• Title/Summary/Keyword: Panel Threshold Regression Model

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Relationship Between Stock Price Indices of Abu Dhabi, Jordan, and USA - Evidence from the Panel Threshold Regression Model

  • Ho, Liang-Chun
    • The Journal of Industrial Distribution & Business
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    • v.4 no.2
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    • pp.13-19
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    • 2013
  • Purpose - The paper tested the relationship between the stock markets of the Middle East and the USA with the oil price and US dollar index as threshold variables. Research design, data, and methodology - The stock price indices of the USA, the Middle East (Abu Dhabi, Jordan), WTI spot crude oil price, and US dollar index were daily returns in the research period from May 21, 2001 to August 9, 2012. Following Hansen (1999), the panel threshold regression model was used. Results - With the US dollar index as the threshold variable, a negative relationship existed between the stock price indices of Jordan and the USA but no significant result was found between the stock price indices of Abu Dhabi and the USA. Conclusions - The USA is an economic power today:even if it has a closer relationship with the US stock market, the dynamic US economy can learn about subsequent developments and plan in advance. Conversely, if it has an estranged relationship with the US stock market, thinking in a different direction and different investment strategies will achieve good results.

Infrastructure-Growth Link and the Threshold Effects of Sub-Indices of Institutions

  • OGBARO, Eyitayo Oyewunmi;OLADEJI, Sunday Idowu
    • Asian Journal of Business Environment
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    • v.11 no.1
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    • pp.17-25
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    • 2021
  • Purpose: This study extends previous empirical work on the threshold effects of institutions on the relationship between infrastructure and economic growth. It does so by using three sub-indices of institutions as the threshold variable in place of aggregate index. This is with a view to determining the roles of the sub-indices in the nexus between infrastructure and economic growth. Research design, data and methodology: The analysis is based on a dynamic panel threshold regression model using a panel data set comprising 41 countries in Sub-Saharan Africa over the sample period of 1996-2015. Data are obtained from Ogbaro (2019). Results: The study finds that infrastructure exerts significant positive effects on economic growth below and above the threshold values of the three sub-indices, with higher effects above the threshold values. Results also show that on average, the Sub-Saharan African countries are not able to satisfy any of the threshold conditions, which accounts for their poor growth experience. Conclusion: The study concludes that countries with weak institutions do not benefit maximally from infrastructure development policies. The paper, therefore, recommends that countries in Sub-Saharan Africa need to focus on improving their institutional patterns if they are to reap the optimum benefits from their infrastructure development efforts.

Nuclear energy consumption, nuclear fusion reactors and environmental quality: The case of G7 countries

  • Cakar, Nigar Demircan;Erdogan, Seyfettin;Gedikli, Ayfer;Oncu, Mehmet Akif
    • Nuclear Engineering and Technology
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    • v.54 no.4
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    • pp.1301-1311
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    • 2022
  • Global climate change brings environmental quality sensitivity, especially in developed countries. Developed countries use non-renewable energy sources intensively both in their own countries and in other countries, they make productions that cause an enormous rate of increase in CO2 emissions and unsustainable environmental costs. This has increased the interest in environmentally friendly alternative energy sources. The aim of this study is to investigate the impact of nuclear energy consumption and technological innovation on environmental quality in G7 countries using annual data over the period 1970-2015. The Panel Threshold Regression Model was used for the analysis. Empirical findings have indicated that the relationship between nuclear energy consumption and carbon emissions differs according to innovation for nuclear power plants. It was also concluded that nuclear energy consumption reduces carbon emissions more after a certain level of innovation. This result shows that the increase in innovative technologies for nuclear power plants not only increases energy efficiency but also contributes positively to environmental quality.

A Study on the Relationship between Foreign Direct Investment and the Absorptive Capacity of a Host Country Using Panel Threshold Regression (패널문턱회귀를 활용한 외국인 직접투자와 현지국 흡수능력의 관계 연구)

  • Cao, Thu Trang;Ji-Young Hwang;Yun-Seop Hwang;Cheon Yu
    • Korea Trade Review
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    • v.47 no.4
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    • pp.89-102
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    • 2022
  • This study is designed to investigate the effect of inflow FDI on the host country's economic growth and the role of absorptive capacity in this relationship. Eight developing countries in East Asia, including Mongolia, Indonesia, Malaysia, Myanmar, the Philippines, Thailand, Vietnam, and Cambodia, are analyzed. Year data from 2000 to 2018 are used. Based on the study of Hansen (1999), the panel threshold effect model is used, and human capital, R&D, and infrastructure are set as absorptive capacity by referring to Wang and Hwang (2013). The analysis results are as follows. It is confirmed that FDI has a positive effect on the economic growth of the host country, and absorption capacity strengthens the relationship between FDI and economic growth in a positive direction. At this time, it appears that a threshold exists for the moderating effect of the absorptive capacity. It presents useful implications for economic growth in developing countries.

Onion yield estimation using spatial panel regression model (공간 패널 회귀모형을 이용한 양파 생산량 추정)

  • Choi, Sungchun;Baek, Jangsun
    • The Korean Journal of Applied Statistics
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    • v.29 no.5
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    • pp.873-885
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    • 2016
  • Onions are grown in a few specific regions of Korea that depend on the climate and the regional characteristic of the production area. Therefore, when onion yields are to be estimated, it is reasonable to use a statistical model in which both the climate and the region are considered simultaneously. In this paper, using a spatial panel regression model, we predicted onion yields with the different weather conditions of the regions. We used the spatial auto regressive (SAR) model that reflects the spatial lag, and panel data of several climate variables for 13 main onion production areas from 2006 to 2015. The spatial weight matrix was considered for the model by the threshold value method and the nearest neighbor method, respectively. Autocorrelation was detected to be significant for the best fitted model using the nearest neighbor method. The random effects model was chosen by the Hausman test, and the significant climate variables of the model were the cumulative duration time of sunshine (January), the average relative humidity (April), the average minimum temperature (June), and the cumulative precipitation (November).

Automatic TFT-LCD Mura Inspection Based on Studentized Residuals in Regression Analysis

  • Chuang, Yu-Chiang;Fan, Shu-Kai S.
    • Industrial Engineering and Management Systems
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    • v.8 no.3
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    • pp.148-154
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    • 2009
  • In recent days, large-sized flat-panel display (FPD) has been increasingly applied to computer monitors and TVs. Mura defects, appearing as low contrast or non-uniform brightness region, sometimes occur in manufacturing of the Thin-Film Transistor Liquid-Crystal Displays (TFT-LCD). Implementation of automatic Mura inspection methods is necessary for TFT-LCD production. Various existing Mura detection methods based on regression diagnostics, surface fitting and data transformation have been presented with good performance. This paper proposes an efficient Mura detection method that is based on a regression diagnostics using studentized residuals for automatic Mura inspection of FPD. The input image is estimated by a linear model and then the studentized residuals are calculated for filtering Mura regions. After image dilation, the proposed threshold is determined for detecting the non-uniform brightness region in TFT-LCD by means of monitoring the every pixel in the image. The experimental results obtained from several test images are used to illustrate the effectiveness and efficiency of the proposed method for Mura detection.