A double-hurdle approach to modelling tobacco consumption in Italy

Aristei, David; Pieroni, Luca

doi:10.1080/00036840600970229

Cited by 72 publications

(59 citation statements)

References 43 publications

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“…Present study shares the similar findings of Yen (2005), Aristei and Pieroni (2008), Bilgic et al (2010) and Lin (2010) that higher educated individuals are less probable to participate in smoking. This may be attributed to the notion that higher educated individuals tend to have better interpreting skill and more general health knowledge, and thereby would be more aware of the negative impacts of smoking (Bilgic et al, 2010;Lin, 2010).…”

Section: Discussionsupporting

confidence: 92%

“…This finding is also shared by Yen (2005) and Aristei and Pieroni (2008), who also find that older individuals are less probable to smoke. There exist two reasons for these outcomes (Manrique and Jensen, 2004;Yen, 2005).…”

Section: Discussionsupporting

confidence: 58%

“…Previous studies have consistently found that education is negatively associated with the probability to smoke (Yen, 2005;Aristei & Pieroni, 2008;Bilgic et al, 2010;Lin, 2010). In other words, individuals who with higher education background are less likely to smoke as compared to the lower educated.…”

Section: Variablesmentioning

confidence: 90%

“…Similarly, Aristei and Pieroni (2008), who based their study on Italian Household Budget Survey, also find that age reduces the likelihood of participating in smoking. In present study, age of respondents in continuous form is included.…”

Section: Variablesmentioning

confidence: 91%

“…Thereby, respondents' ethnic profile is included in the model as three categories -Malay, Chinese and Indian/others. Raptou et al (2005) and Aristei and Pieroni (2008) have all found that healthy lifestyle such as avoid of alcohol consumption would reduce the odds of participating in smoking. Similarly, Charilaou et al (2009), who study the relationship between physical activity and smoking behaviour among the adolescents, find that frequent participation in physical activity is also able to decrease the likelihood of smoking.…”

Section: Variablesmentioning

confidence: 99%

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Exploring Factors Influencing Smoking Behaviour in Malaysia

Cheah

Naidu²

2012

Asian Pacific Journal of Cancer Prevention

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Objective: The objective of present study is to investigate the determinants of smoking behaviour among adults in Malaysia. Method: Findings of the Third National Health and Morbidity Survey (NHMS-3) by the Ministry of Health, Malaysia, were used. The sample consisted of 34,539 observations. A logistic regression model was thus applied to estimate the probability to participate in smoking. Results: Age, income, gender, marital status, ethnicity, employment status, residential area, education, lifestyle and health status were statistically significant in affecting the likelihood of smoking. Specifically, youngsters, low income earners, males, unmarried individuals, Malays, employed individuals, rural residents and primary educated individuals were more likely to smoke. Conclusion: In conclusion, socio-demographic, lifestyle and health factors have significant impacts on smoking participation in Malaysia. Based on these empirical findings, several policy implications are suggested.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionsupporting

confidence: 58%

Section: Variablesmentioning

confidence: 90%

Section: Variablesmentioning

confidence: 91%

Section: Variablesmentioning

confidence: 99%

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Exploring Factors Influencing Smoking Behaviour in Malaysia

Cheah

Naidu²

2012

Asian Pacific Journal of Cancer Prevention

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Double Hurdle Model

Jones

2018

Wiley StatsRef: Statistics Reference Online

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This article reviews the specification, estimation, and application of the double hurdle model. The double hurdle is an extension of the standard censored regression (Tobit) model for limited dependent variables that allows the process that generates zero (censored) observations to be different from that which generates positive (uncensored) observations. Extensions of the hurdle model to count data and to panel data are discussed. The model has been used widely in applied microeconomics and empirical studies and relevant software are cited.

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Linkage between direct marketing and farm income: a double-hurdle approach

et al. 2010

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This study identifies factors affecting the adoption of a direct marketing strategy (DMS) by farmers and its impact on the gross sales of farm operations in the United States. The authors use a double-hurdle model and the 2002 Agricultural Resource Management Survey to evaluate empirically the adoption of a DMS and its impact on gross sales of farm operations managed by American farmers. Results suggest that production of organic crops and the regional location of the farm positively affect adoption of a DMS. Adoption of DMS, however, has a negative relation to large farms, farms with production contracts, and farms specializing in cash grains. Farms adopting a DMS are typically those with organic crops and those located in regions with access to a large metropolitan customer base. Our results show that farmers who have adopted a DMS continue to capture a larger proportion of the consumers' dollar increase gross sales than those who have not adopted a DMS. [EconLit citations: Q120; Q130; Q140]. r

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A double-hurdle approach to modelling tobacco consumption in Italy

Cited by 72 publications

References 43 publications

Exploring Factors Influencing Smoking Behaviour in Malaysia

Exploring Factors Influencing Smoking Behaviour in Malaysia

Double Hurdle Model

Linkage between direct marketing and farm income: a double-hurdle approach

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