• Communications for Statistical Applications and Methods
• /
• v.23 no.2
• /
• pp.179-187
• /
• 2016

The fixed effects panel probit model faces "incidental parameters problem" because it has a property that the number of parameters to be estimated will increase with sample size. The maximum likelihood estimation fails to give a consistent estimator of slope parameter. Unlike the panel regression model, it is not feasible to find an orthogonal reparameterization of fixed effects to get a consistent estimator. In this note, a hierarchical Bayesian model is proposed. The model is essentially equivalent to the frequentist's random effects model, but the individual specific effects are estimable with the help of Gibbs sampling. The Bayesian estimator is shown to reduce reduced the small sample bias. The maximum likelihood estimator in the random effects model is also efficient, which contradicts Green (2004)'s conclusion.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.7
• /
• pp.477-489
• /
• 2021

The purpose of this study is to examine the effects of credit risk on commercial banks' profitability in Afghanistan. Due to the availability of limited data, this study applies the Fixed Effects estimator on balance panel data of six domestic private commercial banks over the period 2014-2018. The study uses LLRTL, TLTA, and TLTD as credit risk indictors, size as bank-specific determinant, ROAA, ROAE, and NIM as profitability indicators. The study finds a robust negative and significant effect of LLRTL on ROAA, and ROAE, but positive and insignificant on NIM. The results also reveal significant positive effect of TLTA on NIM, however insignificant negative on ROAA while insignificant positive on ROAE. The study finds negative effect of TLTD on ROAA, ROAE, and NIM, but only significant on NIM. Further, this study reveals a robust negative and significant effect of size on all profitability indicators. The mean comparison of profitability demonstrates that NIM is in a better situation than others profitability indicators, which is a good sign for the Afghan banking sector. The findings of this study suggest that improving credit management, increasing efficiency of asset management or effectiveness of business model can increase commercial banks' profitability in Afghanistan.

• The Korean Journal of Applied Statistics
• /
• v.14 no.1
• /
• pp.13-24
• /
• 2001

In this paper, we investigated mean estimation methods in two-phase sampling. Under the fixed expected cost we reviewed the optimal sample sizes, minimum variances and approximate unbiased variance estimators for usual ratio estimator, stratified sample mean with proportional allocation and Rao's allocation of the second phase sample. Also we proposed combined ratio estimator, which uses both ratio estimation and stratification and derived optimal sample size, minimum variance and unbiased variance estimator. Through a limited simulation study, we compared estimators by design effects and came to know that ratio estimator is more efficient than stratified sample mean in some cases and inefficient in the other cases, but combined ratio estimator is more efficient than others in most cases.

• The Korean Journal of Applied Statistics
• /
• v.10 no.1
• /
• pp.177-187
• /
• 1997

This article considers the power performance of the tests in unbalanced two way mixed linear models with one fixed factor. The generalized least squares (GLS) F statistic testing no differences among the effects of the levels of the fixed factor is estimated using Henderson's method III, minimum norm quadratic unbiased estimator (MINQUE) with prior guess 1, maximum likelihood (ML) and resticted maximum likelihood (REML). We investigate the power performance of these test statistics. It can be shown, through simulation, that the GLS F statistics using four estimators produce similar type I error rates and power performance.

• Communications for Statistical Applications and Methods
• /
• v.21 no.2
• /
• pp.169-181
• /
• 2014

Marginalized random effects models (MREM) are commonly used to analyze longitudinal categorical data when the population-averaged effects is of interest. In these models, random effects are used to explain both subject and time variations. The estimation of the random effects covariance matrix is not simple in MREM because of the high dimension and the positive definiteness. A relatively simple structure for the correlation is assumed such as a homogeneous AR(1) structure; however, it is too strong of an assumption. In consequence, the estimates of the fixed effects can be biased. To avoid this problem, we introduce one approach to explain a heterogenous random effects covariance matrix using a modified Cholesky decomposition. The approach results in parameters that can be easily modeled without concern that the resulting estimator will not be positive definite. The interpretation of the parameters is sensible. We analyze metabolic syndrome data from a Korean Genomic Epidemiology Study using this method.

