In: Economics
Spatial data are likely to exhibit specific types of dependence between the observations. Suppose that you want explain house prices from the listing of houses on Airbnb. You collect data on house prices and Airbnb listings of about 1,000 houses in 10 different cities. In the regression you want to run, give an example of the following spatial processes that might be relevant for your study: a) Common exposure b) Interdependence c) Measurement errors
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Spatial processes area unit completely different from temporal processes therein they are doing not act in an exceedingly single purpose however bit by bit unfold influences over area, ranging from a boundary between 2 regions. A spacial method is pictured as a field with increasing relevance regions, referred to as growth regions. common exposure to shocks and on banking sector general risk. on paper, this impact is ambiguous. by trial and error, we discover that banks'
Common exposure to shocks has considerably diminished till 2000 and apace multiplied later on. we offer proof that general risk is especially driven by banks' individual risk-taking which, contrary to widespread belief, higher common exposures to risk don't essentially induce higher general risk.
Interdependence is mutual dependence between things. If you study biology, you will discover that there's a good deal of mutuality between plants and animals. Inter- means that "between," thus mutuality is dependence between things. we regularly use mutuality to explain advanced systems.
Measurement Error (also referred to as data-based Error) is that the distinction between a measured amount and its true price. It includes random error (naturally occurring errors that area unit to be expected with any experiment) and systematic error (caused by a mis-calibrated instrument that affects all measurements).