International Tourism Demand and Determinant Factor Analysis in Ethiopia

2019 ◽  
Vol 6 (1) ◽  
pp. 27-51 ◽  
Author(s):  
Yezihalemâ Sisayâ Takele
Keyword(s):  
Regression Model ◽  
Composite Index ◽  
Demographic Characteristics ◽  
International Tourism ◽  
Economic Factors ◽  
Tourism Demand ◽  
Annual Household Income ◽  
Political Factors ◽  
Study Results ◽  
Dynamic Panel Regression

In Ethiopia, the goal is to position tourism as a key economic sector, since recently it has been identified as one of the major strategies of using tourism to alleviate poverty. Motivated by this need, the study sought to investigate the determinants of international tourism demand. Specifically, the effect of economic factors, tourist socio-demographic characteristics, political factors, and destination characteristics on international tourism demand in Ethiopia. The study used both longitudinal and cross-sectional research designs and panel data for economic variables from eleven countries for the period of only one month time as of (December 10th, 2018 to January 10th, 2019). Data was collected from the World Bank database, the United Nations Database, the International Monetary Fund Database and the Ministry of Culture and Tourism Statistics. Survey data was collected from individual tourists leaving the country by using questionnaires. The study used a dynamic panel regression model to determine the effect of economic factors on international tourism demand and a count data regression model to determine the effect of socio-demographic characteristics, political factors and destination characteristics on international tourism demand. The study results indicated that tourism price, travelling cost, trade openness and word of mouth effect were the main economic factors influencing international tourism demand in Ethiopia. The tourist's socio-demographic characteristics such as annual household income, age, and occupational status were found to significantly influence international tourism demand. The political factors composite index and destination characteristics composite index were also important determinants of international tourism demand. Taking into consideration of all these factors affecting tourism demand, the government and all the tourism stakeholders should work towards making Ethiopia's tourism product competitive, maintain reasonable prices, further develop the tourism infrastructure and offer quality services, along with the diversification of tourism products.

Income Diversification and Bank Efficiency in Vietnam

2017 ◽  
pp. 52-67
Author(s):  
Sang Nguyen Minh
Keyword(s):  
Regression Model ◽  
Commercial Banks ◽  
Banking System ◽  
Operational Efficiency ◽  
Commercial Banking ◽  
Tobit Regression ◽  
Income Diversification ◽  
Positive Effects ◽  
Study Results ◽  
The Impact

This study uses the DEA (Data Envelopment Analysis) method to estimate the technical efficiency index of 34 Vietnamese commercial banks in the period 2007-2015, and then it analyzes the impact of income diversification on the operational efficiency of Vietnamese commercial banks through a censored regression model - the Tobit regression model. Research results indicate that income diversification has positive effects on the operational efficiency of Vietnamese commercial banks in the research period. Based on study results, in this research some recommendations forpolicy are given to enhance the operational efficiency of Vietnam’s commercial banking system.

scholarly journals Bivariate binary analysis on composite index of anthropometric failure of under-five children and household wealth-index

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Demeke Lakew Workie ◽  
Lijalem Melie Tesfaw
Keyword(s):  
Logistic Regression ◽  
Composite Index ◽  
Binary Logistic Regression ◽  
Wealth Index ◽  
Household Wealth ◽  
Education Level ◽  
Multiple Birth ◽  
Under Five ◽  
Under Five Children ◽  
Study Results

Abstract Background Malnutrition is the most common cause of mortality and morbidity of children in low and middle income countries including Ethiopia and household wealth index shares the highest contribution. Thus, in this study it is aimed to conduct bivariate binary logistic regression analysis by accounting the possible dependency of child composite index anthropometric failure and household wealth index. Methods In this study the data from Ethiopian Demographic and Health Survey (EDHS) 2016 involved 9411 under five children was considered. Child Composite Index Anthropometric Failure (CIAF) measures the aggregate child undernourished derived from the conventional anthropometric indices (stunting, underweight and wasting). The correlation between CIAF and wealth index was checked and significant correlation found. To address the dependency between the two outcome variables bivariate binary logistic regression was used to analyze the determinants of child CAIF and household wealth index jointly. Results Study results show that region, place of residence, religion, education level of women and husband/partner, sex of child, source of drinking water, household size and number of under five children in the household, mothers body mass index, multiple birth and anemia level of child had significant association with child CIAF. Female children were 0.82 times less likely to be CIAF compared to male and multiple birth children were more likely to be CIAF compared to single birth. Children from Oromia, Somalie, Gambela, SNNPR, Harari and Addis Ababa region were 0.6, 0.56, 0.67, 0.52, 0.6 and 0.44 times less likely to be CIAF compared to Tigray. A household from rural area were 15.49 times more likely poor compared to a household. The estimated odds of children whose mothers attended primary, and secondary and higher education was 0.82, and 0.52 times respectively the estimated odds of children from mothers who had never attended formal education. Conclusion The prevalence of children with composite index anthropometric failure was high and closely tied with the household wealth index. Among the determinants, region, religion, family education level, and anemia level of child were statistically significant determinants of both CIAF and household wealth index. Thus, the authors recommend to concerned bodies and policymakers work on household wealth index to reduce the prevalence of child composite anthropometric failure.

