Portland ordinances: tiny home and short-term rental permits

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Billie Ann Brotman
Keyword(s):  
Economic Activity ◽  
Price Index ◽  
Activity Index ◽  
Housing Price ◽  
Short Term ◽  
Content Type ◽  
Coverage Ratio ◽  
Dummy Variable ◽  
Property Owners ◽  
The City

Purpose This study aims to examine the permit changes enacted by the city of Portland, Oregon, USA, on the construction and subsequent short-term rental of tiny homes. The permitting process was eased by the city in 2014. The city’s enforcement of occupancy and rental ordinances, sometimes called Airbnb laws, were tightened in 2019. The new code restrictions are tighter than the rental codes that existed previously. Design/methodology/approach This paper uses time-series data to first consider the thesis that relaxing building permit requirements for tiny homes has encouraged legal construction and increased the number of applications filed with the city planning office. The number of permits was the dependent variable and time-sensitive dummy variable was the independent variable. An adjusted T-statistic was calculated using a least-squares regression model with a moving average autocorrelation adjustment. The second regression model considers the financial relationship between active listings on Airbnb and HomeAway to a housing price coverage ratio and the aggregated dynamic-factor model used to calculate the economic activity index for Portland. Findings There were two reported case study findings. The first regression used a dummy variable measuring the application response to permit easing. It was positive and significant. The second finding measures active host listings on Airbnb whether they are directly associated with the calculated multiple of the changes in the S&P/Case–Shiller housing price index low tier divided by weekly employee income. Higher numbers for this coverage ratio suggest that listings on short-term rental platforms are increasing directly with the ratio. The economic activity index is insignificant when predicting the level of listings. Regression results indicate that property owners are financially motivated to list dwellings as visitor rentals and possibly motivated to install tiny homes behind their primary residences as short-term rental units. Local economic conditions do not seem to influence the number of properties listed on short-term rental websites. Research limitations/implications Higher coverage ratios encourage property owners to list dwellings on short-term rental websites in the absence of enforceable rental restrictions. Without a method to quickly and feasible identify owners violating short-term rental restriction legislation and enforce fines there is a tendency for active listings to grow in a locale. San Francisco, California, under its new short-term rental ordinance requires online websites such as Airbnb to enforce permit requirements. San Francisco’s ordinance change seems to have resulted in a dramatic drop in active listings available for visitor rentals. Practical implications Information published by Inside Airbnb and Airdna does not separate entire dwelling information into categories such as single-family detached houses; tiny homes; apartments; or condominiums ownership types. Even public housing units are sometimes listed as short-term rentals. The aggregate data makes the relationship between active listings and the coverage ratio difficult to interpret. Listing information is limited and only available for a three-year rolling cycle on a quarterly basis for the city of Portland, Oregon. Social implications Future research studies could consider how tiny homes might play a role in providing permanent housing to local residents or for providing a shelter for the homeless in cities experiencing acute long-term rental shortages. Does limiting the number of homes available as short-term visitor rentals noticeably increase the quantity of housing and lower the monthly rental rates available to permanent residents of the city? Cities have passed short-term rental codes with the objective of increasing the availability of rental housing available to residents at affordable prices. Originality/value Prior research studies focused on who purchases tiny homes; tiny homes used as housing for the homeless; communities composed of tiny homes; and the connection between tiny home living and political activism. The study herein links permit changes to tiny-home building applications. It uses the home price index low tier and the economic condition index for the Portland metropolitan area to predict the number of active listings on Airbnb and HomeAway websites pre-regulation enforcement.

Bank capital, liquidity and risk in Ghana

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Emmanuel Carsamer ◽  
Anthony Abbam ◽  
Yaw N. Queku
Keyword(s):  
Capital Accumulation ◽  
Trust Management ◽  
Theoretical Perspective ◽  
Generalized Method Of Moments ◽  
Basel Iii ◽  
Bank Capital ◽  
Short Term ◽  
Content Type ◽  
Coverage Ratio ◽  
Liquidity Measures

