scholarly journals An Econometric Model to Predict Participation in Urban and Community Forestry Programs in South Carolina, U.S.

2006 ◽  
Vol 32 (5) ◽  
pp. 229-235
Author(s):  
J. Jess Fleming ◽  
Thomas Straka ◽  
Stephen Miller
Keyword(s):  
South Carolina ◽  
Community Forestry ◽  
Econometric Model ◽  
Probability Model ◽  
Program Planning ◽  
Correct Prediction ◽  
Dummy Variables ◽  
Logit Regression ◽  
A Value ◽  
Forestry Programs

A regression-based econometric model was generated from a statewide survey of South Carolina, U.S., residents concerning participation in urban and community forestry programs. The econometric model attempts to estimate the probability of an individual’s participation. Results are intended to increase effectiveness of program planning and organization within state forestry commissions. Model 1 was created as follows: participation = F (gender, age, education, marital status, region, area raised, area reside, household, duties, and income). Because these responses represented qualitative values, a number of dummy variables (0 or 1, for example, for yes or no) were generated to more accurately reflect the values for participation and a logit model was used. Logit regression analysis produces a value between 0 and 1 that can be interpreted as a probability. Model 2, with fewer variables, was later created to reduce possible multicollinearity problems. Model 1 had a pseudo-R 2value of 0.2955 or a 29.55% probability of having a correct prediction for participation. Model 2 had a pseudo-R 2value of 0.2407. The models produced reasonable predictions of participation.

scholarly journals Pengaruh Faktor Sosial Ekonomi terhadap Perkawinan Muslim di Indonesia

2020 ◽  
Vol 6 (8) ◽  
pp. 1674
Author(s):  
Fauzia Aqilla Fadhil ◽  
Ilmiawan Auwalin
Keyword(s):  
Family Life ◽  
Regression Models ◽  
Probability Model ◽  
Muslim Women ◽  
Sample Population ◽  
Probit Regression ◽  
Linear Probability Model ◽  
Logit Regression ◽  
Indonesian Family Life Survey ◽  
Linear Probability

This study aims to find out what factors that affect a Muslim's decision to get married. This study uses the data from the Indonesian Family Life Survey (IFLS) with a quantitative approach using 83% of the sample population in Indonesia covering approximately 30,000 people taken in 13 of the 27 provinces in Indonesia. This study was analyzed using Linear Probability Model (LPM) regression, Logit regression and Probit regression. The data in this study were processed using STATA MP software. According to the results of data using three regression models, the factors that affect the decision of each individual in Indonesia in general to marry are gender, religion, age, education and occupation. The factors that affect each individual Muslim in Indonesia to make a decision to marry are gender, age, education and occupation. Then, for women in Indonesia in general, the factors that affect the decision to get married are religion, age, and occupation. Last but not least, for Muslim women, the factors that affect the decision to marry is age and occupation.Keywords: Socio-Economy, Muslim Marriage, Marital Decision

scholarly journals Financial and Strategic Pricing Analysis in the Development Market Using an Econometric Model

2020 ◽  
Vol 12 (1) ◽  
pp. 144
Author(s):  
Ainur A. Akhmetzianov ◽  
Andrew Y. Sokolov
Keyword(s):  
Real Estate ◽  
Econometric Model ◽  
Real Estate Market ◽  
Average Price ◽  
Planning Stage ◽  
Dummy Variables ◽  
Strategic Pricing ◽  
The Real Estate ◽  
Independent Variables ◽  
The Real Estate Market

This article demonstrates the use of a financial and econometric model with dummy variables to calculate the average price in the real estate market. The average price is used in the model for calculating project effectiveness and allows you to evaluate the profitability of the project at the construction planning stage. The number of rooms, the presence of a balcony, the number of sides of the windows and the number of floors were used as independent variables. A model with these factors showed qualitative estimates and can be applied for the purpose of forecasting prices in standard projects in the Russian real estate market.

