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Since the first mobile camping unit was strapped to the back of a Ford Model T in the 1920’s, the concept of manufactured homes has been an important factor.

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Presentation on theme: "Since the first mobile camping unit was strapped to the back of a Ford Model T in the 1920’s, the concept of manufactured homes has been an important factor."— Presentation transcript:

1 Since the first mobile camping unit was strapped to the back of a Ford Model T in the 1920’s, the concept of manufactured homes has been an important factor of the American housing market. In North Carolina alone, a little more than 16% of the housing stock is comprised of manufactured housing. With approximately 5,200 census block groups of around 2,000 people, 1,300 of which have at least 30% of their housing stock in manufactured homes, we can estimate that about 780,000 North Carolinians live in manufactured homes, and likely half of those live in trailer parks. So what does the trailer park literature have to say about this institution? Next to nothing, it turns out. Current trailer park literature is limited to observations on rent control in trailer parks or measuring how happy people are in trailer parks relative to other forms of low income housing. Nothing discusses why people choose to live in such an odd mixed rental-ownership system as a trailer park, instead of fully owning or renting their housing. We propose four models through which the development of trailer parks could be explained. The first two are equilibrium models, in which tenants and landowners contract while in a housing market equilibrium. The second two show that trailer parks arise in response to growth shocks in the economy in which housing becomes scarce or uncertain. Equilibrium models include 1) Bad Tenants, 2) Capital Constraints on both Investors and Occupants, while disequilibrium models include 3) Risk-Sharing and Uncertain Growth, and 4) Short vs. Long Term Urban Growth.* * Due to space limitations, only models 1) Bad Tenants and 3) Risk-Sharing and Uncertain Growth will be displayed. Empirics Equilibrium Model: Bad Tenants Pure Rental System from Owner’s Perspective: Owns large tract of land upon which rental structures are placed. Goal: maximize profits. He cannot observe whether a renter is “good” or “bad”. Revenues depend on a flat rental rate across types of tenants. Costs are: renovation, park upkeep, eviction and are higher with bad renters. The owner recognizes he cannot maximize profit if he has “bad renters”, so he tries to “homogenize” renters, by requiring them to take on risk. Pure Ownership from Tenants Perspective: Tenants own both land and capital. A bad tenant creates negative externalities for the rest. The tenant maximizes utility subject to a budget constraint, which includes externalities. Neighbors can choose to hire a 3 rd party regulator or not. U i represents utility, e i is effort it takes to be good, ne i is negative externalities, C e is cost of eviction. The Game without 3 rd party actor, Nash Equilibrium in red: The Game with 3 rd party actor as “Benevolent Dictator”. Introduction of eviction costs borne by bad tenants, C e > e i Mixed Rental and Ownership System: Land owners rent only land, and tenants prefer to own only structure, but how does the system come into existence? By a contracting game and backwards induction. When both abide by contract: Owners gains U(r l l), and tenant gains U i -e. If tenant breaches contract, owner finds out with probability, P: owner gains P[U(r l l-r l l i )], tenant gains P(U i -C e ). There is clear incentive for all to abide by the contract. Summary: It is in the owner’s best interest to require tenants to purchase their own housing unit, so he can avoid repairs to rented housing. It is in the tenant’s best interest to hire a 3 rd party regulator to get rid of unsavory neighbors, even though this may mean sacrifice of some housing rights. Predictions: This model predicts that trailer parks will be very homogeneous within parks, but across parks will differ based on the contracting systems between the tenants and owners. The landowner is risk averse and gets less utility from profits than he does disutility from losses. Because the owner has an uncertain future, he wants to minimize his future costs. He cannot minimize costs by scaling back the entire venture; uncertainty can still result in high losses if tenants follow work to another city. It is the owner’s best choice to share some of the burden of risk with the tenants, whom he views as flight risks This model strongly relates to factory towns. In towns with newly built factories, there is a high demand for new housing immediately. Manufactured housing is a low-cost and expedient way to provide housing to blue-collar factory workers. The developer fears the factory will close, leaving the new housing developments empty. It is most profitable for the landowner to rent parcels of land, but not invest in the housing units, instead having renters provide their own units. Owners: maximize utility U(π)=√π where preferences are Cobb-Douglas, satisfying the necessary risk aversion specifications. We will define π=(r k -c k )k+(r l -c l )l, with r’s as rents, and c’s as costs, with respect to k, capital, and l, land. Over two time periods, the owner will maximize his expected utility. We assume the owner has information about the growth and