What caused the rise of Airbnb? An examination of key macroeconomic factors

The social and economic implications of the Airbnb phenomenon have been the subject of much research. Yet, the academic literature on Airbnb is nascent. Specifically, the issue of whether major macroeconomic conditions affect the supply of Airbnb has not been investigated. To address this gap, we propose a conceptual model that explains the determinants of Airbnb supply and examine the extent to which major macroeconomic factors affect the supply of Airbnb. Specifically, we analyze the effects of hotel room rates (ADR), hotel demand, tourism demand, house prices, gross domestic product (GDP), wages and unemployment on the supply of Airbnb in 50 U.S. states. Results show that increases in hotel ADR, house prices, and GDP have contributed to an increase in the supply of Airbnb, whereas increases in unemployment rates and wages have adverse effects on Airbnb supply. Theoretical and policy implications are discussed within realms of macroeconomic theory.     

Are USDA reports still news to changing crop markets?

This study investigates whether major USDA reports still provide important news to changing crop markets. The news component of each report, or market “surprise,” is measured as a difference between the USDA estimate and its private expectation in corn, soybeans, and wheat markets. Changes in the relevance of USDA information are assessed by examining changes in the magnitude of market surprises and shifts in the futures price reaction to these surprises, which isolates the impact of each report. The stable size of market surprises over time suggests that competition from alternative data sources has not reduced the news component of USDA crop reports. Increasing price reaction to most reports, including those facing competition from alternative information sources, suggests that value of public information may be enhanced in uncertain markets affected by structural changes.     

Local network externalities and market segmentation

This paper models interaction between groups of agents by means of a graph where each node represents a group of agents and an arc represents bilateral interaction. It departs from the standard Katz–Shapiro framework by assuming that network benefits are restricted only amongst groups of linked agents. It shows that even if rival firms engage in Bertrand competition, this form of network externalities permits strong market segmentation in which firms divide up the market and earn positive profits. The analysis also shows that some graphs or network structures do not permit such segmentation, while for others, there are easy to interpret conditions under which market segmentation obtains in equilibrium.     

Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks

We present a hierarchical architecture based on recurrent neural networks for predicting disaggregated inflation components of the Consumer Price Index (CPI). While the majority of existing research is focused on predicting headline inflation, many economic and financial institutions are interested in its partial disaggregated components. To this end, we developed the novel Hierarchical Recurrent Neural Network (HRNN) model, which utilizes information from higher levels in the CPI hierarchy to improve predictions at the more volatile lower levels. Based on a large dataset from the US CPI-U index, our evaluations indicate that the HRNN model significantly outperforms a vast array of well-known inflation prediction baselines. Our methodology and results provide additional forecasting measures and possibilities to policy and market makers on sectoral and component-specific price changes.     

THE STOCK MARKET, HOUSING AND CONSUMER SPENDING: A SURVEY OF THE EVIDENCE ON WEALTH EFFECTS

Abstract.  This paper examines the time-series and micro-econometric evidence on the relationship between stock and house prices and consumer spending. The time-series studies distinguish between short-run and long-run links between consumption, income and wealth. They allow us to identify which variables adjust to restore the long-run equilibrium in the case of a shock, and to determine the time taken by the adjustment process. The micro-econometric literature improves our understanding of the link between wealth and expenditure and distinguishes among the alternative hypotheses – of direct wealth effect, common causality and collateral channel – that have been proposed to explain this relationship. The relationship between wealth and consumer spending appears to be strong, but there is some disagreement as to its size and nature. Furthermore, there appear to be some important differences across countries, which should be allowed for by policy makers when appraising the policy implications of a change in asset prices.     

Housing, taxation and retirement provision

This paper considers the tax treatment of housing and the issue of savings for retirement in the context of a simplified model that still allows key aspects of the household context to be realistically represented. A model is developed in which both housing and financial assets can be used as vehicles for household saving. Individuals face perfect capital markets and choose between owner-occupied and rented accommodations. For the model developed, it is shown that the tax advantage of owner-occupied housing is not fully removed even if imputed rents are subject to income taxation. However, deferred income taxation for both housing and savings in the form of financial assets would result in an equal treatment of tenants and owner-occupiers.     

国外住房合作社的经验与启示

住房舍作社作为解决低收入者住房问题的社会团体组织,在国外已有一百多年的历史.鉴于住房合作社在解决低收入者住房方面的重要作用,国外的住房合作社在发展的过程中普遍得到了政府的大力支持.在当前我国各大城市房价扶摇直上的背景下,我们应该借鉴国外发展住房合作社的经验,发展我国的住房合作社,使城市中的低收入者实现居者有其屋.     

上海A股市场股价波动相互影响能力实证研究

股票市场中股票价格的波动是相互影响的,但不同的股票其价格波动时对其他股票价格行为的影响能力是不同的。本文通过对我国上海A股市场的实证分析表明,有少数股票其价格波动时对其他股票价格行为有很强的影响能力,而大多数股票的这种影响能力很小。此外,单个股票价格波动时引起其他股票价格涨、跌的能力一般都有显著差异。     

Supply constraints and housing market dynamics

Although the volatility of house prices is often ascribed to demand-side factors, constraints on housing supply have important and little-studied implications for housing dynamics. I illustrate the strong relationship between the volatility of house prices and the regulation of new housing supply. I then employ a dynamic structural model of housing investment to investigate the mechanisms underlying this relationship. I find that supply constraints increase volatility through two channels: First, regulation lowers the elasticity of new housing supply by increasing lags in the permit process and adding to the cost of supplying new houses on the margin. Second, geographic limitations on the area available for building houses, such as steep slopes and water bodies, lead to less investment on average relative to the size of the existing housing stock, leaving less scope for the supply response to attenuate the effects of a demand shock. My estimates and simulations confirm that regulation and geographic constraints play critical and complementary roles in decreasing the responsiveness of investment to demand shocks, which in turn amplifies house price volatility.     

What drives racial segregation? New evidence using Census microdata

Using restricted Census microdata that link households to the Census block in which they live, this paper re-examines the question of whether racial differences in sociodemographic characteristics can explain observed levels of racial segregation. We develop a simple measurement framework designed to make use of the rich joint distribution of individual and neighborhood characteristics that these data provide, analyzing segregation patterns in the San Francisco Bay Area. The results indicate that racial differences in the collective set of characteristics we consider do have the potential to explain a considerable amount of the observed segregation, although more so for Asians and especially Hispanics than whites and blacks. Different sociodemographic factors emerge as potentially important for each race.