Q

Proposal 1: The indirect effects of Airbnb on job creation

According to the US Travel Association, tourism generated over 2.1 trillion dollars in US output in 2014, and over 900 billion was spent directly by travelers. Furthermore, tourism supports over 15 million jobs in the US, 8 million jobs directly related to tourism, and another 7 million indirectly related jobs, it is estimated that 1 in 9 jobs in the US is related to tourism. Therefore it is safe to say that tourism benefits much of the domestic and local economies in the US.

In the past, when a city experiences an increase in tourist, the laws of supply and demand for hotels prevail. The more tourists, leads to higher prices for hotels. With the advent of the sharing economy, such as Airbnb, instead of shifts in demand determining price, the supply curve shifts, to the benefit of the consumer. Travelers who are travelling on a budget might not have been able to afford to travel to such places without the help of Airbnb. Hence, Airbnb should (in theory) increase the number of tourists that visit a city, thereby helping the local economy. Furthermore, the average Airbnb traveler stays on average of 4.2 days, whereas a hotel traveler stays for 2.5 days. We feel that this difference will generate more tourism revenues within the locale.

There have been numerous reports vilifying Airbnb as having a negative effect on hotel jobs and city tax revenues. In one research article, statistical data showed that

Airbnb had a significant effect on hotel prices. In the paper, “Estimating the impact of Airbnb on the hotel industry” (Zervas, Byers, 2015), data shows the impact of supply of rooms offered on Airbnb having an effect on hotel prices. It is this due to this article that we continue research on the total effects of Airbnb. It is our hypothesis that although Airbnb has a negative effect on the hotel industry, that this effect is only limited to the hotel industry and that it creates jobs in other areas or tourism.

It is our proposal that we study the effects of Airbnb on other parts of the tourism industry. We would be building upon the Zervas-Byers paper, and draw data from the Texas comptroller’s office, since Texas is the only state that has detailed information on hotel revenues. If data shows that the average Airbnb traveler stays 1.4 days longer than the average hotel traveler, then that should translate into higher profits for other areas of tourism, such as restaurants, entertainment, and recreational activities. To measure this profit, we use an instrumental variable, that variable will be the number of jobs created in the specific city. Jobs data will be drawn from the BLS and census bureau. Some error factors that may need to be considered would be the unemployment rate in those cities, the supply of hotels, and population growth, just to name a few.

We hope that our data will show that the number of jobs increased correlates to the number of Airbnb listings. Furthermore, the number of jobs increased due to higher profits for the tourism industry as a whole. There has been many articles vilifying Airbnb, from New York to San Francisco, and we hope to shed more light on the entire situation, that although the sharing economy negatively impacts one sector, it also positively affects another much more positively (where the benefits greatly outweighs the cost) and not just from the hotel revenue perspective.

Proposal 2: Effect of Property Tax on Real Estate Pricing.

Real Estate sector is a big part of financial market. It is an important indicator of the state of economy and a big capital generating tool both for the government entities and individuals. Taxation plays a central role in financing local governments and their needs. In “The connection between house prices house price appreciation and property tax revenues” (Byron Lutz, 2008) the Federal Reserve researcher highlights that property tax accounts for almost three quarters of local government tax revenues and finance approximately 95% of the budget of independent school districts. Taking to consideration that local authorities in pursuit of balancing budgets change property taxes rather frequently, we would like to investigate the effect of property taxes on housing prices.

In our research we would like to adopt Thomas Holmes’s border line approach to test the effect of property tax policy on housing prices. In the research we would compare border line of Hi-Low property tax states with at least 1% in difference between two neighboring states: Texas (1.81%) vs Louisiana (0.18%), New Jersey (1.89%) vs Delaware (0.43%), Nebraska (1.76%) vs Wyoming (0.58%) Colorado (0.6%), Illinois (1.73%) vs Kentucky (0.72%).

By conducting this research we are aiming to find economically significant difference in real estate prices in Hi-Low property tax states. There have been written many articles and researches on importance of property taxation. We would like to build on and at the same time spin off previous researches and provide a summary that could not only be interesting for policy makers, but also to real estate investors.