Scenario 3

question 155

Multiple Choice

Scenario 3.2 Use the following to answer the questions.Clayton Homes, a mobile home manufacturer since 1934, introduced its new i-House in 2007. The i-House is one of the first of its kind, designed as an updated, modern version of the modular home, offered as a base home plus add-ons known as "pods." The base home is a one-bedroom, one-bath 734-square foot version at a price of around $80,000. There is also a 1,000 square-foot version for around $100,000. All versions may add on the additional one-room pods as desired which are shipped to your location and constructed on-site. The homes offer galvanized metal roofing, corrugated steel siding, VOC-free paints, and a "butterfly" roof that collects rainwater. The i-House uses 30% less energy than a similar square-foot home and offers "green" characteristics of solar panels, tankless water heaters, and low-flow faucets. In addition, it comes with bamboo flooring, a renewable resource. The modular, pre-fabricated design offers endless options for creating the customer's home and its engineered building system cuts down on construction waste. Due to the "green effects" of the i-House, the state governments have given it a tax abatement for any sales taxes.
-Refer to Scenario 3.2. In what type of competitive structure is Clayton Homes most likely operating?

• A)Monopoly
• B)Oligopoly
• C)Monopolistic competition
• D)Pure competition
• E)Monopsony

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Definitions:

Industrial Lathe Sales

The commercial activity surrounding the buying and selling of industrial lathes, which are machines used to shape metal, wood, or other materials.

First-Order Autoregressive Model

A time series model where the current value is based on a linear combination of the previous value and a stochastic error term.

Nonautocorrelated Random Error

Errors in a dataset that occur randomly and are not correlated with each other, indicating no predictable pattern in the fluctuations.

Autoregressive Model

An Autoregressive Model is a statistical model for analyzing and forecasting time series data, where future values are assumed to be a linear function of past values.