that some farmers’ vineyards have a low efficiency level and that there are essential determinants of the production system, which can influence its efficiency. This suggests considerable opportunities for improvement of wine grape productivity through better use of available resources considering the state of technology.

This work has overcome the lack of data in the farmers’ vineyards, the lack of efficiency studies in the region and also allowed to evaluate the production systems and to assess their impact on efficiency.