class: center, middle, inverse, title-slide # Econ 330: Urban Economics ## Lecture 12 ### John Morehouse ### May 12th, 2021 --- class: inverse, center, middle # Lecture XIV: Housing Policy --- name: schedule # Schedule ## Today -- 1) .hi.purple[Introduction] 2) .hi.purple[Two Models] 3) .hi.purple[Cross-City Variation] 4) .hi.purple[Two Policies] -- -- ## Upcoming - .hi.slate[HW3] - .hi.slate[Reading] (Chapter 9) -- --- # Housing Markets Before we dive in, let's distinguish the following: - .hi[Rental] Market: Supply and Demand for .pink[rentals] - .hi.purple[Housing Market]: Supply and Demand for .purple[houses] --- count: false # Housing Markets Before we dive in, let's distinguish the following: - .hi[Rental] Market: Supply and Demand for .pink[rentals] - .hi.purple[Housing Market]: Supply and Demand for .purple[houses] Why is it important to distinguish these? Aren't they both markets for living spaces? .hi[Discuss] --- count: false # Housing Markets Before we dive in, let's distinguish the following: - .hi[Rental] Market: Supply and Demand for .pink[rentals] - .hi.purple[Housing Market]: Supply and Demand for .purple[houses] Why is it important to distinguish these? Aren't they both markets for living spaces? .hi[Discuss] - A house is an asset. A month of rent is not - Homeowners are much less mobile than renters --- count: false # Homeownership Why is buying a home different than buying a pair of jeans? (other than the difference in price) --- count: false # Homeownership Why is buying a home different than buying a pair of jeans? (other than the difference in price) A house is a store of value. This value is subject to uncertainty. (This is what I mean by asset) --- count: false # Homeownership Why is buying a home different than buying a pair of jeans? (other than the difference in price) A house is a store of value. This value is subject to uncertainty. (This is what I mean by asset) - Fundamentally, purchasing a home is a dynamic (forward-looking) decision - Jeans (a pure consumption good) is not really a store of value --- count: false # Homeownership Why is buying a home different than buying a pair of jeans? (other than the difference in price) A house is a store of value. This value is subject to uncertainty. (This is what I mean by asset) - Fundamentally, purchasing a home is a dynamic (forward-looking) decision - Jeans (a pure consumption good) is not really a store of value We will focus on renters. But first let's take a look at some data --- # Rentals vs Homeowners <img src="images/ownership_plot.png" width="70%" height="65%" style="display: block; margin: auto;" /> --- class: inverse, middle # Checklist .col-left[ 1) .hi[Introduction] ✅ 2) .hi.purple[Two Models] ] .col-right[ 3) .hi.purple[Two Policies] ] --- # Rental Market Model Just like labor markets, each city has its own market for rental units --- count: false # Rental Market Model Just like labor markets, each city has its own market for rental units - Consists of suppliers (absentee landlords) --- count: false # Rental Market Model Just like labor markets, each city has its own market for rental units - Consists of suppliers (absentee landlords) - Individuals making optimal housing demand decisions --- count: false # Rental Market Model Just like labor markets, each city has its own market for rental units - Consists of suppliers (absentee landlords) - Individuals making optimal housing demand decisions __Important__: Structure of the market has big implications for policy --- # Competitive Model Very similar to the competitive labor market model --- count: false # Competitive Model Very similar to the competitive labor market model 1) No individual landlord can influence the price of rents --- count: false # Competitive Model Very similar