Purpose Capital, risk and liquidity are the vitality of the banking industry, which can improve the efficiency of banking and promote the efficiency of resource allocation. The purpose of this study is to examine how Basel III new liquidity ratios affect bank capital and risk adjustments and how banks respond to the new liquidity rules. Design/methodology/approach The authors adopted the system generalized method of moments (GMM) to examine how Basel III new liquidity ratios affect bank capital and risk adjustments and how banks respond to the new liquidity rules. Based on the call reports data from banks, GMM was used to test the hypotheses that new liquidity ratios affect bank capital and risk adjustments, as well as how banks respond to the regulation. Findings The results indicate banks targeted capital, risk and liquidity and simultaneously coordinate short-term adjustments in capital and risk. New liquidity measures enable banks to coordinate risk and liquidity decisions. Short-term adjustments in new liquidity rules inversely impact bank capital. Short-term adjustments in new liquidity rules inversely impact bank capital and capital adjustments adversely affect changes in the liquidity coverage ratio (LCR). Research limitations/implications The primary results revealed that Ghanaian banks simultaneously coordinate and target capital, risk exposure and liquidity level. Also, capital adjustments positively influence risk adjustments and vice versa while bidirectional negative coordination exists between bank capital and risk on one hand and liquidity on the other hand. Short-term adjustments in new liquidity rule inversely impact bank capital and capital adjustments adversely affect changes in the LCR. The findings partially confirm the theoretical predictions of Repullo (2005) regarding the negative links between capital, risk and liquidity but the authors have higher capital induces higher risk. Practical implications Banks should balance off their targeted risk and liquidity in order not to sacrifice capital accumulation for liquidity. Originality/value This research offers new contributions in the research of bank management of capital and liquidity toward banks during a financial crisis from a theoretical perspective and trust management from an applicative perspective.

Is HOA capitalized in housing price? Evidence from Chongqing, China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Feng Deng
Keyword(s):  
Telephone Survey ◽  
Empirical Finding ◽  
Housing Price ◽  
Data Set ◽  
Chinese Cities ◽  
Content Type ◽  
Dummy Variable ◽  
Homeowners Association ◽  
Private Communities ◽  
Different Sources

Purpose International research has found that Homeowners Association (HOA) is capitalized in housing price in the West. Is that result applicable in Chinese cities? In China there is also widespread applause for HOA. Will that leave trail in the housing market? This paper aims to answers these questions by presenting empirical evidence from 113 private gated communities in Chongqing, China. Design/methodology/approach The data set comes from three different sources including a telephone survey. The research methodology includes hedonic models with an endogenous dummy variable of the presence of HOA in a community. Findings HOA is not capitalized in housing price. Research limitations/implications The empirical finding helps to explain why about 80% of private communities in big Chinese cities have not formed an HOA. Originality/value This is the first empirical study on HOA capitalization in housing price in China.

Dynamic effects and spatial heterogeneity of land supply on housing price: evidence from Nanchang, China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhijiang Wu ◽  
Yongxiang Wang ◽  
Wei Liu
Keyword(s):  
Spatial Heterogeneity ◽  
House Prices ◽  
Housing Prices ◽  
Housing Price ◽  
Dynamic Effects ◽  
Negative Effects ◽  
Land Supply ◽  
Content Type ◽  
Major Factors ◽  
The City

Purpose Economic fundamentals are recognized as determining factors for housing on the city level, but the relationship between housing price and land supply has been disputed. This study aims to examine what kind of impact housing prices have on land supply and whether there is heterogeneity in different regional spaces. Design/methodology/approach This study collects the relevant data of land supply and housing prices in Nanchang from 2010 to 2018, constructs a vector autoregression (VAR) model, including one external factor and four internal factors of land supply to explore the dynamic effects and spatial heterogeneity of land supply on housing prices through regression analysis. Also, the authors use the geographic detector to analyze the spatial heterogeneity of housing prices in Nanchang. Findings This study found that the interaction between land supply and housing price is extremely complex because of the significant differences in the study area; the variables of land supply have both positive and negative effects on housing price, and the actual effect varies with the region; and residential land and GDP are the two major factors leading to the spatial heterogeneity in housing price. Research limitations/implications The dynamic effects of land supply on housing price are mainly reflected in the center and edge of the city, the new development area, and the old town, which is consistent with the spatial pattern of the double core, three circles and five groups in Nanchang. Originality/value This is a novel work to analyze the dynamic effects of land supply on house prices, instead of a single amount of land supply or land prices. Furthermore, the authors also explore the spatial heterogeneity according to the regional characteristics, which is conducive to targeted policymaking.

