Dummy Regression Research Articles

The Effect of Sharia Financial Inclusion on Creative Industry Financing (KSPPS BMT-NU Lenteng Branch, Sumenep)

This study aims to analyze the effect of Islamic financial inclusion on creative industry financing in KSPPS BMT-NU Sumenep. Multiple linear regression analysis technique was applied to identify the influence of independent variables.The research design used in this study is a questionnaire to customers of BMT-NU EAST JAVA Lenteng Branch Office who are willing to be respondents and fill out a questionnaire, the purpose of which is to find out how much influence the independent variables, namely, Profile (X1), Income (X2), Accessibility (X3), and Product (X4) on financing the creative industry in Sumenep Regency. The results of the research obtained through multiple Linear Regression dummy variables are profile variables and products that have a significant positive effect on financing the creative industry of BMT-NU Lenteng Branch Sumenep customers. While the accessibility variable has a significant negative effect on financing the creative industry of BMT-NU Lenteng Sumenep Branch customers. While the income variable has a positive, but insignificant effect on financing the creative idustry of BMT-NU Lenteng Sumenep Branch customers.

The Effects of Pond Type and Water Quality Dynamics on Vannamei Shrimp Growth: A Dummy Regression Analysis

Vannamei shrimp is one of Indonesia's leading aquaculture sector commodities due to its high survival rate, short cultivation time, and disease resistance. Vannamei shrimp cultivation in Indonesia adopts an intensive system favoured for high productivity. In intensive cultivation systems, shrimp ponds typically utilize concrete or high-density polyethylene (HDPE) ponds. Each type has its own positive and negative side that affects the growth and production of Vannamei shrimp. Apart from the type of pond, water quality also played an important role in the growth of Vannamei shrimp. Water quality is one of the important factors in intensive shrimp cultivation. Pond type is categorical data and has a nominal measurement scale, while water quality is numerical data with a ratio measurement scale; ordinary regression analysis is unsuitable for analyzing the effect of pond type and water quality on the growth of Vannamei shrimp. Therefore, a dummy regression model accommodates these measurement scale differences. This research aims to determine the effect of different types of ponds and water quality dynamics on the growth of Vannamei shrimp and to select the best type of pond for intensive cultivation of Vannamei shrimp. Additionally, it aims to identify the water quality parameters that most influence the growth of Vannamei shrimp so that it can serve as a reference for Vannamei shrimp farmers to achieve high productivity efficiently. The study was conducted from November 2022 to January 2023 in Banyuwangi Regency, East Java Province, Indonesia. There are three concrete ponds and 10 HDPE ponds. The research method employed in this study is a survey method utilizing simple random sampling. The parameters in this research are the quality of cultivation water, including pH, temperature and dissolved oxygen (DO). The water samples taken are then measured for water quality in the laboratory. The results of this study indicate that the average values for water quality are still within the optimal range. The average ABW in HDPE and concrete ponds ranges from 2.30 to 9.39 grams per shrimp and 2.22-9.73 grams per shrimp. Based on the study's results, it can be concluded that different pond types and water quality dynamics, specifically pH and temperature, affect shrimp growth based on ABW. However, when considering SGR values, the type of pond does not have a significant impact. The water quality parameters that affect SGR are pH and temperature.

Irish Amyotrophic Lateral Sclerosis Incidence: Age, Period, and Cohort Effects Using a Partial Least Squares Regression Model.

