Panel data analyses of urban economics and housing markets

The thesis looks three pertinent issues in Housing Market and Urban Economics literature with panel data- home sales and house price relationship, efficiency of housing market and commercial property taxation. For the first part, I examine the strong positive correlation that exists between the volume of housing sales and housing prices. I develop a simple model of these flows which suggests they generate a negative price-to-sales relationship. This runs contrary to a different literature on liquidity constraints and loss aversion. Our results from both are strong and robust. Higher sales "Granger cause" higher prices, but higher prices "Granger cause" both lower sales and a growing inventory of units-for-sale. These relationships together provide a more complete picture of the housing market - suggesting the strong positive correlation in the data results from frequent shifts in the negative price-to-sales schedule. For the second part, I tested the hypothesis whether the housing market is efficient and whether "bargains" can be found in the market or not. According to the User cost model, house price appreciation is positively correlated to price. Nevertheless, such correlation between price and appreciation can be caused by productivity differences, behavioral reasons or high transaction costs. Using 4 unique sets of panel data at zip code level, I am able to test the efficiency hypothesis without worrying about productivity reasons and transaction costs. In addition, I tested the efficiency hypothesis by removing influences caused by changes in buyers' preferences over time. The results show that appreciation and house price is positively correlated in San Diego, Boston and Phoenix.