Property investor decisions using income and rental ratio signals

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Billie Ann Brotman
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Discount Rate ◽  
Price Index ◽  
Housing Prices ◽  
Housing Price ◽  
Consumer Sentiment ◽  
Content Type ◽  
Income Ratio ◽  
Real Estate Prices

PurposeThis paper, a case study, aims to consider whether the income ratio and rental ratio tracks the formation of residential housing price spikes and their collapse. The ratios are measuring the risk associated with house price stability. They may signal whether a real estate investor should consider purchasing real property, continue holding it or consider selling it. The Federal Reserve Bank of Dallas (Dallas Fed) calculates and publishes income ratios for Organization for Economic Cooperation and Development countries to measure “irrational exuberance,” which is a measure of housing price risk for a given country's housing market. The USA is a member of the organization. The income ratio idea is being repurposed to act as a buy/sell signal for real estate investors.Design/methodology/approachThe income ratio calculated by the Dallas Fed and this case study's ratio were date-stamped and graphed to determine whether the 2006–2008 housing “bubble and burst” could be visually detected. An ordinary least squares regression with the data transformed into logs and a regression with structural data breaks for the years 1990 through 2019 were modeled using the independent variables income ratio, rent ratio and the University of Michigan Consumer Sentiment Index. The descriptive statistics show a gradual increase in the ratios prior to exposure to an unexpected, exogenous financial shock, which took several months to grow and collapse. The regression analysis with breaks indicates that the income ratio can predict changes in housing prices using a lead of 2 months.FindingsThe gradual increases in the ratios with predetermine limits set by the real estate investor may trigger a sell decision when a specified rate is reached for the ratios even when housing prices are still rising. The independent variables were significant, but the rent ratio had the correct sign only with the regression with time breaks model was used. The housing spike using the Dallas Fed's income ratio and this study's income ratio indicated that the housing boom and collapse occurred rapidly. The boom does not appear to be a continuous housing price increase followed by a sudden price drop when ratio analysis is used. The income ratio is significant through time, but the rental ratio and Consumer Sentiment Index are insignificant for multiple-time breaks.Research limitations/implicationsInvestors should consider the relative prices of residential housing in a neighborhood when purchasing a property coupled with income and rental ratio trends that are taking place in the local market. High relative income ratios may signal that when an unexpected adverse event occurs the housing market may enter a state of crisis. The relative housing prices to income ratio indicates there is rising housing price stability risk. Aggregate data for the country are used, whereas real estate prices are also significantly impacted by local conditions.Practical implicationsRatio trends might enable real estate investors and homeowners to determine when to sell real estate investments prior to a price collapse and preserve wealth, which would otherwise result in the loss of equity. Higher exuberance ratios should result in an increase in the discount rate, which results in lower valuations as measured by the formula net operating income dividend by the discount rate. It can also signal when to start reinvesting in real estate, because real estate prices are rising, and the ratios are relative low compared to income.Social implicationsThe graphical descriptive depictions seem to suggest that government intervention into the housing market while a spike is forming may not be possible due to the speed with which a spike forms and collapses. Expected income declines would cause the income ratios to change and signal that housing prices will start declining. Both the income and rental ratios in the US housing market have continued to increase since 2008.Originality/valueA consumer sentiment variable was added to the analysis. Prior researchers have suggested adding a consumer sentiment explanatory variable to the model. The results generated for this variable were counterintuitive. The Federal Housing Finance Agency (FHFA) price index results signaled a change during a different year than when the S&P/Case–Shiller Home Price Index is used. Many prior studies used the FHFA price index. They emphasized regulatory issues associated with changing exuberance ratio levels. This case study applies these ideas to measure relative increases in risk, which should impact the discount rate used to estimate the intrinsic value of a residential property.