To investigate the underlying reasons for variability in the incidence rate of amyotrophic lateral sclerosis (ALS) within the Irish population between the years 1996 and 2021. The Irish ALS register was used to calculate the incidence and to subsequently extract age at diagnosis (age), year of diagnosis (period), and date of birth (cohort) for all incident patients within the study period (n = 2,771). An age-period-cohort (APC) model using partial least squares regression was constructed to examine each component separately and their respective contribution to the incidence while minimizing the well-known identifiability problem of APC effects. A dummy regression model consisting of 5 periods, 19 cohorts, and 16 age groups was used to examine nonlinear relationships within the data over time. The CIs for each of these were estimated using the jackknife method. The nonlinear model achieved R2 of 99.43% with 2-component extraction. Age variation was evident with those in the ages 65-79 years contributing significantly to the incidence (βmax = 0.0746, SE = 0.000410, CI 0.00665-0.00826). However, those aged 25-60 years contributed significantly less (βmin = -0.00393, SE = 0.000291, CI -0.00454 to -0.00340). Each successive period showed an increase in the regression model coefficient suggesting an increasing incidence over time, independent of the other factors examined-an increase of β from -0.00489 (SE = 0.000264, CI -0.00541 to -0.00437) to 0.00973 (SE = 0.000418, CI 0.0105-0.00891). A cohort effect was demonstrated showing that the contribution of those born between 1927 and 1951 contributed to a significantly greater degree than the other birth cohorts (βmax = 0.00577, SE = 0.000432, CI 0.00493-0.00662). Using the Irish population-based ALS Register, robust age, period, and cohort effects can be identified. The age effect may be accounted for by demographic shifts within the population. Changes in disease categorization, competing risks of death, and improved surveillance may account for period effects. The cohort effect may reflect lifestyle and environmental factors associated with the challenging economic circumstances in Ireland between 1927 and 1951. Age-period-cohort studies can help to account for changes in disease incidence and prevalence, providing additional insights into likely demographic and environmental factors that influence population-based disease risk.

Spatial and temporal scaling of extreme rainfall in the United Kingdom

AbstractExtreme rainfall estimates for ungauged areas contribute to improved resilience to flooding. This study applies a sub‐daily rainfall scaling method to annual daily maximum rainfall series from 102 UK weather stations. We analyse resultant parameters by season, homogenous rainfall region, urban area and geographic factors to investigate how scaling varies temporally and spatially. Dummy regression models are built using these variables to predict the sub‐daily scaling parameter for any location in the United Kingdom. Estimated rainfall intensities are validated with observations and yield Mean Absolute Errors of 3.0, 1.9 and 0.9 mm/h for 1‐, 2‐ and 6‐h events, respectively. We also demonstrate intensity‐duration‐frequency curves at a site in Oxfordshire for scaled and observed data and find that 1‐ to 6‐h, 20‐year rainfall intensities are estimated to be within 9.4%. With such unified scaling relationships, it is possible to derive extreme rainfall for specified durations and return periods at ungauged locations. According to our cross‐validation of estimated and observed intensities, more than 88% of sites fall within 10% error bounds. This method offers a means of generating design rainfall series as input to flood simulation models to evaluate pluvial flood risks in urban areas.

Sampling Design for Car Survey Using Stratified Random Sampling

Perumda Pasar Juara wants to know the number of cars that enter the Kosambi Market parking area for one month. However, limited access to available data means that Perumda has to count vehicles manually. Therefore, an appropriate sampling design is needed to estimate the number of cars. The data used is the result of observations based on preliminary sampling on October 14-20, 2022 at 08:00-17:00 WIB. The variables of the data used are car arrival time, day dummy, and hour dummy. The method used is dummy regression analysis and stratified sampling design. The regression analysis results show that there are four strata where each stratum has a three-parameter Weibull distribution. Based on the results, the minimum sample size required with a 5% error rate is 116 hours per day and is allocated according to the strata

Pengaruh Murottal Qur’an Muri-Q terhadap Kecemasan Ibu Hamil Trimester III Mendekati Kelahiran