scholarly journals Comparing the performance of analytical techniques for genetic parentage of half-sib progeny arrays

2009 ◽  
Vol 91 (5) ◽  
pp. 313-325 ◽  
Author(s):  
DEAN A. CROSHAW ◽  
MAUREEN B. PETERS ◽  
TRAVIS C. GLENN
Keyword(s):  
South Carolina ◽  
Multiple Mating ◽  
Probability Model ◽  
Natural Populations ◽  
Multiple Paternity ◽  
Genetic Data ◽  
Bayesian Probability ◽  
Published Data ◽  
Data Set ◽  
Analytical Approaches

SummaryThe prevalence of female multiple mating in natural populations is important for many questions in mating system evolution. Several statistical techniques use genetic data to estimate the number of fathers that contribute gametes to broods, but they have not been widely compared to assess the magnitude of differences in their performance. With a combination of new data and reanalysis of previously published data, we compared five analytical approaches: (1) allele-counting, (2) parental reconstruction in GERUD, (3) a Bayesian probability model to estimate the frequency of multiple mating (FMM), (4) computer simulations based on population allele frequencies in HAPLOTYPES and (5) Bayesian parental reconstruction in PARENTAGE. The results show that choice of analysis technique can significantly affect estimates of sire number. Estimates from GERUD conformed exactly to results obtained from strict exclusion of potential sires in an experimental context. However, estimates yielded by HAPLOTYPES and PARENTAGE sometimes exceeded the numbers from GERUD by as much as 120 and 55%, respectively. We recommend GERUD over these other approaches for most purposes because of its accuracy and consistency in this analysis. Our novel genetic data set allowed us to investigate the extent and frequency of multiple paternity in a marbled salamander (Ambystoma opacum) population in South Carolina, USA. A. opacum contrasted with other salamander species by having relatively low levels of multiple paternity (only 31–54% compared with 71–96%). Although A. opacum had the lowest level of multiple paternity under all analytical approaches used here, the magnitude of differences among species varied.

Do Chinese dairy firms have market power? an estimation of market power with price heterogeneity

2016 ◽  
Vol 8 (2) ◽  
Author(s):  
Qing Guo ◽  
H. Holly Wang ◽  
Yongjun Chen
Keyword(s):  
Market Power ◽  
Design Methodology ◽  
Small Firms ◽  
Econometric Model ◽  
Dairy Industry ◽  
Large Firms ◽  
Dummy Variables ◽  
Eastern Area ◽  
Competitive Industry ◽  
Western Area

Purpose The purpose of this paper is to investigate market power in dairy industry in China. Specifically, we analyze market power for different firm size, locations of region and city empirically. Design/methodology/approach We estimate the market power by controlling the unobserved price heterogeneity. The econometric model was developed through a typical production function. We added three dummy variables to differentiate firms of different sizes, at urban or rural locations, and in east or other regions, according to the characteristics of the dairy industry. A sample including 511 observations were used to do the regression. Findings Our results show that Chinese dairy industry as a whole is a competitive industry in general，while the large firms have gained considerable market power. The firms locate in the eastern area grow slower than firms locate in the middle and western area. Originality/value The authors believe that this is the first study to analyze the market power in China’s dairy industry by controlling the unobserved price heterogeneity. Dairy is usually thought to be competitive, while in our paper we found that large firms can exercise market power while small firms operate in a competitive market.

scholarly journals ANALISA FAKTOR-FAKTOR RASIO KEUANGAN TERHADAP PERAMALAN TARGET TAKEOVER TAHUN 2005

2008 ◽  
Vol 8 (2) ◽  
pp. 167
Author(s):  
HOTMAN T. POHAN
Keyword(s):  
Regression Analysis ◽  
Discriminant Analysis ◽  
Probability Model ◽  
The Other ◽  
Negative Sign ◽  
Positive Sign ◽  
Logit Regression ◽  
Other Hand ◽  
A Company