• The Journal of Asian Finance, Economics and Business
• /
• v.9 no.3
• /
• pp.195-202
• /
• 2022

This study investigates whether institutional investors increase or decrease the volatility of stock returns in the Thai stock market. For the purpose we used the data from SETSMART, a database provided by the Stock Exchange of Thailand (SET). Our sample is a balanced panel data covering 3,160 firm-year observations from 316 nonfinancial firms listed on the SET from 2011 to 2020. We analyze the link between institutional holdings and the volatility of stock returns by the pooled Ordinary Least Squares (OLS) model, the fixed effects model, and the random-effects model. In particular, we regress the stock return volatility on institutional ownership while controlling for firm size, financial leverage, growth opportunities, and stock turnover and accounting for industry effects and year effects. Our results indicate institutional investors' positive and significant influence on the volatility of the stock returns. Additionally, we performed the dynamic Generalized Method of Moment (GMM) estimator to alleviate concerns of possible endogeneity. The result still shows a positive impact of institutional investors on the volatility in stock returns. Overall, the findings of this study suggest that an increase in the volatility of stock returns in the Thai stock market may stem from a higher proportion of equity held by the institutional investors.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.9
• /
• pp.19-30
• /
• 2020

This paper investigates, in a single equation framework, the effect of bank-specific and macroeconomic determinants on micro-, small- and medium-sized loans by commercial banks in Indonesia. This study uses a sample of 790 observations from 79 commercial banks in Indonesia over the years 2006-2015. This study uses two estimation methods for our panel regressions: static and dynamic generalized method of moments (GMM) panel estimator. In static relationships, the literature usually uses the least square methods on fixed effects (FE) or random effects (RE). I found evidence that all banks, bank profitability and size are positively and significantly related to micro-, small- and medium-sized loans, while the coefficients of liquidity are significantly positive in all specifications, except government banks which is significantly negative. The relationship between risk and credit growth is negative for non-government banks. All estimated equations show that the effect of the capital variable on lending banks to MSMEs is not important in government banks and non-government banks. Finally, macroeconomic variables, such as inflation and gross domestic product, clearly affect the lending of the banking sector particularly non-state banks. The findings have several policy implications to Indonesia government, regulatory authority and bank managers in order to improve bank profitability through bank lending.

• Journal of Distribution Science
• /
• v.11 no.7
• /
• pp.5-13
• /
• 2013

Purpose - The study explores social well-being of the community of five selected countries of the South Asia: India, Pakistan, Sri Lanka, Nepal and Bangladesh. The study compares effectiveness of macroeconomic policies across the countries through interactive effects of the macroeconomic policy variables with the regional dummy variables. Research design, data, and methodology - Using the data set for the period of 1990-2008, this study employs panel data models, quantile regression methods, and the fixed effects method, which the constant is treated as group or country-specific. The model can also be known as the least-squares dummy variables estimator. Results - The results reveal significant chances of improvement in the well-being of the people while living in India and Pakistan as compared to the other countries of the region where India relatively stands with better chances of providing opportunities to improve the well-being of the people. Conclusions - This study recommends an increasing allocation of budget on education and health in order to enhance social well-being in the South Asian region. Inflation is the main cause of deteriorating well-being of the South Asian community by escalating the cost of living. Comprehensive study is recommended by employing the micro data models in the region.

• The Korean Journal of Applied Statistics
• /
• v.17 no.1
• /
• pp.61-73
• /
• 2004

Rotation sampling designs may be classified into two categories. The first type uses the same sample unit for the entire life of the survey. The second type uses the sample unit only for a fixed number of times. In both type of designs, the entire sample is partitioned into a finite number(=G) of rotation groups. This paper is generalization of the first type designs. Since the generalized design can be identified by only G rotation groups and recall level 1, we denote this rotation system as l/G rotation design. Under l/G rotation design, variance and mean squared error (MSE) of generalized composite estimator are derived, incorporating two type of biases and exponentially decaying correlation pattern. Compromising MSE's of some selected l/G designs, we investigate design efficiency, design gap effect, ans the effects of correlation and bias.

• Korea Trade Review
• /
• v.47 no.4
• /
• pp.233-254
• /
• 2022

Although there is growing literature evidence of linkages between global value chains (GVCs) and foreign direct investment (FDI), the results are mixed and ambiguous by geographic dimension, time period and sectoral scope. Moreover, bilateral approaches on these connections have been rarely analyzed. In this context, we investigate the effect of bilateral greenfield FDI and cross-border M&A on GVC linkages between host countries and source countries. We match three-year averages of bilateral FDI and UNCTAD-Eora GVC value-added data from 2005 to 2019 between 37 OECD sources and 176 host countries (37 OECD versus 139 non-OECD countries). In the structural gravity model, the empirical specification includes bilateral and country-period fixed effects and uses a Poisson Pseudo-Maximum Likelihood (PPML) estimator. We find that greenfield and M&A FDI promote forward and backward GVC linkage for all sectors between OECD countries, whereas greenfield FDI promotes backward GVC linkage between OECD and non-OECD countries. In addition, the results indicate that the degree of influence of GVCs by FDI flows is greater for forward GVC than backward GVC among OECD countries.