Anxiety gets worse when pregnant experience fear of childbirth. effectiveness of murottal Qur'an to promote calm. Based on a preliminary study of 64 mothers, 18.8% experienced severe anxiety and this is a fairly high result. The purpose study was analyze effectiveness (duration and frequency) of Murrotal Qur'an muri-Q to anxiety pregnant third trimester. The research design used observational analysis with prospective. Independent variable: level of anxiety and dependent variable: murrotal muri-Q. Zhung Self Rating Scale instrument to determine the level of anxiety of pregnant women, was used before and after 2 weeks of murrotal. The statistical test used was dummy regression with α 0.05. The results There is a difference in the anxiety level of pregnant women before and after listening to Murottal Muri-Q, with an average of 34.9 to 26.4. While the statistical test results showed (0.000<0.05) which means the Murrotal Qur'an muri-Q was effective in reducing anxiety of pregnant women 3rd trimester before delivery and duration affected the anxiety of pregnant ρ: 0,048 while frequency does not affect the anxiety of pregnant ρ: 0,15. To reduce the anxiety level of pregnant women, it is recommended that pregnant women listen to Muri-Q murottal longer.

Do self-regulated learning and flipped learning assisted by learning video affect learning outcomes? (Indonesian)

This study aims to determine how the influence of Self Regulated learning and Flipped Learning with the help of video learning simultaneously or partially can affect learning outcomes and to find the indicators of Self Regulated Learning that most contribute to learning that is carried out with the help of learning videos within the scope of this model. This research is a type of quantitative research with a total sample of 84 students from the 2021 class of the 2021/2022 even semester. The research used questionnaires and written tests as research tools. The data analysis technique uses multiple regression with the term Dummy Regression using gretl. It is called dummy regression because one of the variables is Flipped Learning as a dummy variable. Based on the results of the study, it was found that Flipped Learning and Self-Regulated Learning simultaneously had a significant and positive effect on learning outcomes, partially Flipped Learning had an effect on learning outcomes while Partial Self-Regulated Learning had no significant effect on learning outcomes. The Revisit indicator was found to be one of the most contributing indicators in flipped learning-assisted learning on learning outcomes. In this study, it resulted in implications through a finding that was different from previous research, partially SRL did not significantly affect student learning outcomes. This is possible because students' SRL is not enough to understand students in a learning material. It takes modifications to the environment outside of the student to optimize the student's SRL in learning activities, one of which is the use of learning videos in flipped learning

Effect of On-Street Parking and Pedestrian Crossing on Through Traffic in Jordan

Effect of On-Street Parking and Pedestrian Crossing on Through Traffic in Jordan

Stability Analysis of Macroeconomic Effect on The Jakarta Composite Index (JCI) During 2006-2021

This research aims to provide empirical evidence of macroeconomic effects on the Jakarta Composite Stock Price Index (JCI), precisely the exchange rate, GDP, gold prices, oil prices, and U.S. interest rates, as well as whether there are changes in the structure or stability of the regression during 2006-2021. The study employs quantitative research techniques such as panel data regression and dummy regression analysis with EViews 12. The results show that: (1) The exchange rate significantly negatively affects the JCI. (2) GDP significantly positively affect the JCI. (3) Gold prices significantly positively affect the JCI. (4) Oil prices significantly positively affect the JCI. (5) U.S. interest rates significantly positively affect the JCI. (6). The structure or stability regression of the macroeconomic effect on the JCI varies yearly. It means there is a change in the structure or stability of the regression during 2006-2021.

Overconfidence managers and the presence of leverage risk

In the presence of risky debt, the manager’s incentives change from refusing to accept projects with more risk (risk-shifting) and rejecting projects with less risk (risk-avoidance). Managers with all level confidence produce different biases of behavior about risk and uncertainty. The paper aims to analyze the influence of the debt to asset ratio (DAR) and managers’ overconfidence level on business risk. After extremely censored data 10 percent above, the type of pooled data collected is 3016 observation units of companies listed on the Indonesia Stock Exchange (IDX) period 2008–2019. Dummy regression was used for analysis with DAR, and level of overconfidence manager (high, upper middle, upper lower, low of overconfidence) is the explanatory variable, and business risk is the dependent variable. The presence of risky debt does not always produce risk-shifting, but in the reverse form is risk avoidance (underinvestment in risky projects). Managers fear losing their jobs and earning a bad reputation, and the results have distorted the managers’ all-level confidence role