Green federal tax credits impact on US housing prices

2020 ◽  
Vol 13 (4) ◽  
pp. 553-564
Author(s):  
Billie Ann Brotman
Keyword(s):  
Regression Model ◽  
Energy Policy ◽  
Income Tax ◽  
Housing Prices ◽  
Housing Price ◽  
Tax Credits ◽  
Disposable Income ◽  
Content Type ◽  
Dummy Variable ◽  
Energy Policy Act

Purpose The purpose of this study is to investigate whether increases in homeowner green amenities occurred because of income tax credits to the degree that changes in housing prices are measurable. Are higher incomes, lower mortgage rates and green income-tax credits impacting housing price changes? Design/methodology/approach The paper uses the least-squares regression model with natural log specifications. The log of income and a dummy variable, which was assigned to the Energy Policy Act (2005) and the American Recovery and Reinvestment Act (2009) coverage dates are used as independent variables. Two regression models were examined using monthly housing price data from January 1990 through the year 2018. The first regression model used a single dummy variable for credits available under the Policy Act of 2005 and the Recovery Act of 2009. The second regression model considered the credits granted under these two laws separately. Disposable income per capita impacts demands for housing while green upgrade expenditures affect the cost of housing. Findings The laws set low credit limits of $500 followed by $1,500 but because of the multiplier effect, the spending appears to have magnified and been much higher. The credit availability variables have positive coefficients and were significant at 1 per cent. This implies that single-family housing prices were sensitive to the existence of residential energy property income-tax credits. The R2 results were 0.93 or above for both models. Research limitations/implications The data used was aggregated and publicly available online. Many studies use aggregated macroeconomic data when modeling housing prices using the exogenous variable of disposable income but there is no substitute for examining individual homes by location and their sales price to see under what conditions green income-tax credits have the most impact. There could be demographic issues that are missed when using aggregated information. Practical implications Spending on heating/cooling systems, dual pane windows and other green amenities keeps the housing stock modernized and housing prices steady or rising. An additional benefit is that spending motivated by self-interest can simulate household consumption spending. Houses deteriorate due to wear and tear. Physical-repairable depreciation represents a situation where maintenance funds are continuously needing to be spent. Repairs and upgrades to the structure of the property keep its price stable by stopping the physical depreciation that would otherwise occur with the passage of time. Social implications The paper provides support for the idea that residential green amenity upgrades positively impact the value of a house. These green-amenity upgrades, which other research studies have suggested should be included explicitly in the appraisal process, are a major characteristic of a property when a price estimate is being done. Housing being sold should have a section on the information sheet noting the property green upgrades that exist and an energy efficiency score should be assigned to each house listed for sale. Originality/value There are few (if any) academic research papers studying the impact of green tax credits available under the Energy Policy Act (2005) and under the American Recovery and Reinvestment Act (2009). The degree to which green income-tax credits stimulate spending on housing has not been addressed by researchers. This paper is an initial research attempt to quantify whether these legislative efforts measurably encouraged homeowners to adopt newer, greener technologies.

Russia-Turkey aim to freeze Libya but others will stir

2020 ◽  
Keyword(s):  
Market Share ◽  
Oil Industry ◽  
Short Term ◽  
Content Type ◽  
External Powers ◽  
Energy Companies ◽  
The City ◽  
Global Powers

Significance Regional and global powers will determine whether there will be conflict around the city of Sirte, the scale of the fighting, the short-term future of Libya's oil industry, and the contours of the diplomatic process that will resolve these various quandaries. Impacts The UN’s marginalisation will continue, and Europe will also fade as a broker. Libyan oil output will be unpredictable, as it is a way for external powers to influence the conflict. European energy companies (such as ENI, Repsol and Wintershall) could lose market share to state-aligned companies of intervening players. Cairo could see itself jostled into an intervention with no clear scope.

Protests could shift Albania towards authoritarianism

2019 ◽  
Keyword(s):  
Prime Minister ◽  
European Council ◽  
Political Crisis ◽  
Business Activity ◽  
Short Term ◽  
Content Type ◽  
Student Protests ◽  
The City

Significance Student protests demanding fundamental reform have resumed with the new term and are spreading beyond Tirana to other groups, including -- worryingly for Prime Minister Edi Rama -- miners and other workers. Rama’s sacrifice of senior ministers has failed to quiet the street protests, the largest since the demise of communism. Impacts Thousands of protesters and the closure of roads into the city will interrupt business activity in central Tirana in the short term. A new cabinet with little experience and under close prime ministerial control will depress the quality of policymaking. An escalating political crisis would reduce Albania’s chances of being asked at the June European Council to open accession negotiations.

