scholarly journals Simar and Wilson two-stage efficiency analysis for Stata

2019 ◽  
Vol 19 (4) ◽  
pp. 950-988 ◽  
Author(s):  
Oleg Badunenko ◽  
Harald Tauchmann
Keyword(s):  
Production Efficiency ◽  
Estimation Procedure ◽  
Data Envelopment ◽  
Two Stage ◽  
Global Competitiveness ◽  
Explanatory Variables ◽  
World Economic ◽  
Original Procedure ◽  
Stage Estimation

When one analyzes the determinants of production efficiency, regressing efficiency scores estimated by data envelopment analysis on explanatory variables has much intuitive appeal. Simar and Wilson (2007, Journal of Econometrics 136: 31–64) show that this conventional two-stage estimation procedure suffers from severe flaws that render its results, and particularly statistical inference based on them, questionable. They additionally propose a statistically grounded bootstrap-based two-stage estimator that eliminates the above-mentioned weaknesses of its conventional predecessors and comes in two variants. In this article, we introduce the new command simarwilson, which implements either variant of the suggested estimator in Stata. The command allows for various options and extends the original procedure in some respects. For instance, it allows for analyzing both outputand input-oriented efficiency. To demonstrate the capabilities of simarwilson, we use data from the Penn World Tables and the Global Competitiveness Report by the World Economic Forum to perform a cross-country empirical study about the importance of quality of governance in a country for its efficiency of output production.

Efficiency of Microfinance Institutions in India: A Two-Stage DEA Approach

2019 ◽  
Vol 15 (1) ◽  
pp. 49-77 ◽  
Author(s):  
Ram Pratap Sinha ◽  
Pallavi Pandey
Keyword(s):  
Environmental Variable ◽  
Current Approach ◽  
Data Envelopment ◽  
Microfinance Institutions ◽  
Two Stage ◽  
Conditional Performance ◽  
Evaluation Of Performance ◽  
Bootstrap Approach ◽  
Stage Estimation ◽  
The Relationship

The present study uses robust data envelopment analysis to estimate the performance of 30 Indian microfinance institutions (MFIs) from 2008–2009 to 2015–2016. Due to the non-availability of information in some instances, the present study uses an unbalanced panel of observations. In the matter of evaluation of performance, the study makes a major departure from the extant studies undertaken in the Indian context and adopts a double bootstrap approach originally suggested by Simar and Wilson. The current approach thus evaluates conditional performance of the in-sample MFIs in the presence of capital-to-asset ratio as an environmental variable. The two-stage estimation also involved the estimation of the influence of capital-to-asset ratio on the reciprocal of efficiency scores, and contrary to the expectations, the relationship was found to be positive.

scholarly journals Corporate Practices and National Governance Systems: What do Country Rankings Tell Us?

2005 ◽  
Vol 6 (3) ◽  
pp. 583-604 ◽  
Author(s):  
Peter Cornelius
Keyword(s):  
Corporate Governance ◽  
Firm Level ◽  
Global Competitiveness ◽  
Mode Of Entry ◽  
Governance Systems ◽  
Accession Countries ◽  
Country Rankings ◽  
Investment Capital ◽  
World Economic

AbstractNations compete for investment capital, and the assurances investors seek as they decide to provide that capital are universal. Motivated by the growing appetite for a global benchmark of corporate behaviour, this paper examines the relationship between the measured quality of corporate governance at the firm level and national competitiveness. It begins by analyzing the perceived quality of institutions in the 23 largest capital markets. Hypothesizing that good corporate governance at the company level may compensate for perceived weaknesses in the institutional framework, the paper then focuses on the pilot governance index developed by the Financial Times and ISS and compares it with new survey evidence from the World Economic Forum's Global Competitiveness Report. Finally, the paper discusses corporate governance in the EU accession countries and the extent to which the quality of governance has affected the mode of entry for foreign investment.