Do daily price extremes influence short-term investment decisions? Evidence from the Indian equity market

For short-term investments in equity markets, investors use price points, candlestick patterns, moving averages, support and resistance levels, trendlines, price patterns, relative strength index, and moving average convergence-divergence as reference(s) for making decisions. This study investigates whether investors use daily price extremes (highest and lowest prices for the day) for making short-term investments or trading decisions in the context of the Indian equity market. Using 6,902 observations of daily data of the NIFTY 50 index since its launch, it is observed that daily price extremes (high or low) have no impact on opening returns of the next trading day. Based on the dummy regression analysis, next-day opening returns were found to be statistically significant, which implies the presence of momentum behavior. However, insignificant coefficients for high or low-price extremes of the day mean that investors do not use them as an anchor or reference point for decisions. Results are consistent over time and robust to the rising or falling markets. Further, opening returns were seen to be more volatile than closing returns in the first half of the sample, and they are less volatile in the second half, implying that markets have become more efficient in the last few years.

The Effect of Tai Chi on quality of life in seniors

Objective: This study investigates the effect of Tai Chi exercise on the quality of life of seniors from a demographic perspective. Methods: The SF-36 Quality of Life Scale questionnaire was administered to 224 seniors in Wuhan, divided into an experimental group (n = 134, seniors who had participated in Tai Chi exercise for three years or more) and a control group (n = 90, seniors who had not received Tai Chi exercise). An independent samples t-test, one-way Analysis of Variance ANOVA, and dummy regression analysis are conducted using multivariate statistics. Results: (1) The quality of life scores for seniors who participated in Tai Chi exercise were significantly different from those who did not (p < 0.01), mainly in the dimensions of Physical Functioning , Social Functioning , General Health , Vitality, and Health Transition; (2) The quality of life scores of the Tai Chi exercise group differed significantly (p < 0.05) between the genders, with women being higher than men, but not between the age groups, residence patterns and pre-retirement occupations (p > 0.05); (3) Highly significant differences in quality of life scores between the 61-90 minutes Tai Chi group and the <60 minutes and >90 minutes Tai Chi groups (F = 5.43, p < 0.01); (4) There was a highly significant difference in quality of life scores between the Tai Chi group exercising 5-6 times a week or every day and the Tai Chi group exercising less than 4 times a week (F = 5.28, p < 0.01), but not between the group exercising 5-6 times a week Tai Chi and the group exercising every day Tai Chi (t = -1.403, p > 0.05). Conclusion: Practicing Tai Chi Chuan can improve the quality of life of seniors, but the effect is influenced by gender and the length and frequency of exercise.

Dummy regression to predict dry fiber in Agave lechuguilla Torr. in two large-scale bioclimatic regions in Mexico.

Agave lechuguilla Torr., of the family Agavaceae, is distributed from southwestern United States to southern Mexico and is one of the most representative species of arid and semiarid regions. Its fiber is extracted for multiple purposes. The objective of this study was to generate a robust model to predict dry fiber yield (Dfw) rapidly, simply, and inexpensively. We used a power model in its linear form and bioclimatic areas as dummy variables. Training, generation (80%) and validation (20%) of the model was performed using machine learning with the package ‘caret’ of R. Using canonical correlation analysis (CCA), we evaluated the relationship of Dwf to bioclimatic variables. The principal components analysis (PCA) generated two bioclimatic zones, each with different A. lechuguilla productivities. We evaluated 499 individuals in four states of Mexico. The crown diameter (Cd) of this species adequately predicts its fiber dry weight (R2 = 0.6327; p < 0.05). The intercept (β0), slope [lnCd (β1)], zone [(β2)] and interaction [lnCd:Zona (β3)] of the dummy model was statistically significant (p < 0.05), giving origin to an equation for each bioclimatic zone. The CCA indicates a positive correlation between minimum temperature of the coldest month (Bio 6) and Dwf (r = 0.84 and p < 0.05). In conclusion, because of the decrease in Bio 6 of more than 0.5°C by 2050, the species could be vulnerable to climate change, and A. lechuguilla fiber production could be affected gradually in the coming years.

