{"title":"Housing Market Value Impairment from Future Sea-level Rise Inundation","authors":"David Rodziewicz, C. Amante, Jacob Dice, E. Wahl","doi":"10.2139/ssrn.3657364","DOIUrl":"https://doi.org/10.2139/ssrn.3657364","url":null,"abstract":"Sea level rise will pose increased risks to U.S. coastal real estate markets in the coming decades, though the direct economic costs depend on the severity and uncertainty within climate-change scenarios.","PeriodicalId":239768,"journal":{"name":"Urban Research eJournal","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133164635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Voith, Jing Liu, Sean Zielenbach, Andrew Jakabovics, Brian Y. An, Seva Rodnyansky, Anthony W. Orlando, Raphael W. Bostic
{"title":"The Effects of Concentrated LIHTC Development on Surrounding House Prices","authors":"R. Voith, Jing Liu, Sean Zielenbach, Andrew Jakabovics, Brian Y. An, Seva Rodnyansky, Anthony W. Orlando, Raphael W. Bostic","doi":"10.2139/ssrn.3740758","DOIUrl":"https://doi.org/10.2139/ssrn.3740758","url":null,"abstract":"The Low-Income Housing Tax Credit is the largest supply-side housing subsidy in the United States, costing over $8 billion per year. LIHTC properties tend to be concentrated in low-income urban communities. Numerous studies have examined the spillover effects of these properties but have not accounted for their clustering or teased out the effects of introducing additional LIHTC developments to neighborhoods. We combine an interrupted time series model with a difference-in-difference approach to estimate the additive property value effects in Chicago and surrounding Cook County, Illinois. The development of subsequent LIHTC properties within a neighborhood augments the positive effects of the initial property as far as half a mile away, in both low-income and higher-income areas. The effects are most pronounced in neighborhoods with low median incomes.","PeriodicalId":239768,"journal":{"name":"Urban Research eJournal","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132160835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"How Hurricanes Sweep Up Housing Markets: Evidence from Florida","authors":"Joshua Graff Zivin, Yanjun Liao, Yann Panassie","doi":"10.3386/w27542","DOIUrl":"https://doi.org/10.3386/w27542","url":null,"abstract":"This paper examines the impacts of hurricanes on the housing market and the associated implications for local population turnover. We first characterize the post-hurricane equilibrium dynamics in local housing markets using microdata from Florida during 2000-2016. Our results show that hurricanes cause an increase in equilibrium prices and a concurrent decrease in transactions in affected areas, both lasting up to three years. Together, these dynamics imply a negative transitory shock to the housing supply as a consequence of the hurricane. Furthermore, we match buyer characteristics from mortgage applications to provide the first buyer-level evidence on population turnover. We find that incoming homeowners in this period have higher incomes, leading to an overall shift in the local economic profile toward higher-income groups. Our findings suggest that market responses to destructive natural disasters can lead to uneven and lasting demographic changes in affected communities, even with a full recovery in physical capital.","PeriodicalId":239768,"journal":{"name":"Urban Research eJournal","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123956342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Scaling Up Battery Swapping Services in Cities","authors":"Wei Qi, Yuli Zhang, Ningwei Zhang","doi":"10.2139/ssrn.3631796","DOIUrl":"https://doi.org/10.2139/ssrn.3631796","url":null,"abstract":"Battery swapping for electric vehicle refueling is reviving and thriving. Despite a captivating sustainable future where swapping batteries will be as convenient as refueling gas today, tensions are mounting in practice (beyond the traditional “range anxiety” issue): On one hand, it is desirable to maximize battery proximity and availability to customers. On the other hand, it is undesirable to incur too many batteries which are environmentally detrimental. Additionally, power grids for battery charging are not accessible everywhere. To reconcile these tensions, some cities are embracing an emerging infrastructure network: Decentralized swapping stations replenish charged batteries from centralized charging stations. In this paper, we model this new urban infrastructure network. This task is complicated by non-Poisson swaps (observed from real data), and by the intertwined stochastic operations of swapping, charging, stocking and circulating batteries among swapping and charging stations. We show that these complexities can be captured by analytical models. We next propose a new location-inventory model for citywide deployment of hub charging stations, which jointly determines the location, allocation and reorder quantity decisions with a non-convex non-concave objective function. We solve this problem exactly and efficiently by