Using the SUR model of tourism demand for neighbouring regions in Sweden and Norway

Salman, Khalik

doi:10.5772/24403

Cited by 2 publications

(1 citation statement)

References 72 publications

(96 reference statements)

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“…, T). Following Salman (2011), the errors of each equation are assumed to be normally distributed with mean zero, homoscedastic, and serially not autocorrelated. Furthermore, there is contemporaneous correlation between corresponding errors in different equations.…”

Section: Applicationmentioning

confidence: 99%

Ridge Type Shrinkage Estimation of Seemingly Unrelated Regressions And Analytics of Economic and Financial Data from “Fragile Five” Countries

Yüzbaşı

Ahmed

2020

JRFM

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In this paper, we suggest improved estimation strategies based on preliminarily test and shrinkage principles in a seemingly unrelated regression model when explanatory variables are affected by multicollinearity. To that end, we split the vector regression coefficient of each equation into two parts: one includes the coefficient vector for the main effects, and the other is a vector for nuisance effects, which could be close to zero. Therefore, two competing models per equation of the system regression model are obtained: one includes all the regression of coefficients (full model); the other (sub model) includes only the coefficients of the main effects based on the auxiliary information. The preliminarily test estimation improves the estimation procedure if there is evidence that the vector of nuisance parameters does not provide a useful contribution to the model. The shrinkage estimation method shrinks the full model estimator in the direction of the sub-model estimator. We conduct a Monte Carlo simulation study in order to examine the relative performance of the suggested estimation strategies. More importantly, we apply our methodology based on the preliminarily test and the shrinkage estimations to analyse economic data by investigating the relationship between foreign direct investment and several economic variables in the “Fragile Five” countries between 1983 and 2018.

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Section: Applicationmentioning

confidence: 99%

Ridge Type Shrinkage Estimation of Seemingly Unrelated Regressions And Analytics of Economic and Financial Data from “Fragile Five” Countries

Yüzbaşı

Ahmed

2020

JRFM

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Marcellus Shale Gas Boom and Forestry Employment: Evidence from West Virginia

Gazal

Arano

2021

Forest Science

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Advancement in drilling technology has increased natural gas extraction activities from the Marcellus shale deposit resulting in a shale gas boom in many regions, including West Virginia. This boom has created a significant labor demand shock to local economies experiencing the boom. A number of studies have shown that a shale gas boom directly increases employment and the income of those working in the industry. However, the boom can also have an adverse impact on other sectors through the resource movement effect and intersector labor mobility, pulling workers away from a related sector like forestry. Thus, an econometric model of employment in the forestry sector was developed to investigate the impact of the Marcellus shale gas boom in West Virginia. There is evidence of a labor movement effect with forestry employment negatively affected by the Marcellus shale boom. Specifically, the overall marginal effect of the shale boom on forestry employment is approximately 435 fewer jobs. However, the extent of the decline is slightly moderated by a higher relative wage between gas and forestry, perhaps suggesting diminishing returns and overall slack in the local labor market. Study Implications Although a Marcellus shale gas boom directly increases employment and the income of those working in that industry, it can have an adverse impact on other sectors by pulling workers away from a related sector like forestry. This study showed that employment in the West Virginia forestry sector was negatively affected by the shale gas boom. An important policy issue is how to manage the cyclical nature of shale gas booms and the negative impacts on other industries with long-term growth potential, like the forestry sector. This sector does not suffer through boom-and-bust cycles, making it important for long-term economic stability.

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Using the SUR model of tourism demand for neighbouring regions in Sweden and Norway

Cited by 2 publications

References 72 publications

Ridge Type Shrinkage Estimation of Seemingly Unrelated Regressions And Analytics of Economic and Financial Data from “Fragile Five” Countries

Ridge Type Shrinkage Estimation of Seemingly Unrelated Regressions And Analytics of Economic and Financial Data from “Fragile Five” Countries

Marcellus Shale Gas Boom and Forestry Employment: Evidence from West Virginia

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