Guidelines for Constructing a Tourist Price Index (English version)

1985 ◽  
Keyword(s):  
Price Index ◽  
International Tourism ◽  
Basic Information ◽  
Tourism Demand ◽  
English Version ◽  
Tourism Product

The purpose of these guidelines is to furnish National Tourism Administrations with basic information, assessments and guidelines for constructing a tourist price index: an instrument that makes it possible to guide tourism policies and define actions and measures to be taken with regard to prices and promotion of the tourism product in the light of evolution in the domestic and international tourism demand.

Using Poisson Regression Model to Examine Student Travel Frequency Patterns in Beijing

2014 ◽  
Vol 1030-1032 ◽  
pp. 2738-2741
Author(s):  
Guang Jun Zhan
Keyword(s):  
University Students ◽  
Regression Model ◽  
Poisson Regression ◽  
Family Income ◽  
Influence Factors ◽  
Poisson Regression Model ◽  
Web Based ◽  
Study Results ◽  
Online Travel ◽  
Student Travel

This paper applies Poisson regression model to examine university students' travel frequencies and relevant influence factors, using the data collected from four universities in Beijing by a web-based online travel survey. It finds that student grade, family income and school attended have significant effects on students' travel frequency. The study results reveal students travel frequency characteristics at a disaggregate level and provide information to well understand student travel frequency patterns.

scholarly journals Analysis of decreasing natality trend in the Czech Republic

2008 ◽  
Vol 56 (3) ◽  
pp. 147-156
Author(s):  
Jitka Poměnková ◽  
Lenka Němcová
Keyword(s):  
Czech Republic ◽  
Regression Model ◽  
Multiple Regression Model ◽  
Living Standard ◽  
Second Step ◽  
Economic Factors ◽  
The Czech Republic ◽  
Financial Situation ◽  
Evaluation Influence ◽  
Family State

The aim of this paper is factors identification of the decreasing natality trend in the Czech Republic between years 1991–2005. This identification is done with respect to the financial situation and living standard of families.The first step, analysis of natality factor – animation natality, is performed. Animation natality is divi­ded according to the mother family state in the time of the birth. Trend of born in marriage and trend out of marriage are described. Following analysis is focused on decreasing component of natality – number of born in marriage.The second step is time series correlation analysis used for identification and evaluation influence of demographic and economic factors on decreasing component of natality. Based on this analysis, in­fluen­cing factors for regression model describing natality are selected.The last step is formulation and estimation of multiple regression model describing causality between natality in marriage and selected factors.

scholarly journals PREDICTION FOR THE 2012 UNITED STATES PRESIDENTIAL ELECTION USING MULTIPLE REGRESSION MODEL

2012 ◽  
Vol 6 (2) ◽  
pp. 77-97
Author(s):  
Pankaj Sinha ◽  
Aastha Sharma Aastha Sharma ◽  
Harsh Vardhan Singh
Keyword(s):  
Regression Model ◽  
Unemployment Rate ◽  
Presidential Election ◽  
Voting Behavior ◽  
Presidential Elections ◽  
Multiple Regression Model ◽  
Economic Factors ◽  
Gdp Growth Rate ◽  
Proposed Model ◽  
Midterm Elections

This paper investigates the factors responsible for predicting 2012 U.S. Presidential election. Though contemporary discussions on Presidential election mention that unemployment rate will be a deciding factor in this election, it is found that unemployment rate is not significant for predicting the forthcoming Presidential election. Except GDP growth rate, various other economic factors like interest rate, inflation, public debt, change in oil and gold prices, budget deficit/surplus and exchange rate are also not significant for predicting the U.S. Presidential election outcome. Lewis-Beck and Rice (1982) proposed Gallup rating, obtained in June of the election year, as a significant indicator for forecasting the Presidential election. However, the present study finds that even though there exists a relationship between June Gallup rating and incumbent vote share in the Presidential election, the Gallup rating cannot be used as the sole indicator of the Presidential elections. Various other non-economic factors like scandals linked to the incumbent President and the performance of the two parties in the midterm elections are found to be significant. We study the influence of the above economic and non-economic variables on voting behavior in U.S. Presidential elections and develop a suitable regression model for predicting the 2012 U.S. Presidential election. The emergence of new non-economic factors reflects the changing dynamics of U.S. Presidential election outcomes. The proposed model forecasts that the Democrat candidate Mr. Barack Obama is likely to get a vote percentage between 51.818 % - 54.239 %, with 95% confidence interval.

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