Question

7.24 Many cities in California have passed Inclusionary Zoning policies (also known as below-market hous- Ln ing mandates) as an attempt to make housing more affordable. These policies require develonerss- a some units below the market price on a percentage of the new homes built. For example, in a ment of 10 new homes each with market value $850,000, the developer may have to sell 5 of the at $180,000. Means and Stringham (2012), and exercise 7.13, examine the effects of such polici house prices and number of housing units available using 1990 and 2000 census data on Califori cities. Use the data file means for the following exercises. il a. Use LNPRICE and LNUNITS as dependent variables in difference-in-difference regressions, with on explanatory variables D, the indicator variable for year 2000%; IZLAW, and the interaction of D and IZLAW. Is the estimate of the treatment effect statistically significant, and of the anticipated sign? b. To the regressions in (a) add the control variable LMEDHHINC. Interpret the estimate of the new variable, including its sign and significance. How does this addition affect the estimates of the treatment effect? c. To the regressions in (b) add the variables 100(EDUCATTAIN), 100(PROPPOVERTY), and LPOP. Interpret the estimates of these new variables, including their signs and significance. How do these additions affect the estimates of the treatment effect? d. Consider the differences-in-differences regression for LNPRICE In(PRICE) = B, + B;IZLAW; + B,D, + 8(IZLAW, × D,) + OCITY, + en %3D In this model, CITY, represents some unobservable characteristic of each city that stays consta over time. Write this model for the year 2000 (D, = 1). Write this model for the year 1990 (D, = 0) Subtract the expression for 1990 from the expression for 2000. The dependent variable is %3D DLNPRICE, = [In(PRICE, 2000) – In(PRICE 2000)] ~ %APRICE;/100 which is the decimal equivalent of the percentage change in price for city i. What variables remain on the right-hand side after the subtraction? e. Regress DLNPRICE, against IZLAW, and compare the result to the LNPRICE regression in par s and parameters 725 Denfannne D P .

interpret all of the coefficients and talk about its statistical significance as well

Answer 1

Answer :

interpretation of Coefficients . Here Price is dependent variable

	Estimate	Interpretation
(Intercept)	14.0226372	For every value of price it will be resulted by adding 14.02263
d	0.0767438	If one unit of d increases, the price will increases by 0.0767
izlaw	0.0065325	If one unit of izlaw increases, the price will increases by 0.0065325
Izlaw_d	-0.0270142	If one unit of Izlaw_d increases, the price will decreases by 0.02701
Imedhhinc	-0.7636798	If one unit of Imedhhinc increases, the price will decreases by 0.76367
I(100*education)	0.0134294	If one unit of I(100*education) increases, the price will increases by 0.013429
I(100*proppoverty)	-0.0262031	If one unit of I(100*proppoverty) increases, the price will decreases by 0.026203
Ipop	0.998472	If one unit of Ipop increases, the price will increses by 0.998472

Significance :

we know that null hypothesis is H0: Bi = 0 verses H1:Bi !=0 i.e significant (Bi are coefficients)

By considering level of significance , $\alpha$ = 0.05

If P(>|t|) > $\alpha$ = 0.05 then we reject H0 and the coefficient is significant otherwise insignificant.

The coefficient that are significant will be added in the model.

	Estimate	Pr(>|t|)	Decision	Significance
(Intercept)	14.0226372	<2e-16	less than 0.05,Hence reject H0	Significant
d	0.0767438	3.00E-06	less than 0.05,Hence reject H0	Significant
izlaw	0.0065325	0.8	greater than 0.05,Hence accept H0	Insignificant
Izlaw_d	-0.0270142	0.452	greater than 0.05,Hence accept H0	Insignificant
Imedhhinc	-0.7636798	<2e-16	less than 0.05,Hence reject H0	Significant
I(100*education)	0.0134294	<2e-16	less than 0.05,Hence reject H0	Significant
I(100*proppoverty)	-0.0262031	<2e-16	less than 0.05,Hence reject H0	Significant
Ipop	0.998472	<2e-16	less than 0.05,Hence reject H0	Significant