<p class="Style1"><strong><em>This research intend to continue last research about takeover and Q ratio that using discriminant </em></strong><strong><em>analysis.ln this research discriminant analysis connot be applied because it does not fulfill the assumption,therefore the analysis in this research uses logit regression analysis. By using logit regression analysis,writer get model that has been tested its validity and hypothesis of this research </em></strong><strong><em>can be proved.The hypothesis is that certain ratio can predict the possibility of taking over company </em></strong><strong><em>target.By cutting 5O% off ,a company can be concluded and classified wether it deserves or not to </em></strong><strong><em>be taken over. Ebitda to sales on behalf DER and CFO to sales ratio has positive sign in logit </em></strong><strong><em>regression probability model,it means that EBITDA to sales enhance the probability of taking </em></strong><strong><em>over On the other hand, ROE and PBV ratio have negative sign in this model,it means that these ratio lessen the probability of taking over.</em></strong></p><p class="Style1"><strong><em>Keywords: takeover, q ratio, logit regression probability model</em></strong></p>

scholarly journals Econometric Support of a Mass Valuation Process

2020 ◽  
Vol 20 (1) ◽  
pp. 81-94
Author(s):  
Mariusz Doszyń
Keyword(s):  
Real Estate ◽  
Econometric Model ◽  
Econometric Models ◽  
Dummy Variables ◽  
The Real Estate ◽  
Explanatory Variables ◽  
Advantages And Disadvantages ◽  
Proposed Model ◽  
Valuation Process ◽  
The Impact

AbstractResearch background: The issues undertaken in the paper include the specification of an econometric model in real estate mass appraisal. Advantages and disadvantages of using econometric models in real estate mass appraisal are discussed.Purpose: The issue of aiding the valuation process with an econometric model based on the Szczecin algorithm of real estate mass appraisal is discussed in the paper. Such problems like multicollinearity, lack of coincidence and nonmonotonic influence of attributes are pointed out. Also, potential solutions to these problems are mentioned. Moreover, the paper features a discussion of cases in which econometric appraisal is not sufficient.Research methodology: The base for constructing an econometric model is the so-called Szczecin algorithm of real estate mass appraisal. Based on the algorithm, the econometric model was created to enable determining the impact of real estate attributes and location on their value.Results: problems related with specification, estimation and verification of the real estate mass appraisal econometric model are discussed in an empirical example.Novelty: A non-linear model is proposed, which features explanatory variables introduced into the model, and by taking into consideration the scale of their measurement. The proposed model, by introducing dummy variables, also account for the impact of a location, which significantly improves the fit to empirical values.

scholarly journals Local Outcomes of Federal and State Urban & Community Forestry Programs

2011 ◽  
Vol 37 (4) ◽  
pp. 152-159
Author(s):  
Richard Hauer ◽  
Gary Johnson ◽  
Michael Kilgore
Keyword(s):  
United States ◽  
Regression Model ◽  
Multiple Regression ◽  
Community Forestry ◽  
Urban Community ◽  
The United States ◽  
Multiple Regression Model ◽  
Cost Share ◽  
Rate Of Increase ◽  
Forestry Programs

Increasing local urban and community forestry (U&CF) programs and activities in the United States is a goal of state and federal U&CF programs. This study found local U&CF programs within the 50 United States increased in activity between 1997 and 2002 at a 2.1% annual rate of increase. Several attributes of state U&CF forestry programs from a multiple regression model and correla-tion analysis partially explain the increase in local U&CF program activity. The number of technical assists in a state were a strong pre-dictor for increased local activity. Less certainty was found with state money used to fund the state U&CF program or the use of cost-share assistance (Federal Cooperative Forestry Assistance Challenge Cost-share Grants) and this increase. Study findings provide evidence that state and federal U&CF programs within the United States are furthering the building of capacity and development of local U&CF programs.

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