to the competitive labor market model 1) No individual landlord can influence the price of rents 2) Landlords decide how much housing to provide --- count: false # Competitive Model Very similar to the competitive labor market model 1) No individual landlord can influence the price of rents 2) Landlords decide how much housing to provide 3) The amount of housing they provide will again come from profit maximization __Important__: Labor market model: firm was deciding how much labor to hire. Now we will model the landlord as picking a quantity of housing to provide --- # Competitive Model Math Profit function given by: `\begin{align*} \pi(Q) = P*Q - TC(Q) \end{align*}` --- count: false # Competitive Model Math Profit function given by: `\begin{align*} \pi(Q) = P*Q - TC(Q) \end{align*}` - __Note__: Now cost is a function of quantity --- count: false # Competitive Model Math Profit function given by: `\begin{align*} \pi(Q) = P*Q - TC(Q) \end{align*}` - __Note__: Now cost is a function of quantity - Implicitly we are assuming that at any quantity, the firm will use the optimal level of labor and capital --- count: false # Competitive Model Math Profit function given by: `\begin{align*} \pi(Q) = P*Q - TC(Q) \end{align*}` - __Note__: Now cost is a function of quantity - Implicitly we are assuming that at any quantity, the firm will use the optimal level of labor and capital Marginal profit equals zero , `\(\frac{\Delta \pi(Q)}{\Delta Q}= 0\)`: --- count: false # Competitive Model Math Profit function given by: `\begin{align*} \pi(Q) = P*Q - TC(Q) \end{align*}` - __Note__: Now cost is a function of quantity - Implicitly we are assuming that at any quantity, the firm will use the optimal level of labor and capital Marginal profit equals zero, `\(\frac{\Delta \pi(Q)}{\Delta Q}= 0\)`: `\begin{align*} \frac{P*\Delta Q}{\Delta Q} - \frac{\Delta TC(Q)}{\Delta Q} = 0 \end{align*}` --- count: false # Competitive Model Math Profit function given by: `\begin{align*} \pi(Q) = P*Q - TC(Q) \end{align*}` - __Note__: Now cost is a function of quantity - Implicitly we are assuming that at any quantity, the firm will use the optimal level of labor and capital Marginal profit equals zero, `\(\frac{\Delta \pi(Q)}{\Delta Q}= 0\)`: `\begin{align*} \frac{P*\Delta Q}{\Delta Q} - \frac{\Delta TC(Q)}{\Delta Q} &= 0\\ P &= \frac{\Delta TC(Q)}{\Delta Q} \end{align*}` --- count: false # Competitive Model Math Profit function given by: `\begin{align*} \pi(Q) = P*Q - TC(Q) \end{align*}` - __Note__: Now cost is a function of quantity - Implicitly we are assuming that at any quantity, the firm will use the optimal level of labor and capital Marginal profit equals zero, `\(\frac{\Delta \pi(Q)}{\Delta Q}= 0\)`: `\begin{align*} \frac{P*\Delta Q}{\Delta Q} - \frac{\Delta TC(Q)}{\Delta Q} &= 0\\ P &= \frac{\Delta TC(Q)}{\Delta Q}\\ P &= MC(Q) \end{align*}` --- count: false # Competitive Model Math Profit function given by: `\begin{align*} \pi(Q) = P*Q - TC(Q) \end{align*}` - __Note__: Now cost is a function of quantity - Implicitly we are assuming that at any quantity, the firm will use the optimal level of labor and capital Marginal profit equals zero, `\(\frac{\Delta \pi(Q)}{\Delta Q}= 0\)`: `\begin{align*} \frac{P*\Delta Q}{\Delta Q} - \frac{\Delta TC(Q)}{\Delta Q} &= 0\\ P &= \frac{\Delta TC(Q)}{\Delta Q}\\ P &= MC(Q) \end{align*}` - .pink[Increasing Marginal costs] `\(\implies\)` .pink[upward sloping supply curves!] --- # The Monopoly Model Now let's consider the monopoly situation: --- count: false # The Monopoly Model Now let's consider the monopoly situation: 1) One seller of the good (rental units) --- count: false # The Monopoly Model Now let's consider the monopoly situation: 1) One seller of the good (rental units) 2) Ability to set prices --- count: false # The Monopoly Model Now let's consider the monopoly situation: 1) One seller of the good (rental units) 2) Ability to set prices 3) Still profit maximizing --- # Monopoly: Math - Again, the monopolist will still be a profit-maximizer --- count: false # Monopoly: Math Again, the monopolist will still be a profit-maximizer - TR is now given by: `\(TR = P(Q)*Q\)` --- count: false # Monopoly: Math Again, the monopolist will still be a profit-maximizer - TR is now given by: `\(TR = P(Q)*Q\)` - Quantity that the monopolist produces impacts the price --- count: false # Monopoly: Math Again, the monopolist will still be a profit-maximizer - TR is now given by: `\(TR = P(Q)*Q\)` - Quantity that the monopolist produces impacts the price - `\(P(Q)\)` _is_ the inverse demand function --- count: false # Monopoly: Math Again, the monopolist will still be a profit-maximizer - TR is now given by: `\(TR = P(Q)*Q\)` - Quantity that the monopolist produces impacts the price - `\(P(Q)\)` _is_ the inverse demand function (what you are used to seeing for demand) --- count: false # Monopoly: Math Again, the monopolist will still be a profit-maximizer - TR is now given by: `\(TR = P(Q)*Q\)` - Quantity that the monopolist produces impacts the price - `\(P(Q)\)` _is_ the inverse demand function (what you are used to seeing for demand) __Profit is given by__ `\begin{align*} \pi(Q) = P(Q)*Q - TC(Q) \end{align*}` --- # Monopoly: Profit Maxing Profit Maximization gives us the familiar `\(\frac{\Delta \pi(Q)}{\Delta Q} = 0\)` --- count: false # Monopoly: Profit Maxing Profit Maximization gives us the familiar `\(\frac{\Delta \pi(Q)}{\Delta Q} = 0\)` `\begin{align*} \frac{\Delta P(Q)*Q}{\Delta Q} - \frac{\Delta TC(Q)}{\Delta Q} = 0 \end{align*}` --- count: false # Monopoly: Profit Maxing Profit Maximization gives us the familiar `\(\frac{\Delta \pi(Q)}{\Delta Q} = 0\)` `\begin{align*} \frac{\Delta P(Q)*Q}{\Delta Q} - \frac{\Delta TC(Q)}{\Delta Q} &= 0 \\ MR(Q) &= MC(Q) \end{align*}` --- count: false # Monopoly: Profit Maxing Profit Maximization gives us the familiar `\(\frac{\Delta \pi(Q)}{\Delta Q} = 0\)` `\begin{align*} \frac{\Delta P(Q)*Q}{\Delta Q} - \frac{\Delta TC(Q)}{\Delta Q} &= 0 \\ MR(Q) &= MC(Q) \end{align*}` __Note__: Now, `\(\frac{\Delta P(Q)*Q}{\Delta Q} \neq P\)`. --- # Monopoly Graph <img src="lecture_12_files/figure-html/m1-1.svg" style="display: block; margin: auto;" /> --- count: false # Monopoly Graph <img src="lecture_12_files/figure-html/m2-1.svg" style="display: block; margin: auto;" /> --- count: false # Monopoly Graph <img src="lecture_12_files/figure-html/m3-1.svg" style="display: block; margin: auto;" /> --- class: inverse, middle # Checklist .col-left[ 1) .hi[Introduction] ✅ 2) .hi[Two Models] ✅ - Competitive Model - Monopoly Model ] .col-right[ 3) .hi.purple[Cross-City Variation] 4) .hi.purple[Two Policies] ] --- # Rents Across Cities __Key Question:__ - What causes rental curves to vary across cities? (both in intercept and slope) In general, supply curves across cities are impacted by: local construction costs, land available for development, and land-use regulations -- - .hi[Local construction costs]: shifts .pink[intercept] (labor is more expensive for all firms in one area vs another) - .hi.purple[Land available for development] and .hi.purple[land use regulations]: slope (changes __marginal cost__) of developing land. .qa[Why?] -- .qa[A]: Less land available to develop `\(\rightarrow\)` .hi[oppurtunity cost of developing increases] for each next plot of land. Prices get bid up faster. Similar intuition with land-use regulations --- # Urban Housing Supply Curves <img src="lecture_12_files/figure-html/supply1-1.svg" style="display: block; margin: auto;" /> --- # Urban Housing Supply Curves <img