성과연봉제의 공정성 지각이 조직유효성에 미치는 영향

Purpose: This study was conducted to examine the influence of organizational justice in the relationship betweenperformance based annual salary and organizational effectiveness using 269 usable questionnaires gathered fromemployees who work in Korea. Research design, data, and methodology: Firstly, exploratory factor analysis was used to assess the validity andreliability of measurement scales. Secondly, Pearson correlation analysis and descriptive statistics were conducted todetermine the collinearity problem, further confirm the validity and reliability of constructs and thus test researchhypotheses. Multiple regression analysis and Dummy regression were used to assess the magnitude and direction ofeach independent variable, and vary the mediating variable in the relationship between many independent variablesand two dependent variables. Results: Mutiple Regression analysis showed two important findings: First, performance based annual salary significantlycorrelated with job satisfaction. Second, linking performance based annual salary to organizational justice significantlycorrelated with organizational effectiveness. Statistically, this result demonstrates that organizational justice does act asa partial mediating variable in the relationship between performance based annual salary and organizational effectivenessin the studied organizations. Implications: The implications of this study can be divided into three categories: theoretical contribution, robustness ofresearch methodology, and practical contribution. In terms of theoretical contribution, the findings of this studyhighlight three major issues: firstly, Operation of performance based annual salary partially affects “procedural justice”. Secondly, Structure of performance-Based Annual Salary strongly affects “distributive justice”. Thirdly, organizationaljustice(Procedural Justice and Distributive Justice) affect organizational effectiveness. In sum, this study has provided agreat integrated model to understand the influence of perception of organizational justice in performance models ofthe studied organizations.

Perbandingan Struktur Modal dan Nilai Perusahaan Sebelum dan Saat Pandemi Covid-19 di Bursa Efek Indonesia

The purpose of this study is to know the structure of capital and value companies before and when the covid-19 pandemic in the Indonesian stock exchange. This study includes association research. There are six variables used, which are capital structures, profitability, liquidity, corporate sizes, and dummy variables. The study's population is the health, telecommunications, and tourism Sub Company registered in the Indonesia Stock Exchange in 2018-2021. The sample in this study represents 23 companies. The data used is secondary data. Data collection techniques are documenting. The analysis techniques used are descryptive, electronic regression dummy statistics, multicolicerity tests, autokolinerity tests, heteroocrity tests, modeling verification tests, regression coefficient tests, and deterministic coefficients. Research has shown 1) profitability, liquidity, corporate size, and dummy variables have significantly affected the capital structure before and when the covid-19 pandemic. 2) capital structures, profitability, liquidity, corporate sizes, and dummy variables have significantly affected the company's values before and during the covid-19 pandemic.

Crisis transmission channel for 17 East-European countries during the Global Financial Crisis

ABSTRACT This paper investigates if the transmission channel of the Global Financial Crisis to 17 Eastern European markets can be directly connected with the US market or one of the three largest European markets. By employing a dummy regression model with a GJR-GARCH and EGARCH frameworks, the results show that Euronext is the main transmission channel for most analyzed markets. Latvia, Russia and Serbia were affected by the London Stock Exchange, while Slovakia showed no contagion. These results show that the crisis’s effects and transmission were not identical worldwide. This suggests that measures created to mitigate such crises should be tailored to each market.

