Economics Asked by s7eqx9f74nc4 on July 4, 2021
I have been playing with $V=Pe^{rT}$ and have been thinking about how to apply it to situations involving different assets growing at different rates.
Suppose I had data for the historic sale prices of a row of houses in a street, with two data points per house. My assumption here is going to be that each house’s price grows according to $V=Pe^{rT}$, with $r$ constant.
House no. | Year A | Sold for | Year B | Sold for |
---|---|---|---|---|
1 | 2000 | $100,000 | 2015 | $500,000 |
2 | 2005 | $60,000 | 2019 | $111,000 |
3 | 1999 | $30,000 | 2018 | $80,000 |
4 | 2002 | $125,000 | 2005 | $126,000 |
Using $V=Pe^{rT}$, I could calculate each house’s instantaneous rate of interest $r=frac{ln{V}-ln{P}}{T}$, and its APR $hat{r}=e^{r}-1$, where $T=B-A$ is the number of years elapsed.
House no. | Year A | Sold for | Year B | Sold for | $r$ | $hat{r}$ |
---|---|---|---|---|---|---|
1 | 2000 | $100,000 | 2015 | $500,000 | 10.73% | 11.33% |
2 | 2005 | $60,000 | 2019 | $111,000 | 4.39% | 4.49% |
3 | 1999 | $30,000 | 2018 | $80,000 | 5.16% | 5.30% |
4 | 2002 | $125,000 | 2005 | $126,000 | 0.27% | 0.27% |
My question is, how should I meaningfully combine the growth rates of the different houses? Say I want a figure for the street’s overall growth rate in order to evaluate whether a particular house has been growing more quickly or more slowly than this rate. I have various ideas:
House no. | $r$ | 2000 | 2021 |
---|---|---|---|
1 | 10.73% | $100,000 | $951,827 |
2 | 4.39% | $48,165 | $121,197 |
3 | 5.16% | $31,589 | $93,400 |
4 | 0.27% | $124,338 | $131,470 |
Total | – | $304,092 | $1,297,894 |
Using the totals above as my new $P$ and $V$, I get that $r=6.91%$ and $hat{r}=7.15%$.
Is this a legitimate method? If so, what is it called? I am concerned that it might not be legitimate, because changing the two base years gives different results:
House no. | $r$ | 2005 | 2008 |
---|---|---|---|
1 | 10.73% | $170,998 | $235,930 |
2 | 4.39% | $60,000 | $68,455 |
3 | 5.16% | $40,892 | $47,741 |
4 | 0.27% | $126,000 | $127,008 |
Total | – | $397,890 | $479,134 |
Here, $r=6.19%$ and $hat{r}=6.39%$, which seems strange, since each individual house’s growth rate was constant. Does this mean that the "What if I’d bought the whole street in year $X$ and waited until year $Y$" method is wrong, or does it still have an interpretation?
What is the best way of defining the "overall" rate of growth for the whole street of houses?
Thanks
I don't think there is a unique best way to do this.
A flexible approach might be to compute the average growth rate by regression. Let $P_i, V_i$ and $T_i$ be the variables for house $i$. Then we have the formula: $$ ln(V_i) - ln(P_i) = r_i T_i $$ Putting this into a regression framework gives: $$ ln(V_i) - ln(P_i) = r T_i + varepsilon_i $$ where now $r$ is the "average" growth rate and, by definition $varepsilon_i = (r_i - r) T_i$.
If we assume that $mathbb{E}(varepsilon_i T_i) = 0$ (e.g. this holds if deviations of $r_i$ from $r$ are zero conditional on $T_i$). Then we can multiply this equation by $T_i$ and take expectations to obtain: $$ mathbb{E}[(ln(V_i)- ln(P_i)) T_i] = r mathbb{E}[T_i^2] $$ So: $$ r = frac{mathbb{E}[(ln(V_i) - ln(P_i))T_i]}{mathbb{E}[T_i^2]} = frac{mathbb{E}(r_i T_i^2)}{mathbb{E}(T_i^2)}. $$
An estimate can be constructed by replacing the expectation by the sample mean. $$ hat r = frac{sum_i r_i T_i^2}{sum_i T_i^2} $$ For your data set, this gives an estimate of 0.065
An alternative might be to also include an intercept. $$ ln(V_i) - ln(P_i) = alpha + r T_i + varepsilon_i. $$ Doing this gives an estimate of 0.0742
Answered by tdm on July 4, 2021
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