Bounded Risk Two-stage Estimation Procedure for a U(aq, bq) Distribution

2020 ◽  
pp. 000806832096334
Author(s):  
V. N. Kadam ◽  
H.S. Patil
Keyword(s):  
Stopping Time ◽  
Estimation Procedure ◽  
Sampling Procedure ◽  
Two Stage ◽  
Assigned Value ◽  
Q Model ◽  
Bounded Risk ◽  
Stage Estimation ◽  
Assigned Number ◽  
Uniformly Bounded

In the literature, an extensive work on sequential fixed-width confidence interval for the parameter of U( q, m q) model, where m > 1 is known, is available. In this article, we propose a two-stage sampling procedure for estimating the parameter q of U( aq, bq) distribution, where a < b are positive and known. Here, the risk of an estimator [Formula: see text] of q is less than a pre-assigned number w (>0), that is, [Formula: see text], 0 < A < ∞ is known. We determine the parameter Bk of stopping variable so that the risk is uniformly bounded by a pre-assigned value w. We have also tabulated the values of the expected stopping time and its standard deviation (SD).

Efficiency-based recruitment plan for chained quick-service enterprise

2006 ◽  
Vol 25 (3) ◽  
pp. 197-209
Author(s):  
Chun-Hsiung Lan ◽  
Yu-Hua Lan ◽  
Chi-Chung Chang ◽  
Liang-Lun Chuang
Keyword(s):  
Production Efficiency ◽  
Quantitative Approach ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Two Stage ◽  
Stage Design ◽  
Second Stage ◽  
Two Stage Design ◽  
Using Data ◽  
Quick Service

This paper describes a research method called two-stage design consisting of the determination of the efficiency for each quick-service restaurant of chained enterprise at the first stage by using Data Envelopment Analysis (DEA), and then proposes an approach of Recruitment and Allocation (RA) plan for supporting the everlasting running of the enterprise in the second stage. The technical efficiency, the scale efficiency, the production efficiency, and the return to scale are conducted in the first stage of this two-stage research design. In addition, this study also proposes the potentially improved value to promote the relative efficiency of each chained restaurant through the improvement of inputs or outputs items. Besides, the RA plan is proposed in the second stage of the two-stage design. The RA plan is an efficiency-based quantitative approach to recruit employees as well as to determine the allocation of those recruited employees. This study indeed provides a constructive and quantitative approach of solving the dilemma issue “how to reasonably recruit and allocate employees” for decision makers with profound insight in the quick-service enterprise.

Modeling out-Migration from Depressed Regions: The Significance of Origin and Destination Characteristics

1980 ◽  
Vol 12 (7) ◽  
pp. 799-812 ◽  
Author(s):  
G L Clark ◽  
K P Ballard
Keyword(s):  
Estimation Procedure ◽  
The United States ◽  
Migration Decision ◽  
Two Stage ◽  
Cross Sectional ◽  
Capital Theory ◽  
Testing Procedures ◽  
Stage Estimation ◽  
Theory Use ◽  
Depressed Regions

Many migration models, whether derived from the Hicksian macroadjustment approach or from human capital theory, use simultaneously origin and destination variables in their empirical testing procedures. In this paper it is hypothesized that the actual out-migration decision process has two separate but interrelated stages—the decision to leave and the decision as to the destination. A two-stage estimation procedure is used to analyze the significance of origin characteristics as determinants of out-migration, and the factors that allocate migrants to particular destinations. The model is applied to understanding the patterns and determinants of out-migration from a depressed region, the Central Appalachians of the United States of America. Time-series and cross-sectional models are utilized to evaluate the hypothesized two-stage process over the period 1958–1975.

Speeding up estimation of the Hurst exponent by a two-stage procedure from a large to small range

2017 ◽  
Vol 34 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Yen-Ching Chang
Keyword(s):  
Discrete Time ◽  
Hurst Exponent ◽  
Estimation Procedure ◽  
Computational Time ◽  
Small Range ◽  
Two Stage ◽  
Content Type ◽  
Computational Performance ◽  
The Difference ◽  
Stage Estimation

