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This paper describes a simple and interesting application of structural equation modeling for a single lecture in an undergraduate econometrics course to introduce students to the concept of using data to recover latent variables. The application centers around using hourly observations on ride wait times at Disney’s Magic Kingdom to infer how crowded it is at the theme park. Pedagogically, the material is presented in the context of the linear regression model, so the discussion works to enhance students’ understanding of core material, not to introduce new disparate methods. The application provides interesting economic-based insights, like which ride’s wait times are categorically most informative about how crowded it is at the park.

The article discusses the impact of the upcoming general election on the retail sector. The author mentions that regardless of the election outcome, the new government will introduce new legislation that will affect the industry. Some of the upcoming laws include the Deposit Return Scheme and the Tobacco and Vapes Bill. The author also highlights the challenges faced by retailers, such as stagnant sales and the difficulty of absorbing the annual increase in the national minimum wage. The article concludes by encouraging retailers to attend industry events to stay updated on innovation and current trends. [Extracted from the article]

The article discusses the government's intervention in the vape market and the potential ban on disposable vapes. The author argues that while the ban may be intended to reduce smoking and vaping, it could drive consumers to the black market or back to smoking tobacco. The author suggests that independent retailers should adapt to the changing market by stocking legal products and educating consumers about reusable and refillable devices. The article emphasizes the need to quickly respond to the evolving demands of customers in the vape market. [Extracted from the article]