exploiting the hidden submodularity and combining constraint-generation and parameter-search techniques. Even for solving convexified problems, our algorithm brings a speedup of at least three orders of magnitude relative to Gurobi solver. The major insight is twofold: Centralizing battery charging may harm cost-efficiency and battery asset-lightness; however, this finding is reversed if foreseeing that decentralized charging will have limited access to grids permitting fast charging. We also identify planning and operational flexibilities brought by centralized charging. In a broader sense, this work deepens our understanding about how mobility and energy are coupled in future smart cities.","PeriodicalId":239768,"journal":{"name":"Urban Research eJournal","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123577742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michelle D. Layser, Edward W. De Barbieri, Andrew J. Greenlee, Tracy A. Kaye, Blaine G. Saito
{"title":"Mitigating Housing Instability During a Pandemic","authors":"Michelle D. Layser, Edward W. De Barbieri, Andrew J. Greenlee, Tracy A. Kaye, Blaine G. Saito","doi":"10.2139/ssrn.3613789","DOIUrl":"https://doi.org/10.2139/ssrn.3613789","url":null,"abstract":"Housing instability threatens to impair the United States’ policy response to the COVID-19 pandemic by undermining public health strategies such as social dista","PeriodicalId":239768,"journal":{"name":"Urban Research eJournal","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126930968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Tracking Owners’ Sentiments: Subjective Home Values, Expectations and House Price Dynamics","authors":"A. Lepinteur, S. Waltl","doi":"10.2139/ssrn.3782326","DOIUrl":"https://doi.org/10.2139/ssrn.3782326","url":null,"abstract":"Economic theory predicts that expectations on future house price growth are related to the current price of a house. We test this relationship for the supply side of the secondary housing market using micro data that links individual expectations to a subjective owner estimated value (OEV). We find a strong causal relationship that optimistic expectations indeed imply higher OEVs as compared to neutral or pessimistic expectations. We find qualitatively and quantitatively consistent results for Italy and the US as well as for booming and gloomy years. Our results survive ample robustness checks. Since we use subjective data on house prices, we first show that OEVs are indeed a valid source to study house price dynamics by performing three types of convergent validity tests. We find that price dynamics derived by either combining OEVs and dwelling characteristics, or making use of repeatedly provided OEVs by the same owner over time reproduce objectively measured market trends strikingly well – even over decades. In contrast, OEVs and objective data tend to differ in levels – potentially due to psychological bias. These results hold for a large set of countries. We hence conclude that the \"wisdom of the home-owner crowd\" is sufficient to study house price dynamics but OEVs are less suited for measuring the level of market prices.","PeriodicalId":239768,"journal":{"name":"Urban Research eJournal","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115803927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Return of State Control and Its Impact on Land Market Efficiency","authors":"Ling-Hin Li, Helen X. H. Bao, G. Robinson","doi":"10.2139/ssrn.3642848","DOIUrl":"https://doi.org/10.2139/ssrn.3642848","url":null,"abstract":"Urban land reform in China aims to build an efficient land market. However, it has led to a dual land supply system that consists of both market-based leasing and administrative allocation. In recent years, the control by local municipal government over land supply has strengthened substantially. This has caused concerns over whether the land reforms can achieve efficiency goals given the constraints imposed on market instruments. This paper addresses this important question by studying whether market instruments introduced by urban land reforms improved the efficiency of land supply and new housing supply after state control was tightened from 2002. We propose a theoretical framework that incorporates the interactions between land and housing supply and facilitates analysis at both the macro and the micro levels. We find that the return of state control has caused a general decline of the marketization level in China’s first tier cities. The land marketization level in new first tier and second tier cities has improved significantly over the last decade, but the trend has already slowed down. The overall trajectory of land marketization in China is a clear downward trend since 2002. Meanwhile, we have found consistent evidence that higher levels of land marketization lead to more efficient land and housing supply. As a result, the cost of increased state control has offset the benefits of market-oriented supply methods, and the overall effect is a decline in land market efficiency. These findings have