src="lecture_12_files/figure-html/supply2-1.svg" style="display: block; margin: auto;" /> - .hi[pink]: lower construction cost (lower intercept) --- # Urban Housing Supply Curves <img src="lecture_12_files/figure-html/supply3-1.svg" style="display: block; margin: auto;" /> - __black__: higher land use regs or less available land for development --- class: inverse, middle # Checklist .col-left[ 1) .hi[Introduction] ✅ 2) .hi[Two Models] ✅ - Competitive Model - Monopoly Model ] .col-right[ 3) .hi[Cross-City Variation] ✅ 4) .hi.purple[Two Policies] ] --- # Two Policies - We will focus on two policies: --- count: false # Two Policies - We will focus on two policies: 1) Rent Control --- count: false # Two Policies - We will focus on two policies: 1) Rent Control 2) Land-Use Restrictions (you are familiar with these already) - We will also look at how these could interact --- # Rent Control __Defn__ Rent Control: A _price ceiling_ set on rental units - Price Ceiling: Max allowed price on the market --- count: false # Rent Control __Defn__ Rent Control: A _price ceiling_ set on rental units - Price Ceiling: Max allowed price on the market Brief History (US): - Started around WW1. Expanded during WWII --- count: false # Rent Control __Defn__ Rent Control: A _price ceiling_ set on rental units - Price Ceiling: Max allowed price on the market Brief History (US): - Started around WW1. Expanded during WWII - 1970: Nixon puts 90-day freeze on prices to combat inflation --- count: false # Rent Control __Defn__ Rent Control: A _price ceiling_ set on rental units - Price Ceiling: Max allowed price on the market Brief History (US): - Started around WW1. Expanded during WWII - 1970: Nixon puts 90-day freeze on prices to combat inflation - _Mostly_ a .hi[place based policy]. --- count: false # Rent Control __Defn__ Rent Control: A _price ceiling_ set on rental units - Price Ceiling: Max allowed price on the market Brief History (US): - Started around WW1. Expanded during WWII - 1970: Nixon puts 90-day freeze on prices to combat inflation - _Mostly_ a .hi[place based policy]. - SF, NY, LA, Oakland, DC, Berkeley, West Hollywood - Oregon: first state to have .pink[state-wide rent control] --- # Rent Control <img src="images/oregon_control.png" width="80%" height="80%" style="display: block; margin: auto;" /> --- # Rent Control in Oregon - In 2019: Oregon passes .hi[state-wide] rent control --- count: false # Rent Control in Oregon - In 2019: Oregon passes .hi[state-wide] rent control - Limits annual rent increases to inflation + 7% (inflation is usually 2-3%) --- count: false # Rent Control in Oregon - In 2019: Oregon passes .hi[state-wide] rent control - Limits annual rent increases to inflation + 7% (inflation is usually 2-3%) - If tenants leave on their .pink[own accord], landlords can .purple[increase rent] without limit --- count: false # Rent Control in Oregon - In 2019: Oregon passes .hi[state-wide] rent control - Limits annual rent increases to inflation + 7% (inflation is usually 2-3%) - If tenants leave on their .pink[own accord], landlords can .purple[increase rent] without limit .hi[Question]: Are the ramifications from state-wide rent-control different than local rent control? Why? --- # Land Use Restrictions Land use restrictions limit what one can do with developable land. Examples: --- count: false # Land Use Restrictions Land use restrictions limit what one can do with developable land. Examples: 1. Density Restrictions --- count: false # Land Use Restrictions Land use restrictions limit what one can do with developable land. Examples: 1. Density Restrictions 2. Min Lot Sizes --- count: false # Land Use Restrictions Land use restrictions limit what one can do with developable land. Examples: 1. Density Restrictions 2. Min Lot Sizes 