scholarly journals Stochastic frontiers of efficiency for Brazilian investment funds: a panel data analysis

2019 ◽  
Vol 16 (4) ◽  
pp. 352-365
Author(s):  
Luis Ferruz Agudo ◽  
João Serafim Tusi da Silveira ◽  
Daniel Knebel Baggio ◽  
Isoé Nícolas Schneider ◽  
Maria Margarete Baccin Brizolla
Keyword(s):  
Panel Data ◽  
Stochastic Frontier Analysis ◽  
Panel Data Analysis ◽  
Stochastic Frontier ◽  
Likelihood Method ◽  
Stochastic Frontiers ◽  
Investment Funds ◽  
Frontier Analysis ◽  
Effective Instrument ◽  
Sharpe Ratios

Foundations, methodological and empirical possibilities of measurement and analysis in the performance of financial investments within investment funds have been developed since they were once introduced in the 1970s, thus establishing a path of growing acceptance in financial markets and universities’ academies. The first approaches over the efficiency of these funds, considering their stochastic implications, occurred in the late 1990s and have evolved with the help of SFA – Stochastic Frontier Analysis, although it still needs more careful verification. This article measured and analyzed the stochastic frontier of efficiency over 33 different Brazilian investment funds from 2012 to 2015. For doing so, Battese and Coelli’s (1995) specifications was used. It shows the effects of inefficiencies, which are defined as explicit functions of specific factors in the context of panel data funds. They are estimated by the maximum likelihood method. Sharpe ratios (SR) were also calculated for comparative purposes. Based on these two indicators (SFA and SR), the most recommendable funds to invest and the ones in which the application should not be performed were identified. Such procedures have stimulated the necessary and promising studies, as well as future researches, which, in turn, may establish new methodological formulation as an efficient and effective instrument to choose the best and the safest funds to invest.

HOW FUNDING STRUCTURE AFFECTS EFFICIENCY OF R&D INVESTMENT BY LARGE- AND MEDIUM-SIZED INDUSTRIAL FIRMS IN CHINA? EVIDENCE FROM PROVINCE-LEVEL PANEL DATA

2019 ◽  
Vol 64 (04) ◽  
pp. 921-938
Author(s):  
YIXIAO ZHOU ◽  
RUNYANG ZHANG ◽  
LIGANG SONG
Keyword(s):  
Panel Data ◽  
Stochastic Frontier Analysis ◽  
New Products ◽  
Stochastic Frontier ◽  
Government Funding ◽  
Private Funding ◽  
Industrial Firms ◽  
Frontier Analysis ◽  
D Investment ◽  
Province Level

This study explores the efficiencies of firm’s R&D investment depending on the degree of reliance on government funding relative to firms’ private funding. Stochastic frontier analysis is applied on a sample of 30 provinces with data on R&D inputs and innovation outputs by all large- and medium-sized industrial firms in these provinces from 2000 to 2013. It is found that R&D investment financed by firms’ private funding is more efficient than that by government funding in generating new products, whereas R&D investment financed by government funding is more efficient than that by firms’ private funding in producing new patents.

scholarly journals KEBERLANJUTAN USAHA PENANGKAPAN PURSE SEINE DI PEKALONGAN DITINJAU DARI ASPEK EFISIENSI USAHA

2018 ◽  
Vol 11 (2) ◽  
pp. 7-13
Author(s):  
Dian Ayunita N.N. Dewi ◽  
B.A. Wibowo ◽  
Iqbal Ali Husni
Keyword(s):  
Maximum Likelihood ◽  
Panel Data ◽  
Cross Section ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Purse Seine ◽  
Frontier Analysis ◽  
Likelihood Model