Tripoli offensive punctuates otherwise normal life

2019 ◽  
Keyword(s):  
Foreign Investment ◽  
Economic Activity ◽  
Content Type ◽  
Normal Life ◽  
The City

Significance Tripoli's Mitiga Airport has been closed and flights diverted to Misrata owing to a military offensive by eastern rebel general Khalifa Haftar to take the capital. The fighting has disrupted some areas of the city, whereas in others, life is surprisingly normal. Impacts Government and economic activity will remain steady, despite the conflict. The humanitarian impact of fighting will remain relatively limited. Major new foreign investment is unlikely.

Impact of macroeconomic indicators on housing prices

2019 ◽  
Vol 12 (6) ◽  
pp. 1055-1071 ◽  
Author(s):  
Satish Mohan ◽  
Alan Hutson ◽  
Ian MacDonald ◽  
Chung Chun Lin
Keyword(s):  
Price Index ◽  
Time Series Data ◽  
Statistical Significance ◽  
Housing Prices ◽  
Consumer Price Index ◽  
New York State ◽  
Housing Price ◽  
Series Data ◽  
Content Type ◽  
Macroeconomic Indicators

Purpose This paper uses statistical analyses to quantify the effects of five major macroeconomic indicators, namely crude oil price, 30-year mortgage interest rate (IR), Consumer Price Index (CPI), Dow Jones Industrial Average (DJIA), and unemployment rate (UR), on housing prices over time. Design/methodology/approach Housing price is measured as housing price index (HPI) and is treated as a variable affecting itself. Actual housing sale prices in the Town of Amherst, New York State, USA, 1999-2008, and time-series data of the macroeconomic indicators, 2000-2017, were used in a vector autoregression statistical model to examine the data that show the greatest statistical significance and exert maximum quantitative effects of macroeconomic indicators on housing prices. Findings The analyses concluded that the 30-year IR and HPI have statistically significant effects on housing prices. IR has the highest effect, contributing 5.0 per cent of variance in the first month to 8.5 per cent in the twelfth. The UR has the next greatest influence followed by DJIA and CPI. The disturbance from HPI itself causes the greatest variability in future prices: up to 92.7 per cent in variance 1 month ahead and approximately 74.5 per cent 12 months ahead. This result indicates that current changes in house prices heavily influence people’s expectation of future prices. The total effect of the error variance of the macroeconomic indicators ranged from 7.3 per cent in the first month to 25.5 per cent in the twelfth. Originality/value The conclusions in this paper, along with related tables and figures, will be useful to the housing and real estate communities in planning their business for the next years.

A housing price index with the improvement-value adjusted repeated sales (IVARS) method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chung Yim Edward Yiu ◽  
Ka Shing Cheung
Keyword(s):  
Price Index ◽  
Simulation Analysis ◽  
House Price ◽  
Housing Price ◽  
Housing Quality ◽  
Repeat Sales ◽  
Open Market ◽  
Hedonic Price ◽  
Content Type ◽  
Price Movements

Purpose The repeat sales house price index (HPI) has been widely used to measure house price movements on the assumption that the quality of properties does not change over time. This study aims to develop a novel improvement-value adjusted repeat sales (IVARS) HPI to remedy the bias owing to the constant-quality assumption. Design/methodology/approach This study compares the performance of the IVARS model with the traditional hedonic price model and the repeat sales model by using half a million repeated sales pairs of housing transactions in the Auckland Region of New Zealand, and by a simulation approach. Findings The results demonstrate that using the information on improvement values from mass appraisal can significantly mitigate the time-varying attribute bias. Simulation analysis further reveals that if the improvement work done is not considered, the repeat sales HPI may be overestimated by 2.7% per annum. The more quality enhancement a property has, the more likely it is that the property will be resold. Practical implications This novel index may have the potential to enable the inclusion of home condition reporting in property value assessments prior to listing open market sales. Originality/value The novel IVARS index can help gauge house price movements with housing quality changes.

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