What the Evidence Actually Shows

This chapter examines how the rural crowdfunding study turns a broad question about online finance into a measurable comparison. The focus is not a campaign story or a national ranking of rural places; it is the relationship between successful Kickstarter exposure and the later number of employment-generating establishments in the same industry and county. Understanding the unit of analysis, the time lag, and the model is essential to interpreting the study’s approximately 3% result as a meaningful association without mistaking it for proof that crowdfunding created new ventures.

How campaigns become an industry–county comparison

The study joins two kinds of information that describe different sides of entrepreneurial activity. The KIUS database links Kickstarter projects to an industry and a U.S. county. The County Business Patterns database reports the number of employment-generating establishments in industries and counties. Combining them allows the researcher to ask whether an industry–county location that received successful crowdfunding has a different establishment count afterward.

That phrasing is deliberately specific. The basic observation is an industry, in a county, in a year. It is not a rural county in the abstract, and it is not an individual founder. A single county can contain many industries, and an industry can appear in many counties. The study works at that intersection because crowdfunding may matter for one local activity without changing the entire county economy. It also lets the analysis compare a location with its own earlier pattern rather than treating all rural places as interchangeable.

The period runs from 2009 through 2016, beginning with Kickstarter’s first year of operation and ending with the availability of the County Business Patterns data used in the analysis. The baseline rural classification combines four conditions: fewer than 10,000 people living in urban areas, at least 80% of the county’s population living in rural areas, population density below 250 people per square mile, and more than 50 miles from the border of the closest urban core with at least 50,000 people. Applying all four conditions identifies 565 rural counties, about 18% of the 3,142 counties considered.

The definition is more than a label. A place can be sparsely populated but close to a substantial urban center, or have a small town but a population that is mostly urban. The study’s criteria attempt to capture several dimensions of rurality at once: small urban concentration, rural population share, low density, and remoteness. Later tests use another definition and different distance bands, so the baseline should be read as one operational boundary rather than the one natural meaning of “rural.”

The outcome is the number of employment-generating establishments operating in the focal industry and county in the following period. That distinction rules out several tempting but unsupported translations. An establishment is not the same as a campaign. The count does not show that each new establishment was founded by a Kickstarter creator, that every additional position represents a new job, or that self-employed work is included. The underlying data focus on businesses with employees, so self-employed entrepreneurs are outside this outcome.

The explanatory variable is also defined in more than one way.