Tujuan dari penelitian ini adalah menghitung efiensi teknis usaha penangkapan purse seine di PPN Pekalongan secara stokastik dan deterministik dan menganalisis efisiensi teknis untuk mengetahui prospek keberlanjutan usaha penangkapan purse seine di PPN Pekalongan. Metode analisis menggunakan Stochastic Frontier Analysis (SFA) dan Deterministic Frontier Analysis (DFA). SFA dan DFA merupakan model parametrik yang digunakan untuk mengukur efisiensi teknis. Model 1: DFA dengan data cross-section akan diestimasi dengan COLS. Model 2: SFA dengan data cross-section akan diestimasi dengan ML (Maximum Likelihood). Model 3: SFA dengan data panel diestimasi dengan proses ML. Variabel independent yang digunakan pada penelitian ini adalah lama trip (fishing days atau X1), GRT (Gross Registered Tonnage atau X2) kapal, jumlah ABK (crew members atau X3) sebagai faktor determinan yang digunakan oleh penangkapan purse seine di lokasi penelitian. Dan variabel terikat (Y) adalah output yaitu produksi tangkapan per tahun dari tahun 2015-2017. Fokus penelitian pada kapal purse seine berukuran 60-90 GT. Hasil dari penelitian ini adalah efisiensi teknis dari kedua kelompok kapal menunjukkan nilai inefisiensi dalam penggunaan ketiga variabel input. Hal ini diperkuat dengan hasil nilai korelasi (R) pada metode Deterministik Frontier dan Stokastik Frontier dengan data cross section serta panel data yang rendah (0,39 dan 0,311). Variabel X1 (lama trip) memiliki hubungan negatif dengan variabel Y (produksi) sedangkan X2 dan X3 memiliki hubungan positif terhadap Y. Pada armada penangkapan purse seine ukuran 60-90 GT, ketiga variabel input tidak mempunyai pengaruh yang signifikan terhadap perubahan jumlah produksi penangkapan.

scholarly journals The effects of efficiency on banks’ market risk: Empirical evidence from China

2021 ◽  
Vol 17 (2) ◽  
pp. 81-106
Author(s):  
Mohd Fahmee Ab-Hamid ◽  
Hawati Janor ◽  
Aisyah Abdul-Rahman ◽  
Mariani Abdul-Majid
Keyword(s):  
Value At Risk ◽  
Stochastic Frontier Analysis ◽  
Stock Exchange ◽  
Risk Measures ◽  
Panel Data Analysis ◽  
Stochastic Frontier ◽  
Market Risk ◽  
Frontier Analysis ◽  
Risk Increase ◽  
The Cost

This article investigates the effect of efficiencies on market risk using a sample of Chinese commercial banks from 2000 to 2015 using different measures of market risk; the Value at Risk (VaR) and Expected Shortfall (ES). The cost and profit efficiencies are estimated by the Stochastic Frontier Analysis (SFA) on the 12 biggest banks listed on the Shanghai Stock Exchange. In testing the effect between efficiency and market risk, this study applied four different models to uncover the relationship between VaR and ES as measures of market risk on cost and profit efficiencies. Utilising a panel data analysis, the results show that different banks efficiencies affect market risk measures differently. While bank cost efficiency reduces market risk, increase in profit efficiency increase market risk. The analysis in this study helps explain the unconvincing evidence of an inefficiencies-risk connection in the bank sector. Bank regulators and managers may need to focus on the cost and profit efficiencies-related initiatives to better manage the market risk. These findings provide bank managers with more understanding of bank risk and serve as an underpinning for bank supervision efforts aimed at strengthening the joint risk management of efficiency market risks.

Disaggregate energy efficiency of regions in Taiwan

2018 ◽  
Vol 29 (1) ◽  
pp. 34-48 ◽  
Author(s):  
Jin-Li Hu ◽  
Ming-Chung Chang ◽  
Hui-Wen Tsay
Keyword(s):  
Energy Efficiency ◽  
Panel Data ◽  
Energy Use ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Real Income ◽  
Stochastic Production Frontier ◽  
Content Type ◽  
Frontier Analysis ◽  
Electricity Power

Purpose The purpose of this paper is to explore Taiwan’s regional energy efficiency trend and complement the work of the total-factor energy efficiency (TFEE) index proposed by Hu and Wang (2006). It further extends panel data stochastic frontier analysis (SFA) modeling for estimating disaggregate energy efficiency. Design/methodology/approach This paper applies the panel data stochastic production frontier to estimate the TFEE scores for 20 administrative regions in Taiwan over the period 2004-2015. The SFA models include five inputs (employed population, amount of productive electricity power consumed, amount of electricity consumed for household and non-household electric lighting, amount of gasoline sales, and amount of diesel sales) and one output (total real income in the base year of 2011). Findings This research concludes with three main findings: the inefficient administrative regions of Taiwan include mostly large industrial parks and the petrochemical industry cluster; the top five administrative regions with inefficient diesel use are mostly metropolitan areas that the concern of air pollution caused by diesel system arouses the awareness to use less diesel fuel; and the average TFEE score on household and non-household electric lighting is higher than the usage efficiency of productive electricity power, gasoline, and diesel, but there is still room for efficiency improvement. Originality/value Most administrative regions in Taiwan are not efficient in almost all kinds of energy use. The results show that the efficiencies of using productive electricity power, gasoline, and diesel need to be improved a lot more.

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