urban climate in the first time period, but is uncertain about the second period. We represent the probability of growth, as P, with 0 { "@context": "http://schema.org", "@type": "ImageObject", "contentUrl": "http://images.slideplayer.com/13/4083402/slides/slide_1.jpg", "name": "Since the first mobile camping unit was strapped to the back of a Ford Model T in the 1920’s, the concept of manufactured homes has been an important factor of the American housing market.", "description": "In North Carolina alone, a little more than 16% of the housing stock is comprised of manufactured housing. With approximately 5,200 census block groups of around 2,000 people, 1,300 of which have at least 30% of their housing stock in manufactured homes, we can estimate that about 780,000 North Carolinians live in manufactured homes, and likely half of those live in trailer parks. So what does the trailer park literature have to say about this institution. Next to nothing, it turns out. Current trailer park literature is limited to observations on rent control in trailer parks or measuring how happy people are in trailer parks relative to other forms of low income housing. Nothing discusses why people choose to live in such an odd mixed rental-ownership system as a trailer park, instead of fully owning or renting their housing. We propose four models through which the development of trailer parks could be explained. The first two are equilibrium models, in which tenants and landowners contract while in a housing market equilibrium. The second two show that trailer parks arise in response to growth shocks in the economy in which housing becomes scarce or uncertain. Equilibrium models include 1) Bad Tenants, 2) Capital Constraints on both Investors and Occupants, while disequilibrium models include 3) Risk-Sharing and Uncertain Growth, and 4) Short vs. Long Term Urban Growth.* * Due to space limitations, only models 1) Bad Tenants and 3) Risk-Sharing and Uncertain Growth will be displayed. Empirics Equilibrium Model: Bad Tenants Pure Rental System from Owner’s Perspective: Owns large tract of land upon which rental structures are placed. Goal: maximize profits. He cannot observe whether a renter is good or bad . Revenues depend on a flat rental rate across types of tenants. Costs are: renovation, park upkeep, eviction and are higher with bad renters. The owner recognizes he cannot maximize profit if he has bad renters , so he tries to homogenize renters, by requiring them to take on risk. Pure Ownership from Tenants Perspective: Tenants own both land and capital. A bad tenant creates negative externalities for the rest. The tenant maximizes utility subject to a budget constraint, which includes externalities. Neighbors can choose to hire a 3 rd party regulator or not. U i represents utility, e i is effort it takes to be good, ne i is negative externalities, C e is cost of eviction. The Game without 3 rd party actor, Nash Equilibrium in red: The Game with 3 rd party actor as Benevolent Dictator . Introduction of eviction costs borne by bad tenants, C e > e i Mixed Rental and Ownership System: Land owners rent only land, and tenants prefer to own only structure, but how does the system come into existence. By a contracting game and backwards induction. When both abide by contract: Owners gains U(r l l), and tenant gains U i -e. If tenant breaches contract, owner finds out with probability, P: owner gains P[U(r l l-r l l i )], tenant gains P(U i -C e ). There is clear incentive for all to abide by the contract. Summary: It is in the owner’s best interest to require tenants to purchase their own housing unit, so he can avoid repairs to rented housing. It is in the tenant’s best interest to hire a 3 rd party regulator to get rid of unsavory neighbors, even though this may mean sacrifice of some housing rights. Predictions: This model predicts that trailer parks will be very homogeneous within parks, but across parks will differ based on the contracting systems between the tenants and owners. The landowner is risk averse and gets less utility from profits than he does disutility from losses. Because the owner has an uncertain future, he wants to minimize his future costs. He cannot minimize costs by scaling back the entire venture; uncertainty can still result in high losses if tenants follow work to another city. It is the owner’s best choice to share some of the burden of risk with the tenants, whom he views as flight risks This model strongly relates to factory towns. In towns with newly built factories, there is a high demand for new housing immediately. Manufactured housing is a low-cost and expedient way to provide housing to blue-collar factory workers. The developer fears the factory will close, leaving the new housing developments empty. It is most profitable for the landowner to rent parcels of land, but not invest in the housing units, instead having renters provide their own units. Owners: maximize utility U(π)=√π where preferences are Cobb-Douglas, satisfying the necessary risk aversion specifications. We will define π=(r k -c k )k+(r l -c l )l, with r’s as rents, and c’s as costs, with respect to k, capital, and l, land. Over two time periods, the owner will maximize his expected utility. We assume the owner has information about the growth and urban climate in the first time period, but is uncertain about the second period. We represent the probability of growth, as P, with 0


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