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This paper presents an empirical study of the impact of different factors on real estate sales prices in the Swedish countryside, focusing on the correlation between access to high-speed internet and increased housing prices. Utilizing a hedonic pricing model and multiple linear regression, it examines sales data from 2015 to determine which factors most significantly influence real estate values.
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Policy makers looking to understand housing trends.
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Real estate investors assessing market opportunities.
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Non-profit organizations addressing housing issues.
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Researchers studying social issues related to housing.
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A statistical study on housing is an analysis that collects and evaluates data related to housing conditions, pricing, demographic trends, and occupancy patterns to assess the housing market's status and needs.
Typically, local governments, urban planners, or designated agencies are required to file a statistical study on housing to ensure compliance with housing regulations and to inform policy decisions.
To fill out a statistical study on housing, gather necessary data such as housing inventory, demographic statistics, and occupancy rates, and then complete the specified forms according to the guidelines provided by the regulatory authority.
The purpose of a statistical study on housing is to provide insights into the housing market, guide policy making, identify housing needs, and facilitate urban planning and development.
Information that must be reported typically includes the number of housing units, types of housing, occupancy rates, demographic data, and any relevant socioeconomic indicators.
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