3. Park Requirements --- count: false # Land Use Restrictions Land use restrictions limit what one can do with developable land. Examples: 1. Density Restrictions 2. Min Lot Sizes 3. Park Requirements 4. Sidewalk and street size requirements --- count: false # Land Use Restrictions Land use restrictions limit what one can do with developable land. Examples: 1. Density Restrictions 2. Min Lot Sizes 3. Park Requirements 4. Sidewalk and street size requirements 5. Height Restrictions Not all of these are bad things. But they do make developing land more expensive. --- # Wharton Index <img src="images/wharton_new.png" width="80%" height="80%" style="display: block; margin: auto;" /> Higher values of the Wharton index `\(\implies\)` tighter land use restrictions --- # Example --- # A Model Do Land-Use regs and rent control interact? Absolutely! Let's model it -- `\begin{align*} P(Q_d) &= 20 - 2*Q_d\\ P(Q_s) &= 8 + Q_s\\ \end{align*}` Compute the equilibrium. Graph it, if that is helpful -- - Now suppose the government ratchets up land-use regs. New supply is given by: `\begin{align*} P(Q_s^{new}) = 8 + 2*Q_s^{new} \end{align*}` -- --- # Example Old eq: `\(Q^* = 4\)`, `\(P^* = 12\)` New eq: `\(Q^* = 3\)`, `\(P^* = 15\)` Government comes in and says the rents are too high. Rent control set at `\(12\)` per unit. Now you have: `\begin{align*} 12 = 8+2*Q_s \implies Q_s = 2 \end{align*}` --- count: false # Example Old eq: `\(Q^* = 4\)`, `\(P^* = 12\)` New eq: `\(Q^* = 3\)`, `\(P^* = 15\)` Government comes in and says the rents are too high. Rent control set at `\(12\)` per unit. Now you have: `\begin{align*} 12 = 8+2*Q_s &\implies Q_s = 2\\ 12 = 20 - 2*Q_d &\implies Q_d = 4 \end{align*}` --- count: false # Example Old eq: `\(Q^* = 4\)`, `\(P^* = 12\)` New eq: `\(Q^* = 3\)`, `\(P^* = 15\)` Government comes in and says the rents are too high. Rent control set at `\(12\)` per unit. Now you have: `\begin{align*} 12 = 8+2*Q_s &\implies Q_s = 2\\ 12 = 20 - 2*Q_d &\implies Q_d = 4 \end{align*}` So we have a .pink[shortage] of two units at the .hi.purple[old] equilibrium price. 😧 --- # A Note We wont have time (but it might be good practice) for you to think through what would happen if the market was a .hi[monopoly] --- count: false # A Note We won't have time (but it might be good practice) for you to think through what would happen if the market was a .hi[monopoly] - Similar to the .hi.purple[monopsonist], rent control can actually .pink[lower prices] in a completely .purple[monopolized] housing market --- count: false # A Note We won't have time (but it might be good practice) for you to think through what would happen if the market was a .hi[monopoly] - Similar to the .hi.purple[monopsonist], rent control can actually .pink[lower prices] in a completely .purple[monopolized] housing market - Let's take a (quick) look at some recent empirical evidence --- # Empirics __Empirical Evidence__: [Diamond et. al (2019)](https://web.stanford.edu/~diamondr/DMQ.pdf) - 1979: Rent control in SF put in place for all standing buildings with 5 apartments or more --- count: false # Empirics __Empirical Evidence__: [Diamond et. al (2019)](https://web.stanford.edu/~diamondr/DMQ.pdf) - 1979: Rent control in SF put in place for all standing buildings with 5 apartments or more - New buildings exempt (to promote developers to continue building) --- count: false # Empirics __Empirical Evidence__: [Diamond et. al (2019)](https://web.stanford.edu/~diamondr/DMQ.pdf) - 1979: Rent control in SF put in place for all standing buildings with 5 apartments or more - New buildings exempt (to promote developers to continue building) - Small multi-family apartment buildings ("mom & pop") exempted --- count: false # Empirics __Empirical Evidence__: [Diamond et. al (2019)](https://web.stanford.edu/~diamondr/DMQ.pdf) - 1979: Rent control in SF put in place for all standing buildings with 5 apartments or more - New buildings exempt (to promote developers to continue building) - Small multi-family apartment buildings ("mom & pop") exempted - 1994: Exemption for small multi-family buildings removed. All apartments .hi[built before 1980] subject to rent control --- # Empirics: Findings In this study: - .hi.slate[Treatment]: Those living in small apartment complexes (5 or less) built in 1979 or before --- count: false # Empirics: Findings In this study: - .hi.slate[Treatment]: Those living in small apartment complexes (5 or less) built in 1979 or before - .hi.slate[Control]: Those living in small apartments complexes (5 or less) built after 1979 (not subject to rent control) --- count: false # Empirics: Findings In this study: - .hi.slate[Treatment]: Those living in small apartment complexes (5 or less) built in 1979 or before - .hi.slate[Control]: Those living in small apartments complexes (5 or less) built after 1979 (not subject to rent control) A fair comparison? Maybe concerned that those living in apartments built before or after 1979 are systematically different. --- count: false # Empirics: Findings In this study: - .hi.slate[Treatment]: Those living in small apartment complexes (5 or less) built in 1979 or before - .hi.slate[Control]: Those living in small apartments complexes (5 or less) built after 1979 (not subject to rent control) A fair comparison? Maybe concerned that those living in apartments built before or after 1979 are systematically different - .hi.slate[Main Findings]: 1) .purple[Renter mobility] was reduced by about 20% --- count: false # Empirics: Findings In this study: - .hi.slate[Treatment]: Those living in small apartment complexes (5 or less) built in 1979 or before - .hi.slate[Control]: Those living in small apartments complexes (5 or less) built after 1979 (not subject to rent control) A fair comparison? Maybe concerned that those living in apartments built before or after 1979 are systematically different - .hi.slate[Main Findings]: 1) .purple[Renter mobility] was reduced by about 20% 2) .pink[Housing Supply] was reduced by about 15% --- # So What? __Moral of the story__: Yes, in SF: .pull-left[ <img src="images/too_damn_high.jpg" width="100%" height="100%" style="display: block; margin: auto;" /> ] --- count: false # So What? __Moral of the story__: Yes, in SF: .pull-left[ <img src="images/too_damn_high.jpg" width="100%" height="100%" style="display: block; margin: auto;" /> ] .pull-right[ - Are rent controls the best fix? ] --- count: false # So What? __Moral of the story__: Yes, in SF: .pull-left[ <img src="images/too_damn_high.jpg" width="100%" height="100%" style="display: block; margin: auto;" /> ] .pull-right[ - Are rent controls the best fix? - In SF, probably not ] --- count: false # So What? __Moral of the story__: Yes, in SF: .pull-left[ <img src="images/too_damn_high.jpg" width="100%" height="100%" style="display: block; margin: auto;" /> ] .pull-right[ - Are rent controls the best fix? - In SF, probably not - Evidence that land-use regs are voted for by older, whiter homewoners: [here](https://www.housingpolitics.com/research/who_participates_in_local_government.pdf) ] --- class: inverse, middle # Checklist .col-left[ 1) .hi[Introduction] ✅ 2) .hi[Two Models] ✅ - Competitive Model - Monopoly Model ] .col-right[ 3) .hi[Cross-City Variation] ✅ 4) .hi[Two Policies] ✅ - Land-Use Regulations - Rent Control ] --- exclude: true <!-- --- --> <!-- exclude: true --> <!-- ```{R, generate pdfs, include = F} --> <!-- system("decktape remark 02_goodsmarket_part1.html 02_goodsmarket_part1.pdf --chrome-arg=--allow-file-access-from-files") --> <!-- ``` -->