Effect of Leverage Ratio and Ownership Structure on Internationalization of Indian Firms

The paper attempts to find a relation between internationalization of firms & the amount of leverage and ownership stake in the capital structure. 'Ownership' & 'Leverage' have been taken as independent variables for the purpose of this study; and 'Degree of internationalization'- defined as 'the percentage of total sales coming from foreign operation' is taken as the dependent variable for the purpose of this analysis. The multivariate dummy regression was run on the data of 100 firms to determine the nature of relationship between the capital structure and internationalization of firms. Further, t-test was used to find the strength of this relationship. The study found that a significant relationship exists between the degree of internationalization and capital structure. Ownership impacts internationalization, much more that leverage. Also the number of years used in the study was found insignificant to influence the nature of relationship.

Selection of Export Destination Countries for Home Industry Products Using Multiple Linear Regression Dummy Many Criteria

Purpose: The purpose of this research is to assist home industry products that are eligible for export in choosing the export destination country with the highest economic value. There are three export destinations, i.e Europe, the Middle East and Southeast Asia.&#x0D; Design/methodology/approach: Based on a sample of business actors in eight cities, several primary data were obtained which became the main data for analysis, through a certain approach, namely the analysis and estimation process, the results obtained that the analysis used in this study could be used as an approach to determine the answer to the problem, i.e Regression Multiple Linear Dummy Many criteria that can be used to determine the choice of export destination countries.&#x0D; Findings: There are no other studies that use dummy multiple linear regression analysis with many criteria in the estimation process in finding answers to existing cases. This analysis process turns out to be easier and more accurate when used in the estimation process. So that it becomes a separate alternative in the research analysis method. Therefore, this research can be a solution to the difficulty level of estimation that has been done by other researchers.&#x0D; Paper type: Research paper

Turn-of-the-month effect in cryptocurrencies

Purpose This study examines the turn-of-the-month (TOM) effect in Bitcoin (BIT), Ethereum (ETH) and Litecoin (LIT) cryptocurrencies from August 2015 to August 2021.Design/methodology/approach Dummy regression model is used to examine the presence of the TOM effect and to test the efficiency of the cryptocurrency market. The characteristics of the returns during TOM days are compared with that of the non-non-TOM trading days. The authors also develop a trading strategy to earn abnormal returns using the TOM effect.Findings The authors show that TOM returns are positive and significantly higher than that of non-TOM returns. Interestingly, the authors empirically show that the TOM effect is not driven by the day-of-the-week (DOW) effect or the January effect. Based on the significant TOM effect, the authors formulate a trading strategy that annually outperforms the buy-and-hold strategy for BIT by 21.77% and for LIT by 47.10%. Finally, the results are robust to using a Generailzed Auto Regressive Conditional Heteroskedasticity (GARCH) (1,1) model and the January 2018 sell-off.Practical implications The results have important implications for both traders and investors. The findings suggest that the investors might be able to earn excess profits by timing their positions in BIT and LIT taking the advantage of the TOM effect.Originality/value First, the authors provide the only study to report the evidence of the TOM effect in three leading cryptocurrencies, viz., BIT, LIT and ETH. Second, the authors control for the DOW effect and the January effect while investigating the TOM effect in cryptocurrency market. Finally, this study develops a trading strategy based on which the investors can time the cryptocurrency markets as indicated by the pattern of the TOM effect during the studied time period.

Lawful Sequence of Events and Cryptocurrency Anomalies: An Empirical Investigation

The structural variations related to legal tender of cryptocurrencies operating across the world markets has been instable since their inception. There have been many changes incorporated for their status to be recognized as a legal financial instrument for investment purposes over the virtual financial markets. The concept of anomalies associated with the popular efficient market hypotheses given by Eugene Fama existed for Bitcoin and few other cryptocurrencies over a period of time. The present work attempts to contribute to the existing literature on cryptocurrency studies. A focused investigation has been carried for cryptocurrencies to find different behaviour of returns on these currencies over a varied response from various countries with respect to their permissible manoeuvres. The study has used independent sample t-test, one-way ANOVA and dummy regression analysis to examine the day of the week effect for a time period between 2014–2020 split into multiple sub-periods. Anomalies have been found for cryptocurrencies across multiple sub-periods with varied magnitude.