Econ 4093 -Assignment 1
Total 100 points
1. In lecture 1, we show evidences that urbanization is positively associated with the level of economic growth and income. In this exercise, we have data on urbanization rate, GDP per capita and average wage in Chinese provinces from 2005 to 2020. Please verify the relationship between urbanization and economic growth/wage by running the following regressions (Total 20 points, 5 points for each question)
a) Run a linear-linear model between the GDP per capita/ wage and urbanization rate. Interpret your results.
b) Run a log-linear model between the GDP per capita/wage and urbanization rate. Interpret your results
c) Let’s turn to the fixed effect model by controlling the province fixed effect, and re-run the above regressions (log-linear model). Please interpret the results
d) Let’s control both the province and year fixed effect. Re-run those log-linear regressions and interpret the results.
2. In lecture 2 and 3, we show the AMM model and hedonic pricing for land and housing price. In this exercise, please run log-log regressions between the commercial land price in Shanghai and a number of geographic variables. The data includes about 900 commercial land transactions in Shanghai from 2004-2016. (80 points in total).
a) Run log-log regression on the land parcel price and distance of land parcel to city center. Please interpret the results. Do you think Shanghai is a monocentric city? (5 point)
b) Now add on more variable in the regression: local_gov (distance of land parcel to district government). Please interpret the results. Do you think Shanghai is a monocentric city or polycentric city? (5 point)
c) Add two more variables on land characteristics: LandArea is the size of each parcel, FAR is the density of each parcel. What is the relationship of land price and land characteristics?.(you can to convert LandArea and FAR to log form) (5 points)
d) Add three local amenity variables in the regression: Uni (distance to the closest university); HS (distance to the closest high school); Green (distance to the closest parks). Interpret the results on these three variables. (5 point)
e) Add three variables on transportation: HSR (distance to closest high-speed rail station); Metro (distance to the closest metro station); HW(distance to the closest highway intersection). Please interpret the results on these three variables. (5 point)
f) What could be the concerns on the results in part e)？(5 point)
g) Now, add districts and year fixed effect and rerun the regression in part e). Please interpret the results. Compare your results between (a) and (g), how do the coefficients on the distance to Distance to CBD change? Why? (10 point)
h) Let’s move to density gradient. Using the log-linear function to examine the relationship between the land density (log FAR) and distance to CBD. What is the result by using log-log function? (10 point)
i) Rerun the two regressions in h) by adding district fixed effect and year fixed effect. Please interpret the results. (10 point)
j) Let’s move to price gradient. You need to convert the Total_price to Unit_price: gen Unit_price= Total_price*10000/LandArea
Using the log-linear function to examine the relationship between the land price (Unit_price) and distance to CBD. What is the result by using log-log function? (10 point)
k) Rerun the two regressions in j) by adding district fixed effect and year fixed effect. Please interpret the results. (10 point)