Purpose The Hurst exponent has been very important in telling the difference between fractal signals and explaining their significance. For estimators of the Hurst exponent, accuracy and efficiency are two inevitable considerations. The main purpose of this study is to raise the execution efficiency of the existing estimators, especially the fast maximum likelihood estimator (MLE), which has optimal accuracy. Design/methodology/approach A two-stage procedure combining a quicker method and a more accurate one to estimate the Hurst exponent from a large to small range will be developed. For the best possible accuracy, the data-induction method is currently ideal for the first-stage estimator and the fast MLE is the best candidate for the second-stage estimator. Findings For signals modeled as discrete-time fractional Gaussian noise, the proposed two-stage estimator can save up to 41.18 per cent the computational time of the fast MLE while remaining almost as accurate as the fast MLE, and even for signals modeled as discrete-time fractional Brownian motion, it can also save about 35.29 per cent except for smaller data sizes. Originality/value The proposed two-stage estimation procedure is a novel idea. It can be expected that other fields of parameter estimation can apply the concept of the two-stage estimation procedure to raise computational performance while remaining almost as accurate as the more accurate of two estimators.

scholarly journals Competitiveness of V4 Countries Using the Global Competitiveness Index

2020 ◽  
Vol 74 ◽  
pp. 06007
Author(s):  
Veronika Galgánková
Keyword(s):  
Slovak Republic ◽  
Financial Reports ◽  
Global Competitiveness ◽  
World Economic ◽  
Global Competitiveness Index ◽  
Competitiveness Index ◽  
Future Direction ◽  
The Individual

The article is focused on the evaluation and comparison of the international competitiveness of the Visegrad countries – four countries Slovak Republic, Czech Republic, Hungary and Poland. The article consists of four chapters. The first chapter is focused on a short introduction to the issue. The second chapter briefly describes the methodology used in writing the article. It analyzes in detail the individual parts and subindices of the Global Competitiveness Index. The third chapter evaluates the specific values of the index which the countries of Visegrad four achieved from 2010 to 2018. The fourth chapter focuses on assessing the strengths and weaknesses of the countries’ competitiveness. It also contains a proposal for the future direction of states. The concept of global competitiveness is increasingly being used to assess many different methods and indices in comparing countries. One of the best known indices is the Global Competitiveness Index, which is compiled annually by the World Economic Forum. It assesses how countries achieve and maintain economic growth and how business of every country is influenced by competitiveness. Higher quality of financial reports makes companies more competitiveness and motivate investors to put money into them.

Pairwise estimation of multivariate longitudinal outcomes in a Bayesian setting with extensions to the joint model

2020 ◽  
pp. 1471082X2094506
Author(s):  
Katya Mauff ◽  
Nicole S. Erler ◽  
Isabella Kardys ◽  
Dimitris Rizopoulos
Keyword(s):  
Importance Sampling ◽  
Estimation Procedure ◽  
Joint Model ◽  
Limited Information ◽  
Time To Event ◽  
Two Stage ◽  
Bivariate Model ◽  
Longitudinal Outcomes ◽  
Credible Intervals ◽  
Stage Estimation

Multiple longitudinal outcomes are theoretically easily modelled via extension of the generalized linear mixed effects model. However, due to computational limitations in high dimensions, in practice these models are applied only in situations with relatively few outcomes. We adapt the solution proposed by Fieuws and Verbeke (2006) to the Bayesian setting: fitting all pairwise bivariate models instead of a single multivariate model, and combining the Markov Chain Monte Carlo (MCMC) realizations obtained for each pairwise bivariate model for the relevant parameters. We explore importance sampling as a method to more closely approximate the correct multivariate posterior distribution. Simulation studies show satisfactory results in terms of bias, RMSE and coverage of the 95% credible intervals for multiple longitudinal outcomes, even in scenarios with more limited information and non-continuous outcomes, although the use of importance sampling is not successful. We further examine the incorporation of a time-to-event outcome, proposing the use of Bayesian pairwise estimation of a multivariate GLMM in an adaptation of the corrected two-stage estimation procedure for the joint model for multiple longitudinal outcomes and a time-to-event outcome ( Mauff et al., 2020 , Statistics and Computing). The method does not work as well in the case of the corrected two-stage joint model; however, the results are promising and should be explored further.

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