important implications in understanding the role of government interventions in supporting market-based activities in China’s land and housing markets.","PeriodicalId":239768,"journal":{"name":"Urban Research eJournal","volume":"227 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130836439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Enduring Effects of Interest Rates at Mortgage Origination","authors":"Don Carmichael, Dimuthu Ratnadiwakara, K. Roshak","doi":"10.2139/ssrn.3607979","DOIUrl":"https://doi.org/10.2139/ssrn.3607979","url":null,"abstract":"Modest differences in the interest rate at home purchase can have long-lasting effects on mortgagors. We use within-year variation in average interest rates at loan origination to instrument for contracted mortgage rates. For homeowners with negative equity, a 50bp increase in the national rate at origination leads to an increase in defaults of 10-20% of the sample average, but the instrument is not correlated with worse credit. Consistent with liquidity constraints, the magnitude is constant across many different levels of negative equity. During the boom, lower interest rates result in increased consumption of non-durables and services, while total expenditure is unchanged.","PeriodicalId":239768,"journal":{"name":"Urban Research eJournal","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114831203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"How Prices, Income, and Weather Shape Household Electricity Demand in High-Income and Middle-Income Countries","authors":"Brantley Liddle, H. Huntington","doi":"10.2139/ssrn.3596984","DOIUrl":"https://doi.org/10.2139/ssrn.3596984","url":null,"abstract":"Abstract This analysis provides an international perspective geared towards understanding the future demands being placed on the world's electricity system. It focuses upon the household or residential demand for electricity in a number of high-income and middle-income countries that may raise power demands for cooling in a warming world. Panel estimates on 26 high-income and 29 middle-income countries over the 1978–2013 period provide critical information on how household electricity demand responds to income, weather, and prices. Our dynamic panel estimates address nonstationarity, heterogeneity, and cross-sectional dependence. We believe these are the first panel estimates for middle-income/non-OECD countries and the first panel estimates for high-income/OECD countries to address all three of the previously identified statistical issues. Relative to high-income country responses, long-run elasticities for middle-income nations are larger for income (0.8 compared to 0.6), larger for cooling (0.3 versus insignificant), and smaller for prices (−0.08 relative to −0.2). As middle-income economies are likely to grow more rapidly than high-income/OECD economies, the trends related to income and cooling responses are likely to place greater pressure on a warming world unless the power sector can be decarbonized globally.","PeriodicalId":239768,"journal":{"name":"Urban Research eJournal","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127167959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Steve Cicala, S. Holland, E. Mansur, Nicholas Z. Muller, Andrew Yates
{"title":"Expected Health Effects of Reduced Air Pollution from Covid-19 Social Distancing","authors":"Steve Cicala, S. Holland, E. Mansur, Nicholas Z. Muller, Andrew Yates","doi":"10.3386/w27135","DOIUrl":"https://doi.org/10.3386/w27135","url":null,"abstract":"The COVID-19 pandemic resulted in stay-at-home policies and other social distancing behaviors in the United States in spring of 2020. This paper examines the impact that these actions had on emissions and expected health effects through reduced personal vehicle travel and electricity consumption. Using daily cell phone mobility data for each U.S. county, we find that vehicle travel dropped about 40% by mid-April across the nation. States that imposed stay-at-home policies before March 28 decreased travel slightly more than other states, but travel in all states decreased significantly. Using data on hourly electricity consumption by electricity region (e.g., balancing authority), we find that electricity consumption fell about 6% on average by mid-April with substantial heterogeneity. Given these decreases in travel and electricity use, we estimate the county-level expected improvements in air quality, and, therefore, expected declines in mortality. Overall, we estimate that, for a month of social distancing, the expected premature deaths due to air pollution from personal vehicle travel and electricity consumption declined by approximately 360 deaths, or about 25% of the baseline 1500 deaths. In addition, we estimate that CO2 emissions from these sources fell by 46 million metric tons (a reduction of approximately 19%) over the same time frame.","PeriodicalId":239768,"journal":{"name":"Urban Research eJournal","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124530338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
